chore: 添加虚拟环境到仓库

- 添加 backend_service/venv 虚拟环境
- 包含所有Python依赖包
- 注意:虚拟环境约393MB,包含12655个文件
This commit is contained in:
2025-12-03 10:19:25 +08:00
parent a6c2027caa
commit c4f851d387
12655 changed files with 3009376 additions and 0 deletions

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"""Extensible memoizing collections and decorators."""
__all__ = (
"Cache",
"FIFOCache",
"LFUCache",
"LRUCache",
"RRCache",
"TLRUCache",
"TTLCache",
"cached",
"cachedmethod",
)
__version__ = "6.2.2"
import collections
import collections.abc
import functools
import heapq
import random
import time
from . import keys
class _DefaultSize:
__slots__ = ()
def __getitem__(self, _key):
return 1
def __setitem__(self, _key, _value):
pass
def pop(self, _key):
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)" % (
type(self).__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)
# Note that we cannot simply inherit get(), pop() and setdefault()
# from MutableMapping, since these rely on __getitem__ throwing a
# KeyError on cache miss. This is not the case if __missing__ is
# implemented for a Cache subclass, so we have to roll our own,
# somewhat less elegant versions.
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."""
class _Link:
__slots__ = ("count", "keys", "next", "prev")
def __init__(self, count):
self.count = count
self.keys = set()
def unlink(self):
next = self.next
prev = self.prev
prev.next = next
next.prev = prev
def __init__(self, maxsize, getsizeof=None):
Cache.__init__(self, maxsize, getsizeof)
self.__root = root = LFUCache._Link(0) # sentinel
root.prev = root.next = root
self.__links = {}
def __getitem__(self, key, cache_getitem=Cache.__getitem__):
value = cache_getitem(self, key)
if key in self: # __missing__ may not store item
self.__touch(key)
return value
def __setitem__(self, key, value, cache_setitem=Cache.__setitem__):
cache_setitem(self, key, value)
if key in self.__links:
return self.__touch(key)
root = self.__root
link = root.next
if link.count != 1:
link = LFUCache._Link(1)
link.next = root.next
root.next = link.next.prev = link
link.prev = root
link.keys.add(key)
self.__links[key] = link
def __delitem__(self, key, cache_delitem=Cache.__delitem__):
cache_delitem(self, key)
link = self.__links.pop(key)
link.keys.remove(key)
if not link.keys:
link.unlink()
def popitem(self):
"""Remove and return the `(key, value)` pair least frequently used."""
root = self.__root
curr = root.next
if curr is root:
raise KeyError("%s is empty" % type(self).__name__) from None
key = next(iter(curr.keys)) # remove an arbitrary element
return (key, self.pop(key))
def __touch(self, key):
"""Increment use count"""
link = self.__links[key]
curr = link.next
if curr.count != link.count + 1:
if len(link.keys) == 1:
link.count += 1
return
curr = LFUCache._Link(link.count + 1)
curr.next = link.next
link.next = curr.next.prev = curr
curr.prev = link
curr.keys.add(key)
link.keys.remove(key)
if not link.keys:
link.unlink()
self.__links[key] = curr
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.__touch(key)
return value
def __setitem__(self, key, value, cache_setitem=Cache.__setitem__):
cache_setitem(self, key, value)
self.__touch(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 __touch(self, key):
"""Mark as recently used"""
try:
self.__order.move_to_end(key)
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
self.__index = {}
self.__keys = []
@property
def choice(self):
"""The `choice` function used by the cache."""
return self.__choice
def __setitem__(self, key, value, cache_setitem=Cache.__setitem__):
cache_setitem(self, key, value)
if key not in self.__index:
self.__index[key] = len(self.__keys)
self.__keys.append(key)
def __delitem__(self, key, cache_delitem=Cache.__delitem__):
cache_delitem(self, key)
index = self.__index.pop(key)
if index != len(self.__keys) - 1:
last = self.__keys[-1]
self.__keys[index] = last
self.__index[last] = index
self.__keys.pop()
def popitem(self):
"""Remove and return a random `(key, value)` pair."""
try:
key = self.__choice(self.__keys)
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 and return an iterable of the
expired `(key, value)` pairs.
"""
if time is None:
time = self.timer()
root = self.__root
curr = root.next
links = self.__links
expired = []
cache_delitem = Cache.__delitem__
cache_getitem = Cache.__getitem__
while curr is not root and not (time < curr.expires):
expired.append((curr.key, cache_getitem(self, curr.key)))
cache_delitem(self, curr.key)
del links[curr.key]
next = curr.next
curr.unlink()
curr = next
return expired
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 and return an iterable of the
expired `(key, value)` pairs.
"""
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)
expired = []
cache_delitem = Cache.__delitem__
cache_getitem = Cache.__getitem__
while order and (order[0].removed or not (time < order[0].expires)):
item = heapq.heappop(order)
if not item.removed:
expired.append((item.key, cache_getitem(self, item.key)))
cache_delitem(self, item.key)
del items[item.key]
return expired
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" % type(self).__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, condition=None, info=False):
"""Decorator to wrap a function with a memoizing callable that saves
results in a cache.
"""
from ._cached import _wrapper
if isinstance(condition, bool):
from warnings import warn
warn(
"passing `info` as positional parameter is deprecated",
DeprecationWarning,
stacklevel=2,
)
info = condition
condition = None
def decorator(func):
if info:
if isinstance(cache, Cache):
def make_info(hits, misses):
return _CacheInfo(hits, misses, cache.maxsize, cache.currsize)
elif isinstance(cache, collections.abc.Mapping):
def make_info(hits, misses):
return _CacheInfo(hits, misses, None, len(cache))
else:
def make_info(hits, misses):
return _CacheInfo(hits, misses, 0, 0)
return _wrapper(func, cache, key, lock, condition, info=make_info)
else:
return _wrapper(func, cache, key, lock, condition)
return decorator
def cachedmethod(cache, key=keys.methodkey, lock=None, condition=None):
"""Decorator to wrap a class or instance method with a memoizing
callable that saves results in a cache.
"""
from ._cachedmethod import _wrapper
def decorator(method):
return _wrapper(method, cache, key, lock, condition)
return decorator

