"""functools.py - Tools for working with functions and callable objects """ # Python module wrapper for _functools C module # to allow utilities written in Python to be added # to the functools module. # Written by Nick Coghlan # and Raymond Hettinger # Copyright (C) 2006-2010 Python Software Foundation. # See C source code for _functools credits/copyright __all__ = ['update_wrapper', 'wraps', 'WRAPPER_ASSIGNMENTS', 'WRAPPER_UPDATES', 'total_ordering', 'cmp_to_key', 'lru_cache', 'reduce', 'partial'] from _functools import partial, reduce from collections import namedtuple try: from _thread import allocate_lock as Lock except: from _dummy_thread import allocate_lock as Lock ################################################################################ ### update_wrapper() and wraps() decorator ################################################################################ # update_wrapper() and wraps() are tools to help write # wrapper functions that can handle naive introspection WRAPPER_ASSIGNMENTS = ('__module__', '__name__', '__qualname__', '__doc__', '__annotations__') WRAPPER_UPDATES = ('__dict__',) def update_wrapper(wrapper, wrapped, assigned = WRAPPER_ASSIGNMENTS, updated = WRAPPER_UPDATES): """Update a wrapper function to look like the wrapped function wrapper is the function to be updated wrapped is the original function assigned is a tuple naming the attributes assigned directly from the wrapped function to the wrapper function (defaults to functools.WRAPPER_ASSIGNMENTS) updated is a tuple naming the attributes of the wrapper that are updated with the corresponding attribute from the wrapped function (defaults to functools.WRAPPER_UPDATES) """ wrapper.__wrapped__ = wrapped for attr in assigned: try: value = getattr(wrapped, attr) except AttributeError: pass else: setattr(wrapper, attr, value) for attr in updated: getattr(wrapper, attr).update(getattr(wrapped, attr, {})) # Return the wrapper so this can be used as a decorator via partial() return wrapper def wraps(wrapped, assigned = WRAPPER_ASSIGNMENTS, updated = WRAPPER_UPDATES): """Decorator factory to apply update_wrapper() to a wrapper function Returns a decorator that invokes update_wrapper() with the decorated function as the wrapper argument and the arguments to wraps() as the remaining arguments. Default arguments are as for update_wrapper(). This is a convenience function to simplify applying partial() to update_wrapper(). """ return partial(update_wrapper, wrapped=wrapped, assigned=assigned, updated=updated) ################################################################################ ### total_ordering class decorator ################################################################################ def total_ordering(cls): """Class decorator that fills in missing ordering methods""" convert = { '__lt__': [('__gt__', lambda self, other: not (self < other or self == other)), ('__le__', lambda self, other: self < other or self == other), ('__ge__', lambda self, other: not self < other)], '__le__': [('__ge__', lambda self, other: not self <= other or self == other), ('__lt__', lambda self, other: self <= other and not self == other), ('__gt__', lambda self, other: not self <= other)], '__gt__': [('__lt__', lambda self, other: not (self > other or self == other)), ('__ge__', lambda self, other: self > other or self == other), ('__le__', lambda self, other: not self > other)], '__ge__': [('__le__', lambda self, other: (not self >= other) or self == other), ('__gt__', lambda self, other: self >= other and not self == other), ('__lt__', lambda self, other: not self >= other)] } # Find user-defined comparisons (not those inherited from object). roots = [op for op in convert if getattr(cls, op, None) is not getattr(object, op, None)] if not roots: raise ValueError('must define at least one ordering operation: < > <= >=') root = max(roots) # prefer __lt__ to __le__ to __gt__ to __ge__ for opname, opfunc in convert[root]: if opname not in roots: opfunc.__name__ = opname opfunc.__doc__ = getattr(int, opname).