pax_global_header00006660000000000000000000000064141746517560014532gustar00rootroot0000000000000052 comment=1f5f1121b9174ac9b1f9c12ee431daf37bbcb6ed kazhala-pfzy-1f5f112/000077500000000000000000000000001417465175600144625ustar00rootroot00000000000000kazhala-pfzy-1f5f112/.github/000077500000000000000000000000001417465175600160225ustar00rootroot00000000000000kazhala-pfzy-1f5f112/.github/workflows/000077500000000000000000000000001417465175600200575ustar00rootroot00000000000000kazhala-pfzy-1f5f112/.github/workflows/ci.yaml000066400000000000000000000032561417465175600213440ustar00rootroot00000000000000name: CI on: [push, pull_request] jobs: pyright: name: Pyright Lint runs-on: ubuntu-latest steps: - uses: actions/checkout@v2 - name: Setup python uses: actions/setup-python@v2 with: python-version: 3.9 - name: Install poetry uses: abatilo/actions-poetry@v2.0.0 with: poetry-version: 1.1.5 - name: Install dependencies run: poetry install --no-dev - name: Setup node uses: actions/setup-node@v1 with: node-version: 12 - name: Install pyright run: npm install -g pyright - name: Pyright check run: pyright InquirerPy pre-commit: name: Pre-commit Check runs-on: ubuntu-latest steps: - uses: actions/checkout@v2 - name: Setup python uses: actions/setup-python@v2 with: python-version: 3.9 - name: Run pre-commit uses: pre-commit/action@v2.0.0 unittest: name: Unit Test runs-on: ubuntu-latest strategy: matrix: python-version: [3.8, 3.9] steps: - uses: actions/checkout@v2 - name: Setup python uses: actions/setup-python@v2 with: python-version: ${{ matrix.python-version }} - name: Install poetry uses: abatilo/actions-poetry@v2.0.0 with: poetry-version: 1.1.7 - name: Install dependencies run: poetry install - name: Test with pytest run: poetry run pytest --cov=pfzy - name: Report coverage if: matrix.python-version == 3.8 env: GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }} run: poetry run coveralls --service=github kazhala-pfzy-1f5f112/.gitignore000066400000000000000000000037631417465175600164630ustar00rootroot00000000000000# Byte-compiled / optimized / DLL files __pycache__/ *.py[cod] *$py.class # C extensions *.so # Distribution / packaging .Python build/ develop-eggs/ dist/ downloads/ eggs/ .eggs/ lib/ lib64/ parts/ sdist/ var/ wheels/ share/python-wheels/ *.egg-info/ .installed.cfg *.egg MANIFEST # 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/ .nox/ .coverage .coverage.* .cache nosetests.xml coverage.xml *.cover *.py,cover .hypothesis/ .pytest_cache/ cover/ # Translations *.mo *.pot # Django stuff: *.log local_settings.py db.sqlite3 db.sqlite3-journal # Flask stuff: instance/ .webassets-cache # Scrapy stuff: .scrapy # Sphinx documentation docs/_build/ # PyBuilder .pybuilder/ target/ # Jupyter Notebook .ipynb_checkpoints # IPython profile_default/ ipython_config.py # pyenv # For a library or package, you might want to ignore these files since the code is # intended to run in multiple environments; otherwise, check them in: # .python-version # pipenv # According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control. # However, in case of collaboration, if having platform-specific dependencies or dependencies # having no cross-platform support, pipenv may install dependencies that don't work, or not # install all needed dependencies. #Pipfile.lock # PEP 582; used by e.g. github.com/David-OConnor/pyflow __pypackages__/ # Celery stuff celerybeat-schedule celerybeat.pid # SageMath parsed files *.sage.py # Environments .env .venv env/ venv/ ENV/ env.bak/ venv.bak/ # Spyder project settings .spyderproject .spyproject # Rope project settings .ropeproject # mkdocs documentation /site # mypy .mypy_cache/ .dmypy.json dmypy.json # Pyre type checker .pyre/ # pytype static type analyzer .pytype/ # Cython debug symbols cython_debug/ kazhala-pfzy-1f5f112/.pre-commit-config.yaml000066400000000000000000000005651417465175600207510ustar00rootroot00000000000000repos: - repo: https://github.com/psf/black rev: 21.7b0 hooks: - id: black files: pfzy - repo: https://github.com/PyCQA/pydocstyle rev: 6.1.1 hooks: - id: pydocstyle files: pfzy additional_dependencies: [toml] - repo: https://github.com/pycqa/isort rev: 5.9.3 hooks: - id: isort files: pfzy kazhala-pfzy-1f5f112/.readthedocs.yaml000066400000000000000000000002361417465175600177120ustar00rootroot00000000000000version: 2 sphinx: configuration: docs/conf.py python: version: 