summaryrefslogtreecommitdiffstats
path: root/Lib/functools.py
blob: 0fbf3cd3706b0c97b249f47d5c0905c818b5ce9e (plain)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
"""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 <ncoghlan at gmail.com>
# and Raymond Hettinger <python at rcn.com>
#   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 OrderedDict, namedtuple
try:
    from _thread import allocate_lock as Lock
except:
    from _dummy_thread import allocate_lock as Lock

# update_wrapper() and wraps() are tools to help write
# wrapper functions that can handle naive introspection

WRAPPER_ASSIGNMENTS = ('__module__', '__name__', '__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)

def total_ordering(cls):
    """Class decorator that fills in missing ordering methods"""
    convert = {
        '__lt__': [('__gt__', lambda self, other: other < self),
                   ('__le__', lambda self, other: not other < self),
                   ('__ge__', lambda self, other: not self < other)],
        '__le__': [('__ge__', lambda self, other: other <= self),
                   ('__lt__', lambda self, other: not other <= self),
                   ('__gt__', lambda self, other: not self <= other)],
        '__gt__': [('__lt__', lambda self, other: other > self),
                   ('__ge__', lambda self, other: not other > self),
                   ('__le__', lambda self, other: not self > other)],
        '__ge__': [('__le__', lambda self, other: other >= self),
                   ('__gt__', lambda self, other: not other >= self),
                   ('__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

def cmp_to_key(mycmp):
    """Convert a cmp= function into a key= function"""
    class K(object):
        def __init__(self, obj, *args):
            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
        def __hash__(self):
            raise TypeError('hash not implemented')
    return K

_CacheInfo = namedtuple("CacheInfo", "hits misses maxsize currsize")

def lru_cache(maxsize=100):
    """Least-recently-used cache decorator.

    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,
                tuple=tuple, sorted=sorted, len=len, KeyError=KeyError):

        cache = OrderedDict()           # ordered least recent to most recent
        cache_popitem = cache.popitem
        cache_renew = cache.move_to_end
        hits = misses = 0
        kwd_mark = object()             # separates positional and keyword args
        lock = Lock()

        @wraps(user_function)
        def wrapper(*args, **kwds):
            nonlocal hits, misses
            key = args
            if kwds:
                key += (kwd_mark,) + tuple(sorted(kwds.items()))
            try:
                with lock:
                    result = cache[key]
                    cache_renew(key)            # record recent use of this key
                    hits += 1
            except KeyError:
                result = user_function(*args, **kwds)
                with lock:
                    cache[key] = result         # record recent use of this key
                    misses += 1
                    if len(cache) > maxsize:
                        cache_popitem(0)        # purge least recently used cache entry
            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()
                hits = misses = 0

        wrapper.cache_info = cache_info
        wrapper.cache_clear = cache_clear
        return wrapper

    return decorating_function