pax_global_header00006660000000000000000000000064145671711240014522gustar00rootroot0000000000000052 comment=1fcadea96ce67d499965b085f0b0b2253b78bb80 cachetools-5.3.3/000077500000000000000000000000001456717112400136565ustar00rootroot00000000000000cachetools-5.3.3/.github/000077500000000000000000000000001456717112400152165ustar00rootroot00000000000000cachetools-5.3.3/.github/ISSUE_TEMPLATE/000077500000000000000000000000001456717112400174015ustar00rootroot00000000000000cachetools-5.3.3/.github/ISSUE_TEMPLATE/bug_report.md000066400000000000000000000010271456717112400220730ustar00rootroot00000000000000--- name: Bug report about: Create a report to help us improve title: '' labels: bug assignees: tkem --- Before reporting a bug, please make sure you have the latest `cachetools` version installed: ``` pip install --upgrade cachetools ``` **Describe the bug** A clear and concise description of what the bug is. **Expected result** A clear and concise description of what you expected to happen. **Actual result** A clear and concise description of what happened instead. **Reproduction steps** ```python import cachetools ``` cachetools-5.3.3/.github/ISSUE_TEMPLATE/config.yml000066400000000000000000000000341456717112400213660ustar00rootroot00000000000000blank_issues_enabled: false cachetools-5.3.3/.github/ISSUE_TEMPLATE/feature_request.md000066400000000000000000000002761456717112400231330ustar00rootroot00000000000000--- name: Feature request about: Suggest an idea for this project title: '' labels: enhancement assignees: tkem --- Sorry, but `cachetools` is not accepting feature requests at this time. cachetools-5.3.3/.github/SECURITY.md000066400000000000000000000014071456717112400170110ustar00rootroot00000000000000# Security Policy ## Supported Versions Security updates are applied only to the latest release. ## Reporting a Vulnerability If you have discovered a security vulnerability in this project, please report it privately. **Do not disclose it as a public issue.** This gives us time to work with you to fix the issue before public exposure, reducing the chance that the exploit will be used before a patch is released. Please disclose it at [security advisory](https://github.com/tkem/cachetools/security/advisories/new). This project is maintained by a single person on a best effort basis. As such, vulnerability reports will be investigated and fixed or disclosed as soon as possible, but there may be delays in response time due to the maintainer's other commitments. cachetools-5.3.3/.github/dependabot.yml000066400000000000000000000001671456717112400200520ustar00rootroot00000000000000version: 2 updates: - package-ecosystem: "github-actions" directory: "/" schedule: interval: "monthly" cachetools-5.3.3/.github/workflows/000077500000000000000000000000001456717112400172535ustar00rootroot00000000000000cachetools-5.3.3/.github/workflows/ci.yml000066400000000000000000000014211456717112400203670ustar00rootroot00000000000000name: CI on: [push, pull_request, workflow_dispatch] permissions: contents: read jobs: main: name: Python ${{ matrix.python }} runs-on: ubuntu-20.04 strategy: fail-fast: false matrix: python: ["3.7", "3.8", "3.9", "3.10", "3.11", "3.12", "pypy3.9", "pypy3.10"] steps: - uses: actions/checkout@b4ffde65f46336ab88eb53be808477a3936bae11 # v4.1.1 - uses: actions/setup-python@0a5c61591373683505ea898e09a3ea4f39ef2b9c # v5.0.0 with: python-version: ${{ matrix.python }} allow-prereleases: true - run: python -m pip install coverage tox - run: python -m tox - uses: codecov/codecov-action@eaaf4bedf32dbdc6b720b63067d99c4d77d6047d # v3.1.4 with: name: ${{ matrix.python }} cachetools-5.3.3/.gitignore000066400000000000000000000001411456717112400156420ustar00rootroot00000000000000*.egg-info *.pyc *.swp .cache/ .coverage .tox/ MANIFEST build/ dist/ docs/_build/ .pytest_cache/ cachetools-5.3.3/.readthedocs.yaml000066400000000000000000000002071456717112400171040ustar00rootroot00000000000000# Configure ReadTheDocs. version: 2 build: os: "ubuntu-22.04" tools: python: "3.11" sphinx: configuration: "docs/conf.py" cachetools-5.3.3/CHANGELOG.rst000066400000000000000000000220531456717112400157010ustar00rootroot00000000000000v5.3.3 (2024-02-26) =================== - Documentation improvements. - Update CI environment. v5.3.2 (2023-10-24) =================== - Add support for Python 3.12. - Various documentation improvements. v5.3.1 (2023-05-27) =================== - Depend on Python >= 3.7. v5.3.0 (2023-01-22) =================== - Add ``cache_info()`` function to ``@cached`` decorator. v5.2.1 (2023-01-08) =================== - Add support for Python 3.11. - Correct version information in RTD documentation. - ``badges/shields``: Change to GitHub workflow badge routes. v5.2.0 (2022-05-29) =================== - Add ``cachetools.keys.methodkey()``. - Add ``cache_clear()`` function to decorators. - Add ``src`` directory to ``sys.path`` for Sphinx autodoc. - Modernize ``func`` wrappers. v5.1.0 (2022-05-15) =================== - Add cache decorator parameters as wrapper function attributes. v5.0.0 (2021-12-21) =================== - Require Python 3.7 or later (breaking change). - Remove deprecated submodules (breaking change). The ``cache``, ``fifo``, ``lfu``, ``lru``, ``mru``, ``rr`` and ``ttl`` submodules have been deleted. Therefore, statements like ``from cachetools.ttl import TTLCache`` will no longer work. Use ``from cachetools import TTLCache`` instead. - Pass ``self`` to ``@cachedmethod`` key function (breaking change). The ``key`` function passed to the ``@cachedmethod`` decorator is now called as ``key(self, *args, **kwargs)``. The default key function has been changed to ignore its first argument, so this should only affect applications using custom key functions with the ``@cachedmethod`` decorator. - Change exact time of expiration in ``TTLCache`` (breaking change). ``TTLCache`` items now get expired if their expiration time is less than *or equal to* ``timer()``. For applications using the default ``timer()``, this should be barely noticeable, but it may affect the use of custom timers with larger tick intervals. Note that this also implies that a ``TTLCache`` with ``ttl=0`` can no longer hold any items, since they will expire immediately. - Change ``Cache.__repr__()`` format (breaking change). String representations of cache instances now use a more compact and efficient format, e.g. ``LRUCache({1: 1, 2: 2}, maxsize=10, currsize=2)`` - Add TLRU cache implementation. - Documentation improvements. v4.2.4 (2021-09-30) =================== - Add submodule shims for backward compatibility. v4.2.3 (2021-09-29) =================== - Add documentation and tests for using ``TTLCache`` with ``datetime``. - Link to typeshed typing stubs. - Flatten package file hierarchy. v4.2.2 (2021-04-27) =================== - Update build environment. - Remove Python 2 remnants. - Format code with Black. v4.2.1 (2021-01-24) =================== - Handle ``__missing__()`` not storing cache items. - Clean up ``__missing__()`` example. v4.2.0 (2020-12-10) =================== - Add FIFO cache implementation. - Add MRU cache implementation. - Improve behavior of decorators in case of race conditions. - Improve documentation regarding mutability of caches values and use of key functions with decorators. - Officially support Python 3.9. v4.1.1 (2020-06-28) =================== - Improve ``popitem()`` exception context handling. - Replace ``float('inf')`` with ``math.inf``. - Improve "envkey" documentation example. v4.1.0 (2020-04-08) =================== - Support ``user_function`` with ``cachetools.func`` decorators (Python 3.8 compatibility). - Support ``cache_parameters()`` with ``cachetools.func`` decorators (Python 3.9 compatibility). v4.0.0 (2019-12-15) =================== - Require Python 3.5 or later. v3.1.1 (2019-05-23) =================== - Document how to use shared caches with ``@cachedmethod``. - Fix pickling/unpickling of cache keys v3.1.0 (2019-01-29) =================== - Fix Python 3.8 compatibility issue. - Use ``time.monotonic`` as default timer if available. - Improve documentation regarding thread safety. v3.0.0 (2018-11-04) =================== - Officially support Python 3.7. - Drop Python 3.3 support (breaking change). - Remove ``missing`` cache constructor parameter (breaking change). - Remove ``self`` from ``@cachedmethod`` key arguments (breaking change). - Add support for ``maxsize=None`` in ``cachetools.func`` decorators. v2.1.0 (2018-05-12) =================== - Deprecate ``missing`` cache constructor parameter. - Handle overridden ``getsizeof()`` method in subclasses. - Fix Python 2.7 ``RRCache`` pickling issues. - Various documentation improvements. v2.0.1 (2017-08-11) =================== - Officially support Python 3.6. - Move documentation to RTD. - Documentation: Update import paths for key functions (courtesy of slavkoja). v2.0.0 (2016-10-03) =================== - Drop Python 3.2 support (breaking change). - Drop support for deprecated features (breaking change). - Move key functions to separate package (breaking change). - Accept non-integer ``maxsize`` in ``Cache.__repr__()``. v1.1.6 (2016-04-01) =================== - Reimplement ``LRUCache`` and ``TTLCache`` using ``collections.OrderedDict``. Note that this will break pickle compatibility with previous versions. - Fix ``TTLCache`` not calling ``__missing__()`` of derived classes. - Handle ``ValueError`` in ``Cache.__missing__()`` for consistency with caching decorators. - Improve how ``TTLCache`` handles expired items. - Use ``Counter.most_common()`` for ``LFUCache.popitem()``. v1.1.5 (2015-10-25) =================== - Refactor ``Cache`` base class. Note that this will break pickle compatibility with previous versions. - Clean up ``LRUCache`` and ``TTLCache`` implementations. v1.1.4 (2015-10-24) =================== - Refactor ``LRUCache`` and ``TTLCache`` implementations. Note that this will break pickle compatibility with previous versions. - Document pending removal of deprecated features. - Minor documentation improvements. v1.1.3 (2015-09-15) =================== - Fix pickle tests. v1.1.2 (2015-09-15) =================== - Fix pickling of large ``LRUCache`` and ``TTLCache`` instances. v1.1.1 (2015-09-07) =================== - Improve key functions. - Improve documentation. - Improve unit test coverage. v1.1.0 (2015-08-28) =================== - Add ``@cached`` function decorator. - Add ``hashkey`` and ``typedkey`` functions. - Add `key` and `lock` arguments to ``@cachedmethod``. - Set ``__wrapped__`` attributes for Python versions < 3.2. - Move ``functools`` compatible decorators to ``cachetools.func``. - Deprecate ``@cachedmethod`` `typed` argument. - Deprecate `cache` attribute for ``@cachedmethod`` wrappers. - Deprecate `getsizeof` and `lock` arguments for `cachetools.func` decorator. v1.0.3 (2015-06-26) =================== - Clear cache statistics when calling ``clear_cache()``. v1.0.2 (2015-06-18) =================== - Allow simple cache instances to be pickled. - Refactor ``Cache.getsizeof`` and ``Cache.missing`` default implementation. v1.0.1 (2015-06-06) =================== - Code cleanup for improved PEP 8 conformance. - Add documentation and unit tests for using ``@cachedmethod`` with generic mutable mappings. - Improve documentation. v1.0.0 (2014-12-19) =================== - Provide ``RRCache.choice`` property. - Improve documentation. v0.8.2 (2014-12-15) =================== - Use a ``NestedTimer`` for ``TTLCache``. v0.8.1 (2014-12-07) =================== - Deprecate ``Cache.getsize()``. v0.8.0 (2014-12-03) =================== - Ignore ``ValueError`` raised on cache insertion in decorators. - Add ``Cache.getsize()``. - Add ``Cache.__missing__()``. - Feature freeze for `v1.0`. v0.7.1 (2014-11-22) =================== - Fix `MANIFEST.in`. v0.7.0 (2014-11-12) =================== - Deprecate ``TTLCache.ExpiredError``. - Add `choice` argument to ``RRCache`` constructor. - Refactor ``LFUCache``, ``LRUCache`` and ``TTLCache``. - Use custom ``NullContext`` implementation for unsynchronized function decorators. v0.6.0 (2014-10-13) =================== - Raise ``TTLCache.ExpiredError`` for expired ``TTLCache`` items. - Support unsynchronized function decorators. - Allow ``@cachedmethod.cache()`` to return None v0.5.1 (2014-09-25) =================== - No formatting of ``KeyError`` arguments. - Update ``README.rst``. v0.5.0 (2014-09-23) =================== - Do not delete expired items in TTLCache.