mirror of https://github.com/mahmoud/boltons.git
55 lines
1.8 KiB
ReStructuredText
55 lines
1.8 KiB
ReStructuredText
``cacheutils`` - Caches and caching
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===================================
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.. automodule:: boltons.cacheutils
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Least-Recently Inserted (LRI)
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-----------------------------
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The :class:`LRI` is the simpler cache, implementing a very simple first-in,
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first-out (FIFO) approach to cache eviction. If the use case calls for
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simple, very-low overhead caching, such as somewhat expensive local
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operations (e.g., string operations), then the LRI is likely the right
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choice.
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.. autoclass:: boltons.cacheutils.LRI
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:members:
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Least-Recently Used (LRU)
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-------------------------
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The :class:`LRU` is the more advanced cache, but it's still quite
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simple. When it reaches capacity, a new insertion replaces the
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least-recently used item. This strategy makes the LRU a more effective
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cache than the LRI for a wide variety of applications, but also
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entails more operations for all of its APIs, especially reads. Unlike
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the :class:`LRI`, the LRU has threadsafety built in.
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.. autoclass:: boltons.cacheutils.LRU
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:members:
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Automatic function caching
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--------------------------
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Continuing in the theme of cache tunability and experimentation,
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``cacheutils`` also offers a pluggable way to cache function return
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values: the :func:`cached` function decorator and the
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:func:`cachedmethod` method decorator.
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.. autofunction:: boltons.cacheutils.cached
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.. autofunction:: boltons.cacheutils.cachedmethod
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Similar functionality can be found in Python 3.4's
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:func:`functools.lru_cache` decorator, but the functools approach does
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not support the same cache strategy modification, nor does it support
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sharing the cache object across multiple functions.
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.. autofunction:: boltons.cacheutils.cachedproperty
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Threshold-bounded Counting
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--------------------------
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.. autoclass:: boltons.cacheutils.ThresholdCounter
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:members:
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