3.7 install: - method: pip path: . extra_requirements: - docs kazhala-pfzy-1f5f112/LICENSE000066400000000000000000000020551417465175600154710ustar00rootroot00000000000000MIT License Copyright (c) 2021 Kevin Zhuang Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. kazhala-pfzy-1f5f112/README.md000066400000000000000000000067151417465175600157520ustar00rootroot00000000000000# pfzy [![CI](https://github.com/kazhala/pfzy/workflows/CI/badge.svg)](https://github.com/kazhala/pfzy/actions?query=workflow%3ACI) [![Docs](https://img.shields.io/readthedocs/pfzy?label=Docs&logo=Read%20the%20Docs)](https://readthedocs.org/projects/pfzy/) [![Build](https://codebuild.ap-southeast-2.amazonaws.com/badges?uuid=eyJlbmNyeXB0ZWREYXRhIjoiT2pwUFo2MVBzV1ptL0d4VDhmSHo4bSswVHFuaEh6bEU1d2g3bmpsdnZjSzcwWkxac3NHcjBKZDkyT2t1R0VveHJ0WlNFWmZmUjNQUGFpemxwV2loRm9rPSIsIml2UGFyYW1ldGVyU3BlYyI6Imw4dlcwYjlxaU9kYVd0UkoiLCJtYXRlcmlhbFNldFNlcmlhbCI6MX0%3D&branch=master)](https://ap-southeast-2.console.aws.amazon.com/codesuite/codebuild/378756445655/projects/pfzy/history?region=ap-southeast-2&builds-meta=eyJmIjp7InRleHQiOiIifSwicyI6e30sIm4iOjIwLCJpIjowfQ) [![Coverage](https://img.shields.io/coveralls/github/kazhala/pfzy?logo=coveralls)](https://coveralls.io/github/kazhala/pfzy?branch=master) [![Version](https://img.shields.io/pypi/pyversions/pfzy)](https://pypi.org/project/pfzy/) [![PyPi](https://img.shields.io/pypi/v/pfzy)](https://pypi.org/project/pfzy/) [![License](https://img.shields.io/pypi/l/pfzy)](https://github.com/kazhala/pfzy/blob/master/LICENSE) Python port of the [fzy](https://github.com/jhawthorn/fzy) fuzzy string matching algorithm. - [Async fuzzy match function](https://pfzy.readthedocs.io/en/latest/pages/usage.html#matcher) - [Fzy scorer (fuzzy string match)](https://pfzy.readthedocs.io/en/latest/pages/usage.html#fzy-scorer) - [Substring scorer (exact substring match)](https://pfzy.readthedocs.io/en/latest/pages/usage.html#substr-scorer) ## Requirements ``` python >= 3.7 ``` ## Installation ```sh pip install pfzy ``` ## Quick Start **Full documentation: [https://pfzy.readthedocs.io/](https://pfzy.readthedocs.io/)** ```python import asyncio from pfzy import fuzzy_match result = asyncio.run(fuzzy_match("ab", ["acb", "acbabc"])) ``` ``` >>> print(result) [{'value': 'acbabc', 'indices': [3, 4]}, {'value': 'acb', 'indices': [0, 2]}] ``` ## Background [fuzzywuzzy](https://github.com/seatgeek/fuzzywuzzy) is a famous python package for performing fuzzy matching between strings powered by [python-Levenshtein](https://github.com/miohtama/python-Levenshtein). While it does its job well it doesn't calculate/provide the matching indices which is essential in a fuzzy finder applications. The [fzy](https://github.com/jhawthorn/fzy) fuzzy matching algorithm can calculate the matching score while also providing the matching indices which fuzzy finder applications can use to provide extra highlights. The initial implementation of this algorithm can be found at [sweep.py](https://github.com/aslpavel/sweep.py) which is a python implementation of the terminal fuzzy finder. The code snippet is later used by the project [vim-clap](https://github.com/liuchengxu/vim-clap). **I found myself needing this logic across multiple projects hence decided to strip out the logic and publish a dedicated package with detailed documentation and unittest.** ## Credit - [fzy](https://github.com/jhawthorn/fzy) - [sweep.py](https://github.com/aslpavel/sweep.py) - [vim-clap](https://github.com/liuchengxu/vim-clap) ## LICENSE > All 3 projects mentioned in [Credit](#credit) are all licensed under [MIT](https://opensource.org/licenses/MIT). This project is licensed under [MIT](https://github.com/kazhala/pfzy). Copyright (c) 2021 Kevin Zhuang kazhala-pfzy-1f5f112/buildspec.yml000066400000000000000000000007551417465175600171660ustar00rootroot00000000000000version: 0.2 env: parameter-store: PYPI_USERNAME: /pypi/username PYPI_PASSWORD: /pypi/password phases: install: runtime-versions: python: latest commands: - curl -sSL https://raw.githubusercontent.com/python-poetry/poetry/master/get-poetry.py | python - - source $HOME/.poetry/env - poetry install build: commands: - poetry build post_build: commands: - poetry publish --username $PYPI_USERNAME --password $PYPI_PASSWORD kazhala-pfzy-1f5f112/docs/000077500000000000000000000000001417465175600154125ustar00rootroot00000000000000kazhala-pfzy-1f5f112/docs/Makefile000066400000000000000000000013101417465175600170450ustar00rootroot00000000000000# Minimal makefile for Sphinx documentation # # You can set these variables from the command line, and also # from the environment for the first two. SPHINXOPTS ?