__getitem__(). - Add ``@ttl_cache`` function decorator. - Fix public ``getsizeof()`` usage. v0.4.0 (2014-06-16) =================== - Add ``TTLCache``. - Add ``Cache`` base class. - Remove ``@cachedmethod`` `lock` parameter. v0.3.1 (2014-05-07) =================== - Add proper locking for ``cache_clear()`` and ``cache_info()``. - Report `size` in ``cache_info()``. v0.3.0 (2014-05-06) =================== - Remove ``@cache`` decorator. - Add ``size``, ``getsizeof`` members. - Add ``@cachedmethod`` decorator. v0.2.0 (2014-04-02) =================== - Add ``@cache`` decorator. - Update documentation. v0.1.0 (2014-03-27) =================== - Initial release. cachetools-5.3.3/LICENSE000066400000000000000000000020751456717112400146670ustar00rootroot00000000000000The MIT License (MIT) Copyright (c) 2014-2024 Thomas Kemmer 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. cachetools-5.3.3/MANIFEST.in000066400000000000000000000003011456717112400154060ustar00rootroot00000000000000include CHANGELOG.rst include LICENSE include MANIFEST.in include README.rst include tox.ini exclude .readthedocs.yaml recursive-include docs * prune docs/_build recursive-include tests *.py cachetools-5.3.3/README.rst000066400000000000000000000103701456717112400153460ustar00rootroot00000000000000cachetools ======================================================================== .. image:: https://img.shields.io/pypi/v/cachetools :target: https://pypi.org/project/cachetools/ :alt: Latest PyPI version .. image:: https://img.shields.io/github/actions/workflow/status/tkem/cachetools/ci.yml :target: https://github.com/tkem/cachetools/actions/workflows/ci.yml :alt: CI build status .. image:: https://img.shields.io/readthedocs/cachetools :target: https://cachetools.readthedocs.io/ :alt: Documentation build status .. image:: https://img.shields.io/codecov/c/github/tkem/cachetools/master.svg :target: https://codecov.io/gh/tkem/cachetools :alt: Test coverage .. image:: https://img.shields.io/librariesio/sourcerank/pypi/cachetools :target: https://libraries.io/pypi/cachetools :alt: Libraries.io SourceRank .. image:: https://img.shields.io/github/license/tkem/cachetools :target: https://raw.github.com/tkem/cachetools/master/LICENSE :alt: License .. image:: https://img.shields.io/badge/code%20style-black-000000.svg :target: https://github.com/psf/black :alt: Code style: black This module provides various memoizing collections and decorators, including variants of the Python Standard Library's `@lru_cache`_ function decorator. .. code-block:: python from cachetools import cached, LRUCache, TTLCache # speed up calculating Fibonacci numbers with dynamic programming @cached(cache={}) def fib(n): return n if n < 2 else fib(n - 1) + fib(n - 2) # cache least recently used Python Enhancement Proposals @cached(cache=LRUCache(maxsize=32)) def get_pep(num): url = 'http://www.python.org/dev/peps/pep-%04d/' % num with urllib.request.urlopen(url) as s: return s.read() # cache weather data for no longer than ten minutes @cached(cache=TTLCache(maxsize=1024, ttl=600)) def get_weather(place): return owm.weather_at_place(place).get_weather() For the purpose of this module, a *cache* is a mutable_ mapping_ of a fixed maximum size. When the cache is full, i.e. by adding another item the cache would exceed its maximum size, the cache must choose which item(s) to discard based on a suitable `cache algorithm`_. This module provides multiple cache classes based on different cache algorithms, as well as decorators for easily memoizing function and method calls. Installation ------------------------------------------------------------------------ cachetools is available from PyPI_ and can be installed by running:: pip install cachetools Typing stubs for this package are provided by typeshed_ and can be installed by running:: pip install types-cachetools Project Resources ------------------------------------------------------------------------ - `Documentation`_ - `Issue tracker`_ - `Source code`_ - `Change log`_ Related Projects ------------------------------------------------------------------------ - asyncache_: Helpers to use cachetools with async functions - cacheing_: Pure Python Cacheing Library - CacheToolsUtils_: Cachetools Utilities - kids.cache_: Kids caching library - shelved-cache_: Persistent cache for Python cachetools License ------------------------------------------------------------------------ Copyright (c) 2014-2024 Thomas Kemmer. Licensed under the `MIT License`_. .. _@lru_cache: https://docs.python.org/3/library/functools.html#functools.lru_cache .. _mutable: https://docs.python.org/dev/glossary.html#term-mutable .. _mapping: https://docs.python.org/dev/glossary.html#term-mapping .. _cache algorithm: https://en.wikipedia.org/wiki/Cache_algorithms .. _PyPI: https://pypi.org/project/cachetools/ .. _typeshed: https://github.com/python/typeshed/ .. _Documentation: https://cachetools.readthedocs.io/ .. _Issue tracker: https://github.com/tkem/cachetools/issues/ .. _Source code: https://github.com/tkem/cachetools/ .. _Change log: https://github.com/tkem/cachetools/blob/master/CHANGELOG.rst .. _MIT License: https://raw.github.com/tkem/cachetools/master/LICENSE .. _asyncache: https://pypi.org/project/asyncache/ .. _cacheing: https://github.com/breid48/cacheing .. _CacheToolsUtils: https://pypi.org/project/CacheToolsUtils/ .. _kids.cache: https://pypi.org/project/kids.cache/ .. _shelved-cache: https://pypi.org/project/shelved-cache/ cachetools-5.3.3/docs/000077500000000000000000000000001456717112400146065ustar00rootroot00000000000000cachetools-5.3.3/docs/conf.py000066400000000000000000000016171456717112400161120ustar00rootroot00000000000000import pathlib import sys src_directory = (pathlib.Path(__file__).parent.parent / "src").resolve() sys.path.insert(0, str(src_directory)) # Extract the current version from the source. def get_version(): """Get the version and release from the source code.""" text = (src_directory / "cachetools/__init__.py").read_text() for line in text.splitlines(): if not line.strip().startswith("__version__"): continue full_version = line.partition("=")[2].strip().strip("\"'") partial_version = ".".join(full_version.split(".")[:2]) return full_version, partial_version project = "cachetools" copyright = "2014-2024 Thomas Kemmer" release, version = get_version() extensions = [ "sphinx.ext.autodoc", "sphinx.ext.coverage", "sphinx.ext.doctest", "sphinx.ext.todo", ] exclude_patterns = ["_build"] master_doc = "index" html_theme = "classic" cachetools-5.3.3/docs/index.rst000066400000000000000000000552441456717112400164610ustar00rootroot00000000000000:tocdepth: 3 ********************************************************************* :mod:`cachetools` --- Extensible memoizing collections and decorators ********************************************************************* .. module:: cachetools This module provides various memoizing collections and decorators, including variants of the Python Standard Library's `@lru_cache`_ function decorator. For the purpose of this module, a *cache* is a mutable_ mapping_ of a fixed maximum size. When the cache is full, i.e. by adding another item the cache would exceed its maximum size, the cache must choose which item(s) to discard based on a suitable `cache algorithm`_. This module provides multiple cache classes based on different cache algorithms, as well as decorators for easily memoizing function and method calls. .. testsetup:: * from cachetools import cached, cachedmethod, LRUCache, TLRUCache, TTLCache from unittest import mock urllib = mock.MagicMock() Cache implementations ===================== This module provides several classes implementing caches using different cache algorithms. All these classes derive from class :class:`Cache`, which in turn derives from :class:`collections.MutableMapping`, and provide :attr:`maxsize` and :attr:`currsize` properties to retrieve the maximum and current size of the cache. When a cache is full, :meth:`Cache.__setitem__()` calls :meth:`self.popitem()` repeatedly until there is enough room for the item to be added. In general, a cache's size is the total size of its item's values. Therefore, :class:`Cache` provides a :meth:`getsizeof` method, which returns the size of a given `value`. The default implementation of :meth:`getsizeof` returns :const:`1` irrespective of its argument, making the cache's size equal to the number of its items, or ``len(cache)``. For convenience, all cache classes accept an optional named constructor parameter `getsizeof`, which may specify a function of one argument used to retrieve the size of an item's value. Note that the values of a :class:`Cache` are mutable by default, as are e.g. the values of a :class:`dict`. It is the user's responsibility to take care that cached values are not accidentally modified. This is especially important when using a custom `getsizeof` function, since the size of an item's value will only be computed when the item is inserted into the cache. .. note:: Please be aware that all these classes are *not* thread-safe. Access to a shared cache from multiple threads must be properly synchronized, e.g. by using one of the memoizing decorators with a suitable `lock` object. .. autoclass:: Cache(maxsize, getsizeof=None) :members: currsize, getsizeof, maxsize This class discards arbitrary items using :meth:`popitem` to make space when necessary. Derived classes may override :meth:`popitem` to implement specific caching strategies. If a subclass has to keep track of item access, insertion or deletion, it may additionally need to override :meth:`__getitem__`, :meth:`__setitem__` and :meth:`__delitem__`. .. autoclass:: FIFOCache(maxsize, getsizeof=None) :members: popitem This class evicts items in the order they were added to make space when necessary. .. autoclass:: LFUCache(maxsize, getsizeof=None) :members: popitem This class counts how often an item is retrieved, and discards the items used least often to make space when necessary. .. autoclass:: LRUCache(maxsize, getsizeof=None) :members: popitem This class discards the least recently used items first to make space when necessary. .. autoclass:: MRUCache(maxsize, getsizeof=None) :members: popitem This class discards the most recently used items first to make space when necessary. .. autoclass:: RRCache(maxsize, choice=random.choice, getsizeof=None) :members: choice, popitem This class randomly selects candidate items and discards them to make space when necessary. By default, items are selected from the list of cache keys using :func:`random.choice`. The optional argument `choice` may specify an alternative function that returns an arbitrary element from a non-empty sequence. .. autoclass:: TTLCache(maxsize, ttl, timer=time.monotonic, getsizeof=None) :members: popitem, timer, ttl This class associates a time-to-live value with each item. Items that expire because they have exceeded their time-to-live will be no longer accessible, and will be removed eventually. If no expired items are there to remove, the least recently used items will be discarded first to make space when necessary. By default, the time-to-live is specified in seconds and :func:`time.monotonic` is used to retrieve the current time. .. testcode:: cache = TTLCache(maxsize=10, ttl=60) A custom `timer` function can also be supplied, which does not have to return seconds, or even a numeric value. The expression `timer() + ttl` at the time of insertion defines the expiration time of a cache item and must be comparable against later results of `timer()`, but `ttl` does not necessarily have to be a number, either. .. testcode:: from datetime import datetime, timedelta cache = TTLCache(maxsize=10, ttl=timedelta(hours=12), timer=datetime.now) .. method:: expire(self, time=None) Expired items will be removed from a cache only at the next mutating operation, e.g. :meth:`__setitem__` or :meth:`__delitem__`, and therefore may still claim memory. Calling this method removes all items whose time-to-live would have expired by `time`, so garbage collection is free to reuse their memory. If `time` is :const:`None`, this removes all items that have expired by the current value returned by :attr:`timer`. .. autoclass:: TLRUCache(maxsize, ttu, timer=time.monotonic, getsizeof=None) :members: popitem, timer, ttu Similar to :class:`TTLCache`, this class also associates an expiration time with each item. However, for :class:`TLRUCache` items, expiration time is calculated by a user-provided time-to-use (`ttu`) function, which is passed three arguments at the time of insertion: the new item's key and value, as well as the current value of `timer()`. .. testcode:: from datetime import datetime, timedelta def my_ttu(_key, value, now): # assume value.ttl contains the item's time-to-live in hours return now + timedelta(hours=value.ttl) cache = TLRUCache(maxsize=10, ttu=my_ttu, timer=datetime.now) The expression `ttu(key, value, timer())` defines the expiration time of a cache item, and must be comparable against later results of `timer()`. Items that expire because they have exceeded their time-to-use will be no longer accessible, and will be removed eventually. If no expired items are there to remove, the least recently used items will be discarded first to make space when necessary. .. method:: expire(self, time=None) Expired items will be removed from a cache only at the next mutating operation, e.g. :meth:`__setitem__` or :meth:`__delitem__`, and therefore may still claim memory. Calling this method removes all items whose time-to-use would have expired by `time`, so garbage collection is free to reuse their memory. If `time` is :const:`None`, this removes all items that have expired by the current value returned by :attr:`timer`. Extending cache classes ======================= Sometimes it may be desirable to notice when and what cache items are evicted, i.e. removed from a cache to make room for new items. Since all cache implementations call :meth:`popitem` to evict items from the cache, this can be achieved by overriding this method in a subclass: .. doctest:: :pyversion: >= 3 >>> class MyCache(LRUCache): ... def popitem(self): ... key, value = super().popitem() ... print('Key "%s" evicted with value "%s"' % (key, value)) ... return key, value >>> c = MyCache(maxsize=2) >>> c['a'] = 1 >>> c['b'] = 2 >>> c['c'] = 3 Key "a" evicted with value "1" Similar to the standard library's :class:`collections.defaultdict`, subclasses of :class:`Cache` may implement a :meth:`__missing__` method which is called by :meth:`Cache.