pax_global_header00006660000000000000000000000064147577054670014540gustar00rootroot0000000000000052 comment=5828eebe162e91f2fc6370a66199f239f1d84260 api-0.45.3/000077500000000000000000000000001475770546700124025ustar00rootroot00000000000000api-0.45.3/.coveragerc000066400000000000000000000001441475770546700145220ustar00rootroot00000000000000[run] omit = *test* */resources.py */models.py */models/* */_consumer/client.py api-0.45.3/.github/000077500000000000000000000000001475770546700137425ustar00rootroot00000000000000api-0.45.3/.github/workflows/000077500000000000000000000000001475770546700157775ustar00rootroot00000000000000api-0.45.3/.github/workflows/lint.yml000066400000000000000000000010171475770546700174670ustar00rootroot00000000000000name: Linting on: push: branches: [main] pull_request: branches: [main] permissions: contents: read jobs: lint: runs-on: ubuntu-latest steps: - uses: actions/checkout@v3 - name: Set up Python uses: actions/setup-python@v4 with: python-version: "3.11" cache: pip - name: Install dependencies run: | pip install pre-commit - name: Run pre-commit run: | pre-commit run --all-files --show-diff-on-failure api-0.45.3/.github/workflows/release.yml000066400000000000000000000024531475770546700201460ustar00rootroot00000000000000name: release on: release: types: [published] jobs: deploy: runs-on: ubuntu-latest strategy: max-parallel: 6 steps: - uses: actions/checkout@v3 - uses: actions/setup-python@v4 with: python-version: 3.9 - name: Install dependencies run: | python -m pip install --upgrade pip pip install setuptools setuptools_scm wheel build - name: Build packages run: python -m build working-directory: ./ - name: Publish package uses: pypa/gh-action-pypi-publish@master with: user: __token__ password: ${{ secrets.PYPY_API_TOKEN }} packages_dir: ./dist/ docs: runs-on: ubuntu-latest needs: - deploy steps: - uses: actions/checkout@v3 - uses: actions/setup-python@v4 with: python-version: 3.9 - name: Install dependencies run: | python -m pip install --upgrade pip pip install -r requirements.txt pip install -e . pip install -r requirements-docs.txt - name: Build run: sphinx-build ./docs ./docs/_build - name: Deploy uses: peaceiris/actions-gh-pages@v3.8.0 with: github_token: ${{ secrets.GITHUB_TOKEN }} publish_dir: ./docs/_build api-0.45.3/.github/workflows/testing.yml000066400000000000000000000050171475770546700202020ustar00rootroot00000000000000name: testing on: workflow_dispatch: push: branches: [main] pull_request: branches: [main] concurrency: group: ${{ github.workflow }}-${{ github.ref }} cancel-in-progress: true jobs: test: strategy: max-parallel: 2 matrix: os: ["ubuntu-latest"] python-version: ["3.10", "3.11"] runs-on: ${{ matrix.os }} steps: - uses: actions/checkout@v4 - name: Set up Python ${{ matrix.python-version }} uses: actions/setup-python@v5 with: python-version: ${{ matrix.python-version }} - name: Install Python dependencies run: | python -m pip install --upgrade pip pip install -r requirements/requirements-${{ matrix.os }}_py${{ matrix.python-version }}.txt pip install -r requirements/requirements-${{ matrix.os }}_py${{ matrix.python-version }}_extras.txt - name: Set SSL_CERT_FILE (Linux) if: matrix.os == 'ubuntu-latest' || matrix.os == 'macos-latest' run: echo "SSL_CERT_FILE=$(python -m certifi)" >> $GITHUB_ENV - name: Set SSL_CERT_FILE (Windows) if: matrix.os == 'windows-latest' run: echo "SSL_CERT_FILE=$(python -m certifi)" | Out-File -FilePath $Env:GITHUB_ENV -Encoding utf8 -Append - name: Format API key name (Linux/MacOS) if: matrix.os == 'ubuntu-latest' || matrix.os == 'macos-latest' run: | echo "API_KEY_NAME=$(echo ${{ format('MP_API_KEY_{0}_{1}', matrix.os, matrix.python-version) }} | awk '{gsub(/-|\./, "_"); print}' | tr '[:lower:]' '[:upper:]')" >> $GITHUB_ENV - name: Format API key name (Windows) if: matrix.os == 'windows-latest' run: | echo "API_KEY_NAME=$(echo ${{ format('MP_API_KEY_{0}_{1}', matrix.os, matrix.python-version) }} | awk '{gsub(/-|\./, "_"); print}' | tr '[:lower:]' '[:upper:]')" | Out-File -FilePath $Env:GITHUB_ENV -Encoding utf8 -Append - name: Test with pytest env: MP_API_KEY: ${{ secrets[env.API_KEY_NAME] }} #MP_API_ENDPOINT: https://api-preview.materialsproject.org/ run: | pip install -e . pytest -x --cov=mp_api --cov-report=xml - uses: codecov/codecov-action@v1 with: token: ${{ secrets.CODECOV_TOKEN }} file: ./coverage.xml auto-gen-release: needs: [test] runs-on: ubuntu-latest env: GITHUB_TOKEN: ${{ secrets.API_VER_BUMP_TOKEN }} steps: - uses: rymndhng/release-on-push-action@v0.20.0 with: bump_version_scheme: norelease api-0.45.3/.github/workflows/upgrade_dependencies.yml000066400000000000000000000073321475770546700226640ustar00rootroot00000000000000name: Upgrade Dependencies on: workflow_dispatch: jobs: upgrade: name: ${{ matrix.package }} (${{ matrix.os }}/py${{ matrix.python-version }}) runs-on: ${{ matrix.os }} strategy: matrix: os: ['ubuntu-latest'] package: ["mp-api"] python-version: ["3.10", "3.11"] steps: - uses: actions/checkout@v4 with: fetch-depth: 0 - uses: actions/setup-python@v5 with: python-version: ${{ matrix.python-version }} cache: 'pip' - name: Upgrade Python dependencies shell: bash run: | python -m pip install --upgrade pip pip-tools python -m piptools compile -q --upgrade --resolver=backtracking -o requirements/requirements-${{ matrix.os }}_py${{ matrix.python-version }}.txt pyproject.toml python -m piptools compile -q --upgrade --resolver=backtracking --all-extras -o requirements/requirements-${{ matrix.os }}_py${{ matrix.python-version }}_extras.txt pyproject.toml - name: Detect changes id: changes shell: bash run: | echo "count=$(git diff-index HEAD | wc -l | xargs)" >> $GITHUB_OUTPUT echo "files=$(git ls-files --exclude-standard --others | wc -l | xargs)" >> $GITHUB_OUTPUT - name: commit & push changes if: steps.changes.outputs.count > 0 || steps.changes.outputs.files > 0 shell: bash run: | git config user.name github-actions git config user.email github-actions@github.com git add requirements/requirements-${{ matrix.os }}_py${{ matrix.python-version }}.txt git add requirements/requirements-${{ matrix.os }}_py${{ matrix.python-version }}_extras.txt git commit --allow-empty -m "Update ${{ matrix.os }} dependencies for ${{ matrix.package }}" git push -f origin ${{ github.ref_name }}:auto-dependency-upgrades-${{ matrix.package }}-${{ matrix.os }}-py${{ matrix.python-version }} pull_request: name: Merge all branches and open PR runs-on: ubuntu-latest needs: upgrade strategy: matrix: python-version: ["3.10"] steps: - uses: actions/checkout@v4 with: fetch-depth: 0 - uses: actions/setup-python@v5 with: python-version: ${{ matrix.python-version }} - name: detect auto-upgrade-dependency branches id: changes run: echo "count=$(git branch -r | grep auto-dependency-upgrades- | wc -l | xargs)" >> $GITHUB_OUTPUT - name: merge all auto-dependency-upgrades branches if: steps.changes.outputs.count > 0 run: | git config user.name github-actions git config user.email github-actions@github.com git checkout -b auto-dependency-upgrades git branch -r | grep auto-dependency-upgrades- | xargs -I {} git merge {} git rebase ${GITHUB_REF##*/} git push -f origin auto-dependency-upgrades git branch -r | grep auto-dependency-upgrades- | cut -d/ -f2 | xargs -I {} git push origin :{} - name: Open pull request if needed if: steps.changes.outputs.count > 0 env: GITHUB_TOKEN: ${{ secrets.GH_TOKEN }} # Only open a PR if the branch is not attached to an existing one run: | PR=$(gh pr list --head auto-dependency-upgrades --json number -q '.[0].number') if [ -z $PR ]; then gh pr create \ --head auto-dependency-upgrades \ --title "Automated dependency upgrades" \ --body "Full log: https://github.com/${{ github.repository }}/actions/runs/${{ github.run_id }} (THIS IS AN AUTOMATED COMMENT)" else echo "Pull request already exists, won't create a new one." fi api-0.45.3/.gitignore000066400000000000000000000024561475770546700144010ustar00rootroot00000000000000# Byte-compiled / optimized / DLL files __pycache__/ *.py[cod] *$py.class # C extensions *.so # Distribution / packaging .Python env/ build/ develop-eggs/ dist/ downloads/ eggs/ .eggs/ lib/ lib64/ parts/ sdist/ var/ wheels/ *.egg-info/ .installed.cfg *.egg # PyInstaller # Usually these files are written by a python script from a template # before PyInstaller builds the exe, so as to inject date/other infos into it. *.manifest *.spec # Installer logs pip-log.txt pip-delete-this-directory.txt # Unit test / coverage reports htmlcov/ .tox/ .coverage .coverage.* .cache nosetests.xml coverage.xml *.cover .hypothesis/ # Translations *.mo *.pot # Django stuff: *.log local_settings.py # Flask stuff: instance/ .webassets-cache # Scrapy stuff: .scrapy # Sphinx documentation docs/_build/ source/apidoc/maggma.* source/apidoc/modules.rst # PyBuilder target/ # Jupyter Notebook .ipynb_checkpoints # pyenv .python-version # celery beat schedule file celerybeat-schedule # SageMath parsed files *.sage.py # dotenv .env # virtualenv .venv venv/ ENV/ # Spyder project settings .spyderproject .spyproject # Rope project settings .ropeproject # mkdocs documentation /site # mypy .mypy_cache/ # eclipse .project .pydevproject # fleet .fleet *~ .idea .DS_Store .vscode .pytest_cache # Doc folder _autosummary api-0.45.3/.pre-commit-config.yaml000066400000000000000000000020341475770546700166620ustar00rootroot00000000000000default_stages: [commit] default_install_hook_types: [pre-commit, commit-msg] ci: autoupdate_commit_msg: "chore: update pre-commit hooks" repos: - repo: https://github.com/astral-sh/ruff-pre-commit rev: v0.0.292 hooks: - id: ruff args: [--fix, --show-fixes] - repo: https://github.com/psf/black rev: 23.9.1 hooks: - id: black - repo: https://github.com/asottile/blacken-docs rev: "1.16.0" hooks: - id: blacken-docs additional_dependencies: [black>=23.7.0] - repo: https://github.com/pre-commit/pre-commit-hooks rev: v4.5.0 hooks: - id: check-case-conflict - id: check-symlinks - id: check-yaml - id: destroyed-symlinks - id: end-of-file-fixer - id: mixed-line-ending - id: trailing-whitespace - repo: https://github.com/codespell-project/codespell rev: v2.2.6 hooks: - id: codespell stages: [commit, commit-msg] exclude_types: [json, bib, svg] args: [--ignore-words-list, "mater,fwe,te"] api-0.45.3/CODE_OF_CONDUCT.md000066400000000000000000000045561475770546700152130ustar00rootroot00000000000000# Contributor Code of Conduct As contributors and maintainers of this project, and in the interest of fostering an open and welcoming community, we pledge to respect all people who contribute through reporting issues, posting feature requests, updating documentation, submitting pull requests or patches, and other activities. We are committed to making participation in this project a harassment-free experience for everyone, regardless of level of experience, gender, gender identity and expression, sexual orientation, disability, personal appearance, body size, race, ethnicity, age, religion, or nationality. Examples of unacceptable behavior by participants include: * The use of sexualized language or imagery * Personal attacks * Trolling or insulting/derogatory comments * Public or private harassment * Publishing other's private information, such as physical or electronic addresses, without explicit permission * Other unethical or unprofessional conduct Project maintainers have the right and responsibility to remove, edit, or reject comments, commits, code, wiki edits, issues, and other contributions that are not aligned to this Code of Conduct, or to ban temporarily or permanently any contributor for other behaviors that they deem inappropriate, threatening, offensive, or harmful. By adopting this Code of Conduct, project maintainers commit themselves to fairly and consistently applying these principles to every aspect of managing this project. Project maintainers who do not follow or enforce the Code of Conduct may be permanently removed from the project team. This Code of Conduct applies both within project spaces and in public spaces when an individual is representing the project or its community. Instances of abusive, harassing, or otherwise unacceptable behavior may be reported by contacting a project maintainer at conduct@materialsproject.org. All complaints will be reviewed and investigated and will result in a response that is deemed necessary and appropriate to the circumstances. Maintainers are obligated to maintain confidentiality with regard to the reporter of an incident to the extent possible by law and institutional policy. This Code of Conduct is adapted from the [Contributor Covenant][homepage], version 1.3.0, available at https://www.contributor-covenant.org/version/1/3/0/code-of-conduct.html [homepage]: https://www.contributor-covenant.org api-0.45.3/LICENSE000066400000000000000000000045611475770546700134150ustar00rootroot00000000000000maggma Copyright (c) 2017, The Regents of the University of California, through Lawrence Berkeley National Laboratory (subject to receipt of any required approvals from the U.S. Dept. of Energy). All rights reserved. Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: (1) Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. (2) Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. (3) Neither the name of the University of California, Lawrence Berkeley National Laboratory, U.S. Dept. of Energy nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission. THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. You are under no obligation whatsoever to provide any bug fixes, patches, or upgrades to the features, functionality or performance of the source code ("Enhancements") to anyone; however, if you choose to make your Enhancements available either publicly, or directly to Lawrence Berkeley National Laboratory or its contributors, without imposing a separate written license agreement for such Enhancements, then you hereby grant the following license: a non-exclusive, royalty-free perpetual license to install, use, modify, prepare derivative works, incorporate into other computer software, distribute, and sublicense such enhancements or derivative works thereof, in binary and source code form. api-0.45.3/README.md000066400000000000000000000013151475770546700136610ustar00rootroot00000000000000# The Materials Project API [![testing](https://github.com/materialsproject/api/workflows/testing/badge.svg)](https://github.com/materialsproject/api/actions?query=workflow%3Atesting) [![codecov](https://codecov.io/gh/materialsproject/api/branch/main/graph/badge.svg)](https://codecov.io/gh/materialsproject/api) ![python](https://img.shields.io/badge/Python-3.9+-blue.svg?logo=python&logoColor=white) This repository is the development environment for the new Materials Project API. A core client implementation will reside here. For information on how to use the API, please see the updated [documentation](https://docs.materialsproject.org/downloading-data/how-do-i-download-the-materials-project-database). api-0.45.3/docs/000077500000000000000000000000001475770546700133325ustar00rootroot00000000000000api-0.45.3/docs/Makefile000066400000000000000000000011721475770546700147730ustar00rootroot00000000000000# Minimal makefile for Sphinx documentation # # You can set these variables from the command line, and also # from the environment for the first two. SPHINXOPTS ?= SPHINXBUILD ?= sphinx-build SOURCEDIR = . BUILDDIR = _build # Put it first so that "make" without argument is like "make help". help: @$(SPHINXBUILD) -M help "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O) .PHONY: help Makefile # Catch-all target: route all unknown targets to Sphinx using the new # "make mode" option. $(O) is meant as a shortcut for $(SPHINXOPTS). %: Makefile @$(SPHINXBUILD) -M $@ "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O) api-0.45.3/docs/_templates/000077500000000000000000000000001475770546700154675ustar00rootroot00000000000000api-0.45.3/docs/_templates/custom-class-template.rst000066400000000000000000000011431475770546700224460ustar00rootroot00000000000000{{ fullname | escape | underline}} .. currentmodule:: {{ module }} .. autoclass:: {{ objname }} :members: :show-inheritance: :inherited-members: {% block methods %} .. automethod:: __init__ {% if methods %} .. rubric:: {{ _('Methods') }} .. autosummary:: {% for item in methods %} ~{{ name }}.{{ item }} {%- endfor %} {% endif %} {% endblock %} {% block attributes %} {% if attributes %} .. rubric:: {{ _('Attributes') }} .. autosummary:: {% for item in attributes %} ~{{ name }}.{{ item }} {%- endfor %} {% endif %} {% endblock %} api-0.45.3/docs/_templates/custom-module-template.rst000066400000000000000000000022701475770546700226300ustar00rootroot00000000000000{{ fullname | escape | underline}} .. automodule:: {{ fullname }} {% block attributes %} {% if attributes %} .. rubric:: Module Attributes .. autosummary:: :toctree: {% for item in attributes %} {{ item }} {%- endfor %} {% endif %} {% endblock %} {% block functions %} {% if functions %} .. rubric:: {{ _('Functions') }} .. autosummary:: :toctree: {% for item in functions %} {{ item }} {%- endfor %} {% endif %} {% endblock %} {% block classes %} {% if classes %} .. rubric:: {{ _('Classes') }} .. autosummary:: :toctree: :template: custom-class-template.rst {% for item in classes %} {{ item }} {%- endfor %} {% endif %} {% endblock %} {% block exceptions %} {% if exceptions %} .. rubric:: {{ _('Exceptions') }} .. autosummary:: :toctree: {% for item in exceptions %} {{ item }} {%- endfor %} {% endif %} {% endblock %} {% block modules %} {% if modules %} .. rubric:: Modules .. autosummary:: :toctree: :template: custom-module-template.rst :recursive: {% for item in modules %} {{ item }} {%- endfor %} {% endif %} {% endblock %} api-0.45.3/docs/conf.py000066400000000000000000000072501475770546700146350ustar00rootroot00000000000000# Configuration file for the Sphinx documentation builder. # # For the full list of built-in configuration values, see the documentation: # https://www.sphinx-doc.org/en/master/usage/configuration.html # -- Project information ----------------------------------------------------- # https://www.sphinx-doc.org/en/master/usage/configuration.html#project-information project = "mp-api" copyright = "2022, The Materials Project" author = "The Materials Project" release = "2022" # -- General configuration --------------------------------------------------- # https://www.sphinx-doc.org/en/master/usage/configuration.html#general-configuration extensions = [ "sphinx.ext.autodoc", "sphinx.ext.viewcode", "sphinx.ext.intersphinx", "sphinx.ext.napoleon", "sphinx.ext.autosummary", ] ## Include Python objects as they appear in source files ## Default: alphabetically ('alphabetical') autodoc_member_order = "bysource" ## Default flags used by autodoc directives autodoc_default_flags = ["members", "show-inheritance"] autoclass_content = "init" ## Generate autodoc stubs with summaries from code autosummary_generate = True templates_path = ["_templates"] exclude_patterns = ["_build", "Thumbs.db", ".DS_Store"] # The suffix(es) of source filenames. # You can specify multiple suffix as a list of string: # # source_suffix = ['.rst', '.md'] source_suffix = ".rst" # The master toctree document. master_doc = "index" # The name of the Pygments (syntax highlighting) style to use. pygments_style = "sphinx" # -- Options for HTML output ------------------------------------------------- # https://www.sphinx-doc.org/en/master/usage/configuration.html#options-for-html-output html_theme = "alabaster" # html_static_path = ['_static'] # Theme options are theme-specific and customize the look and feel of a theme # further. For a list of options available for each theme, see the # documentation. # html_theme_options = { "github_button": True, "github_type": "star&v=2", "github_user": "materialsproject", "github_repo": "api", "github_banner": True, } # Custom sidebar templates, must be a dictionary that maps document names # to template names. # # The default sidebars (for documents that don't match any pattern) are # defined by theme itself. Builtin themes are using these templates by # default: ``['localtoc.html', 'relations.html', 'sourcelink.html', # 'searchbox.html']``. # html_sidebars = { "**": [ "about.html", "navigation.html", "searchbox.html", ] } # -- Options for HTMLHelp output --------------------------------------------- # Output file base name for HTML help builder. htmlhelp_basename = "mapidoc" # -- Options for manual page output ------------------------------------------ # One entry per manual page. List of tuples # (source start file, name, description, authors, manual section). man_pages = [(master_doc, "mp-api", "mp-api Documentation", [author], 1)] # -- Options for Texinfo output ---------------------------------------------- # Grouping the document tree into Texinfo files. List of tuples # (source start file, target name, title, author, # dir menu entry, description, category) texinfo_documents = [ ( master_doc, "mp-api", "mp-api Documentation", author, "mp-api", "The Materials Project API.", "", ), ] # -- Extension configuration ------------------------------------------------- autodoc_mock_imports = [] # Example configuration for intersphinx: refer to the Python standard library. ## Add Python version number to the default address to corretcly reference ## the Python standard library intersphinx_mapping = {"https://docs.python.org/3.8": None} api-0.45.3/docs/index.rst000066400000000000000000000021021475770546700151660ustar00rootroot00000000000000.. mp-api documentation master file, created by sphinx-quickstart on Mon Oct 3 13:56:19 2022. You can adapt this file completely to your liking, but it should at least contain the root `toctree` directive. Welcome to the **mp-api** code documentation! ================================== **mp-api** contains the core client implementation for the updated Materials Project API. This is intended to be barebones documentation for the client classes and their methods. For more comprehensive documentation on how to use the code to access Materials Project data, `see the main updated documentation `_. Support ------- If you are having issues, please let us know through `github `_, or `on the MatSci community discourse `_. Contents -------- .. toctree:: :maxdepth: 2 modules Indices and tables ================== * :ref:`genindex` * :ref:`modindex` * :ref:`search` api-0.45.3/docs/make.bat000066400000000000000000000014401475770546700147360ustar00rootroot00000000000000@ECHO OFF pushd %~dp0 REM Command file for Sphinx documentation if "%SPHINXBUILD%" == "" ( set SPHINXBUILD=sphinx-build ) set SOURCEDIR=. set BUILDDIR=_build %SPHINXBUILD% >NUL 2>NUL if errorlevel 9009 ( echo. echo.The 'sphinx-build' command was not found. Make sure you have Sphinx echo.installed, then set the SPHINXBUILD environment variable to point echo.to the full path of the 'sphinx-build' executable. Alternatively you echo.may add the Sphinx directory to PATH. echo. echo.If you don't have Sphinx installed, grab it from echo.https://www.sphinx-doc.org/ exit /b 1 ) if "%1" == "" goto help %SPHINXBUILD% -M %1 %SOURCEDIR% %BUILDDIR% %SPHINXOPTS% %O% goto end :help %SPHINXBUILD% -M help %SOURCEDIR% %BUILDDIR% %SPHINXOPTS% %O% :end popd api-0.45.3/docs/modules.rst000066400000000000000000000003631475770546700155360ustar00rootroot00000000000000:orphan: Project Modules =============== This page contains the list of project's modules .. autosummary:: :toctree: _autosummary :template: custom-module-template.rst :recursive: mp_api.client.mprester mp_api.client.routes api-0.45.3/mp_api/000077500000000000000000000000001475770546700136475ustar00rootroot00000000000000api-0.45.3/mp_api/client/000077500000000000000000000000001475770546700151255ustar00rootroot00000000000000api-0.45.3/mp_api/client/__init__.py000066400000000000000000000005351475770546700172410ustar00rootroot00000000000000"""Primary MAPI module.""" from __future__ import annotations import os from importlib.metadata import PackageNotFoundError, version from .core import MPRestError from .mprester import MPRester try: __version__ = version("mp_api") except PackageNotFoundError: # pragma: no cover __version__ = os.getenv("SETUPTOOLS_SCM_PRETEND_VERSION") api-0.45.3/mp_api/client/core/000077500000000000000000000000001475770546700160555ustar00rootroot00000000000000api-0.45.3/mp_api/client/core/__init__.py000066400000000000000000000001711475770546700201650ustar00rootroot00000000000000from __future__ import annotations from .client import BaseRester, MPRestError from .settings import MAPIClientSettings api-0.45.3/mp_api/client/core/client.py000066400000000000000000001421211475770546700177060ustar00rootroot00000000000000"""This module provides classes to interface with the Materials Project REST API v3 to enable the creation of data structures and pymatgen objects using Materials Project data. """ from __future__ import annotations import inspect import itertools import json import os import platform import sys import warnings from concurrent.futures import FIRST_COMPLETED, ThreadPoolExecutor, wait from copy import copy from functools import cache from importlib.metadata import PackageNotFoundError, version from json import JSONDecodeError from math import ceil from typing import TYPE_CHECKING, Generic, TypeVar from urllib.parse import quote, urljoin import requests from bson import json_util from emmet.core.utils import jsanitize from monty.json import MontyDecoder from pydantic import BaseModel, create_model from requests.adapters import HTTPAdapter from requests.exceptions import RequestException from smart_open import open from tqdm.auto import tqdm from urllib3.util.retry import Retry from mp_api.client.core.settings import MAPIClientSettings from mp_api.client.core.utils import api_sanitize, validate_ids try: import boto3 from botocore import UNSIGNED from botocore.config import Config except ImportError: boto3 = None try: import flask except ImportError: flask = None if TYPE_CHECKING: from typing import Any, Callable try: __version__ = version("mp_api") except PackageNotFoundError: # pragma: no cover __version__ = os.getenv("SETUPTOOLS_SCM_PRETEND_VERSION") SETTINGS = MAPIClientSettings() # type: ignore T = TypeVar("T") class BaseRester(Generic[T]): """Base client class with core stubs.""" suffix: str = "" document_model: BaseModel = None # type: ignore supports_versions: bool = False primary_key: str = "material_id" def __init__( self, api_key: str | None = None, endpoint: str | None = None, include_user_agent: bool = True, session: requests.Session | None = None, s3_client: Any | None = None, debug: bool = False, monty_decode: bool = True, use_document_model: bool = True, timeout: int = 20, headers: dict | None = None, mute_progress_bars: bool = SETTINGS.MUTE_PROGRESS_BARS, ): """Initialize the REST API helper class. Arguments: api_key: A String API key for accessing the MaterialsProject REST interface. Please obtain your API key at https://www.materialsproject.org/dashboard. If this is None, the code will check if there is a "PMG_MAPI_KEY" setting. If so, it will use that environment variable. This makes easier for heavy users to simply add this environment variable to their setups and MPRester can then be called without any arguments. endpoint: Url of endpoint to access the MaterialsProject REST interface. Defaults to the standard Materials Project REST address at "https://api.materialsproject.org", but can be changed to other urls implementing a similar interface. include_user_agent: If True, will include a user agent with the HTTP request including information on pymatgen and system version making the API request. This helps MP support pymatgen users, and is similar to what most web browsers send with each page request. Set to False to disable the user agent. session: requests Session object with which to connect to the API, for advanced usage only. s3_client: boto3 S3 client object with which to connect to the object stores.ct to the object stores.ct to the object stores. debug: if True, print the URL for every request monty_decode: Decode the data using monty into python objects use_document_model: If False, skip the creating the document model and return data as a dictionary. This can be simpler to work with but bypasses data validation and will not give auto-complete for available fields. timeout: Time in seconds to wait until a request timeout error is thrown headers: Custom headers for localhost connections. mute_progress_bars: Whether to disable progress bars. """ # TODO: think about how to migrate from PMG_MAPI_KEY self.api_key = api_key or os.getenv("MP_API_KEY") self.base_endpoint = self.endpoint = endpoint or os.getenv( "MP_API_ENDPOINT", "https://api.materialsproject.org/" ) self.debug = debug self.include_user_agent = include_user_agent self.monty_decode = monty_decode self.use_document_model = use_document_model self.timeout = timeout self.headers = headers or {} self.mute_progress_bars = mute_progress_bars self.db_version = BaseRester._get_database_version(self.endpoint) if self.suffix: self.endpoint = urljoin(self.endpoint, self.suffix) if not self.endpoint.endswith("/"): self.endpoint += "/" if session: self._session = session else: self._session = None # type: ignore if s3_client: self._s3_client = s3_client else: self._s3_client = None self.document_model = ( api_sanitize(self.document_model) # type: ignore if self.document_model is not None else None # type: ignore ) @property def session(self) -> requests.Session: if not self._session: self._session = self._create_session( self.api_key, self.include_user_agent, self.headers ) return self._session @property def s3_client(self): if boto3 is None: raise MPRestError( "boto3 not installed. To query charge density, " "band structure, or density of states data first " "install with: 'pip install boto3'" ) if not self._s3_client: self._s3_client = boto3.client( "s3", config=Config(signature_version=UNSIGNED), # type: ignore ) return self._s3_client @staticmethod def _create_session(api_key, include_user_agent, headers): session = requests.Session() session.headers = {"x-api-key": api_key} session.headers.update(headers) if include_user_agent: mp_api_info = "mp-api/" + __version__ if __version__ else None python_info = f"Python/{sys.version.split()[0]}" platform_info = f"{platform.system()}/{platform.release()}" user_agent = f"{mp_api_info} ({python_info} {platform_info})" session.headers["user-agent"] = user_agent settings = MAPIClientSettings() # type: ignore max_retry_num = settings.MAX_RETRIES retry = Retry( total=max_retry_num, read=max_retry_num, connect=max_retry_num, respect_retry_after_header=True, status_forcelist=[429, 504, 502], # rate limiting backoff_factor=settings.BACKOFF_FACTOR, ) adapter = HTTPAdapter(max_retries=retry) session.mount("http://", adapter) session.mount("https://", adapter) return session def __enter__(self): # pragma: no cover """Support for "with" context.""" return self def __exit__(self, exc_type, exc_val, exc_tb): # pragma: no cover """Support for "with" context.""" if self.session is not None: self.session.close() self._session = None @staticmethod @cache def _get_database_version(endpoint): """The Materials Project database is periodically updated and has a database version associated with it. When the database is updated, consolidated data (information about "a material") may and does change, while calculation data about a specific calculation task remains unchanged and available for querying via its task_id. The database version is set as a date in the format YYYY_MM_DD, where "_DD" may be optional. An additional numerical or `postN` suffix might be added if multiple releases happen on the same day. Returns: database version as a string """ return requests.get(url=endpoint + "heartbeat").json()["db_version"] def _post_resource( self, body: dict | None = None, params: dict | None = None, suburl: str | None = None, use_document_model: bool | None = None, ) -> dict: """Post data to the endpoint for a Resource. Arguments: body: body json to send in post request params: extra params to send in post request suburl: make a request to a specified sub-url use_document_model: if None, will defer to the self.use_document_model attribute Returns: A Resource, a dict with two keys, "data" containing a list of documents, and "meta" containing meta information, e.g. total number of documents available. """ if use_document_model is None: use_document_model = self.use_document_model payload = jsanitize(body) try: url = self.endpoint if suburl: url = urljoin(self.endpoint, suburl) if not url.endswith("/"): url += "/" response = self.session.post(url, json=payload, verify=True, params=params) if response.status_code == 200: if self.monty_decode: data = json.loads(response.text, cls=MontyDecoder) else: data = json.loads(response.text) if self.document_model and use_document_model: if isinstance(data["data"], dict): data["data"] = self.document_model.model_validate(data["data"]) # type: ignore elif isinstance(data["data"], list): data["data"] = [ self.document_model.model_validate(d) for d in data["data"] ] # type: ignore return data else: try: data = json.loads(response.text)["detail"] except (JSONDecodeError, KeyError): data = f"Response {response.text}" if isinstance(data, str): message = data else: try: message = ", ".join( f"{entry['loc'][1]} - {entry['msg']}" for entry in data ) except (KeyError, IndexError): message = str(data) raise MPRestError( f"REST post query returned with error status code {response.status_code} " f"on URL {response.url} with message:\n{message}" ) except RequestException as ex: raise MPRestError(str(ex)) def _patch_resource( self, body: dict | None = None, params: dict | None = None, suburl: str | None = None, use_document_model: bool | None = None, ) -> dict: """Patch data to the endpoint for a Resource. Arguments: body: body json to send in patch request params: extra params to send in patch request suburl: make a request to a specified sub-url use_document_model: if None, will defer to the self.use_document_model attribute Returns: A Resource, a dict with two keys, "data" containing a list of documents, and "meta" containing meta information, e.g. total number of documents available. """ if use_document_model is None: use_document_model = self.use_document_model payload = jsanitize(body) try: url = self.endpoint if suburl: url = urljoin(self.endpoint, suburl) if not url.endswith("/"): url += "/" response = self.session.patch(url, json=payload, verify=True, params=params) if response.status_code == 200: if self.monty_decode: data = json.loads(response.text, cls=MontyDecoder) else: data = json.loads(response.text) if self.document_model and use_document_model: if isinstance(data["data"], dict): data["data"] = self.document_model.model_validate(data["data"]) # type: ignore elif isinstance(data["data"], list): data["data"] = [ self.document_model.model_validate(d) for d in data["data"] ] # type: ignore return data else: try: data = json.loads(response.text)["detail"] except (JSONDecodeError, KeyError): data = f"Response {response.text}" if isinstance(data, str): message = data else: try: message = ", ".join( f"{entry['loc'][1]} - {entry['msg']}" for entry in data ) except (KeyError, IndexError): message = str(data) raise MPRestError( f"REST post query returned with error status code {response.status_code} " f"on URL {response.url} with message:\n{message}" ) except RequestException as ex: raise MPRestError(str(ex)) def _query_open_data( self, bucket: str, key: str, decoder: Callable, ) -> tuple[list[dict] | list[bytes], int]: """Query and deserialize Materials Project AWS open data s3 buckets. Args: bucket (str): Materials project bucket name key (str): Key for file including all prefixes decoder(Callable): Callable used to deserialize data Returns: dict: MontyDecoded data """ file = open( f"s3://{bucket}/{key}", encoding="utf-8", transport_params={"client": self.s3_client}, ) if "jsonl" in key: decoded_data = [decoder(jline) for jline in file.read().splitlines()] else: decoded_data = decoder(file.read()) if not isinstance(decoded_data, list): decoded_data = [decoded_data] return decoded_data, len(decoded_data) # type: ignore def _query_resource( self, criteria: dict | None = None, fields: list[str] | None = None, suburl: str | None = None, use_document_model: bool | None = None, parallel_param: str | None = None, num_chunks: int | None = None, chunk_size: int | None = None, timeout: int | None = None, ) -> dict: """Query the endpoint for a Resource containing a list of documents and meta information about pagination and total document count. For the end-user, methods .search() and .count() are intended to be easier to use. Arguments: criteria: dictionary of criteria to filter down fields: list of fields to return suburl: make a request to a specified sub-url use_document_model: if None, will defer to the self.use_document_model attribute parallel_param: parameter used to make parallel requests num_chunks: Maximum number of chunks of data to yield. None will yield all possible. chunk_size: Number of data entries per chunk. timeout : Time in seconds to wait until a request timeout error is thrown Returns: A Resource, a dict with two keys, "data" containing a list of documents, and "meta" containing meta information, e.g. total number of documents available. """ if use_document_model is None: use_document_model = self.use_document_model if timeout is None: timeout = self.timeout if criteria: criteria = {k: v for k, v in criteria.items() if v is not None} else: criteria = {} # Query s3 if no query is passed and all documents are asked for # TODO also skip fields set to same as their default no_query = not {field for field in criteria if field[0] != "_"} query_s3 = no_query and num_chunks is None if fields: if isinstance(fields, str): fields = [fields] if not suburl: invalid_fields = [ f for f in fields if f.split(".", 1)[0] not in self.available_fields ] if invalid_fields: raise MPRestError( f"invalid fields requested: {invalid_fields}. Available fields: {self.available_fields}" ) criteria["_fields"] = ",".join(fields) try: url = self.endpoint if suburl: url = urljoin(self.endpoint, suburl) if not url.endswith("/"): url += "/" if query_s3: db_version = self.db_version.replace(".", "-") if "/" not in self.suffix: suffix = self.suffix elif self.suffix == "molecules/summary": suffix = "molecules" else: infix, suffix = self.suffix.split("/", 1) suffix = infix if suffix == "core" else suffix suffix = suffix.replace("_", "-") # Paginate over all entries in the bucket. # TODO: change when a subset of entries needed from DB if "tasks" in suffix: bucket_suffix, prefix = "parsed", "tasks_atomate2" else: bucket_suffix = "build" prefix = f"collections/{db_version}/{suffix}" bucket = f"materialsproject-{bucket_suffix}" paginator = self.s3_client.get_paginator("list_objects_v2") pages = paginator.paginate(Bucket=bucket, Prefix=prefix) keys = [] for page in pages: for obj in page.get("Contents", []): key = obj.get("Key") if key and "manifest" not in key: keys.append(key) if len(keys) < 1: return self._submit_requests( url=url, criteria=criteria, use_document_model=use_document_model, parallel_param=parallel_param, num_chunks=num_chunks, chunk_size=chunk_size, timeout=timeout, ) if fields: warnings.warn( "Ignoring `fields` argument: All fields are always included when no query is provided." ) decoder = ( MontyDecoder().decode if self.monty_decode else json_util.loads ) # Multithreaded function inputs s3_params_list = { key: { "bucket": bucket, "key": key, "decoder": decoder, } for key in keys } # Setup progress bar pbar_message = ( # type: ignore f"Retrieving {self.document_model.__name__} documents" # type: ignore if self.document_model is not None else "Retrieving documents" ) num_docs_needed = int(self.count()) pbar = ( tqdm( desc=pbar_message, total=num_docs_needed, ) if not self.mute_progress_bars else None ) byte_data = self._multi_thread( self._query_open_data, list(s3_params_list.values()), pbar, # type: ignore ) unzipped_data = [] for docs, _, _ in byte_data: unzipped_data.extend(docs) data = {"data": unzipped_data, "meta": {}} if self.use_document_model: data["data"] = self._convert_to_model(data["data"]) data["meta"]["total_doc"] = len(data["data"]) else: data = self._submit_requests( url=url, criteria=criteria, use_document_model=not query_s3 and use_document_model, parallel_param=parallel_param, num_chunks=num_chunks, chunk_size=chunk_size, timeout=timeout, ) return data except RequestException as ex: raise MPRestError(str(ex)) def _submit_requests( # noqa self, url, criteria, use_document_model, chunk_size, parallel_param=None, num_chunks=None, timeout=None, ) -> dict: """Handle submitting requests. Parallel requests supported if possible. Parallelization will occur either over the largest list of supported query parameters used and/or over pagination. The number of threads is chosen by NUM_PARALLEL_REQUESTS in settings. Arguments: criteria: dictionary of criteria to filter down url: url used to make request use_document_model: if None, will defer to the self.use_document_model attribute parallel_param: parameter to parallelize requests with num_chu: fieldsnky: Maximum number of chunks of data to yield. None will yield all possible. chunk_size: Number of data entries per chunk. timeout: Time in seconds to wait until a request timeout error is thrown Returns: Dictionary containing data and metadata """ # Generate new sets of criteria dicts to be run in parallel # with new appropriate limit values. New limits obtained from # trying to evenly divide num_chunks by the total number of new # criteria dicts. if parallel_param is not None: # Determine slice size accounting for character maximum in HTTP URL # First get URl length without parallel param url_string = "" for key, value in criteria.items(): if key != parallel_param: parsed_val = quote(str(value)) url_string += f"{key}={parsed_val}&" bare_url_len = len(url_string) max_param_str_length = ( MAPIClientSettings().MAX_HTTP_URL_LENGTH - bare_url_len # type: ignore ) # Next, check if default number of parallel requests works. # If not, make slice size the minimum number of param entries # contained in any substring of length max_param_str_length. param_length = len(criteria[parallel_param].split(",")) slice_size = ( int(param_length / MAPIClientSettings().NUM_PARALLEL_REQUESTS) or 1 # type: ignore ) url_param_string = quote(criteria[parallel_param]) parallel_param_str_chunks = [ url_param_string[i : i + max_param_str_length] for i in range(0, len(url_param_string), max_param_str_length) if (i + max_param_str_length) <= len(url_param_string) ] if len(parallel_param_str_chunks) > 0: params_min_chunk = min( parallel_param_str_chunks, key=lambda x: len(x.split("%2C")) ) num_params_min_chunk = len(params_min_chunk.split("%2C")) if num_params_min_chunk < slice_size: slice_size = num_params_min_chunk or 1 new_param_values = [ entry for entry in ( criteria[parallel_param].split(",")[i : (i + slice_size)] for i in range(0, param_length, slice_size) ) if entry != [] ] # Get new limit values that sum to chunk_size num_new_params = len(new_param_values) q = int(chunk_size / num_new_params) # quotient r = chunk_size % num_new_params # remainder new_limits = [] for _ in range(num_new_params): val = q + 1 if r > 0 else q if q > 0 else 1 new_limits.append(val) r -= 1 # Split list and generate multiple criteria new_criteria = [ { **{ key: criteria[key] for key in criteria if key not in [parallel_param, "_limit"] }, parallel_param: ",".join(list_chunk), "_limit": new_limits[list_num], } for list_num, list_chunk in enumerate(new_param_values) ] else: # Only parallelize over pagination parameters new_criteria = [criteria] new_limits = [chunk_size] total_num_docs = 0 total_data = {"data": []} # type: dict # Obtain first page of results and get pagination information. # Individual total document limits (subtotal) will potentially # be used for rebalancing should one new of the criteria # queries result in a smaller amount of docs compared to the # new limit value we assigned. subtotals = [] remaining_docs_avail = {} initial_params_list = [ { "url": url, "verify": True, "params": copy(crit), "use_document_model": use_document_model, "timeout": timeout, } for crit in new_criteria ] initial_data_tuples = self._multi_thread( self._submit_request_and_process, initial_params_list ) for data, subtotal, crit_ind in initial_data_tuples: subtotals.append(subtotal) sub_diff = subtotal - new_limits[crit_ind] remaining_docs_avail[crit_ind] = sub_diff total_data["data"].extend(data["data"]) last_data_entry = initial_data_tuples[-1][0] # Rebalance if some parallel queries produced too few results if len(remaining_docs_avail) > 1 and len(total_data["data"]) < chunk_size: remaining_docs_avail = dict( sorted(remaining_docs_avail.items(), key=lambda item: item[1]) ) # Redistribute missing docs from initial chunk among queries # which have head room with respect to remaining document number. fill_docs = 0 rebalance_params = [] for crit_ind, amount_avail in remaining_docs_avail.items(): if amount_avail <= 0: fill_docs += abs(amount_avail) new_limits[crit_ind] = 0 else: crit = new_criteria[crit_ind] crit["_skip"] = crit["_limit"] if fill_docs == 0: continue if fill_docs >= amount_avail: crit["_limit"] = amount_avail new_limits[crit_ind] += amount_avail fill_docs -= amount_avail else: crit["_limit"] = fill_docs new_limits[crit_ind] += fill_docs fill_docs = 0 rebalance_params.append( { "url": url, "verify": True, "params": copy(crit), "use_document_model": use_document_model, "timeout": timeout, } ) new_criteria[crit_ind]["_skip"] += crit["_limit"] new_criteria[crit_ind]["_limit"] = chunk_size # Obtain missing initial data after rebalancing if len(rebalance_params) > 0: rebalance_data_tuples = self._multi_thread( self._submit_request_and_process, rebalance_params ) for data, _, _ in rebalance_data_tuples: total_data["data"].extend(data["data"]) last_data_entry = rebalance_data_tuples[-1][0] total_num_docs = sum(subtotals) if "meta" in last_data_entry: last_data_entry["meta"]["total_doc"] = total_num_docs total_data["meta"] = last_data_entry["meta"] # Get max number of response pages max_pages = ( num_chunks if num_chunks is not None else ceil(total_num_docs / chunk_size) ) # Get total number of docs needed num_docs_needed = min((max_pages * chunk_size), total_num_docs) # Setup progress bar pbar_message = ( # type: ignore f"Retrieving {self.document_model.