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124 lines
4.3 KiB
124 lines
4.3 KiB
Metadata-Version: 2.1
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Name: cachetools
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Version: 4.1.1
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Summary: Extensible memoizing collections and decorators
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Home-page: https://github.com/tkem/cachetools/
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Author: Thomas Kemmer
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Author-email: tkemmer@computer.org
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License: MIT
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Platform: UNKNOWN
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Classifier: Development Status :: 5 - Production/Stable
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Classifier: Environment :: Other Environment
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Classifier: Intended Audience :: Developers
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Classifier: License :: OSI Approved :: MIT License
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Classifier: Operating System :: OS Independent
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Classifier: Programming Language :: Python
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Classifier: Programming Language :: Python :: 3
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Classifier: Programming Language :: Python :: 3.5
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Classifier: Programming Language :: Python :: 3.6
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Classifier: Programming Language :: Python :: 3.7
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Classifier: Programming Language :: Python :: 3.8
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Classifier: Topic :: Software Development :: Libraries :: Python Modules
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Requires-Python: ~=3.5
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cachetools
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========================================================================
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.. image:: http://img.shields.io/pypi/v/cachetools
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:target: https://pypi.org/project/cachetools/
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:alt: Latest PyPI version
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.. image:: https://img.shields.io/readthedocs/cachetools
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:target: http://cachetools.readthedocs.io/
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:alt: Documentation build status
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.. image:: http://img.shields.io/travis/tkem/cachetools
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:target: https://travis-ci.org/tkem/cachetools/
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:alt: Travis CI build status
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.. image:: http://img.shields.io/coveralls/tkem/cachetools
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:target: https://coveralls.io/r/tkem/cachetools
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:alt: Test coverage
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.. image:: https://img.shields.io/github/license/tkem/cachetools
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:target: http://raw.github.com/tkem/cachetools/master/LICENSE
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:alt: License
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This module provides various memoizing collections and decorators,
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including variants of the Python Standard Library's `@lru_cache`_
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function decorator.
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.. code-block:: python
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from cachetools import cached, LRUCache, TTLCache
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# speed up calculating Fibonacci numbers with dynamic programming
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@cached(cache={})
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def fib(n):
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return n if n < 2 else fib(n - 1) + fib(n - 2)
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# cache least recently used Python Enhancement Proposals
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@cached(cache=LRUCache(maxsize=32))
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def get_pep(num):
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url = 'http://www.python.org/dev/peps/pep-%04d/' % num
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with urllib.request.urlopen(url) as s:
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return s.read()
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# cache weather data for no longer than ten minutes
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@cached(cache=TTLCache(maxsize=1024, ttl=600))
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def get_weather(place):
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return owm.weather_at_place(place).get_weather()
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For the purpose of this module, a *cache* is a mutable_ mapping_ of a
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fixed maximum size. When the cache is full, i.e. by adding another
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item the cache would exceed its maximum size, the cache must choose
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which item(s) to discard based on a suitable `cache algorithm`_. In
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general, a cache's size is the total size of its items, and an item's
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size is a property or function of its value, e.g. the result of
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``sys.getsizeof(value)``. For the trivial but common case that each
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item counts as ``1``, a cache's size is equal to the number of its
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items, or ``len(cache)``.
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Multiple cache classes based on different caching algorithms are
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implemented, and decorators for easily memoizing function and method
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calls are provided, too.
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Installation
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------------------------------------------------------------------------
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cachetools is available from PyPI_ and can be installed by running::
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pip install cachetools
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Project Resources
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------------------------------------------------------------------------
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- `Documentation`_
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- `Issue tracker`_
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- `Source code`_
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- `Change log`_
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License
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------------------------------------------------------------------------
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Copyright (c) 2014-2020 Thomas Kemmer.
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Licensed under the `MIT License`_.
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.. _@lru_cache: http://docs.python.org/3/library/functools.html#functools.lru_cache
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.. _mutable: http://docs.python.org/dev/glossary.html#term-mutable
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.. _mapping: http://docs.python.org/dev/glossary.html#term-mapping
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.. _cache algorithm: http://en.wikipedia.org/wiki/Cache_algorithms
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.. _PyPI: https://pypi.org/project/cachetools/
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.. _Documentation: https://cachetools.readthedocs.io/
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.. _Issue tracker: https://github.com/tkem/cachetools/issues/
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.. _Source code: https://github.com/tkem/cachetools/
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.. _Change log: https://github.com/tkem/cachetools/blob/master/CHANGELOG.rst
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.. _MIT License: http://raw.github.com/tkem/cachetools/master/LICENSE
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