__getitem__` if the requested key is not found: .. doctest:: :pyversion: >= 3 >>> class PepStore(LRUCache): ... def __missing__(self, key): ... """Retrieve text of a Python Enhancement Proposal""" ... url = 'http://www.python.org/dev/peps/pep-%04d/' % key ... with urllib.request.urlopen(url) as s: ... pep = s.read() ... self[key] = pep # store text in cache ... return pep >>> peps = PepStore(maxsize=4) >>> for n in 8, 9, 290, 308, 320, 8, 218, 320, 279, 289, 320: ... pep = peps[n] >>> print(sorted(peps.keys())) [218, 279, 289, 320] Note, though, that such a class does not really behave like a *cache* any more, and will lead to surprising results when used with any of the memoizing decorators described below. However, it may be useful in its own right. Memoizing decorators ==================== The :mod:`cachetools` module provides decorators for memoizing function and method calls. This can save time when a function is often called with the same arguments: .. doctest:: >>> @cached(cache={}) ... def fib(n): ... 'Compute the nth number in the Fibonacci sequence' ... return n if n < 2 else fib(n - 1) + fib(n - 2) >>> fib(42) 267914296 .. decorator:: cached(cache, key=cachetools.keys.hashkey, lock=None, info=False) Decorator to wrap a function with a memoizing callable that saves results in a cache. The `cache` argument specifies a cache object to store previous function arguments and return values. Note that `cache` need not be an instance of the cache implementations provided by the :mod:`cachetools` module. :func:`cached` will work with any mutable mapping type, including plain :class:`dict` and :class:`weakref.WeakValueDictionary`. `key` specifies a function that will be called with the same positional and keyword arguments as the wrapped function itself, and which has to return a suitable cache key. Since caches are mappings, the object returned by `key` must be hashable. The default is to call :func:`cachetools.keys.hashkey`. If `lock` is not :const:`None`, it must specify an object implementing the `context manager`_ protocol. Any access to the cache will then be nested in a ``with lock:`` statement. This can be used for synchronizing thread access to the cache by providing a :class:`threading.Lock` instance, for example. .. note:: The `lock` context manager is used only to guard access to the cache object. The underlying wrapped function will be called outside the `with` statement, and must be thread-safe by itself. The decorator's `cache`, `key` and `lock` parameters are also available as :attr:`cache`, :attr:`cache_key` and :attr:`cache_lock` attributes of the memoizing wrapper function. These can be used for clearing the cache or invalidating individual cache items, for example. .. testcode:: from threading import Lock # 640K should be enough for anyone... @cached(cache=LRUCache(maxsize=640*1024, getsizeof=len), lock=Lock()) def get_pep(num): 'Retrieve text of a Python Enhancement Proposal' url = 'http://www.python.org/dev/peps/pep-%04d/' % num with urllib.request.urlopen(url) as s: return s.read() # make sure access to cache is synchronized with get_pep.cache_lock: get_pep.cache.clear() # always use the key function for accessing cache items with get_pep.cache_lock: get_pep.cache.pop(get_pep.cache_key(42), None) For the common use case of clearing or invalidating the cache, the decorator also provides a :func:`cache_clear()` function which takes care of locking automatically, if needed: .. testcode:: # no need for get_pep.cache_lock here get_pep.cache_clear() If `info` is set to :const:`True`, the wrapped function is instrumented with a :func:`cache_info()` function that returns a named tuple showing `hits`, `misses`, `maxsize` and `currsize`, to help measure the effectiveness of the cache. .. note:: Note that this will inflict a - probably minor - performance penalty, so it has to be explicitly enabled. .. doctest:: :pyversion: >= 3 >>> @cached(cache=LRUCache(maxsize=32), info=True) ... def get_pep(num): ... url = 'http://www.python.org/dev/peps/pep-%04d/' % num ... with urllib.request.urlopen(url) as s: ... return s.read() >>> for n in 8, 290, 308, 320, 8, 218, 320, 279, 289, 320, 9991: ... pep = get_pep(n) >>> get_pep.cache_info() CacheInfo(hits=3, misses=8, maxsize=32, currsize=8) The original underlying function is accessible through the :attr:`__wrapped__` attribute. This can be used for introspection or for bypassing the cache. It is also possible to use a single shared cache object with multiple functions. However, care must be taken that different cache keys are generated for each function, even for identical function arguments: .. doctest:: :options: +ELLIPSIS >>> from cachetools.keys import hashkey >>> from functools import partial >>> # shared cache for integer sequences >>> numcache = {} >>> # compute Fibonacci numbers >>> @cached(numcache, key=partial(hashkey, 'fib')) ... def fib(n): ... return n if n < 2 else fib(n - 1) + fib(n - 2) >>> # compute Lucas numbers >>> @cached(numcache, key=partial(hashkey, 'luc')) ... def luc(n): ... return 2 - n if n < 2 else luc(n - 1) + luc(n - 2) >>> fib(42) 267914296 >>> luc(42) 599074578 >>> list(sorted(numcache.items())) [..., (('fib', 42), 267914296), ..., (('luc', 42), 599074578)] .. decorator:: cachedmethod(cache, key=cachetools.keys.methodkey, lock=None) Decorator to wrap a class or instance method with a memoizing callable that saves results in a (possibly shared) cache. The main difference between this and the :func:`cached` function decorator is that `cache` and `lock` are not passed objects, but functions. Both will be called with :const:`self` (or :const:`cls` for class methods) as their sole argument to retrieve the cache or lock object for the method's respective instance or class. .. note:: As with :func:`cached`, the context manager obtained by calling ``lock(self)`` will only guard access to the cache itself. It is the user's responsibility to handle concurrent calls to the underlying wrapped method in a multithreaded environment. The `key` function will be called as `key(self, *args, **kwargs)` to retrieve a suitable cache key. Note that the default `key` function, :func:`cachetools.keys.methodkey`, ignores its first argument, i.e. :const:`self`. This has mostly historical reasons, but also ensures that :const:`self` does not have to be hashable. You may provide a different `key` function, e.g. :func:`cachetools.keys.hashkey`, if you need :const:`self` to be part of the cache key. One advantage of :func:`cachedmethod` over the :func:`cached` function decorator is that cache properties such as `maxsize` can be set at runtime: .. testcode:: class CachedPEPs(object): def __init__(self, cachesize): self.cache = LRUCache(maxsize=cachesize) @cachedmethod(lambda self: self.cache) def get(self, num): """Retrieve text of a Python Enhancement Proposal""" url = 'http://www.python.org/dev/peps/pep-%04d/' % num with urllib.request.urlopen(url) as s: return s.read() peps = CachedPEPs(cachesize=10) print("PEP #1: %s" % peps.get(1)) .. testoutput:: :hide: :options: +ELLIPSIS PEP #1: ... When using a shared cache for multiple methods, be aware that different cache keys must be created for each method even when function arguments are the same, just as with the `@cached` decorator: .. testcode:: class CachedReferences(object): def __init__(self, cachesize): self.cache = LRUCache(maxsize=cachesize) @cachedmethod(lambda self: self.cache, key=partial(hashkey, 'pep')) def get_pep(self, num): """Retrieve text of a Python Enhancement Proposal""" url = 'http://www.python.org/dev/peps/pep-%04d/' % num with urllib.request.urlopen(url) as s: return s.read() @cachedmethod(lambda self: self.cache, key=partial(hashkey, 'rfc')) def get_rfc(self, num): """Retrieve text of an IETF Request for Comments""" url = 'https://tools.ietf.org/rfc/rfc%d.txt' % num with urllib.request.urlopen(url) as s: return s.read() docs = CachedReferences(cachesize=100) print("PEP #1: %s" % docs.get_pep(1)) print("RFC #1: %s" % docs.get_rfc(1)) .. testoutput:: :hide: :options: +ELLIPSIS PEP #1: ... RFC #1: ... ***************************************************************** :mod:`cachetools.keys` --- Key functions for memoizing decorators ***************************************************************** .. module:: cachetools.keys This module provides several functions that can be used as key functions with the :func:`cached` and :func:`cachedmethod` decorators: .. autofunction:: hashkey This function returns a :class:`tuple` instance suitable as a cache key, provided the positional and keywords arguments are hashable. .. autofunction:: methodkey This function is equivalent to :func:`hashkey`, but ignores its first positional argument, i.e. `self` when used with the :func:`cachedmethod` decorator. .. autofunction:: typedkey This function is similar to :func:`hashkey`, but arguments of different types will yield distinct cache keys. For example, ``typedkey(3)`` and ``typedkey(3.0)`` will return different results. These functions can also be helpful when implementing custom key functions for handling some non-hashable arguments. For example, calling the following function with a dictionary as its `env` argument will raise a :class:`TypeError`, since :class:`dict` is not hashable:: @cached(LRUCache(maxsize=128)) def foo(x, y, z, env={}): pass However, if `env` always holds only hashable values itself, a custom key function can be written that handles the `env` keyword argument specially:: def envkey(*args, env={}, **kwargs): key = hashkey(*args, **kwargs) key += tuple(sorted(env.items())) return key The :func:`envkey` function can then be used in decorator declarations like this:: @cached(LRUCache(maxsize=128), key=envkey) def foo(x, y, z, env={}): pass foo(1, 2, 3, env=dict(a='a', b='b')) **************************************************************************** :mod:`cachetools.func` --- :func:`functools.lru_cache` compatible decorators **************************************************************************** .. module:: cachetools.func To ease migration from (or to) Python 3's :func:`functools.lru_cache`, this module provides several memoizing function decorators with a similar API. All these decorators wrap a function with a memoizing callable that saves up to the `maxsize` most recent calls, using different caching strategies. If `maxsize` is set to :const:`None`, the caching strategy is effectively disabled and the cache can grow without bound. If the optional argument `typed` is set to :const:`True`, function arguments of different types will be cached separately. For example, ``f(3)`` and ``f(3.0)`` will be treated as distinct calls with distinct results. If a `user_function` is specified instead, it must be a callable. This allows the decorator to be applied directly to a user function, leaving the `maxsize` at its default value of 128:: @cachetools.func.lru_cache def count_vowels(sentence): sentence = sentence.casefold() return sum(sentence.count(vowel) for vowel in 'aeiou') The wrapped function is instrumented with a :func:`cache_parameters` function that returns a new :class:`dict` showing the values for `maxsize` and `typed`. This is for information purposes only. Mutating the values has no effect. The wrapped function is also instrumented with :func:`cache_info` and :func:`cache_clear` functions to provide information about cache performance and clear the cache. Please see the :func:`functools.lru_cache` documentation for details. Also note that all the decorators in this module are thread-safe by default. .. decorator:: fifo_cache(user_function) fifo_cache(maxsize=128, typed=False) Decorator that wraps a function with a memoizing callable that saves up to `maxsize` results based on a First In First Out (FIFO) algorithm. .. decorator:: lfu_cache(user_function) lfu_cache(maxsize=128, typed=False) Decorator that wraps a function with a memoizing callable that saves up to `maxsize` results based on a Least Frequently Used (LFU) algorithm. .. decorator:: lru_cache(user_function) lru_cache(maxsize=128, typed=False) Decorator that wraps a function with a memoizing callable that saves up to `maxsize` results based on a Least Recently Used (LRU) algorithm. .. decorator:: mru_cache(user_function) mru_cache(maxsize=128, typed=False) Decorator that wraps a function with a memoizing callable that saves up to `maxsize` results based on a Most Recently Used (MRU) algorithm. .. decorator:: rr_cache(user_function) rr_cache(maxsize=128, choice=random.choice, typed=False) Decorator that wraps a function with a memoizing callable that saves up to `maxsize` results based on a Random Replacement (RR) algorithm. .. decorator:: ttl_cache(user_function) ttl_cache(maxsize=128, ttl=600, timer=time.monotonic, typed=False) Decorator to wrap a function with a memoizing callable that saves up to `maxsize` results based on a Least Recently Used (LRU) algorithm with a per-item time-to-live (TTL) value. .. _@lru_cache: http://docs.python.org/3/library/functools.html#functools.lru_cache .. _cache algorithm: http://en.wikipedia.org/wiki/Cache_algorithms .. _context manager: http://docs.python.org/dev/glossary.html#term-context-manager .. _mapping: http://docs.python.org/dev/glossary.html#term-mapping .. _mutable: http://docs.python.org/dev/glossary.html#term-mutable cachetools-5.3.3/pyproject.toml000066400000000000000000000001441456717112400165710ustar00rootroot00000000000000[build-system] requires = ["setuptools >= 46.4.0", "wheel"] build-backend = "setuptools.build_meta" cachetools-5.3.3/setup.cfg000066400000000000000000000024201456717112400154750ustar00rootroot00000000000000[metadata] name = cachetools version = attr: cachetools.