__name__} documents" # type: ignore if self.document_model is not None else "Retrieving documents" ) pbar = ( tqdm( desc=pbar_message, total=num_docs_needed, ) if not self.mute_progress_bars else None ) initial_data_length = len(total_data["data"]) # If we have all the results in a single page, return directly if initial_data_length >= num_docs_needed or num_chunks == 1: new_total_data = copy(total_data) new_total_data["data"] = total_data["data"][:num_docs_needed] if pbar is not None: pbar.update(num_docs_needed) pbar.close() return new_total_data # otherwise, prepare to paginate in parallel if chunk_size is None: raise ValueError("A chunk size must be provided to enable pagination") if pbar is not None: pbar.update(initial_data_length) # Warning to select specific fields only for many results if criteria.get("_all_fields", False) and (total_num_docs / chunk_size > 10): warnings.warn( f"Use the 'fields' argument to select only fields of interest to speed " f"up data retrieval for large queries. " f"Choose from: {self.available_fields}" ) # Get all pagination input params for parallel requests params_list = [] doc_counter = 0 for crit_num, crit in enumerate(new_criteria): remaining = remaining_docs_avail[crit_num] if "_skip" not in crit: crit["_skip"] = chunk_size if "_limit" not in crit else crit["_limit"] while remaining > 0: if doc_counter == (num_docs_needed - initial_data_length): break if remaining < chunk_size: crit["_limit"] = remaining doc_counter += remaining else: n = chunk_size - (doc_counter % chunk_size) crit["_limit"] = n doc_counter += n params_list.append( { "url": url, "verify": True, "params": {**crit, "_skip": crit["_skip"]}, "use_document_model": use_document_model, "timeout": timeout, } ) crit["_skip"] += crit["_limit"] remaining -= crit["_limit"] # Submit requests and process data data_tuples = self._multi_thread( self._submit_request_and_process, params_list, pbar ) for data, _, _ in data_tuples: total_data["data"].extend(data["data"]) if data_tuples and "meta" in data_tuples[0][0]: total_data["meta"]["time_stamp"] = data_tuples[0][0]["meta"]["time_stamp"] if pbar is not None: pbar.close() return total_data def _multi_thread( self, func: Callable, params_list: list[dict], progress_bar: tqdm | None = None, ): """Handles setting up a threadpool and sending parallel requests. Arguments: func (Callable): Callable function to multi params_list (list): list of dictionaries containing url and params for each request progress_bar (tqdm): progress bar to update with progress Returns: Tuples with data, total number of docs in matching the query in the database, and the index of the criteria dictionary in the provided parameter list """ return_data = [] params_gen = iter( params_list ) # Iter necessary for islice to keep track of what has been accessed params_ind = 0 with ThreadPoolExecutor( max_workers=MAPIClientSettings().NUM_PARALLEL_REQUESTS # type: ignore ) as executor: # Get list of initial futures defined by max number of parallel requests futures = set() for params in itertools.islice( params_gen, MAPIClientSettings().NUM_PARALLEL_REQUESTS, # type: ignore ): future = executor.submit( func, **params, ) future.crit_ind = params_ind # type: ignore futures.add(future) params_ind += 1 while futures: # Wait for at least one future to complete and process finished finished, futures = wait(futures, return_when=FIRST_COMPLETED) for future in finished: data, subtotal = future.result() if progress_bar is not None: if isinstance(data, dict): size = len(data["data"]) elif isinstance(data, list): size = len(data) else: size = 1 progress_bar.update(size) return_data.append((data, subtotal, future.crit_ind)) # type: ignore # Populate more futures to replace finished for params in itertools.islice(params_gen, len(finished)): new_future = executor.submit( func, **params, ) new_future.crit_ind = params_ind # type: ignore futures.add(new_future) params_ind += 1 return return_data def _submit_request_and_process( self, url: str, verify: bool, params: dict, use_document_model: bool, timeout: int | None = None, ) -> tuple[dict, int]: """Submits GET request and handles the response. Arguments: url: URL to send request to verify: whether to verify the server's TLS certificate params: dictionary of parameters to send in the request use_document_model: if None, will defer to the self.use_document_model attribute timeout: Time in seconds to wait until a request timeout error is thrown Returns: Tuple with data and total number of docs in matching the query in the database. """ headers = None if flask is not None and flask.has_request_context(): headers = flask.request.headers try: response = self.session.get( url=url, verify=verify, params=params, timeout=timeout, headers=headers if headers else self.headers, ) except requests.exceptions.ConnectTimeout: raise MPRestError( f"REST query timed out on URL {url}. Try again with a smaller request." ) if response.status_code in [400]: raise MPRestError( f"The server does not support the request made to {response.url}. " "This may be due to an outdated mp-api package, or a problem with the query." ) if response.status_code == 200: if self.monty_decode: data = json.loads(response.text, cls=MontyDecoder) else: data = json.loads(response.text) # other sub-urls may use different document models # the client does not handle this in a particularly smart way currently if self.document_model and use_document_model: data["data"] = self._convert_to_model(data["data"]) meta_total_doc_num = data.get("meta", {}).get("total_doc", 1) return data, meta_total_doc_num else: try: data = json.loads(response.text)["detail"] except (JSONDecodeError, KeyError): data = f"Response {response.text}" if isinstance(data, str): message = data else: try: message = ", ".join( f"{entry['loc'][1]} - {entry['msg']}" for entry in data ) except (KeyError, IndexError): message = str(data) raise MPRestError( f"REST query returned with error status code {response.status_code} " f"on URL {response.url} with message:\n{message}" ) def _convert_to_model(self, data: list[dict]): """Converts dictionary documents to instantiated MPDataDoc objects. Args: data (list[dict]): Raw dictionary data objects Returns: (list[MPDataDoc]): List of MPDataDoc objects """ raw_doc_list = [self.document_model.model_validate(d) for d in data] # type: ignore if len(raw_doc_list) > 0: data_model, set_fields, _ = self._generate_returned_model(raw_doc_list[0]) data = [ data_model( **{ field: value for field, value in dict(raw_doc).items() if field in set_fields } ) for raw_doc in raw_doc_list ] return data def _generate_returned_model(self, doc): model_fields = self.document_model.model_fields set_fields = doc.model_fields_set unset_fields = [field for field in model_fields if field not in set_fields] include_fields = { name: (model_fields[name].annotation, model_fields[name]) for name in set_fields } data_model = create_model( # type: ignore "MPDataDoc", **include_fields, # TODO fields_not_requested is not the same as unset_fields # i.e. field could be requested but not available in the raw doc fields_not_requested=(list[str], unset_fields), __base__=self.document_model, ) def new_repr(self) -> str: extra = ",\n".join( f"\033[1m{n}\033[0;0m={getattr(self, n)!r}" for n in data_model.model_fields if n == "fields_not_requested" or n in set_fields ) s = f"\033[4m\033[1m{self.__class__.__name__}<{self.__class__.__base__.__name__}>\033[0;0m\033[0;0m(\n{extra}\n)" # noqa: E501 return s def new_str(self) -> str: extra = ",\n".join( f"\033[1m{n}\033[0;0m={getattr(self, n)!r}" for n in data_model.model_fields if n in set_fields ) s = f"\033[4m\033[1m{self.__class__.__name__}<{self.__class__.__base__.__name__}>\033[0;0m\033[0;0m\n{extra}\n\n\033[1mFields not requested:\033[0;0m\n{unset_fields}" # noqa: E501 return s def new_getattr(self, attr) -> str: if attr in self.fields_not_requested: raise AttributeError( f"'{attr}' data is available but has not been requested in 'fields'." " A full list of unrequested fields can be found in `fields_not_requested`." ) else: raise AttributeError( f"{self.__class__.__name__!r} object has no attribute {attr!r}" ) def new_dict(self, *args, **kwargs): d = super(data_model, self).model_dump(*args, **kwargs) return jsanitize(d) data_model.__repr__ = new_repr data_model.__str__ = new_str data_model.__getattr__ = new_getattr data_model.dict = new_dict return data_model, set_fields, unset_fields def _query_resource_data( self, criteria: dict | None = None, fields: list[str] | None = None, suburl: str | None = None, use_document_model: bool | None = None, timeout: int | None = None, ) -> list[T] | list[dict]: """Query the endpoint for a list of documents without associated meta information. Only returns a single page of results. Arguments: criteria: dictionary of criteria to filter down fields: list of fields to return suburl: make a request to a specified sub-url use_document_model: if None, will defer to the self.use_document_model attribute timeout: Time in seconds to wait until a request timeout error is thrown Returns: A list of documents """ return self._query_resource( # type: ignore criteria=criteria, fields=fields, suburl=suburl, use_document_model=use_document_model, chunk_size=1000, num_chunks=1, ).get("data") def _search( self, num_chunks: int | None = None, chunk_size: int = 1000, all_fields: bool = True, fields: list[str] | None = None, **kwargs, ) -> list[T] | list[dict]: """A generic search method to retrieve documents matching specific parameters. Arguments: mute (bool): Whether to mute progress bars. num_chunks (int): Maximum number of chunks of data to yield. None will yield all possible. chunk_size (int): Number of data entries per chunk. all_fields (bool): Set to False to only return specific fields of interest. This will significantly speed up data retrieval for large queries and help us by reducing load on the Materials Project servers. Set to True by default to reduce confusion, unless "fields" are set, in which case all_fields will be set to False. fields (List[str]): List of fields to project. When searching, it is better to only ask for the specific fields of interest to reduce the time taken to retrieve the documents. See the available_fields property to see a list of fields to choose from. kwargs: Supported search terms, e.g. nelements_max=3 for the "materials" search API. Consult the specific API route for valid search terms. Returns: A list of documents. """ # This method should be customized for each end point to give more user friendly, # documented kwargs. return self._get_all_documents( kwargs, all_fields=all_fields, fields=fields, chunk_size=chunk_size, num_chunks=num_chunks, ) def get_data_by_id( self, document_id: str, fields: list[str] | None = None, ) -> T | dict: warnings.warn( "get_data_by_id is deprecated and will be removed soon. Please use the search method instead.", DeprecationWarning, stacklevel=2, ) if self.primary_key in ["material_id", "task_id"]: validate_ids([document_id]) if isinstance(fields, str): # pragma: no cover fields = (fields,) # type: ignore docs = self._search( # type: ignorech( # type: ignorech( # type: ignore **{self.primary_key + "s": document_id}, num_chunks=1, chunk_size=1, all_fields=fields is None, fields=fields, ) return docs[0] if docs else None def _get_all_documents( self, query_params, all_fields=True, fields=None, chunk_size=1000, num_chunks=None, ) -> list[T] | list[dict]: """Iterates over pages until all documents are retrieved. Displays progress using tqdm. This method is designed to give a common implementation for the search_* methods on various endpoints. See materials endpoint for an example of this in use. """ if chunk_size <= 0: raise MPRestError("Chunk size must be greater than zero") if isinstance(num_chunks, int) and num_chunks <= 0: raise MPRestError("Number of chunks must be greater than zero or None.") if all_fields and not fields: query_params["_all_fields"] = True query_params["_limit"] = chunk_size # Check if specific parameters are present that can be parallelized over list_entries = sorted( ( (key, len(entry.split(","))) for key, entry in query_params.items() if isinstance(entry, str) and len(entry.split(",")) > 0 and key not in MAPIClientSettings().QUERY_NO_PARALLEL # type: ignore ), key=lambda item: item[1], reverse=True, ) chosen_param = list_entries[0][0] if len(list_entries) > 0 else None results = self._query_resource( query_params, fields=fields, parallel_param=chosen_param, chunk_size=chunk_size, num_chunks=num_chunks, ) return results["data"] def count(self, criteria: dict | None = None) -> int | str: """Return a count of total documents. Args: criteria (dict | None): As in .search(). Defaults to None Returns: (int | str): Count of total results, or string indicating error """ criteria = criteria or {} user_preferences = ( self.monty_decode, self.use_document_model, self.mute_progress_bars, ) self.monty_decode, self.use_document_model, self.mute_progress_bars = ( False, False, True, ) # do not waste cycles decoding results = self._query_resource(criteria=criteria, num_chunks=1, chunk_size=1) cnt = results["meta"]["total_doc"] no_query = not {field for field in criteria if field[0] != "_"} if no_query and hasattr(self, "search"): allowed_params = inspect.getfullargspec(self.search).args if "deprecated" in allowed_params: criteria["deprecated"] = True results = self._query_resource( criteria=criteria, num_chunks=1, chunk_size=1 ) cnt += results["meta"]["total_doc"] warnings.warn( "Omitting a query also includes deprecated documents in the results. " "Make sure to post-filter them out." ) ( self.monty_decode, self.use_document_model, self.mute_progress_bars, ) = user_preferences return cnt @property def available_fields(self) -> list[str]: if self.document_model is None: return ["Unknown fields."] return list(self.document_model.model_json_schema()["properties"].keys()) # type: ignore def __repr__(self): # pragma: no cover return f"<{self.__class__.__name__} {self.endpoint}>" def __str__(self): # pragma: no cover if self.document_model is None: return self.__repr__() return ( f"{self.__class__.__name__} connected to {self.endpoint}\n\n" f"Available fields: {', '.join(self.available_fields)}\n\n" ) class MPRestError(Exception): """Raised when the query has problems, e.g., bad query format.""" api-0.45.3/mp_api/client/core/settings.py000066400000000000000000000053351475770546700202750ustar00rootroot00000000000000import os from multiprocessing import cpu_count from typing import List from pydantic import Field from pydantic_settings import BaseSettings from pymatgen.core import _load_pmg_settings from mp_api.client import __file__ as root_dir PMG_SETTINGS = _load_pmg_settings() _NUM_PARALLEL_REQUESTS = min(PMG_SETTINGS.get("MPRESTER_NUM_PARALLEL_REQUESTS", 4), 4) _MAX_RETRIES = min(PMG_SETTINGS.get("MPRESTER_MAX_RETRIES", 3), 3) _MUTE_PROGRESS_BAR = PMG_SETTINGS.get("MPRESTER_MUTE_PROGRESS_BARS", False) _MAX_HTTP_URL_LENGTH = PMG_SETTINGS.get("MPRESTER_MAX_HTTP_URL_LENGTH", 2000) _MAX_LIST_LENGTH = min(PMG_SETTINGS.get("MPRESTER_MAX_LIST_LENGTH", 10000), 10000) try: CPU_COUNT = cpu_count() except NotImplementedError: pass class MAPIClientSettings(BaseSettings): """Special class to store settings for MAPI client python module. """ TEST_FILES: str = Field( os.path.join(os.path.dirname(os.path.abspath(root_dir)), "../../test_files"), description="Directory with test files", ) QUERY_NO_PARALLEL: List[str] = Field( [ "elements", "exclude_elements", "possible_species", "coordination_envs", "coordination_envs_anonymous", "has_props", "gb_plane", "rotation_axis", "keywords", "substrate_orientation", "film_orientation", "synthesis_type", "operations", "condition_mixing_device", "condition_mixing_media", "condition_heating_atmosphere", "operations", "_fields", ], description="List API query parameters that do not support parallel requests.", ) NUM_PARALLEL_REQUESTS: int = Field( _NUM_PARALLEL_REQUESTS, description="Number of parallel requests to send.", ) MAX_RETRIES: int = Field( _MAX_RETRIES, description="Maximum number of retries for requests." ) BACKOFF_FACTOR: float = Field( 0.1, description="A backoff factor to apply between retry attempts. To disable, set to 0.", ) MUTE_PROGRESS_BARS: bool = Field( _MUTE_PROGRESS_BAR, description="Whether to mute progress bars when data is retrieved.", ) MAX_HTTP_URL_LENGTH: int = Field( _MAX_HTTP_URL_LENGTH, description="Number of characters to use to define the maximum length of a given HTTP URL.", ) MIN_EMMET_VERSION: str = Field( "0.54.0", description="Minimum compatible version of emmet-core for the client." ) MAX_LIST_LENGTH: int = Field( _MAX_LIST_LENGTH, description="Maximum length of query parameter list" ) class Config: env_prefix = "MPRESTER_" api-0.45.3/mp_api/client/core/utils.py000066400000000000000000000102501475770546700175650ustar00rootroot00000000000000from __future__ import annotations import re from functools import cache from typing import Optional, get_args from maggma.utils import get_flat_models_from_model from monty.json import MSONable from pydantic import BaseModel from pydantic._internal._utils import lenient_issubclass from pydantic.fields import FieldInfo from mp_api.client.core.settings import MAPIClientSettings def validate_ids(id_list: list[str]): """Function to validate material and task IDs. Args: id_list (List[str]): List of material or task IDs. Raises: ValueError: If at least one ID is not formatted correctly. Returns: id_list: Returns original ID list if everything is formatted correctly. """ if len(id_list) > MAPIClientSettings().MAX_LIST_LENGTH: raise ValueError( "List of material/molecule IDs provided is too long. Consider removing the ID filter to automatically pull" " data for all IDs and filter locally." ) pattern = "(mp|mvc|mol|mpcule)-.*" for entry in id_list: if re.match(pattern, entry) is None: raise ValueError(f"{entry} is not formatted correctly!") return id_list @cache def api_sanitize( pydantic_model: BaseModel, fields_to_leave: list[str] | None = None, allow_dict_msonable=False, ): """Function to clean up pydantic models for the API by: 1.) Making fields optional 2.) Allowing dictionaries in-place of the objects for MSONable quantities. WARNING: This works in place, so it mutates the model and all sub-models Args: pydantic_model (BaseModel): Pydantic model to alter fields_to_leave (list[str] | None): list of strings for model fields as "model__name__.field". Defaults to None. allow_dict_msonable (bool): Whether to allow dictionaries in place of MSONable quantities. Defaults to False """ models = [ model for model in get_flat_models_from_model(pydantic_model) if issubclass(model, BaseModel) ] # type: list[BaseModel] fields_to_leave = fields_to_leave or [] fields_tuples = [f.split(".") for f in fields_to_leave] assert all(len(f) == 2 for f in fields_tuples) for model in models: model_fields_to_leave = {f[1] for f in fields_tuples if model.__name__ == f[0]} for name in model.model_fields: field = model.model_fields[name] field_json_extra = field.json_schema_extra field_type = field.annotation if field_type is not None and allow_dict_msonable: if lenient_issubclass(field_type, MSONable): field_type = allow_msonable_dict(field_type) else: for sub_type in get_args(field_type): if lenient_issubclass(sub_type, MSONable): allow_msonable_dict(sub_type) if name not in model_fields_to_leave: new_field = FieldInfo.from_annotated_attribute( Optional[field_type], None ) new_field.json_schema_extra = field_json_extra or {} model.model_fields[name] = new_field model.model_rebuild(force=True) return pydantic_model def allow_msonable_dict(monty_cls: type[MSONable]): """Patch Monty to allow for dict values for MSONable.""" def validate_monty(cls, v, _): """Stub validator for MSONable as a dictionary only.""" if isinstance(v, cls): return v elif isinstance(v, dict): # Just validate the simple Monty Dict Model errors = [] if v.get("@module", "") != monty_cls.__module__: errors.append("@module") if v.get("@class", "") != monty_cls.__name__: errors.append("@class") if len(errors) > 0: raise ValueError( "Missing Monty seriailzation fields in dictionary: {errors}" ) return v else: raise ValueError(f"Must provide {cls.__name__} or MSONable dictionary") monty_cls.validate_monty_v2 = classmethod(validate_monty) return monty_cls api-0.45.3/mp_api/client/mprester.py000066400000000000000000002051641475770546700173500ustar00rootroot00000000000000from __future__ import annotations import itertools import json import os import warnings from functools import cache, lru_cache from json import loads from typing import TYPE_CHECKING from emmet.core.electronic_structure import BSPathType from emmet.core.mpid import MPID from emmet.core.settings import EmmetSettings from emmet.core.tasks import TaskDoc from emmet.core.vasp.calc_types import CalcType from monty.json import MontyDecoder from packaging import version from pymatgen.analysis.phase_diagram import PhaseDiagram from pymatgen.analysis.pourbaix_diagram import IonEntry from pymatgen.core import SETTINGS, Composition, Element, Structure from pymatgen.core.ion import Ion from pymatgen.entries.computed_entries import ComputedStructureEntry from pymatgen.io.vasp import Chgcar from pymatgen.symmetry.analyzer import SpacegroupAnalyzer from requests import Session, get from mp_api.client.core import BaseRester, MPRestError from mp_api.client.core.settings import MAPIClientSettings from mp_api.client.core.utils import validate_ids from mp_api.client.routes import GeneralStoreRester, MessagesRester, UserSettingsRester from mp_api.client.routes.materials import ( AbsorptionRester, AlloysRester, BandStructureRester, BondsRester, ChemenvRester, DielectricRester, DOIRester, DosRester, ElasticityRester, ElectrodeRester, ElectronicStructureRester, EOSRester, GrainBoundaryRester, MagnetismRester, OxidationStatesRester, PhononRester, PiezoRester, ProvenanceRester, RobocrysRester, SimilarityRester, SubstratesRester, SummaryRester, SurfacePropertiesRester, SynthesisRester, TaskRester, ThermoRester, XASRester, ) from mp_api.client.routes.materials.materials import MaterialsRester from mp_api.client.routes.molecules import MoleculeRester if TYPE_CHECKING: from typing import Literal _EMMET_SETTINGS = EmmetSettings() _MAPI_SETTINGS = MAPIClientSettings() class MPRester: """Access the new Materials Project API.""" # Type hints for all routes # To re-generate this list, use: # for rester in MPRester()._all_resters: # print(f"{rester.suffix.replace('/', '_')}: {rester.__class__.__name__}") # Materials eos: EOSRester materials: MaterialsRester similarity: SimilarityRester tasks: TaskRester xas: XASRester grain_boundaries: GrainBoundaryRester substrates: SubstratesRester surface_properties: SurfacePropertiesRester phonon: PhononRester elasticity: ElasticityRester thermo: ThermoRester dielectric: DielectricRester piezoelectric: PiezoRester magnetism: MagnetismRester summary: SummaryRester robocrys: RobocrysRester synthesis: SynthesisRester insertion_electrodes: ElectrodeRester electronic_structure: ElectronicStructureRester electronic_structure_bandstructure: BandStructureRester electronic_structure_dos: DosRester oxidation_states: OxidationStatesRester provenance: ProvenanceRester bonds: BondsRester alloys: AlloysRester absorption: AbsorptionRester chemenv: ChemenvRester # Molecules molecules: MoleculeRester # Generic doi: DOIRester _user_settings: UserSettingsRester _general_store: GeneralStoreRester _messages: MessagesRester def __init__( self, api_key: str | None = None, endpoint: str | None = None, notify_db_version: bool = False, include_user_agent: bool = True, monty_decode: bool = True, use_document_model: bool = True, session: Session | None = None, headers: dict | None = None, mute_progress_bars: bool = _MAPI_SETTINGS.MUTE_PROGRESS_BARS, ): """Initialize the MPRester. Arguments: api_key (str): A String API key for accessing the MaterialsProject REST interface. Please obtain your API key at https://next-gen.materialsproject.org/api. If this is None, the code will check if there is a "MP_API_KEY" setting. If so, it will use that environment variable. This makes easier for heavy users to simply add this environment variable to their setups and MPRester can then be called without any arguments. endpoint (str): URL of endpoint to access the MaterialsProject REST interface. Defaults to the standard Materials Project REST address at "https://api.materialsproject.org", but can be changed to other URLs implementing a similar interface. notify_db_version (bool): If True, the current MP database version will be retrieved and logged locally in the ~/.mprester.log.yaml. If the database version changes, you will be notified. The current database version is also printed on instantiation. These local logs are not sent to materialsproject.org and are not associated with your API key, so be aware that a notification may not be presented if you run MPRester from multiple computing environments. include_user_agent (bool): If True, will include a user agent with the HTTP request including information on pymatgen and system version making the API request. This helps MP support pymatgen users, and is similar to what most web browsers send with each page request. Set to False to disable the user agent. monty_decode: Decode the data using monty into python objects use_document_model: If False, skip the creating the document model and return data as a dictionary. This can be simpler to work with but bypasses data validation and will not give auto-complete for available fields. session: Session object to use. By default (None), the client will create one. headers: Custom headers for localhost connections. mute_progress_bars: Whether to mute progress bars. """ # SETTINGS tries to read API key from ~/.config/.pmgrc.yaml api_key = api_key or os.getenv("MP_API_KEY") or SETTINGS.get("PMG_MAPI_KEY") if api_key and len(api_key) != 32: raise ValueError( "Please use a new API key from https://materialsproject.org/api " "Keys for the new API are 32 characters, whereas keys for the legacy " "API are 16 characters." ) self.api_key = api_key self.endpoint = endpoint or os.getenv( "MP_API_ENDPOINT", "https://api.materialsproject.org/" ) self.headers = headers or {} self.session = session or BaseRester._create_session( api_key=self.api_key, include_user_agent=include_user_agent, headers=self.headers, ) self.use_document_model = use_document_model self.monty_decode = monty_decode self.mute_progress_bars = mute_progress_bars self._contribs = None self._deprecated_attributes = [ "eos", "similarity", "tasks", "xas", "fermi", "grain_boundaries", "substrates", "surface_properties", "phonon", "elasticity", "thermo", "dielectric", "piezoelectric", "magnetism", "summary", "robocrys", "synthesis", "insertion_electrodes", "electronic_structure", "electronic_structure_bandstructure", "electronic_structure_dos", "oxidation_states", "provenance", "bonds", "alloys", "absorption", "chemenv", ] # Check if emmet version of server is compatible emmet_version = MPRester.get_emmet_version(self.endpoint) if version.parse(emmet_version.base_version) < version.parse( _MAPI_SETTINGS.MIN_EMMET_VERSION ): warnings.warn( "The installed version of the mp-api client may not be compatible with the API server. " "Please install a previous version if any problems occur." ) if notify_db_version: raise NotImplementedError("This has not yet been implemented.") if not self.endpoint.endswith("/"): self.endpoint += "/" # Dynamically set rester attributes. # First, materials and molecules top level resters are set. # Nested rested are then setup to be loaded dynamically with custom __getattr__ functions. self._all_resters = [] # Get all rester classes for _cls in BaseRester.__subclasses__(): sub_resters = _cls.__subclasses__() if sub_resters: self._all_resters.extend(sub_resters) else: self._all_resters.append(_cls) # Instantiate top level molecules and materials resters and set them as attributes core_suffix = ["molecules/core", "materials/core"] core_resters = { cls.suffix.split("/")[0]: cls( api_key=api_key, endpoint=self.endpoint, include_user_agent=include_user_agent, session=self.session, monty_decode=self.monty_decode, use_document_model=self.use_document_model, headers=self.headers, mute_progress_bars=self.mute_progress_bars, ) for cls in self._all_resters if cls.suffix in core_suffix } # Set remaining top level resters, or get an attribute-class name mapping # for all sub-resters _sub_rester_suffix_map = {"materials": {}, "molecules": {}} for cls in self._all_resters: if cls.suffix not in core_suffix: suffix_split = cls.suffix.split("/") if len(suffix_split) == 1: # Disable monty decode on nested data which may give errors monty_disable = cls in [TaskRester, ProvenanceRester] monty_decode = False if monty_disable else self.monty_decode rester = cls( api_key=api_key, endpoint=self.endpoint, include_user_agent=include_user_agent, session=self.session, monty_decode=monty_decode, use_document_model=self.use_document_model, headers=self.headers, mute_progress_bars=self.mute_progress_bars, ) # type: BaseRester setattr( self, suffix_split[0], rester, ) else: attr = "_".join(suffix_split[1:]) if "materials" in suffix_split: _sub_rester_suffix_map["materials"][attr] = cls elif "molecules" in suffix_split: _sub_rester_suffix_map["molecules"][attr] = cls # TODO: Enable monty decoding when tasks and SNL schema is normalized # # Allow lazy loading of nested resters under materials and molecules using custom __getattr__ methods def __core_custom_getattr(_self, _attr, _rester_map): if _attr in _rester_map: cls = _rester_map[_attr] monty_disable = cls in [TaskRester, ProvenanceRester] monty_decode = False if monty_disable else self.monty_decode rester = cls( api_key=api_key, endpoint=self.endpoint, include_user_agent=include_user_agent, session=self.session, monty_decode=monty_decode, use_document_model=self.use_document_model, headers=self.headers, mute_progress_bars=self.mute_progress_bars, ) # type: BaseRester setattr( _self, _attr, rester, ) return rester else: raise AttributeError( f"{_self.__class__.__name__!r} object has no attribute {_attr!r}" ) def __materials_getattr__(_self, attr): _rester_map = _sub_rester_suffix_map["materials"] rester = __core_custom_getattr(_self, attr, _rester_map) return rester def __molecules_getattr__(_self, attr): _rester_map = _sub_rester_suffix_map["molecules"] rester = __core_custom_getattr(_self, attr, _rester_map) return rester MaterialsRester.__getattr__ = __materials_getattr__ # type: ignore MoleculeRester.__getattr__ = __molecules_getattr__ # type: ignore for attr, rester in core_resters.items(): setattr( self, attr, rester, ) @property def contribs(self): if self._contribs is None: try: from mpcontribs.client import Client self._contribs = Client( self.api_key, # type: ignore headers=self.headers, session=self.session, ) except ImportError: self._contribs = None warnings.warn( "mpcontribs-client not installed. " "Install the package to query MPContribs data, or construct pourbaix diagrams: " "'pip install mpcontribs-client'" ) except Exception as error: self._contribs = None warnings.warn(f"Problem loading MPContribs client: {error}") return self._contribs def __enter__(self): """Support for "with" context.""" return self def __exit__(self, exc_type, exc_val, exc_tb): """Support for "with" context.""" self.session.close() def __getattr__(self, attr): if attr in self._deprecated_attributes: warnings.warn( f"Accessing {attr} data through MPRester.{attr} is deprecated. " f"Please use MPRester.materials.{attr} instead.", DeprecationWarning, stacklevel=2, ) return getattr(super().__getattribute__("materials"), attr) else: raise AttributeError( f"{self.__class__.__name__!r} object has no attribute {attr!r}" ) def __dir__(self): return dir(MPRester) + self._deprecated_attributes + ["materials", "molecules"] def get_task_ids_associated_with_material_id( self, material_id: str, calc_types: list[CalcType] | None = None ) -> list[str]: """Get Task ID values associated with a specific Material ID. Args: material_id (str): Material ID calc_types ([CalcType]): If specified, will restrict to a certain task type, e.g. [CalcType.GGA_STATIC] Returns: ([str]): List of Task ID values. """ tasks = self.materials.search(material_ids=material_id, fields=["calc_types"]) if not tasks: return [] calculations = ( tasks[0].calc_types # type: ignore if self.use_document_model else tasks[0]["calc_types"] # type: ignore ) if calc_types: return [ task for task, calc_type in calculations.items() if calc_type in calc_types ] else: return list(calculations.keys()) def get_structure_by_material_id( self, material_id: str, final: bool = True, conventional_unit_cell: bool = False ) -> Structure | list[Structure]: """Get a Structure corresponding to a material_id. Args: material_id (str): Materials Project material_id (a string, e.g., mp-1234). final (bool): Whether to get the final structure, or the list of initial (pre-relaxation) structures. Defaults to True. conventional_unit_cell (bool): Whether to get the standard conventional unit cell for the final or list of initial structures. Returns: Structure object or list of Structure objects. """ structure_data = self.materials.get_structure_by_material_id( material_id=material_id, final=final ) if conventional_unit_cell and structure_data: if final: structure_data = SpacegroupAnalyzer( structure_data ).get_conventional_standard_structure() else: structure_data = [ SpacegroupAnalyzer(structure).get_conventional_standard_structure() for structure in structure_data ] return structure_data def get_database_version(self): """The Materials Project database is periodically updated and has a database version associated with it. When the database is updated, consolidated data (information about "a material") may and does change, while calculation data about a specific calculation task remains unchanged and available for querying via its task_id. The database version is set as a date in the format YYYY_MM_DD, where "_DD" may be optional. An additional numerical suffix might be added if multiple releases happen on the same day. Returns: database version as a string """ return get(url=self.endpoint + "heartbeat").json()["db_version"] @staticmethod @cache def get_emmet_version(endpoint): """Get the latest version emmet-core and emmet-api used in the current API service. Returns: version as a string """ response = get(url=endpoint + "heartbeat").json() error = response.get("error", None) if error: raise MPRestError(error) return version.parse(response["version"]) def get_material_id_from_task_id(self, task_id: str) -> str | None: """Returns the current material_id from a given task_id. The material_id should rarely change, and is usually chosen from among the smallest numerical id from the group of task_ids for that material. However, in some circumstances it might change, and this method is useful for finding the new material_id. Args: task_id (str): A task id. Returns: material_id (MPID) """ docs = self.materials.search(task_ids=[task_id], fields=["material_id"]) if len(docs) == 1: # pragma: no cover return str(docs[0].material_id) # type: ignore elif len(docs) > 1: # pragma: no cover raise ValueError( f"Multiple documents return for {task_id}, this should not happen, please report it!" ) else: # pragma: no cover warnings.warn( f"No material found containing task {task_id}. Please report it if you suspect a task has gone missing." ) return None def get_material_id_references(self, material_id: str) -> list[str]: """Returns all references for a material id. Args: material_id (str): A material id. Returns: List of BibTeX references ([str]) """ docs = self.materials.provenance.search(material_ids=material_id) if not docs: return [] return docs[0].references if self.use_document_model else docs[0]["references"] # type: ignore def get_material_ids( self, chemsys_formula: str | list[str], ) -> list[MPID]: """Get all materials ids for a formula or chemsys. Args: chemsys_formula (str, List[str]): A chemical system, list of chemical systems (e.g., Li-Fe-O, Si-*, [Si-O, Li-Fe-P]), or single formula (e.g., Fe2O3, Si*). Returns: List of all materials ids ([MPID]) """ if isinstance(chemsys_formula, list) or ( isinstance(chemsys_formula, str) and "-" in chemsys_formula ): input_params = {"chemsys": chemsys_formula} else: input_params = {"formula": chemsys_formula} return sorted( doc.material_id if self.use_document_model else doc["material_id"] # type: ignore for doc in self.materials.search( **input_params, # type: ignore all_fields=False, fields=["material_id"], ) ) def get_structures( self, chemsys_formula: str | list[str], final=True ) -> list[Structure]: """Get a list of Structures corresponding to a chemical system or formula. Args: chemsys_formula (str, List[str]): A chemical system, list of chemical systems (e.g., Li-Fe-O, Si-*, [Si-O, Li-Fe-P]), or single formula (e.g., Fe2O3, Si*). final (bool): Whether to get the final structure, or the list of initial (pre-relaxation) structures. Defaults to True. Returns: List of Structure objects. ([Structure]) """ if isinstance(chemsys_formula, list) or ( isinstance(chemsys_formula, str) and "-" in chemsys_formula ): input_params = {"chemsys": chemsys_formula} else: input_params = {"formula": chemsys_formula} if final: docs = self.materials.search( **input_params, # type: ignore all_fields=False, fields=["structure"], ) if not self.use_document_model: return [doc["structure"] for doc in docs] # type: ignore return [doc.structure for doc in docs] # type: ignore else: structures = [] for doc in self.materials.search( **input_params, # type: ignore all_fields=False, fields=["initial_structures"], ): initial_structures = ( doc.initial_structures # type: ignore if self.use_document_model else doc["initial_structures"] # type: ignore ) structures.extend(initial_structures) return structures def find_structure( self, filename_or_structure: str | Structure, ltol: float = _EMMET_SETTINGS.LTOL, stol: float = _EMMET_SETTINGS.STOL, angle_tol: float = _EMMET_SETTINGS.ANGLE_TOL, allow_multiple_results: bool = False, ) -> list[str] | str: """Finds matching structures from the Materials Project database. Multiple results may be returned of "similar" structures based on distance using the pymatgen StructureMatcher algorithm, however only a single result should match with the same spacegroup, calculated to the default tolerances. Args: filename_or_structure: filename or Structure object ltol: fractional length tolerance stol: site tolerance angle_tol: angle tolerance in degrees allow_multiple_results: changes return type for either a single material_id or list of material_ids Returns: A matching material_id if one is found or list of results if allow_multiple_results is True Raises: MPRestError """ return self.materials.find_structure( filename_or_structure, ltol=ltol, stol=stol, angle_tol=angle_tol, allow_multiple_results=allow_multiple_results, ) def get_entries( self, chemsys_formula_mpids: str | list[str], compatible_only: bool = True, inc_structure: bool | None = None, property_data: list[str] | None = None, conventional_unit_cell: bool = False, additional_criteria: dict | None = None, ) -> list[ComputedStructureEntry]: """Get a list of ComputedEntries or ComputedStructureEntries corresponding to a chemical system or formula. This returns entries for all thermo types represented in the database. Each type corresponds to a different mixing scheme (i.e. GGA/GGA+U, GGA/GGA+U/R2SCAN, R2SCAN). By default the thermo_type of the entry is also returned. Args: chemsys_formula_mpids (str, List[str]): A chemical system, list of chemical systems (e.g., Li-Fe-O, Si-*, [Si-O, Li-Fe-P]), formula, list of formulas (e.g., Fe2O3, Si*, [SiO2, BiFeO3]), Materials Project ID, or list of Materials Project IDs (e.g., mp-22526, [mp-22526, mp-149]). compatible_only (bool): Whether to return only "compatible" entries. Compatible entries are entries that have been processed using the MaterialsProject2020Compatibility class, which performs adjustments to allow mixing of GGA and GGA+U calculations for more accurate phase diagrams and reaction energies. This data is obtained from the core "thermo" API endpoint. inc_structure (str): *This is a deprecated argument*. Previously, if None, entries returned were ComputedEntries. If inc_structure="initial", ComputedStructureEntries with initial structures were returned. Otherwise, ComputedStructureEntries with final structures were returned. This is no longer needed as all entries will contain the final structure data by default. property_data (list): Specify additional properties to include in entry.data. If None, only default data is included. Should be a subset of input parameters in the 'MPRester.thermo.available_fields' list. conventional_unit_cell (bool): Whether to get the standard conventional unit cell additional_criteria (dict): Any additional criteria to pass. The keys and values should correspond to proper function inputs to `MPRester.thermo.search`. For instance, if you are only interested in entries on the convex hull, you could pass {"energy_above_hull": (0.0, 0.0)} or {"is_stable": True}. Returns: List ComputedStructureEntry objects. """ if inc_structure is not None: warnings.warn( "The 'inc_structure' argument is deprecated as structure " "data is now always included in all returned entry objects." ) if isinstance(chemsys_formula_mpids, str): chemsys_formula_mpids = [chemsys_formula_mpids] try: input_params = {"material_ids": validate_ids(chemsys_formula_mpids)} except ValueError: if any("-" in entry for entry in chemsys_formula_mpids): input_params = {"chemsys": chemsys_formula_mpids} else: input_params = {"formula": chemsys_formula_mpids} if additional_criteria: input_params = {**input_params, **additional_criteria} entries = [] fields = ( ["entries", "thermo_type"] if not property_data else ["entries", "thermo_type"] + property_data ) docs = self.materials.thermo.search( **input_params, # type: ignore all_fields=False, fields=fields, ) for doc in docs: entry_list = ( doc.entries.values() # type: ignore if self.use_document_model else doc["entries"].values() # type: ignore ) for entry in entry_list: entry_dict: dict = entry.as_dict() if self.monty_decode else entry # type: ignore if not compatible_only: entry_dict["correction"] = 0.0 entry_dict["energy_adjustments"] = [] if property_data: for property in property_data: entry_dict["data"][property] = ( doc.model_dump()[property] # type: ignore if self.use_document_model else doc[property] # type: ignore ) if conventional_unit_cell: entry_struct = Structure.from_dict(entry_dict["structure"]) s = SpacegroupAnalyzer( entry_struct ).get_conventional_standard_structure() site_ratio = len(s) / len(entry_struct) new_energy = entry_dict["energy"] * site_ratio entry_dict["energy"] = new_energy entry_dict["structure"] = s.as_dict() entry_dict["correction"] = 0.0 for element in entry_dict["composition"]: entry_dict["composition"][element] *= site_ratio for correction in entry_dict["energy_adjustments"]: if "n_atoms" in correction: correction["n_atoms"] *= site_ratio entry = ( ComputedStructureEntry.from_dict(entry_dict) if self.monty_decode else entry_dict ) entries.append(entry) return entries def get_pourbaix_entries( self, chemsys: str | list, solid_compat="MaterialsProject2020Compatibility", use_gibbs: Literal[300] | None = None, ): """A helper function to get all entries necessary to generate a Pourbaix diagram from the rest interface. Args: chemsys (str or [str]): Chemical system string comprising element symbols separated by dashes, e.g., "Li-Fe-O" or List of element symbols, e.g., ["Li", "Fe", "O"]. solid_compat: Compatibility scheme used to pre-process solid DFT energies prior to applying aqueous energy adjustments. May be passed as a class (e.g. MaterialsProject2020Compatibility) or an instance (e.g., MaterialsProject2020Compatibility()). If None, solid DFT energies are used as-is. Default: MaterialsProject2020Compatibility use_gibbs: Set to 300 (for 300 Kelvin) to use a machine learning model to estimate solid free energy from DFT energy (see GibbsComputedStructureEntry). This can slightly improve the accuracy of the Pourbaix diagram in some cases. Default: None. Note that temperatures other than 300K are not permitted here, because MaterialsProjectAqueousCompatibility corrections, used in Pourbaix diagram construction, are calculated based on 300 K data. """ # imports are not top-level due to expense from pymatgen.analysis.pourbaix_diagram import PourbaixEntry from pymatgen.entries.compatibility import ( Compatibility, MaterialsProject2020Compatibility, MaterialsProjectAqueousCompatibility, MaterialsProjectCompatibility, ) from pymatgen.entries.computed_entries import ComputedEntry if solid_compat == "MaterialsProjectCompatibility": solid_compat = MaterialsProjectCompatibility() elif solid_compat == "MaterialsProject2020Compatibility": solid_compat = MaterialsProject2020Compatibility() elif isinstance(solid_compat, Compatibility): pass else: raise ValueError( "Solid compatibility can only be 'MaterialsProjectCompatibility', " "'MaterialsProject2020Compatibility', or an instance of a Compatibility class" ) pbx_entries = [] if isinstance(chemsys, str): chemsys = chemsys.split("-") # capitalize and sort the elements chemsys = sorted(e.capitalize() for e in chemsys) # Get ion entries first, because certain ions have reference # solids that aren't necessarily in the chemsys (Na2SO4) # download the ion reference data from MPContribs ion_data = self.get_ion_reference_data_for_chemsys(chemsys) # build the PhaseDiagram for get_ion_entries ion_ref_comps = [ Ion.from_formula(d["data"]["RefSolid"]).composition for d in ion_data ] ion_ref_elts = set( itertools.chain.from_iterable(i.elements for i in ion_ref_comps) ) # TODO - would be great if the commented line below would work # However for some reason you cannot process GibbsComputedStructureEntry with # MaterialsProjectAqueousCompatibility ion_ref_entries = self.get_entries_in_chemsys( list([str(e) for e in ion_ref_elts] + ["O", "H"]), # use_gibbs=use_gibbs ) # suppress the warning about supplying the required energies; they will be calculated from the # entries we get from MPRester with warnings.catch_warnings(): warnings.filterwarnings( "ignore", message="You did not provide the required O2 and H2O energies.", ) compat = MaterialsProjectAqueousCompatibility(solid_compat=solid_compat) # suppress the warning about missing oxidation states with warnings.catch_warnings(): warnings.filterwarnings( "ignore", message="Failed to guess oxidation states.