add alru_cache(), async_= to timed_cache()
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3 changed files with 241 additions and 14 deletions
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@ -8,7 +8,7 @@
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* Automatically handles commit and rollback
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* Automatically handles commit and rollback
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+ `sqlalchemy_async` also offers `async_query()`
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+ `sqlalchemy_async` also offers `async_query()`
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+ Changed `sqlalchemy.parent_children()` to use `lazy='selectin'` by default
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+ Changed `sqlalchemy.parent_children()` to use `lazy='selectin'` by default
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+ Add `timed_cache()`, `TimedDict()`, `none_pass()`, `twocolon_list()`, `quote_css_string()`, `must_be()`
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+ Add `timed_cache()`, `alru_cache()`, `TimedDict()`, `none_pass()`, `twocolon_list()`, `quote_css_string()`, `must_be()`
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+ Add module `calendar` with `want_*` date type conversion utilities and `age_and_days()`
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+ Add module `calendar` with `want_*` date type conversion utilities and `age_and_days()`
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+ Move obsolete stuff to `obsolete` package (includes configparse 0.3 as of now)
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+ Move obsolete stuff to `obsolete` package (includes configparse 0.3 as of now)
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+ Add `redact` module with `redact_url_password()`
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+ Add `redact` module with `redact_url_password()`
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@ -14,11 +14,16 @@ This software is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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"""
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"""
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from collections import namedtuple
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import math
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import math
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from threading import RLock
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import time
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import time
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from typing import Callable, TypeVar
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from types import CoroutineType, NoneType
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from typing import Callable, Iterable, Mapping, TypeVar
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import warnings
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import warnings
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from functools import wraps, lru_cache
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from functools import update_wrapper, wraps, lru_cache
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from suou.itertools import hashed_list
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_T = TypeVar('_T')
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_T = TypeVar('_T')
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_U = TypeVar('_U')
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_U = TypeVar('_U')
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@ -70,26 +75,227 @@ def not_implemented(msg: Callable | str | None = None):
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return decorator
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return decorator
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def timed_cache(ttl: int, maxsize: int = 128, typed: bool = False) -> Callable[[Callable], Callable]:
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def flat_args(args: Iterable, kwds: Mapping, typed,
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kwd_mark = (object(),),
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fasttypes = {int, str, frozenset, NoneType},
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sorted=sorted, tuple=tuple, type=type, len=len):
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'''Turn optionally positional and keyword arguments into a hashable key for use in caches.
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Shamelessly copied from functools._make_key() from the Python Standard Library.
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Never trust underscores, you know.
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This assumes all argument types are hashable!'''
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key = args
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if kwds:
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sorted_items = sorted(kwds.items())
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key += kwd_mark
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for item in sorted_items:
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key += item
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if typed:
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key += tuple(type(v) for v in args)
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if kwds:
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key += tuple(type(v) for k, v in sorted_items)
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elif len(key) == 1 and type(key[0]) in fasttypes:
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return key[0]
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return hashed_list(key)
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def _make_alru_cache(_CacheInfo):
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def alru_cache(maxsize: int = 128, typed: bool = False):
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"""
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Reimplementation of lru_cache(). In fact it's lru_cache() from Python==3.13.7 Standard
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Library with just three lines modified.
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Shamelessly adapted from the Python Standard Library with modifications.
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PSA there is no C speed up. Unlike PSL. Sorry.
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NEW 0.5.0
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"""
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# Users should only access the lru_cache through its public API:
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# cache_info, cache_clear, and f.__wrapped__
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# The internals of the lru_cache are encapsulated for thread safety and
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# to allow the implementation to change (including a possible C version).
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# suou.alru_cache is based on pure-Python functools.lru_cache() as of Python 3.13.7.
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if isinstance(maxsize, int):
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# Negative maxsize is treated as 0
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if maxsize < 0:
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maxsize = 0
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elif callable(maxsize) and isinstance(typed, bool):
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# The user_function was passed in directly via the maxsize argument
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user_function, maxsize = maxsize, 128
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wrapper = _alru_cache_wrapper(user_function, maxsize, typed, _CacheInfo)
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wrapper.cache_parameters = lambda : {'maxsize': maxsize, 'typed': typed}
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return update_wrapper(wrapper, user_function)
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elif maxsize is not None:
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raise TypeError(
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'Expected first argument to be an integer, a callable, or None')
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def decorating_function(user_function: CoroutineType):
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wrapper = _alru_cache_wrapper(user_function, maxsize, typed, _CacheInfo)
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wrapper.cache_parameters = lambda : {'maxsize': maxsize, 'typed': typed}
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return update_wrapper(wrapper, user_function)
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return decorating_function
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def _alru_cache_wrapper(user_function, maxsize, typed):
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# Constants shared by all lru cache instances:
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sentinel = object() # unique object used to signal cache misses
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make_key = flat_args # build a key from the function arguments
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PREV, NEXT, KEY, RESULT = 0, 1, 2, 3 # names for the link fields
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cache = {}
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hits = misses = 0
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full = False
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cache_get = cache.get # bound method to lookup a key or return None
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cache_len = cache.__len__ # get cache size without calling len()
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lock = RLock() # because linkedlist updates aren't threadsafe
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root = [] # root of the circular doubly linked list
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root[:] = [root, root, None, None] # initialize by pointing to self
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if maxsize == 0:
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async def wrapper(*args, **kwds):
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# No caching -- just a statistics update
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nonlocal misses
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misses += 1
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result = await user_function(*args, **kwds)
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return result
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elif maxsize is None:
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async def wrapper(*args, **kwds):
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# Simple caching without ordering or size limit
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nonlocal hits, misses
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key = make_key(args, kwds, typed)
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result = cache_get(key, sentinel)
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if result is not sentinel:
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hits += 1
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return result
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misses += 1
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result = await user_function(*args, **kwds)
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cache[key] = result
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return result
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else:
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async def wrapper(*args, **kwds):
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# Size limited caching that tracks accesses by recency
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nonlocal root, hits, misses, full
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key = make_key(args, kwds, typed)
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with lock:
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link = cache_get(key)
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if link is not None:
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# Move the link to the front of the circular queue
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link_prev, link_next, _key, result = link
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link_prev[NEXT] = link_next
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link_next[PREV] = link_prev
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last = root[PREV]
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last[NEXT] = root[PREV] = link
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link[PREV] = last
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link[NEXT] = root
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hits += 1
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return result
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misses += 1
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result = await user_function(*args, **kwds)
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with lock:
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if key in cache:
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# Getting here means that this same key was added to the
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# cache while the lock was released. Since the link
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# update is already done, we need only return the
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# computed result and update the count of misses.