= SPHINXBUILD ?= sphinx-build SOURCEDIR = . BUILDDIR = _build # Put it first so that "make" without argument is like "make help". help: @$(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) $(O) live: sphinx-autobuild "$(SOURCEDIR)" "$(BUILDDIR)"/html $(SPHINXOPTS) $(O) kazhala-pfzy-1f5f112/docs/conf.py000066400000000000000000000013301417465175600167060ustar00rootroot00000000000000import os import sys sys.path.insert(0, os.path.abspath(".")) project = "pfzy" copyright = "2021, Kevin Zhuang" author = "Kevin Zhuang" version = "0.3.4" release = version extensions = [ "sphinx.ext.autodoc", "sphinx.ext.napoleon", "sphinx.ext.intersphinx", "sphinx.ext.viewcode", "sphinx.ext.autosectionlabel", "myst_parser", "sphinx_copybutton", ] templates_path = ["_templates"] exclude_patterns = ["_build", "Thumbs.db", ".DS_Store"] html_theme = "furo" html_title = "pfzy" napoleon_include_init_with_doc = True autosectionlabel_prefix_document = True autodoc_typehints = "description" autodoc_member_order = "bysource" intersphinx_mapping = {"python": ("https://docs.python.org/3", None)} kazhala-pfzy-1f5f112/docs/index.md000066400000000000000000000005651417465175600170510ustar00rootroot00000000000000# pfzy ```{include} ../README.md :start-after: :end-before: ``` ```{include} ../README.md :start-after: :end-before: ``` ```{toctree} :hidden: pages/usage.md pages/api.md GitHub Repository ``` kazhala-pfzy-1f5f112/docs/pages/000077500000000000000000000000001417465175600165115ustar00rootroot00000000000000kazhala-pfzy-1f5f112/docs/pages/api.md000066400000000000000000000003201417465175600175770ustar00rootroot00000000000000# API Reference ## match ```{eval-rst} .. automodule:: pfzy.match :members: fuzzy_match ``` ## score ```{eval-rst} .. automodule:: pfzy.score :members: fzy_scorer, substr_scorer ``` kazhala-pfzy-1f5f112/docs/pages/usage.md000066400000000000000000000061571417465175600201500ustar00rootroot00000000000000# Usage ## Matcher The [pfzy](https://github.com/jhawthorn/fzy) package provides an async entry point [fuzzy_match](https://pfzy.readthedocs.io/en/latest/pages/api.html#pfzy.match.fuzzy_match) to perform fuzzy matching using a given string against a given list of strings and will perform ranking automatically. ```{code-block} python --- caption: main.py --- import asyncio from pfzy import fuzzy_match async def main(): return await fuzzy_match("ab", ["acb", "acbabc"]) if __name__ == "__main__": print(asyncio.run(main())) ``` ```{code-block} python >>> python main.py [{"value": "acbabc", "indices": [3, 4]}, {"value": "acb", "indices": [0, 2]}] ``` ### Matching against dictionaries The second argument can also be a list of dictionary but you'll have to also specify the argument `key` so that the function knows which key in the dictionary contains the value to match. ```{code-block} python import asyncio from pfzy import fuzzy_match result = asyncio.run(fuzzy_match("ab", [{"val": "acb"}, {"val": "acbabc"}], key="val")) ``` ```{code-block} python >>> print(result) [{"val": "acbabc", "indices": [3, 4]}, {"val": "acb", "indices": [0, 2]}] ``` ### Using different scorer By default, it uses the [fzy_scorer](#fzy_scorer) to perform string matching if not specified. You can explicitly set a different scorer using the argument `scorer`. Reference [#Scorer](#scorer) for a list of available scorers. ```{code-block} python import asyncio from pfzy import fuzzy_match, substr_scorer result = asyncio.run(fuzzy_match("ab", ["acb", "acbabc"], scorer=substr_scorer)) ``` ```{code-block} python >>> print(result) [{'value': 'acbabc', 'indices': [3, 4]}] ``` ## Scorer ### [fzy_scorer](https://pfzy.readthedocs.io/en/latest/pages/api.html#pfzy.score.fzy_scorer) ```{Tip} The higher the score, the higher the string similarity. ``` The `fzy_scorer` uses [fzy](https://github.com/jhawthorn/fzy) matching logic to perform string fuzzy matching. The returned value is a tuple with the matching score and the matching indices. ```{code-block} python from pfzy import fzy_scorer score, indices = fzy_scorer("ab", "acbabc") ``` ```{code-block} python >>> print(score) 0.98 >>> print(indices) [3, 