*" ) ion_ref_entries = compat.process_entries(ion_ref_entries) # type: ignore # TODO - if the commented line above would work, this conditional block # could be removed if use_gibbs: # replace the entries with GibbsComputedStructureEntry from pymatgen.entries.computed_entries import GibbsComputedStructureEntry ion_ref_entries = GibbsComputedStructureEntry.from_entries( ion_ref_entries, temp=use_gibbs ) ion_ref_pd = PhaseDiagram(ion_ref_entries) # type: ignore ion_entries = self.get_ion_entries(ion_ref_pd, ion_ref_data=ion_data) pbx_entries = [PourbaixEntry(e, f"ion-{n}") for n, e in enumerate(ion_entries)] # Construct the solid pourbaix entries from filtered ion_ref entries extra_elts = ( set(ion_ref_elts) - {Element(s) for s in chemsys} - {Element("H"), Element("O")} ) for entry in ion_ref_entries: entry_elts = set(entry.composition.elements) # Ensure no OH chemsys or extraneous elements from ion references if not ( entry_elts <= {Element("H"), Element("O")} or extra_elts.intersection(entry_elts) ): # Create new computed entry form_e = ion_ref_pd.get_form_energy(entry) # type: ignore new_entry = ComputedEntry( entry.composition, form_e, entry_id=entry.entry_id ) pbx_entry = PourbaixEntry(new_entry) pbx_entries.append(pbx_entry) return pbx_entries @lru_cache def get_ion_reference_data(self) -> list[dict]: """Download aqueous ion reference data used in the construction of Pourbaix diagrams. Use this method to examine the ion reference data and to add additional ions if desired. The data returned from this method can be passed to get_ion_entries(). Data are retrieved from the Aqueous Ion Reference Data project hosted on MPContribs. Refer to that project and its associated documentation for more details about the format and meaning of the data. Returns: [dict]: Among other data, each record contains 1) the experimental ion free energy, 2) the formula of the reference solid for the ion, and 3) the experimental free energy of the reference solid. All energies are given in kJ/mol. An example is given below. {'identifier': 'Li[+]', 'formula': 'Li[+]', 'data': {'charge': {'display': '1.0', 'value': 1.0, 'unit': ''}, 'ΔGᶠ': {'display': '-293.71 kJ/mol', 'value': -293.71, 'unit': 'kJ/mol'}, 'MajElements': 'Li', 'RefSolid': 'Li2O', 'ΔGᶠRefSolid': {'display': '-561.2 kJ/mol', 'value': -561.2, 'unit': 'kJ/mol'}, 'reference': 'H. E. Barner and R. V. Scheuerman, Handbook of thermochemical data for compounds and aqueous species, Wiley, New York (1978)'}} """ return self.contribs.query_contributions( # type: ignore query={"project": "ion_ref_data"}, fields=["identifier", "formula", "data"], paginate=True, ).get( "data" ) # type: ignore def get_ion_reference_data_for_chemsys(self, chemsys: str | list) -> list[dict]: """Download aqueous ion reference data used in the construction of Pourbaix diagrams. Use this method to examine the ion reference data and to add additional ions if desired. The data returned from this method can be passed to get_ion_entries(). Data are retrieved from the Aqueous Ion Reference Data project hosted on MPContribs. Refer to that project and its associated documentation for more details about the format and meaning of the data. Args: chemsys (str or [str]): Chemical system string comprising element symbols separated by dashes, e.g., "Li-Fe-O" or List of element symbols, e.g., ["Li", "Fe", "O"]. Returns: [dict]: Among other data, each record contains 1) the experimental ion free energy, 2) the formula of the reference solid for the ion, and 3) the experimental free energy of the reference solid. All energies are given in kJ/mol. An example is given below. {'identifier': 'Li[+]', 'formula': 'Li[+]', 'data': {'charge': {'display': '1.0', 'value': 1.0, 'unit': ''}, 'ΔGᶠ': {'display': '-293.71 kJ/mol', 'value': -293.71, 'unit': 'kJ/mol'}, 'MajElements': 'Li', 'RefSolid': 'Li2O', 'ΔGᶠRefSolid': {'display': '-561.2 kJ/mol', 'value': -561.2, 'unit': 'kJ/mol'}, 'reference': 'H. E. Barner and R. V. Scheuerman, Handbook of thermochemical data for compounds and aqueous species, Wiley, New York (1978)'}} """ ion_data = self.get_ion_reference_data() if isinstance(chemsys, str): chemsys = chemsys.split("-") return [d for d in ion_data if d["data"]["MajElements"] in chemsys] def get_ion_entries( self, pd: PhaseDiagram, ion_ref_data: list[dict] | None = None ) -> list[IonEntry]: """Retrieve IonEntry objects that can be used in the construction of Pourbaix Diagrams. The energies of the IonEntry are calculaterd from the solid energies in the provided Phase Diagram to be consistent with experimental free energies. NOTE! This is an advanced method that assumes detailed understanding of how to construct computational Pourbaix Diagrams. If you just want to build a Pourbaix Diagram using default settings, use get_pourbaix_entries. Args: pd: Solid phase diagram on which to construct IonEntry. Note that this Phase Diagram MUST include O and H in its chemical system. For example, to retrieve IonEntry for Ti, the phase diagram passed here should contain materials in the H-O-Ti chemical system. It is also assumed that solid energies have already been corrected with MaterialsProjectAqueousCompatibility, which is necessary for proper construction of Pourbaix diagrams. ion_ref_data: Aqueous ion reference data. If None (default), the data are downloaded from the Aqueous Ion Reference Data project hosted on MPContribs. To add a custom ionic species, first download data using get_ion_reference_data, then add or customize it with your additional data, and pass the customized list here. Returns: [IonEntry]: IonEntry are similar to PDEntry objects. Their energies are free energies in eV. """ # determine the chemsys from the phase diagram chemsys = "-".join([el.symbol for el in pd.elements]) # raise ValueError if O and H not in chemsys if "O" not in chemsys or "H" not in chemsys: raise ValueError( "The phase diagram chemical system must contain O and H! Your" f" diagram chemical system is {chemsys}." ) if not ion_ref_data: ion_data = self.get_ion_reference_data_for_chemsys(chemsys) else: ion_data = ion_ref_data # position the ion energies relative to most stable reference state ion_entries = [] for _, i_d in enumerate(ion_data): ion = Ion.from_formula(i_d["formula"]) refs = [ e for e in pd.all_entries if e.composition.reduced_formula == i_d["data"]["RefSolid"] ] if not refs: raise ValueError("Reference solid not contained in entry list") stable_ref = sorted(refs, key=lambda x: x.energy_per_atom)[0] rf = stable_ref.composition.get_reduced_composition_and_factor()[1] # TODO - need a more robust way to convert units # use pint here? if i_d["data"]["ΔGᶠRefSolid"]["unit"] == "kJ/mol": # convert to eV/formula unit ref_solid_energy = i_d["data"]["ΔGᶠRefSolid"]["value"] / 96.485 elif i_d["data"]["ΔGᶠRefSolid"]["unit"] == "MJ/mol": # convert to eV/formula unit ref_solid_energy = i_d["data"]["ΔGᶠRefSolid"]["value"] / 96485 else: raise ValueError( f"Ion reference solid energy has incorrect unit {i_d['data']['ΔGᶠRefSolid']['unit']}" ) solid_diff = pd.get_form_energy(stable_ref) - ref_solid_energy * rf elt = i_d["data"]["MajElements"] correction_factor = ion.composition[elt] / stable_ref.composition[elt] # TODO - need a more robust way to convert units # use pint here? if i_d["data"]["ΔGᶠ"]["unit"] == "kJ/mol": # convert to eV/formula unit ion_free_energy = i_d["data"]["ΔGᶠ"]["value"] / 96.485 elif i_d["data"]["ΔGᶠ"]["unit"] == "MJ/mol": # convert to eV/formula unit ion_free_energy = i_d["data"]["ΔGᶠ"]["value"] / 96485 else: raise ValueError( f"Ion free energy has incorrect unit {i_d['data']['ΔGᶠ']['unit']}" ) energy = ion_free_energy + solid_diff * correction_factor ion_entries.append(IonEntry(ion, energy)) return ion_entries def get_entry_by_material_id( self, material_id: str, compatible_only: bool = True, inc_structure: bool | None = None, property_data: list[str] | None = None, conventional_unit_cell: bool = False, ): """Get all ComputedEntry objects corresponding to a material_id. Args: material_id (str): Materials Project material_id (a string, e.g., mp-1234). compatible_only (bool): Whether to return only "compatible" entries. Compatible entries are entries that have been processed using the MaterialsProject2020Compatibility class, which performs adjustments to allow mixing of GGA and GGA+U calculations for more accurate phase diagrams and reaction energies. This data is obtained from the core "thermo" API endpoint. inc_structure (str): *This is a deprecated argument*. Previously, if None, entries returned were ComputedEntries. If inc_structure="initial", ComputedStructureEntries with initial structures were returned. Otherwise, ComputedStructureEntries with final structures were returned. This is no longer needed as all entries will contain structure data by default. property_data (list): Specify additional properties to include in entry.data. If None, only default data is included. Should be a subset of input parameters in the 'MPRester.thermo.available_fields' list. conventional_unit_cell (bool): Whether to get the standard conventional unit cell Returns: List of ComputedEntry or ComputedStructureEntry object. """ return self.get_entries( material_id, compatible_only=compatible_only, inc_structure=inc_structure, property_data=property_data, conventional_unit_cell=conventional_unit_cell, ) def get_entries_in_chemsys( self, elements: str | list[str], use_gibbs: int | None = None, compatible_only: bool = True, inc_structure: bool | None = None, property_data: list[str] | None = None, conventional_unit_cell: bool = False, additional_criteria=None, ): """Helper method to get a list of ComputedEntries in a chemical system. For example, elements = ["Li", "Fe", "O"] will return a list of all entries in the parent Li-Fe-O chemical system, as well as all subsystems (i.e., all LixOy, FexOy, LixFey, LixFeyOz, Li, Fe and O phases). Extremely useful for creating phase diagrams of entire chemical systems. Note that by default this returns mixed GGA/GGA+U entries. For others, pass GGA/GGA+U/R2SCAN, or R2SCAN as thermo_types in additional_criteria. Args: elements (str or [str]): Parent chemical system string comprising element symbols separated by dashes, e.g., "Li-Fe-O" or List of element symbols, e.g., ["Li", "Fe", "O"]. use_gibbs: If None (default), DFT energy is returned. If a number, return the free energy of formation estimated using a machine learning model (see GibbsComputedStructureEntry). The number is the temperature in Kelvin at which to estimate the free energy. Must be between 300 K and 2000 K. compatible_only (bool): Whether to return only "compatible" entries. Compatible entries are entries that have been processed using the MaterialsProject2020Compatibility class, which performs adjustments to allow mixing of GGA and GGA+U calculations for more accurate phase diagrams and reaction energies. This data is obtained from the core "thermo" API endpoint. inc_structure (str): *This is a deprecated argument*. Previously, if None, entries returned were ComputedEntries. If inc_structure="initial", ComputedStructureEntries with initial structures were returned. Otherwise, ComputedStructureEntries with final structures were returned. This is no longer needed as all entries will contain structure data by default. property_data (list): Specify additional properties to include in entry.data. If None, only default data is included. Should be a subset of input parameters in the 'MPRester.thermo.available_fields' list. conventional_unit_cell (bool): Whether to get the standard conventional unit cell additional_criteria (dict): Any additional criteria to pass. The keys and values should correspond to proper function inputs to `MPRester.thermo.search`. For instance, if you are only interested in entries on the convex hull, you could pass {"energy_above_hull": (0.0, 0.0)} or {"is_stable": True}, or if you are only interested in entry data Returns: List of ComputedStructureEntries. """ if isinstance(elements, str): elements = elements.split("-") elements_set = set(elements) # remove duplicate elements all_chemsyses = [] for i in range(len(elements_set)): for els in itertools.combinations(elements_set, i + 1): all_chemsyses.append("-".join(sorted(els))) entries = [] entries.extend( self.get_entries( all_chemsyses, compatible_only=compatible_only, inc_structure=inc_structure, property_data=property_data, conventional_unit_cell=conventional_unit_cell, additional_criteria=additional_criteria or {"thermo_types": ["GGA_GGA+U"]}, ) ) if not self.monty_decode: entries = [ComputedStructureEntry.from_dict(entry) for entry in entries] if use_gibbs: # replace the entries with GibbsComputedStructureEntry from pymatgen.entries.computed_entries import GibbsComputedStructureEntry entries = GibbsComputedStructureEntry.from_entries(entries, temp=use_gibbs) if not self.monty_decode: entries = [entry.as_dict() for entry in entries] return entries def get_bandstructure_by_material_id( self, material_id: str, path_type: BSPathType = BSPathType.setyawan_curtarolo, line_mode=True, ): """Get the band structure pymatgen object associated with a Materials Project ID. Arguments: material_id (str): Materials Project ID for a material path_type (BSPathType): k-point path selection convention line_mode (bool): Whether to return data for a line-mode calculation Returns: bandstructure (Union[BandStructure, BandStructureSymmLine]): BandStructure or BandStructureSymmLine object """ return self.materials.electronic_structure_bandstructure.get_bandstructure_from_material_id( # type: ignore material_id=material_id, path_type=path_type, line_mode=line_mode ) def get_dos_by_material_id(self, material_id: str): """Get the complete density of states pymatgen object associated with a Materials Project ID. Arguments: material_id (str): Materials Project ID for a material Returns: dos (CompleteDos): CompleteDos object """ return self.materials.electronic_structure_dos.get_dos_from_material_id( material_id=material_id ) # type: ignore def get_phonon_dos_by_material_id(self, material_id: str): """Get phonon density of states data corresponding to a material_id. Args: material_id (str): Materials Project material_id. Returns: CompletePhononDos: A phonon DOS object. """ doc = self.materials.phonon.search(material_ids=material_id, fields=["ph_dos"]) if not doc: return None return doc[0].ph_dos if self.use_document_model else doc[0]["ph_dos"] # type: ignore def get_phonon_bandstructure_by_material_id(self, material_id: str): """Get phonon dispersion data corresponding to a material_id. Args: material_id (str): Materials Project material_id. Returns: PhononBandStructureSymmLine: phonon band structure. """ doc = self.materials.phonon.search(material_ids=material_id, fields=["ph_bs"]) if not doc: return None return doc[0].ph_bs if self.use_document_model else doc[0]["ph_bs"] # type: ignore def get_wulff_shape(self, material_id: str): """Constructs a Wulff shape for a material. Args: material_id (str): Materials Project material_id, e.g. 'mp-123'. Returns: pymatgen.analysis.wulff.WulffShape """ from pymatgen.analysis.wulff import WulffShape from pymatgen.symmetry.analyzer import SpacegroupAnalyzer structure = self.get_structure_by_material_id(material_id) doc = self.materials.surface_properties.search(material_ids=material_id) if not doc: return None surfaces: list = ( doc[0].surfaces if self.use_document_model else doc[0]["surfaces"] # type: ignore ) lattice = ( SpacegroupAnalyzer(structure).get_conventional_standard_structure().lattice ) miller_energy_map = {} for surf in surfaces: miller = tuple(surf.miller_index) if surf.miller_index else () # Prefer reconstructed surfaces, which have lower surface energies. if (miller not in miller_energy_map) or surf.is_reconstructed: miller_energy_map[miller] = surf.surface_energy millers, energies = zip(*miller_energy_map.items()) return WulffShape(lattice, millers, energies) def get_charge_density_from_task_id( self, task_id: str, inc_task_doc: bool = False ) -> Chgcar | tuple[Chgcar, TaskDoc | dict] | None: """Get charge density data for a given task_id. Arguments: task_id (str): A task id inc_task_doc (bool): Whether to include the task document in the returned data. Returns: (Chgcar, (Chgcar, TaskDoc | dict), None): Pymatgen Chgcar object, or tuple with object and TaskDoc """ decoder = MontyDecoder().decode if self.monty_decode else json.loads kwargs = dict( bucket="materialsproject-parsed", key=f"chgcars/{str(task_id)}.json.gz", decoder=decoder, ) chgcar = self.materials.tasks._query_open_data(**kwargs)[0] if not chgcar: raise MPRestError(f"No charge density fetched for task_id {task_id}.") chgcar = chgcar[0]["data"] # type: ignore if inc_task_doc: task_doc = self.materials.tasks.search(task_ids=task_id)[0] return chgcar, task_doc return chgcar def get_charge_density_from_material_id( self, material_id: str, inc_task_doc: bool = False ) -> Chgcar | tuple[Chgcar, TaskDoc | dict] | None: """Get charge density data for a given Materials Project ID. Arguments: material_id (str): Material Project ID inc_task_doc (bool): Whether to include the task document in the returned data. Returns: (Chgcar, (Chgcar, TaskDoc | dict), None): Pymatgen Chgcar object, or tuple with object and TaskDoc """ # TODO: really we want a recommended task_id for charge densities here # this could potentially introduce an ambiguity task_ids = self.get_task_ids_associated_with_material_id( material_id, calc_types=[CalcType.GGA_Static, CalcType.GGA_U_Static] ) if not task_ids: return None results: list[TaskDoc] = self.materials.tasks.search( task_ids=task_ids, fields=["last_updated", "task_id"] ) # type: ignore if len(results) == 0: return None latest_doc = max( # type: ignore results, key=lambda x: ( x.last_updated # type: ignore if self.use_document_model else x["last_updated"] ), # type: ignore ) task_id = ( latest_doc.task_id if self.use_document_model else latest_doc["task_id"] ) return self.get_charge_density_from_task_id(task_id, inc_task_doc) def get_download_info(self, material_ids, calc_types=None, file_patterns=None): """Get a list of URLs to retrieve raw VASP output files from the NoMaD repository Args: material_ids (list): list of material identifiers (mp-id's) task_types (list): list of task types to include in download (see CalcType Enum class) file_patterns (list): list of wildcard file names to include for each task Returns: a tuple of 1) a dictionary mapping material_ids to task_ids and calc_types, and 2) a list of URLs to download zip archives from NoMaD repository. Each zip archive will contain a manifest.json with metadata info, e.g. the task/external_ids that belong to a directory. """ # task_id's correspond to NoMaD external_id's calc_types = ( [t.value for t in calc_types if isinstance(t, CalcType)] if calc_types else [] ) meta = {} for doc in self.materials.search( # type: ignore task_ids=material_ids, fields=["calc_types", "deprecated_tasks", "material_id"], ): doc_dict: dict = doc.model_dump() if self.use_document_model else doc # type: ignore for task_id, calc_type in doc_dict["calc_types"].items(): if calc_types and calc_type not in calc_types: continue mp_id = doc_dict["material_id"] if meta.get(mp_id) is None: meta[mp_id] = [{"task_id": task_id, "calc_type": calc_type}] else: meta[mp_id].append({"task_id": task_id, "calc_type": calc_type}) if not meta: raise ValueError(f"No tasks found for material id {material_ids}.") # return a list of URLs for NoMaD Downloads containing the list of files # for every external_id in `task_ids` # For reference, please visit https://nomad-lab.eu/prod/rae/api/ # check if these task ids exist on NOMAD prefix = "https://nomad-lab.eu/prod/rae/api/repo/?" if file_patterns is not None: for file_pattern in file_patterns: prefix += f"file_pattern={file_pattern}&" prefix += "external_id=" task_ids = [t["task_id"] for tl in meta.values() for t in tl] nomad_exist_task_ids = self._check_get_download_info_url_by_task_id( prefix=prefix, task_ids=task_ids ) if len(nomad_exist_task_ids) != len(task_ids): self._print_help_message( nomad_exist_task_ids, task_ids, file_patterns, calc_types ) # generate download links for those that exist prefix = "https://nomad-lab.eu/prod/rae/api/raw/query?" if file_patterns is not None: for file_pattern in file_patterns: prefix += f"file_pattern={file_pattern}&" prefix += "external_id=" urls = [prefix + tids for tids in nomad_exist_task_ids] return meta, urls def _check_get_download_info_url_by_task_id(self, prefix, task_ids) -> list[str]: nomad_exist_task_ids: list[str] = [] prefix = prefix.replace("/raw/query", "/repo/") for task_id in task_ids: url = prefix + task_id if self._check_nomad_exist(url): nomad_exist_task_ids.append(task_id) return nomad_exist_task_ids @staticmethod def _check_nomad_exist(url) -> bool: response = get(url=url) if response.status_code != 200: return False content = loads(response.text) if content["pagination"]["total"] == 0: return False return True @staticmethod def _print_help_message(nomad_exist_task_ids, task_ids, file_patterns, calc_types): non_exist_ids = set(task_ids) - set(nomad_exist_task_ids) warnings.warn( f"For file patterns [{file_patterns}] and calc_types [{calc_types}], \n" f"the following ids are not found on NOMAD [{list(non_exist_ids)}]. \n" f"If you need to upload them, please contact Patrick Huck at phuck@lbl.gov" ) def query(*args, **kwargs): """The MPRester().query method has been replaced with the MPRester().summary.search method. Note this method also no longer supports direct MongoDB-type queries. For more information, please see the new documentation. """ raise NotImplementedError( """ The MPRester().query method has been replaced with the MPRester().summary.search method. Note this method also no longer supports direct MongoDB-type queries. For more information, please see the new documentation. """ ) def get_cohesive_energy( self, material_ids: list[MPID | str], normalization: Literal["atom", "formula_unit"] = "atom", ) -> float | dict[str, float]: """Obtain the cohesive energy of the structure(s) corresponding to multiple MPIDs. Args: material_ids ([MPID | str]) : List of MPIDs to compute cohesive energies. normalization (str = "atom" (default) or "formula_unit") : Whether to normalize the cohesive energy by the number of atoms (default) or by the number of formula units. Note that the current default is inconsistent with the legacy API. Returns: (dict[str,float]) : The cohesive energies (in eV/atom or eV/formula unit) for each material, indexed by MPID. """ entry_preference = { k: i for i, k in enumerate(["GGA", "GGA_U", "SCAN", "R2SCAN"]) } run_type_to_dfa = {"GGA": "PBE", "GGA_U": "PBE", "R2SCAN": "r2SCAN"} energies = {mp_id: {} for mp_id in material_ids} entries = self.get_entries( material_ids, compatible_only=False, inc_structure=True, property_data=None, conventional_unit_cell=False, ) for entry in entries: # Ensure that this works with monty_decode = False and True if not self.monty_decode: entry["uncorrected_energy_per_atom"] = entry["energy"] / sum( entry["composition"].values() ) else: entry = { "data": entry.data, "uncorrected_energy_per_atom": entry.uncorrected_energy_per_atom, "composition": entry.composition, } mp_id = entry["data"]["material_id"] if (run_type := entry["data"]["run_type"]) not in energies[mp_id]: energies[mp_id][run_type] = { "total_energy_per_atom": float("inf"), "composition": None, } # Obtain lowest total energy/atom within a given run type if ( entry["uncorrected_energy_per_atom"] < energies[mp_id][run_type]["total_energy_per_atom"] ): energies[mp_id][run_type] = { "total_energy_per_atom": entry["uncorrected_energy_per_atom"], "composition": entry["composition"], } atomic_energies = self.get_atom_reference_data() e_coh_per_atom = {} for mp_id, entries in energies.items(): if not entries: e_coh_per_atom[str(mp_id)] = None continue # take entry from most reliable and available functional prefered_func = sorted(list(entries), key=lambda k: entry_preference[k])[-1] e_coh_per_atom[str(mp_id)] = self._get_cohesive_energy( entries[prefered_func]["composition"], entries[prefered_func]["total_energy_per_atom"], atomic_energies[run_type_to_dfa.get(prefered_func, prefered_func)], normalization=normalization, ) return e_coh_per_atom @lru_cache def get_atom_reference_data( self, funcs: tuple[str] = ( "PBE", "SCAN", "r2SCAN", ), ) -> dict[str, dict[str, float]]: """Retrieve energies of isolated neutral atoms from MPContribs. Args: funcs ([str] or None) : list of functionals to retrieve data for. Defaults to all available functionals ("PBE", "SCAN", "r2SCAN") when set to None. Returns: (dict[str, dict[str, float]]) : dict containing isolated atom energies, indexed first by the functionals in funcs, and second by the atom. """ _atomic_energies = self.contribs.query_contributions( query={"project": "isolated_atom_energies"}, fields=["formula", *[f"data.{dfa}.energy" for dfa in funcs]], ).get("data") return { dfa: { entry["formula"]: entry["data"][dfa]["energy"]["value"] for entry in _atomic_energies } for dfa in funcs } @staticmethod def _get_cohesive_energy( composition: Composition | dict, energy_per_atom: float, atomic_energies: dict[str, float], normalization: Literal["atom", "formula_unit"] = "atom", ) -> float: """Obtain the cohesive energy of a given composition and energy. Args: composition (Composition or dict) : the composition of the structure. energy_per_atom (float) : the energy per atom of the structure. atomic_energies (dict[str,float]) : a dict containing reference total energies of neutral atoms. normalization (str = "atom" (default) or "formula_unit") : Whether to normalize the cohesive energy by the number of atoms (default) or by the number of formula units. Returns: (float) : the cohesive energy per atom. """ comp = Composition(composition).remove_charges() atomic_energy = sum( coeff * atomic_energies[str(element)] for element, coeff in comp.items() ) natom = sum(comp.values()) if normalization == "atom": return energy_per_atom - atomic_energy / natom elif normalization == "formula_unit": num_form_unit = comp.get_reduced_composition_and_factor()[1] return (energy_per_atom * natom - atomic_energy) / num_form_unit api-0.45.3/mp_api/client/routes/000077500000000000000000000000001475770546700164465ustar00rootroot00000000000000api-0.45.3/mp_api/client/routes/__init__.py000066400000000000000000000002501475770546700205540ustar00rootroot00000000000000from __future__ import annotations from ._general_store import GeneralStoreRester from ._messages import MessagesRester from ._user_settings import UserSettingsRester api-0.45.3/mp_api/client/routes/_general_store.py000066400000000000000000000022731475770546700220140ustar00rootroot00000000000000from __future__ import annotations from emmet.core._general_store import GeneralStoreDoc from mp_api.client.core import BaseRester class GeneralStoreRester(BaseRester[GeneralStoreDoc]): # pragma: no cover suffix = "_general_store" document_model = GeneralStoreDoc # type: ignore primary_key = "submission_id" monty_decode = False use_document_model = False def add_item(self, kind: str, markdown: str, meta: dict): # pragma: no cover """Set general store data. Args: kind: Data type description markdown: Markdown data meta: Metadata Returns: Dictionary with written data and submission id. Raises: MPRestError. """ return self._post_resource( body=meta, params={"kind": kind, "markdown": markdown} ).get("data") def get_items(self, kind): # pragma: no cover """Get general store data. Args: kind: Data type description Returns: List of dictionaries with kind, markdown, metadata, and submission_id. Raises: MPRestError. """ return self.search(kind=kind) api-0.45.3/mp_api/client/routes/_messages.py000066400000000000000000000045411475770546700207720ustar00rootroot00000000000000from __future__ import annotations from datetime import datetime from emmet.core._messages import MessagesDoc, MessageType from mp_api.client.core import BaseRester class MessagesRester(BaseRester[MessagesDoc]): # pragma: no cover suffix = "_messages" document_model = MessagesDoc # type: ignore primary_key = "title" monty_decode = False use_document_model = False def set_message( self, title: str, body: str, type: MessageType = MessageType.generic, authors: list[str] = None, ): # pragma: no cover """Set user settings. Args: title: Message title body: Message text body type: Message type authors: Message authors Returns: Dictionary with updated message data Raises: MPRestError. """ d = {"title": title, "body": body, "type": type.value, "authors": authors or []} return self._post_resource(body=d).get("data") def get_messages( self, last_updated: datetime, sort_fields: list[str] | None = None, num_chunks: int | None = None, chunk_size: int = 1000, all_fields: bool = True, fields: list[str] | None = None, ): # pragma: no cover """Get user settings. Args: last_updated (datetime): Datetime to use to query for newer messages sort_fields (List[str]): Fields used to sort results. Prefix with '-' to sort in descending order. num_chunks (int): Maximum number of chunks of data to yield. None will yield all possible. chunk_size (int): Number of data entries per chunk. all_fields (bool): Whether to return all fields in the document. Defaults to True. fields (List[str]): List of fields to project. Returns: Dictionary with messages data Raises: MPRestError. """ query_params = {} if sort_fields: query_params.update( {"_sort_fields": ",".join([s.strip() for s in sort_fields])} ) return self._search( last_updated=last_updated, num_chunks=num_chunks, chunk_size=chunk_size, all_fields=all_fields, fields=fields, **query_params, ) api-0.45.3/mp_api/client/routes/_user_settings.py000066400000000000000000000055051475770546700220620ustar00rootroot00000000000000from __future__ import annotations from emmet.core._user_settings import UserSettingsDoc from mp_api.client.core import BaseRester class UserSettingsRester(BaseRester[UserSettingsDoc]): # pragma: no cover suffix = "_user_settings" document_model = UserSettingsDoc # type: ignore primary_key = "consumer_id" monty_decode = False use_document_model = False def create_user_settings(self, consumer_id, settings): """Create user settings. Args: consumer_id: Consumer ID for the user settings: Dictionary with user settings that use UserSettingsDoc schema Returns: Dictionary with consumer_id and write status. """ return self._post_resource( body=settings, params={"consumer_id": consumer_id} ).get("data") def patch_user_settings(self, consumer_id, settings): # pragma: no cover """Patch user settings. Args: consumer_id: Consumer ID for the user settings: Dictionary with user settings Returns: Dictionary with consumer_id and write status. Raises: MPRestError. """ body = dict() for key in settings: if key not in [ "institution", "sector", "job_role", "is_email_subscribed", "agreed_terms", ]: raise ValueError( f"Invalid setting key {key}. Must be one of" "institution, sector, job_role, is_email_subscribed, agreed_terms" ) body[f"settings.{key}"] = settings[key] return self._patch_resource(body=body, params={"consumer_id": consumer_id}).get( "data" ) def patch_user_time_settings(self, consumer_id, time): # pragma: no cover """Set user settings last_read_message field. Args: consumer_id: Consumer ID for the user time: utc datetime object for when the user last see messages Returns: Dictionary with consumer_id and write status. Raises: MPRestError. """ return self._patch_resource( body={"settings.message_last_read": time.isoformat()}, params={"consumer_id": consumer_id}, ).get("data") def get_user_settings(self, consumer_id, fields): # pragma: no cover """Get user settings. Args: consumer_id: Consumer ID for the user fields: List of fields to project Returns: Dictionary with consumer_id and settings. Raises: MPRestError. """ return self._query_resource( suburl=f"{consumer_id}", fields=fields, num_chunks=1, chunk_size=1 ).get("data") api-0.45.3/mp_api/client/routes/materials/000077500000000000000000000000001475770546700204275ustar00rootroot00000000000000api-0.45.3/mp_api/client/routes/materials/__init__.py000066400000000000000000000023311475770546700225370ustar00rootroot00000000000000from __future__ import annotations from .absorption import AbsorptionRester from .bonds import BondsRester from .chemenv import ChemenvRester from .dielectric import DielectricRester from .doi import DOIRester from .elasticity import ElasticityRester from .electrodes import ElectrodeRester from .electronic_structure import ( BandStructureRester, DosRester, ElectronicStructureRester, ) from .eos import EOSRester from .grain_boundaries import GrainBoundaryRester from .magnetism import MagnetismRester from .oxidation_states import OxidationStatesRester from .phonon import PhononRester from .piezo import PiezoRester from .provenance import ProvenanceRester from .robocrys import RobocrysRester from .similarity import SimilarityRester from .substrates import SubstratesRester from .summary import SummaryRester from .surface_properties import SurfacePropertiesRester from .synthesis import SynthesisRester from .tasks import TaskRester from .thermo import ThermoRester from .xas import XASRester try: from .alloys import AlloysRester except ImportError: AlloysRester = None # type: ignore try: from .charge_density import ChargeDensityRester except ImportError: ChargeDensityRester = None # type: ignore api-0.45.3/mp_api/client/routes/materials/absorption.py000066400000000000000000000061441475770546700231660ustar00rootroot00000000000000from __future__ import annotations from collections import defaultdict from emmet.core.absorption import AbsorptionDoc from mp_api.client.core import BaseRester from mp_api.client.core.utils import validate_ids class AbsorptionRester(BaseRester[AbsorptionDoc]): suffix = "materials/absorption" document_model = AbsorptionDoc # type: ignore primary_key = "material_id" def search( self, material_ids: str | list[str] | None = None, chemsys: str | list[str] | None = None, elements: list[str] | None = None, exclude_elements: list[str] | None = None, formula: list[str] | None = None, num_chunks: int | None = None, chunk_size: int = 1000, all_fields: bool = True, fields: list[str] | None = None, ) -> list[AbsorptionDoc] | list[dict]: """Query for optical absorption spectra data. Arguments: material_ids (str, List[str]): Search for optical absorption data associated with the specified Material IDs chemsys (str, List[str]): A chemical system or list of chemical systems (e.g., Li-Fe-O, Si-*, [Si-O, Li-Fe-P]). elements (List[str]): A list of elements. exclude_elements (List[str]): A list of elements to exclude. formula (str, List[str]): A formula including anonymized formula or wild cards (e.g., Fe2O3, ABO3, Si*). A list of chemical formulas can also be passed (e.g., [Fe2O3, ABO3]). num_chunks (int): Maximum number of chunks of data to yield. None will yield all possible. chunk_size (int): Number of data entries per chunk. all_fields (bool): Whether to return all fields in the document. Defaults to True. fields (List[str]): List of fields in AbsorptionDoc to return data for. Returns: ([AbsorptionDoc], [dict]) List of optical absorption documents or dictionaries. """ query_params = defaultdict(dict) # type: dict if formula: if isinstance(formula, str): formula = [formula] query_params.update({"formula": ",".join(formula)}) if chemsys: if isinstance(chemsys, str): chemsys = [chemsys] query_params.update({"chemsys": ",".join(chemsys)}) if elements: query_params.update({"elements": ",".join(elements)}) if exclude_elements: query_params.update({"exclude_elements": ",".join(exclude_elements)}) if material_ids: if isinstance(material_ids, str): material_ids = [material_ids] query_params.update({"material_ids": ",".join(validate_ids(material_ids))}) query_params = { entry: query_params[entry] for entry in query_params if query_params[entry] is not None } return super()._search( formulae=formula, num_chunks=num_chunks, chunk_size=chunk_size, all_fields=all_fields, fields=fields, **query_params, ) api-0.45.3/mp_api/client/routes/materials/alloys.py000066400000000000000000000043501475770546700223060ustar00rootroot00000000000000from __future__ import annotations from collections import defaultdict from emmet.core.alloys import AlloyPairDoc from mp_api.client.core import BaseRester from mp_api.client.core.utils import validate_ids class AlloysRester(BaseRester[AlloyPairDoc]): suffix = "materials/alloys" document_model = AlloyPairDoc # type: ignore primary_key = "pair_id" def search( self, material_ids: str | list[str] | None = None, formulae: list[str] | None = None, num_chunks: int | None = None, chunk_size: int = 1000, all_fields: bool = True, fields: list[str] | None = None, ) -> list[AlloyPairDoc] | list[dict]: """Query for hypothetical alloys formed between two commensurate crystal structures, following the methodology in https://doi.org/10.48550/arXiv.2206.10715. Please cite the relevant publication if data provided by this endpoint is useful. Arguments: material_ids (str, List[str]): Search for alloys containing the specified Material IDs formulae (List[str]): Search for alloys containing the specified formulae num_chunks (int): Maximum number of chunks of data to yield. None will yield all possible. chunk_size (int): Number of data entries per chunk. all_fields (bool): Whether to return all fields in the document. Defaults to True. fields (List[str]): List of fields in AlloyPairDoc to return data for. Returns: ([AlloyPairDoc], [dict]) List of alloy pair documents or dictionaries. """ query_params = defaultdict(dict) # type: dict query_params = { entry: query_params[entry] for entry in query_params if query_params[entry] is not None } if material_ids: if isinstance(material_ids, str): material_ids = [material_ids] query_params.update({"material_ids": ",".join(validate_ids(material_ids))}) return super()._search( formulae=formulae, num_chunks=num_chunks, chunk_size=chunk_size, all_fields=all_fields, fields=fields, **query_params, ) api-0.45.3/mp_api/client/routes/materials/bonds.py000066400000000000000000000076721475770546700221220ustar00rootroot00000000000000from __future__ import annotations from collections import defaultdict from emmet.core.bonds import BondingDoc from mp_api.client.core import BaseRester from mp_api.client.core.utils import validate_ids class BondsRester(BaseRester[BondingDoc]): suffix = "materials/bonds" document_model = BondingDoc # type: ignore primary_key = "material_id" def search( self, material_ids: str | list[str] | None = None, coordination_envs: list[str] | None = None, coordination_envs_anonymous: list[str] | None = None, max_bond_length: tuple[float, float] | None = None, mean_bond_length: tuple[float, float] | None = None, min_bond_length: tuple[float, float] | None = None, num_chunks: int | None = None, chunk_size: int = 1000, all_fields: bool = True, fields: list[str] | None = None, ) -> list[BondingDoc] | list[dict]: """Query bonding docs using a variety of search criteria. Arguments: material_ids (str, List[str]): Search for bonding data for the specified Material IDs coordination_envs (List[str]): List of coordination environments to consider (e.g. ['Mo-S(6)', 'S-Mo(3)']). coordination_envs_anonymous (List[str]): List of anonymous coordination environments to consider (e.g. ['A-B(6)', 'A-B(3)']). max_bond_length (Tuple[float,float]): Minimum and maximum value for the maximum bond length in the structure to consider. mean_bond_length (Tuple[float,float]): Minimum and maximum value for the mean bond length in the structure to consider. min_bond_length (Tuple[float,float]): Minimum and maximum value for the minimum bond length in the structure to consider. num_chunks (int): Maximum number of chunks of data to yield. None will yield all possible. chunk_size (int): Number of data entries per chunk. all_fields (bool): Whether to return all fields in the document. Defaults to True. fields (List[str]): List of fields in DielectricDoc to return data for. Default is material_id and last_updated if all_fields is False. Returns: ([BondingDoc], [dict]) List of bonding documents or dictionaries. """ query_params = defaultdict(dict) # type: dict if material_ids: if isinstance(material_ids, str): material_ids = [material_ids] query_params.update({"material_ids": ",".join(validate_ids(material_ids))}) if max_bond_length: query_params.update( { "max_bond_length_min": max_bond_length[0], "max_bond_length_max": max_bond_length[1], } ) if min_bond_length: query_params.update( { "min_bond_length_min": min_bond_length[0], "min_bond_length_max": min_bond_length[1], } ) if mean_bond_length: query_params.update( { "mean_bond_length_min": mean_bond_length[0], "mean_bond_length_max": mean_bond_length[1], } ) if coordination_envs is not None: query_params.update({"coordination_envs": ",".join(coordination_envs)}) if coordination_envs_anonymous is not None: query_params.update( {"coordination_envs_anonymous": ",".join(coordination_envs_anonymous)} ) query_params = { entry: query_params[entry] for entry in query_params if query_params[entry] is not None } return super()._search( num_chunks=num_chunks, chunk_size=chunk_size, all_fields=all_fields, fields=fields, **query_params, ) api-0.45.3/mp_api/client/routes/materials/chemenv.py000066400000000000000000000143331475770546700224320ustar00rootroot00000000000000from __future__ import annotations from collections import defaultdict from emmet.core.chemenv import ( COORDINATION_GEOMETRIES, COORDINATION_GEOMETRIES_IUCR, COORDINATION_GEOMETRIES_IUPAC, COORDINATION_GEOMETRIES_NAMES, ChemEnvDoc, ) from mp_api.client.core import BaseRester from mp_api.client.core.utils import validate_ids class ChemenvRester(BaseRester[ChemEnvDoc]): suffix = "materials/chemenv" document_model = ChemEnvDoc # type: ignore primary_key = "material_id" def search( self, material_ids: str | list[str] | None = None, chemenv_iucr: COORDINATION_GEOMETRIES_IUCR | list[COORDINATION_GEOMETRIES_IUCR] | None = None, chemenv_iupac: COORDINATION_GEOMETRIES_IUPAC | list[COORDINATION_GEOMETRIES_IUPAC] | None = None, chemenv_name: COORDINATION_GEOMETRIES_NAMES | list[COORDINATION_GEOMETRIES_NAMES] | None = None, chemenv_symbol: COORDINATION_GEOMETRIES | list[COORDINATION_GEOMETRIES] | None = None, species: str | list[str] | None = None, elements: str | list[str] | None = None, exclude_elements: list[str] | None = None, csm: tuple[float, float] | None = None, density: tuple[float, float] | None = None, num_elements: tuple[int, int] | None = None, num_sites: tuple[int, int] | None = None, volume: tuple[float, float] | None = None, num_chunks: int | None = None, chunk_size: int = 1000, all_fields: bool = True, fields: list[str] | None = None, ) -> list[ChemEnvDoc] | list[dict]: """Query for chemical environment data. Arguments: material_ids (str, List[str]): Search forchemical environment associated with the specified Material IDs. chemenv_iucr (COORDINATION_GEOMETRIES_IUCR, List[COORDINATION_GEOMETRIES_IUCR]): Unique cationic species in IUCR format, e.g. "[3n]". chemenv_iupac (COORDINATION_GEOMETRIES_IUPAC, List[COORDINATION_GEOMETRIES_IUPAC]): Unique cationic species in IUPAC format, e.g., "T-4". chemenv_name (COORDINATION_GEOMETRIES_NAMES, List[COORDINATION_GEOMETRIES_NAMES]): Coordination environment descriptions in text form for unique cationic species, e.g. "Tetrahedron". chemenv_symbol (COORDINATION_GEOMETRIES, List[COORDINATION_GEOMETRIES]): Coordination environment descriptions as used in ChemEnv package for unique cationic species, e.g. "T:4". species (str, List[str]): Cationic species in the crystal structure, e.g. "Ti4+". elements (str, List[str]): Element names in the crystal structure, e.g., "Ti". exclude_elements (List[str]): A list of elements to exclude. csm (Tuple[float,float]): Minimum and maximum value of continuous symmetry measure to consider. density (Tuple[float,float]): Minimum and maximum density to consider. num_elements (Tuple[int,int]): Minimum and maximum number of elements to consider. num_sites (Tuple[int,int]): Minimum and maximum number of sites to consider. volume (Tuple[float,float]): Minimum and maximum volume to consider. num_chunks (int): Maximum number of chunks of data to yield. None will yield all possible. chunk_size (int): Number of data entries per chunk. all_fields (bool): Whether to return all fields in the document. Defaults to True. fields (List[str]): List of fields in ChemEnvDoc to return data for. Returns: ([ChemEnvDoc], [dict]) List of chemenv documents or dictionaries. """ query_params = defaultdict(dict) # type: dict if csm: query_params.update({"csm_min": csm[0], "csm_max": csm[1]}) if volume: query_params.update({"volume_min": volume[0], "volume_max": volume[1]}) if density: query_params.update({"density_min": density[0], "density_max": density[1]}) if num_sites: query_params.update( {"nsites_min": num_sites[0], "nsites_max": num_sites[1]} ) if elements: query_params.update({"elements": ",".join(elements)}) if exclude_elements: query_params.update({"exclude_elements": ",".join(exclude_elements)}) if num_elements: if isinstance(num_elements, int): num_elements = (num_elements, num_elements) query_params.update( {"nelements_min": num_elements[0], "nelements_max": num_elements[1]} ) if material_ids: if isinstance(material_ids, str): material_ids = [material_ids] query_params.update({"material_ids": ",".join(validate_ids(material_ids))}) chemenv_literals = { "chemenv_iucr": (chemenv_iucr, COORDINATION_GEOMETRIES_IUCR), "chemenv_iupac": (chemenv_iupac, COORDINATION_GEOMETRIES_IUPAC), "chemenv_name": (chemenv_name, COORDINATION_GEOMETRIES_NAMES), "chemenv_symbol": (chemenv_symbol, COORDINATION_GEOMETRIES), } for chemenv_var_name, (chemenv_var, literals) in chemenv_literals.items(): if chemenv_var: t_types = {t if isinstance(t, str) else t.value for t in chemenv_var} valid_types = {*map(str, literals.