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"""Function decorator helpers."""
import functools
def _condition_info(func, cache, key, lock, cond, info):
hits = misses = 0
pending = set()
def wrapper(*args, **kwargs):
nonlocal hits, misses
k = key(*args, **kwargs)
with lock:
cond.wait_for(lambda: k not in pending)
try:
result = cache[k]
hits += 1
return result
except KeyError:
pending.add(k)
misses += 1
try:
v = func(*args, **kwargs)
with lock:
try:
cache[k] = v
except ValueError:
pass # value too large
return v
finally:
with lock:
pending.remove(k)
cond.notify_all()
def cache_clear():
nonlocal hits, misses
with lock:
cache.clear()
hits = misses = 0
def cache_info():
with lock:
return info(hits, misses)
wrapper.cache_clear = cache_clear
wrapper.cache_info = cache_info
return wrapper
def _locked_info(func, cache, key, lock, info):
hits = misses = 0
def wrapper(*args, **kwargs):
nonlocal hits, misses
k = key(*args, **kwargs)
with lock:
try:
result = cache[k]
hits += 1
return result
except KeyError:
misses += 1
v = func(*args, **kwargs)
with lock:
try:
# In case of a race condition, i.e. if another thread
# stored a value for this key while we were calling
# func(), prefer the cached value.
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 info(hits, misses)
wrapper.cache_clear = cache_clear
wrapper.cache_info = cache_info
return wrapper
def _unlocked_info(func, cache, key, info):
hits = misses = 0
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
wrapper.cache_clear = cache_clear
wrapper.cache_info = lambda: info(hits, misses)
return wrapper
def _uncached_info(func, info):
misses = 0
def wrapper(*args, **kwargs):
nonlocal misses
misses += 1
return func(*args, **kwargs)
def cache_clear():
nonlocal misses
misses = 0
wrapper.cache_clear = cache_clear
wrapper.cache_info = lambda: info(0, misses)
return wrapper
def _condition(func, cache, key, lock, cond):
pending = set()
def wrapper(*args, **kwargs):
k = key(*args, **kwargs)
with lock:
cond.wait_for(lambda: k not in pending)
try:
result = cache[k]
return result
except KeyError:
pending.add(k)
try:
v = func(*args, **kwargs)
with lock:
try:
cache[k] = v
except ValueError:
pass # value too large
return v
finally:
with lock:
pending.remove(k)
cond.notify_all()
def cache_clear():
with lock:
cache.clear()
wrapper.cache_clear = cache_clear
return wrapper
def _locked(func, cache, key, lock):
def wrapper(*args, **kwargs):
k = key(*args, **kwargs)
with lock:
try:
return cache[k]
except KeyError:
pass # key not found
v = func(*args, **kwargs)
with lock:
try:
# possible race condition: see above
return cache.setdefault(k, v)
except ValueError:
return v # value too large
def cache_clear():
with lock:
cache.clear()
wrapper.cache_clear = cache_clear
return wrapper
def _unlocked(func, cache, key):
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
wrapper.cache_clear = lambda: cache.clear()
return wrapper
def _uncached(func):
def wrapper(*args, **kwargs):
return func(*args, **kwargs)
wrapper.cache_clear = lambda: None
return wrapper
def _wrapper(func, cache, key, lock=None, cond=None, info=None):
if info is not None:
if cache is None:
wrapper = _uncached_info(func, info)
elif cond is not None and lock is not None:
wrapper = _condition_info(func, cache, key, lock, cond, info)
elif cond is not None:
wrapper = _condition_info(func, cache, key, cond, cond, info)
elif lock is not None:
wrapper = _locked_info(func, cache, key, lock, info)
else:
wrapper = _unlocked_info(func, cache, key, info)
else:
if cache is None:
wrapper = _uncached(func)
elif cond is not None and lock is not None:
wrapper = _condition(func, cache, key, lock, cond)
elif cond is not None:
wrapper = _condition(func, cache, key, cond, cond)
elif lock is not None:
wrapper = _locked(func, cache, key, lock)
else:
wrapper = _unlocked(func, cache, key)
wrapper.cache_info = None
wrapper.cache = cache
wrapper.cache_key = key
wrapper.cache_lock = lock if lock is not None else cond
wrapper.cache_condition = cond
return functools.update_wrapper(wrapper, func)