__version__ url = https://github.com/tkem/cachetools/ author = Thomas Kemmer author_email = tkemmer@computer.org license = MIT license_files = LICENSE description = Extensible memoizing collections and decorators long_description = file: README.rst classifiers = Development Status :: 5 - Production/Stable Environment :: Other Environment Intended Audience :: Developers License :: OSI Approved :: MIT License Operating System :: OS Independent Programming Language :: Python Programming Language :: Python :: 3 Programming Language :: Python :: 3.7 Programming Language :: Python :: 3.8 Programming Language :: Python :: 3.9 Programming Language :: Python :: 3.10 Programming Language :: Python :: 3.11 Programming Language :: Python :: 3.12 Topic :: Software Development :: Libraries :: Python Modules [options] package_dir = = src packages = find: python_requires = >= 3.7 [options.packages.find] where = src [flake8] max-line-length = 80 exclude = .git, .tox, build select = C, E, F, W, B, B950, I, N # F401: imported but unused (submodule shims) # E501: line too long (black) ignore = F401, E501 [build_sphinx] source-dir = docs/ build-dir = docs/_build all_files = 1 cachetools-5.3.3/setup.py000066400000000000000000000000461456717112400153700ustar00rootroot00000000000000from setuptools import setup setup() cachetools-5.3.3/src/000077500000000000000000000000001456717112400144455ustar00rootroot00000000000000cachetools-5.3.3/src/cachetools/000077500000000000000000000000001456717112400165715ustar00rootroot00000000000000cachetools-5.3.3/src/cachetools/__init__.py000066400000000000000000000606251456717112400207130ustar00rootroot00000000000000"""Extensible memoizing collections and decorators.""" __all__ = ( "Cache", "FIFOCache", "LFUCache", "LRUCache", "MRUCache", "RRCache", "TLRUCache", "TTLCache", "cached", "cachedmethod", ) __version__ = "5.3.3" import collections import collections.abc import functools import heapq import random import time from . import keys class _DefaultSize: __slots__ = () def __getitem__(self, _): return 1 def __setitem__(self, _, value): assert value == 1 def pop(self, _): return 1 class Cache(collections.abc.MutableMapping): """Mutable mapping to serve as a simple cache or cache base class.""" __marker = object() __size = _DefaultSize() def __init__(self, maxsize, getsizeof=None): if getsizeof: self.getsizeof = getsizeof if self.getsizeof is not Cache.getsizeof: self.__size = dict() self.__data = dict() self.__currsize = 0 self.__maxsize = maxsize def __repr__(self): return "%s(%s, maxsize=%r, currsize=%r)" % ( self.__class__.__name__, repr(self.__data), self.__maxsize, self.__currsize, ) def __getitem__(self, key): try: return self.__data[key] except KeyError: return self.__missing__(key) def __setitem__(self, key, value): maxsize = self.__maxsize size = self.getsizeof(value) if size > maxsize: raise ValueError("value too large") if key not in self.__data or self.__size[key] < size: while self.__currsize + size > maxsize: self.popitem() if key in self.__data: diffsize = size - self.__size[key] else: diffsize = size self.__data[key] = value self.__size[key] = size self.__currsize += diffsize def __delitem__(self, key): size = self.__size.pop(key) del self.__data[key] self.__currsize -= size def __contains__(self, key): return key in self.__data def __missing__(self, key): raise KeyError(key) def __iter__(self): return iter(self.__data) def __len__(self): return len(self.__data) def get(self, key, default=None): if key in self: return self[key] else: return default def pop(self, key, default=__marker): if key in self: value = self[key] del self[key] elif default is self.__marker: raise KeyError(key) else: value = default return value def setdefault(self, key, default=None): if key in self: value = self[key] else: self[key] = value = default return value @property def maxsize(self): """The maximum size of the cache.""" return self.__maxsize @property def currsize(self): """The current size of the cache.""" return self.__currsize @staticmethod def getsizeof(value): """Return the size of a cache element's value.""" return 1 class FIFOCache(Cache): """First In First Out (FIFO) cache implementation.""" def __init__(self, maxsize, getsizeof=None): Cache.__init__(self, maxsize, getsizeof) self.__order = collections.OrderedDict() def __setitem__(self, key, value, cache_setitem=Cache.__setitem__): cache_setitem(self, key, value) try: self.__order.move_to_end(key) except KeyError: self.__order[key] = None def __delitem__(self, key, cache_delitem=Cache.__delitem__): cache_delitem(self, key) del self.__order[key] def popitem(self): """Remove and return the `(key, value)` pair first inserted.""" try: key = next(iter(self.__order)) except StopIteration: raise KeyError("%s is empty" % type(self).__name__) from None else: return (key, self.pop(key)) class LFUCache(Cache): """Least Frequently Used (LFU) cache implementation.""" def __init__(self, maxsize, getsizeof=None): Cache.__init__(self, maxsize, getsizeof) self.__counter = collections.Counter() def __getitem__(self, key, cache_getitem=Cache.__getitem__): value = cache_getitem(self, key) if key in self: # __missing__ may not store item self.__counter[key] -= 1 return value def __setitem__(self, key, value, cache_setitem=Cache.__setitem__): cache_setitem(self, key, value) self.__counter[key] -= 1 def __delitem__(self, key, cache_delitem=Cache.__delitem__): cache_delitem(self, key) del self.__counter[key] def popitem(self): """Remove and return the `(key, value)` pair least frequently used.""" try: ((key, _),) = self.__counter.most_common(1) except ValueError: raise KeyError("%s is empty" % type(self).__name__) from None else: return (key, self.pop(key)) class LRUCache(Cache): """Least Recently Used (LRU) cache implementation.""" def __init__(self, maxsize, getsizeof=None): Cache.__init__(self, maxsize, getsizeof) self.__order = collections.OrderedDict() def __getitem__(self, key, cache_getitem=Cache.__getitem__): value = cache_getitem(self, key) if key in self: # __missing__ may not store item self.__update(key) return value def __setitem__(self, key, value, cache_setitem=Cache.__setitem__): cache_setitem(self, key, value) self.__update(key) def __delitem__(self, key, cache_delitem=Cache.__delitem__): cache_delitem(self, key) del self.__order[key] def popitem(self): """Remove and return the `(key, value)` pair least recently used.""" try: key = next(iter(self.__order)) except StopIteration: raise KeyError("%s is empty" % type(self).__name__) from None else: return (key, self.pop(key)) def __update(self, key): try: self.__order.move_to_end(key) except KeyError: self.__order[key] = None class MRUCache(Cache): """Most Recently Used (MRU) cache implementation.""" def __init__(self, maxsize, getsizeof=None): Cache.__init__(self, maxsize, getsizeof) self.__order = collections.OrderedDict() def __getitem__(self, key, cache_getitem=Cache.__getitem__): value = cache_getitem(self, key) if key in self: # __missing__ may not store item self.__update(key) return value def __setitem__(self, key, value, cache_setitem=Cache.__setitem__): cache_setitem(self, key, value) self.__update(key) def __delitem__(self, key, cache_delitem=Cache.__delitem__): cache_delitem(self, key) del self.__order[key] def popitem(self): """Remove and return the `(key, value)` pair most recently used.""" try: key = next(iter(self.__order)) except StopIteration: raise KeyError("%s is empty" % type(self).__name__) from None else: return (key, self.pop(key)) def __update(self, key): try: self.__order.move_to_end(key, last=False) except KeyError: self.__order[key] = None class RRCache(Cache): """Random Replacement (RR) cache implementation.""" def __init__(self, maxsize, choice=random.choice, getsizeof=None): Cache.__init__(self, maxsize, getsizeof) self.__choice = choice @property def choice(self): """The `choice` function used by the cache.""" return self.__choice def popitem(self): """Remove and return a random `(key, value)` pair.""" try: key = self.__choice(list(self)) except IndexError: raise KeyError("%s is empty" % type(self).__name__) from None else: return (key, self.pop(key)) class _TimedCache(Cache): """Base class for time aware cache implementations.""" class _Timer: def __init__(self, timer): self.__timer = timer self.__nesting = 0 def __call__(self): if self.__nesting == 0: return self.__timer() else: return self.__time def __enter__(self): if self.__nesting == 0: self.__time = time = self.__timer() else: time = self.__time self.__nesting += 1 return time def __exit__(self, *exc): self.__nesting -= 1 def __reduce__(self): return _TimedCache._Timer, (self.__timer,) def __getattr__(self, name): return getattr(self.__timer, name) def __init__(self, maxsize, timer=time.monotonic, getsizeof=None): Cache.__init__(self, maxsize, getsizeof) self.__timer = _TimedCache._Timer(timer) def __repr__(self, cache_repr=Cache.__repr__): with self.__timer as time: self.expire(time) return cache_repr(self) def __len__(self, cache_len=Cache.__len__): with self.__timer as time: self.expire(time) return cache_len(self) @property def currsize(self): with self.__timer as time: self.expire(time) return super().currsize @property def timer(self): """The timer function used by the cache.""" return self.__timer def clear(self): with self.__timer as time: self.expire(time) Cache.clear(self) def get(self, *args, **kwargs): with self.__timer: return Cache.get(self, *args, **kwargs) def pop(self, *args, **kwargs): with self.__timer: return Cache.pop(self, *args, **kwargs) def setdefault(self, *args, **kwargs): with self.__timer: return Cache.setdefault(self, *args, **kwargs) class TTLCache(_TimedCache): """LRU Cache implementation with per-item time-to-live (TTL) value.""" class _Link: __slots__ = ("key", "expires", "next", "prev") def __init__(self, key=None, expires=None): self.key = key self.expires = expires def __reduce__(self): return TTLCache._Link, (self.key, self.expires) def unlink(self): next = self.next prev = self.prev prev.next = next next.prev = prev def __init__(self, maxsize, ttl, timer=time.monotonic, getsizeof=None): _TimedCache.__init__(self, maxsize, timer, getsizeof) self.__root = root = TTLCache._Link() root.prev = root.next = root self.__links = collections.OrderedDict() self.__ttl = ttl def __contains__(self, key): try: link = self.__links[key] # no reordering except KeyError: return False else: return self.timer() < link.expires def __getitem__(self, key, cache_getitem=Cache.__getitem__): try: link = self.__getlink(key) except KeyError: expired = False else: expired = not (self.timer() < link.expires) if expired: return self.__missing__(key) else: return cache_getitem(self, key) def __setitem__(self, key, value, cache_setitem=Cache.__setitem__): with self.timer as time: self.expire(time) cache_setitem(self, key, value) try: link = self.__getlink(key) except KeyError: self.__links[key] = link = TTLCache._Link(key) else: link.unlink() link.expires = time + self.__ttl link.next = root = self.__root link.prev = prev = root.prev prev.next = root.prev = link def __delitem__(self, key, cache_delitem=Cache.__delitem__): cache_delitem(self, key) link = self.__links.pop(key) link.unlink() if not (self.timer() < link.expires): raise KeyError(key) def __iter__(self): root = self.__root curr = root.next while curr is not root: # "freeze" time for iterator access with self.timer as time: if time < curr.expires: yield curr.key curr = curr.next def __setstate__(self, state): self.__dict__.update(state) root = self.__root root.prev = root.next = root for link in sorted(self.__links.values(), key=lambda obj: obj.expires): link.next = root link.prev = prev = root.prev prev.next = root.prev = link self.expire(self.timer()) @property def ttl(self): """The time-to-live value of the cache's items.""" return self.__ttl def expire(self, time=None): """Remove expired items from the cache.""" if time is None: time = self.timer() root = self.__root curr = root.next links = self.__links cache_delitem = Cache.__delitem__ while curr is not root and not (time < curr.expires): cache_delitem(self, curr.key) del links[curr.key] next = curr.next curr.unlink() curr = next def popitem(self): """Remove and return the `(key, value)` pair least recently used that has not already expired. """ with self.timer as time: self.expire(time) try: key = next(iter(self.__links)) except StopIteration: raise KeyError("%s is empty" % type(self).__name__) from None else: return (key, self.pop(key)) def __getlink(self, key): value = self.__links[key] self.__links.move_to_end(key) return value class TLRUCache(_TimedCache): """Time aware Least Recently Used (TLRU) cache implementation.""" @functools.total_ordering class _Item: __slots__ = ("key", "expires", "removed") def __init__(self, key=None, expires=None): self.key = key self.expires = expires self.removed = False def __lt__(self, other): return self.expires < other.expires def __init__(self, maxsize, ttu, timer=time.monotonic, getsizeof=None): _TimedCache.__init__(self, maxsize, timer, getsizeof) self.__items = collections.OrderedDict() self.__order = [] self.__ttu = ttu def __contains__(self, key): try: item = self.__items[key] # no reordering except KeyError: return False else: return self.timer() < item.expires def __getitem__(self, key, cache_getitem=Cache.__getitem__): try: item = self.__getitem(key) except KeyError: expired = False else: expired = not (self.timer() < item.expires) if expired: return self.__missing__(key) else: return cache_getitem(self, key) def __setitem__(self, key, value, cache_setitem=Cache.__setitem__): with self.timer as time: expires = self.__ttu(key, value, time) if not (time < expires): return # skip expired items self.expire(time) cache_setitem(self, key, value) # removing an existing item would break the heap structure, so # only mark it as removed for now try: self.__getitem(key).removed = True except KeyError: pass self.__items[key] = item = TLRUCache._Item(key, expires) heapq.heappush(self.__order, item) def __delitem__(self, key, cache_delitem=Cache.__delitem__): with self.timer as time: # no self.expire() for performance reasons, e.g. self.clear() [#67] cache_delitem(self, key) item = self.