__args__)} if invalid_types := t_types - valid_types: raise ValueError( f"Invalid type(s) passed for {chemenv_var_name}: {invalid_types}, valid types are: {valid_types}" ) query_params.update({chemenv_var_name: ",".join(t_types)}) if species: if isinstance(species, str): species = [species] query_params.update({"species": ",".join(species)}) query_params = { entry: query_params[entry] for entry in query_params if query_params[entry] is not None } return super()._search( num_chunks=num_chunks, chunk_size=chunk_size, all_fields=all_fields, fields=fields, **query_params, ) api-0.45.3/mp_api/client/routes/materials/dielectric.py000066400000000000000000000061441475770546700231150ustar00rootroot00000000000000from __future__ import annotations from collections import defaultdict from emmet.core.polar import DielectricDoc from mp_api.client.core import BaseRester from mp_api.client.core.utils import validate_ids class DielectricRester(BaseRester[DielectricDoc]): suffix = "materials/dielectric" document_model = DielectricDoc # type: ignore primary_key = "material_id" def search( self, material_ids: str | list[str] | None = None, e_total: tuple[float, float] | None = None, e_ionic: tuple[float, float] | None = None, e_electronic: tuple[float, float] | None = None, n: tuple[float, float] | None = None, num_chunks: int | None = None, chunk_size: int = 1000, all_fields: bool = True, fields: list[str] | None = None, ) -> list[DielectricDoc] | list[dict]: """Query dielectric docs using a variety of search criteria. Arguments: material_ids (str, List[str]): A single Material ID string or list of strings (e.g., mp-149, [mp-149, mp-13]). e_total (Tuple[float,float]): Minimum and maximum total dielectric constant to consider. e_ionic (Tuple[float,float]): Minimum and maximum ionic dielectric constant to consider. e_electronic (Tuple[float,float]): Minimum and maximum electronic dielectric constant to consider. n (Tuple[float,float]): Minimum and maximum refractive index to consider. num_chunks (int): Maximum number of chunks of data to yield. None will yield all possible. chunk_size (int): Number of data entries per chunk. all_fields (bool): Whether to return all fields in the document. Defaults to True. fields (List[str]): List of fields in DielectricDoc to return data for. Default is material_id and last_updated if all_fields is False. Returns: ([DielectricDoc], [dict]) List of dielectric documents or dictionaries. """ query_params = defaultdict(dict) # type: dict if material_ids: if isinstance(material_ids, str): material_ids = [material_ids] query_params.update({"material_ids": ",".join(validate_ids(material_ids))}) if e_total: query_params.update({"e_total_min": e_total[0], "e_total_max": e_total[1]}) if e_ionic: query_params.update({"e_ionic_min": e_ionic[0], "e_ionic_max": e_ionic[1]}) if e_electronic: query_params.update( { "e_electronic_min": e_electronic[0], "e_electronic_max": e_electronic[1], } ) if n: query_params.update({"n_min": n[0], "n_max": n[1]}) query_params = { entry: query_params[entry] for entry in query_params if query_params[entry] is not None } return super()._search( num_chunks=num_chunks, chunk_size=chunk_size, all_fields=all_fields, fields=fields, **query_params, ) api-0.45.3/mp_api/client/routes/materials/doi.py000066400000000000000000000034401475770546700215550ustar00rootroot00000000000000from __future__ import annotations from collections import defaultdict from emmet.core.dois import DOIDoc from mp_api.client.core import BaseRester from mp_api.client.core.utils import validate_ids class DOIRester(BaseRester[DOIDoc]): suffix = "doi" document_model = DOIDoc # type: ignore primary_key = "material_id" def search( self, material_ids: str | list[str] | None = None, num_chunks: int | None = None, chunk_size: int = 1000, all_fields: bool = True, fields: list[str] | None = None, ) -> list[DOIDoc] | list[dict]: """Query for DOI data. Arguments: material_ids (str, List[str]): Search for DOI data associated with the specified Material IDs num_chunks (int): Maximum number of chunks of data to yield. None will yield all possible. chunk_size (int): Number of data entries per chunk. all_fields (bool): Whether to return all fields in the document. Defaults to True. fields (List[str]): List of fields in DOIDoc to return data for. Returns: ([DOIDoc], [dict]) List of DOIDoc documents or dictionaries. """ query_params = defaultdict(dict) # type: dict if material_ids: if isinstance(material_ids, str): material_ids = [material_ids] query_params.update({"material_ids": ",".join(validate_ids(material_ids))}) query_params = { entry: query_params[entry] for entry in query_params if query_params[entry] is not None } return super()._search( num_chunks=num_chunks, chunk_size=chunk_size, all_fields=all_fields, fields=fields, **query_params, ) api-0.45.3/mp_api/client/routes/materials/elasticity.py000066400000000000000000000111101475770546700231450ustar00rootroot00000000000000from __future__ import annotations from collections import defaultdict from emmet.core.elasticity import ElasticityDoc from mp_api.client.core import BaseRester from mp_api.client.core.utils import validate_ids class ElasticityRester(BaseRester[ElasticityDoc]): suffix = "materials/elasticity" document_model = ElasticityDoc # type: ignore primary_key = "material_id" def search( self, material_ids: str | list[str] | None = None, elastic_anisotropy: tuple[float, float] | None = None, g_voigt: tuple[float, float] | None = None, g_reuss: tuple[float, float] | None = None, g_vrh: tuple[float, float] | None = None, k_voigt: tuple[float, float] | None = None, k_reuss: tuple[float, float] | None = None, k_vrh: tuple[float, float] | None = None, poisson_ratio: tuple[float, float] | None = None, num_chunks: int | None = None, chunk_size: int = 1000, all_fields: bool = True, fields: list[str] | None = None, ) -> list[ElasticityDoc] | list[dict]: """Query elasticity docs using a variety of search criteria. Arguments: material_ids (str, List[str]): A single Material ID string or list of strings (e.g., mp-149, [mp-149, mp-13]). elastic_anisotropy (Tuple[float,float]): Minimum and maximum value to consider for the elastic anisotropy. g_voigt (Tuple[float,float]): Minimum and maximum value in GPa to consider for the Voigt average of the shear modulus. g_reuss (Tuple[float,float]): Minimum and maximum value in GPa to consider for the Reuss average of the shear modulus. g_vrh (Tuple[float,float]): Minimum and maximum value in GPa to consider for the Voigt-Reuss-Hill average of the shear modulus. k_voigt (Tuple[float,float]): Minimum and maximum value in GPa to consider for the Voigt average of the bulk modulus. k_reuss (Tuple[float,float]): Minimum and maximum value in GPa to consider for the Reuss average of the bulk modulus. k_vrh (Tuple[float,float]): Minimum and maximum value in GPa to consider for the Voigt-Reuss-Hill average of the bulk modulus. poisson_ratio (Tuple[float,float]): Minimum and maximum value to consider for Poisson's ratio. num_chunks (int): Maximum number of chunks of data to yield. None will yield all possible. chunk_size (int): Number of data entries per chunk. all_fields (bool): Whether to return all fields in the document. Defaults to True. fields (List[str]): List of fields in ElasticityDoc to return data for. Default is material_id and prett-formula if all_fields is False. Returns: ([ElasticityDoc], [dict]) List of elasticity documents or dictionaries. """ query_params = defaultdict(dict) # type: dict if material_ids: if isinstance(material_ids, str): material_ids = [material_ids] query_params.update({"material_ids": ",".join(validate_ids(material_ids))}) if k_voigt: query_params.update({"k_voigt_min": k_voigt[0], "k_voigt_max": k_voigt[1]}) if k_reuss: query_params.update({"k_reuss_min": k_reuss[0], "k_reuss_max": k_reuss[1]}) if k_vrh: query_params.update({"k_vrh_min": k_vrh[0], "g_vrh_max": k_vrh[1]}) if g_voigt: query_params.update({"g_voigt_min": g_voigt[0], "g_voigt_max": g_voigt[1]}) if g_reuss: query_params.update({"g_reuss_min": g_reuss[0], "g_reuss_max": g_reuss[1]}) if g_vrh: query_params.update({"g_vrh_min": g_vrh[0], "g_vrh_max": g_vrh[1]}) if elastic_anisotropy: query_params.update( { "elastic_anisotropy_min": elastic_anisotropy[0], "elastic_anisotropy_max": elastic_anisotropy[1], } ) if poisson_ratio: query_params.update( {"poisson_min": poisson_ratio[0], "poisson_max": poisson_ratio[1]} ) query_params = { entry: query_params[entry] for entry in query_params if query_params[entry] is not None } return super()._search( num_chunks=num_chunks, chunk_size=chunk_size, all_fields=all_fields, fields=fields, **query_params, ) api-0.45.3/mp_api/client/routes/materials/electrodes.py000066400000000000000000000157661475770546700231510ustar00rootroot00000000000000from __future__ import annotations from collections import defaultdict from emmet.core.electrode import InsertionElectrodeDoc from pymatgen.core.periodic_table import Element from mp_api.client.core import BaseRester from mp_api.client.core.utils import validate_ids class ElectrodeRester(BaseRester[InsertionElectrodeDoc]): suffix = "materials/insertion_electrodes" document_model = InsertionElectrodeDoc # type: ignore primary_key = "battery_id" def search( # pragma: ignore self, material_ids: str | list[str] | None = None, battery_ids: str | list[str] | None = None, average_voltage: tuple[float, float] | None = None, capacity_grav: tuple[float, float] | None = None, capacity_vol: tuple[float, float] | None = None, elements: list[str] | None = None, energy_grav: tuple[float, float] | None = None, energy_vol: tuple[float, float] | None = None, exclude_elements: list[str] | None = None, formula: str | list[str] | None = None, fracA_charge: tuple[float, float] | None = None, fracA_discharge: tuple[float, float] | None = None, max_delta_volume: tuple[float, float] | None = None, max_voltage_step: tuple[float, float] | None = None, num_elements: tuple[int, int] | None = None, num_steps: tuple[int, int] | None = None, stability_charge: tuple[float, float] | None = None, stability_discharge: tuple[float, float] | None = None, working_ion: Element | None = None, num_chunks: int | None = None, chunk_size: int = 1000, all_fields: bool = True, fields: list[str] | None = None, ) -> list[InsertionElectrodeDoc] | list[dict]: """Query using a variety of search criteria. Arguments: material_ids (str, List[str]): A single Material ID string or list of strings (e.g., mp-149, [mp-149, mp-13]). battery_ids (str, List[str]): A single battery ID string or list of strings (e.g., mp-22526_Li, [mp-22526_Li, mp-22526_Ca]). average_voltage (Tuple[float,float]): Minimum and maximum value of the average voltage for a particular voltage step in V. capacity_grav (Tuple[float,float]): Minimum and maximum value of the gravimetric capacity in maH/g. capacity_vol (Tuple[float,float]): Minimum and maximum value of the volumetric capacity in maH/cc. elements (List[str]): A list of elements for the framework material. energy_grav (Tuple[float,float]): Minimum and maximum value of the gravimetric energy (specific energy) in Wh/kg. energy_vol (Tuple[float,float]): Minimum and maximum value of the volumetric energy (energy density) in Wh/l. exclude_elements (List[str]): A list of elements to exclude for the framework material. formula (str, List[str]): Chemical formula or list of chemical formulas of any of the materials associated with the electrode system. This includes materials partially along the charge-discharge path. fracA_charge (Tuple[float,float]): Minimum and maximum value of the atomic fraction of the working ion in the charged state. fracA_discharge (Tuple[float,float]): Minimum and maximum value of the atomic fraction of the working ion in the discharged state. max_delta_volume (Tuple[float,float]): Minimum and maximum value of the max volume change in percent for a particular voltage step. max_voltage_step (Tuple[float,float]): Minimum and maximum value of the maximum voltage for a particular voltage step in V. num_elements (Tuple[int,int]): Minimum and maximum number of elements to consider. num_steps (int): Number of distinct voltage steps from charged to discharged based on stable intermediates. stability_charge (Tuple[float,float]): Minimum and maximum value of the energy above hull of the charged material. stability_discharge (Tuple[float,float]): Minimum and maximum value of the energy above hull of the discharged material. working_ion (Element, List[Element]): Element or list of elements of the working ion. num_chunks (int): Maximum number of chunks of data to yield. None will yield all possible. chunk_size (int): Number of data entries per chunk. all_fields (bool): Whether to return all fields in the document. Defaults to True. fields (List[str]): List of fields in InsertionElectrodeDoc to return data for. Default is battery_id and last_updated if all_fields is False. Returns: ([InsertionElectrodeDoc], [dict]) List of insertion electrode documents or dictionaries. """ query_params = defaultdict(dict) # type: dict if material_ids: if isinstance(material_ids, str): material_ids = [material_ids] query_params.update({"material_ids": ",".join(validate_ids(material_ids))}) if battery_ids: if isinstance(battery_ids, str): battery_ids = [battery_ids] query_params.update({"battery_ids": ",".join(validate_ids(battery_ids))}) if working_ion: if isinstance(working_ion, (str, Element)): working_ion = [working_ion] # type: ignore query_params.update( {"working_ion": ",".join([str(ele) for ele in working_ion])} # type: ignore ) if formula: if isinstance(formula, str): formula = [formula] query_params.update({"formula": ",".join(formula)}) if elements: query_params.update({"elements": ",".join(elements)}) if num_elements: if isinstance(num_elements, int): num_elements = (num_elements, num_elements) query_params.update( {"nelements_min": num_elements[0], "nelements_max": num_elements[1]} ) if exclude_elements: query_params.update({"exclude_elements": ",".join(exclude_elements)}) for param, value in locals().items(): if ( param not in [ "__class__", "self", "working_ion", "query_params", "num_elements", ] and value ): if isinstance(value, tuple): query_params.update( {f"{param}_min": value[0], f"{param}_max": value[1]} ) else: query_params.update({param: value}) query_params = { entry: query_params[entry] for entry in query_params if query_params[entry] is not None } return super()._search(**query_params) api-0.45.3/mp_api/client/routes/materials/electronic_structure.py000066400000000000000000000436321475770546700252600ustar00rootroot00000000000000from __future__ import annotations import json import warnings from collections import defaultdict from emmet.core.electronic_structure import ( BSPathType, DOSProjectionType, ElectronicStructureDoc, ) from monty.json import MontyDecoder from pymatgen.analysis.magnetism.analyzer import Ordering from pymatgen.core.periodic_table import Element from pymatgen.electronic_structure.core import OrbitalType, Spin from mp_api.client.core import BaseRester, MPRestError from mp_api.client.core.utils import validate_ids class ElectronicStructureRester(BaseRester[ElectronicStructureDoc]): suffix = "materials/electronic_structure" document_model = ElectronicStructureDoc # type: ignore primary_key = "material_id" def search_electronic_structure_docs(self, *args, **kwargs): # pragma: no cover """Deprecated.""" warnings.warn( "MPRester.electronic_structure.search_electronic_structure_docs is deprecated. " "Please use MPRester.electronic_structure.search instead.", DeprecationWarning, stacklevel=2, ) return self.search(*args, **kwargs) def search( self, material_ids: str | list[str] | None = None, band_gap: tuple[float, float] | None = None, chemsys: str | list[str] | None = None, efermi: tuple[float, float] | None = None, elements: list[str] | None = None, exclude_elements: list[str] | None = None, formula: str | list[str] | None = None, is_gap_direct: bool | None = None, is_metal: bool | None = None, magnetic_ordering: Ordering | None = None, num_elements: tuple[int, int] | None = None, num_chunks: int | None = None, chunk_size: int = 1000, all_fields: bool = True, fields: list[str] | None = None, ): """Query electronic structure docs using a variety of search criteria. Arguments: material_ids (str, List[str]): A single Material ID string or list of strings (e.g., mp-149, [mp-149, mp-13]). band_gap (Tuple[float,float]): Minimum and maximum band gap in eV to consider. chemsys (str, List[str]): A chemical system or list of chemical systems (e.g., Li-Fe-O, Si-*, [Si-O, Li-Fe-P]). efermi (Tuple[float,float]): Minimum and maximum fermi energy in eV to consider. elements (List[str]): A list of elements. exclude_elements (List[str]): A list of elements to exclude. formula (str, List[str]): A formula including anonymized formula or wild cards (e.g., Fe2O3, ABO3, Si*). A list of chemical formulas can also be passed (e.g., [Fe2O3, ABO3]). is_gap_direct (bool): Whether the material has a direct band gap. is_metal (bool): Whether the material is considered a metal. magnetic_ordering (Ordering): Magnetic ordering of the material. num_elements (Tuple[int,int]): Minimum and maximum number of elements to consider. num_chunks (int): Maximum number of chunks of data to yield. None will yield all possible. chunk_size (int): Number of data entries per chunk. all_fields (bool): Whether to return all fields in the document. Defaults to True. fields (List[str]): List of fields in EOSDoc to return data for. Default is material_id and last_updated if all_fields is False. Returns: ([ElectronicStructureDoc]) List of electronic structure documents """ query_params = defaultdict(dict) # type: dict if material_ids: if isinstance(material_ids, str): material_ids = [material_ids] query_params.update({"material_ids": ",".join(validate_ids(material_ids))}) if formula: if isinstance(formula, str): formula = [formula] query_params.update({"formula": ",".join(formula)}) if chemsys: if isinstance(chemsys, str): chemsys = [chemsys] query_params.update({"chemsys": ",".join(chemsys)}) if elements: query_params.update({"elements": ",".join(elements)}) if exclude_elements: query_params.update({"exclude_elements": ",".join(exclude_elements)}) if band_gap: query_params.update( {"band_gap_min": band_gap[0], "band_gap_max": band_gap[1]} ) if efermi: query_params.update({"efermi_min": efermi[0], "efermi_max": efermi[1]}) if magnetic_ordering: query_params.update({"magnetic_ordering": magnetic_ordering.value}) if num_elements: if isinstance(num_elements, int): num_elements = (num_elements, num_elements) query_params.update( {"nelements_min": num_elements[0], "nelements_max": num_elements[1]} ) if is_gap_direct is not None: query_params.update({"is_gap_direct": is_gap_direct}) if is_metal is not None: query_params.update({"is_metal": is_metal}) query_params = { entry: query_params[entry] for entry in query_params if query_params[entry] is not None } return super()._search( num_chunks=num_chunks, chunk_size=chunk_size, all_fields=all_fields, fields=fields, **query_params, ) class BandStructureRester(BaseRester): suffix = "materials/electronic_structure/bandstructure" document_model = ElectronicStructureDoc # type: ignore def search_bandstructure_summary(self, *args, **kwargs): # pragma: no cover """Deprecated.""" warnings.warn( "MPRester.electronic_structure_bandstructure.search_bandstructure_summary is deprecated. " "Please use MPRester.electronic_structure_bandstructure.search instead.", DeprecationWarning, stacklevel=2, ) return self.search(*args, **kwargs) def search( self, band_gap: tuple[float, float] | None = None, efermi: tuple[float, float] | None = None, is_gap_direct: bool | None = None, is_metal: bool | None = None, magnetic_ordering: Ordering | None = None, path_type: BSPathType = BSPathType.setyawan_curtarolo, num_chunks: int | None = None, chunk_size: int = 1000, all_fields: bool = True, fields: list[str] | None = None, ): """Query band structure summary data in electronic structure docs using a variety of search criteria. Arguments: band_gap (Tuple[float,float]): Minimum and maximum band gap in eV to consider. efermi (Tuple[float,float]): Minimum and maximum fermi energy in eV to consider. is_gap_direct (bool): Whether the material has a direct band gap. is_metal (bool): Whether the material is considered a metal. magnetic_ordering (Ordering): Magnetic ordering of the material. path_type (BSPathType): k-path selection convention for the band structure. num_chunks (int): Maximum number of chunks of data to yield. None will yield all possible. chunk_size (int): Number of data entries per chunk. all_fields (bool): Whether to return all fields in the document. Defaults to True. fields (List[str]): List of fields in ElectronicStructureDoc to return data for. Default is material_id and last_updated if all_fields is False. Returns: ([ElectronicStructureDoc]) List of electronic structure documents """ query_params = defaultdict(dict) # type: dict query_params["path_type"] = path_type.value if band_gap: query_params.update( {"band_gap_min": band_gap[0], "band_gap_max": band_gap[1]} ) if efermi: query_params.update({"efermi_min": efermi[0], "efermi_max": efermi[1]}) if magnetic_ordering: query_params.update({"magnetic_ordering": magnetic_ordering.value}) if is_gap_direct is not None: query_params.update({"is_gap_direct": is_gap_direct}) if is_metal is not None: query_params.update({"is_metal": is_metal}) query_params = { entry: query_params[entry] for entry in query_params if query_params[entry] is not None } return super()._search( num_chunks=num_chunks, chunk_size=chunk_size, all_fields=all_fields, fields=fields, **query_params, ) def get_bandstructure_from_task_id(self, task_id: str): """Get the band structure pymatgen object associated with a given task ID. Arguments: task_id (str): Task ID for the band structure calculation Returns: bandstructure (BandStructure): BandStructure or BandStructureSymmLine object """ decoder = MontyDecoder().decode if self.monty_decode else json.loads result = self._query_open_data( bucket="materialsproject-parsed", key=f"bandstructures/{task_id}.json.gz", decoder=decoder, )[0] if result: return result[0]["data"] else: raise MPRestError("No object found") def get_bandstructure_from_material_id( self, material_id: str, path_type: BSPathType = BSPathType.setyawan_curtarolo, line_mode=True, ): """Get the band structure pymatgen object associated with a Materials Project ID. Arguments: material_id (str): Materials Project ID for a material path_type (BSPathType): k-point path selection convention line_mode (bool): Whether to return data for a line-mode calculation Returns: bandstructure (Union[BandStructure, BandStructureSymmLine]): BandStructure or BandStructureSymmLine object """ es_rester = ElectronicStructureRester( api_key=self.api_key, endpoint=self.base_endpoint, include_user_agent=self.include_user_agent, session=self.session, monty_decode=self.monty_decode, use_document_model=self.use_document_model, headers=self.headers, mute_progress_bars=self.mute_progress_bars, ) if line_mode: bs_doc = es_rester.search( material_ids=material_id, fields=["bandstructure"] ) if not bs_doc: raise MPRestError("No electronic structure data found.") bs_data = ( bs_doc[0].bandstructure # type: ignore if self.use_document_model else bs_doc[0]["bandstructure"] # type: ignore ) if bs_data is None: raise MPRestError( f"No {path_type.value} band structure data found for {material_id}" ) else: bs_data: dict = ( bs_data.model_dump() if self.use_document_model else bs_data # type: ignore ) if bs_data.get(path_type.value, None): bs_task_id = bs_data[path_type.value]["task_id"] else: raise MPRestError( f"No {path_type.value} band structure data found for {material_id}" ) else: bs_doc = es_rester.search(material_ids=material_id, fields=["dos"]) if not bs_doc: raise MPRestError("No electronic structure data found.") bs_data = ( bs_doc[0].dos # type: ignore if self.use_document_model else bs_doc[0]["dos"] # type: ignore ) if bs_data is None: raise MPRestError( f"No uniform band structure data found for {material_id}" ) else: bs_data: dict = ( bs_data.model_dump() if self.use_document_model else bs_data # type: ignore ) if bs_data.get("total", None): bs_task_id = bs_data["total"]["1"]["task_id"] else: raise MPRestError( f"No uniform band structure data found for {material_id}" ) bs_obj = self.get_bandstructure_from_task_id(bs_task_id) if bs_obj: return bs_obj else: raise MPRestError("No band structure object found.") class DosRester(BaseRester): suffix = "materials/electronic_structure/dos" document_model = ElectronicStructureDoc # type: ignore def search_dos_summary(self, *args, **kwargs): # pragma: no cover """Deprecated.""" warnings.warn( "MPRester.electronic_structure_dos.search_dos_summary is deprecated. " "Please use MPRester.electronic_structure_dos.search instead.", DeprecationWarning, stacklevel=2, ) return self.search(*args, **kwargs) def search( self, band_gap: tuple[float, float] | None = None, efermi: tuple[float, float] | None = None, element: Element | None = None, magnetic_ordering: Ordering | None = None, orbital: OrbitalType | None = None, projection_type: DOSProjectionType = DOSProjectionType.total, spin: Spin = Spin.up, num_chunks: int | None = None, chunk_size: int = 1000, all_fields: bool = True, fields: list[str] | None = None, ): """Query density of states summary data in electronic structure docs using a variety of search criteria. Arguments: band_gap (Tuple[float,float]): Minimum and maximum band gap in eV to consider. efermi (Tuple[float,float]): Minimum and maximum fermi energy in eV to consider. element (Element): Element for element-projected dos data. magnetic_ordering (Ordering): Magnetic ordering of the material. orbital (OrbitalType): Orbital for orbital-projected dos data. projection_type (DOSProjectionType): Projection type of dos data. Default is the total dos. spin (Spin): Spin channel of dos data. If non spin-polarized data is stored in Spin.up num_chunks (int): Maximum number of chunks of data to yield. None will yield all possible. chunk_size (int): Number of data entries per chunk. all_fields (bool): Whether to return all fields in the document. Defaults to True. fields (List[str]): List of fields in EOSDoc to return data for. Default is material_id and last_updated if all_fields is False. Returns: ([ElectronicStructureDoc]) List of electronic structure documents """ query_params = defaultdict(dict) # type: dict query_params["projection_type"] = projection_type.value query_params["spin"] = spin.value if element: query_params["element"] = element.value if orbital: query_params["orbital"] = orbital.value if band_gap: query_params.update( {"band_gap_min": band_gap[0], "band_gap_max": band_gap[1]} ) if efermi: query_params.update({"efermi_min": efermi[0], "efermi_max": efermi[1]}) if magnetic_ordering: query_params.update({"magnetic_ordering": magnetic_ordering.value}) query_params = { entry: query_params[entry] for entry in query_params if query_params[entry] is not None } return super()._search( num_chunks=num_chunks, chunk_size=chunk_size, all_fields=all_fields, fields=fields, **query_params, ) def get_dos_from_task_id(self, task_id: str): """Get the density of states pymatgen object associated with a given calculation ID. Arguments: task_id (str): Task ID for the density of states calculation Returns: bandstructure (CompleteDos): CompleteDos object """ decoder = MontyDecoder().decode if self.monty_decode else json.loads result = self._query_open_data( bucket="materialsproject-parsed", key=f"dos/{task_id}.json.gz", decoder=decoder, )[0] if result: return result[0]["data"] # type: ignore else: raise MPRestError("No object found") def get_dos_from_material_id(self, material_id: str): """Get the complete density of states pymatgen object associated with a Materials Project ID. Arguments: material_id (str): Materials Project ID for a material Returns: dos (CompleteDos): CompleteDos object """ es_rester = ElectronicStructureRester( api_key=self.api_key, endpoint=self.base_endpoint, include_user_agent=self.include_user_agent, session=self.session, monty_decode=self.monty_decode, use_document_model=self.use_document_model, headers=self.headers, mute_progress_bars=self.mute_progress_bars, ) dos_doc = es_rester.search(material_ids=material_id, fields=["dos"]) if not dos_doc: return None dos_data: dict = ( dos_doc[0].model_dump() if self.use_document_model else dos_doc[0] # type: ignore ) if dos_data["dos"]: dos_task_id = dos_data["dos"]["total"]["1"]["task_id"] else: raise MPRestError(f"No density of states data found for {material_id}") dos_obj = self.get_dos_from_task_id(dos_task_id) if dos_obj: return dos_obj else: raise MPRestError("No density of states object found.") api-0.45.3/mp_api/client/routes/materials/eos.py000066400000000000000000000047641475770546700216020ustar00rootroot00000000000000from __future__ import annotations from collections import defaultdict from emmet.core.eos import EOSDoc from mp_api.client.core import BaseRester from mp_api.client.core.utils import validate_ids class EOSRester(BaseRester[EOSDoc]): suffix = "materials/eos" document_model = EOSDoc # type: ignore primary_key = "material_id" def search( self, material_ids: str | list[str] | None = None, energies: tuple[float, float] | None = None, volumes: tuple[float, float] | None = None, num_chunks: int | None = None, chunk_size: int = 1000, all_fields: bool = True, fields: list[str] | None = None, ) -> list[EOSDoc] | list[dict]: """Query equations of state docs using a variety of search criteria. Arguments: material_ids (str, List[str]): Search for equation of states associated with the specified Material IDs energies (Tuple[float,float]): Minimum and maximum energy in eV/atom to consider for EOS plot range. volumes (Tuple[float,float]): Minimum and maximum volume in A³/atom to consider for EOS plot range. num_chunks (int): Maximum number of chunks of data to yield. None will yield all possible. chunk_size (int): Number of data entries per chunk. all_fields (bool): Whether to return all fields in the document. Defaults to True. fields (List[str]): List of fields in EOSDoc to return data for. Default is material_id only if all_fields is False. Returns: ([EOSDoc], [dict]) List of equations of state docs or dictionaries. """ query_params = defaultdict(dict) # type: dict if material_ids: if isinstance(material_ids, str): material_ids = [material_ids] query_params.update({"material_ids": ",".join(validate_ids(material_ids))}) if volumes: query_params.update({"volumes_min": volumes[0], "volumes_max": volumes[1]}) if energies: query_params.update( {"energies_min": energies[0], "energies_max": energies[1]} ) query_params = { entry: query_params[entry] for entry in query_params if query_params[entry] is not None } return super()._search( num_chunks=num_chunks, chunk_size=chunk_size, all_fields=all_fields, fields=fields, **query_params, ) api-0.45.3/mp_api/client/routes/materials/grain_boundaries.py000066400000000000000000000107211475770546700243150ustar00rootroot00000000000000from __future__ import annotations from collections import defaultdict from emmet.core.grain_boundary import GBTypeEnum, GrainBoundaryDoc from mp_api.client.core import BaseRester from mp_api.client.core.utils import validate_ids class GrainBoundaryRester(BaseRester[GrainBoundaryDoc]): suffix = "materials/grain_boundaries" document_model = GrainBoundaryDoc # type: ignore primary_key = "material_id" def search( self, material_ids: str | list[str] | None = None, chemsys: str | None = None, gb_plane: list[str] | None = None, gb_energy: tuple[float, float] | None = None, pretty_formula: str | None = None, rotation_axis: list[str] | None = None, rotation_angle: tuple[float, float] | None = None, separation_energy: tuple[float, float] | None = None, sigma: int | None = None, type: GBTypeEnum | None = None, num_chunks: int | None = None, chunk_size: int = 1000, all_fields: bool = True, fields: list[str] | None = None, ) -> list[GrainBoundaryDoc] | list[dict]: """Query grain boundary docs using a variety of search criteria. Arguments: material_ids (str, List[str]): Search for grain boundary data associated with the specified Material IDs chemsys (str): Dash-delimited string of elements in the material. gb_plane(List[str]): The Miller index of grain boundary plane. e.g., [1, 1, 1] gb_energy (Tuple[float,float]): Minimum and maximum grain boundary energy in J/m³ to consider. material_ids (List[str]): List of Materials Project IDs to query with. pretty_formula (str): Formula of the material. rotation_angle (Tuple[float,float]): Minimum and maximum rotation angle in degrees to consider. rotation_axis(List[str]): The Miller index of rotation axis. e.g., [1, 0, 0], [1, 1, 0], and [1, 1, 1] sigma (int): Sigma value of grain boundary. separation_energy (Tuple[float,float]): Minimum and maximum work of separation energy in J/m³ to consider. sigma (int): Sigma value of the boundary. type (GBTypeEnum): Grain boundary type. num_chunks (int): Maximum number of chunks of data to yield. None will yield all possible. chunk_size (int): Number of data entries per chunk. all_fields (bool): Whether to return all fields in the document. Defaults to True. fields (List[str]): List of fields in GrainBoundaryDoc to return data for. Default is material_id and last_updated if all_fields is False. Returns: ([GrainBoundaryDoc], [dict]) List of grain boundary documents or dictionaries. """ query_params = defaultdict(dict) # type: dict if material_ids: if isinstance(material_ids, str): material_ids = [material_ids] query_params.update({"material_ids": ",".join(validate_ids(material_ids))}) if gb_plane: query_params.update({"gb_plane": ",".join([str(n) for n in gb_plane])}) if gb_energy: query_params.update( {"gb_energy_min": gb_energy[0], "gb_energy_max": gb_energy[1]} ) if separation_energy: query_params.update( {"w_sep_min": separation_energy[0], "w_sep_max": separation_energy[1]} ) if rotation_angle: query_params.update( { "rotation_angle_min": rotation_angle[0], "rotation_angle_max": rotation_angle[1], } ) if rotation_axis: query_params.update( {"rotation_axis": ",".join([str(n) for n in rotation_axis])} ) if sigma: query_params.update({"sigma": sigma}) if type: query_params.update({"type": type.value}) if chemsys: query_params.update({"chemsys": chemsys}) if pretty_formula: query_params.update({"pretty_formula": pretty_formula}) query_params = { entry: query_params[entry] for entry in query_params if query_params[entry] is not None } return super()._search( num_chunks=num_chunks, chunk_size=chunk_size, all_fields=all_fields, fields=fields, **query_params, ) api-0.45.3/mp_api/client/routes/materials/magnetism.py000066400000000000000000000116531475770546700227730ustar00rootroot00000000000000from __future__ import annotations from collections import defaultdict from emmet.core.magnetism import MagnetismDoc from pymatgen.analysis.magnetism import Ordering from mp_api.client.core import BaseRester from mp_api.client.core.utils import validate_ids class MagnetismRester(BaseRester[MagnetismDoc]): suffix = "materials/magnetism" document_model = MagnetismDoc # type: ignore primary_key = "material_id" def search( self, material_ids: str | list[str] | None = None, num_magnetic_sites: tuple[int, int] | None = None, num_unique_magnetic_sites: tuple[int, int] | None = None, ordering: Ordering | None = None, total_magnetization: tuple[float, float] | None = None, total_magnetization_normalized_vol: tuple[float, float] | None = None, total_magnetization_normalized_formula_units: tuple[float, float] | None = None, num_chunks: int | None = None, chunk_size: int = 1000, all_fields: bool = True, fields: list[str] | None = None, ) -> list[MagnetismDoc] | list[dict]: """Query magnetism docs using a variety of search criteria. Arguments: material_ids (str, List[str]): A single Material ID string or list of strings (e.g., mp-149, [mp-149, mp-13]). num_magnetic_sites (Tuple[int,int]): Minimum and maximum number of magnetic sites to consider. num_unique_magnetic_sites (Tuple[int,int]): Minimum and maximum number of unique magnetic sites to consider. ordering (Ordering]): The magnetic ordering of the material. total_magnetization (Tuple[float,float]): Minimum and maximum total magnetization values to consider. total_magnetization_normalized_vol (Tuple[float,float]): Minimum and maximum total magnetization values normalized by volume to consider. total_magnetization_normalized_formula_units (Tuple[float,float]): Minimum and maximum total magnetization values normalized by formula units to consider. num_chunks (int): Maximum number of chunks of data to yield. None will yield all possible. chunk_size (int): Number of data entries per chunk. all_fields (bool): Whether to return all fields in the document. Defaults to True. fields (List[str]): List of fields in MagnetismDoc to return data for. Default is material_id and last_updated if all_fields is False. Returns: ([MagnetismDoc], [dict]) List of magnetism documents or dictionaries. """ query_params = defaultdict(dict) # type: dict if material_ids: if isinstance(material_ids, str): material_ids = [material_ids] query_params.update({"material_ids": ",".join(validate_ids(material_ids))}) if total_magnetization: query_params.update( { "total_magnetization_min": total_magnetization[0], "total_magnetization_max": total_magnetization[1], } ) if total_magnetization_normalized_vol: query_params.update( { "total_magnetization_normalized_vol_min": total_magnetization_normalized_vol[ 0 ], "total_magnetization_normalized_vol_max": total_magnetization_normalized_vol[ 1 ], } ) if total_magnetization_normalized_formula_units: query_params.update( { "total_magnetization_normalized_formula_units_min": total_magnetization_normalized_formula_units[ 0 ], "total_magnetization_normalized_formula_units_max": total_magnetization_normalized_formula_units[ 1 ], } ) if num_magnetic_sites: query_params.update( { "num_magnetic_sites_min": num_magnetic_sites[0], "num_magnetic_sites_max": num_magnetic_sites[1], } ) if num_unique_magnetic_sites: query_params.update( { "num_unique_magnetic_sites_min": num_unique_magnetic_sites[0], "num_unique_magnetic_sites_max": num_unique_magnetic_sites[1], } ) if ordering: query_params.update({"ordering": ordering.value}) query_params = { entry: query_params[entry] for entry in query_params if query_params[entry] is not None } return super()._search( num_chunks=num_chunks, chunk_size=chunk_size, all_fields=all_fields, fields=fields, **query_params, ) api-0.45.3/mp_api/client/routes/materials/materials.py000066400000000000000000000252121475770546700227640ustar00rootroot00000000000000from __future__ import annotations from emmet.core.settings import EmmetSettings from emmet.core.symmetry import CrystalSystem from emmet.core.vasp.material import MaterialsDoc from pymatgen.core.structure import Structure from mp_api.client.core import BaseRester, MPRestError from mp_api.client.core.utils import validate_ids from mp_api.client.routes.materials import ( AbsorptionRester, AlloysRester, BandStructureRester, BondsRester, ChemenvRester, DielectricRester, DosRester, ElasticityRester, ElectrodeRester, ElectronicStructureRester, EOSRester, GrainBoundaryRester, MagnetismRester, OxidationStatesRester, PhononRester, PiezoRester, ProvenanceRester, RobocrysRester, SimilarityRester, SubstratesRester, SummaryRester, SurfacePropertiesRester, SynthesisRester, TaskRester, ThermoRester, XASRester, ) _EMMET_SETTINGS = EmmetSettings() # type: ignore class MaterialsRester(BaseRester[MaterialsDoc]): suffix = "materials/core" document_model = MaterialsDoc # type: ignore supports_versions = True primary_key = "material_id" _sub_resters = [ "eos", "similarity", "tasks", "xas", "grain_boundaries", "substrates", "surface_properties", "phonon", "elasticity", "thermo", "dielectric", "piezoelectric", "magnetism", "summary", "robocrys", "synthesis", "insertion_electrodes", "electronic_structure", "electronic_structure_bandstructure", "electronic_structure_dos", "oxidation_states", "provenance", "bonds", "alloys", "absorption", "chemenv", ] # Materials subresters eos: EOSRester materials: MaterialsRester similarity: SimilarityRester tasks: TaskRester xas: XASRester grain_boundary: GrainBoundaryRester substrates: SubstratesRester surface_properties: SurfacePropertiesRester phonon: PhononRester elasticity: ElasticityRester thermo: ThermoRester dielectric: DielectricRester piezoelectric: PiezoRester magnetism: MagnetismRester summary: SummaryRester robocrys: RobocrysRester synthesis: SynthesisRester insertion_electrodes: ElectrodeRester electronic_structure: ElectronicStructureRester electronic_structure_bandstructure: BandStructureRester electronic_structure_dos: DosRester oxidation_states: OxidationStatesRester provenance: ProvenanceRester bonds: BondsRester alloys: AlloysRester absorption: AbsorptionRester chemenv: ChemenvRester def __dir__(self): return dir(MaterialsRester) + self._sub_resters def get_structure_by_material_id( self, material_id: str, final: bool = True ) -> Structure | list[Structure]: """Get a structure for a given Materials Project ID. Arguments: material_id (str): Materials project ID final (bool): Whether to get the final structure, or the list of initial (pre-relaxation) structures. Defaults to True. Returns: structure (Union[Structure, List[Structure]]): Pymatgen structure object or list of pymatgen structure objects. """ field = "structure" if final else "initial_structures" response = self.search(material_ids=material_id, fields=[field]) if response: response = ( response[0].model_dump() if self.use_document_model else response[0] # type: ignore ) return response[field] if response else response # type: ignore def search( self, material_ids: str | list[str] | None = None, chemsys: str | list[str] | None = None, crystal_system: CrystalSystem | None = None, density: tuple[float, float] | None = None, deprecated: bool | None = False, elements: list[str] | None = None, exclude_elements: list[str] | None = None, formula: str | list[str] | None = None, num_elements: tuple[int, int] | None = None, num_sites: tuple[int, int] | None = None, spacegroup_number: int | None = None, spacegroup_symbol: str | None = None, task_ids: list[str] | None = None, volume: tuple[float, float] | None = None, num_chunks: int | None = None, chunk_size: int = 1000, all_fields: bool = True, fields: list[str] | None = None, ) -> list[MaterialsDoc] | list[dict]: """Query core material docs using a variety of search criteria. Arguments: material_ids (str, List[str]): A single Material ID string or list of strings (e.g., mp-149, [mp-149, mp-13]). chemsys (str, List[str]): A chemical system or list of chemical systems (e.g., Li-Fe-O, Si-*, [Si-O, Li-Fe-P]). crystal_system (CrystalSystem): Crystal system of material. density (Tuple[float,float]): Minimum and maximum density to consider. deprecated (bool): Whether the material is tagged as deprecated. elements (List[str]): A list of elements. exclude_elements (List[str]): A list of elements to exclude. formula (str, List[str]): A formula including anonymized formula or wild cards (e.g., Fe2O3, ABO3, Si*). A list of chemical formulas can also be passed (e.g., [Fe2O3, ABO3]). num_elements (Tuple[int,int]): Minimum and maximum number of elements to consider. num_sites (Tuple[int,int]): Minimum and maximum number of sites to consider. spacegroup_number (int): Space group number of material. spacegroup_symbol (str): Space group symbol of the material in international short symbol notation. task_ids (List[str]): List of Materials Project IDs to return data for. volume (Tuple[float,float]): Minimum and maximum volume to consider. num_chunks (int): Maximum number of chunks of data to yield. None will yield all possible. chunk_size (int): Number of data entries per chunk. all_fields (bool): Whether to return all fields in the document. Defaults to True. fields (List[str]): List of fields in MaterialsCoreDoc to return data for. Default is material_id, last_updated, and formula_pretty if all_fields is False. Returns: ([MaterialsDoc], [dict]) List of material documents or dictionaries. """ query_params = {"deprecated": deprecated} # type: dict if material_ids: if isinstance(material_ids, str): material_ids = [material_ids] query_params.update({"material_ids": ",".join(validate_ids(material_ids))}) if formula: if isinstance(formula, str): formula = [formula] query_params.update({"formula": ",".join(formula)}) if chemsys: if isinstance(chemsys, str): chemsys = [chemsys] query_params.update({"chemsys": ",".join(chemsys)}) if elements: query_params.update({"elements": ",".join(elements)}) if exclude_elements: query_params.update({"exclude_elements": ",".join(exclude_elements)}) if task_ids: query_params.update({"task_ids": ",".join(validate_ids(task_ids))}) query_params.update( { "crystal_system": crystal_system, "spacegroup_number": spacegroup_number, "spacegroup_symbol": spacegroup_symbol, } ) if num_sites: query_params.update( {"nsites_min": num_sites[0], "nsites_max": num_sites[1]} ) if num_elements: if isinstance(num_elements, int): num_elements = (num_elements, num_elements) query_params.update( {"nelements_min": num_elements[0], "nelements_max": num_elements[1]} ) if volume: query_params.update({"volume_min": volume[0], "volume_max": volume[1]}) if density: query_params.update({"density_min": density[0], "density_max": density[1]}) query_params = { entry: query_params[entry] for entry in query_params if query_params[entry] is not None } return super()._search( num_chunks=num_chunks, chunk_size=chunk_size, all_fields=all_fields, fields=fields, **query_params, ) def find_structure( self, filename_or_structure, ltol=_EMMET_SETTINGS.LTOL, stol=_EMMET_SETTINGS.STOL, angle_tol=_EMMET_SETTINGS.ANGLE_TOL, allow_multiple_results=False, ) -> list[str] | str: """Finds matching structures from the Materials Project database. Multiple results may be returned of "similar" structures based on distance using the pymatgen StructureMatcher algorithm, however only a single result should match with the same spacegroup, calculated to the default tolerances. Args: filename_or_structure: filename or Structure object ltol: fractional length tolerance stol: site tolerance angle_tol: angle tolerance in degrees allow_multiple_results: changes return type for either a single material_id or list of material_ids Returns: A matching material_id if one is found or list of results if allow_multiple_results is True Raises: MPRestError """ params = {"ltol": ltol, "stol": stol, "angle_tol": angle_tol, "_limit": 1} if isinstance(filename_or_structure, str): s = Structure.from_file(filename_or_structure) elif isinstance(filename_or_structure, Structure): s = filename_or_structure else: raise MPRestError("Provide filename or Structure object.") results = self._post_resource( body=s.as_dict(), params=params, suburl="find_structure", use_document_model=False, ).get("data") if len(results) > 1: # type: ignore if not allow_multiple_results: raise ValueError( "Multiple matches found for this combination of tolerances, but " "`allow_multiple_results` set to False." ) return results # type: ignore if results: return results[0]["material_id"] else: return [] api-0.45.3/mp_api/client/routes/materials/oxidation_states.py000066400000000000000000000061651475770546700243720ustar00rootroot00000000000000from __future__ import annotations from collections import defaultdict from emmet.core.oxidation_states import OxidationStateDoc from mp_api.client.core import BaseRester from mp_api.client.core.utils import validate_ids class OxidationStatesRester(BaseRester[OxidationStateDoc]): suffix = "materials/oxidation_states" document_model = OxidationStateDoc # type: ignore primary_key = "material_id" def search( self, material_ids: str | list[str] | None = None, chemsys: str | list[str] | None = None, formula: str | list[str] | None = None, possible_species: str | list[str] | None = None, num_chunks: int | None = None, chunk_size: int = 1000, all_fields: bool = True, fields: list[str] | None = None, ) -> list[OxidationStateDoc] | list[dict]: """Query oxidation state docs using a variety of search criteria. Arguments: material_ids (str, List[str]): A single Material ID string or list of strings (e.g., mp-149, [mp-149, mp-13]). chemsys (str, List[str]): A chemical system or list of chemical systems (e.g., Li-Fe-O, Si-*, [Si-O, Li-Fe-P]). formula (str, List[str]): A formula including anonymized formula or wild cards (e.g., Fe2O3, ABO3, Si*). A list of chemical formulas can also be passed (e.g., [Fe2O3, ABO3]). possible_species (List[str]): A list of element symbols appended with oxidation states (e.g. [Cr2+, O2-]]). num_chunks (int): Maximum number of chunks of data to yield. None will yield all possible. chunk_size (int): Number of data entries per chunk. all_fields (bool): Whether to return all fields in the document. Defaults to True. fields (List[str]): List of fields in OxidationStateDoc to return data for. Default is material_id, last_updated, and formula_pretty if all_fields is False. Returns: ([OxidationStateDoc], [dict]) List of oxidation state documents or dictionaries. """ query_params = defaultdict(dict) # type: dict if material_ids: if isinstance(material_ids, str): material_ids = [material_ids] query_params.update({"material_ids": ",".join(validate_ids(material_ids))}) if formula: if