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"""Method decorator helpers."""
import functools
import weakref
def warn_cache_none():
from warnings import warn
warn(
"returning `None` from `cache(self)` is deprecated",
DeprecationWarning,
stacklevel=3,
)
def _condition(method, cache, key, lock, cond):
pending = weakref.WeakKeyDictionary()
def wrapper(self, *args, **kwargs):
c = cache(self)
if c is None:
warn_cache_none()
return method(self, *args, **kwargs)
k = key(self, *args, **kwargs)
with lock(self):
p = pending.setdefault(self, set())
cond(self).wait_for(lambda: k not in p)
try:
return c[k]
except KeyError:
p.add(k)
try:
v = method(self, *args, **kwargs)
with lock(self):
try:
c[k] = v
except ValueError:
pass # value too large
return v
finally:
with lock(self):
pending[self].remove(k)
cond(self).notify_all()
def cache_clear(self):
c = cache(self)
if c is not None:
with lock(self):
c.clear()
wrapper.cache_clear = cache_clear
return wrapper
def _locked(method, cache, key, lock):
def wrapper(self, *args, **kwargs):
c = cache(self)
if c is None:
warn_cache_none()
return method(self, *args, **kwargs)
k = key(self, *args, **kwargs)
with lock(self):
try:
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
with lock(self):
try:
return c.setdefault(k, v)
except ValueError:
return v # value too large
def cache_clear(self):
c = cache(self)
if c is not None:
with lock(self):
c.clear()
wrapper.cache_clear = cache_clear
return wrapper
def _unlocked(method, cache, key):
def wrapper(self, *args, **kwargs):
c = cache(self)
if c is None:
warn_cache_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 cache_clear(self):
c = cache(self)
if c is not None:
c.clear()
wrapper.cache_clear = cache_clear
return wrapper
def _wrapper(method, cache, key, lock=None, cond=None):
if cond is not None and lock is not None:
wrapper = _condition(method, cache, key, lock, cond)
elif cond is not None:
wrapper = _condition(method, cache, key, cond, cond)
elif lock is not None:
wrapper = _locked(method, cache, key, lock)
else:
wrapper = _unlocked(method, cache, key)
wrapper.cache = cache
wrapper.cache_key = key
wrapper.cache_lock = lock if lock is not None else cond
wrapper.cache_condition = cond
return functools.update_wrapper(wrapper, method)

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"""`functools.lru_cache` compatible memoizing function decorators."""
__all__ = ("fifo_cache", "lfu_cache", "lru_cache", "rr_cache", "ttl_cache")
import functools
import math
import random
import time
from threading import Condition
from . import FIFOCache, LFUCache, LRUCache, 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, condition=Condition(), 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 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)

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"""Key functions for memoizing decorators."""
__all__ = ("hashkey", "methodkey", "typedkey", "typedmethodkey")
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 {}
# A sentinel for separating args from kwargs. Using the class itself
# ensures uniqueness and preserves identity 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
def typedmethodkey(self, *args, **kwargs):
"""Return a typed cache key for use with cached methods."""
return typedkey(*args, **kwargs)