__items.pop(key) item.removed = True if not (time < item.expires): raise KeyError(key) def __iter__(self): for curr in self.__order: # "freeze" time for iterator access with self.timer as time: if time < curr.expires and not curr.removed: yield curr.key @property def ttu(self): """The local time-to-use function used by the cache.""" return self.__ttu def expire(self, time=None): """Remove expired items from the cache.""" if time is None: time = self.timer() items = self.__items order = self.__order # clean up the heap if too many items are marked as removed if len(order) > len(items) * 2: self.__order = order = [item for item in order if not item.removed] heapq.heapify(order) cache_delitem = Cache.__delitem__ while order and (order[0].removed or not (time < order[0].expires)): item = heapq.heappop(order) if not item.removed: cache_delitem(self, item.key) del items[item.key] def popitem(self): """Remove and return the `(key, value)` pair least recently used that has not already expired. """ with self.timer as time: self.expire(time) try: key = next(iter(self.__items)) except StopIteration: raise KeyError("%s is empty" % self.__class__.__name__) from None else: return (key, self.pop(key)) def __getitem(self, key): value = self.__items[key] self.__items.move_to_end(key) return value _CacheInfo = collections.namedtuple( "CacheInfo", ["hits", "misses", "maxsize", "currsize"] ) def cached(cache, key=keys.hashkey, lock=None, info=False): """Decorator to wrap a function with a memoizing callable that saves results in a cache. """ def decorator(func): if info: hits = misses = 0 if isinstance(cache, Cache): def getinfo(): nonlocal hits, misses return _CacheInfo(hits, misses, cache.maxsize, cache.currsize) elif isinstance(cache, collections.abc.Mapping): def getinfo(): nonlocal hits, misses return _CacheInfo(hits, misses, None, len(cache)) else: def getinfo(): nonlocal hits, misses return _CacheInfo(hits, misses, 0, 0) if cache is None: def wrapper(*args, **kwargs): nonlocal misses misses += 1 return func(*args, **kwargs) def cache_clear(): nonlocal hits, misses hits = misses = 0 cache_info = getinfo elif lock is None: def wrapper(*args, **kwargs): nonlocal hits, misses k = key(*args, **kwargs) try: result = cache[k] hits += 1 return result except KeyError: misses += 1 v = func(*args, **kwargs) try: cache[k] = v except ValueError: pass # value too large return v def cache_clear(): nonlocal hits, misses cache.clear() hits = misses = 0 cache_info = getinfo else: def wrapper(*args, **kwargs): nonlocal hits, misses k = key(*args, **kwargs) try: with lock: result = cache[k] hits += 1 return result except KeyError: with lock: misses += 1 v = func(*args, **kwargs) # in case of a race, prefer the item already in the cache try: with lock: return cache.setdefault(k, v) except ValueError: return v # value too large def cache_clear(): nonlocal hits, misses with lock: cache.clear() hits = misses = 0 def cache_info(): with lock: return getinfo() else: if cache is None: def wrapper(*args, **kwargs): return func(*args, **kwargs) def cache_clear(): pass elif lock is None: def wrapper(*args, **kwargs): k = key(*args, **kwargs) try: return cache[k] except KeyError: pass # key not found v = func(*args, **kwargs) try: cache[k] = v except ValueError: pass # value too large return v def cache_clear(): cache.clear() else: def wrapper(*args, **kwargs): k = key(*args, **kwargs) try: with lock: return cache[k] except KeyError: pass # key not found v = func(*args, **kwargs) # in case of a race, prefer the item already in the cache try: with lock: return cache.setdefault(k, v) except ValueError: return v # value too large def cache_clear(): with lock: cache.clear() cache_info = None wrapper.cache = cache wrapper.cache_key = key wrapper.cache_lock = lock wrapper.cache_clear = cache_clear wrapper.cache_info = cache_info return functools.update_wrapper(wrapper, func) return decorator def cachedmethod(cache, key=keys.methodkey, lock=None): """Decorator to wrap a class or instance method with a memoizing callable that saves results in a cache. """ def decorator(method): if lock is None: def wrapper(self, *args, **kwargs): c = cache(self) if c is None: return method(self, *args, **kwargs) k = key(self, *args, **kwargs) try: return c[k] except KeyError: pass # key not found v = method(self, *args, **kwargs) try: c[k] = v except ValueError: pass # value too large return v def clear(self): c = cache(self) if c is not None: c.clear() else: def wrapper(self, *args, **kwargs): c = cache(self) if c is None: return method(self, *args, **kwargs) k = key(self, *args, **kwargs) try: with lock(self): return c[k] except KeyError: pass # key not found v = method(self, *args, **kwargs) # in case of a race, prefer the item already in the cache try: with lock(self): return c.setdefault(k, v) except ValueError: return v # value too large def clear(self): c = cache(self) if c is not None: with lock(self): c.clear() wrapper.cache = cache wrapper.cache_key = key wrapper.cache_lock = lock wrapper.cache_clear = clear return functools.update_wrapper(wrapper, method) return decorator cachetools-5.3.3/src/cachetools/func.py000066400000000000000000000070401456717112400200770ustar00rootroot00000000000000"""`functools.lru_cache` compatible memoizing function decorators.""" __all__ = ("fifo_cache", "lfu_cache", "lru_cache", "mru_cache", "rr_cache", "ttl_cache") import math import random import time try: from threading import RLock except ImportError: # pragma: no cover from dummy_threading import RLock from . import FIFOCache, LFUCache, LRUCache, MRUCache, RRCache, TTLCache from . import cached from . import keys class _UnboundTTLCache(TTLCache): def __init__(self, ttl, timer): TTLCache.__init__(self, math.inf, ttl, timer) @property def maxsize(self): return None def _cache(cache, maxsize, typed): def decorator(func): key = keys.typedkey if typed else keys.hashkey wrapper = cached(cache=cache, key=key, lock=RLock(), info=True)(func) wrapper.cache_parameters = lambda: {"maxsize": maxsize, "typed": typed} return wrapper return decorator def fifo_cache(maxsize=128, typed=False): """Decorator to wrap a function with a memoizing callable that saves up to `maxsize` results based on a First In First Out (FIFO) algorithm. """ if maxsize is None: return _cache({}, None, typed) elif callable(maxsize): return _cache(FIFOCache(128), 128, typed)(maxsize) else: return _cache(FIFOCache(maxsize), maxsize, typed) def lfu_cache(maxsize=128, typed=False): """Decorator to wrap a function with a memoizing callable that saves up to `maxsize` results based on a Least Frequently Used (LFU) algorithm. """ if maxsize is None: return _cache({}, None, typed) elif callable(maxsize): return _cache(LFUCache(128), 128, typed)(maxsize) else: return _cache(LFUCache(maxsize), maxsize, typed) def lru_cache(maxsize=128, typed=False): """Decorator to wrap a function with a memoizing callable that saves up to `maxsize` results based on a Least Recently Used (LRU) algorithm. """ if maxsize is None: return _cache({}, None, typed) elif callable(maxsize): return _cache(LRUCache(128), 128, typed)(maxsize) else: return _cache(LRUCache(maxsize), maxsize, typed) def mru_cache(maxsize=128, typed=False): """Decorator to wrap a function with a memoizing callable that saves up to `maxsize` results based on a Most Recently Used (MRU) algorithm. """ if maxsize is None: return _cache({}, None, typed) elif callable(maxsize): return _cache(MRUCache(128), 128, typed)(maxsize) else: return _cache(MRUCache(maxsize), maxsize, typed) def rr_cache(maxsize=128, choice=random.choice, typed=False): """Decorator to wrap a function with a memoizing callable that saves up to `maxsize` results based on a Random Replacement (RR) algorithm. """ if maxsize is None: return _cache({}, None, typed) elif callable(maxsize): return _cache(RRCache(128, choice), 128, typed)(maxsize) else: return _cache(RRCache(maxsize, choice), maxsize, typed) def ttl_cache(maxsize=128, ttl=600, timer=time.monotonic, typed=False): """Decorator to wrap a function with a memoizing callable that saves up to `maxsize` results based on a Least Recently Used (LRU) algorithm with a per-item time-to-live (TTL) value. """ if maxsize is None: return _cache(_UnboundTTLCache(ttl, timer), None, typed) elif callable(maxsize): return _cache(TTLCache(128, ttl, timer), 128, typed)(maxsize) else: return _cache(TTLCache(maxsize, ttl, timer), maxsize, typed) cachetools-5.3.3/src/cachetools/keys.py000066400000000000000000000031151456717112400201160ustar00rootroot00000000000000"""Key functions for memoizing decorators.""" __all__ = ("hashkey", "methodkey", "typedkey") class _HashedTuple(tuple): """A tuple that ensures that hash() will be called no more than once per element, since cache decorators will hash the key multiple times on a cache miss. See also _HashedSeq in the standard library functools implementation. """ __hashvalue = None def __hash__(self, hash=tuple.__hash__): hashvalue = self.__hashvalue if hashvalue is None: self.__hashvalue = hashvalue = hash(self) return hashvalue def __add__(self, other, add=tuple.__add__): return _HashedTuple(add(self, other)) def __radd__(self, other, add=tuple.__add__): return _HashedTuple(add(other, self)) def __getstate__(self): return {} # used for separating keyword arguments; we do not use an object # instance here so identity is preserved when pickling/unpickling _kwmark = (_HashedTuple,) def hashkey(*args, **kwargs): """Return a cache key for the specified hashable arguments.""" if kwargs: return _HashedTuple(args + sum(sorted(kwargs.items()), _kwmark)) else: return _HashedTuple(args) def methodkey(self, *args, **kwargs): """Return a cache key for use with cached methods.""" return hashkey(*args, **kwargs) def typedkey(*args, **kwargs): """Return a typed cache key for the specified hashable arguments.""" key = hashkey(*args, **kwargs) key += tuple(type(v) for v in args) key += tuple(type(v) for _, v in sorted(kwargs.items())) return key cachetools-5.3.3/tests/000077500000000000000000000000001456717112400150205ustar00rootroot00000000000000cachetools-5.3.3/tests/__init__.py000066400000000000000000000230201456717112400171260ustar00rootroot00000000000000import unittest class CacheTestMixin: Cache = None def test_defaults(self): cache = self.Cache(maxsize=1) self.assertEqual(0, len(cache)) self.assertEqual(1, cache.maxsize) self.assertEqual(0, cache.currsize) self.assertEqual(1, cache.getsizeof(None)) self.assertEqual(1, cache.getsizeof("")) self.assertEqual(1, cache.getsizeof(0)) self.assertTrue(repr(cache).startswith(cache.__class__.__name__)) def test_insert(self): cache = self.Cache(maxsize=2) cache.update({1: 1, 2: 2}) self.assertEqual(2, len(cache)) self.assertEqual(1, cache[1]) self.assertEqual(2, cache[2]) cache[3] = 3 self.assertEqual(2, len(cache)) self.assertEqual(3, cache[3]) self.assertTrue(1 in cache or 2 in cache) cache[4] = 4 self.assertEqual(2, len(cache)) self.assertEqual(4, cache[4]) self.assertTrue(1 in cache or 2 in cache or 3 in cache) def test_update(self): cache = self.Cache(maxsize=2) cache.update({1: 1, 2: 2}) self.assertEqual(2, len(cache)) self.assertEqual(1, cache[1]) self.assertEqual(2, cache[2]) cache.update({1: 1, 2: 2}) self.assertEqual(2, len(cache)) self.assertEqual(1, cache[1]) self.assertEqual(2, cache[2]) cache.update({1: "a", 2: "b"}) self.assertEqual(2, len(cache)) self.assertEqual("a", cache[1]) self.assertEqual("b", cache[2]) def test_delete(self): cache = self.Cache(maxsize=2) cache.update({1: 1, 2: 2}) self.assertEqual(2, len(cache)) self.assertEqual(1, cache[1]) self.assertEqual(2, cache[2]) del cache[2] self.assertEqual(1, len(cache)) self.assertEqual(1, cache[1]) self.assertNotIn(2, cache) del cache[1] self.assertEqual(0, len(cache)) self.assertNotIn(1, cache) self.assertNotIn(2, cache) with self.assertRaises(KeyError): del cache[1] self.assertEqual(0, len(cache)) self.assertNotIn(1, cache) self.assertNotIn(2, cache) def test_pop(self): cache = self.Cache(maxsize=2) cache.update({1: 1, 2: 2}) self.assertEqual(2, cache.pop(2)) self.assertEqual(1, len(cache)) self.assertEqual(1, cache.pop(1)) self.assertEqual(0, len(cache)) with self.assertRaises(KeyError): cache.pop(2) with self.assertRaises(KeyError): cache.pop(1) with self.assertRaises(KeyError): cache.pop(0) self.assertEqual(None, cache.pop(2, None)) self.assertEqual(None, cache.pop(1, None)) self.assertEqual(None, cache.pop(0, None)) def test_popitem(self): cache = self.Cache(maxsize=2) cache.update({1: 1, 2: 2}) self.assertIn(cache.pop(1), {1: 1, 2: 2}) self.assertEqual(1, len(cache)) self.assertIn(cache.pop(2), {1: 1, 2: 2}) self.assertEqual(0, len(cache)) with self.assertRaises(KeyError): cache.popitem() def test_popitem_exception_context(self): # since Python 3.7, MutableMapping.popitem() suppresses # exception context as implementation detail exception = None try: self.Cache(maxsize=2).popitem() except Exception as e: exception = e self.assertIsNone(exception.__cause__) self.assertTrue(exception.