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pass
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elif full:
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# Use the old root to store the new key and result.
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oldroot = root
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oldroot[KEY] = key
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oldroot[RESULT] = result
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# Empty the oldest link and make it the new root.
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# Keep a reference to the old key and old result to
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# prevent their ref counts from going to zero during the
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# update. That will prevent potentially arbitrary object
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# clean-up code (i.e. __del__) from running while we're
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# still adjusting the links.
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root = oldroot[NEXT]
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oldkey = root[KEY]
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oldresult = root[RESULT]
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root[KEY] = root[RESULT] = None
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# Now update the cache dictionary.
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del cache[oldkey]
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# Save the potentially reentrant cache[key] assignment
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# for last, after the root and links have been put in
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# a consistent state.
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cache[key] = oldroot
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else:
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# Put result in a new link at the front of the queue.
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last = root[PREV]
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link = [last, root, key, result]
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last[NEXT] = root[PREV] = cache[key] = link
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# Use the cache_len bound method instead of the len() function
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# which could potentially be wrapped in an lru_cache itself.
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full = (cache_len() >= maxsize)
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return result
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def cache_info():
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"""Report cache statistics"""
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with lock:
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return _CacheInfo(hits, misses, maxsize, cache_len())
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def cache_clear():
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"""Clear the cache and cache statistics"""
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nonlocal hits, misses, full
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with lock:
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cache.clear()
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root[:] = [root, root, None, None]
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hits = misses = 0
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full = False
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wrapper.cache_info = cache_info
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wrapper.cache_clear = cache_clear
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return wrapper
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return alru_cache
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alru_cache = _make_alru_cache(namedtuple("CacheInfo", ["hits", "misses", "maxsize", "currsize"]))
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del _make_alru_cache
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def timed_cache(ttl: int, maxsize: int = 128, typed: bool = False, *, async_: bool = False) -> Callable[[Callable], Callable]:
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"""
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"""
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LRU cache which expires after the TTL in seconds passed as argument.
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LRU cache which expires after the TTL in seconds passed as argument.
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Supports coroutines with async_=True.
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NEW 0.5.0
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NEW 0.5.0
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"""
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"""
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def decorator(func):
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def decorator(func):
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start_time = None
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start_time = None
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@lru_cache(maxsize, typed)
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if async_:
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def inner_wrapper(ttl_period: int, *a, **k):
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@alru_cache(maxsize, typed)
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return func(*a, **k)
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async def inner_wrapper(ttl_period: int, /, *a, **k):
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return await func(*a, **k)
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@wraps(func)
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@wraps(func)
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def wrapper(*a, **k):
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async def wrapper(*a, **k):
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nonlocal start_time
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nonlocal start_time
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if not start_time:
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if not start_time:
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start_time = int(time.time())
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start_time = int(time.time())
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return inner_wrapper(math.floor((time.time() - start_time) // ttl), *a, **k)
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return await inner_wrapper(math.floor((time.time() - start_time) // ttl), *a, **k)
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return wrapper
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return wrapper
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else:
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@lru_cache(maxsize, typed)
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def inner_wrapper(ttl_period: int, /, *a, **k):
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return func(*a, **k)
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@wraps(func)
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def wrapper(*a, **k):
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nonlocal start_time
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if not start_time:
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start_time = int(time.time())
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return inner_wrapper(math.floor((time.time() - start_time) // ttl), *a, **k)
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return wrapper
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return decorator
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return decorator
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def none_pass(func: Callable, *args, **kwargs) -> Callable:
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def none_pass(func: Callable, *args, **kwargs) -> Callable:
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@ -103,6 +103,27 @@ def addattr(obj: Any, /, name: str = None):
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return func
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return func
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return decorator
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return decorator
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class hashed_list(list):
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"""
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Used by lru_cache() functions.
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This class guarantees that hash() will be called no more than once
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per element. This is important because the lru_cache() will hash
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the key multiple times on a cache miss.
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Shamelessly copied from functools._HashedSeq() from the Python Standard Library.
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Never trust underscores, you know.
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"""
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__slots__ = 'hashvalue'
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def __init__(self, tup, hash=hash):
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self[:] = tup
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self.hashvalue = hash(tup)
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def __hash__(self):
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return self.hashvalue
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__all__ = ('makelist', 'kwargs_prefix', 'ltuple', 'rtuple', 'additem', 'addattr')
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__all__ = ('makelist', 'kwargs_prefix', 'ltuple', 'rtuple', 'additem', 'addattr')
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