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from __future__ import absolute_import, division, print_function
from functools import wraps
__all__ = ['memoize', 'singleton', 'memoize_attr_check']
def _make_key(args, kwargs):
return args, frozenset(kwargs.items())
def memoize(func):
"""Save results of function calls to avoid repeated calculation"""
memo = {}
@wraps(func)
def wrapper(*args, **kwargs):
# Note that here we have two separate try...except statements, because
# we want to make sure that we catch only TypeError on the first
# statement, and both TypeError and KeyError on the second.
try:
key = _make_key(args, kwargs)
except TypeError: # unhashable input
return func(*args, **kwargs)
try:
return memo[key]
except KeyError:
result = func(*args, **kwargs)
memo[key] = result
return result
except TypeError: # unhashable input
return func(*args, **kwargs)
wrapper.__memoize_cache = memo
return wrapper
def clear_cache(func):
"""
Clear the cache of a function that has potentially been
decorated by memoize. Safely ignores non-decorated functions
"""
try:
func.__memoize_cache.clear()
except AttributeError:
pass
def memoize_attr_check(attr):
""" Memoize a method call, cached both on arguments and given attribute
of first argument (which is presumably self)
Has the effect of re-calculating results if a specific attribute changes
"""
def decorator(func):
# must return a decorator function
@wraps(func)
def result(*args, **kwargs):
first_arg = getattr(args[0], attr)
return memo(first_arg, *args, **kwargs)
@memoize
def memo(*args, **kwargs):
return func(*args[1:], **kwargs)
return result
return decorator
def singleton(cls):
"""Turn a class into a singleton, such that new objects
in this class share the same instance"""
instances = {}
@wraps(cls)
def getinstance():
if cls not in instances:
instances[cls] = cls()
return instances[cls]
return getinstance
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