__suppress_context__) def test_missing(self): class DefaultCache(self.Cache): def __missing__(self, key): self[key] = key return key cache = DefaultCache(maxsize=2) self.assertEqual(0, cache.currsize) self.assertEqual(2, cache.maxsize) self.assertEqual(0, len(cache)) self.assertEqual(1, cache[1]) self.assertEqual(2, cache[2]) self.assertEqual(2, len(cache)) self.assertTrue(1 in cache and 2 in cache) self.assertEqual(3, cache[3]) self.assertEqual(2, len(cache)) self.assertTrue(3 in cache) self.assertTrue(1 in cache or 2 in cache) self.assertTrue(1 not in cache or 2 not in cache) self.assertEqual(4, cache[4]) self.assertEqual(2, len(cache)) self.assertTrue(4 in cache) self.assertTrue(1 in cache or 2 in cache or 3 in cache) # verify __missing__() is *not* called for any operations # besides __getitem__() self.assertEqual(4, cache.get(4)) self.assertEqual(None, cache.get(5)) self.assertEqual(5 * 5, cache.get(5, 5 * 5)) self.assertEqual(2, len(cache)) self.assertEqual(4, cache.pop(4)) with self.assertRaises(KeyError): cache.pop(5) self.assertEqual(None, cache.pop(5, None)) self.assertEqual(5 * 5, cache.pop(5, 5 * 5)) self.assertEqual(1, len(cache)) cache.clear() cache[1] = 1 + 1 self.assertEqual(1 + 1, cache.setdefault(1)) self.assertEqual(1 + 1, cache.setdefault(1, 1)) self.assertEqual(1 + 1, cache[1]) self.assertEqual(2 + 2, cache.setdefault(2, 2 + 2)) self.assertEqual(2 + 2, cache.setdefault(2, None)) self.assertEqual(2 + 2, cache.setdefault(2)) self.assertEqual(2 + 2, cache[2]) self.assertEqual(2, len(cache)) self.assertTrue(1 in cache and 2 in cache) self.assertEqual(None, cache.setdefault(3)) self.assertEqual(2, len(cache)) self.assertTrue(3 in cache) self.assertTrue(1 in cache or 2 in cache) self.assertTrue(1 not in cache or 2 not in cache) def test_missing_getsizeof(self): class DefaultCache(self.Cache): def __missing__(self, key): try: self[key] = key except ValueError: pass # not stored return key cache = DefaultCache(maxsize=2, getsizeof=lambda x: x) self.assertEqual(0, cache.currsize) self.assertEqual(2, cache.maxsize) self.assertEqual(1, cache[1]) self.assertEqual(1, len(cache)) self.assertEqual(1, cache.currsize) self.assertIn(1, cache) self.assertEqual(2, cache[2]) self.assertEqual(1, len(cache)) self.assertEqual(2, cache.currsize) self.assertNotIn(1, cache) self.assertIn(2, cache) self.assertEqual(3, cache[3]) # not stored self.assertEqual(1, len(cache)) self.assertEqual(2, cache.currsize) self.assertEqual(1, cache[1]) self.assertEqual(1, len(cache)) self.assertEqual(1, cache.currsize) self.assertEqual((1, 1), cache.popitem()) def _test_getsizeof(self, cache): self.assertEqual(0, cache.currsize) self.assertEqual(3, cache.maxsize) self.assertEqual(1, cache.getsizeof(1)) self.assertEqual(2, cache.getsizeof(2)) self.assertEqual(3, cache.getsizeof(3)) cache.update({1: 1, 2: 2}) self.assertEqual(2, len(cache)) self.assertEqual(3, cache.currsize) self.assertEqual(1, cache[1]) self.assertEqual(2, cache[2]) cache[1] = 2 self.assertEqual(1, len(cache)) self.assertEqual(2, cache.currsize) self.assertEqual(2, cache[1]) self.assertNotIn(2, cache) cache.update({1: 1, 2: 2}) self.assertEqual(2, len(cache)) self.assertEqual(3, cache.currsize) self.assertEqual(1, cache[1]) self.assertEqual(2, cache[2]) cache[3] = 3 self.assertEqual(1, len(cache)) self.assertEqual(3, cache.currsize) self.assertEqual(3, cache[3]) self.assertNotIn(1, cache) self.assertNotIn(2, cache) with self.assertRaises(ValueError): cache[3] = 4 self.assertEqual(1, len(cache)) self.assertEqual(3, cache.currsize) self.assertEqual(3, cache[3]) with self.assertRaises(ValueError): cache[4] = 4 self.assertEqual(1, len(cache)) self.assertEqual(3, cache.currsize) self.assertEqual(3, cache[3]) def test_getsizeof_param(self): self._test_getsizeof(self.Cache(maxsize=3, getsizeof=lambda x: x)) def test_getsizeof_subclass(self): class Cache(self.Cache): def getsizeof(self, value): return value self._test_getsizeof(Cache(maxsize=3)) def test_pickle(self): import pickle source = self.Cache(maxsize=2) source.update({1: 1, 2: 2}) cache = pickle.loads(pickle.dumps(source)) self.assertEqual(source, cache) self.assertEqual(2, len(cache)) self.assertEqual(1, cache[1]) self.assertEqual(2, cache[2]) cache[3] = 3 self.assertEqual(2, len(cache)) self.assertEqual(3, cache[3]) self.assertTrue(1 in cache or 2 in cache) cache[4] = 4 self.assertEqual(2, len(cache)) self.assertEqual(4, cache[4]) self.assertTrue(1 in cache or 2 in cache or 3 in cache) self.assertEqual(cache, pickle.loads(pickle.dumps(cache))) def test_pickle_maxsize(self): import pickle import sys # test empty cache, single element, large cache (recursion limit) for n in [0, 1, sys.getrecursionlimit() * 2]: source = self.Cache(maxsize=n) source.update((i, i) for i in range(n)) cache = pickle.loads(pickle.dumps(source)) self.assertEqual(n, len(cache)) self.assertEqual(source, cache) cachetools-5.3.3/tests/test_cache.py000066400000000000000000000002251456717112400174730ustar00rootroot00000000000000import unittest import cachetools from . import CacheTestMixin class CacheTest(unittest.TestCase, CacheTestMixin): Cache = cachetools.Cache cachetools-5.3.3/tests/test_cached.py000066400000000000000000000202771456717112400176500ustar00rootroot00000000000000import unittest import cachetools import cachetools.keys class CountedLock: def __init__(self): self.count = 0 def __enter__(self): self.count += 1 def __exit__(self, *exc): pass class DecoratorTestMixin: def cache(self, minsize): raise NotImplementedError def func(self, *args, **kwargs): if hasattr(self, "count"): self.count += 1 else: self.count = 0 return self.count def test_decorator(self): cache = self.cache(2) wrapper = cachetools.cached(cache)(self.func) self.assertEqual(len(cache), 0) self.assertEqual(wrapper(0), 0) self.assertEqual(len(cache), 1) self.assertIn(cachetools.keys.hashkey(0), cache) self.assertNotIn(cachetools.keys.hashkey(1), cache) self.assertNotIn(cachetools.keys.hashkey(1.0), cache) self.assertEqual(wrapper(1), 1) self.assertEqual(len(cache), 2) self.assertIn(cachetools.keys.hashkey(0), cache) self.assertIn(cachetools.keys.hashkey(1), cache) self.assertIn(cachetools.keys.hashkey(1.0), cache) self.assertEqual(wrapper(1), 1) self.assertEqual(len(cache), 2) self.assertEqual(wrapper(1.0), 1) self.assertEqual(len(cache), 2) self.assertEqual(wrapper(1.0), 1) self.assertEqual(len(cache), 2) def test_decorator_typed(self): cache = self.cache(3) key = cachetools.keys.typedkey wrapper = cachetools.cached(cache, key=key)(self.func) self.assertEqual(len(cache), 0) self.assertEqual(wrapper(0), 0) self.assertEqual(len(cache), 1) self.assertIn(cachetools.keys.typedkey(0), cache) self.assertNotIn(cachetools.keys.typedkey(1), cache) self.assertNotIn(cachetools.keys.typedkey(1.0), cache) self.assertEqual(wrapper(1), 1) self.assertEqual(len(cache), 2) self.assertIn(cachetools.keys.typedkey(0), cache) self.assertIn(cachetools.keys.typedkey(1), cache) self.assertNotIn(cachetools.keys.typedkey(1.0), cache) self.assertEqual(wrapper(1), 1) self.assertEqual(len(cache), 2) self.assertEqual(wrapper(1.0), 2) self.assertEqual(len(cache), 3) self.assertIn(cachetools.keys.typedkey(0), cache) self.assertIn(cachetools.keys.typedkey(1), cache) self.assertIn(cachetools.keys.typedkey(1.0), cache) self.assertEqual(wrapper(1.0), 2) self.assertEqual(len(cache), 3) def test_decorator_lock(self): cache = self.cache(2) lock = CountedLock() wrapper = cachetools.cached(cache, lock=lock)(self.func) self.assertEqual(len(cache), 0) self.assertEqual(wrapper(0), 0) self.assertEqual(lock.count, 2) self.assertEqual(wrapper(1), 1) self.assertEqual(lock.count, 4) self.assertEqual(wrapper(1), 1) self.assertEqual(lock.count, 5) def test_decorator_wrapped(self): cache = self.cache(2) wrapper = cachetools.cached(cache)(self.func) self.assertEqual(wrapper.__wrapped__, self.func) self.assertEqual(len(cache), 0) self.assertEqual(wrapper.__wrapped__(0), 0) self.assertEqual(len(cache), 0) self.assertEqual(wrapper(0), 1) self.assertEqual(len(cache), 1) self.assertEqual(wrapper(0), 1) self.assertEqual(len(cache), 1) def test_decorator_attributes(self): cache = self.cache(2) wrapper = cachetools.cached(cache)(self.func) self.assertIs(wrapper.cache, cache) self.assertIs(wrapper.cache_key, cachetools.keys.hashkey) self.assertIs(wrapper.cache_lock, None) def test_decorator_attributes_lock(self): cache = self.cache(2) lock = CountedLock() wrapper = cachetools.cached(cache, lock=lock)(self.func) self.assertIs(wrapper.cache, cache) self.assertIs(wrapper.cache_key, cachetools.keys.hashkey) self.assertIs(wrapper.cache_lock, lock) def test_decorator_clear(self): cache = self.cache(2) wrapper = cachetools.cached(cache)(self.func) self.assertEqual(wrapper(0), 0) self.assertEqual(len(cache), 1) wrapper.cache_clear() self.assertEqual(len(cache), 0) def test_decorator_clear_lock(self): cache = self.cache(2) lock = CountedLock() wrapper = cachetools.cached(cache, lock=lock)(self.func) self.assertEqual(wrapper(0), 0) self.assertEqual(len(cache), 1) self.assertEqual(lock.count, 2) wrapper.cache_clear() self.assertEqual(len(cache), 0) self.assertEqual(lock.count, 3) class CacheWrapperTest(unittest.TestCase, DecoratorTestMixin): def cache(self, minsize): return cachetools.Cache(maxsize=minsize) def test_decorator_info(self): cache = self.cache(2) wrapper = cachetools.cached(cache, info=True)(self.func) self.assertEqual(wrapper.cache_info(), (0, 0, 2, 0)) self.assertEqual(wrapper(0), 0) self.assertEqual(wrapper.cache_info(), (0, 1, 2, 1)) self.assertEqual(wrapper(1), 1) self.assertEqual(wrapper.cache_info(), (0, 2, 2, 2)) self.assertEqual(wrapper(0), 0) self.assertEqual(wrapper.cache_info(), (1, 2, 2, 2)) wrapper.cache_clear() self.assertEqual(len(cache), 0) self.assertEqual(wrapper.cache_info(), (0, 0, 2, 0)) def test_zero_size_cache_decorator(self): cache = self.cache(0) wrapper = cachetools.cached(cache)(self.func) self.assertEqual(len(cache), 0) self.assertEqual(wrapper(0), 0) self.assertEqual(len(cache), 0) def test_zero_size_cache_decorator_lock(self): cache = self.cache(0) lock = CountedLock() wrapper = cachetools.cached(cache, lock=lock)(self.func) self.assertEqual(len(cache), 0) self.assertEqual(wrapper(0), 0) self.assertEqual(len(cache), 0) self.assertEqual(lock.count, 2) def test_zero_size_cache_decorator_info(self): cache = self.cache(0) wrapper = cachetools.cached(cache, info=True)(self.func) self.assertEqual(wrapper.cache_info(), (0, 0, 0, 0)) self.assertEqual(wrapper(0), 0) self.assertEqual(wrapper.cache_info(), (0, 1, 0, 0)) class DictWrapperTest(unittest.TestCase, DecoratorTestMixin): def cache(self, minsize): return dict() def test_decorator_info(self): cache = self.cache(2) wrapper = cachetools.cached(cache, info=True)(self.func) self.assertEqual(wrapper.cache_info(), (0, 0, None, 0)) self.assertEqual(wrapper(0), 0) self.assertEqual(wrapper.cache_info(), (0, 1, None, 1)) self.assertEqual(wrapper(1), 1) self.assertEqual(wrapper.cache_info(), (0, 2, None, 2)) self.assertEqual(wrapper(0), 0) self.assertEqual(wrapper.cache_info(), (1, 2, None, 2)) wrapper.cache_clear() self.assertEqual(len(cache), 0) self.assertEqual(wrapper.cache_info(), (0, 0, None, 0)) class NoneWrapperTest(unittest.TestCase): def func(self, *args, **kwargs): return args + tuple(kwargs.items()) def test_decorator(self): wrapper = cachetools.cached(None)(self.func) self.assertEqual(wrapper(0), (0,)) self.assertEqual(wrapper(1), (1,)) self.assertEqual(wrapper(1, foo="bar"), (1, ("foo", "bar"))) def test_decorator_attributes(self): wrapper = cachetools.cached(None)(self.func) self.assertIs(wrapper.cache, None) self.assertIs(wrapper.cache_key, cachetools.keys.hashkey) self.assertIs(wrapper.cache_lock, None) def test_decorator_clear(self): wrapper = cachetools.cached(None)(self.func) wrapper.cache_clear() # no-op def test_decorator_info(self): wrapper = cachetools.cached(None, info=True)(self.func) self.assertEqual(wrapper.cache_info(), (0, 0, 0, 0)) self.assertEqual(wrapper(0), (0,)) self.assertEqual(wrapper.cache_info(), (0, 1, 0, 0)) self.assertEqual(wrapper(1), (1,)) self.assertEqual(wrapper.cache_info(), (0, 2, 0, 0)) wrapper.cache_clear() self.assertEqual(wrapper.cache_info(), (0, 0, 0, 0)) cachetools-5.3.3/tests/test_cachedmethod.py000066400000000000000000000154261456717112400210510ustar00rootroot00000000000000import unittest from cachetools import LRUCache, cachedmethod, keys class Cached: def __init__(self, cache, count=0): self.cache = cache self.count = count @cachedmethod(lambda self: self.cache) def get(self, value): count = self.count self.count += 1 return count @cachedmethod(lambda self: self.cache, key=keys.typedkey) def get_typed(self, value): count = self.count self.count += 1 return count class Locked: def __init__(self, cache): self.cache = cache self.count = 0 @cachedmethod(lambda self: self.cache, lock=lambda self: self) def get(self, value): return self.count def __enter__(self): self.count += 1 def __exit__(self, *exc): pass class Unhashable: def __init__(self, cache): self.cache = cache @cachedmethod(lambda self: self.cache) def get_default(self, value): return value @cachedmethod(lambda self: self.cache, key=keys.hashkey) def get_hashkey(self, value): return value # https://github.com/tkem/cachetools/issues/107 def __hash__(self): raise TypeError("unhashable type") class CachedMethodTest(unittest.TestCase): def test_dict(self): cached = Cached({}) self.assertEqual(cached.get(0), 0) self.assertEqual(cached.get(1), 1) self.assertEqual(cached.get(1), 1) self.assertEqual(cached.get(1.0), 1) self.assertEqual(cached.get(1.0), 1) cached.cache.clear() self.assertEqual(cached.get(1), 2) def test_typed_dict(self): cached = Cached(LRUCache(maxsize=2)) self.assertEqual(cached.get_typed(0), 0) self.assertEqual(cached.get_typed(1), 1) self.assertEqual(cached.get_typed(1), 1) self.assertEqual(cached.get_typed(1.0), 2) self.assertEqual(cached.get_typed(1.0), 2) self.assertEqual(cached.get_typed(0.0), 3) self.assertEqual(cached.get_typed(0), 4) def test_lru(self): cached = Cached(LRUCache(maxsize=2)) self.assertEqual(cached.get(0), 0) self.assertEqual(cached.get(1), 1) self.assertEqual(cached.get(1), 1) self.assertEqual(cached.get(1.0), 1) self.assertEqual(cached.get(1.0), 1) cached.cache.clear() self.assertEqual(cached.get(1), 2) def test_typed_lru(self): cached = Cached(LRUCache(maxsize=2)) self.assertEqual(cached.get_typed(0), 0) self.assertEqual(cached.get_typed(1), 1) self.assertEqual(cached.get_typed(1), 1) self.assertEqual(cached.get_typed(1.0), 2) self.assertEqual(cached.get_typed(1.0), 2) self.assertEqual(cached.get_typed(0.0), 3) self.assertEqual(cached.get_typed(0), 4) def test_nospace(self): cached = Cached(LRUCache(maxsize=0)) self.assertEqual(cached.get(0), 0) self.assertEqual(cached.get(1), 1) self.assertEqual(cached.get(1), 2) self.assertEqual(cached.get(1.0), 3) self.assertEqual(cached.get(1.0), 4) def test_nocache(self): cached = Cached(None) self.assertEqual(cached.get(0), 0) self.assertEqual(cached.get(1), 1) self.assertEqual(cached.get(1), 2) self.assertEqual(cached.get(1.0), 3) self.assertEqual(cached.get(1.0), 4) def test_weakref(self): import weakref import fractions import gc # in Python 3.7, `int` does not support weak references even # when subclassed, but Fraction apparently does... class Int(fractions.Fraction): def __add__(self, other): return Int(fractions.Fraction.