4] ``` ### [substr_scorer](https://pfzy.readthedocs.io/en/latest/pages/api.html#pfzy.score.substr_scorer) ```{Note} The score returned by `substr_scorer` might be negative value, but it doesn't mean its not a match. As a rule of thumb, the higher the score, the higher the string similarity. ``` Use this scorer when exact substring matching is preferred. Different than the [fzy_scorer](#fzy_scorer), `substr_scorer` only performs exact matching and the score calculation works differently. The returned value is a tuple with the matching score and the matching indices. ```{code-block} python from pfzy import substr_scorer score, indices = substr_scorer("ab", "awsab") ``` ```{code-block} python >>> print(score) -1.3 >>> print(indices) [3, 4] ``` ```{code-block} python from pfzy import substr_scorer score, indices = substr_scorer("ab", "asdafswabc") ``` ```{code-block} python >>> print(score) -1.6388888888888888 >>> print(indices) [7, 8] ``` kazhala-pfzy-1f5f112/docs/requirements.txt000066400000000000000000000000731417465175600206760ustar00rootroot00000000000000Sphinx furo myst-parser sphinx-autobuild sphinx-copybutton kazhala-pfzy-1f5f112/pfzy/000077500000000000000000000000001417465175600154525ustar00rootroot00000000000000kazhala-pfzy-1f5f112/pfzy/__init__.py000066400000000000000000000001241417465175600175600ustar00rootroot00000000000000from pfzy.match import fuzzy_match from pfzy.score import fzy_scorer, substr_scorer kazhala-pfzy-1f5f112/pfzy/match.py000066400000000000000000000075271417465175600171330ustar00rootroot00000000000000"""Module contains the async interface to match needle against haystack in batch.""" import asyncio import heapq from typing import Any, Callable, Dict, List, Union, cast from pfzy.score import SCORE_INDICES, fzy_scorer from pfzy.types import HAYSTACKS async def _rank_task( scorer: Callable[[str, str], SCORE_INDICES], needle: str, haystacks: List[Union[str, Dict[str, Any]]], key: str, ) -> List[Dict[str, Any]]: """Calculate the score for needle against given list of haystacks and rank them. Args: scorer: Scorer to be used to do the calculation. needle: Substring to search. haystacks: List of dictionary containing the haystack to be searched. key: The key within the `haystacks` dictionary that contains the actual string value. Return: Sorted list of haystacks based on the needle score with additional keys for the `score` and `indices`. """ result = [] for haystack in haystacks: score, indices = scorer(needle, cast(Dict, haystack)[key]) if indices is None: continue result.append( { "score": score, "indices": indices, "haystack": haystack, } ) result.sort(key=lambda x: x["score"], reverse=True) return result async def fuzzy_match( needle: str, haystacks: HAYSTACKS, key: str = "", batch_size: int = 4096, scorer: Callable[[str, str], SCORE_INDICES] = None, ) -> List[Dict[str, Any]]: """Fuzzy find the needle within list of haystacks and get matched results with matching index. Note: The `key` argument is optional when the provided `haystacks` argument is a list of :class:`str`. It will be given a default key `value` if not present. Warning: The `key` argument is required when provided `haystacks` argument is a list of :class:`dict`. If not present, :class:`TypeError` will be raised. Args: needle: String to search within the `haystacks`. haystacks: List of haystack/longer strings to be searched. key: If `haystacks` is a list of dictionary, provide the key that can obtain the haystack value to search. batch_size: Number of entry to be processed together. scorer (Callable[[str, str], SCORE_indices]): Desired scorer to use. Currently only :func:`~pfzy.score.fzy_scorer` and :func:`~pfzy.score.substr_scorer` is supported. Raises: TypeError: When the argument `haystacks` is :class:`list` of :class:`dict` and the `key` argument is missing, :class:`TypeError` will be raised. Returns: List of matching `haystacks` with additional key indices and score. Examples: >>> import asyncio >>> asyncio.run(fuzzy_match("ab", ["acb", "acbabc"])) [{'value': 'acbabc', 'indices': [3, 4]}, {'value': 'acb', 'indices': [0, 2]}] """ if scorer is None: scorer = fzy_scorer for index, haystack in enumerate(haystacks): if not isinstance(haystack, dict): if not key: key = "value" haystacks[index] = {key: haystack} if not key: raise TypeError( f"${fuzzy_match.