isinstance(formula, str): formula = [formula] query_params.update({"formula": ",".join(formula)}) if chemsys: if isinstance(chemsys, str): chemsys = [chemsys] query_params.update({"chemsys": ",".join(chemsys)}) if possible_species: query_params.update({"possible_species": ",".join(possible_species)}) query_params = { entry: query_params[entry] for entry in query_params if query_params[entry] is not None } return super()._search( num_chunks=num_chunks, chunk_size=chunk_size, all_fields=all_fields, fields=fields, **query_params, ) api-0.45.3/mp_api/client/routes/materials/phonon.py000066400000000000000000000040061475770546700223020ustar00rootroot00000000000000from __future__ import annotations from collections import defaultdict from emmet.core.phonon import PhononBSDOSDoc from mp_api.client.core import BaseRester from mp_api.client.core.utils import validate_ids class PhononRester(BaseRester[PhononBSDOSDoc]): suffix = "materials/phonon" document_model = PhononBSDOSDoc # type: ignore primary_key = "material_id" def search( self, material_ids: str | list[str] | None = None, num_chunks: int | None = None, chunk_size: int = 1000, all_fields: bool = True, fields: list[str] | None = None, ) -> list[PhononBSDOSDoc] | list[dict]: """Query phonon docs using a variety of search criteria. Arguments: material_ids (str, List[str]): A single Material ID string or list of strings (e.g., mp-149, [mp-149, mp-13]). num_chunks (int): Maximum number of chunks of data to yield. None will yield all possible. chunk_size (int): Number of data entries per chunk. all_fields (bool): Whether to return all fields in the document. Defaults to True. fields (List[str]): List of fields in PhononBSDOSDoc to return data for. Default is material_id, last_updated, and formula_pretty if all_fields is False. Returns: ([PhononBSDOSDoc], [dict]) List of phonon documents or dictionaries. """ query_params = defaultdict(dict) # type: dict if material_ids: if isinstance(material_ids, str): material_ids = [material_ids] query_params.update({"material_ids": ",".join(validate_ids(material_ids))}) query_params = { entry: query_params[entry] for entry in query_params if query_params[entry] is not None } return super()._search( num_chunks=num_chunks, chunk_size=chunk_size, all_fields=all_fields, fields=fields, **query_params, ) api-0.45.3/mp_api/client/routes/materials/piezo.py000066400000000000000000000047001475770546700221300ustar00rootroot00000000000000from __future__ import annotations from collections import defaultdict from emmet.core.polar import PiezoelectricDoc from mp_api.client.core import BaseRester from mp_api.client.core.utils import validate_ids class PiezoRester(BaseRester[PiezoelectricDoc]): suffix = "materials/piezoelectric" document_model = PiezoelectricDoc # type: ignore primary_key = "material_id" def search( self, material_ids: str | list[str] | None = None, piezoelectric_modulus: tuple[float, float] | None = None, num_chunks: int | None = None, chunk_size: int = 1000, all_fields: bool = True, fields: list[str] | None = None, ) -> list[PiezoelectricDoc] | list[dict]: """Query piezoelectric data using a variety of search criteria. Arguments: material_ids (str, List[str]): A single Material ID string or list of strings (e.g., mp-149, [mp-149, mp-13]). piezoelectric_modulus (Tuple[float,float]): Minimum and maximum of the piezoelectric modulus in C/m² to consider. num_chunks (int): Maximum number of chunks of data to yield. None will yield all possible. chunk_size (int): Number of data entries per chunk. all_fields (bool): Whether to return all fields in the document. Defaults to True. fields (List[str]): List of fields in PiezoDoc to return data for. Default is material_id and last_updated if all_fields is False. Returns: ([PiezoDoc], [dict]) List of piezoelectric documents """ query_params = defaultdict(dict) # type: dict if material_ids: if isinstance(material_ids, str): material_ids = [material_ids] query_params.update({"material_ids": ",".join(validate_ids(material_ids))}) if piezoelectric_modulus: query_params.update( { "piezo_modulus_min": piezoelectric_modulus[0], "piezo_modulus_max": piezoelectric_modulus[1], } ) query_params = { entry: query_params[entry] for entry in query_params if query_params[entry] is not None } return super()._search( num_chunks=num_chunks, chunk_size=chunk_size, all_fields=all_fields, fields=fields, **query_params, ) api-0.45.3/mp_api/client/routes/materials/provenance.py000066400000000000000000000041551475770546700231460ustar00rootroot00000000000000from __future__ import annotations from emmet.core.provenance import ProvenanceDoc from mp_api.client.core import BaseRester from mp_api.client.core.utils import validate_ids class ProvenanceRester(BaseRester[ProvenanceDoc]): suffix = "materials/provenance" document_model = ProvenanceDoc # type: ignore primary_key = "material_id" def search( self, material_ids: str | list[str] | None = None, deprecated: bool | None = False, num_chunks: int | None = None, chunk_size: int = 1000, all_fields: bool = True, fields: list[str] | None = None, ) -> list[ProvenanceDoc] | list[dict]: """Query provenance docs using a variety of search criteria. Arguments: material_ids (str, List[str]): A single Material ID string or list of strings (e.g., mp-149, [mp-149, mp-13]). deprecated (bool): Whether the material is tagged as deprecated. num_chunks (int): Maximum number of chunks of data to yield. None will yield all possible. chunk_size (int): Number of data entries per chunk. all_fields (bool): Whether to return all fields in the document. Defaults to True. fields (List[str]): List of fields in ProvenanceDoc to return data for. Default is material_id, last_updated, and formula_pretty if all_fields is False. Returns: ([ProvenanceDoc], [dict]) List of provenance documents or dictionaries. """ query_params = {"deprecated": deprecated} # type: dict if material_ids: if isinstance(material_ids, str): material_ids = [material_ids] query_params.update({"material_ids": ",".join(validate_ids(material_ids))}) query_params = { entry: query_params[entry] for entry in query_params if query_params[entry] is not None } return super()._search( num_chunks=num_chunks, chunk_size=chunk_size, all_fields=all_fields, fields=fields, **query_params, ) api-0.45.3/mp_api/client/routes/materials/robocrys.py000066400000000000000000000061211475770546700226430ustar00rootroot00000000000000from __future__ import annotations from emmet.core.robocrys import RobocrystallogapherDoc from mp_api.client.core import BaseRester, MPRestError from mp_api.client.core.utils import validate_ids class RobocrysRester(BaseRester[RobocrystallogapherDoc]): suffix = "materials/robocrys" document_model = RobocrystallogapherDoc # type: ignore primary_key = "material_id" def search( self, keywords: list[str], num_chunks: int | None = None, chunk_size: int | None = 100, ): """Search text generated from Robocrystallographer. Arguments: keywords (List[str]): List of search keywords num_chunks (Optional[int]): Maximum number of chunks of data to yield. None will yield all possible. chunk_size (Optional[int]): Number of data entries per chunk. Returns: robocrys_docs (List[RobocrystallogapherDoc]): List of robocrystallographer documents """ keyword_string = ",".join(keywords) robocrys_docs = self._query_resource( criteria={"keywords": keyword_string, "_limit": chunk_size}, suburl="text_search", use_document_model=True, chunk_size=chunk_size, num_chunks=num_chunks, ).get("data", None) if robocrys_docs is None: raise MPRestError("Cannot find any matches.") return robocrys_docs def search_docs( self, material_ids: str | list[str] | None = None, num_chunks: int | None = None, chunk_size: int = 1000, all_fields: bool = True, fields: list[str] | None = None, ) -> list[RobocrystallogapherDoc] | list[dict]: """Query robocrystallographer docs using a variety of search criteria. Arguments: material_ids (str, List[str]): A single Material ID string or list of strings (e.g., mp-149, [mp-149, mp-13]). num_chunks (int): Maximum number of chunks of data to yield. None will yield all possible. chunk_size (int): Number of data entries per chunk. all_fields (bool): Whether to return all fields in the document. Defaults to True. fields (List[str]): List of fields in RobocrystallogapherDoc to return data for. Default is material_id, last_updated, and formula_pretty if all_fields is False. Returns: ([RobocrystallogapherDoc], [dict]) List of robocrystallographer documents or dictionaries. """ query_params = {} # type: dict if material_ids: if isinstance(material_ids, str): material_ids = [material_ids] query_params.update({"material_ids": ",".join(validate_ids(material_ids))}) query_params = { entry: query_params[entry] for entry in query_params if query_params[entry] is not None } return super()._search( num_chunks=num_chunks, chunk_size=chunk_size, all_fields=all_fields, fields=fields, **query_params, ) api-0.45.3/mp_api/client/routes/materials/similarity.py000066400000000000000000000037371475770546700232010ustar00rootroot00000000000000from __future__ import annotations from emmet.core.similarity import SimilarityDoc from mp_api.client.core import BaseRester from mp_api.client.core.utils import validate_ids class SimilarityRester(BaseRester[SimilarityDoc]): suffix = "materials/similarity" document_model = SimilarityDoc # type: ignore primary_key = "material_id" def search( self, material_ids: str | list[str] | None = None, num_chunks: int | None = None, chunk_size: int = 1000, all_fields: bool = True, fields: list[str] | None = None, ) -> list[SimilarityDoc] | list[dict]: """Query similarity docs using a variety of search criteria. Arguments: material_ids (str, List[str]): A single Material ID string or list of strings (e.g., mp-149, [mp-149, mp-13]). num_chunks (int): Maximum number of chunks of data to yield. None will yield all possible. chunk_size (int): Number of data entries per chunk. all_fields (bool): Whether to return all fields in the document. Defaults to True. fields (List[str]): List of fields in SimilarityDoc to return data for. Default is material_id, last_updated, and formula_pretty if all_fields is False. Returns: ([SimilarityDoc], [dict]) List of similarity documents or dictionaries. """ query_params = {} # type: dict if material_ids: if isinstance(material_ids, str): material_ids = [material_ids] query_params.update({"material_ids": ",".join(validate_ids(material_ids))}) query_params = { entry: query_params[entry] for entry in query_params if query_params[entry] is not None } return super()._search( num_chunks=num_chunks, chunk_size=chunk_size, all_fields=all_fields, fields=fields, **query_params, ) api-0.45.3/mp_api/client/routes/materials/substrates.py000066400000000000000000000067031475770546700232060ustar00rootroot00000000000000from __future__ import annotations from collections import defaultdict from emmet.core.substrates import SubstratesDoc from mp_api.client.core import BaseRester class SubstratesRester(BaseRester[SubstratesDoc]): suffix = "materials/substrates" document_model = SubstratesDoc # type: ignore primary_key = "film_id" def search( self, area: tuple[float, float] | None = None, energy: tuple[float, float] | None = None, film_id: str | None = None, film_orientation: list[int] | None = None, substrate_id: str | None = None, substrate_formula: str | None = None, substrate_orientation: list[int] | None = None, num_chunks: int | None = None, chunk_size: int = 1000, all_fields: bool = True, fields: list[str] | None = None, ) -> list[SubstratesDoc] | list[dict]: """Query substrate docs using a variety of search criteria. Arguments: area (Tuple[float,float]): Minimum and maximum volume in Ų to consider for the minimum coincident interface area range. energy (Tuple[float,float]): Minimum and maximum energy in meV to consider for the elastic energy range. film_id (str): Materials Project ID of the film material. film_orientation (List[int]): Vector indicating the surface orientation of the film material. substrate_id (str): Materials Project ID of the substrate material. substrate_formula (str): Reduced formula of the substrate material. substrate_orientation (List[int]): Vector indicating the surface orientation of the substrate material. num_chunks (int): Maximum number of chunks of data to yield. None will yield all possible. chunk_size (int): Number of data entries per chunk. all_fields (bool): Whether to return all fields in the document. Defaults to True. fields (List[str]): List of fields in SubstratesDoc to return data for. Default is the film_id and substrate_id only if all_fields is False. Returns: ([SubstratesDoc], [dict]) List of substrate documents or dictionaries. """ query_params = defaultdict(dict) # type: dict if film_id: query_params.update({"film_id": film_id}) if substrate_id: query_params.update({"sub_id": substrate_id}) if substrate_formula: query_params.update({"sub_form": substrate_formula}) if film_orientation: query_params.update( {"film_orientation": ",".join([str(i) for i in film_orientation])} ) if substrate_orientation: query_params.update( { "substrate_orientation": ",".join( [str(i) for i in substrate_orientation] ) } ) if area: query_params.update({"area_min": area[0], "area_max": area[1]}) if energy: query_params.update({"energy_min": energy[0], "energy_max": energy[1]}) query_params = { entry: query_params[entry] for entry in query_params if query_params[entry] is not None } return super()._search( **query_params, num_chunks=num_chunks, chunk_size=chunk_size, all_fields=all_fields, fields=fields, ) api-0.45.3/mp_api/client/routes/materials/summary.py000066400000000000000000000343711475770546700225060ustar00rootroot00000000000000from __future__ import annotations from collections import defaultdict from emmet.core.summary import HasProps, SummaryDoc from emmet.core.symmetry import CrystalSystem from pymatgen.analysis.magnetism import Ordering from mp_api.client.core import BaseRester, MPRestError from mp_api.client.core.utils import validate_ids class SummaryRester(BaseRester[SummaryDoc]): suffix = "materials/summary" document_model = SummaryDoc # type: ignore primary_key = "material_id" def search( self, band_gap: tuple[float, float] | None = None, chemsys: str | list[str] | None = None, crystal_system: CrystalSystem | None = None, density: tuple[float, float] | None = None, deprecated: bool | None = None, e_electronic: tuple[float, float] | None = None, e_ionic: tuple[float, float] | None = None, e_total: tuple[float, float] | None = None, efermi: tuple[float, float] | None = None, elastic_anisotropy: tuple[float, float] | None = None, elements: list[str] | None = None, energy_above_hull: tuple[float, float] | None = None, equilibrium_reaction_energy: tuple[float, float] | None = None, exclude_elements: list[str] | None = None, formation_energy: tuple[float, float] | None = None, formula: str | list[str] | None = None, g_reuss: tuple[float, float] | None = None, g_voigt: tuple[float, float] | None = None, g_vrh: tuple[float, float] | None = None, has_props: list[HasProps] | list[str] | None = None, has_reconstructed: bool | None = None, is_gap_direct: bool | None = None, is_metal: bool | None = None, is_stable: bool | None = None, k_reuss: tuple[float, float] | None = None, k_voigt: tuple[float, float] | None = None, k_vrh: tuple[float, float] | None = None, magnetic_ordering: Ordering | None = None, material_ids: str | list[str] | None = None, n: tuple[float, float] | None = None, num_elements: tuple[int, int] | None = None, num_sites: tuple[int, int] | None = None, num_magnetic_sites: tuple[int, int] | None = None, num_unique_magnetic_sites: tuple[int, int] | None = None, piezoelectric_modulus: tuple[float, float] | None = None, poisson_ratio: tuple[float, float] | None = None, possible_species: list[str] | None = None, shape_factor: tuple[float, float] | None = None, spacegroup_number: int | None = None, spacegroup_symbol: str | None = None, surface_energy_anisotropy: tuple[float, float] | None = None, theoretical: bool | None = None, total_energy: tuple[float, float] | None = None, total_magnetization: tuple[float, float] | None = None, total_magnetization_normalized_formula_units: tuple[float, float] | None = None, total_magnetization_normalized_vol: tuple[float, float] | None = None, uncorrected_energy: tuple[float, float] | None = None, volume: tuple[float, float] | None = None, weighted_surface_energy: tuple[float, float] | None = None, weighted_work_function: tuple[float, float] | None = None, include_gnome: bool = True, num_chunks: int | None = None, chunk_size: int = 1000, all_fields: bool = True, fields: list[str] | None = None, ) -> list[SummaryDoc] | list[dict]: """Query core data using a variety of search criteria. Arguments: band_gap (Tuple[float,float]): Minimum and maximum band gap in eV to consider. chemsys (str, List[str]): A chemical system or list of chemical systems (e.g., Li-Fe-O, Si-*, [Si-O, Li-Fe-P]). crystal_system (CrystalSystem): Crystal system of material. density (Tuple[float,float]): Minimum and maximum density to consider. deprecated (bool): Whether the material is tagged as deprecated. e_electronic (Tuple[float,float]): Minimum and maximum electronic dielectric constant to consider. e_ionic (Tuple[float,float]): Minimum and maximum ionic dielectric constant to consider. e_total (Tuple[float,float]): Minimum and maximum total dielectric constant to consider. efermi (Tuple[float,float]): Minimum and maximum fermi energy in eV to consider. elastic_anisotropy (Tuple[float,float]): Minimum and maximum value to consider for the elastic anisotropy. elements (List[str]): A list of elements. energy_above_hull (Tuple[int,int]): Minimum and maximum energy above the hull in eV/atom to consider. equilibrium_reaction_energy (Tuple[float,float]): Minimum and maximum equilibrium reaction energy in eV/atom to consider. exclude_elements (List(str)): List of elements to exclude. formation_energy (Tuple[int,int]): Minimum and maximum formation energy in eV/atom to consider. formula (str, List[str]): A formula including anonymized formula or wild cards (e.g., Fe2O3, ABO3, Si*). A list of chemical formulas can also be passed (e.g., [Fe2O3, ABO3]). g_reuss (Tuple[float,float]): Minimum and maximum value in GPa to consider for the Reuss average of the shear modulus. g_voigt (Tuple[float,float]): Minimum and maximum value in GPa to consider for the Voigt average of the shear modulus. g_vrh (Tuple[float,float]): Minimum and maximum value in GPa to consider for the Voigt-Reuss-Hill average of the shear modulus. has_props: (List[HasProps], List[str]): The calculated properties available for the material. has_reconstructed (bool): Whether the entry has any reconstructed surfaces. is_gap_direct (bool): Whether the material has a direct band gap. is_metal (bool): Whether the material is considered a metal. is_stable (bool): Whether the material lies on the convex energy hull. k_reuss (Tuple[float,float]): Minimum and maximum value in GPa to consider for the Reuss average of the bulk modulus. k_voigt (Tuple[float,float]): Minimum and maximum value in GPa to consider for the Voigt average of the bulk modulus. k_vrh (Tuple[float,float]): Minimum and maximum value in GPa to consider for the Voigt-Reuss-Hill average of the bulk modulus. magnetic_ordering (Ordering): Magnetic ordering of the material. material_ids (str, List[str]): A single Material ID string or list of strings (e.g., mp-149, [mp-149, mp-13]). n (Tuple[float,float]): Minimum and maximum refractive index to consider. num_elements (Tuple[int,int]): Minimum and maximum number of elements to consider. num_sites (Tuple[int,int]): Minimum and maximum number of sites to consider. num_magnetic_sites (Tuple[int,int]): Minimum and maximum number of magnetic sites to consider. num_unique_magnetic_sites (Tuple[int,int]): Minimum and maximum number of unique magnetic sites to consider. piezoelectric_modulus (Tuple[float,float]): Minimum and maximum piezoelectric modulus to consider. poisson_ratio (Tuple[float,float]): Minimum and maximum value to consider for Poisson's ratio. possible_species (List(str)): List of element symbols appended with oxidation states. (e.g. Cr2+,O2-) shape_factor (Tuple[float,float]): Minimum and maximum shape factor values to consider. spacegroup_number (int): Space group number of material. spacegroup_symbol (str): Space group symbol of the material in international short symbol notation. surface_energy_anisotropy (Tuple[float,float]): Minimum and maximum surface energy anisotropy values to consider. theoretical: (bool): Whether the material is theoretical. total_energy (Tuple[int,int]): Minimum and maximum corrected total energy in eV/atom to consider. total_magnetization (Tuple[float,float]): Minimum and maximum total magnetization values to consider. total_magnetization_normalized_formula_units (Tuple[float,float]): Minimum and maximum total magnetization values normalized by formula units to consider. total_magnetization_normalized_vol (Tuple[float,float]): Minimum and maximum total magnetization values normalized by volume to consider. uncorrected_energy (Tuple[int,int]): Minimum and maximum uncorrected total energy in eV/atom to consider. volume (Tuple[float,float]): Minimum and maximum volume to consider. weighted_surface_energy (Tuple[float,float]): Minimum and maximum weighted surface energy in J/m² to consider. weighted_work_function (Tuple[float,float]): Minimum and maximum weighted work function in eV to consider. include_gnome (bool): whether to include materials from GNoMe dataset num_chunks (int): Maximum number of chunks of data to yield. None will yield all possible. chunk_size (int): Number of data entries per chunk. all_fields (bool): Whether to return all fields in the document. Defaults to True. fields (List[str]): List of fields in SummaryDoc to return data for. Default is material_id if all_fields is False. Returns: ([SummaryDoc], [dict]) List of SummaryDoc documents or dictionaries. """ query_params = defaultdict(dict) # type: dict min_max_name_dict = { "total_energy": "energy_per_atom", "formation_energy": "formation_energy_per_atom", "energy_above_hull": "energy_above_hull", "uncorrected_energy": "uncorrected_energy_per_atom", "equilibrium_reaction_energy": "equilibrium_reaction_energy_per_atom", "nsites": "nsites", "volume": "volume", "density": "density", "band_gap": "band_gap", "efermi": "efermi", "total_magnetization": "total_magnetization", "total_magnetization_normalized_vol": "total_magnetization_normalized_vol", "total_magnetization_normalized_formula_units": "total_magnetization_normalized_formula_units", "num_magnetic_sites": "num_magnetic_sites", "num_unique_magnetic_sites": "num_unique_magnetic_sites", "k_voigt": "k_voigt", "k_reuss": "k_reuss", "k_vrh": "k_vrh", "g_voigt": "g_voigt", "g_reuss": "g_reuss", "g_vrh": "g_vrh", "elastic_anisotropy": "universal_anisotropy", "poisson_ratio": "homogeneous_poisson", "e_total": "e_total", "e_ionic": "e_ionic", "e_electronic": "e_electronic", "n": "n", "num_sites": "nsites", "num_elements": "nelements", "piezoelectric_modulus": "e_ij_max", "weighted_surface_energy": "weighted_surface_energy", "weighted_work_function": "weighted_work_function", "surface_energy_anisotropy": "surface_anisotropy", "shape_factor": "shape_factor", } for param, value in locals().items(): if param in min_max_name_dict and value: if isinstance(value, (int, float)): value = (value, value) query_params.update( { f"{min_max_name_dict[param]}_min": value[0], f"{min_max_name_dict[param]}_max": value[1], } ) if material_ids: if isinstance(material_ids, str): material_ids = [material_ids] query_params.update({"material_ids": ",".join(validate_ids(material_ids))}) if deprecated is not None: query_params.update({"deprecated": deprecated}) if formula: if isinstance(formula, str): formula = [formula] query_params.update({"formula": ",".join(formula)}) if chemsys: if isinstance(chemsys, str): chemsys = [chemsys] query_params.update({"chemsys": ",".join(chemsys)}) if elements: query_params.update({"elements": ",".join(elements)}) if exclude_elements is not None: query_params.update({"exclude_elements": ",".join(exclude_elements)}) if possible_species is not None: query_params.update({"possible_species": ",".join(possible_species)}) query_params.update( { "crystal_system": crystal_system, "spacegroup_number": spacegroup_number, "spacegroup_symbol": spacegroup_symbol, } ) if is_stable is not None: query_params.update({"is_stable": is_stable}) if is_gap_direct is not None: query_params.update({"is_gap_direct": is_gap_direct}) if is_metal is not None: query_params.update({"is_metal": is_metal}) if magnetic_ordering: query_params.update({"ordering": magnetic_ordering.value}) if has_reconstructed is not None: query_params.update({"has_reconstructed": has_reconstructed}) if has_props: has_props_clean = [] for prop in has_props: try: has_props_clean.append(HasProps(prop).value) except ValueError: raise MPRestError(f"'{prop}' is not a valid property.") query_params.update({"has_props": ",".join(has_props_clean)}) if theoretical is not None: query_params.update({"theoretical": theoretical}) if not include_gnome: query_params.update({"batch_id_not_eq": "gnome_r2scan_statics"}) query_params = { entry: query_params[entry] for entry in query_params if query_params[entry] is not None } return super()._search( num_chunks=num_chunks, chunk_size=chunk_size, all_fields=all_fields, fields=fields, **query_params, ) api-0.45.3/mp_api/client/routes/materials/surface_properties.py000066400000000000000000000100421475770546700247020ustar00rootroot00000000000000from __future__ import annotations from collections import defaultdict from emmet.core.surface_properties import SurfacePropDoc from mp_api.client.core import BaseRester from mp_api.client.core.utils import validate_ids class SurfacePropertiesRester(BaseRester[SurfacePropDoc]): suffix = "materials/surface_properties" document_model = SurfacePropDoc # type: ignore primary_key = "material_id" def search( self, material_ids: str | list[str] | None = None, has_reconstructed: bool | None = None, shape_factor: tuple[float, float] | None = None, surface_energy_anisotropy: tuple[float, float] | None = None, weighted_surface_energy: tuple[float, float] | None = None, weighted_work_function: tuple[float, float] | None = None, num_chunks: int | None = None, chunk_size: int = 1000, all_fields: bool = True, fields: list[str] | None = None, ) -> list[SurfacePropDoc] | list[dict]: """Query surface properties docs using a variety of search criteria. Arguments: material_ids (str, List[str]): A single Material ID string or list of strings (e.g., mp-149, [mp-149, mp-13]). has_reconstructed (bool): Whether the entry has any reconstructed surfaces. shape_factor (Tuple[float,float]): Minimum and maximum shape factor values to consider. surface_energy_anisotropy (Tuple[float,float]): Minimum and maximum surface energy anisotropy values to consider. weighted_surface_energy (Tuple[float,float]): Minimum and maximum weighted surface energy in J/m² to consider. weighted_work_function (Tuple[float,float]): Minimum and maximum weighted work function in eV to consider. num_chunks (int): Maximum number of chunks of data to yield. None will yield all possible. chunk_size (int): Number of data entries per chunk. all_fields (bool): Whether to return all fields in the document. Defaults to True. fields (List[str]): List of fields in SurfacePropDoc to return data for. Default is material_id only if all_fields is False. Returns: ([SurfacePropDoc], [dict]) List of surface properties documents """ query_params = defaultdict(dict) # type: dict if material_ids: if isinstance(material_ids, str): material_ids = [material_ids] query_params.update({"material_ids": ",".join(validate_ids(material_ids))}) if weighted_surface_energy: query_params.update( { "weighted_surface_energy_min": weighted_surface_energy[0], "weighted_surface_energy_max": weighted_surface_energy[1], } ) if weighted_work_function: query_params.update( { "weighted_work_function_min": weighted_work_function[0], "weighted_work_function_max": weighted_work_function[1], } ) if surface_energy_anisotropy: query_params.update( { "surface_anisotropy_min": surface_energy_anisotropy[0], "surface_anisotropy_max": surface_energy_anisotropy[1], } ) if shape_factor: query_params.update( { "shape_factor_min": shape_factor[0], "shape_factor_max": shape_factor[1], } ) if has_reconstructed is not None: query_params.update({"has_reconstructed": has_reconstructed}) query_params = { entry: query_params[entry] for entry in query_params if query_params[entry] is not None } return super()._search( num_chunks=num_chunks, chunk_size=chunk_size, all_fields=all_fields, fields=fields, **query_params, ) api-0.45.3/mp_api/client/routes/materials/synthesis.py000066400000000000000000000103701475770546700230330ustar00rootroot00000000000000from __future__ import annotations from emmet.core.synthesis import ( OperationTypeEnum, SynthesisSearchResultModel, SynthesisTypeEnum, ) from mp_api.client.core import BaseRester, MPRestError class SynthesisRester(BaseRester[SynthesisSearchResultModel]): suffix = "materials/synthesis" document_model = SynthesisSearchResultModel # type: ignore def search( self, keywords: list[str] | None = None, synthesis_type: list[SynthesisTypeEnum] | None = None, target_formula: str | None = None, precursor_formula: str | None = None, operations: list[OperationTypeEnum] | None = None, condition_heating_temperature_min: float | None = None, condition_heating_temperature_max: float | None = None, condition_heating_time_min: float | None = None, condition_heating_time_max: float | None = None, condition_heating_atmosphere: list[str] | None = None, condition_mixing_device: list[str] | None = None, condition_mixing_media: list[str] | None = None, num_chunks: int | None = None, chunk_size: int | None = 10, ) -> list[SynthesisSearchResultModel] | list[dict]: """Search synthesis recipe text. Arguments: keywords (Optional[List[str]]): List of string keywords to search synthesis paragraph text with synthesis_type (Optional[List[SynthesisTypeEnum]]): Type of synthesis to include target_formula (Optional[str]): Chemical formula of the target material precursor_formula (Optional[str]): Chemical formula of the precursor material operations (Optional[List[OperationTypeEnum]]): List of operations that syntheses must have condition_heating_temperature_min (Optional[float]): Minimal heating temperature condition_heating_temperature_max (Optional[float]): Maximal heating temperature condition_heating_time_min (Optional[float]): Minimal heating time condition_heating_time_max (Optional[float]): Maximal heating time condition_heating_atmosphere (Optional[List[str]]): Required heating atmosphere, such as "air", "argon" condition_mixing_device (Optional[List[str]]): Required mixing device, such as "zirconia", "Al2O3". condition_mixing_media (Optional[List[str]]): Required mixing media, such as "alcohol", "water" num_chunks (Optional[int]): Maximum number of chunks of data to yield. None will yield all possible. chunk_size (Optional[int]): Number of data entries per chunk. Returns: ([SynthesisSearchResultModel], [dict]): List of synthesis documents or dictionaries. """ # Turn None and empty list into None keywords = keywords or None synthesis_type = synthesis_type or None operations = operations or None condition_heating_atmosphere = condition_heating_atmosphere or None condition_mixing_device = condition_mixing_device or None condition_mixing_media = condition_mixing_media or None if keywords: keywords = ",".join([word.strip() for word in keywords]) # type: ignore synthesis_docs = self._query_resource( criteria={ "keywords": keywords, "synthesis_type": synthesis_type, "target_formula": target_formula, "precursor_formula": precursor_formula, "operations": operations, "condition_heating_temperature_min": condition_heating_temperature_min, "condition_heating_temperature_max": condition_heating_temperature_max, "condition_heating_time_min": condition_heating_time_min, "condition_heating_time_max": condition_heating_time_max, "condition_heating_atmosphere": condition_heating_atmosphere, "condition_mixing_device": condition_mixing_device, "condition_mixing_media": condition_mixing_media, "_limit": chunk_size, }, chunk_size=chunk_size, num_chunks=num_chunks, ).get("data", None) if synthesis_docs is None: raise MPRestError("Cannot find any matches.") return synthesis_docs api-0.45.3/mp_api/client/routes/materials/tasks.py000066400000000000000000000067721475770546700221420ustar00rootroot00000000000000from __future__ import annotations from datetime import datetime from emmet.core.tasks import TaskDoc from mp_api.client.core import BaseRester, MPRestError from mp_api.client.core.utils import validate_ids class TaskRester(BaseRester[TaskDoc]): suffix = "materials/tasks" document_model = TaskDoc # type: ignore primary_key = "task_id" def get_trajectory(self, task_id): """Returns a Trajectory object containing the geometry of the material throughout a calculation. This is most useful for observing how a material relaxes during a geometry optimization. Args: task_id (str): Task ID """ traj_data = self._query_resource_data( {"task_ids": [task_id]}, suburl="trajectory/", use_document_model=False )[0].get( "trajectories", None ) # type: ignore if traj_data is None: raise MPRestError(f"No trajectory data for {task_id} found") return traj_data def search( self, task_ids: str | list[str] | None = None, elements: list[str] | None = None, exclude_elements: list[str] | None = None, formula: str | list[str] | None = None, last_updated: tuple[datetime, datetime] | None = None, num_chunks: int | None = None, chunk_size: int = 1000, all_fields: bool = True, fields: list[str] | None = None, ) -> list[TaskDoc] | list[dict]: """Query core task docs using a variety of search criteria. Arguments: task_ids (str, List[str]): List of Materials Project IDs to return data for. elements (List[str]): A list of elements. exclude_elements (List[str]): A list of elements to exclude. formula (str, List[str]): A formula including anonymized formula or wild cards (e.g., Fe2O3, ABO3, Si*). A list of chemical formulas can also be passed (e.g., [Fe2O3, ABO3]). last_updated (tuple[datetime, datetime]): A tuple of min and max UTC formatted datetimes. num_chunks (int): Maximum number of chunks of data to yield. None will yield all possible. chunk_size (int): Number of data entries per chunk. Max size is 100. all_fields (bool): Whether to return all fields in the document. Defaults to True. fields (List[str]): List of fields in TaskDoc to return data for. Default is material_id, last_updated, and formula_pretty if all_fields is False. Returns: ([TaskDoc], [dict]) List of task documents or dictionaries. """ query_params = {} # type: dict if task_ids: if isinstance(task_ids, str): task_ids = [task_ids] query_params.update({"task_ids": ",".join(validate_ids(task_ids))}) if formula: query_params.update({"formula": formula}) if elements: query_params.update({"elements": ",".join(elements)}) if exclude_elements: query_params.update({"exclude_elements": ",".join(exclude_elements)}) if last_updated: query_params.update( { "last_updated_min": last_updated[0], "last_updated_max": last_updated[1], } ) return super()._search( num_chunks=num_chunks, chunk_size=chunk_size, all_fields=all_fields, fields=fields, **query_params, ) api-0.45.3/mp_api/client/routes/materials/thermo.py000066400000000000000000000175711475770546700223120ustar00rootroot00000000000000from __future__ import annotations from collections import defaultdict import numpy as np from emmet.core.thermo import ThermoDoc, ThermoType from monty.json import MontyDecoder from pymatgen.analysis.phase_diagram import PhaseDiagram from pymatgen.core import Element from mp_api.client.core import BaseRester from mp_api.client.core.utils import validate_ids class ThermoRester(BaseRester[ThermoDoc]): suffix = "materials/thermo" document_model = ThermoDoc # type: ignore supports_versions = True primary_key = "thermo_id" def search( self, material_ids: str | list[str] | None = None, chemsys: str | list[str] | None = None, energy_above_hull: tuple[float, float] | None = None, equilibrium_reaction_energy: tuple[float, float] | None = None, formation_energy: tuple[float, float] | None = None, formula: str | list[str] | None = None, is_stable: bool | None = None, num_elements: tuple[int, int] | None = None, thermo_ids: list[str] | None = None, thermo_types: list[ThermoType | str] | None = None, total_energy: tuple[float, float] | None = None, uncorrected_energy: tuple[float, float] | None = None, num_chunks: int | None = None, chunk_size: int = 1000, all_fields: bool = True, fields: list[str] | None = None, ) -> list[ThermoDoc] | list[dict]: """Query core thermo docs using a variety of search criteria. Arguments: material_ids (str, List[str]): A single Material ID string or list of strings (e.g., mp-149, [mp-149, mp-13]). chemsys (str, List[str]): A chemical system or list of chemical systems (e.g., Li-Fe-O, Si-*, [Si-O, Li-Fe-P]). energy_above_hull (Tuple[float,float]): Minimum and maximum energy above the hull in eV/atom to consider. equilibrium_reaction_energy (Tuple[float,float]): Minimum and maximum equilibrium reaction energy in eV/atom to consider. formation_energy (Tuple[float,float]): Minimum and maximum formation energy in eV/atom to consider. formula (str, List[str]): A formula including anonymized formula or wild cards (e.g., Fe2O3, ABO3, Si*). A list of chemical formulas can also be passed (e.g., [Fe2O3, ABO3]). is_stable (bool): Whether the material is stable. material_ids (List[str]): List of Materials Project IDs to return data for. thermo_ids (List[str]): List of thermo IDs to return data for. This is a combination of the Materials Project ID and thermo type (e.g. mp-149_GGA_GGA+U). thermo_types (List[ThermoType]): List of thermo types to return data for (e.g. ThermoType.GGA_GGA_U). num_elements (Tuple[int,int]): Minimum and maximum number of elements in the material to consider. total_energy (Tuple[float,float]): Minimum and maximum corrected total energy in eV/atom to consider. uncorrected_energy (Tuple[float,float]): Minimum and maximum uncorrected total energy in eV/atom to consider. num_chunks (int): Maximum number of chunks of data to yield. None will yield all possible. chunk_size (int): Number of data entries per chunk. all_fields (bool): Whether to return all fields in the document. Defaults to True. fields (List[str]): List of fields in ThermoDoc to return data for. Default is material_id and last_updated if all_fields is False. Returns: ([ThermoDoc], [dict]) List of thermo documents or dictionaries. """ query_params = defaultdict(dict) # type: dict if formula: if isinstance(formula, str): formula = [formula] query_params.update({"formula": ",".join(formula)}) if chemsys: if isinstance(chemsys, str): chemsys = [chemsys] query_params.update({"chemsys": ",".join(chemsys)}) if material_ids: if isinstance(material_ids, str): material_ids = [material_ids] query_params.update({"material_ids": ",".join(validate_ids(material_ids))}) if thermo_ids: query_params.update({"thermo_ids": ",".join(validate_ids(thermo_ids))}) if thermo_types: t_types = {t if isinstance(t, str) else t.value for t in thermo_types} valid_types = {*map(str, ThermoType.__members__.values())} if invalid_types := t_types - valid_types: raise ValueError( f"Invalid thermo type(s) passed: {invalid_types}, valid types are: {valid_types}" ) query_params.update({"thermo_types": ",".join(t_types)}) if num_elements: if isinstance(num_elements, int): num_elements = (num_elements, num_elements) query_params.update( {"nelements_min": num_elements[0], "nelements_max": num_elements[1]} ) if is_stable is not None: query_params.update({"is_stable": is_stable}) name_dict = { "total_energy": "energy_per_atom", "formation_energy": "formation_energy_per_atom", "energy_above_hull": "energy_above_hull", "equilibrium_reaction_energy": "equilibrium_reaction_energy_per_atom", "uncorrected_energy": "uncorrected_energy_per_atom", } for param, value in locals().items(): if "energy" in param and value: query_params.update( { f"{name_dict[param]}_min": value[0], f"{name_dict[param]}_max": value[1], } ) query_params = { entry: query_params[entry] for entry in query_params if query_params[entry] is not None } return super()._search( num_chunks=num_chunks, chunk_size=chunk_size, all_fields=all_fields, fields=fields, **query_params, ) def get_phase_diagram_from_chemsys( self, chemsys: str, thermo_type: ThermoType | str ) -> PhaseDiagram: """Get a pre-computed phase diagram for a given chemsys. Arguments: chemsys (str): A chemical system (e.g. Li-Fe-O) thermo_type (ThermoType): The thermo type for the phase diagram. Defaults to ThermoType.GGA_GGA_U. Returns: (PhaseDiagram): Pymatgen phase diagram object. """ t_type = thermo_type if isinstance(thermo_type, str) else thermo_type.value valid_types = {*map(str, ThermoType.