__add__(self, other)) cached = Cached(weakref.WeakValueDictionary(), count=Int(0)) self.assertEqual(cached.get(0), 0) gc.collect() self.assertEqual(cached.get(0), 1) ref = cached.get(1) self.assertEqual(ref, 2) self.assertEqual(cached.get(1), 2) self.assertEqual(cached.get(1.0), 2) ref = cached.get_typed(1) self.assertEqual(ref, 3) self.assertEqual(cached.get_typed(1), 3) self.assertEqual(cached.get_typed(1.0), 4) cached.cache.clear() self.assertEqual(cached.get(1), 5) def test_locked_dict(self): cached = Locked({}) self.assertEqual(cached.get(0), 1) self.assertEqual(cached.get(1), 3) self.assertEqual(cached.get(1), 3) self.assertEqual(cached.get(1.0), 3) self.assertEqual(cached.get(2.0), 7) def test_locked_nocache(self): cached = Locked(None) self.assertEqual(cached.get(0), 0) self.assertEqual(cached.get(1), 0) self.assertEqual(cached.get(1), 0) self.assertEqual(cached.get(1.0), 0) self.assertEqual(cached.get(1.0), 0) def test_locked_nospace(self): cached = Locked(LRUCache(maxsize=0)) self.assertEqual(cached.get(0), 1) self.assertEqual(cached.get(1), 3) self.assertEqual(cached.get(1), 5) self.assertEqual(cached.get(1.0), 7) self.assertEqual(cached.get(1.0), 9) def test_unhashable(self): cached = Unhashable(LRUCache(maxsize=0)) self.assertEqual(cached.get_default(0), 0) self.assertEqual(cached.get_default(1), 1) with self.assertRaises(TypeError): cached.get_hashkey(0) def test_wrapped(self): cache = {} cached = Cached(cache) self.assertEqual(len(cache), 0) self.assertEqual(cached.get.__wrapped__(cached, 0), 0) self.assertEqual(len(cache), 0) self.assertEqual(cached.get(0), 1) self.assertEqual(len(cache), 1) self.assertEqual(cached.get(0), 1) self.assertEqual(len(cache), 1) def test_attributes(self): cache = {} cached = Cached(cache) self.assertIs(cached.get.cache(cached), cache) self.assertIs(cached.get.cache_key, keys.methodkey) self.assertIs(cached.get.cache_lock, None) def test_attributes_lock(self): cache = {} cached = Locked(cache) self.assertIs(cached.get.cache(cached), cache) self.assertIs(cached.get.cache_key, keys.methodkey) self.assertIs(cached.get.cache_lock(cached), cached) def test_clear(self): cache = {} cached = Cached(cache) self.assertEqual(cached.get(0), 0) self.assertEqual(len(cache), 1) cached.get.cache_clear(cached) self.assertEqual(len(cache), 0) def test_clear_locked(self): cache = {} cached = Locked(cache) self.assertEqual(cached.get(0), 1) self.assertEqual(len(cache), 1) self.assertEqual(cached.count, 2) cached.get.cache_clear(cached) self.assertEqual(len(cache), 0) self.assertEqual(cached.count, 3) cachetools-5.3.3/tests/test_fifo.py000066400000000000000000000025411456717112400173560ustar00rootroot00000000000000import unittest from cachetools import FIFOCache from . import CacheTestMixin class LRUCacheTest(unittest.TestCase, CacheTestMixin): Cache = FIFOCache def test_fifo(self): cache = FIFOCache(maxsize=2) cache[1] = 1 cache[2] = 2 cache[3] = 3 self.assertEqual(len(cache), 2) self.assertEqual(cache[2], 2) self.assertEqual(cache[3], 3) self.assertNotIn(1, cache) cache[2] cache[4] = 4 self.assertEqual(len(cache), 2) self.assertEqual(cache[3], 3) self.assertEqual(cache[4], 4) self.assertNotIn(2, cache) cache[5] = 5 self.assertEqual(len(cache), 2) self.assertEqual(cache[4], 4) self.assertEqual(cache[5], 5) self.assertNotIn(3, cache) def test_fifo_getsizeof(self): cache = FIFOCache(maxsize=3, getsizeof=lambda x: x) cache[1] = 1 cache[2] = 2 self.assertEqual(len(cache), 2) self.assertEqual(cache[1], 1) self.assertEqual(cache[2], 2) cache[3] = 3 self.assertEqual(len(cache), 1) self.assertEqual(cache[3], 3) self.assertNotIn(1, cache) self.assertNotIn(2, cache) with self.assertRaises(ValueError): cache[4] = 4 self.assertEqual(len(cache), 1) self.assertEqual(cache[3], 3) cachetools-5.3.3/tests/test_func.py000066400000000000000000000117551456717112400173750ustar00rootroot00000000000000import unittest import cachetools.func class DecoratorTestMixin: def decorator(self, maxsize, **kwargs): return self.DECORATOR(maxsize, **kwargs) def test_decorator(self): cached = self.decorator(maxsize=2)(lambda n: n) self.assertEqual(cached.cache_parameters(), {"maxsize": 2, "typed": False}) self.assertEqual(cached.cache_info(), (0, 0, 2, 0)) self.assertEqual(cached(1), 1) self.assertEqual(cached.cache_info(), (0, 1, 2, 1)) self.assertEqual(cached(1), 1) self.assertEqual(cached.cache_info(), (1, 1, 2, 1)) self.assertEqual(cached(1.0), 1.0) self.assertEqual(cached.cache_info(), (2, 1, 2, 1)) def test_decorator_clear(self): cached = self.decorator(maxsize=2)(lambda n: n) self.assertEqual(cached.cache_parameters(), {"maxsize": 2, "typed": False}) self.assertEqual(cached.cache_info(), (0, 0, 2, 0)) self.assertEqual(cached(1), 1) self.assertEqual(cached.cache_info(), (0, 1, 2, 1)) cached.cache_clear() self.assertEqual(cached.cache_info(), (0, 0, 2, 0)) self.assertEqual(cached(1), 1) self.assertEqual(cached.cache_info(), (0, 1, 2, 1)) def test_decorator_nocache(self): cached = self.decorator(maxsize=0)(lambda n: n) self.assertEqual(cached.cache_parameters(), {"maxsize": 0, "typed": False}) self.assertEqual(cached.cache_info(), (0, 0, 0, 0)) self.assertEqual(cached(1), 1) self.assertEqual(cached.cache_info(), (0, 1, 0, 0)) self.assertEqual(cached(1), 1) self.assertEqual(cached.cache_info(), (0, 2, 0, 0)) self.assertEqual(cached(1.0), 1.0) self.assertEqual(cached.cache_info(), (0, 3, 0, 0)) def test_decorator_unbound(self): cached = self.decorator(maxsize=None)(lambda n: n) self.assertEqual(cached.cache_parameters(), {"maxsize": None, "typed": False}) self.assertEqual(cached.cache_info(), (0, 0, None, 0)) self.assertEqual(cached(1), 1) self.assertEqual(cached.cache_info(), (0, 1, None, 1)) self.assertEqual(cached(1), 1) self.assertEqual(cached.cache_info(), (1, 1, None, 1)) self.assertEqual(cached(1.0), 1.0) self.assertEqual(cached.cache_info(), (2, 1, None, 1)) def test_decorator_typed(self): cached = self.decorator(maxsize=2, typed=True)(lambda n: n) self.assertEqual(cached.cache_parameters(), {"maxsize": 2, "typed": True}) self.assertEqual(cached.cache_info(), (0, 0, 2, 0)) self.assertEqual(cached(1), 1) self.assertEqual(cached.cache_info(), (0, 1, 2, 1)) self.assertEqual(cached(1), 1) self.assertEqual(cached.cache_info(), (1, 1, 2, 1)) self.assertEqual(cached(1.0), 1.0) self.assertEqual(cached.cache_info(), (1, 2, 2, 2)) self.assertEqual(cached(1.0), 1.0) self.assertEqual(cached.cache_info(), (2, 2, 2, 2)) def test_decorator_user_function(self): cached = self.decorator(lambda n: n) self.assertEqual(cached.cache_parameters(), {"maxsize": 128, "typed": False}) self.assertEqual(cached.cache_info(), (0, 0, 128, 0)) self.assertEqual(cached(1), 1) self.assertEqual(cached.cache_info(), (0, 1, 128, 1)) self.assertEqual(cached(1), 1) self.assertEqual(cached.cache_info(), (1, 1, 128, 1)) self.assertEqual(cached(1.0), 1.0) self.assertEqual(cached.cache_info(), (2, 1, 128, 1)) def test_decorator_needs_rlock(self): cached = self.decorator(lambda n: n) class RecursiveEquals: def __init__(self, use_cache): self._use_cache = use_cache def __hash__(self): return hash(self._use_cache) def __eq__(self, other): if self._use_cache: # This call will happen while the cache-lock is held, # requiring a reentrant lock to avoid deadlock. cached(self) return self._use_cache == other._use_cache # Prime the cache. cached(RecursiveEquals(False)) cached(RecursiveEquals(True)) # Then do a call which will cause a deadlock with a non-reentrant lock. self.assertEqual(cached(RecursiveEquals(True)), RecursiveEquals(True)) class FIFODecoratorTest(unittest.TestCase, DecoratorTestMixin): DECORATOR = staticmethod(cachetools.func.fifo_cache) class LFUDecoratorTest(unittest.TestCase, DecoratorTestMixin): DECORATOR = staticmethod(cachetools.func.lfu_cache) class LRUDecoratorTest(unittest.TestCase, DecoratorTestMixin): DECORATOR = staticmethod(cachetools.func.lru_cache) class MRUDecoratorTest(unittest.TestCase, DecoratorTestMixin): DECORATOR = staticmethod(cachetools.func.mru_cache) class RRDecoratorTest(unittest.TestCase, DecoratorTestMixin): DECORATOR = staticmethod(cachetools.func.rr_cache) class TTLDecoratorTest(unittest.TestCase, DecoratorTestMixin): DECORATOR = staticmethod(cachetools.func.ttl_cache) cachetools-5.3.3/tests/test_keys.py000066400000000000000000000051441456717112400174100ustar00rootroot00000000000000import unittest import cachetools.keys class CacheKeysTest(unittest.TestCase): def test_hashkey(self, key=cachetools.keys.hashkey): self.assertEqual(key(), key()) self.assertEqual(hash(key()), hash(key())) self.assertEqual(key(1, 2, 3), key(1, 2, 3)) self.assertEqual(hash(key(1, 2, 3)), hash(key(1, 2, 3))) self.assertEqual(key(1, 2, 3, x=0), key(1, 2, 3, x=0)) self.assertEqual(hash(key(1, 2, 3, x=0)), hash(key(1, 2, 3, x=0))) self.assertNotEqual(key(1, 2, 3), key(3, 2, 1)) self.assertNotEqual(key(1, 2, 3), key(1, 2, 3, x=None)) self.assertNotEqual(key(1, 2, 3, x=0), key(1, 2, 3, x=None)) self.assertNotEqual(key(1, 2, 3, x=0), key(1, 2, 3, y=0)) with self.assertRaises(TypeError): hash(key({})) # untyped keys compare equal self.assertEqual(key(1, 2, 3), key(1.0, 2.0, 3.0)) self.assertEqual(hash(key(1, 2, 3)), hash(key(1.0, 2.0, 3.0))) def test_typedkey(self, key=cachetools.keys.typedkey): self.assertEqual(key(), key()) self.assertEqual(hash(key()), hash(key())) self.assertEqual(key(1, 2, 3), key(1, 2, 3)) self.assertEqual(hash(key(1, 2, 3)), hash(key(1, 2, 3))) self.assertEqual(key(1, 2, 3, x=0), key(1, 2, 3, x=0)) self.assertEqual(hash(key(1, 2, 3, x=0)), hash(key(1, 2, 3, x=0))) self.assertNotEqual(key(1, 2, 3), key(3, 2, 1)) self.assertNotEqual(key(1, 2, 3), key(1, 2, 3, x=None)) self.assertNotEqual(key(1, 2, 3, x=0), key(1, 2, 3, x=None)) self.assertNotEqual(key(1, 2, 3, x=0), key(1, 2, 3, y=0)) with self.assertRaises(TypeError): hash(key({})) # typed keys compare unequal self.assertNotEqual(key(1, 2, 3), key(1.0, 2.0, 3.0)) def test_addkeys(self, key=cachetools.keys.hashkey): self.assertIsInstance(key(), tuple) self.assertIsInstance(key(1, 2, 3) + key(4, 5, 6), type(key())) self.assertIsInstance(key(1, 2, 3) + (4, 5, 6), type(key())) self.assertIsInstance((1, 2, 3) + key(4, 5, 6), type(key())) def test_pickle(self, key=cachetools.keys.hashkey): import pickle for k in [key(), key("abc"), key("abc", 123), key("abc", q="abc")]: # white-box test: assert cached hash value is not pickled self.assertEqual(len(k.__dict__), 0) h = hash(k) self.assertEqual(len(k.__dict__), 1) pickled = pickle.loads(pickle.dumps(k)) self.assertEqual(len(pickled.__dict__), 0) self.assertEqual(k, pickled) self.assertEqual(h, hash(pickled)) cachetools-5.3.3/tests/test_lfu.py000066400000000000000000000022561456717112400172240ustar00rootroot00000000000000import unittest from cachetools import LFUCache from . import CacheTestMixin class LFUCacheTest(unittest.TestCase, CacheTestMixin): Cache = LFUCache def test_lfu(self): cache = LFUCache(maxsize=2) cache[1] = 1 cache[1] cache[2] = 2 cache[3] = 3 self.assertEqual(len(cache), 2) self.assertEqual(cache[1], 1) self.assertTrue(2 in cache or 3 in cache) self.assertTrue(2 not in cache or 3 not in cache) cache[4] = 4 self.assertEqual(len(cache), 2) self.assertEqual(cache[4], 4) self.assertEqual(cache[1], 1) def test_lfu_getsizeof(self): cache = LFUCache(maxsize=3, getsizeof=lambda x: x) cache[1] = 1 cache[2] = 2 self.assertEqual(len(cache), 2) self.assertEqual(cache[1], 1) self.assertEqual(cache[2], 2) cache[3] = 3 self.assertEqual(len(cache), 1) self.assertEqual(cache[3], 3) self.assertNotIn(1, cache) self.assertNotIn(2, cache) with self.assertRaises(ValueError): cache[4] = 4 self.assertEqual(len(cache), 1) self.assertEqual(cache[3], 3) cachetools-5.3.3/tests/test_lru.py000066400000000000000000000025331456717112400172360ustar00rootroot00000000000000import unittest from cachetools import LRUCache from . import CacheTestMixin class LRUCacheTest(unittest.TestCase, CacheTestMixin): Cache = LRUCache def test_lru(self): cache = LRUCache(maxsize=2) cache[1] = 1 cache[2] = 2 cache[3] = 3 self.assertEqual(len(cache), 2) self.assertEqual(cache[2], 2) self.assertEqual(cache[3], 3) self.assertNotIn(1, cache) cache[2] cache[4] = 4 self.assertEqual(len(cache), 2) self.assertEqual(cache[2], 2) self.assertEqual(cache[4], 4) self.assertNotIn(3, cache) cache[5] = 5 self.assertEqual(len(cache), 2) self.assertEqual(cache[4], 4) self.assertEqual(cache[5], 5) self.assertNotIn(2, cache) def test_lru_getsizeof(self): cache = LRUCache(maxsize=3, getsizeof=lambda x: x) cache[1] = 1 cache[2] = 2 self.assertEqual(len(cache), 2) self.assertEqual(cache[1], 1) self.assertEqual(cache[2], 2) cache[3] = 3 self.assertEqual(len(cache), 1) self.assertEqual(cache[3], 3) self.assertNotIn(1, cache) self.assertNotIn(2, cache) with