__name__} missing 1 required argument: 'key', 'key' is required when haystacks is an instance of dict" ) batches = await asyncio.gather( *( _rank_task( scorer, needle, haystacks[offset : offset + batch_size], key, ) for offset in range(0, len(haystacks), batch_size) ) ) results = heapq.merge(*batches, key=lambda x: x["score"], reverse=True) choices = [] for candidate in results: candidate["haystack"]["indices"] = candidate["indices"] choices.append(candidate["haystack"]) return choices kazhala-pfzy-1f5f112/pfzy/score.py000066400000000000000000000231621417465175600171430ustar00rootroot00000000000000"""Module contains the score calculation algorithems.""" from functools import partial from typing import Dict, List, Union, cast from pfzy.types import SCORE_INDICES SCORE_MIN = float("-inf") SCORE_MAX = float("inf") SCORE_GAP_LEADING = -0.005 SCORE_GAP_TRAILING = -0.005 SCORE_GAP_INNER = -0.01 SCORE_MATCH_CONSECUTIVE = 1.0 def _char_range_with( char_start: str, char_stop: str, value, hash_table: Dict[str, Union[int, float]] ) -> Dict[str, Union[int, float]]: """Generate index mapping for `bonus` calculation. Args: char_start: Starting char of the range. char_stop: Ending char of the range. value: Value to give to the range of char. hash_table: Base dictionary to add the mapping. Returns: A dictionary containing the given range with provided index. Examples: >>> _char_range_with("a", "d", 1, {}) {'a': 1, 'b': 1, 'c': 1, 'd': 1} """ hash_table = hash_table.copy() hash_table.update( (chr(uni_char), value) for uni_char in range(ord(char_start), ord(char_stop) + 1) ) return hash_table lower_with = partial(_char_range_with, "a", "z") upper_with = partial(_char_range_with, "A", "Z") digit_with = partial(_char_range_with, "0", "9") SCORE_MATCH_SLASH = 0.9 SCORE_MATCH_WORD = 0.8 SCORE_MATCH_CAPITAL = 0.7 SCORE_MATCH_DOT = 0.6 BONUS_MAP = { "/": SCORE_MATCH_SLASH, "-": SCORE_MATCH_WORD, "_": SCORE_MATCH_WORD, " ": SCORE_MATCH_WORD, ".": SCORE_MATCH_DOT, } BONUS_STATES = [{}, BONUS_MAP, lower_with(SCORE_MATCH_CAPITAL, BONUS_MAP)] BONUS_INDEX = cast(Dict[str, int], digit_with(1, lower_with(1, upper_with(2, {})))) def _bonus(haystack: str) -> List[float]: """Calculate bonus score for the given haystack. The bonus are applied to each char based on the previous char. When previous char is within the `BONUS_MAP` then additional bonus are applied to the current char due to it might be the start of a new word. When encountered a mix case character, if the current char is capitalised then if the previous char is normal case or within `BONUS_MAP`, additional bounus are applied. Args: haystack: String to calculate bonus. Returns: A list of float matching the length of the given haystack with each index representing the bonus score to apply. Examples: >>> _bonus("asdf") [0.9, 0, 0, 0] >>> _bonus("asdf asdf") [0.9, 0, 0, 0, 0, 0.8, 0, 0, 0] >>> _bonus("asdf aSdf") [0.9, 0, 0, 0, 0, 0.8, 0.7, 0, 0] >>> _bonus("asdf/aSdf") [0.9, 0, 0, 0, 0, 0.9, 0.7, 0, 0] """ prev_char = "/" bonus = [] for char in haystack: bonus.append(BONUS_STATES[BONUS_INDEX.get(char, 0)].get(prev_char, 0)) prev_char = char return bonus def _score(needle: str, haystack: str) -> SCORE_INDICES: """Use fzy logic to calculate score for `needle` within the given `haystack`. 2 2D array to track the score. 1. The running score (`running_score`) which represents the best score for the current position. 2. The result score (`result_score`) which tracks to overall best score that could be for the current positon. With every consequtive match, additional bonuse score are given and for every non matching char, a negative gap score is applied. After the score is calculated, the final matching score will be stored at the last position of the `result_score`. Backtrack the result by comparing the 2 2D array to find the corresponding indices. Args: needle: Substring to find in haystack. haystack: String to be searched and scored. Returns: A tuple of matching score with a list of matching indices. """ needle_len, haystack_len = len(needle), len(haystack) bonus_score = _bonus(haystack) # smart case if needle.islower(): haystack = haystack.lower() # return all values if no query if needle_len == 0 or needle_len == haystack_len: return SCORE_MAX, list(range(needle_len)) # best score for the position running_score: List[List[float]] = [ [0 for _ in range(haystack_len)] for _ in range(needle_len) ] # overall best score at each position result_score: List[List[float]] = [ [0 for _ in range(haystack_len)] for _ in range(needle_len) ] for i in range(needle_len): prev_score = SCORE_MIN # gap between matching char # more gaps, less score gap_score = SCORE_GAP_TRAILING if i == needle_len - 1 else SCORE_GAP_INNER for j in range(haystack_len): if needle[i] == haystack[j]: score = SCORE_MIN if i == 0: score = j * SCORE_GAP_LEADING + bonus_score[j] elif j != 0: score = max( result_score[i - 1][j - 1] + bonus_score[j], # consecutive match if value is higher running_score[i - 1][j - 1] + SCORE_MATCH_CONSECUTIVE, ) running_score[i][j] = score result_score[i][j] = prev_score = max(score, prev_score + gap_score) else: running_score[i][j] = SCORE_MIN # increment the best score with gap_score since no match result_score[i][j] = prev_score = prev_score + gap_score # backtrace to find the all indices of optimal matching # starting from the end to pick the first possible match we encounter i, j = needle_len - 1, haystack_len - 1 # use to determine if the current match is consequtive match match_required = False indices = [0 for _ in range(needle_len)] while i >= 0: while j >= 0: # if the prev score is determined to be consecutive match # then the current position must be a match # e.g. haystack, needle = "auibywcabc", "abc" # using match_required: [7, 8, 9] # without match_required: [0, 8, 9] if ( match_required or running_score[i][j] == result_score[i][j] ) and running_score[i][j] != SCORE_MIN: match_required = ( i > 0 and j > 0 and result_score[i][j] == running_score[i - 1][j - 1] + SCORE_MATCH_CONSECUTIVE ) indices[i] = j j -= 1 break else: j -= 1 i -= 1 return result_score[needle_len - 1][haystack_len - 1], indices def _subsequence(needle: str, haystack: str) -> bool: """Check if needle is subsequence of haystack. Args: needle: Substring to find in haystack. haystack: String to be searched and scored. Returns: Boolean indicating if `needle` is subsequence of `haystack`. Examples: >>> _subsequence("as", "bbwi") False >>> _subsequence("as", "bbaiws") True >>> _subsequence("sa", "bbaiws") False """ needle, haystack = needle.lower(), haystack.lower() if not needle: return True offset = 0 for char in needle: offset = haystack.find(char, offset) + 1 if offset <= 0: return False return True def fzy_scorer(needle: str, haystack: str) -> SCORE_INDICES: """Use fzy matching algorithem to match needle against haystack. Note: The `fzf` unordered search is not supported for performance concern. When the provided `needle` is not a subsequence of `haystack` at all, then `(-inf, None)` is returned. See Also: https://github.com/jhawthorn/fzy/blob/master/src/match.c Args: needle: Substring to find in haystack. haystack: String to be searched and scored against. Returns: A tuple of matching score with a list of matching indices. Examples: >>> fzy_scorer("ab", "acb") (0.89, [0, 2]) >>> fzy_scorer("ab", "acbabc") (0.98, [3, 4]) >>> fzy_scorer("ab", "wc") (-inf, None) """ if _subsequence(needle, haystack): return _score(needle, haystack) else: return SCORE_MIN, None def substr_scorer(needle: str, haystack: str) -> SCORE_INDICES: """Match needle against haystack using :meth:`str.find`. Note: Scores may be negative but the higher the score, the higher the match rank. `-inf` score means no match found. See Also: https://github.com/aslpavel/sweep.py/blob/3f4a179b708059c12b9e5d76d1eb3c70bf2caadc/sweep.py#L837 Args: needle: Substring to find in haystack. haystack: String to be searched and scored against. Returns: A tuple of matching score with a list of matching indices. Example: >>> substr_scorer("ab", "awsab") (-1.3, [3, 4]) >>> substr_scorer("ab", "abc") (0.5, [0, 1]) >>> substr_scorer("ab", "iop") (-inf, None) >>> substr_scorer("ab", "asdafswabc") (-1.6388888888888888, [7, 8]) >>> substr_scorer(" ", "asdf") (0, []) """ indices = [] offset = 0 needle, haystack = needle.lower(), haystack.lower() for needle in needle.split(" "): if not needle: continue offset = haystack.find(needle, offset) if offset < 0: return SCORE_MIN, None needle_len = len(needle) indices.extend(range(offset, offset + needle_len)) offset += needle_len if not indices: return 0, indices return ( -(indices[-1] + 1 - indices[0]) + 2 / (indices[0] + 1) + 1 / (indices[-1] + 1), indices, ) kazhala-pfzy-1f5f112/pfzy/types.py000066400000000000000000000003011417465175600171620ustar00rootroot00000000000000"""Module contains typing aliases.""" from