__doc__ setattr(cls, opname, opfunc) return cls ################################################################################ ### cmp_to_key() function converter ################################################################################ def cmp_to_key(mycmp): """Convert a cmp= function into a key= function""" class K(object): __slots__ = ['obj'] def __init__(self, obj): self.obj = obj def __lt__(self, other): return mycmp(self.obj, other.obj) < 0 def __gt__(self, other): return mycmp(self.obj, other.obj) > 0 def __eq__(self, other): return mycmp(self.obj, other.obj) == 0 def __le__(self, other): return mycmp(self.obj, other.obj) <= 0 def __ge__(self, other): return mycmp(self.obj, other.obj) >= 0 def __ne__(self, other): return mycmp(self.obj, other.obj) != 0 __hash__ = None return K try: from _functools import cmp_to_key except ImportError: pass ################################################################################ ### LRU Cache function decorator ################################################################################ _CacheInfo = namedtuple("CacheInfo", ["hits", "misses", "maxsize", "currsize"]) def lru_cache(maxsize=100, typed=False): """Least-recently-used cache decorator. If *maxsize* is set to None, the LRU features are disabled and the cache can grow without bound. If *typed* is True, arguments of different types will be cached separately. For example, f(3.0) and f(3) will be treated as distinct calls with distinct results. Arguments to the cached function must be hashable. View the cache statistics named tuple (hits, misses, maxsize, currsize) with f.cache_info(). Clear the cache and statistics with f.cache_clear(). Access the underlying function with f.__wrapped__. See: http://en.wikipedia.org/wiki/Cache_algorithms#Least_Recently_Used """ # Users should only access the lru_cache through its public API: # cache_info, cache_clear, and f.__wrapped__ # The internals of the lru_cache are encapsulated for thread safety and # to allow the implementation to change (including a possible C version). def decorating_function(user_function): cache = dict() hits = misses = 0 kwd_mark = (object(),) # separate positional and keyword args cache_get = cache.get # bound method to lookup key or return None _len = len # localize the global len() function lock = Lock() # because linkedlist updates aren't threadsafe root = [] # root of the circular doubly linked list root[:] = [root, root, None, None] # initialize by pointing to self PREV, NEXT, KEY, RESULT = 0, 1, 2, 3 # names for the link fields def make_key(args, kwds, typed, tuple=tuple, sorted=sorted, type=type): # helper function to build a cache key from positional and keyword args key = args if kwds: sorted_items = tuple(sorted(kwds.items())) key += kwd_mark + sorted_items if typed: key += tuple(type(v) for v in args) if kwds: key += tuple(type(v) for k, v in sorted_items) return key if maxsize == 0: @wraps(user_function) def wrapper(*args, **kwds): # no caching, just do a statistics update after a successful call nonlocal misses result = user_function(*args, **kwds) misses += 1 return result elif maxsize is None: @wraps(user_function) def wrapper(*args, **kwds): # simple caching without ordering or size limit nonlocal hits, misses key = make_key(args, kwds, typed) if kwds or typed else args result = cache_get(key, root) # root used here as a unique not-found sentinel if result is not root: hits += 1 return result result = user_function(*args, **kwds) cache[key] = result misses += 1 return result else: @wraps(user_function) def wrapper(*args, **kwds): # size limited caching that tracks accesses by recency nonlocal hits, misses key = make_key(args, kwds, typed) if kwds or typed else args with lock: link = cache_get(key) if link is not None: # record recent use of the key by moving it to the front of the list link_prev, link_next, key, result = link link_prev[NEXT] = link_next link_next[PREV] = link_prev last = root[PREV] last[NEXT] = root[PREV] = link link[PREV] = last link[NEXT] = root hits += 1 return result result = user_function(*args, **kwds) with lock: last = root[PREV] link = [last, root, key, result] cache[key] = last[NEXT] = root[PREV] = link if _len(cache) > maxsize: # purge least recently used cache entry old_prev, old_next, old_key, old_result = root[NEXT] root[NEXT] = old_next old_next[PREV] = root del cache[old_key] misses += 1 return result def cache_info(): """Report cache statistics""" with lock: return _CacheInfo(hits, misses, maxsize, len(cache)) def cache_clear(): """Clear the cache and cache statistics""" nonlocal hits, misses with lock: cache.clear() root[:] = [root, root, None, None] hits = misses = 0 wrapper.cache_info = cache_info wrapper.cache_clear = cache_clear return wrapper return decorating_function