__members__.values())} if invalid_types := {t_type} - valid_types: raise ValueError( f"Invalid thermo type(s) passed: {invalid_types}, valid types are: {valid_types}" ) sorted_chemsys = "-".join(sorted(chemsys.split("-"))) phdiag_id = f"thermo_type={t_type}/chemsys={sorted_chemsys}" version = self.db_version.replace(".", "-") obj_key = f"objects/{version}/phase-diagrams/{phdiag_id}.jsonl.gz" pd = self._query_open_data( bucket="materialsproject-build", key=obj_key, decoder=MontyDecoder().decode, )[0][0].get("phase_diagram") # Ensure el_ref keys are Element objects for PDPlotter. # Ensure qhull_data is a numpy array # This should be fixed in pymatgen if pd: for key, entry in list(pd.el_refs.items()): if not isinstance(key, str): break pd.el_refs[Element(str(key))] = entry pd.el_refs.pop(key) if isinstance(pd.qhull_data, list): pd.qhull_data = np.array(pd.qhull_data) return pd # type: ignore api-0.45.3/mp_api/client/routes/materials/xas.py000066400000000000000000000075221475770546700216020ustar00rootroot00000000000000from __future__ import annotations from emmet.core.xas import Edge, Type, XASDoc from pymatgen.core.periodic_table import Element from mp_api.client.core import BaseRester from mp_api.client.core.utils import validate_ids class XASRester(BaseRester[XASDoc]): suffix = "materials/xas" document_model = XASDoc # type: ignore primary_key = "spectrum_id" def search( self, edge: Edge | None = None, absorbing_element: Element | None = None, formula: str | None = None, chemsys: str | list[str] | None = None, elements: list[str] | None = None, material_ids: list[str] | None = None, spectrum_type: Type | None = None, spectrum_ids: str | list[str] | None = None, num_chunks: int | None = None, chunk_size: int = 1000, all_fields: bool = True, fields: list[str] | None = None, ): """Query core XAS docs using a variety of search criteria. Arguments: edge (Edge): The absorption edge (e.g. K, L2, L3, L2,3). absorbing_element (Element): The absorbing element. formula (str): A formula including anonymized formula or wild cards (e.g., Fe2O3, ABO3, Si*). chemsys (str, List[str]): A chemical system or list of chemical systems (e.g., Li-Fe-O, Si-*, [Si-O, Li-Fe-P]). elements (List[str]): A list of elements. material_ids (str, List[str]): A single Material ID string or list of strings (e.g., mp-149, [mp-149, mp-13]). spectrum_type (Type): Spectrum type (e.g. EXAFS, XAFS, or XANES). spectrum_ids (str, List[str]): A single Spectrum ID string or list of strings (e.g., mp-149-XANES-Li-K, [mp-149-XANES-Li-K, mp-13-XANES-Li-K]). num_chunks (int): Maximum number of chunks of data to yield. None will yield all possible. chunk_size (int): Number of data entries per chunk. all_fields (bool): Whether to return all fields in the document. Defaults to True. fields (List[str]): List of fields in MaterialsCoreDoc to return data for. Default is material_id, last_updated, and formula_pretty if all_fields is False. Returns: ([MaterialsDoc]) List of material documents """ query_params = {} if edge: query_params.update({"edge": edge}) if absorbing_element: query_params.update( { "absorbing_element": str(absorbing_element.symbol) if type(absorbing_element) == Element else absorbing_element } ) if spectrum_type: query_params.update({"spectrum_type": spectrum_type}) if formula: query_params.update({"formula": formula}) if chemsys: if isinstance(chemsys, str): chemsys = [chemsys] query_params.update({"chemsys": ",".join(chemsys)}) if elements: query_params.update({"elements": ",".join(elements)}) if material_ids: if isinstance(material_ids, str): material_ids = [material_ids] query_params.update({"material_ids": ",".join(validate_ids(material_ids))}) if spectrum_ids: if isinstance(spectrum_ids, str): spectrum_ids = [spectrum_ids] query_params.update({"spectrum_ids": ",".join(spectrum_ids)}) query_params = { entry: query_params[entry] for entry in query_params if query_params[entry] is not None } return super()._search( num_chunks=num_chunks, chunk_size=chunk_size, all_fields=all_fields, fields=fields, **query_params, ) api-0.45.3/mp_api/client/routes/molecules/000077500000000000000000000000001475770546700204365ustar00rootroot00000000000000api-0.45.3/mp_api/client/routes/molecules/__init__.py000066400000000000000000000010511475770546700225440ustar00rootroot00000000000000from __future__ import annotations from .bonds import MoleculesBondRester from .jcesr import JcesrMoleculesRester from .molecules import AssociatedMoleculeRester, MoleculeRester from .orbitals import MoleculesOrbitalsRester from .partial_charges import MoleculesPartialChargesRester from .partial_spins import MoleculesPartialSpinsRester from .redox import MoleculesRedoxRester from .summary import MoleculesSummaryRester from .tasks import MoleculesTaskRester from .thermo import MoleculesThermoRester from .vibrations import MoleculesVibrationRester api-0.45.3/mp_api/client/routes/molecules/bonds.py000066400000000000000000000123071475770546700221200ustar00rootroot00000000000000from __future__ import annotations from emmet.core.molecules.bonds import MoleculeBondingDoc from emmet.core.mpid import MPculeID from mp_api.client.core import BaseRester class MoleculesBondRester(BaseRester[MoleculeBondingDoc]): suffix = "molecules/bonding" document_model = MoleculeBondingDoc primary_key = "property_id" def search( self, molecule_ids: MPculeID | list[MPculeID] | None = None, property_ids: str | list[str] | None = None, method: str | None = None, bond_type: str | None = None, max_bond_length: float | None = None, min_bond_length: float | None = None, charge: int | None = None, spin_multiplicity: int | None = None, level_of_theory: str | None = None, solvent: str | None = None, lot_solvent: str | None = None, formula: str | list[str] | None = None, elements: list[str] | None = None, exclude_elements: list[str] | None = None, chemsys: str | list[str] | None = None, num_chunks: int | None = None, chunk_size: int = 1000, all_fields: bool = True, fields: list[str] | None = None, ): """Query molecules bonding docs using a variety of search criteria. Arguments: molecule_ids (MPculeID, List[MPculeID]): List of Materials Project Molecule IDs (MPculeIDs) to return data for. property_ids (str, List[str]): List of property IDs to return data for. method (str): Method used to generate bonding data (e.g. "nbo", "critic2", or "OpenBabelNN + metal_edge_extender") bond_type (str): Bond type of interest (e.g. "C-O" for carbon-oxygen bonds) max_bond_length (float): Maximum bond length in the molecule of the specified type min_bond_length (float): Minimum bond length in the molecule of the specified type charge (Tuple[int, int]): Minimum and maximum charge for the molecule. spin_multiplicity (Tuple[int, int]): Minimum and maximum spin for the molecule. level_of_theory (str): Desired level of theory (e.g. "wB97X-V/def2-TZVPPD/SMD") solvent (str): Desired solvent (e.g. "SOLVENT=WATER") lot_solvent (str): Desired combination of level of theory and solvent (e.g. "wB97X-V/def2-TZVPPD/SMD(SOLVENT=THF)") formula (str, List[str]): An alphabetical formula or list of formulas (e.g. "C2 Li2 O4", ["C2 H4", "C2 H6"]). elements (List[str]): A list of elements. exclude_elements (List(str)): List of elements to exclude. chemsys (str, List[str]): A chemical system, list of chemical systems (e.g., Li-C-O, [C-O-H-N, Li-N]). num_chunks (int): Maximum number of chunks of data to yield. None will yield all possible. chunk_size (int): Number of data entries per chunk. all_fields (bool): Whether to return all fields in the document. Defaults to True. fields (List[str]): List of fields in MoleculeDoc to return data for. Default is "molecule_id", "property_id", "solvent", "method", "last_updated" if all_fields is False. Returns: ([MoleculeBondingDoc]) List of bonding documents """ query_params = {} # type: dict if molecule_ids: if isinstance(molecule_ids, str): molecule_ids = [molecule_ids] query_params.update({"molecule_ids": ",".join(molecule_ids)}) if property_ids: if isinstance(property_ids, str): property_ids = [property_ids] query_params.update({"property_ids": ",".join(property_ids)}) if method: query_params.update({"method": method}) if bond_type: query_params.update({"bond_type": bond_type}) if max_bond_length: query_params.update({"max_bond_length": max_bond_length}) if min_bond_length: query_params.update({"min_bond_length": max_bond_length}) if charge: query_params.update({"charge": charge}) if spin_multiplicity: query_params.update({"spin_multiplicity": spin_multiplicity}) if level_of_theory: query_params.update({"level_of_theory": level_of_theory}) if solvent: query_params.update({"solvent": solvent}) if lot_solvent: query_params.update({"lot_solvent": lot_solvent}) if formula: if isinstance(formula, str): formula = [formula] query_params.update({"formula": ",".join(formula)}) if chemsys: if isinstance(chemsys, str): chemsys = [chemsys] query_params.update({"chemsys": ",".join(chemsys)}) if elements: query_params.update({"elements": ",".join(elements)}) if exclude_elements: query_params.update({"exclude_elements": ",".join(exclude_elements)}) return super()._search( num_chunks=num_chunks, chunk_size=chunk_size, all_fields=all_fields, fields=fields, **query_params, ) api-0.45.3/mp_api/client/routes/molecules/jcesr.py000066400000000000000000000073241475770546700221240ustar00rootroot00000000000000from __future__ import annotations from collections import defaultdict from emmet.core.molecules_jcesr import MoleculesDoc from pymatgen.core.periodic_table import Element from mp_api.client.core import BaseRester from mp_api.client.core.utils import validate_ids class JcesrMoleculesRester(BaseRester[MoleculesDoc]): suffix = "molecules/jcesr" document_model = MoleculesDoc # type: ignore primary_key = "task_id" def search( self, task_ids: str | list[str] | None = None, charge: tuple[float, float] | None = None, elements: list[Element] | None = None, EA: tuple[float, float] | None = None, IE: tuple[float, float] | None = None, nelements: tuple[float, float] | None = None, pointgroup: str | None = None, smiles: str | None = None, num_chunks: int | None = None, chunk_size: int = 1000, all_fields: bool = True, fields: list[str] | None = None, ): """Query equations of state docs using a variety of search criteria. Arguments: task_ids (str, List[str]): A single molecule task ID string or list of strings. (e.g., mol-45004, [mol-45004, mol-45228]). charge (Tuple[float,float]): Minimum and maximum value of the charge in +e to consider. elements (List[Element]): A list of elements. film_orientation (List[Elements]): List of elements that are in the molecule. EA (Tuple[float,float]): Minimum and maximum value of the electron affinity in eV to consider. IE (Tuple[float,float]): Minimum and maximum value of the ionization energy in eV to consider. nelements (Tuple[float,float]): Minimum and maximum number of elements in the molecule to consider. pointgroup (str): Point group of the molecule in Schoenflies notation. smiles (str): The simplified molecular input line-entry system (SMILES) representation of the molecule. num_chunks (int): Maximum number of chunks of data to yield. None will yield all possible. chunk_size (int): Number of data entries per chunk. all_fields (bool): Whether to return all fields in the document. Defaults to True. fields (List[str]): List of fields in MoleculesDoc to return data for. Default is the material_id only if all_fields is False. Returns: ([MoleculesDoc]) List of molecule documents """ query_params = defaultdict(dict) # type: dict if task_ids: if isinstance(task_ids, str): task_ids = [task_ids] query_params.update({"task_ids": ",".join(validate_ids(task_ids))}) if elements: query_params.update({"elements": ",".join([str(ele) for ele in elements])}) if pointgroup: query_params.update({"pointgroup": pointgroup}) if smiles: query_params.update({"smiles": smiles}) if nelements: query_params.update( {"nelements_min": nelements[0], "nelements_max": nelements[1]} ) if EA: query_params.update({"EA_min": EA[0], "EA_max": EA[1]}) if IE: query_params.update({"IE_min": IE[0], "IE_max": IE[1]}) if charge: query_params.update({"charge_min": charge[0], "charge_max": charge[1]}) query_params = { entry: query_params[entry] for entry in query_params if query_params[entry] is not None } return super()._search( num_chunks=num_chunks, chunk_size=chunk_size, all_fields=all_fields, fields=fields, **query_params, ) api-0.45.3/mp_api/client/routes/molecules/molecules.py000066400000000000000000000176671475770546700230210ustar00rootroot00000000000000from __future__ import annotations import warnings from emmet.core.mpid import MPculeID from emmet.core.qchem.molecule import MoleculeDoc from emmet.core.settings import EmmetSettings from pymatgen.core.structure import Molecule from mp_api.client.core import BaseRester, MPRestError from mp_api.client.core.utils import validate_ids _EMMET_SETTINGS = EmmetSettings() class BaseMoleculeRester(BaseRester[MoleculeDoc]): document_model = MoleculeDoc primary_key = "molecule_id" def get_molecule_by_mpculeid( self, mpcule_id: str, final: bool = True ) -> Molecule | list[Molecule]: """Get a molecule object for a given Materials Project molecules ID (MPculeID). Arguments: mpcule_id (str): Materials project molecule ID final (bool): Whether to get the final (optimized) molecule, or the list of initial (pre-optimized) structures. Defaults to True. Returns: molecule (Union[Molecule, List[Molecule]]): Pymatgen Molecule object or list of pymatgen Molecule objects. """ field = "molecule" if final else "initial_molecules" response = self.search(molecule_ids=[mpcule_id], fields=[field]) # type: ignore if response: response = ( response[0].model_dump() if self.use_document_model else response[0] # type: ignore ) return response[field] if response else response # type: ignore def find_molecule( self, filename_or_molecule: str | Molecule, charge: int | None = None, spin_multiplicity: int | None = None, tolerance: float = 0.01, allow_multiple_results: bool = False, ) -> list[str] | str: """Finds matching molecules from the Materials Project molecules database (MPcules). Multiple results may be returned of "similar" molecules based on distance using the pymatgen MoleculeMatcher algorithm. Args: filename_or_molecule: filename or Molecule object charge: Molecule charge. Default is None, meaning that the charge will not be used to restrict the output. spin_multiplicity: Molecule's spin multiplicity. Default is None, meaning that the output will not be restricted by spin multiplicity. tolerance: RMSD difference threshold for MoleculeMatcher allow_multiple_results: changes return type for either a single mpcule_id or list of mpcule_ids Returns: A matching mpcule_id if one is found or list of results if allow_multiple_results is True Raises: MPRestError """ if isinstance(filename_or_molecule, str): m = Molecule.from_file(filename_or_molecule) elif isinstance(filename_or_molecule, Molecule): m = filename_or_molecule else: raise MPRestError("Provide filename or Structure object.") results = self._post_resource( body=m.as_dict(), params={ "tolerance": tolerance, "charge": charge, "spin_multiplicity": spin_multiplicity, }, suburl="find_molecule", use_document_model=False, ).get("data") if len(results) > 1: # type: ignore if not allow_multiple_results: raise ValueError( "Multiple matches found for this combination of tolerances, but " "`allow_multiple_results` set to False." ) return results # type: ignore if results: return results[0]["molecule_id"] else: return [] def search( self, charge: tuple[int, int] | None = None, spin_multiplicity: tuple[int, int] | None = None, nelements: tuple[int, int] | None = None, chemsys: str | list[str] | None = None, deprecated: bool | None = None, elements: list[str] | None = None, exclude_elements: list[str] | None = None, formula: str | list[str] | None = None, molecule_ids: MPculeID | list[MPculeID] | None = None, task_ids: str | list[str] | None = None, num_chunks: int | None = None, chunk_size: int = 1000, all_fields: bool = True, fields: list[str] | None = None, ): """Query molecule docs using a variety of search criteria. Arguments: charge (Tuple[int, int]): Minimum and maximum charge for the molecule. spin_multiplicity (Tuple[int, int]): Minimum and maximum spin for the molecule. nelements (Tuple[int, int]): Minimum and maximum number of elements chemsys (str, List[str]): A chemical system, list of chemical systems (e.g., Li-C-O, [C-O-H-N, Li-N]). deprecated (bool): Whether the material is tagged as deprecated. elements (List[str]): A list of elements. exclude_elements (List(str)): List of elements to exclude. formula (str, List[str]): An alphabetical formula or list of formulas (e.g. "C2 Li2 O4", ["C2 H4", "C2 H6"]). molecule_ids (MPculeID, List[MPculeID]): List of Materials Project Molecule IDs (MPculeIDs) to return data for. task_ids (str, List[str]): List of Materials Project IDs to return data for. num_chunks (int): Maximum number of chunks of data to yield. None will yield all possible. chunk_size (int): Number of data entries per chunk. all_fields (bool): Whether to return all fields in the document. Defaults to True. fields (List[str]): List of fields in MoleculeDoc to return data for. Default is molecule_id, last_updated, and formula_alphabetical if all_fields is False. Returns: ([MoleculeDoc]) List of molecules documents """ query_params = {"deprecated": deprecated} # type: dict if molecule_ids: if isinstance(molecule_ids, str): molecule_ids = [molecule_ids] query_params.update({"molecule_ids": ",".join(molecule_ids)}) if charge: query_params.update({"charge": charge}) if spin_multiplicity: query_params.update({"spin_multiplicity": spin_multiplicity}) if formula: if isinstance(formula, str): formula = [formula] query_params.update({"formula": ",".join(formula)}) if chemsys: if isinstance(chemsys, str): chemsys = [chemsys] query_params.update({"chemsys": ",".join(chemsys)}) if elements: query_params.update({"elements": ",".join(elements)}) if exclude_elements: query_params.update({"exclude_elements": ",".join(exclude_elements)}) if task_ids: if isinstance(task_ids, str): task_ids = [task_ids] query_params.update({"task_ids": ",".join(validate_ids(task_ids))}) query_params = { entry: query_params[entry] for entry in query_params if query_params[entry] is not None } return super()._search( num_chunks=num_chunks, chunk_size=chunk_size, all_fields=all_fields, fields=fields, **query_params, ) class AssociatedMoleculeRester(BaseMoleculeRester): suffix = "molecules/assoc" class MoleculeRester(BaseMoleculeRester): suffix = "molecules/core" _sub_resters = ["summary", "jcesr"] def __getattribute__(self, attr): if "jcesr" in attr: warnings.warn( "NOTE: You are accessing the unmaintained legacy molecules data, " "please use MPRester.molecules.summary." ) return super().__getattribute__(attr) def __dir__(self): return dir(MoleculeRester) + self._sub_resters api-0.45.3/mp_api/client/routes/molecules/orbitals.py000066400000000000000000000310731475770546700226330ustar00rootroot00000000000000from __future__ import annotations from emmet.core.molecules.orbitals import OrbitalDoc from emmet.core.mpid import MPculeID from mp_api.client.core import BaseRester class MoleculesOrbitalsRester(BaseRester[OrbitalDoc]): suffix = "molecules/orbitals" document_model = OrbitalDoc primary_key = "property_id" def search( self, molecule_ids: MPculeID | list[MPculeID] | None = None, property_ids: str | list[str] | None = None, charge: int | None = None, spin_multiplicity: int | None = None, level_of_theory: str | None = None, solvent: str | None = None, lot_solvent: str | None = None, formula: str | list[str] | None = None, elements: list[str] | None = None, exclude_elements: list[str] | None = None, chemsys: str | list[str] | None = None, electron_type_population: str | None = None, core_electrons: tuple[float, float] | None = None, valence_electrons: tuple[float, float] | None = None, rydberg_electrons: tuple[float, float] | None = None, total_electrons: tuple[float, float] | None = None, electron_type_lp: str | None = None, lp_type: str | None = None, s_character: tuple[float, float] | None = None, p_character: tuple[float, float] | None = None, d_character: tuple[float, float] | None = None, f_character: tuple[float, float] | None = None, lp_occupancy: tuple[float, float] | None = None, electron_type_bond: str | None = None, bond_type: str | None = None, s_character_atom1: tuple[float, float] | None = None, s_character_atom2: tuple[float, float] | None = None, p_character_atom1: tuple[float, float] | None = None, p_character_atom2: tuple[float, float] | None = None, d_character_atom1: tuple[float, float] | None = None, d_character_atom2: tuple[float, float] | None = None, f_character_atom1: tuple[float, float] | None = None, f_character_atom2: tuple[float, float] | None = None, polarization_atom1: tuple[float, float] | None = None, polarization_atom2: tuple[float, float] | None = None, bond_occupancy: tuple[float, float] | None = None, electron_type_interaction: str | None = None, donor_type: str | None = None, acceptor_type: str | None = None, perturbation_energy: tuple[float, float] | None = None, energy_difference: tuple[float, float] | None = None, fock_element: tuple[float, float] | None = None, num_chunks: int | None = None, chunk_size: int = 1000, all_fields: bool = True, fields: list[str] | None = None, ): """Query molecules redox docs using a variety of search criteria. Arguments: molecule_ids (MPculeID, List[MPculeID]): List of Materials Project Molecule IDs (MPculeIDs) to return data for. property_ids (str, List[str]): List of property IDs to return data for. charge (Tuple[int, int]): Minimum and maximum charge for the molecule. spin_multiplicity (Tuple[int, int]): Minimum and maximum spin for the molecule. level_of_theory (str): Desired level of theory (e.g. "wB97X-V/def2-TZVPPD/SMD") solvent (str): Desired solvent (e.g. "SOLVENT=WATER") lot_solvent (str): Desired combination of level of theory and solvent (e.g. "wB97X-V/def2-TZVPPD/SMD(SOLVENT=THF)") correction_level_of_theory (str): Desired correction level of theory (e.g. "wB97X-V/def2-TZVPPD/SMD") correction_solvent (str): Desired correction solvent (e.g. "SOLVENT=WATER") correction_lot_solvent (str): Desired correction combination of level of theory and solvent (e.g. "wB97X-V/def2-TZVPPD/SMD(SOLVENT=THF)") combined_lot_solvent (str): Desired combination of level of theory and solvent including both main thermo calculation and single-point energy correction (e.g. "wB97X-D/def2-SVPD/VACUUM//wB97X-V/def2-TZVPPD/SMD(SOLVENT=THF)") formula (str, List[str]): An alphabetical formula or list of formulas (e.g. "C2 Li2 O4", ["C2 H4", "C2 H6"]). elements (List[str]): A list of elements. exclude_elements (List(str)): List of elements to exclude. chemsys (str, List[str]): A chemical system, list of chemical systems (e.g., Li-C-O, [C-O-H-N, Li-N]). electron_type_population (str): Should alpha ('alpha'), beta ('beta'), or all electrons (None) be considered in a query of natural electron populations? core_electrons (Tuple[float, float]): Minimum and maximum number of core electrons in an atom in this molecule. valence_electrons (Tuple[float, float]): Minimum and maximum number of valence electrons in an atom in this molecule. rydberg_electrons (Tuple[float, float]): Minimum and maximum number of rydberg electrons in an atom in this molecule. total_electrons: (Tuple[float, float]): Minimum and maximum number of total electrons in an atom in this molecule. electron_type_lp (str): Should alpha ('alpha'), beta ('beta'), or all electrons (None) be considered in a query of lone pairs? lp_type (str): Type of orbital - "LP" for "lone pair" or "LV" for "lone vacant" s_character (Tuple[float, float]): Min and max percentage of the lone pair constituted by s atomic orbitals. p_character (Tuple[float, float]): Min and max percentage of the lone pair constituted by p atomic orbitals. d_character (Tuple[float, float]): Min and max percentage of the lone pair constituted by d atomic orbitals. f_character (Tuple[float, float]): Min and max percentage of the lone pair constituted by f atomic orbitals. lp_occupancy(Tuple[float, float]): Min and max number of electrons in the lone pair. electron_type_bond (str): Should alpha ('alpha'), beta ('beta'), or all electrons (None) be considered in a query of bonds? bond_type (str): Type of orbital, e.g. "BD" for bonding or "BD*" for antibonding s_character_atom1 (Tuple[float, float]): Min and max percentage of the bond constituted by s atomic orbitals on the first atom. s_character_atom2 (Tuple[float, float]): Min and max percentage of the bond constituted by s atomic orbitals on the second atom. p_character_atom1 (Tuple[float, float]): Min and max percentage of the bond constituted by p atomic orbitals on the first atom. p_character_atom2 (Tuple[float, float]): Min and max percentage of the bond constituted by p atomic orbitals on the second atom. d_character_atom1 (Tuple[float, float]): Min and max percentage of the bond constituted by d atomic orbitals on the first atom. d_character_atom2 (Tuple[float, float]): Min and max percentage of the bond constituted by d atomic orbitals on the second atom. f_character_atom1 (Tuple[float, float]): Min and max percentage of the bond constituted by f atomic orbitals on the first atom. f_character_atom2 (Tuple[float, float]): Min and max percentage of the bond constituted by f atomic orbitals on the second atom. polarization_atom1 (Tuple[float, float]): Min and max fraction of electrons in the bond donated by the first atom. polarization_atom2 (Tuple[float, float]): Min and max fraction of electrons in the bond donated by the second atom. bond_occupancy (Tuple[float, float]): Min and max number of electrons in the bond. electron_type_interaction (str): Should alpha ('alpha'), beta ('beta'), or all electrons (None) be considered in a query of orbital interactions? donor_type (str): Type of donor orbital, e.g. 'BD' for bonding or 'RY*' for anti-Rydberg acceptor_type (str): Type of acceptor orbital, e.g. 'BD' for bonding or 'RY*' for anti-Rydberg perturbation_energy (Tuple[float, float]): Min and max perturbation energy of the interaction energy_difference (Tuple[float, float]): Min and max energy difference between interacting orbitals fock_element (Tuple[float, float]): Min and max interaction Fock matrix element num_chunks (int): Maximum number of chunks of data to yield. None will yield all possible. chunk_size (int): Number of data entries per chunk. all_fields (bool): Whether to return all fields in the document. Defaults to True. fields (List[str]): List of fields in MoleculeDoc to return data for. Default is "molecule_id", "property_id", "solvent", "method", "last_updated" if all_fields is False. Returns: ([RedoxDoc]) List of molecule redox documents """ query_params = {} # type: dict min_max = [ "core_electrons", "valence_electrons", "rydberg_electrons", "total_electrons", "s_character", "p_character", "d_character", "f_character", "lp_occupancy", "s_character_atom1", "s_character_atom2", "p_character_atom1", "p_character_atom2", "d_character_atom1", "d_character_atom2", "f_character_atom1", "f_character_atom2", "polarization_atom1", "polarization_atom2", "bond_occupancy", "perturbation_energy", "energy_difference", "fock_element", ] for param, value in locals().items(): if param in min_max and value: if isinstance(value, (int, float)): value = (value, value) query_params.update( { f"min_{param}": value[0], f"max_{param}": value[1], } ) if molecule_ids: if isinstance(molecule_ids, str): molecule_ids = [molecule_ids] query_params.update({"molecule_ids": ",".join(molecule_ids)}) if property_ids: if isinstance(property_ids, str): property_ids = [property_ids] query_params.update({"property_ids": ",".join(property_ids)}) if charge: query_params.update({"charge": charge}) if spin_multiplicity: query_params.update({"spin_multiplicity": spin_multiplicity}) if level_of_theory: query_params.update({"level_of_theory": level_of_theory}) if solvent: query_params.update({"solvent": solvent}) if lot_solvent: query_params.update({"lot_solvent": lot_solvent}) if formula: if isinstance(formula, str): formula = [formula] query_params.update({"formula": ",".join(formula)}) if chemsys: if isinstance(chemsys, str): chemsys = [chemsys] query_params.update({"chemsys": ",".join(chemsys)}) if elements: query_params.update({"elements": ",".join(elements)}) if exclude_elements: query_params.update({"exclude_elements": ",".join(exclude_elements)}) if electron_type_population: query_params.update({"electron_type_population": electron_type_population}) if electron_type_lp: query_params.update({"electron_type_lp": electron_type_lp}) if lp_type: query_params.update({"lp_type": lp_type}) if electron_type_bond: query_params.update({"electron_type_bond": electron_type_bond}) if bond_type: query_params.update({"bond_type": bond_type}) if electron_type_interaction: query_params.update( {"electron_type_interaction": electron_type_interaction} ) if donor_type: query_params.update({"donor_type": donor_type}) if acceptor_type: query_params.update({"acceptor_type": acceptor_type}) return super()._search( num_chunks=num_chunks, chunk_size=chunk_size, all_fields=all_fields, fields=fields, **query_params, ) api-0.45.3/mp_api/client/routes/molecules/partial_charges.py000066400000000000000000000110461475770546700241420ustar00rootroot00000000000000from __future__ import annotations from emmet.core.molecules.atomic import PartialChargesDoc from emmet.core.mpid import MPculeID from mp_api.client.core import BaseRester class MoleculesPartialChargesRester(BaseRester[PartialChargesDoc]): suffix = "molecules/partial_charges" document_model = PartialChargesDoc primary_key = "property_id" def search( self, molecule_ids: MPculeID | list[MPculeID] | None = None, property_ids: str | list[str] | None = None, method: str | None = None, charge: int | None = None, spin_multiplicity: int | None = None, level_of_theory: str | None = None, solvent: str | None = None, lot_solvent: str | None = None, formula: str | list[str] | None = None, elements: list[str] | None = None, exclude_elements: list[str] | None = None, chemsys: str | list[str] | None = None, num_chunks: int | None = None, chunk_size: int = 1000, all_fields: bool = True, fields: list[str] | None = None, ): """Query molecules partial charges docs using a variety of search criteria. Arguments: molecule_ids (MPculeID, List[MPculeID]): List of Materials Project Molecule IDs (MPculeIDs) to return data for. property_ids (str, List[str]): List of property IDs to return data for. method (str): Method used to generate bonding data (e.g. "nbo", "critic2", "mulliken", or "resp") charge (Tuple[int, int]): Minimum and maximum charge for the molecule. spin_multiplicity (Tuple[int, int]): Minimum and maximum spin for the molecule. level_of_theory (str): Desired level of theory (e.g. "wB97X-V/def2-TZVPPD/SMD") solvent (str): Desired solvent (e.g. "SOLVENT=WATER") lot_solvent (str): Desired combination of level of theory and solvent (e.g. "wB97X-V/def2-TZVPPD/SMD(SOLVENT=THF)") formula (str, List[str]): An alphabetical formula or list of formulas (e.g. "C2 Li2 O4", ["C2 H4", "C2 H6"]). elements (List[str]): A list of elements. exclude_elements (List(str)): List of elements to exclude. chemsys (str, List[str]): A chemical system, list of chemical systems (e.g., Li-C-O, [C-O-H-N, Li-N]). num_chunks (int): Maximum number of chunks of data to yield. None will yield all possible. chunk_size (int): Number of data entries per chunk. all_fields (bool): Whether to return all fields in the document. Defaults to True. fields (List[str]): List of fields in MoleculeDoc to return data for. Default is "molecule_id", "property_id", "solvent", "method", "last_updated" if all_fields is False. Returns: ([PartialChargesDoc]) List of partial charges documents """ query_params = {} # type: dict if molecule_ids: if isinstance(molecule_ids, str): molecule_ids = [molecule_ids] query_params.update({"molecule_ids": ",".join(molecule_ids)}) if property_ids: if isinstance(property_ids, str): property_ids = [property_ids] query_params.update({"property_ids": ",".join(property_ids)}) if method: query_params.update({"method": method}) if charge: query_params.update({"charge": charge}) if spin_multiplicity: query_params.update({"spin_multiplicity": spin_multiplicity}) if level_of_theory: query_params.update({"level_of_theory": level_of_theory}) if solvent: query_params.update({"solvent": solvent}) if lot_solvent: query_params.update({"lot_solvent": lot_solvent}) if formula: if isinstance(formula, str): formula = [formula] query_params.update({"formula": ",".join(formula)}) if chemsys: if isinstance(chemsys, str): chemsys = [chemsys] query_params.update({"chemsys": ",".join(chemsys)}) if elements: query_params.update({"elements": ",".join(elements)}) if exclude_elements: query_params.update({"exclude_elements": ",".join(exclude_elements)}) return super()._search( num_chunks=num_chunks, chunk_size=chunk_size, all_fields=all_fields, fields=fields, **query_params, ) api-0.45.3/mp_api/client/routes/molecules/partial_spins.py000066400000000000000000000110041475770546700236540ustar00rootroot00000000000000from __future__ import annotations from emmet.core.molecules.atomic import PartialSpinsDoc from emmet.core.mpid import MPculeID from mp_api.client.core import BaseRester class MoleculesPartialSpinsRester(BaseRester[PartialSpinsDoc]): suffix = "molecules/partial_spins" document_model = PartialSpinsDoc primary_key = "property_id" def search( self, molecule_ids: MPculeID | list[MPculeID] | None = None, property_ids: str | list[str] | None = None, method: str | None = None, charge: int | None = None, spin_multiplicity: int | None = None, level_of_theory: str | None = None, solvent: str | None = None, lot_solvent: str | None = None, formula: str | list[str] | None = None, elements: list[str] | None = None, exclude_elements: list[str] | None = None, chemsys: str | list[str] | None = None, num_chunks: int | None = None, chunk_size: int = 1000, all_fields: bool = True, fields: list[str] | None = None, ): """Query molecules partial spins docs using a variety of search criteria. Arguments: molecule_ids (MPculeID, List[MPculeID]): List of Materials Project Molecule IDs (MPculeIDs) to return data for. property_ids (str, List[str]): List of property IDs to return data for. method (str): Method used to generate bonding data (e.g. "nbo" or "mulliken") charge (Tuple[int, int]): Minimum and maximum charge for the molecule. spin_multiplicity (Tuple[int, int]): Minimum and maximum spin for the molecule. level_of_theory (str): Desired level of theory (e.g. "wB97X-V/def2-TZVPPD/SMD") solvent (str): Desired solvent (e.g. "SOLVENT=WATER") lot_solvent (str): Desired combination of level of theory and solvent (e.g. "wB97X-V/def2-TZVPPD/SMD(SOLVENT=THF)") formula (str, List[str]): An alphabetical formula or list of formulas (e.g. "C2 Li2 O4", ["C2 H4", "C2 H6"]). elements (List[str]): A list of elements. exclude_elements (List(str)): List of elements to exclude. chemsys (str, List[str]): A chemical system, list of chemical systems (e.g., Li-C-O, [C-O-H-N, Li-N]). num_chunks (int): Maximum number of chunks of data to yield. None will yield all possible. chunk_size (int): Number of data entries per chunk. all_fields (bool): Whether to return all fields in the document. Defaults to True. fields (List[str]): List of fields in MoleculeDoc to return data for. Default is "molecule_id", "property_id", "solvent", "method", "last_updated" if all_fields is False. Returns: ([PartialSpinsDoc]) List of partial charges documents """ query_params = {} # type: dict if molecule_ids: if isinstance(molecule_ids, str): molecule_ids = [molecule_ids] query_params.update({"molecule_ids": ",".join(molecule_ids)}) if property_ids: if isinstance(property_ids, str): property_ids = [property_ids] query_params.update({"property_ids": ",".join(property_ids)}) if method: query_params.update({"method": method}) if charge: query_params.update({"charge": charge}) if spin_multiplicity: query_params.update({"spin_multiplicity": spin_multiplicity}) if level_of_theory: query_params.update({"level_of_theory": level_of_theory}) if solvent: query_params.update({"solvent": solvent}) if lot_solvent: query_params.update({"lot_solvent": lot_solvent}) if formula: if isinstance(formula, str): formula = [formula] query_params.update({"formula": ",".join(formula)}) if chemsys: if isinstance(chemsys, str): chemsys = [chemsys] query_params.update({"chemsys": ",".join(chemsys)}) if elements: query_params.update({"elements": ",".join(elements)}) if exclude_elements: query_params.update({"exclude_elements": ",".join(exclude_elements)}) return super()._search( num_chunks=num_chunks, chunk_size=chunk_size, all_fields=all_fields, fields=fields, **query_params, ) api-0.45.3/mp_api/client/routes/molecules/redox.py000066400000000000000000000161151475770546700221350ustar00rootroot00000000000000from __future__ import annotations from emmet.core.molecules.redox import RedoxDoc from emmet.core.mpid import MPculeID from mp_api.client.core import BaseRester class MoleculesRedoxRester(BaseRester[RedoxDoc]): suffix = "molecules/redox" document_model = RedoxDoc primary_key = "property_id" def search( self, molecule_ids: MPculeID | list[MPculeID] | None = None, property_ids: str | list[str] | None = None, charge: int | None = None, spin_multiplicity: int | None = None, level_of_theory: str | None = None, solvent: str | None = None, lot_solvent: str | None = None, formula: str | list[str] | None = None, elements: list[str] | None = None, exclude_elements: list[str] | None = None, chemsys: str | list[str] | None = None, electrode: str | None = None, min_reduction_potential: float | None = None, max_reduction_potential: float | None = None, min_oxidation_potential: float | None = None, max_oxidation_potential: float | None = None, electron_affinity: tuple[float, float] | None = None, ionization_energy: tuple[float, float] | None = None, reduction_energy: tuple[float, float] | None = None, reduction_free_energy: tuple[float, float] | None = None, oxidation_energy: tuple[float, float] | None = None, oxidation_free_energy: tuple[float, float] | None = None, num_chunks: int | None = None, chunk_size: int = 1000, all_fields: bool = True, fields: list[str] | None = None, ): """Query molecules redox docs using a variety of search criteria. Arguments: molecule_ids (MPculeID, List[MPculeID]): List of Materials Project Molecule IDs (MPculeIDs) to return data for. property_ids (str, List[str]): List of property IDs to return data for. charge (Tuple[int, int]): Minimum and maximum charge for the molecule. spin_multiplicity (Tuple[int, int]): Minimum and maximum spin for the molecule. level_of_theory (str): Desired level of theory (e.g. "wB97X-V/def2-TZVPPD/SMD") solvent (str): Desired solvent (e.g. "SOLVENT=WATER") lot_solvent (str): Desired combination of level of theory and solvent (e.g. "wB97X-V/def2-TZVPPD/SMD(SOLVENT=THF)") formula (str, List[str]): An alphabetical formula or list of formulas (e.g. "C2 Li2 O4", ["C2 H4", "C2 H6"]). elements (List[str]): A list of elements. exclude_elements (List(str)): List of elements to exclude. chemsys (str, List[str]): A chemical system, list of chemical systems (e.g., Li-C-O, [C-O-H-N, Li-N]). electrode (str): For redox potential queries, a string representation of the reference electrode (currently accepted: "H", "Li", "Mg", "Ca") min_reduction_potential (float): Minimum reduction potential considered max_reduction_potential (float): Maximum reduction potential considered min_oxidation_potential (float): Minimum oxidation potential considered max_oxidation_potential (float): Maximum oxidation potential considered electron_affinity (Tuple[float, float]): Minimum and maximum electron affinities ionization_energy (Tuple[float, float]): Minimum and maximum ionization energies reduction_energy (Tuple[float, float]): Minimum and maximum reduction energies reduction_free_energy (Tuple[float, float]): Minimum and maximum reduction free energies oxidation_energy (Tuple[float, float]): Minimum and maximum oxidation energies oxidation_free_energy (Tuple[float, float]): Minimum and maximum oxidation free energies num_chunks (int): Maximum number of chunks of data to yield. None will yield all possible. chunk_size (int): Number of data entries per chunk. all_fields (bool): Whether to return all fields in the document. Defaults to True. fields (List[str]): List of fields in MoleculeDoc to return data for. Default is "molecule_id", "property_id", "solvent", "method", "last_updated" if all_fields is False. Returns: ([RedoxDoc]) List of molecule redox documents """ query_params = {} # type: dict min_max = [ "electron_affinity", "ionization_energy", "reduction_energy", "reduction_free_energy", "oxidation_energy", "oxidation_free_energy", ] for param, value in locals().items(): if param in min_max and value: if isinstance(value, (int, float)): value = (value, value) query_params.update( { f"{param}_min": value[0], f"{param}_max": value[1], } ) if molecule_ids: if isinstance(molecule_ids, str): molecule_ids = [molecule_ids] query_params.update({"molecule_ids": ",".join(molecule_ids)}) if property_ids: if isinstance(property_ids, str): property_ids = [property_ids] query_params.update({"property_ids": ",".join(property_ids)}) if charge: query_params.update({"charge": charge}) if spin_multiplicity: query_params.update({"spin_multiplicity": spin_multiplicity}) if level_of_theory: query_params.update({"level_of_theory": level_of_theory}) if solvent: query_params.update({"solvent": solvent}) if lot_solvent: query_params.update({"lot_solvent": lot_solvent}) if formula: if isinstance(formula, str): formula = [formula] query_params.update({"formula": ",".join(formula)}) if chemsys: if isinstance(chemsys, str): chemsys = [chemsys] query_params.update({"chemsys": ",".join(chemsys)}) if elements: query_params.update({"elements": ",".join(elements)}) if exclude_elements: query_params.update({"exclude_elements": ",".join(exclude_elements)}) if electrode: query_params.update({"electrode": electrode}) if min_reduction_potential: query_params.update({"min_reduction_potential": min_reduction_potential}) if max_reduction_potential: query_params.update({"max_reduction_potential": max_reduction_potential}) if min_oxidation_potential: query_params.update({"min_oxidation_potential": min_oxidation_potential}) if max_oxidation_potential: query_params.update({"max_oxidation_potential": max_oxidation_potential}) return super()._search( num_chunks=num_chunks, chunk_size=chunk_size, all_fields=all_fields, fields=fields, **query_params, ) api-0.45.3/mp_api/client/routes/molecules/summary.py000066400000000000000000000130211475770546700225020ustar00rootroot00000000000000from __future__ import annotations from collections import defaultdict from emmet.core.molecules.summary import HasProps, MoleculeSummaryDoc from emmet.core.mpid import MPculeID from mp_api.client.core import BaseRester class MoleculesSummaryRester(BaseRester[MoleculeSummaryDoc]): suffix = "molecules/summary" document_model = MoleculeSummaryDoc # type: ignore primary_key = "molecule_id" def search( self, charge: int | None = None, spin_multiplicity: int | None = None, nelements: tuple[int, int] | None = None, chemsys: str | list[str] | None = None, deprecated: bool | None = None, elements: list[str] | None = None, exclude_elements: list[str] | None = None, formula: str | list[str] | None = None, has_props: list[HasProps] | None = None, molecule_ids: list[MPculeID] | None = None, # has_solvent: Optional[Union[str, List[str]]] = None, # has_level_of_theory: Optional[Union[str, List[str]]] = None, # has_lot_solvent: Optional[Union[str, List[str]]] = None, # with_solvent: Optional[str] = None, # num_sites: Optional[Tuple[int, int]] = None, num_chunks: int | None = None, chunk_size: int = 1000, all_fields: bool = True, fields: list[str] | None = None, ): """Query core data using a variety of search criteria. Arguments: charge (int): Minimum and maximum charge for the molecule. spin_multiplicity (int): Minimum and maximum spin for the molecule. nelements (Tuple[int, int]): Minimum and maximum number of elements # has_solvent (str, List[str]): Whether the molecule has properties calculated in # solvents (e.g., "SOLVENT=THF", ["SOLVENT=WATER", "VACUUM"]) # has_level_of_theory (str, List[str]): Whether the molecule has properties calculated # using a particular level of theory (e.g. "wB97M-V/def2-SVPD/SMD", # ["wB97X-V/def2-TZVPPD/SMD", "wB97M-V/def2-QZVPPD/SMD"]) # has_lot_solvent (str, List[str]): Whether the molecule has properties calculated # using a particular combination of level of theory and solvent (e.g. # "wB97X-V/def2-SVPD/SMD(SOLVENT=THF)", # ["wB97X-V/def2-TZVPPD/SMD(VACUUM)", "wB97M-V/def2-QZVPPD/SMD(SOLVENT=WATER)"]) chemsys (str, List[str]): A chemical system, list of chemical systems (e.g., Li-C-O, [C-O-H-N, Li-N]). deprecated (bool): Whether the material is tagged as deprecated. elements (List[str]): A list of elements. exclude_elements (List(str)): List of elements to exclude. formula (str, List[str]): An alphabetical formula or list of formulas (e.g. "C2 Li2 O4", ["C2 H4", "C2 H6"]). has_props: (List[HasProps]): The calculated properties available for the material. molecule_ids (List[MPculeID]): List of Materials Project Molecule IDs (MPculeIDs) to return data for. num_chunks (int): Maximum number of chunks of data to yield. None will yield all possible. chunk_size (int): Number of data entries per chunk. all_fields (bool): Whether to return all fields in the document. Defaults to True. fields (List[str]): List of fields in SearchDoc to return data for. Default is material_id if all_fields is False. Returns: ([MoleculeSummaryDoc]) List of molecules summary documents """ query_params = defaultdict(dict) # type: dict min_max = [ "nelements", "ionization_energy", "electron_affinity", "reduction_free_energy", "oxidation_free_energy", ] for param, value in locals().items(): if param in min_max and value: if isinstance(value, (int, float)): value = (value, value) query_params.update( { f"{param}_min": value[0], f"{param}_max": value[1], } ) if molecule_ids: query_params.update({"molecule_ids": ",".join(molecule_ids)}) if charge: query_params.update({"charge": charge}) if spin_multiplicity: query_params.update({"spin_multiplicity": spin_multiplicity}) if deprecated is not None: query_params.update({"deprecated": deprecated}) if formula: if isinstance(formula, str): formula = [formula] query_params.update({"formula": ",".join(formula)}) if chemsys: if isinstance(chemsys, str): chemsys = [chemsys] query_params.update({"chemsys": ",".join(chemsys)}) if elements: query_params.update({"elements": ",".join(elements)}) if exclude_elements is not None: query_params.update({"exclude_elements": ",".join(exclude_elements)}) if has_props: query_params.update({"has_props": ",".join([i.value for i in has_props])}) query_params = { entry: query_params[entry] for entry in query_params if query_params[entry] is not None } return super()._search( num_chunks=num_chunks, chunk_size=chunk_size, all_fields=all_fields, fields=fields, **query_params, ) api-0.45.3/mp_api/client/routes/molecules/tasks.py000066400000000000000000000051371475770546700221430ustar00rootroot00000000000000from __future__ import annotations from emmet.core.qchem.task import TaskDocument from mp_api.client.core import BaseRester from mp_api.client.core.utils import validate_ids class MoleculesTaskRester(BaseRester[TaskDocument]): suffix = "molecules/tasks" document_model = TaskDocument primary_key = "task_id" # TODO: get_trajectory method (once PR in pymatgen) def search( self, task_ids: list[str] | None = None, chemsys: str | list[str] | None = None, elements: list[str] | None = None, exclude_elements: list[str] | None = None, formula: str | list[str] | None = None, num_chunks: int | None = None, chunk_size: int = 1000, all_fields: bool = True, fields: list[str] | None = None, ): """Query core task docs using a variety of search criteria. Arguments: task_ids (List[str]): List of Materials Project IDs to return data for. chemsys (str, List[str]): A chemical system or list of chemical systems (e.g., C-H-O, [C-Li-O, Li-O]). elements (List[str]): A list of elements. exclude_elements (List[str]): A list of elements to exclude. formula (str, List[str]): An alphabetical formula (e.g. "C1 Li2 O3" or ["C2 H4", "C2 H6"]). num_chunks (int): Maximum number of chunks of data to yield. None will yield all possible. chunk_size (int): Number of data entries per chunk. Max size is 100. all_fields (bool): Whether to return all fields in the document. Defaults to True. fields (List[str]): List of fields in TaskDocument to return data for. Default is material_id, last_updated, and formula_pretty if all_fields is False. Returns: ([TaskDocument]) List of task documents """ query_params = {} # type: dict if task_ids: query_params.update({"task_ids": ",".join(validate_ids(task_ids))}) if formula: query_params.update({"formula": formula}) if elements: query_params.update({"elements": ",".join(elements)}) if exclude_elements: query_params.update({"exclude_elements": ",".join(exclude_elements)}) if chemsys: if isinstance(chemsys, str): chemsys = [chemsys] query_params.update({"chemsys": ",".join(chemsys)}) return super()._search( num_chunks=num_chunks, chunk_size=chunk_size, all_fields=all_fields, fields=fields, **query_params, ) api-0.45.3/mp_api/client/routes/molecules/thermo.py000066400000000000000000000200221475770546700223020ustar00rootroot00000000000000from __future__ import annotations from emmet.core.molecules.thermo import MoleculeThermoDoc from emmet.core.mpid import MPculeID from mp_api.client.core import BaseRester class MoleculesThermoRester(BaseRester[MoleculeThermoDoc]): suffix = "molecules/thermo" document_model = MoleculeThermoDoc primary_key = "property_id" def search( self, molecule_ids: MPculeID | list[MPculeID] | None = None, property_ids: str | list[str] | None = None, charge: int | None = None, spin_multiplicity: int | None = None, level_of_theory: str | None = None, solvent: str | None = None, lot_solvent: str | None = None, correction_level_of_theory: str | None = None, correction_solvent: str | None = None, correction_lot_solvent: str | None = None, combined_lot_solvent: str | None = None, electronic_energy: tuple[float, float] | None = None, zero_point_energy: tuple[float, float] | None = None, total_enthalpy: tuple[float, float] | None = None, total_entropy: tuple[float, float] | None = None, translational_enthalpy: tuple[float, float] | None = None, rotational_enthalpy: tuple[float, float] | None = None, vibrational_enthalpy: tuple[float, float] | None = None, translational_entropy: tuple[float, float] | None = None, rotational_entropy: tuple[float, float] | None = None, vibrational_entropy: tuple[float, float] | None = None, free_energy: tuple[float, float] | None = None, formula: str | list[str] | None = None, elements: list[str] | None = None, exclude_elements: list[str] | None = None, chemsys: str | list[str] | None = None, num_chunks: int | None = None, chunk_size: int = 1000, all_fields: bool = True, fields: list[str] | None = None, ): """Query molecules thermo docs using a variety of search criteria. Arguments: molecule_ids (MPculeID, List[MPculeID]): List of Materials Project Molecule IDs (MPculeIDs) to return data for. property_ids (str, List[str]): List of property IDs to return data for. charge (Tuple[int, int]): Minimum and maximum charge for the molecule. spin_multiplicity (Tuple[int, int]): Minimum and maximum spin for the molecule. level_of_theory (str): Desired level of theory (e.g. "wB97X-V/def2-TZVPPD/SMD") solvent (str): Desired solvent (e.g. "SOLVENT=WATER") lot_solvent (str): Desired combination of level of theory and solvent (e.g. "wB97X-V/def2-TZVPPD/SMD(SOLVENT=THF)") correction_level_of_theory (str): Desired correction level of theory (e.g. "wB97X-V/def2-TZVPPD/SMD") correction_solvent (str): Desired correction solvent (e.g. "SOLVENT=WATER") correction_lot_solvent (str): Desired correction combination of level of theory and solvent (e.g. "wB97X-V/def2-TZVPPD/SMD(SOLVENT=THF)") combined_lot_solvent (str): Desired combination of level of theory and solvent including both main thermo calculation and single-point energy correction (e.g. "wB97X-D/def2-SVPD/VACUUM//wB97X-V/def2-TZVPPD/SMD(SOLVENT=THF)") electronic_energy (Tuple[float, float]): Minimum and maximum electronic energy zero_point_energy (Tuple[float, float]): Minimum and maximum zero-point energy total_enthalpy (Tuple[float, float]): Minimum and maximum total enthalpy total_entropy (Tuple[float, float]): Minimum and maximum total entropy translational_enthalpy (Tuple[float, float]): Minimum and maximum translational enthalpy rotational_enthalpy (Tuple[float, float]): Minimum and maximum rotational enthalpy vibrational_enthalpy (Tuple[float, float]): Minimum and maximum vibrational enthalpy translational_entropy (Tuple[float, float]): Minimum and maximum translational enthalpy rotational_entropy (Tuple[float, float]): Minimum