typing import Any, Dict, List, Optional, Tuple, Union SCORE_INDICES = Tuple[float, Optional[List[int]]] HAYSTACKS = List[Union[str, Dict[str, Any]]] kazhala-pfzy-1f5f112/poetry.lock000066400000000000000000002152141417465175600166630ustar00rootroot00000000000000[[package]] name = "alabaster" version = "0.7.12" description = "A configurable sidebar-enabled Sphinx theme" category = "main" optional = true python-versions = "*" [[package]] name = "appdirs" version = "1.4.4" description = "A small Python module for determining appropriate platform-specific dirs, e.g. a \"user data dir\"." category = "dev" optional = false python-versions = "*" [[package]] name = "atomicwrites" version = "1.4.0" description = "Atomic file writes." category = "dev" optional = false python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*" [[package]] name = "attrs" version = "21.2.0" description = "Classes Without Boilerplate" category = "main" optional = false python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*" [package.extras] dev = ["coverage[toml] (>=5.0.2)", "hypothesis", "pympler", "pytest (>=4.3.0)", "six", "mypy", "pytest-mypy-plugins", "zope.interface", "furo", "sphinx", "sphinx-notfound-page", "pre-commit"] docs = ["furo", "sphinx", "zope.interface", "sphinx-notfound-page"] tests = ["coverage[toml] (>=5.0.2)", "hypothesis", "pympler", "pytest (>=4.3.0)", "six", "mypy", "pytest-mypy-plugins", "zope.interface"] tests_no_zope = ["coverage[toml] (>=5.0.2)", "hypothesis", "pympler", "pytest (>=4.3.0)", "six", "mypy", "pytest-mypy-plugins"] [[package]] name = "babel" version = "2.9.1" description = "Internationalization utilities" category = "main" optional = true python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*" [package.dependencies] pytz = ">=2015.7" [[package]] name = "backports.entry-points-selectable" version = "1.1.0" description = "Compatibility shim providing selectable entry points for older implementations" category = "dev" optional = false python-versions = ">=2.7" [package.dependencies] importlib-metadata = {version = "*", markers = "python_version < \"3.8\""} [package.extras] docs = ["sphinx", "jaraco.packaging (>=8.2)", "rst.linker (>=1.9)"] testing = ["pytest (>=4.6)", "pytest-flake8", "pytest-cov", "pytest-black (>=0.3.7)", "pytest-mypy", "pytest-checkdocs (>=2.4)", "pytest-enabler (>=1.0.1)"] [[package]] name = "beautifulsoup4" version = "4.9.3" description = "Screen-scraping library" category = "main" optional = true python-versions = "*" [package.dependencies] soupsieve = {version = ">1.2", markers = "python_version >= \"3.0\""} [package.extras] html5lib = ["html5lib"] lxml = ["lxml"] [[package]] name = "black" version = "21.7b0" description = "The uncompromising code formatter." category = "dev" optional = false python-versions = ">=3.6.2" [package.dependencies] appdirs = "*" click = ">=7.1.2" mypy-extensions = ">=0.4.3" pathspec = ">=0.8.1,<1" regex = ">=2020.1.8" tomli = ">=0.2.6,<2.0.0" typed-ast = {version = ">=1.4.2", markers = "python_version < \"3.8\""} typing-extensions = {version = ">=3.7.4", markers = "python_version < \"3.8\""} [package.extras] colorama = ["colorama (>=0.4.3)"] d = ["aiohttp (>=3.6.0)", "aiohttp-cors (>=0.4.0)"] python2 = ["typed-ast (>=1.4.2)"] uvloop = ["uvloop (>=0.15.2)"] [[package]] name = "certifi" version = "2021.5.30" description = "Python package for providing Mozilla's CA Bundle." category = "main" optional = false python-versions = "*" [[package]] name = "cfgv" version = "3.3.0" description = "Validate configuration and produce human readable error messages." category = "dev" optional = false python-versions = ">=3.6.1" [[package]] name = "charset-normalizer" version = "2.0.4" description = "The Real First Universal Charset Detector. 