self.assertRaises(ValueError): cache[4] = 4 self.assertEqual(len(cache), 1) self.assertEqual(cache[3], 3) cachetools-5.3.3/tests/test_mru.py000066400000000000000000000023451456717112400172400ustar00rootroot00000000000000import unittest from cachetools import MRUCache from . import CacheTestMixin class MRUCacheTest(unittest.TestCase, CacheTestMixin): Cache = MRUCache def test_evict__writes_only(self): cache = MRUCache(maxsize=2) cache[1] = 1 cache[2] = 2 cache[3] = 3 # Evicts 1 because nothing's been used yet assert len(cache) == 2 assert 1 not in cache, "Wrong key was evicted. Should have been '1'." assert 2 in cache assert 3 in cache def test_evict__with_access(self): cache = MRUCache(maxsize=2) cache[1] = 1 cache[2] = 2 cache[1] cache[2] cache[3] = 3 # Evicts 2 assert 2 not in cache, "Wrong key was evicted. Should have been '2'." assert 1 in cache assert 3 in cache def test_evict__with_delete(self): cache = MRUCache(maxsize=2) cache[1] = 1 cache[2] = 2 del cache[2] cache[3] = 3 # Doesn't evict anything because we just deleted 2 assert 2 not in cache assert 1 in cache cache[4] = 4 # Should evict 1 as we just accessed it with __contains__ assert 1 not in cache assert 3 in cache assert 4 in cache cachetools-5.3.3/tests/test_rr.py000066400000000000000000000015001456717112400170500ustar00rootroot00000000000000import unittest from cachetools import RRCache from . import CacheTestMixin class RRCacheTest(unittest.TestCase, CacheTestMixin): Cache = RRCache def test_rr(self): cache = RRCache(maxsize=2, choice=min) self.assertEqual(min, cache.choice) cache[1] = 1 cache[2] = 2 cache[3] = 3 self.assertEqual(2, len(cache)) self.assertEqual(2, cache[2]) self.assertEqual(3, cache[3]) self.assertNotIn(1, cache) cache[0] = 0 self.assertEqual(2, len(cache)) self.assertEqual(0, cache[0]) self.assertEqual(3, cache[3]) self.assertNotIn(2, cache) cache[4] = 4 self.assertEqual(2, len(cache)) self.assertEqual(3, cache[3]) self.assertEqual(4, cache[4]) self.assertNotIn(0, cache) cachetools-5.3.3/tests/test_tlru.py000066400000000000000000000174021456717112400174230ustar00rootroot00000000000000import math import unittest from cachetools import TLRUCache from . import CacheTestMixin class Timer: def __init__(self, auto=False): self.auto = auto self.time = 0 def __call__(self): if self.auto: self.time += 1 return self.time def tick(self): self.time += 1 class TLRUTestCache(TLRUCache): def default_ttu(_key, _value, _time): return math.inf def __init__(self, maxsize, ttu=default_ttu, **kwargs): TLRUCache.__init__(self, maxsize, ttu, timer=Timer(), **kwargs) class TLRUCacheTest(unittest.TestCase, CacheTestMixin): Cache = TLRUTestCache def test_ttu(self): cache = TLRUCache(maxsize=6, ttu=lambda _, v, t: t + v + 1, timer=Timer()) self.assertEqual(0, cache.timer()) self.assertEqual(3, cache.ttu(None, 1, 1)) cache[1] = 1 self.assertEqual(1, cache[1]) self.assertEqual(1, len(cache)) self.assertEqual({1}, set(cache)) cache.timer.tick() self.assertEqual(1, cache[1]) self.assertEqual(1, len(cache)) self.assertEqual({1}, set(cache)) cache[2] = 2 self.assertEqual(1, cache[1]) self.assertEqual(2, cache[2]) self.assertEqual(2, len(cache)) self.assertEqual({1, 2}, set(cache)) cache.timer.tick() self.assertNotIn(1, cache) self.assertEqual(2, cache[2]) self.assertEqual(1, len(cache)) self.assertEqual({2}, set(cache)) cache[3] = 3 self.assertNotIn(1, cache) self.assertEqual(2, cache[2]) self.assertEqual(3, cache[3]) self.assertEqual(2, len(cache)) self.assertEqual({2, 3}, set(cache)) cache.timer.tick() self.assertNotIn(1, cache) self.assertEqual(2, cache[2]) self.assertEqual(3, cache[3]) self.assertEqual(2, len(cache)) self.assertEqual({2, 3}, set(cache)) cache[1] = 1 self.assertEqual(1, cache[1]) self.assertEqual(2, cache[2]) self.assertEqual(3, cache[3]) self.assertEqual(3, len(cache)) self.assertEqual({1, 2, 3}, set(cache)) cache.timer.tick() self.assertEqual(1, cache[1]) self.assertNotIn(2, cache) self.assertEqual(3, cache[3]) self.assertEqual(2, len(cache)) self.assertEqual({1, 3}, set(cache)) cache.timer.tick() self.assertNotIn(1, cache) self.assertNotIn(2, cache) self.assertEqual(3, cache[3]) self.assertEqual(1, len(cache)) self.assertEqual({3}, set(cache)) cache.timer.tick() self.assertNotIn(1, cache) self.assertNotIn(2, cache) self.assertNotIn(3, cache) with self.assertRaises(KeyError): del cache[1] with self.assertRaises(KeyError): cache.pop(2) with self.assertRaises(KeyError): del cache[3] self.assertEqual(0, len(cache)) self.assertEqual(set(), set(cache)) def test_ttu_lru(self): cache = TLRUCache(maxsize=2, ttu=lambda k, v, t: t + 1, timer=Timer()) self.assertEqual(0, cache.timer()) self.assertEqual(2, cache.ttu(None, None, 1)) cache[1] = 1 cache[2] = 2 cache[3] = 3 self.assertEqual(len(cache), 2) self.assertNotIn(1, cache) self.assertEqual(cache[2], 2) self.assertEqual(cache[3], 3) cache[2] cache[4] = 4 self.assertEqual(len(cache), 2) self.assertNotIn(1, cache) self.assertEqual(cache[2], 2) self.assertNotIn(3, cache) self.assertEqual(cache[4], 4) cache[5] = 5 self.assertEqual(len(cache), 2) self.assertNotIn(1, cache) self.assertNotIn(2, cache) self.assertNotIn(3, cache) self.assertEqual(cache[4], 4) self.assertEqual(cache[5], 5) def test_ttu_expire(self): cache = TLRUCache(maxsize=3, ttu=lambda k, v, t: t + 3, timer=Timer()) with cache.timer as time: self.assertEqual(time, cache.timer()) cache[1] = 1 cache.timer.tick() cache[2] = 2 cache.timer.tick() cache[3] = 3 self.assertEqual(2, cache.timer()) self.assertEqual({1, 2, 3}, set(cache)) self.assertEqual(3, len(cache)) self.assertEqual(1, cache[1]) self.assertEqual(2, cache[2]) self.assertEqual(3, cache[3]) cache.expire() self.assertEqual({1, 2, 3}, set(cache)) self.assertEqual(3, len(cache)) self.assertEqual(1, cache[1]) self.assertEqual(2, cache[2]) self.assertEqual(3, cache[3]) cache.expire(3) self.assertEqual({2, 3}, set(cache)) self.assertEqual(2, len(cache)) self.assertNotIn(1, cache) self.assertEqual(2, cache[2]) self.assertEqual(3, cache[3]) cache.expire(4) self.assertEqual({3}, set(cache)) self.assertEqual(1, len(cache)) self.assertNotIn(1, cache) self.assertNotIn(2, cache) self.assertEqual(3, cache[3]) cache.expire(5) self.assertEqual(set(), set(cache)) self.assertEqual(0, len(cache)) self.assertNotIn(1, cache) self.assertNotIn(2, cache) self.assertNotIn(3, cache) def test_ttu_expired(self): cache = TLRUCache(maxsize=1, ttu=lambda k, _, t: t + k, timer=Timer()) cache[1] = None self.assertEqual(cache[1], None) self.assertEqual(1, len(cache)) cache[0] = None self.assertNotIn(0, cache) self.assertEqual(cache[1], None) self.assertEqual(1, len(cache)) cache[-1] = None self.assertNotIn(-1, cache) self.assertNotIn(0, cache) self.assertEqual(cache[1], None) self.assertEqual(1, len(cache)) def test_ttu_atomic(self): cache = TLRUCache(maxsize=1, ttu=lambda k, v, t: t + 2, timer=Timer(auto=True)) cache[1] = 1 self.assertEqual(1, cache[1]) cache[1] = 1 self.assertEqual(1, cache.get(1)) cache[1] = 1 self.assertEqual(1, cache.pop(1)) cache[1] = 1 self.assertEqual(1, cache.setdefault(1)) cache[1] = 1 cache.clear() self.assertEqual(0, len(cache)) def test_ttu_tuple_key(self): cache = TLRUCache(maxsize=1, ttu=lambda k, v, t: t + 1, timer=Timer()) cache[(1, 2, 3)] = 42 self.assertEqual(42, cache[(1, 2, 3)]) cache.timer.tick() with self.assertRaises(KeyError): cache[(1, 2, 3)] self.assertNotIn((1, 2, 3), cache) def test_ttu_reverse_insert(self): cache = TLRUCache(maxsize=4, ttu=lambda k, v, t: t + v, timer=Timer()) self.assertEqual(0, cache.timer()) cache[3] = 3 cache[2] = 2 cache[1] = 1 cache[0] = 0 self.assertEqual({1, 2, 3}, set(cache)) self.assertEqual(3, len(cache)) self.assertNotIn(0, cache) self.assertEqual(1, cache[1]) self.assertEqual(2, cache[2]) self.assertEqual(3, cache[3]) cache.timer.tick() self.assertEqual({2, 3}, set(cache)) self.assertEqual(2, len(cache)) self.assertNotIn(0, cache) self.assertNotIn(1, cache) self.assertEqual(2, cache[2]) self.assertEqual(3, cache[3]) cache.timer.tick() self.assertEqual({3}, set(cache)) self.assertEqual(1, len(cache)) self.assertNotIn(0, cache) self.assertNotIn(1, cache) self.assertNotIn(2, cache) self.assertEqual(3, cache[3]) cache.timer.tick() self.assertEqual(set(), set(cache)) self.assertEqual(0, len(cache)) self.assertNotIn(0, cache) self.assertNotIn(1, cache) self.assertNotIn(2, cache) self.assertNotIn(3, cache) cachetools-5.3.3/tests/test_ttl.py000066400000000000000000000130431456717112400172350ustar00rootroot00000000000000import math import unittest from cachetools import TTLCache from . import CacheTestMixin class Timer: def __init__(self, auto=False): self.auto = auto self.time = 0 def __call__(self): if self.auto: self.time += 1 return self.time def tick(self): self.time += 1 class TTLTestCache(TTLCache): def __init__(self, maxsize, ttl=math.inf, **kwargs): TTLCache.__init__(self, maxsize, ttl=ttl, timer=Timer(), **kwargs) class TTLCacheTest(unittest.TestCase, CacheTestMixin): Cache = TTLTestCache def test_ttl(self): cache = TTLCache(maxsize=2, ttl=2, timer=Timer()) self.assertEqual(0, cache.timer()) self.assertEqual(2, cache.ttl) cache[1] = 1 self.assertEqual(1, cache[1]) self.assertEqual(1, len(cache)) self.assertEqual({1}, set(cache)) cache.timer.tick() self.assertEqual(1, cache[1]) self.assertEqual(1, len(cache)) self.assertEqual({1}, set(cache)) cache[2] = 2 self.assertEqual(1, cache[1]) self.assertEqual(2, cache[2]) self.assertEqual(2, len(cache)) self.assertEqual({1, 2}, set(cache)) cache.timer.tick() self.assertNotIn(1, cache) self.assertEqual(2, cache[2]) self.assertEqual(1, len(cache)) self.assertEqual({2}, set(cache)) cache[3] = 3 self.assertNotIn(1, cache) self.assertEqual(2, cache[2]) self.assertEqual(3, cache[3]) self.assertEqual(2, len(cache)) self.assertEqual({2, 3}, set(cache)) cache.timer.tick() self.assertNotIn(1, cache) self.assertNotIn(2, cache) self.assertEqual(3, cache[3]) self.assertEqual(1, len(cache)) self.assertEqual({3}, set(cache)) cache.timer.tick() self.assertNotIn(1, cache) self.assertNotIn(2, cache) self.assertNotIn(3, cache) with self.assertRaises(KeyError): del cache[1] with self.assertRaises(KeyError): cache.pop(2) with self.assertRaises(KeyError): del cache[3] self.assertEqual(0, len(cache)) self.assertEqual(set(), set(cache)) def test_ttl_lru(self): cache = TTLCache(maxsize=2, ttl=1, timer=Timer()) cache[1] = 1 cache[2] = 2 cache[3] = 3 self.assertEqual(len(cache), 2) self.assertNotIn(1, cache) self.assertEqual(cache[2], 2) self.assertEqual(cache[3], 3) cache[2] cache[4] = 4 self.assertEqual(len(cache), 2) self.assertNotIn(1, cache) self.assertEqual(cache[2], 2) self.assertNotIn(3, cache) self.assertEqual(cache[4], 4) cache[5] = 5 self.assertEqual(len(cache), 2) self.assertNotIn(1, cache) self.assertNotIn(2, cache) self.assertNotIn(3, cache) self.assertEqual(cache[4], 4) self.assertEqual(cache[5], 5) def test_ttl_expire(self): cache = TTLCache(maxsize=3, ttl=3, timer=Timer()) with cache.timer as time: self.assertEqual(time, cache.timer()) self.assertEqual(3, cache.ttl) cache[1] = 1 cache.timer.tick() cache[2] = 2 cache.timer.tick() cache[3] = 3 self.assertEqual(2, cache.timer()) self.assertEqual({1, 2, 3}, set(cache)) self.assertEqual(3, len(cache)) self.assertEqual(1, cache[1]) self.assertEqual(2, cache[2]) self.assertEqual(3, cache[3]) cache.expire() self.assertEqual({1, 2, 3}, set(cache)) self.assertEqual(3, len(cache)) self.assertEqual(1, cache[1]) self.assertEqual(2, cache[2]) self.assertEqual(3, cache[3]) cache.expire(3) self.assertEqual({2, 3}, set(cache)) self.assertEqual(2, len(cache)) self.assertNotIn(1, cache) self.assertEqual(2, cache[2]) self.assertEqual(3, cache[3]) cache.expire(4) self.assertEqual({3}, set(cache)) self.assertEqual(1, len(cache)) self.assertNotIn(1, cache) self.assertNotIn(2, cache) self.assertEqual(3, cache[3]) cache.expire(5) self.assertEqual(set(), set(cache)) self.assertEqual(0, len(cache)) self.assertNotIn(1, cache) self.assertNotIn(2, cache) self.assertNotIn(3, cache) def test_ttl_atomic(self): cache = TTLCache(maxsize=1, ttl=2, timer=Timer(auto=True)) cache[1] = 1 self.assertEqual(1, cache[1]) cache[1] = 1 self.assertEqual(1, cache.get(1)) cache[1] = 1 self.assertEqual(1, cache.pop(1)) cache[1] = 1 self.assertEqual(1, cache.setdefault(1)) cache[1] = 1 cache.clear() self.assertEqual(0, len(cache)) def test_ttl_tuple_key(self): cache = TTLCache(maxsize=1, ttl=1, timer=Timer()) self.assertEqual(1, cache.ttl) cache[(1, 2, 3)] = 42 self.assertEqual(42, cache[(1, 2, 3)]) cache.timer.tick() with self.assertRaises(KeyError): cache[(1, 2, 3)] self.assertNotIn((1, 2, 3), cache) def test_ttl_datetime(self): from datetime import datetime, timedelta cache = TTLCache(maxsize=1, ttl=timedelta(days=1), timer=datetime.now) cache[1] = 1 self.assertEqual(1, len(cache)) cache.expire(datetime.now()) self.assertEqual(1, len(cache)) cache.expire(datetime.now() + timedelta(days=1)) self.assertEqual(0, len(cache)) cachetools-5.3.3/tox.ini000066400000000000000000000014671456717112400152010ustar00rootroot00000000000000[tox] envlist = check-manifest,docs,doctest,flake8,py [testenv] deps = pytest pytest-cov commands = py.test --basetemp={envtmpdir} --cov=cachetools {posargs} [testenv:check-manifest] deps = check-manifest==0.44; python_version < "3.8" check-manifest; python_version >= "3.8" commands = check-manifest skip_install = true [testenv:docs] deps = sphinx commands = sphinx-build -W -b html -d {envtmpdir}/doctrees docs {envtmpdir}/html [testenv:doctest] deps = sphinx commands = sphinx-build -W -b doctest -d {envtmpdir}/doctrees docs {envtmpdir}/doctest [testenv:flake8] deps = flake8 flake8-black; implementation_name == "cpython" black==22.12.0; implementation_name == "cpython" flake8-bugbear flake8-import-order commands = flake8 skip_install = true