and maximum rotational enthalpy vibrational_entropy (Tuple[float, float]): Minimum and maximum vibrational enthalpy free_energy (Tuple[float, float]): Minimum and maximum free energy formula (str, List[str]): An alphabetical formula or list of formulas (e.g. "C2 Li2 O4", ["C2 H4", "C2 H6"]). elements (List[str]): A list of elements. exclude_elements (List(str)): List of elements to exclude. chemsys (str, List[str]): A chemical system, list of chemical systems (e.g., Li-C-O, [C-O-H-N, Li-N]). num_chunks (int): Maximum number of chunks of data to yield. None will yield all possible. chunk_size (int): Number of data entries per chunk. all_fields (bool): Whether to return all fields in the document. Defaults to True. fields (List[str]): List of fields in MoleculeDoc to return data for. Default is "molecule_id", "property_id", "solvent", "method", "last_updated" if all_fields is False. Returns: ([MoleculeThermoDoc]) List of molecule thermo documents """ query_params = {} # type: dict min_max = [ "electronic_energy", "zero_point_energy", "total_enthalpy", "total_entropy", "translational_enthalpy", "rotational_enthalpy", "vibrational_enthalpy", "translational_entropy", "rotational_entropy", "vibrational_entropy", "free_energy", ] for param, value in locals().items(): if param in min_max and value: if isinstance(value, (int, float)): value = (value, value) query_params.update( { f"{param}_min": value[0], f"{param}_max": value[1], } ) if molecule_ids: if isinstance(molecule_ids, str): molecule_ids = [molecule_ids] query_params.update({"molecule_ids": ",".join(molecule_ids)}) if property_ids: if isinstance(property_ids, str): property_ids = [property_ids] query_params.update({"property_ids": ",".join(property_ids)}) if charge: query_params.update({"charge": charge}) if spin_multiplicity: query_params.update({"spin_multiplicity": spin_multiplicity}) if level_of_theory: query_params.update({"level_of_theory": level_of_theory}) if solvent: query_params.update({"solvent": solvent}) if lot_solvent: query_params.update({"lot_solvent": lot_solvent}) if correction_level_of_theory: query_params.update( {"correction_level_of_theory": correction_level_of_theory} ) if correction_solvent: query_params.update({"correction_solvent": correction_solvent}) if correction_lot_solvent: query_params.update({"correction_lot_solvent": correction_lot_solvent}) if combined_lot_solvent: query_params.update({"combined_lot_solvent": combined_lot_solvent}) if formula: if isinstance(formula, str): formula = [formula] query_params.update({"formula": ",".join(formula)}) if chemsys: if isinstance(chemsys, str): chemsys = [chemsys] query_params.update({"chemsys": ",".join(chemsys)}) if elements: query_params.update({"elements": ",".join(elements)}) if exclude_elements: query_params.update({"exclude_elements": ",".join(exclude_elements)}) return super()._search( num_chunks=num_chunks, chunk_size=chunk_size, all_fields=all_fields, fields=fields, **query_params, ) api-0.45.3/mp_api/client/routes/molecules/vibrations.py000066400000000000000000000136201475770546700231720ustar00rootroot00000000000000from __future__ import annotations from emmet.core.molecules.vibration import VibrationDoc from emmet.core.mpid import MPculeID from mp_api.client.core import BaseRester class MoleculesVibrationRester(BaseRester[VibrationDoc]): suffix = "molecules/vibrations" document_model = VibrationDoc primary_key = "property_id" def search( self, molecule_ids: MPculeID | list[MPculeID] | None = None, property_ids: str | list[str] | None = None, charge: int | None = None, spin_multiplicity: int | None = None, level_of_theory: str | None = None, solvent: str | None = None, lot_solvent: str | None = None, formula: str | list[str] | None = None, elements: list[str] | None = None, exclude_elements: list[str] | None = None, chemsys: str | list[str] | None = None, num_chunks: int | None = None, chunk_size: int = 1000, all_fields: bool = True, fields: list[str] | None = None, ): """Query molecules vibration docs using a variety of search criteria. Arguments: molecule_ids (MPculeID, List[MPculeID]): List of Materials Project Molecule IDs (MPculeIDs) to return data for. property_ids (str, List[str]): List of property IDs to return data for. charge (Tuple[int, int]): Minimum and maximum charge for the molecule. spin_multiplicity (Tuple[int, int]): Minimum and maximum spin for the molecule. level_of_theory (str): Desired level of theory (e.g. "wB97X-V/def2-TZVPPD/SMD") solvent (str): Desired solvent (e.g. "SOLVENT=WATER") lot_solvent (str): Desired combination of level of theory and solvent (e.g. "wB97X-V/def2-TZVPPD/SMD(SOLVENT=THF)") correction_level_of_theory (str): Desired correction level of theory (e.g. "wB97X-V/def2-TZVPPD/SMD") correction_solvent (str): Desired correction solvent (e.g. "SOLVENT=WATER") correction_lot_solvent (str): Desired correction combination of level of theory and solvent (e.g. "wB97X-V/def2-TZVPPD/SMD(SOLVENT=THF)") combined_lot_solvent (str): Desired combination of level of theory and solvent including both main thermo calculation and single-point energy correction (e.g. "wB97X-D/def2-SVPD/VACUUM//wB97X-V/def2-TZVPPD/SMD(SOLVENT=THF)") electronic_energy (Tuple[float, float]): Minimum and maximum electronic energy zero_point_energy (Tuple[float, float]): Minimum and maximum zero-point energy total_enthalpy (Tuple[float, float]): Minimum and maximum total enthalpy total_entropy (Tuple[float, float]): Minimum and maximum total entropy translational_enthalpy (Tuple[float, float]): Minimum and maximum translational enthalpy rotational_enthalpy (Tuple[float, float]): Minimum and maximum rotational enthalpy vibrational_enthalpy (Tuple[float, float]): Minimum and maximum vibrational enthalpy translational_entropy (Tuple[float, float]): Minimum and maximum translational enthalpy rotational_entropy (Tuple[float, float]): Minimum and maximum rotational enthalpy vibrational_entropy (Tuple[float, float]): Minimum and maximum vibrational enthalpy free_energy (Tuple[float, float]): Minimum and maximum free energy formula (str, List[str]): An alphabetical formula or list of formulas (e.g. "C2 Li2 O4", ["C2 H4", "C2 H6"]). elements (List[str]): A list of elements. exclude_elements (List(str)): List of elements to exclude. chemsys (str, List[str]): A chemical system, list of chemical systems (e.g., Li-C-O, [C-O-H-N, Li-N]). num_chunks (int): Maximum number of chunks of data to yield. None will yield all possible. chunk_size (int): Number of data entries per chunk. all_fields (bool): Whether to return all fields in the document. Defaults to True. fields (List[str]): List of fields in MoleculeDoc to return data for. Default is "molecule_id", "property_id", "solvent", "method", "last_updated" if all_fields is False. Returns: ([VibrationDoc]) List of molecule vibration documents """ query_params = {} # type: dict if molecule_ids: if isinstance(molecule_ids, str): molecule_ids = [molecule_ids] query_params.update({"molecule_ids": ",".join(molecule_ids)}) if property_ids: if isinstance(property_ids, str): property_ids = [property_ids] query_params.update({"property_ids": ",".join(property_ids)}) if charge: query_params.update({"charge": charge}) if spin_multiplicity: query_params.update({"spin_multiplicity": spin_multiplicity}) if level_of_theory: query_params.update({"level_of_theory": level_of_theory}) if solvent: query_params.update({"solvent": solvent}) if lot_solvent: query_params.update({"lot_solvent": lot_solvent}) if formula: if isinstance(formula, str): formula = [formula] query_params.update({"formula": ",".join(formula)}) if chemsys: if isinstance(chemsys, str): chemsys = [chemsys] query_params.update({"chemsys": ",".join(chemsys)}) if elements: query_params.update({"elements": ",".join(elements)}) if exclude_elements: query_params.update({"exclude_elements": ",".join(exclude_elements)}) return super()._search( num_chunks=num_chunks, chunk_size=chunk_size, all_fields=all_fields, fields=fields, **query_params, ) api-0.45.3/pyproject.toml000066400000000000000000000057421475770546700153260ustar00rootroot00000000000000[build-system] requires = ["setuptools", "setuptools-scm"] build-backend = "setuptools.build_meta" [project] name = "mp-api" authors = [ { name = "The Materials Project", email = "feedback@materialsproject.org" }, ] description = "API Client for the Materials Project" readme = "README.md" requires-python = ">=3.9" license = { text = "modified BSD" } classifiers = [ "Programming Language :: Python :: 3", "Development Status :: 4 - Beta", "Intended Audience :: Science/Research", "Intended Audience :: Information Technology", "Operating System :: OS Independent", "Topic :: Scientific/Engineering", ] dependencies = [ "setuptools", "msgpack", "maggma>=0.57.1", "pymatgen>=2022.3.7,!=2024.2.20", "typing-extensions>=3.7.4.1", "requests>=2.23.0", "monty>=2024.12.10", "emmet-core>=0.84.3rc6", "smart_open", ] dynamic = ["version"] [project.optional-dependencies] all = ["emmet-core[all]>=0.69.1", "custodian", "mpcontribs-client", "boto3"] test = [ "pre-commit", "pytest", "pytest-asyncio", "pytest-cov", "pytest-mock", "flake8", "pycodestyle", "mypy", "mypy-extensions", "typing-extensions", "types-setuptools", "types-requests", ] [tool.setuptools.packages.find] include = ["mp_api*"] namespaces = true [tool.setuptools_scm] [tool.pytest.ini_options] minversion = "6.0" addopts = ["-ra", "--showlocals", "--strict-markers", "--strict-config"] xfail_strict = true filterwarnings = ["default"] log_cli_level = "info" testpaths = ["tests"] [tool.ruff] target-version = "py38" select = [ "B", # flake8-bugbear "D", # pydocstyle "E", # pycodestyle "F", # pyflakes "I", # isort "PLE", # pylint error "PLW", # pylint warning "PYI", # flakes8-pyi "Q", # flake8-quotes "SIM", # flake8-simplify "TID", # tidy imports "UP", # pyupgrade "W", # pycodestyle "YTT", # flake8-2020 ] ignore = [ "B019", # Use of functools.lru_cache or functools.cache on methods can lead to memory leaks "B028", # No explicit stacklevel keyword argument found "B904", # Within an except clause, raise exceptions with raise ... from err "D100", # Missing docstring in public module "D104", # Missing docstring in public package "D101", # Missing docstring in public class "D102", # Missing docstring in public method "D105", # Missing docstring in magic method "D106", # Missing docstring in public nested class "D205", # 1 blank line required between summary line and description "PLW2901", # Outer for loop variable overwritten by inner assignment target "SIM105", # Use contextlib.suppress(FileNotFoundError) instead of try-except-pass "SIM115", # Use context handler for opening files, "E501", ] exclude = ["docs", ".ruff_cache", "requirements", "test*", "settings.py"] pydocstyle.convention = "google" flake8-unused-arguments.ignore-variadic-names = true isort.required-imports = ["from __future__ import annotations"] [tool.ruff.per-file-ignores] "*/__init__.py" = ["F401"] # F401: imported but unused api-0.45.3/requirements/000077500000000000000000000000001475770546700151255ustar00rootroot00000000000000api-0.45.3/requirements/requirements-ubuntu-latest_py3.10.txt000066400000000000000000000076661475770546700242540ustar00rootroot00000000000000# # This file is autogenerated by pip-compile with Python 3.10 # by the following command: # # pip-compile --output-file=requirements/requirements-ubuntu-latest_py3.10.txt pyproject.toml # aioitertools==0.12.0 # via maggma annotated-types==0.7.0 # via pydantic attrs==24.2.0 # via # jsonlines # jsonschema # referencing bcrypt==4.2.1 # via paramiko boto3==1.35.78 # via maggma botocore==1.35.78 # via # boto3 # s3transfer certifi==2024.8.30 # via requests cffi==1.17.1 # via # cryptography # pynacl charset-normalizer==3.4.0 # via requests contourpy==1.3.1 # via matplotlib cryptography==44.0.0 # via paramiko cycler==0.12.1 # via matplotlib dnspython==2.7.0 # via # maggma # pymongo emmet-core==0.84.3rc6 # via mp-api (pyproject.toml) fonttools==4.55.3 # via matplotlib idna==3.10 # via requests jmespath==1.0.1 # via # boto3 # botocore joblib==1.4.2 # via pymatgen jsonlines==4.0.0 # via maggma jsonschema==4.23.0 # via maggma jsonschema-specifications==2024.10.1 # via jsonschema kiwisolver==1.4.7 # via matplotlib latexcodec==3.0.0 # via pybtex maggma==0.70.0 # via mp-api (pyproject.toml) matplotlib==3.9.3 # via pymatgen mongomock==4.3.0 # via maggma monty==2024.12.10 # via # emmet-core # maggma # mp-api (pyproject.toml) # pymatgen mpmath==1.3.0 # via sympy msgpack==1.1.0 # via # maggma # mp-api (pyproject.toml) networkx==3.4.2 # via pymatgen numpy==1.26.4 # via # contourpy # emmet-core # maggma # matplotlib # monty # pandas # pymatgen # scipy # spglib orjson==3.10.12 # via maggma packaging==24.2 # via # matplotlib # mongomock # plotly palettable==3.3.3 # via pymatgen pandas==2.2.3 # via # maggma # pymatgen paramiko==3.5.0 # via sshtunnel pillow==11.0.0 # via matplotlib plotly==5.24.1 # via pymatgen pybtex==0.24.0 # via # emmet-core # pymatgen pycparser==2.22 # via cffi pydantic==2.10.3 # via # emmet-core # maggma # pydantic-settings pydantic-core==2.27.1 # via pydantic pydantic-settings==2.6.1 # via # emmet-core # maggma pydash==8.0.4 # via maggma pymatgen==2024.11.13 # via # emmet-core # mp-api (pyproject.toml) pymongo==4.10.1 # via maggma pynacl==1.5.0 # via paramiko pyparsing==3.2.0 # via matplotlib python-dateutil==2.9.0.post0 # via # botocore # maggma # matplotlib # pandas python-dotenv==1.0.1 # via pydantic-settings pytz==2024.2 # via # mongomock # pandas pyyaml==6.0.2 # via pybtex pyzmq==26.2.0 # via maggma referencing==0.35.1 # via # jsonschema # jsonschema-specifications requests==2.32.3 # via # mp-api (pyproject.toml) # pymatgen rpds-py==0.22.3 # via # jsonschema # referencing ruamel-yaml==0.18.6 # via # maggma # monty # pymatgen ruamel-yaml-clib==0.2.12 # via ruamel-yaml s3transfer==0.10.4 # via boto3 scipy==1.14.1 # via pymatgen sentinels==1.0.0 # via mongomock six==1.17.0 # via # pybtex # python-dateutil smart-open==7.0.5 # via mp-api (pyproject.toml) spglib==2.5.0 # via pymatgen sshtunnel==0.4.0 # via maggma sympy==1.13.3 # via pymatgen tabulate==0.9.0 # via pymatgen tenacity==9.0.0 # via plotly tqdm==4.67.1 # via # maggma # pymatgen typing-extensions==4.12.2 # via # emmet-core # mp-api (pyproject.toml) # pydantic # pydantic-core # pydash tzdata==2024.2 # via pandas uncertainties==3.2.2 # via pymatgen urllib3==2.2.3 # via # botocore # requests wrapt==1.17.0 # via smart-open # The following packages are considered to be unsafe in a requirements file: # setuptools api-0.45.3/requirements/requirements-ubuntu-latest_py3.10_extras.txt000066400000000000000000000266201475770546700256310ustar00rootroot00000000000000# # This file is autogenerated by pip-compile with Python 3.10 # by the following command: # # pip-compile --all-extras --output-file=requirements/requirements-ubuntu-latest_py3.10_extras.txt pyproject.toml # aioitertools==0.12.0 # via maggma annotated-types==0.7.0 # via pydantic arrow==1.3.0 # via isoduration ase==3.23.0 # via # matcalc # pymatgen-analysis-diffusion asttokens==3.0.0 # via stack-data attrs==24.2.0 # via # jsonlines # jsonschema # referencing bcrypt==4.2.1 # via paramiko boltons==24.1.0 # via mpcontribs-client boto3==1.35.78 # via # maggma # mp-api (pyproject.toml) botocore==1.35.78 # via # boto3 # s3transfer bravado==11.0.3 # via mpcontribs-client bravado-core==6.1.1 # via bravado cachetools==5.5.0 # via mpcontribs-client certifi==2024.8.30 # via requests cffi==1.17.1 # via # cryptography # pynacl cfgv==3.4.0 # via pre-commit charset-normalizer==3.4.0 # via requests contourpy==1.3.1 # via matplotlib coverage[toml]==7.6.9 # via pytest-cov cryptography==44.0.0 # via paramiko custodian==2024.10.16 # via mp-api (pyproject.toml) cycler==0.12.1 # via matplotlib decorator==5.1.1 # via ipython distlib==0.3.9 # via virtualenv dnspython==2.7.0 # via # maggma # pyisemail # pymongo emmet-core[all]==0.84.3rc6 # via # mp-api # mp-api (pyproject.toml) exceptiongroup==1.2.2 # via # ipython # pytest executing==2.1.0 # via stack-data fasteners==0.19 # via mdanalysis filelock==3.16.1 # via virtualenv filetype==1.2.0 # via mpcontribs-client flake8==7.1.1 # via mp-api (pyproject.toml) flatten-dict==0.4.2 # via mpcontribs-client fonttools==4.55.3 # via matplotlib fqdn==1.5.1 # via jsonschema griddataformats==1.0.2 # via mdanalysis h5py==3.12.1 # via phonopy identify==2.6.3 # via pre-commit idna==3.10 # via # jsonschema # requests imageio==2.36.1 # via scikit-image importlib-resources==6.4.5 # via swagger-spec-validator inflect==7.4.0 # via robocrys iniconfig==2.0.0 # via pytest ipython==8.30.0 # via mpcontribs-client isoduration==20.11.0 # via jsonschema jedi==0.19.2 # via ipython jmespath==1.0.1 # via # boto3 # botocore joblib==1.4.2 # via # matcalc # mdanalysis # pymatgen # pymatgen-analysis-diffusion # scikit-learn json2html==1.3.0 # via mpcontribs-client jsonlines==4.0.0 # via maggma jsonpointer==3.0.0 # via jsonschema jsonref==1.1.0 # via bravado-core jsonschema[format-nongpl]==4.23.0 # via # bravado-core # maggma # swagger-spec-validator jsonschema-specifications==2024.10.1 # via jsonschema kiwisolver==1.4.7 # via matplotlib latexcodec==3.0.0 # via pybtex lazy-loader==0.4 # via scikit-image maggma==0.70.0 # via # mp-api # mp-api (pyproject.toml) matcalc==0.0.4 # via emmet-core matminer==0.9.3 # via robocrys matplotlib==3.9.3 # via # ase # mdanalysis # pathsimanalysis # phonopy # pymatgen # seaborn # solvation-analysis matplotlib-inline==0.1.7 # via ipython mccabe==0.7.0 # via flake8 mda-xdrlib==0.2.0 # via mdanalysis mdahole2==0.5.0 # via mdanalysis mdanalysis==2.8.0 # via # emmet-core # mdahole2 # pathsimanalysis # solvation-analysis # waterdynamics mmtf-python==1.1.3 # via mdanalysis mongomock==4.3.0 # via maggma monotonic==1.6 # via bravado monty==2024.12.10 # via # custodian # emmet-core # maggma # matminer # mp-api # mp-api (pyproject.toml) # pymatgen # robocrys more-itertools==10.5.0 # via inflect mp-api==0.43.0 # via robocrys mp-pyrho==0.4.5 # via pymatgen-analysis-defects mpcontribs-client==5.9.0 # via mp-api (pyproject.toml) mpmath==1.3.0 # via sympy mrcfile==1.5.3 # via griddataformats msgpack==1.1.0 # via # bravado # bravado-core # maggma # mmtf-python # mp-api # mp-api (pyproject.toml) mypy==1.13.0 # via mp-api (pyproject.toml) mypy-extensions==1.0.0 # via # mp-api (pyproject.toml) # mypy networkx==3.4.2 # via # pymatgen # robocrys # scikit-image nodeenv==1.9.1 # via pre-commit numpy==1.26.4 # via # ase # contourpy # emmet-core # griddataformats # h5py # imageio # maggma # matminer # matplotlib # mdanalysis # monty # mpcontribs-client # mrcfile # pandas # pathsimanalysis # patsy # phonopy # pymatgen # pymatgen-analysis-defects # pymatgen-analysis-diffusion # rdkit # robocrys # scikit-image # scikit-learn # scipy # seaborn # seekpath # shapely # solvation-analysis # spglib # statsmodels # symfc # tifffile # waterdynamics orjson==3.10.12 # via maggma packaging==24.2 # via # lazy-loader # matplotlib # mdanalysis # mongomock # plotly # pytest # scikit-image # statsmodels palettable==3.3.3 # via pymatgen pandas==2.2.3 # via # maggma # matminer # mpcontribs-client # pymatgen # seaborn # solvation-analysis # statsmodels paramiko==3.5.0 # via sshtunnel parso==0.8.4 # via jedi pathsimanalysis==1.2.0 # via mdanalysis patsy==1.0.1 # via statsmodels pexpect==4.9.0 # via ipython phonopy==2.32.0 # via matcalc pillow==11.0.0 # via # imageio # matplotlib # rdkit # scikit-image pint==0.19.2 # via mpcontribs-client platformdirs==4.3.6 # via virtualenv plotly==5.24.1 # via # mpcontribs-client # pymatgen # solvation-analysis pluggy==1.5.0 # via pytest pre-commit==4.0.1 # via mp-api (pyproject.toml) prompt-toolkit==3.0.48 # via ipython psutil==6.1.0 # via custodian ptyprocess==0.7.0 # via pexpect pubchempy==1.0.4 # via robocrys pure-eval==0.2.3 # via stack-data pybtex==0.24.0 # via # emmet-core # pymatgen # robocrys pycodestyle==2.12.1 # via # flake8 # mp-api (pyproject.toml) pycparser==2.22 # via cffi pydantic==2.10.3 # via # emmet-core # maggma # pydantic-settings pydantic-core==2.27.1 # via pydantic pydantic-settings==2.6.1 # via # emmet-core # maggma pydash==8.0.4 # via maggma pyflakes==3.2.0 # via flake8 pygments==2.18.0 # via ipython pyisemail==2.0.1 # via mpcontribs-client pymatgen==2024.11.13 # via # emmet-core # matcalc # matminer # mp-api # mp-api (pyproject.toml) # mp-pyrho # mpcontribs-client # pymatgen-analysis-alloys # pymatgen-analysis-defects # pymatgen-analysis-diffusion # robocrys pymatgen-analysis-alloys==0.0.7 # via emmet-core pymatgen-analysis-defects==2024.10.22 # via emmet-core pymatgen-analysis-diffusion==2024.7.15 # via emmet-core pymongo==4.10.1 # via # maggma # matminer # mpcontribs-client pynacl==1.5.0 # via paramiko pyparsing==3.2.0 # via matplotlib pytest==8.3.4 # via # mp-api (pyproject.toml) # pytest-asyncio # pytest-cov # pytest-mock # solvation-analysis pytest-asyncio==0.24.0 # via mp-api (pyproject.toml) pytest-cov==6.0.0 # via mp-api (pyproject.toml) pytest-mock==3.14.0 # via mp-api (pyproject.toml) python-dateutil==2.9.0.post0 # via # arrow # botocore # bravado # bravado-core # maggma # matplotlib # pandas python-dotenv==1.0.1 # via pydantic-settings pytz==2024.2 # via # bravado-core # mongomock # pandas pyyaml==6.0.2 # via # bravado # bravado-core # phonopy # pre-commit # pybtex # swagger-spec-validator pyzmq==26.2.0 # via maggma rdkit==2024.3.6 # via solvation-analysis referencing==0.35.1 # via # jsonschema # jsonschema-specifications requests==2.32.3 # via # bravado # bravado-core # matminer # mp-api # mp-api (pyproject.toml) # pymatgen # requests-futures requests-futures==1.0.2 # via mpcontribs-client rfc3339-validator==0.1.4 # via jsonschema rfc3986-validator==0.1.1 # via jsonschema robocrys==0.2.10 # via emmet-core rpds-py==0.22.3 # via # jsonschema # referencing ruamel-yaml==0.18.6 # via # custodian # maggma # monty # pymatgen # robocrys ruamel-yaml-clib==0.2.12 # via ruamel-yaml s3transfer==0.10.4 # via boto3 scikit-image==0.24.0 # via pymatgen-analysis-defects scikit-learn==1.6.0 # via matminer scipy==1.14.1 # via # ase # griddataformats # mdanalysis # pathsimanalysis # pymatgen # robocrys # scikit-image # scikit-learn # solvation-analysis # statsmodels # symfc seaborn==0.13.2 # via pymatgen-analysis-diffusion seekpath==2.1.0 # via emmet-core semantic-version==2.10.0 # via mpcontribs-client sentinels==1.0.0 # via mongomock shapely==2.0.6 # via pymatgen-analysis-alloys simplejson==3.19.3 # via # bravado # bravado-core six==1.17.0 # via # bravado # bravado-core # flatten-dict # pybtex # python-dateutil # rfc3339-validator smart-open==7.0.5 # via # mp-api # mp-api (pyproject.toml) solvation-analysis==0.4.1 # via emmet-core spglib==2.5.0 # via # phonopy # pymatgen # robocrys # seekpath # symfc sshtunnel==0.4.0 # via maggma stack-data==0.6.3 # via ipython statsmodels==0.14.4 # via solvation-analysis swagger-spec-validator==3.0.4 # via # bravado-core # mpcontribs-client symfc==1.1.6 # via phonopy sympy==1.13.3 # via # matminer # pymatgen tabulate==0.9.0 # via pymatgen tenacity==9.0.0 # via plotly threadpoolctl==3.5.0 # via # mdanalysis # scikit-learn tifffile==2024.9.20 # via scikit-image tomli==2.2.1 # via # coverage # mypy # pytest tqdm==4.67.1 # via # maggma # matminer # mdanalysis # mpcontribs-client # pymatgen traitlets==5.14.3 # via # ipython # matplotlib-inline typeguard==4.4.1 # via inflect types-python-dateutil==2.9.0.20241206 # via arrow types-requests==2.32.0.20241016 # via mp-api (pyproject.toml) types-setuptools==75.6.0.20241126 # via mp-api (pyproject.toml) typing-extensions==4.12.2 # via # bravado # emmet-core # ipython # mp-api # mp-api (pyproject.toml) # mypy # pydantic # pydantic-core # pydash # swagger-spec-validator # typeguard tzdata==2024.2 # via pandas ujson==5.10.0 # via mpcontribs-client uncertainties==3.2.2 # via pymatgen uri-template==1.3.0 # via jsonschema urllib3==2.2.3 # via # botocore # requests # types-requests virtualenv==20.28.0 # via pre-commit waterdynamics==1.2.0 # via mdanalysis wcwidth==0.2.13 # via prompt-toolkit webcolors==24.11.1 # via jsonschema wrapt==1.17.0 # via smart-open # The following packages are considered to be unsafe in a requirements file: # setuptools api-0.45.3/requirements/requirements-ubuntu-latest_py3.11.txt000066400000000000000000000076661475770546700242550ustar00rootroot00000000000000# # This file is autogenerated by pip-compile with Python 3.11 # by the following command: # # pip-compile --output-file=requirements/requirements-ubuntu-latest_py3.11.txt pyproject.toml # aioitertools==0.12.0 # via maggma annotated-types==0.7.0 # via pydantic attrs==24.2.0 # via # jsonlines # jsonschema # referencing bcrypt==4.2.1 # via paramiko boto3==1.35.78 # via maggma botocore==1.35.78 # via # boto3 # s3transfer certifi==2024.8.30 # via requests cffi==1.17.1 # via # cryptography # pynacl charset-normalizer==3.4.0 # via requests contourpy==1.3.1 # via matplotlib cryptography==44.0.0 # via paramiko cycler==0.12.1 # via matplotlib dnspython==2.7.0 # via # maggma # pymongo emmet-core==0.84.3rc6 # via mp-api (pyproject.toml) fonttools==4.55.3 # via matplotlib idna==3.10 # via requests jmespath==1.0.1 # via # boto3 # botocore joblib==1.4.2 # via pymatgen jsonlines==4.0.0 # via maggma jsonschema==4.23.0 # via maggma jsonschema-specifications==2024.10.1 # via jsonschema kiwisolver==1.4.7 # via matplotlib latexcodec==3.0.0 # via pybtex maggma==0.70.0 # via mp-api (pyproject.toml) matplotlib==3.9.3 # via pymatgen mongomock==4.3.0 # via maggma monty==2024.12.10 # via # emmet-core # maggma # mp-api (pyproject.toml) # pymatgen mpmath==1.3.0 # via sympy msgpack==1.1.0 # via # maggma # mp-api (pyproject.toml) networkx==3.4.2 # via pymatgen numpy==1.26.4 # via # contourpy # emmet-core # maggma # matplotlib # monty # pandas # pymatgen # scipy # spglib orjson==3.10.12 # via maggma packaging==24.2 # via # matplotlib # mongomock # plotly palettable==3.3.3 # via pymatgen pandas==2.2.3 # via # maggma # pymatgen paramiko==3.5.0 # via sshtunnel pillow==11.0.0 # via matplotlib plotly==5.24.1 # via pymatgen pybtex==0.24.0 # via # emmet-core # pymatgen pycparser==2.22 # via cffi pydantic==2.10.3 # via # emmet-core # maggma # pydantic-settings pydantic-core==2.27.1 # via pydantic pydantic-settings==2.6.1 # via # emmet-core # maggma pydash==8.0.4 # via maggma pymatgen==2024.11.13 # via # emmet-core # mp-api (pyproject.toml) pymongo==4.10.1 # via maggma pynacl==1.5.0 # via paramiko pyparsing==3.2.0 # via matplotlib python-dateutil==2.9.0.post0 # via # botocore # maggma # matplotlib # pandas python-dotenv==1.0.1 # via pydantic-settings pytz==2024.2 # via # mongomock # pandas pyyaml==6.0.2 # via pybtex pyzmq==26.2.0 # via maggma referencing==0.35.1 # via # jsonschema # jsonschema-specifications requests==2.32.3 # via # mp-api (pyproject.toml) # pymatgen rpds-py==0.22.3 # via # jsonschema # referencing ruamel-yaml==0.18.6 # via # maggma # monty # pymatgen ruamel-yaml-clib==0.2.12 # via ruamel-yaml s3transfer==0.10.4 # via boto3 scipy==1.14.1 # via pymatgen sentinels==1.0.0 # via mongomock six==1.17.0 # via # pybtex # python-dateutil smart-open==7.0.5 # via mp-api (pyproject.toml) spglib==2.5.0 # via pymatgen sshtunnel==0.4.0 # via maggma sympy==1.13.3 # via pymatgen tabulate==0.9.0 # via pymatgen tenacity==9.0.0 # via plotly tqdm==4.67.1 # via # maggma # pymatgen typing-extensions==4.12.2 # via # emmet-core # mp-api (pyproject.toml) # pydantic # pydantic-core # pydash tzdata==2024.2 # via pandas uncertainties==3.2.2 # via pymatgen urllib3==2.2.3 # via # botocore # requests wrapt==1.17.0 # via smart-open # The following packages are considered to be unsafe in a requirements file: # setuptools api-0.45.3/requirements/requirements-ubuntu-latest_py3.11_extras.txt000066400000000000000000000264151475770546700256340ustar00rootroot00000000000000# # This file is autogenerated by pip-compile with Python 3.11 # by the following command: # # pip-compile --all-extras --output-file=requirements/requirements-ubuntu-latest_py3.11_extras.txt pyproject.toml # aioitertools==0.12.0 # via maggma annotated-types==0.7.0 # via pydantic arrow==1.3.0 # via isoduration ase==3.23.0 # via # matcalc # pymatgen-analysis-diffusion asttokens==3.0.0 # via stack-data attrs==24.2.0 # via # jsonlines # jsonschema # referencing bcrypt==4.2.1 # via paramiko boltons==24.1.0 # via mpcontribs-client boto3==1.35.78 # via # maggma # mp-api (pyproject.toml) botocore==1.35.78 # via # boto3 # s3transfer bravado==11.0.3 # via mpcontribs-client bravado-core==6.1.1 # via bravado cachetools==5.5.0 # via mpcontribs-client certifi==2024.8.30 # via requests cffi==1.17.1 # via # cryptography # pynacl cfgv==3.4.0 # via pre-commit charset-normalizer==3.4.0 # via requests contourpy==1.3.1 # via matplotlib coverage[toml]==7.6.9 # via pytest-cov cryptography==44.0.0 # via paramiko custodian==2024.10.16 # via mp-api (pyproject.toml) cycler==0.12.1 # via matplotlib decorator==5.1.1 # via ipython distlib==0.3.9 # via virtualenv dnspython==2.7.0 # via # maggma # pyisemail # pymongo emmet-core[all]==0.84.3rc6 # via # mp-api # mp-api (pyproject.toml) executing==2.1.0 # via stack-data fasteners==0.19 # via mdanalysis filelock==3.16.1 # via virtualenv filetype==1.2.0 # via mpcontribs-client flake8==7.1.1 # via mp-api (pyproject.toml) flatten-dict==0.4.2 # via mpcontribs-client fonttools==4.55.3 # via matplotlib fqdn==1.5.1 # via jsonschema griddataformats==1.0.2 # via mdanalysis h5py==3.12.1 # via phonopy identify==2.6.3 # via pre-commit idna==3.10 # via # jsonschema # requests imageio==2.36.1 # via scikit-image importlib-resources==6.4.5 # via swagger-spec-validator inflect==7.4.0 # via robocrys iniconfig==2.0.0 # via pytest ipython==8.30.0 # via mpcontribs-client isoduration==20.11.0 # via jsonschema jedi==0.19.2 # via ipython jmespath==1.0.1 # via # boto3 # botocore joblib==1.4.2 # via # matcalc # mdanalysis # pymatgen # pymatgen-analysis-diffusion # scikit-learn json2html==1.3.0 # via mpcontribs-client jsonlines==4.0.0 # via maggma jsonpointer==3.0.0 # via jsonschema jsonref==1.1.0 # via bravado-core jsonschema[format-nongpl]==4.23.0 # via # bravado-core # maggma # swagger-spec-validator jsonschema-specifications==2024.10.1 # via jsonschema kiwisolver==1.4.7 # via matplotlib latexcodec==3.0.0 # via pybtex lazy-loader==0.4 # via scikit-image maggma==0.70.0 # via # mp-api # mp-api (pyproject.toml) matcalc==0.0.4 # via emmet-core matminer==0.9.3 # via robocrys matplotlib==3.9.3 # via # ase # mdanalysis # pathsimanalysis # phonopy # pymatgen # seaborn # solvation-analysis matplotlib-inline==0.1.7 # via ipython mccabe==0.7.0 # via flake8 mda-xdrlib==0.2.0 # via mdanalysis mdahole2==0.5.0 # via mdanalysis mdanalysis==2.8.0 # via # emmet-core # mdahole2 # pathsimanalysis # solvation-analysis # waterdynamics mmtf-python==1.1.3 # via mdanalysis mongomock==4.3.0 # via maggma monotonic==1.6 # via bravado monty==2024.12.10 # via # custodian # emmet-core # maggma # matminer # mp-api # mp-api (pyproject.toml) # pymatgen # robocrys more-itertools==10.5.0 # via inflect mp-api==0.43.0 # via robocrys mp-pyrho==0.4.5 # via pymatgen-analysis-defects mpcontribs-client==5.9.0 # via mp-api (pyproject.toml) mpmath==1.3.0 # via sympy mrcfile==1.5.3 # via griddataformats msgpack==1.1.0 # via # bravado # bravado-core # maggma # mmtf-python # mp-api # mp-api (pyproject.toml) mypy==1.13.0 # via mp-api (pyproject.toml) mypy-extensions==1.0.0 # via # mp-api (pyproject.toml) # mypy networkx==3.4.2 # via # pymatgen # robocrys # scikit-image nodeenv==1.9.1 # via pre-commit numpy==1.26.4 # via # ase # contourpy # emmet-core # griddataformats # h5py # imageio # maggma # matminer # matplotlib # mdanalysis # monty # mpcontribs-client # mrcfile # pandas # pathsimanalysis # patsy # phonopy # pymatgen # pymatgen-analysis-defects # pymatgen-analysis-diffusion # rdkit # robocrys # scikit-image # scikit-learn # scipy # seaborn # seekpath # shapely # solvation-analysis # spglib # statsmodels # symfc # tifffile # waterdynamics orjson==3.10.12 # via maggma packaging==24.2 # via # lazy-loader # matplotlib # mdanalysis # mongomock # plotly # pytest # scikit-image # statsmodels palettable==3.3.3 # via pymatgen pandas==2.2.3 # via # maggma # matminer # mpcontribs-client # pymatgen # seaborn # solvation-analysis # statsmodels paramiko==3.5.0 # via sshtunnel parso==0.8.4 # via jedi pathsimanalysis==1.2.0 # via mdanalysis patsy==1.0.1 # via statsmodels pexpect==4.9.0 # via ipython phonopy==2.32.0 # via matcalc pillow==11.0.0 # via # imageio # matplotlib # rdkit # scikit-image pint==0.19.2 # via mpcontribs-client platformdirs==4.3.6 # via virtualenv plotly==5.24.1 # via # mpcontribs-client # pymatgen # solvation-analysis pluggy==1.5.0 # via pytest pre-commit==4.0.1 # via mp-api (pyproject.toml) prompt-toolkit==3.0.48 # via ipython psutil==6.1.0 # via custodian ptyprocess==0.7.0 # via pexpect pubchempy==1.0.4 # via robocrys pure-eval==0.2.3 # via stack-data pybtex==0.24.0 # via # emmet-core # pymatgen # robocrys pycodestyle==2.12.1 # via # flake8 # mp-api (pyproject.toml) pycparser==2.22 # via cffi pydantic==2.10.3 # via # emmet-core # maggma # pydantic-settings pydantic-core==2.27.1 # via pydantic pydantic-settings==2.6.1 # via # emmet-core # maggma pydash==8.0.4 # via maggma pyflakes==3.2.0 # via flake8 pygments==2.18.0 # via ipython pyisemail==2.0.1 # via mpcontribs-client pymatgen==2024.11.13 # via # emmet-core # matcalc # matminer # mp-api # mp-api (pyproject.toml) # mp-pyrho # mpcontribs-client # pymatgen-analysis-alloys # pymatgen-analysis-defects # pymatgen-analysis-diffusion # robocrys pymatgen-analysis-alloys==0.0.7 # via emmet-core pymatgen-analysis-defects==2024.10.22 # via emmet-core pymatgen-analysis-diffusion==2024.7.15 # via emmet-core pymongo==4.10.1 # via # maggma # matminer # mpcontribs-client pynacl==1.5.0 # via paramiko pyparsing==3.2.0 # via matplotlib pytest==8.3.4 # via # mp-api (pyproject.toml) # pytest-asyncio # pytest-cov # pytest-mock # solvation-analysis pytest-asyncio==0.24.0 # via mp-api (pyproject.toml) pytest-cov==6.0.0 # via mp-api (pyproject.toml) pytest-mock==3.14.0 # via mp-api (pyproject.toml) python-dateutil==2.9.0.post0 # via # arrow # botocore # bravado # bravado-core # maggma # matplotlib # pandas python-dotenv==1.0.1 # via pydantic-settings pytz==2024.2 # via # bravado-core # mongomock # pandas pyyaml==6.0.2 # via # bravado # bravado-core # phonopy # pre-commit # pybtex # swagger-spec-validator pyzmq==26.2.0 # via maggma rdkit==2024.3.6 # via solvation-analysis referencing==0.35.1 # via # jsonschema # jsonschema-specifications requests==2.32.3 # via # bravado # bravado-core # matminer # mp-api # mp-api (pyproject.toml) # pymatgen # requests-futures requests-futures==1.0.2 # via mpcontribs-client rfc3339-validator==0.1.4 # via jsonschema rfc3986-validator==0.1.1 # via jsonschema robocrys==0.2.10 # via emmet-core rpds-py==0.22.3 # via # jsonschema # referencing ruamel-yaml==0.18.6 # via # custodian # maggma # monty # pymatgen # robocrys ruamel-yaml-clib==0.2.12 # via ruamel-yaml s3transfer==0.10.4 # via boto3 scikit-image==0.24.0 # via pymatgen-analysis-defects scikit-learn==1.6.0 # via matminer scipy==1.14.1 # via # ase # griddataformats # mdanalysis # pathsimanalysis # pymatgen # robocrys # scikit-image # scikit-learn # solvation-analysis # statsmodels # symfc seaborn==0.13.2 # via pymatgen-analysis-diffusion seekpath==2.1.0 # via emmet-core semantic-version==2.10.0 # via mpcontribs-client sentinels==1.0.0 # via mongomock shapely==2.0.6 # via pymatgen-analysis-alloys simplejson==3.19.3 # via # bravado # bravado-core six==1.17.0 # via # bravado # bravado-core # flatten-dict # pybtex # python-dateutil # rfc3339-validator smart-open==7.0.5 # via # mp-api # mp-api (pyproject.toml) solvation-analysis==0.4.1 # via emmet-core spglib==2.5.0 # via # phonopy # pymatgen # robocrys # seekpath # symfc sshtunnel==0.4.0 # via maggma stack-data==0.6.3 # via ipython statsmodels==0.14.4 # via solvation-analysis swagger-spec-validator==3.0.4 # via # bravado-core # mpcontribs-client symfc==1.1.6 # via phonopy sympy==1.13.3 # via # matminer # pymatgen tabulate==0.9.0 # via pymatgen tenacity==9.0.0 # via plotly threadpoolctl==3.5.0 # via # mdanalysis # scikit-learn tifffile==2024.9.20 # via scikit-image tqdm==4.67.1 # via # maggma # matminer # mdanalysis # mpcontribs-client # pymatgen traitlets==5.14.3 # via # ipython # matplotlib-inline typeguard==4.4.1 # via inflect types-python-dateutil==2.9.0.20241206 # via arrow types-requests==2.32.0.20241016 # via mp-api (pyproject.toml) types-setuptools==75.6.0.20241126 # via mp-api (pyproject.toml) typing-extensions==4.12.2 # via # bravado # emmet-core # ipython # mp-api # mp-api (pyproject.toml) # mypy # pydantic # pydantic-core # pydash # swagger-spec-validator # typeguard tzdata==2024.2 # via pandas ujson==5.10.0 # via mpcontribs-client uncertainties==3.2.2 # via pymatgen uri-template==1.3.0 # via jsonschema urllib3==2.2.3 # via # botocore # requests # types-requests virtualenv==20.28.0 # via pre-commit waterdynamics==1.2.0 # via mdanalysis wcwidth==0.2.13 # via prompt-toolkit webcolors==24.11.1 # via jsonschema wrapt==1.17.0 # via smart-open # The following packages are considered to be unsafe in a requirements file: # setuptools api-0.45.3/test_files/000077500000000000000000000000001475770546700145435ustar00rootroot00000000000000api-0.45.3/test_files/Si_mp_149.cif000066400000000000000000000020631475770546700166730ustar00rootroot00000000000000# generated using pymatgen data_Si _symmetry_space_group_name_H-M 'P 1' _cell_length_a 5.46872800 _cell_length_b 5.46872800 _cell_length_c 5.46872800 _cell_angle_alpha 90.00000000 _cell_angle_beta 90.00000000 _cell_angle_gamma 90.00000000 _symmetry_Int_Tables_number 1 _chemical_formula_structural Si _chemical_formula_sum Si8 _cell_volume 163.55317139 _cell_formula_units_Z 8 loop_ _symmetry_equiv_pos_site_id _symmetry_equiv_pos_as_xyz 1 'x, y, z' loop_ _atom_site_type_symbol _atom_site_label _atom_site_symmetry_multiplicity _atom_site_fract_x _atom_site_fract_y _atom_site_fract_z _atom_site_occupancy Si Si0 1 0.25000000 0.75000000 0.25000000 1.0 Si Si1 1 0.00000000 0.00000000 0.50000000 1.0 Si Si2 1 0.25000000 0.25000000 0.75000000 1.0 Si Si3 1 0.00000000 0.50000000 0.00000000 1.0 Si Si4 1 0.75000000 0.75000000 0.75000000 1.0 Si Si5 1 0.50000000 0.00000000 0.00000000 1.0 Si Si6 1 0.75000000 0.25000000 0.25000000 1.0 Si Si7 1 0.50000000 0.50000000 0.50000000 1.0 api-0.45.3/test_files/calcs_reversed_mp_1031016.json000066400000000000000000002001761475770546700220170ustar00rootroot00000000000000[ { 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], "@module": "pymatgen.io.vasp.inputs", "@class": "Kpoints", "actual_points": [ { "abc": [ 0.25, 0.25, 0.25 ], "weight": 1.0 } ] }, "potcar": [ "Na_pv", "Ce", "Mg_pv", "O" ], "potcar_spec": [ { "titel": "PAW_PBE Na_pv 05Jan2001", "hash": "c71d0ed99a871c91fccae9347860d8ba" }, { "titel": "PAW_PBE Ce 28Sep2000", "hash": "ff3a09f2ff91798e58eb4b9854e9be4a" }, { "titel": "PAW_PBE Mg_pv 06Sep2000", "hash": "bbcf6f81cc34a3090d483ad641178746" }, { "titel": "PAW_PBE O 08Apr2002", "hash": "7a25bc5b9a5393f46600a4939d357982" } ], "potcar_type": [ "PAW_PBE", "PAW_PBE", "PAW_PBE", "PAW_PBE" ], "parameters": { "SYSTEM": "unknown system", "LCOMPAT": false, "PREC": "accura", "ENMAX": 520.0, "ENAUG": 659.424, "EDIFF": 0.0008, "IALGO": 38, "IWAVPR": 10, "NBANDS": 70, "NELECT": 115.0, "TURBO": 0, "IRESTART": 0, "NREBOOT": 0, "NMIN": 0, "EREF": 0.0, "ISMEAR": 0, "SIGMA": 0.05, "KSPACING": 0.5, "KGAMMA": true, "LREAL": true, "ROPT": [ -0.00025, -0.00025, -0.00025, -0.00025 ], "LMAXPAW": -100, "LMAXMIX": 2, 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api-0.45.3/tests/000077500000000000000000000000001475770546700135445ustar00rootroot00000000000000api-0.45.3/tests/__init__.py000066400000000000000000000000001475770546700156430ustar00rootroot00000000000000api-0.45.3/tests/materials/000077500000000000000000000000001475770546700155255ustar00rootroot00000000000000api-0.45.3/tests/materials/core_function.py000066400000000000000000000057761475770546700207530ustar00rootroot00000000000000from __future__ import annotations from typing import Callable, Any def client_search_testing( search_method: Callable, excluded_params: list[str], alt_name_dict: dict[str, str], custom_field_tests: dict[str, Any], sub_doc_fields: list[str], ): """ Function to test a client using its search method. Each parameter is used to query for data, which is then checked. Args: search_method (Callable): Client search method excluded_params (list[str]): List of parameters to exclude from testing alt_name_dict (dict[str, str]): Alternative names for parameters used in the projection and subsequent data checking custom_field_tests (dict[str, Any]): Custom queries for specific fields. sub_doc_fields (list[str]): Prefixes for fields to check in resulting data. Useful when data to be tested is nested. """ if search_method is not None: # Get list of parameters param_tuples = list(search_method.