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kazhala-pfzy-1f5f112/pyproject.toml000066400000000000000000000032611417465175600174000ustar00rootroot00000000000000[tool.poetry] name = "pfzy" version = "0.3.4" description = "Python port of the fzy fuzzy string matching algorithm" authors = ["Kevin Zhuang "] readme = "README.md" repository = "https://github.com/kazhala/pfzy" documentation = "https://pfzy.readthedocs.io/" license = "MIT" keywords=["fuzzy", "string", "fzy", "search","development"] classifiers = [ "Development Status :: 4 - Beta", "Intended Audience :: Developers", "License :: OSI Approved :: MIT License", "Operating System :: Unix", "Operating System :: Microsoft", "Programming Language :: Python :: 3", "Programming Language :: Python :: 3.7", "Programming Language :: Python :: 3.8", "Programming Language :: Python :: 3.9", "Topic :: Software Development", "Topic :: Software Development :: Libraries", ] packages = [ {include = "pfzy"} ] [tool.poetry.dependencies] python = "^3.7" Sphinx = {version = "^4.1.2", optional = true} furo = {version = "^2021.8.17-beta.43", optional = true} myst-parser = {version = "^0.15.1", optional = true} sphinx-autobuild = {version = "^2021.3.14", optional = true} sphinx-copybutton = {version = "^0.4.0", optional = true} [tool.poetry.dev-dependencies] pre-commit = "^2.14.0" pydocstyle = "^6.1.1" isort = "^5.9.3" black = "^21.7b0" pytest = "^6.2.4" pytest-cov = "^2.12.1" pytest-asyncio = "^0.15.1" coveralls = "^3.2.0" [tool.poetry.extras] docs = ["Sphinx", "furo", "myst-parser", "sphinx-autobuild", "sphinx-copybutton"] [tool.isort] profile = "black" [tool.pydocstyle] convention = "pep257" add_ignore = "D104" [tool.pytest.ini_options] addopts = "--doctest-modules" [build-system] requires = ["poetry-core>=1.0.0"] build-backend = "poetry.core.masonry.api" kazhala-pfzy-1f5f112/tests/000077500000000000000000000000001417465175600156245ustar00rootroot00000000000000kazhala-pfzy-1f5f112/tests/__init__.py000066400000000000000000000000001417465175600177230ustar00rootroot00000000000000kazhala-pfzy-1f5f112/tests/test_match.py000066400000000000000000000035401417465175600203330ustar00rootroot00000000000000import pytest from pfzy.match import _rank_task, fuzzy_match from pfzy.score import fzy_scorer, substr_scorer @pytest.mark.asyncio async def test_rank_task() -> None: assert await _rank_task(substr_scorer, "abc", [{"val": "wzawbc"}], "val") == [] assert await _rank_task( substr_scorer, "abc", [{"val": "wabco"}, {"val": "abcabc"}], "val" ) == [ { "haystack": {"val": "abcabc"}, "indices": [0, 1, 2], "score": -0.6666666666666667, }, {"haystack": {"val": "wabco"}, "indices": [1, 2, 3], "score": -1.75}, ] assert await _rank_task( fzy_scorer, "abc", [{"val": "acbabc"}, {"val": "abcABC"}, {"val": "bwd abc"}], "val", ) == [ { "haystack": {"val": "abcABC"}, "indices": [0, 1, 2], "score": 2.8850000000000002, }, { "haystack": {"val": "bwd abc"}, "indices": [4, 5, 6], "score": 2.7800000000000002, }, { "haystack": {"val": "acbabc"}, "indices": [3, 4, 5], "score": 1.9849999999999999, }, ] assert await _rank_task( fzy_scorer, "ab", [{"val": "acb"}, {"val": "acbabc"}], "val" ) == [ {"score": 0.98, "indices": [3, 4], "haystack": {"val": "acbabc"}}, {"score": 0.89, "indices": [0, 2], "haystack": {"val": "acb"}}, ] @pytest.mark.asyncio async def test_fuzzy_match() -> None: await fuzzy_match("a", ["abca"]) == [{"value": "abca", "indices": [0]}] await fuzzy_match( "a", [{"val": "abca"}, {"val": "aAbc"}], key="val", scorer=substr_scorer, batch_size=1, ) == [{"val": "abca", "indices": [0]}, {"val": "aAbc", "indices": [0]}] with pytest.raises(TypeError): await fuzzy_match("a", [{"val": "abc"}]) kazhala-pfzy-1f5f112/tests/test_score.py000066400000000000000000000025601417465175600203530ustar00rootroot00000000000000import pytest from pfzy.score import SCORE_MAX, _bonus, _char_range_with, _score, _subsequence def test_char_range_with(): result = _char_range_with("0", "9", 10, {"a": 1}) assert result == { "0": 10, "1": 10, "2": 10, "3": 10, "4": 10, "5": 10, "6": 10, "7": 10, "8": 10, "9": 10, "a": 1, } result = _char_range_with("A", "D", 2, {}) assert result == {"A": 2, "B": 2, "C": 2, "D": 2} def test_bonus(): assert _bonus("abc") == [0.9, 0, 0] assert _bonus("abc abc") == [0.9, 0, 0, 0, 0.8, 0, 0] assert _bonus("abc/abc") == [0.9, 0, 0, 0, 0.9, 0, 0] assert _bonus("abc/abC") == [0.9, 0, 0, 0, 0.9, 0, 0.7] assert _bonus("/abc") == [0, 0.9, 0, 0] def test_score(): assert _score("", "abc") == (SCORE_MAX, []) assert _score("abc", "abc") == (SCORE_MAX, [0, 1, 2]) assert _score("abc", "acbabc") == (1.9849999999999999, [3, 4, 5]) assert _score("abc", "acbABC") == (2.685, [3, 4, 5]) assert _score("ABC", "acbABC") == (2.685, [3, 4, 5]) assert _score("b ABC", "acb bABC") == (3.6799999999999997, [2, 3, 5, 6, 7]) def test_subsequence(): assert _subsequence("awc", "abc") == False assert _subsequence("awc", "abcwc") == True assert _subsequence("a ui", "waui wou i") == True assert _subsequence("", "waui wou i") == True