__annotations__.items()) # Query API for each numeric and boolean parameter and check if returned for entry in param_tuples: param = entry[0] if param not in excluded_params + ["return"]: param_type = entry[1] q = None if "tuple[int, int]" in param_type: project_field = alt_name_dict.get(param, None) q = { param: (-100, 100), "chunk_size": 1, "num_chunks": 1, } elif "tuple[float, float]" in param_type: project_field = alt_name_dict.get(param, None) q = { param: (-100.12, 100.12), "chunk_size": 1, "num_chunks": 1, } elif "bool" in param_type: project_field = alt_name_dict.get(param, None) q = { param: False, "chunk_size": 1, "num_chunks": 1, } elif param in custom_field_tests: project_field = alt_name_dict.get(param, None) q = { param: custom_field_tests[param], "chunk_size": 1, "num_chunks": 1, } if q is None: raise ValueError( f"Parameter '{param}' with type '{param_type}' was not " "properly identified in the generic search method test." ) doc = search_method(**q)[0].model_dump() for sub_field in sub_doc_fields: if sub_field in doc: doc = doc[sub_field] assert ( doc[project_field if project_field is not None else param] is not None ) api-0.45.3/tests/materials/test_bonds.py000066400000000000000000000021451475770546700202450ustar00rootroot00000000000000import os from core_function import client_search_testing import pytest from mp_api.client.routes.materials.bonds import BondsRester @pytest.fixture def rester(): rester = BondsRester() yield rester rester.session.close() excluded_params = [ "sort_fields", "chunk_size", "num_chunks", "all_fields", "fields", ] sub_doc_fields = [] # type: list alt_name_dict = { "material_ids": "material_id", "max_bond_length": "bond_length_stats", "min_bond_length": "bond_length_stats", "mean_bond_length": "bond_length_stats", } # type: dict custom_field_tests = { "material_ids": ["mp-149"], "coordination_envs": ["Mo-S(6)"], "coordination_envs_anonymous": ["A-B(6)"], } # type: dict @pytest.mark.skipif(os.getenv("MP_API_KEY", None) is None, reason="No API key found.") def test_client(rester): search_method = rester.search client_search_testing( search_method=search_method, excluded_params=excluded_params, alt_name_dict=alt_name_dict, custom_field_tests=custom_field_tests, sub_doc_fields=sub_doc_fields, ) api-0.45.3/tests/materials/test_chemenv.py000066400000000000000000000024071475770546700205660ustar00rootroot00000000000000import os from core_function import client_search_testing import pytest from mp_api.client.routes.materials.chemenv import ChemenvRester @pytest.fixture def rester(): rester = ChemenvRester() yield rester rester.session.close() excluded_params = [ "sort_fields", "chunk_size", "num_chunks", "all_fields", "fields", "volume", "csm", # temp until timeout fix ] sub_doc_fields = [] # type: list alt_name_dict = { "material_ids": "material_id", "exclude_elements": "material_id", "num_elements": "nelements", "num_sites": "nsites", } # type: dict custom_field_tests = { "material_ids": ["mp-22526"], "elements": ["Si", "O"], "exclude_elements": ["Si", "O"], "chemenv_symbol": ["S:1"], "chemenv_iupac": ["IC-12"], "chemenv_iucr": ["[2l]"], "chemenv_name": ["Octahedron"], "species": ["Cu2+"], } # type: dict @pytest.mark.skipif(os.getenv("MP_API_KEY", None) is None, reason="No API key found.") def test_client(rester): search_method = rester.search client_search_testing( search_method=search_method, excluded_params=excluded_params, alt_name_dict=alt_name_dict, custom_field_tests=custom_field_tests, sub_doc_fields=sub_doc_fields, ) api-0.45.3/tests/materials/test_dielectric.py000066400000000000000000000016671475770546700212570ustar00rootroot00000000000000import os from core_function import client_search_testing import pytest from mp_api.client.routes.materials.dielectric import DielectricRester @pytest.fixture def rester(): rester = DielectricRester() yield rester rester.session.close() excluded_params = [ "sort_fields", "chunk_size", "num_chunks", "all_fields", "fields", ] sub_doc_fields = [] # type: list alt_name_dict = { "e_static": "e_ionic", "material_ids": "material_id", } # type: dict custom_field_tests = { "material_ids": ["mp-149"], } # type: dict @pytest.mark.skipif(os.getenv("MP_API_KEY", None) is None, reason="No API key found.") def test_client(rester): search_method = rester.search client_search_testing( search_method=search_method, excluded_params=excluded_params, alt_name_dict=alt_name_dict, custom_field_tests=custom_field_tests, sub_doc_fields=sub_doc_fields, ) api-0.45.3/tests/materials/test_elasticity.py000066400000000000000000000022541475770546700213130ustar00rootroot00000000000000import os from core_function import client_search_testing import pytest from mp_api.client.routes.materials.elasticity import ElasticityRester @pytest.fixture def rester(): rester = ElasticityRester() yield rester rester.session.close() excluded_params = [ "sort_fields", "chunk_size", "num_chunks", "all_fields", "fields", ] sub_doc_fields = [] # type: list alt_name_dict = { "material_ids": "material_id", "elastic_anisotropy": "universal_anisotropy", "poisson_ratio": "homogeneous_poisson", "g_voigt": "bulk_modulus", "g_reuss": "bulk_modulus", "g_vrh": "bulk_modulus", "k_voigt": "shear_modulus", "k_reuss": "shear_modulus", "k_vrh": "shear_modulus", } # type: dict custom_field_tests = {"material_ids": ["mp-149"]} # type: dict @pytest.mark.skipif(os.getenv("MP_API_KEY", None) is None, reason="No API key found.") def test_client(rester): search_method = rester.search client_search_testing( search_method=search_method, excluded_params=excluded_params, alt_name_dict=alt_name_dict, custom_field_tests=custom_field_tests, sub_doc_fields=sub_doc_fields, ) api-0.45.3/tests/materials/test_electrodes.py000066400000000000000000000023731475770546700212740ustar00rootroot00000000000000import os from core_function import client_search_testing import pytest from pymatgen.core.periodic_table import Element from mp_api.client.routes.materials.electrodes import ElectrodeRester @pytest.fixture def rester(): rester = ElectrodeRester() yield rester rester.session.close() excluded_params = [ "sort_fields", "chunk_size", "num_chunks", "all_fields", "fields", ] sub_doc_fields = [] # type: list alt_name_dict = { "battery_ids": "battery_id", "formula": "battery_id", "exclude_elements": "battery_id", "num_elements": "nelements", "num_sites": "nsites", } # type: dict custom_field_tests = { "material_ids": ["mp-16722"], "battery_ids": ["mp-16722_Al"], "working_ion": Element("Li"), "formula": "CoO2", "chemsys": "Co-O", "elements": ["Co", "O"], "exclude_elements": ["Co"], } # type: dict @pytest.mark.skipif(os.getenv("MP_API_KEY", None) is None, reason="No API key found.") def test_client(rester): search_method = rester.search client_search_testing( search_method=search_method, excluded_params=excluded_params, alt_name_dict=alt_name_dict, custom_field_tests=custom_field_tests, sub_doc_fields=sub_doc_fields, ) api-0.45.3/tests/materials/test_electronic_structure.py000066400000000000000000000075351475770546700234170ustar00rootroot00000000000000import os from core_function import client_search_testing import pytest from pymatgen.analysis.magnetism import Ordering from mp_api.client.routes.materials.electronic_structure import ( BandStructureRester, DosRester, ElectronicStructureRester, ) @pytest.fixture def es_rester(): rester = ElectronicStructureRester() yield rester rester.session.close() es_excluded_params = [ "sort_fields", "chunk_size", "num_chunks", "all_fields", "fields", ] sub_doc_fields = [] # type: list es_alt_name_dict = { "material_ids": "material_id", "exclude_elements": "material_id", "formula": "material_id", "num_elements": "nelements", "num_sites": "nsites", } # type: dict es_custom_field_tests = { "material_ids": ["mp-149"], "magnetic_ordering": Ordering.FM, "formula": "CoO2", "chemsys": "Co-O", "elements": ["Co", "O"], "exclude_elements": ["Co"], } # type: dict @pytest.mark.skipif(os.getenv("MP_API_KEY", None) is None, reason="No API key found.") @pytest.mark.skip(reason="magnetic ordering fields not build correctly") def test_es_client(es_rester): search_method = es_rester.search client_search_testing( search_method=search_method, excluded_params=es_excluded_params, alt_name_dict=es_alt_name_dict, custom_field_tests=es_custom_field_tests, sub_doc_fields=sub_doc_fields, ) bs_custom_field_tests = { "magnetic_ordering": Ordering.FM, "is_metal": True, "is_gap_direct": True, "efermi": (0, 100), "band_gap": (0, 5), } bs_sub_doc_fields = ["bandstructure"] bs_alt_name_dict = {} # type: dict @pytest.fixture def bs_rester(): rester = BandStructureRester() yield rester rester.session.close() @pytest.mark.skipif(os.getenv("MP_API_KEY", None) is None, reason="No API key found.") @pytest.mark.skip(reason="magnetic ordering fields not build correctly") def test_bs_client(bs_rester): # Get specific search method search_method = bs_rester.search # Query fields for param in bs_custom_field_tests: project_field = bs_alt_name_dict.get(param, None) q = { param: bs_custom_field_tests[param], "chunk_size": 1, "num_chunks": 1, } doc = search_method(**q)[0].model_dump() for sub_field in bs_sub_doc_fields: if sub_field in doc: doc = doc[sub_field] if param != "path_type": doc = doc["setyawan_curtarolo"] assert doc[project_field if project_field is not None else param] is not None dos_custom_field_tests = { "magnetic_ordering": Ordering.FM, "efermi": (0, 100), "band_gap": (0, 5), } dos_excluded_params = ["orbital", "element"] dos_sub_doc_fields = ["dos"] dos_alt_name_dict = {} # type: dict @pytest.fixture def dos_rester(): rester = DosRester() yield rester rester.session.close() @pytest.mark.skipif(os.getenv("MP_API_KEY", None) is None, reason="No API key found.") @pytest.mark.skip(reason="magnetic ordering fields not build correctly") def test_dos_client(dos_rester): search_method = dos_rester.search # Query fields for param in dos_custom_field_tests: if param not in dos_excluded_params: project_field = dos_alt_name_dict.get(param, None) q = { param: dos_custom_field_tests[param], "chunk_size": 1, "num_chunks": 1, } doc = search_method(**q)[0].model_dump() for sub_field in dos_sub_doc_fields: if sub_field in doc: doc = doc[sub_field] if param != "projection_type" and param != "magnetic_ordering": doc = doc["total"]["1"] assert ( doc[project_field if project_field is not None else param] is not None ) api-0.45.3/tests/materials/test_eos.py000066400000000000000000000016361475770546700177320ustar00rootroot00000000000000import os from core_function import client_search_testing import pytest from mp_api.client.routes.materials.eos import EOSRester @pytest.fixture def rester(): rester = EOSRester() yield rester rester.session.close() excluded_params = [ "energies", "volumes", "sort_fields", "chunk_size", "num_chunks", "all_fields", "fields", ] sub_doc_fields = [] # type: list alt_name_dict = {"material_ids": "material_id"} # type: dict custom_field_tests = { # type: dict "material_ids": ["mp-149"] } @pytest.mark.skipif(os.getenv("MP_API_KEY", None) is None, reason="No API key found.") def test_client(rester): search_method = rester.search client_search_testing( search_method=search_method, excluded_params=excluded_params, alt_name_dict=alt_name_dict, custom_field_tests=custom_field_tests, sub_doc_fields=sub_doc_fields, ) api-0.45.3/tests/materials/test_grain_boundary.py000066400000000000000000000022401475770546700221370ustar00rootroot00000000000000import os from core_function import client_search_testing import pytest from emmet.core.grain_boundary import GBTypeEnum from mp_api.client.routes.materials.grain_boundaries import GrainBoundaryRester @pytest.fixture def rester(): rester = GrainBoundaryRester() yield rester rester.session.close() excluded_params = [ "sort_fields", "chunk_size", "num_chunks", "all_fields", "fields", ] sub_doc_fields = [] # type: list alt_name_dict = { "material_ids": "material_id", "separation_energy": "w_sep", } # type: dict custom_field_tests = { "material_ids": ["mp-81"], "gb_plane": ["1", "0", "0"], "rotation_axis": ["1", "0", "0"], "sigma": 5, "type": GBTypeEnum.twist, "chemsys": "Mo", "pretty_formula": "Mo", } # type: dict @pytest.mark.skipif(os.getenv("MP_API_KEY", None) is None, reason="No API key found.") def test_client(rester): search_method = rester.search client_search_testing( search_method=search_method, excluded_params=excluded_params, alt_name_dict=alt_name_dict, custom_field_tests=custom_field_tests, sub_doc_fields=sub_doc_fields, ) api-0.45.3/tests/materials/test_magnetism.py000066400000000000000000000017251475770546700211270ustar00rootroot00000000000000import os from core_function import client_search_testing import pytest from pymatgen.analysis.magnetism import Ordering from mp_api.client.routes.materials.magnetism import MagnetismRester @pytest.fixture def rester(): rester = MagnetismRester() yield rester rester.session.close() excluded_params = [ "sort_fields", "chunk_size", "num_chunks", "all_fields", "fields", ] sub_doc_fields = [] # type: list alt_name_dict = {"material_ids": "material_id"} # type: dict custom_field_tests = {"material_ids": ["mp-149"], "ordering": Ordering.FM} # type: dict @pytest.mark.skipif(os.getenv("MP_API_KEY", None) is None, reason="No API key found.") def test_client(rester): search_method = rester.search client_search_testing( search_method=search_method, excluded_params=excluded_params, alt_name_dict=alt_name_dict, custom_field_tests=custom_field_tests, sub_doc_fields=sub_doc_fields, ) api-0.45.3/tests/materials/test_materials.py000066400000000000000000000031401475770546700211150ustar00rootroot00000000000000import os from core_function import client_search_testing import pytest from emmet.core.symmetry import CrystalSystem from mp_api.client.routes.materials.materials import MaterialsRester @pytest.fixture def rester(): rester = MaterialsRester() yield rester rester.session.close() excluded_params = [ "sort_fields", "chunk_size", "num_chunks", "all_fields", "fields", "exclude_elements", # temp until server timeout increase "num_elements", # temp until server timeout increase "num_sites", # temp until server timeout increase "density", # temp until server timeout increase ] sub_doc_fields = [] # type: list alt_name_dict = { "material_ids": "material_id", "formula": "material_id", "crystal_system": "symmetry", "spacegroup_number": "symmetry", "spacegroup_symbol": "symmetry", "exclude_elements": "material_id", "num_elements": "nelements", "num_sites": "nsites", } # type: dict custom_field_tests = { "material_ids": ["mp-149"], "formula": "Si", "chemsys": "Si-P", "elements": ["Si", "P"], "task_ids": ["mp-149"], "crystal_system": CrystalSystem.cubic, "spacegroup_number": 38, "spacegroup_symbol": "Amm2", } # type: dict @pytest.mark.skipif(os.getenv("MP_API_KEY") is None, reason="No API key found.") def test_client(rester): search_method = rester.search client_search_testing( search_method=search_method, excluded_params=excluded_params, alt_name_dict=alt_name_dict, custom_field_tests=custom_field_tests, sub_doc_fields=sub_doc_fields, ) api-0.45.3/tests/materials/test_oxidation_states.py000066400000000000000000000020241475770546700225150ustar00rootroot00000000000000import os from core_function import client_search_testing import pytest from mp_api.client.routes.materials.oxidation_states import OxidationStatesRester @pytest.fixture def rester(): rester = OxidationStatesRester() yield rester rester.session.close() excluded_params = [ "sort_fields", "chunk_size", "num_chunks", "all_fields", "fields", ] sub_doc_fields = [] # type: list alt_name_dict = {"formula": "material_id", "material_ids": "material_id"} # type: dict custom_field_tests = { "material_ids": ["mp-149"], "formula": "Si", "chemsys": "Si-O", "possible_species": ["Cr2+", "O2-"], } # type: dict @pytest.mark.skipif(os.getenv("MP_API_KEY", None) is None, reason="No API key found.") def test_client(rester): search_method = rester.search client_search_testing( search_method=search_method, excluded_params=excluded_params, alt_name_dict=alt_name_dict, custom_field_tests=custom_field_tests, sub_doc_fields=sub_doc_fields, ) api-0.45.3/tests/materials/test_piezo.py000066400000000000000000000016601475770546700202670ustar00rootroot00000000000000import os from core_function import client_search_testing import pytest from mp_api.client.routes.materials.piezo import PiezoRester @pytest.fixture def rester(): rester = PiezoRester() yield rester rester.session.close() excluded_params = [ "sort_fields", "chunk_size", "num_chunks", "all_fields", "fields", ] sub_doc_fields = [] # type: list alt_name_dict = { "piezoelectric_modulus": "e_ij_max", "material_ids": "material_id", } # type: dict custom_field_tests = {"material_ids": ["mp-9900"]} # type: dict @pytest.mark.skipif(os.getenv("MP_API_KEY", None) is None, reason="No API key found.") def test_client(rester): search_method = rester.search client_search_testing( search_method=search_method, excluded_params=excluded_params, alt_name_dict=alt_name_dict, custom_field_tests=custom_field_tests, sub_doc_fields=sub_doc_fields, ) api-0.45.3/tests/materials/test_provenance.py000066400000000000000000000016161475770546700213020ustar00rootroot00000000000000import os from core_function import client_search_testing import pytest from mp_api.client.routes.materials.provenance import ProvenanceRester @pytest.fixture def rester(): rester = ProvenanceRester() yield rester rester.session.close() excluded_params = [ "sort_fields", "chunk_size", "num_chunks", "all_fields", "fields", ] sub_doc_fields = [] # type: list alt_name_dict = {"material_ids": "material_id"} # type: dict custom_field_tests = {"material_ids": ["mp-149"]} # type: dict @pytest.mark.skipif(os.getenv("MP_API_KEY", None) is None, reason="No API key found.") def test_client(rester): search_method = rester.search client_search_testing( search_method=search_method, excluded_params=excluded_params, alt_name_dict=alt_name_dict, custom_field_tests=custom_field_tests, sub_doc_fields=sub_doc_fields, ) api-0.45.3/tests/materials/test_robocrys.py000066400000000000000000000010711475770546700207770ustar00rootroot00000000000000import os import pytest from mp_api.client.routes.materials.robocrys import RobocrysRester @pytest.fixture def rester(): rester = RobocrysRester() yield rester rester.session.close() @pytest.mark.skipif(os.getenv("MP_API_KEY", None) is None, reason="No API key found.") def test_client(rester): search_method = rester.search if search_method is not None: q = {"keywords": ["silicon"], "num_chunks": 1} doc = search_method(**q)[0] assert doc.description is not None assert doc.condensed_structure is not None api-0.45.3/tests/materials/test_substrates.py000066400000000000000000000022151475770546700213350ustar00rootroot00000000000000import os from core_function import client_search_testing import pytest from mp_api.client.routes.materials.substrates import SubstratesRester @pytest.fixture def rester(): rester = SubstratesRester() yield rester rester.session.close() excluded_params = [ "sort_fields", "chunk_size", "num_chunks", "all_fields", "fields", ] sub_doc_fields = [] # type: list alt_name_dict = { "substrate_id": "sub_id", "substrate_formula": "sub_form", "film_orientation": "film_orient", "substrate_orientation": "orient", } # type: dict custom_field_tests = { "film_id": "mp-1046", "substrate_id": "mp-804", "substrate_formula": "GaN", "film_orientation": [1, 0, 0], "substrate_orientation": [1, 0, 0], } # type: dict @pytest.mark.skipif(os.getenv("MP_API_KEY", None) is None, reason="No API key found.") def test_client(rester): search_method = rester.search client_search_testing( search_method=search_method, excluded_params=excluded_params, alt_name_dict=alt_name_dict, custom_field_tests=custom_field_tests, sub_doc_fields=sub_doc_fields, ) api-0.45.3/tests/materials/test_summary.py000066400000000000000000000042031475770546700206320ustar00rootroot00000000000000import os from core_function import client_search_testing import pytest from emmet.core.summary import HasProps from emmet.core.symmetry import CrystalSystem from pymatgen.analysis.magnetism import Ordering from mp_api.client.routes.materials.summary import SummaryRester excluded_params = [ "include_gnome", "sort_fields", "chunk_size", "num_chunks", "all_fields", "fields", ] alt_name_dict = { "material_ids": "material_id", "formula": "formula_pretty", "exclude_elements": "formula_pretty", "piezoelectric_modulus": "e_ij_max", "crystal_system": "symmetry", "spacegroup_symbol": "symmetry", "spacegroup_number": "symmetry", "total_energy": "energy_per_atom", "formation_energy": "formation_energy_per_atom", "uncorrected_energy": "uncorrected_energy_per_atom", "equilibrium_reaction_energy": "equilibrium_reaction_energy_per_atom", "magnetic_ordering": "ordering", "elastic_anisotropy": "universal_anisotropy", "poisson_ratio": "homogeneous_poisson", "g_reuss": "bulk_modulus", "g_vrh": "bulk_modulus", "g_voigt": "bulk_modulus", "k_reuss": "shear_modulus", "k_vrh": "shear_modulus", "k_voigt": "shear_modulus", "num_sites": "nsites", "num_elements": "nelements", "surface_energy_anisotropy": "surface_anisotropy", } # type: dict custom_field_tests = { "material_ids": ["mp-149"], "formula": "SiO2", "chemsys": "Si-O", "elements": ["Si", "O"], "exclude_elements": ["Si", "O"], "possible_species": ["O2-"], "crystal_system": CrystalSystem.cubic, "spacegroup_number": 38, "spacegroup_symbol": "Amm2", "has_props": [HasProps.dielectric], "theoretical": True, "has_reconstructed": False, "magnetic_ordering": Ordering.FM, } # type: dict @pytest.mark.skipif(os.getenv("MP_API_KEY") is None, reason="No API key found.") def test_client(): search_method = SummaryRester().search client_search_testing( search_method=search_method, excluded_params=excluded_params, alt_name_dict=alt_name_dict, custom_field_tests=custom_field_tests, sub_doc_fields=[], ) api-0.45.3/tests/materials/test_surface_properties.py000066400000000000000000000017441475770546700230500ustar00rootroot00000000000000import os from core_function import client_search_testing import pytest from mp_api.client.routes.materials.surface_properties import SurfacePropertiesRester @pytest.fixture def rester(): rester = SurfacePropertiesRester() yield rester rester.session.close() excluded_params = [ "sort_fields", "chunk_size", "num_chunks", "all_fields", "fields", ] sub_doc_fields = [] # type: list alt_name_dict = { "surface_energy_anisotropy": "surface_anisotropy", "material_ids": "material_id", } # type: dict custom_field_tests = {"material_ids": ["mp-23152"]} # type: dict @pytest.mark.skipif(os.getenv("MP_API_KEY", None) is None, reason="No API key found.") def test_client(rester): search_method = rester.search client_search_testing( search_method=search_method, excluded_params=excluded_params, alt_name_dict=alt_name_dict, custom_field_tests=custom_field_tests, sub_doc_fields=sub_doc_fields, ) api-0.45.3/tests/materials/test_synthesis.py000066400000000000000000000110511475770546700211650ustar00rootroot00000000000000import os from typing import List import pytest from emmet.core.synthesis import SynthesisRecipe, SynthesisTypeEnum from mp_api.client.routes.materials.synthesis import SynthesisRester @pytest.fixture def rester(): rester = SynthesisRester() yield rester rester.session.close() @pytest.mark.skipif(os.getenv("MP_API_KEY", None) is None, reason="No API key found.") def test_client(rester): search_method = rester.search if search_method is not None: q = {"keywords": ["silicon"]} doc = search_method(**q)[0] assert doc.doi is not None assert doc.paragraph_string is not None assert doc.synthesis_type is not None @pytest.mark.skipif(os.getenv("MP_API_KEY", None) is None, reason="No API key found.") def test_filters_keywords(rester): search_method = rester.search if search_method is not None: doc = search_method(keywords=["silicon"])[0] assert isinstance(doc.search_score, float) highlighted = sum((x["texts"] for x in doc.highlights), []) assert "silicon" in " ".join([x["value"] for x in highlighted]).lower() @pytest.mark.skipif(os.getenv("MP_API_KEY", None) is None, reason="No API key found.") def test_filters_synthesis_type(rester): search_method = rester.search if search_method is not None: doc = search_method( synthesis_type=[SynthesisTypeEnum.solid_state], num_chunks=1 ) assert all(x.synthesis_type == SynthesisTypeEnum.solid_state for x in doc) doc = search_method(synthesis_type=[SynthesisTypeEnum.sol_gel], num_chunks=1) assert all(x.synthesis_type == SynthesisTypeEnum.sol_gel for x in doc) @pytest.mark.skipif(os.getenv("MP_API_KEY", None) is None, reason="No API key found.") @pytest.mark.xfail # Needs fixing def test_filters_temperature_range(rester): search_method = rester.search if search_method is not None: docs: List[SynthesisRecipe] = search_method( condition_heating_temperature_min=700, condition_heating_temperature_max=1000, num_chunks=5, ) for doc in docs: for op in doc.operations: for temp in op.conditions.heating_temperature: for val in temp.values: assert 700 <= val <= 1000 @pytest.mark.skipif(os.getenv("MP_API_KEY", None) is None, reason="No API key found.") @pytest.mark.xfail # Needs fixing def test_filters_time_range(rester): search_method = rester.search if search_method is not None: docs: List[SynthesisRecipe] = search_method( condition_heating_time_min=7, condition_heating_time_max=11, num_chunks=5 ) for doc in docs: for op in doc.operations: for temp in op.conditions.heating_time: for val in temp.values: assert 7 <= val <= 11 @pytest.mark.skipif(os.getenv("MP_API_KEY", None) is None, reason="No API key found.") def test_filters_atmosphere(rester): search_method = rester.search if search_method is not None: docs: List[SynthesisRecipe] = search_method( condition_heating_atmosphere=["air", "O2"], num_chunks=5, ) for doc in docs: found = False for op in doc.operations: for atm in op.conditions.heating_atmosphere: if atm in ["air", "O2"]: found = True assert found @pytest.mark.skipif(os.getenv("MP_API_KEY", None) is None, reason="No API key found.") def test_filters_mixing_device(rester): search_method = rester.search if search_method is not None: docs: List[SynthesisRecipe] = search_method( condition_mixing_device=["zirconia", "Al2O3"], num_chunks=5, ) for doc in docs: found = False for op in doc.operations: if op.conditions.mixing_device in ["zirconia", "Al2O3"]: found = True assert found @pytest.mark.skipif(os.getenv("MP_API_KEY", None) is None, reason="No API key found.") def test_filters_mixing_media(rester): search_method = rester.search if search_method is not None: docs: List[SynthesisRecipe] = search_method( condition_mixing_media=["water", "alcohol"], num_chunks=5, ) for doc in docs: found = False for op in doc.operations: if op.conditions.mixing_media in ["water", "alcohol"]: found = True assert found api-0.45.3/tests/materials/test_tasks.py000066400000000000000000000024631475770546700202700ustar00rootroot00000000000000import os from core_function import client_search_testing from datetime import datetime import pytest from mp_api.client.routes.materials.tasks import TaskRester @pytest.fixture def rester(): rester = TaskRester(monty_decode=False) yield rester rester.session.close() excluded_params = [ "sort_fields", "chunk_size", "num_chunks", "all_fields", "fields", "formula", "elements", "exclude_elements", ] sub_doc_fields = [] # type: list alt_name_dict = { "formula": "task_id", "task_ids": "task_id", "exclude_elements": "task_id", } # type: dict custom_field_tests = { "chemsys": "Si-O", "last_updated": (None, datetime.utcnow()), "task_ids": ["mp-149"], } # type: dict @pytest.mark.skipif(os.getenv("MP_API_KEY") is None, reason="No API key found.") def test_client(rester): search_method = rester.search client_search_testing( search_method=search_method, excluded_params=excluded_params, alt_name_dict=alt_name_dict, custom_field_tests=custom_field_tests, sub_doc_fields=sub_doc_fields, ) def test_get_trajectories(rester): trajectories = [traj for traj in rester.get_trajectory("mp-149")] for traj in trajectories: assert ("@module", "pymatgen.core.trajectory") in traj.items() api-0.45.3/tests/materials/test_thermo.py000066400000000000000000000033661475770546700204440ustar00rootroot00000000000000import os from core_function import client_search_testing import pytest from emmet.core.thermo import ThermoType from pymatgen.analysis.phase_diagram import PhaseDiagram from mp_api.client.routes.materials.thermo import ThermoRester @pytest.fixture def rester(): rester = ThermoRester() yield rester rester.session.close() excluded_params = [ "sort_fields", "chunk_size", "num_chunks", "all_fields", "fields", "equilibrium_reaction_energy", ] sub_doc_fields = [] # type: list alt_name_dict = { "formula": "formula_pretty", "material_ids": "material_id", "thermo_ids": "thermo_id", "thermo_types": "thermo_type", "total_energy": "energy_per_atom", "formation_energy": "formation_energy_per_atom", "uncorrected_energy": "uncorrected_energy_per_atom", "equilibrium_reaction_energy": "equilibrium_reaction_energy_per_atom", "num_elements": "nelements", "num_sites": "nsites", } # type: dict custom_field_tests = { "material_ids": ["mp-149"], "thermo_ids": ["mp-149_GGA_GGA+U"], "thermo_types": [ThermoType.GGA_GGA_U], "formula": "SiO2", "chemsys": "Si-O", } # type: dict @pytest.mark.skipif(os.getenv("MP_API_KEY") is None, reason="No API key found.") def test_client(rester): search_method = rester.search client_search_testing( search_method=search_method, excluded_params=excluded_params, alt_name_dict=alt_name_dict, custom_field_tests=custom_field_tests, sub_doc_fields=sub_doc_fields, ) def test_get_phase_diagram_from_chemsys(): # Test that a phase diagram is returned assert isinstance( ThermoRester().get_phase_diagram_from_chemsys("Hf-Pm", thermo_type="GGA_GGA+U"), PhaseDiagram, ) api-0.45.3/tests/materials/test_xas.py000066400000000000000000000024501475770546700177320ustar00rootroot00000000000000import os from core_function import client_search_testing import pytest from emmet.core.xas import Edge, Type from pymatgen.core.periodic_table import Element from mp_api.client.routes.materials.xas import XASRester @pytest.fixture def rester(): rester = XASRester() yield rester rester.session.close() excluded_params = [ "sort_fields", "chunk_size", "num_chunks", "all_fields", "fields", "material_ids", ] sub_doc_fields = [] # type: list alt_name_dict = { "required_elements": "elements", "formula": "formula_pretty", "exclude_elements": "material_id", } # type: dict custom_field_tests = { "edge": Edge.L2_3, "spectrum_type": Type.EXAFS, "absorbing_element": Element("Ce"), "required_elements": [Element("Ce")], "formula": "Ce(WO4)2", "chemsys": "Ce-O-W", "elements": ["Ce"], } # type: dict @pytest.mark.skip(reason="Temp skip until timeout update.") @pytest.mark.skipif(os.getenv("MP_API_KEY") is None, reason="No API key found.") def test_client(rester): search_method = rester.search client_search_testing( search_method=search_method, excluded_params=excluded_params, alt_name_dict=alt_name_dict, custom_field_tests=custom_field_tests, sub_doc_fields=sub_doc_fields, ) api-0.45.3/tests/molecules/000077500000000000000000000000001475770546700155345ustar00rootroot00000000000000api-0.45.3/tests/molecules/__init__.py000066400000000000000000000000001475770546700176330ustar00rootroot00000000000000api-0.45.3/tests/molecules/core_function.py000066400000000000000000000046431475770546700207520ustar00rootroot00000000000000from __future__ import annotations from typing import Callable, Any def client_search_testing( search_method: Callable, excluded_params: list[str], alt_name_dict: dict[str, str], custom_field_tests: dict[str, Any], sub_doc_fields: list[str], ): """ Function to test a client using its search method. Each parameter is used to query for data, which is then checked. Args: search_method (Callable): Client search method excluded_params (list[str]): List of parameters to exclude from testing alt_name_dict (dict[str, str]): Alternative names for parameters used in the projection and subsequent data checking custom_field_tests (dict[str, Any]): Custom queries for specific fields. sub_doc_fields (list[str]): Prefixes for fields to check in resulting data. Useful when data to be tested is nested. """ if search_method is not None: # Get list of parameters param_tuples = list(search_method.__annotations__.items()) # Query API for each numeric and boolean parameter and check if returned for entry in param_tuples: param = entry[0] if param not in excluded_params: param_type = entry[1] q = None if param in custom_field_tests: q = { param: custom_field_tests[param], "chunk_size": 1, "num_chunks": 1, } elif "tuple[int, int]" in param_type: q = { param: (-100, 100), "chunk_size": 1, "num_chunks": 1, } elif "tuple[float, float]" in param_type: q = { param: (-3000.12, 3000.12), "chunk_size": 1, "num_chunks": 1, } elif param_type is bool: q = { param: False, "chunk_size": 1, "num_chunks": 1, } docs = search_method(**q) if len(docs) > 0: doc = docs[0].model_dump() else: raise ValueError("No documents returned") assert doc[alt_name_dict.get(param, param)] is not None api-0.45.3/tests/molecules/test_jcesr.py000066400000000000000000000020431475770546700202520ustar00rootroot00000000000000import os from .core_function import client_search_testing import pytest from pymatgen.core.periodic_table import Element from mp_api.client.routes.molecules.jcesr import JcesrMoleculesRester @pytest.fixture def rester(): rester = JcesrMoleculesRester() yield rester rester.session.close() excluded_params = [ "sort_fields", "chunk_size", "num_chunks", "all_fields", "fields", "charge", ] sub_doc_fields = [] # type: list alt_name_dict = {"task_ids": "task_id"} # type: dict custom_field_tests = { "task_ids": ["mol-45228"], "elements": [Element("H")], "pointgroup": "C1", "smiles": "C#CC(=C)C.CNCCNC", } # type: dict @pytest.mark.skipif(os.getenv("MP_API_KEY") is None, reason="No API key found.") def test_client(rester): search_method = rester.search client_search_testing( search_method=search_method, excluded_params=excluded_params, alt_name_dict=alt_name_dict, custom_field_tests=custom_field_tests, sub_doc_fields=sub_doc_fields, ) api-0.45.3/tests/molecules/test_summary.py000066400000000000000000000025441475770546700206470ustar00rootroot00000000000000import os from .core_function import client_search_testing import pytest from emmet.core.molecules.summary import HasProps from mp_api.client.routes.molecules.summary import MoleculesSummaryRester excluded_params = [ "sort_fields", "chunk_size", "num_chunks", "all_fields", "fields", "exclude_elements", "has_props", ] alt_name_dict = {"formula": "formula_alphabetical", "molecule_ids": "molecule_id"} custom_field_tests = { "molecule_ids": ["351ef090ebd90b661a4e1205756f6957-C1Mg1N2O1S1-m2-1"], "formula": "C2 H4", "chemsys": "C-H", "elements": ["P"], "has_solvent": "DIELECTRIC=18,500;N=1,415;ALPHA=0,000;BETA=0,735;GAMMA=20,200;PHI=0,000;PSI=0,000", "has_level_of_theory": "wB97X-V/def2-TZVPPD/SMD", "has_lot_solvent": "wB97X-V/def2-TZVPPD/SMD(SOLVENT=THF)", "nelements": 2, "charge": 1, "spin_multiplicity": 1, "has_props": [HasProps.orbitals], } # type: dict @pytest.mark.skip(reason="Temporary until data adjustments") @pytest.mark.skipif(os.getenv("MP_API_KEY") is None, reason="No API key found.") def test_client(): search_method = MoleculesSummaryRester().search client_search_testing( search_method=search_method, excluded_params=excluded_params, alt_name_dict=alt_name_dict, custom_field_tests=custom_field_tests, sub_doc_fields=[], ) api-0.45.3/tests/test_client.py000066400000000000000000000046521475770546700164420ustar00rootroot00000000000000import os import warnings import pytest from mp_api.client import MPRester from mp_api.client.routes.materials import TaskRester, ProvenanceRester # -- Rester name data for generic tests key_only_resters = { "materials_phonon": "mp-11703", "materials_similarity": "mp-149", "doi": "mp-149", "materials_wulff": "mp-149", "materials_charge_density": "mp-1936745", "materials_provenance": "mp-149", "materials_robocrys": "mp-1025395", } search_only_resters = [ "materials_grain_boundaries", "materials_electronic_structure_bandstructure", "materials_electronic_structure_dos", "materials_substrates", "materials_synthesis", "materials_similarity", ] special_resters = ["materials_charge_density", "doi"] ignore_generic = [ "_user_settings", "_general_store", "_messages", # "tasks", # "bonds", "materials_xas", "materials_elasticity", "materials_fermi", "materials_alloys", # "summary", ] # temp mpr = MPRester() # Temporarily ignore molecules resters while molecules query operators are changed resters_to_test = [ rester for rester in mpr._all_resters if "molecule" not in rester.suffix ] @pytest.mark.skipif(os.getenv("MP_API_KEY") is None, reason="No API key found.") @pytest.mark.parametrize("rester", resters_to_test) def test_generic_get_methods(rester): # -- Test generic search and get_data_by_id methods name = rester.suffix.replace("/", "_") rester = rester( endpoint=mpr.endpoint, include_user_agent=True, session=mpr.session, # Disable monty decode on nested data which may give errors monty_decode=rester not in [TaskRester, ProvenanceRester], use_document_model=True, ) if name not in ignore_generic: key = rester.primary_key if name not in key_only_resters: if key not in rester.available_fields: key = rester.available_fields[0] doc = rester._query_resource_data({"_limit": 1}, fields=[key])[0] assert isinstance(doc, rester.document_model) if name not in search_only_resters: doc = rester.get_data_by_id(doc.model_dump()[key], fields=[key]) assert isinstance(doc, rester.document_model) elif name not in special_resters: doc = rester.get_data_by_id(key_only_resters[name], fields=[key]) assert isinstance(doc, rester.document_model) api-0.45.3/tests/test_core_client.py000066400000000000000000000022151475770546700174430ustar00rootroot00000000000000import os import pytest from mp_api.client import MPRester from mp_api.client.core import BaseRester @pytest.fixture def rester(): rester = BaseRester() yield rester rester.session.close() @pytest.fixture() def mpr(): rester = MPRester() yield rester rester.session.close() @pytest.mark.skipif(os.getenv("MP_API_KEY", None) is None, reason="No API key found.") @pytest.mark.xfail def test_post_fail(rester): rester._post_resource({}, suburl="materials/find_structure") @pytest.mark.skipif(os.getenv("MP_API_KEY", None) is None, reason="No API key found.") def test_pagination(mpr): mpids = mpr.materials.search( all_fields=False, fields=["material_id"], num_chunks=2, chunk_size=1000 ) assert len(mpids) > 1000 @pytest.mark.skipif(os.getenv("MP_API_KEY", None) is None, reason="No API key found.") def test_count(mpr): count = mpr.materials.count( dict(task_ids="mp-149", _all_fields=False, _fields="material_id") ) assert count == 1 def test_available_fields(rester, mpr): assert len(mpr.materials.available_fields) > 0 assert rester.available_fields == ["Unknown fields."] api-0.45.3/tests/test_mprester.py000066400000000000000000000413171475770546700170240ustar00rootroot00000000000000import itertools import os import random import importlib import numpy as np import pytest from emmet.core.tasks import TaskDoc from emmet.core.vasp.calc_types import CalcType from pymatgen.analysis.phase_diagram import PhaseDiagram from pymatgen.analysis.pourbaix_diagram import IonEntry, PourbaixDiagram, PourbaixEntry from pymatgen.analysis.wulff import WulffShape from pymatgen.core import SETTINGS from pymatgen.core.ion import Ion from pymatgen.core.periodic_table import Element from pymatgen.electronic_structure.bandstructure import ( BandStructure, BandStructureSymmLine, ) from pymatgen.electronic_structure.dos import CompleteDos from pymatgen.entries.compatibility import MaterialsProjectAqueousCompatibility from pymatgen.entries.computed_entries import ComputedEntry, GibbsComputedStructureEntry from pymatgen.io.cif import CifParser from pymatgen.io.vasp import Chgcar from pymatgen.phonon.bandstructure import PhononBandStructureSymmLine from pymatgen.phonon.dos import PhononDos from mp_api.client import MPRester from mp_api.client.core.client import MPRestError from mp_api.client.core.settings import MAPIClientSettings @pytest.fixture() def mpr(): rester = MPRester() yield rester rester.session.close() @pytest.mark.skipif(os.getenv("MP_API_KEY", None) is None, reason="No API key found.") class TestMPRester: fake_mp_api_key = "12345678901234567890123456789012" # 32 chars default_endpoint = "https://api.materialsproject.org/" def test_get_structure_by_material_id(self, mpr): s0 = mpr.get_structure_by_material_id("mp-149") assert s0.formula == "Si2" s1 = mpr.get_structure_by_material_id("mp-4163", conventional_unit_cell=True) assert s1.formula == "Ca12 Ti8 O28" s2 = mpr.get_structure_by_material_id("mp-149", final=False) assert {s.formula for s in s2} == {"Si2"} def test_get_database_version(self, mpr): db_version = mpr.get_database_version() assert db_version is not None def test_get_material_id_from_task_id(self, mpr): assert mpr.get_material_id_from_task_id("mp-540081") == "mp-19017" def test_get_task_ids_associated_with_material_id(self, mpr): results = mpr.get_task_ids_associated_with_material_id( "mp-149", calc_types=[CalcType.GGA_Static, CalcType.GGA_U_Static] ) assert len(results) > 0 def test_get_material_id_references(self, mpr): data = mpr.get_material_id_references("mp-123") assert len(data) > 5 def test_get_material_id_doc(self, mpr): mp_ids = mpr.get_material_ids("Al2O3") random.shuffle(mp_ids) doc = mpr.materials.search(material_ids=mp_ids.pop(0))[0] assert doc.formula_pretty == "Al2O3" mp_ids = mpr.get_material_ids("Al-O") random.shuffle(mp_ids) doc = mpr.materials.search(material_ids=mp_ids.pop(0))[0] assert doc.chemsys == "Al-O" def test_get_structures(self, mpr): structs = mpr.get_structures("Mn3O4") assert len(structs) > 0 structs = mpr.get_structures("Mn-O", final=False) assert len(structs) > 0 @pytest.mark.skip(reason="Endpoint issues") def test_find_structure(self, mpr): path = os.path.join(MAPIClientSettings().TEST_FILES, "Si_mp_149.cif") with open(path) as file: data = mpr.find_structure(path) assert len(data) > 0 s = CifParser(file).get_structures()[0] data = mpr.find_structure(s) assert len(data) > 0 def test_get_bandstructure_by_material_id(self, mpr): bs = mpr.get_bandstructure_by_material_id("mp-149") assert isinstance(bs, BandStructureSymmLine) bs_uniform = mpr.get_bandstructure_by_material_id("mp-149", line_mode=False) assert isinstance(bs_uniform, BandStructure) assert not isinstance(bs_uniform, BandStructureSymmLine) def test_get_dos_by_id(self, mpr): dos = mpr.get_dos_by_material_id("mp-149") assert isinstance(dos, CompleteDos) def test_get_entry_by_material_id(self, mpr): e = mpr.get_entry_by_material_id("mp-19017") assert isinstance(e[0], ComputedEntry) assert e[0].composition.reduced_formula == "LiFePO4" def test_get_entries(self, mpr): syms = ["Li", "Fe", "O"] chemsys = "Li-Fe-O" entries = mpr.get_entries(chemsys) elements = {Element(sym) for sym in syms} for e in entries: assert isinstance(e, ComputedEntry) assert set(e.composition.elements).issubset(elements) # Formula formula = "SiO2" entries = mpr.get_entries(formula) for e in entries: assert isinstance(e, ComputedEntry) # Property data formula = "BiFeO3" entries = mpr.get_entries(formula, property_data=["energy_above_hull"]) for e in entries: assert e.data.get("energy_above_hull", None) is not None # Conventional structure entry = mpr.get_entry_by_material_id("mp-22526", conventional_unit_cell=True)[1] s = entry.structure assert pytest.approx(s.lattice.a) == s.lattice.b assert pytest.approx(s.lattice.a) != s.lattice.c assert pytest.approx(s.lattice.alpha) == 90 assert pytest.approx(s.lattice.beta) == 90 assert pytest.approx(s.lattice.gamma) == 120 # Ensure energy per atom is same prim = mpr.get_entry_by_material_id("mp-22526", conventional_unit_cell=False)[1] s = prim.structure assert pytest.approx(s.lattice.a) == s.lattice.b assert pytest.approx(s.lattice.a, abs=1e-3) == s.lattice.c assert pytest.approx(s.lattice.alpha, abs=1e-3) == s.lattice.beta assert pytest.approx(s.lattice.alpha, abs=1e-3) == s.lattice.gamma # Additional criteria entry = mpr.get_entries( "mp-149", additional_criteria={"energy_above_hull": (0.0, 10)}, property_data=["energy_above_hull"], )[0] assert "energy_above_hull" in entry.data entries = mpr.get_entries( "mp-149", additional_criteria={"energy_above_hull": (1, 10)}, property_data=["energy_above_hull"], ) assert len(entries) == 0 def test_get_entries_in_chemsys(self, mpr): syms = ["Li", "Fe", "O"] syms2 = "Li-Fe-O" entries = mpr.get_entries_in_chemsys(syms) entries2 = mpr.get_entries_in_chemsys(syms2) elements = {Element(sym) for sym in syms} for e in entries: assert isinstance(e, ComputedEntry) assert set(e.composition.elements).issubset(elements) e1 = {i.entry_id for i in entries} e2 = {i.entry_id for i in entries2} assert e1 == e2 gibbs_entries = mpr.get_entries_in_chemsys(syms2, use_gibbs=500) for e in gibbs_entries: assert isinstance(e, GibbsComputedStructureEntry) @pytest.mark.skip(reason="SSL issues") def test_get_pourbaix_entries(self, mpr): # test input chemsys as a list of elements pbx_entries = mpr.get_pourbaix_entries(["Fe", "Cr"]) for pbx_entry in pbx_entries: assert isinstance(pbx_entry, PourbaixEntry) # test input chemsys as a string pbx_entries = mpr.get_pourbaix_entries("Fe-Cr") for pbx_entry in pbx_entries: assert isinstance(pbx_entry, PourbaixEntry) # test use_gibbs kwarg pbx_entries = mpr.get_pourbaix_entries("Li-O", use_gibbs=300) for pbx_entry in pbx_entries: assert isinstance(pbx_entry, PourbaixEntry) # test solid_compat kwarg with pytest.raises(ValueError, match="Solid compatibility can only be"): mpr.get_pourbaix_entries("Ti-O", solid_compat=None) # test removal of extra elements from reference solids # Li-Zn-S has Na in reference solids pbx_entries = mpr.get_pourbaix_entries("Li-Zn-S") assert not any(e for e in pbx_entries if "Na" in e.composition) # Ensure entries are pourbaix compatible PourbaixDiagram(pbx_entries) # TODO - old tests copied from pymatgen with specific energy values. Update or delete # fe_two_plus = [e for e in pbx_entries if e.entry_id == "ion-0"][0] # self.assertAlmostEqual(fe_two_plus.energy, -1.12369, places=3) # # feo2 = [e for e in pbx_entries if e.entry_id == "mp-25332"][0] # self.assertAlmostEqual(feo2.energy, 3.56356, places=3) # # # Test S, which has Na in reference solids # pbx_entries = self.rester.get_pourbaix_entries(["S"]) # so4_two_minus = pbx_entries[9] # self.assertAlmostEqual(so4_two_minus.energy, 0.301511, places=3) @pytest.mark.skip(reason="SSL issues") def test_get_ion_entries(self, mpr): entries = mpr.get_entries_in_chemsys("Ti-O-H") pd = PhaseDiagram(entries) ion_entry_data = mpr.get_ion_reference_data_for_chemsys("Ti-O-H") ion_entries = mpr.get_ion_entries(pd, ion_entry_data) assert len(ion_entries) == 5 assert all([isinstance(i, IonEntry) for i in ion_entries]) bi_v_entry_data = mpr.get_ion_reference_data_for_chemsys("Bi-V") bi_data = mpr.get_ion_reference_data_for_chemsys("Bi") v_data = mpr.get_ion_reference_data_for_chemsys("V") assert len(bi_v_entry_data) == len(bi_data) + v_data # test an incomplete phase diagram entries = mpr.get_entries_in_chemsys("Ti-O") pd = PhaseDiagram(entries) with pytest.raises(ValueError, match="The phase diagram chemical system"): mpr.get_ion_entries(pd) # test ion energy calculation ion_data = mpr.get_ion_reference_data_for_chemsys("S") ion_ref_comps = [ Ion.from_formula(d["data"]["RefSolid"]).composition for d in ion_data ] ion_ref_elts = set( itertools.chain.from_iterable(i.elements for i in ion_ref_comps) ) ion_ref_entries = mpr.get_entries_in_chemsys( [*map(str, ion_ref_elts), "O", "H"] ) mpc = MaterialsProjectAqueousCompatibility() ion_ref_entries = mpc.process_entries(ion_ref_entries) ion_ref_pd = PhaseDiagram(ion_ref_entries) ion_entries = mpr.get_ion_entries(ion_ref_pd, ion_ref_data=ion_data) # In ion ref data, SO4-2 is -744.27 kJ/mol; ref solid is -1,279.0 kJ/mol # so the ion entry should have an energy (-744.27 +1279) = 534.73 kJ/mol # or 5.542 eV/f.u. above the energy of Na2SO4 so4_two_minus = [e for e in ion_entries if e.ion.reduced_formula == "SO4[-2]"][ 0 ] # the ref solid is Na2SO4, ground state mp-4770 # the rf factor correction is necessary to make sure the composition # of the reference solid is normalized to a single formula unit ref_solid_entry = [e for e in ion_ref_entries if e.entry_id == "mp-4770"][0] rf = ref_solid_entry.composition.get_reduced_composition_and_factor()[1] solid_energy = ion_ref_pd.get_form_energy(ref_solid_entry) / rf assert np.allclose(so4_two_minus.energy, solid_energy + 5.542, atol=1e-3) def test_get_phonon_data_by_material_id(self, mpr): bs = mpr.get_phonon_bandstructure_by_material_id("mp-2172") assert isinstance(bs, PhononBandStructureSymmLine) dos = mpr.get_phonon_dos_by_material_id("mp-2172") assert isinstance(dos, PhononDos) def test_get_charge_density_from_material_id(self, mpr): chgcar = mpr.get_charge_density_from_material_id("mp-149") assert isinstance(chgcar, Chgcar) chgcar, task_doc = mpr.get_charge_density_from_material_id( "mp-149", inc_task_doc=True ) assert isinstance(chgcar, Chgcar) assert isinstance(task_doc, TaskDoc) def test_get_charge_density_from_task_id(self, mpr): chgcar = mpr.get_charge_density_from_task_id("mp-2246557") assert isinstance(chgcar, Chgcar) chgcar, task_doc = mpr.get_charge_density_from_task_id( "mp-2246557", inc_task_doc=True ) assert isinstance(chgcar, Chgcar) assert isinstance(task_doc, TaskDoc) def test_get_wulff_shape(self, mpr): ws = mpr.get_wulff_shape("mp-126") assert isinstance(ws, WulffShape) def test_large_list(self, mpr): mpids = [ str(doc.material_id) for doc in mpr.summary.search( chunk_size=1000, num_chunks=10, fields=["material_id"] ) ] docs = mpr.summary.search(material_ids=mpids, fields=["material_id"]) assert len(docs) == 10000 def test_get_api_key_endpoint_from_env_var(self, monkeypatch: pytest.MonkeyPatch): """Ensure the MP_API_KEY and MP_API_ENDPOINT from environment variable is retrieved at runtime, not import time. """ # Mock an invalid key and endpoint set before import MPRester import mp_api.client monkeypatch.setenv("MP_API_ENDPOINT", "INVALID ENDPOINT") monkeypatch.setenv("MP_API_KEY", "INVALID KEY") importlib.reload(mp_api.client) from mp_api.client import MPRester monkeypatch.setenv("MP_API_KEY", self.fake_mp_api_key) monkeypatch.setenv("MP_API_ENDPOINT", self.default_endpoint) assert MPRester().api_key == self.fake_mp_api_key assert MPRester().endpoint == self.default_endpoint def test_get_api_key_endpoint_from_settings(self, monkeypatch: pytest.MonkeyPatch): """Test environment variable "MP_API_KEY" is not set and get "PMG_MAPI_KEY" from "SETTINGS". """ monkeypatch.delenv("MP_API_KEY", raising=False) # patch pymatgen.core.SETTINGS to contain PMG_MAPI_KEY monkeypatch.setitem(SETTINGS, "PMG_MAPI_KEY", self.fake_mp_api_key) assert MPRester().api_key == self.fake_mp_api_key def test_get_default_api_key_endpoint(self, monkeypatch: pytest.MonkeyPatch): monkeypatch.delenv("MP_API_ENDPOINT", raising=False) assert MPRester().endpoint == self.default_endpoint monkeypatch.delenv("MP_API_KEY", raising=False) with pytest.raises(MPRestError, match="No API key found in request"): MPRester().get_structure_by_material_id("mp-149") def test_invalid_api_key(self, monkeypatch): monkeypatch.setenv("MP_API_KEY", "INVALID") with pytest.raises(ValueError, match="Keys for the new API are 32 characters"): MPRester().get_structure_by_material_id("mp-149") def test_get_cohesive_energy_per_atom_utility(self): composition = { "H": 5, "V": 2, "P": 3, } toten_per_atom = -2.0e3 atomic_energies = {"H": -13.6, "V": -7.2, "P": -0.1} by_hand_e_coh = toten_per_atom - sum( atomic_energies[k] * v for k, v in composition.items() ) / sum(composition.values()) assert MPRester._get_cohesive_energy( composition, toten_per_atom, atomic_energies ) == pytest.approx(by_hand_e_coh) def test_get_atom_references(self, mpr): ae = mpr.get_atom_reference_data(funcs=("PBE",)) assert list(ae) == ["PBE"] assert len(ae["PBE"]) == 89 assert all(isinstance(v, float) for v in ae["PBE"].values()) ae = mpr.get_atom_reference_data() assert set(ae) == {"PBE", "r2SCAN", "SCAN"} assert all(len(entries) == 89 for entries in ae.values()) assert all( isinstance(v, float) for entries in ae.values() for v in entries.values() ) def test_get_cohesive_energy(self): ref_e_coh = { "atom": { "mp-123": -4.029208982500002, "mp-149": -4.669184594999999, "mp-4163": -6.351402620416668, "mp-19017": -4.933409960714286, }, "formula_unit": { "mp-123": -4.029208982500002, "mp-149": -4.669184594999999, "mp-4163": -76.21683144500001, "mp-19017": -34.533869725, }, } e_coh = {} for monty_decode in (True, False): with MPRester( use_document_model=monty_decode, monty_decode=monty_decode ) as _mpr: for norm, refs in ref_e_coh.items(): _e_coh = _mpr.get_cohesive_energy(list(refs), normalization=norm) if norm == "atom": e_coh["serial" if monty_decode else "noserial"] = _e_coh.copy() # Ensure energies match reference data assert all(v == pytest.approx(refs[k]) for k, v in _e_coh.items()) # Ensure energies are the same regardless of serialization assert all( v == pytest.approx(e_coh["noserial"][k]) for k, v in e_coh["serial"].items() )