mitogen/mitogen/compat/functools.py

# encoding: utf-8
"""Selected backports from Python stdlib functools module
"""
# Written by Nick Coghlan <ncoghlan at gmail.com>,
# Raymond Hettinger <python at rcn.com>,
# and Łukasz Langa <lukasz at langa.pl>.
#   Copyright (C) 2006-2013 Python Software Foundation.

__all__ = [
    'update_wrapper', 'wraps', 'WRAPPER_ASSIGNMENTS', 'WRAPPER_UPDATES',
    'lru_cache',
]

from threading import RLock


################################################################################
### 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)
    """
    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, {}))
    # Issue #17482: set __wrapped__ last so we don't inadvertently copy it
    # from the wrapped function when updating __dict__
    wrapper.__wrapped__ = wrapped
    # 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)


################################################################################
### partial() argument application
################################################################################

# Purely functional, no descriptor behaviour
def partial(func, *args, **keywords):
    """New function with partial application of the given arguments
    and keywords.
    """
    if hasattr(func, 'func'):
        args = func.args + args
        tmpkw = func.keywords.copy()
        tmpkw.update(keywords)
        keywords = tmpkw
        del tmpkw
        func = func.func

    def newfunc(*fargs, **fkeywords):
        newkeywords = keywords.copy()
        newkeywords.update(fkeywords)
        return func(*(args + fargs), **newkeywords)
    newfunc.func = func
    newfunc.args = args
    newfunc.keywords = keywords
    return newfunc


################################################################################
### LRU Cache function decorator
################################################################################

class _HashedSeq(list):
    """ This class guarantees that hash() will be called no more than once
        per element.  This is important because the lru_cache() will hash
        the key multiple times on a cache miss.
    """

    __slots__ = 'hashvalue'

    def __init__(self, tup, hash=hash):
        self[:] = tup
        self.hashvalue = hash(tup)

    def __hash__(self):
        return self.hashvalue

def _make_key(args, kwds, typed,
             kwd_mark = (object(),),
             fasttypes = set([int, str, frozenset, type(None)]),
             sorted=sorted, tuple=tuple, type=type, len=len):
    """Make a cache key from optionally typed positional and keyword arguments
    The key is constructed in a way that is flat as possible rather than
    as a nested structure that would take more memory.
    If there is only a single argument and its data type is known to cache
    its hash value, then that argument is returned without a wrapper.  This
    saves space and improves lookup speed.
    """
    key = args
    if kwds:
        sorted_items = sorted(kwds.items())
        key += kwd_mark
        for item in sorted_items:
            key += item
    if typed:
        key += tuple(type(v) for v in args)
        if kwds:
            key += tuple(type(v) for k, v in sorted_items)
    elif len(key) == 1 and type(key[0]) in fasttypes:
        return key[0]
    return _HashedSeq(key)

def lru_cache(maxsize=128, 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).

    # Early detection of an erroneous call to @lru_cache without any arguments
    # resulting in the inner function being passed to maxsize instead of an
    # integer or None.
    if maxsize is not None and not isinstance(maxsize, int):
        raise TypeError('Expected maxsize to be an integer or None')

    def decorating_function(user_function):
        wrapper = _lru_cache_wrapper(user_function, maxsize, typed)
        return update_wrapper(wrapper, user_function)

    return decorating_function

def _lru_cache_wrapper(user_function, maxsize, typed):
    # Constants shared by all lru cache instances:
    sentinel = object()          # unique object used to signal cache misses
    make_key = _make_key         # build a key from the function arguments
    PREV, NEXT, KEY, RESULT = 0, 1, 2, 3   # names for the link fields

    cache = {}
    cache_get = cache.get    # bound method to lookup a key or return None
    lock = RLock()           # because linkedlist updates aren't threadsafe
    root = []                # root of the circular doubly linked list
    root[:] = [root, root, None, None]     # initialize by pointing to self
    hits_misses_full_root = [0, 0, False, root]
    HITS,MISSES,FULL,ROOT = 0, 1, 2, 3

    if maxsize == 0:

        def wrapper(*args, **kwds):
            # No caching -- just a statistics update after a successful call
            result = user_function(*args, **kwds)
            hits_misses_full_root[MISSES] += 1
            return result

    elif maxsize is None:

        def wrapper(*args, **kwds):
            # Simple caching without ordering or size limit
            key = make_key(args, kwds, typed)
            result = cache_get(key, sentinel)
            if result is not sentinel:
                hits_misses_full_root[HITS] += 1
                return result
            result = user_function(*args, **kwds)
            cache[key] = result
            hits_misses_full_root[MISSES] += 1
            return result

    else:

        def wrapper(*args, **kwds):
            # Size limited caching that tracks accesses by recency
            key = make_key(args, kwds, typed)
            lock.acquire()
            try:
                link = cache_get(key)
                if link is not None:
                    # Move the link to the front of the circular queue
                    root = hits_misses_full_root[ROOT]
                    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_misses_full_root[HITS] += 1
                    return result
            finally:
                lock.release()
            result = user_function(*args, **kwds)
            lock.acquire()
            try:
                if key in cache:
                    # Getting here means that this same key was added to the
                    # cache while the lock was released.  Since the link
                    # update is already done, we need only return the
                    # computed result and update the count of misses.
                    pass
                elif hits_misses_full_root[FULL]:
                    # Use the old root to store the new key and result.
                    oldroot = root = hits_misses_full_root[ROOT]
                    oldroot[KEY] = key
                    oldroot[RESULT] = result
                    # Empty the oldest link and make it the new root.
                    # Keep a reference to the old key and old result to
                    # prevent their ref counts from going to zero during the
                    # update. That will prevent potentially arbitrary object
                    # clean-up code (i.e. __del__) from running while we're
                    # still adjusting the links.
                    root = hits_misses_full_root[ROOT] = oldroot[NEXT]
                    oldkey = root[KEY]
                    oldresult = root[RESULT]
                    root[KEY] = root[RESULT] = None
                    # Now update the cache dictionary.
                    del cache[oldkey]
                    # Save the potentially reentrant cache[key] assignment
                    # for last, after the root and links have been put in
                    # a consistent state.
                    cache[key] = oldroot
                else:
                    # Put result in a new link at the front of the queue.
                    root = hits_misses_full_root[ROOT]
                    last = root[PREV]
                    link = [last, root, key, result]
                    last[NEXT] = root[PREV] = cache[key] = link
                    # Use the __len__() method instead of the len() function
                    # which could potentially be wrapped in an lru_cache itself.
                    hits_misses_full_root[FULL] = (cache.__len__() >= maxsize)
                hits_misses_full_root[MISSES]
            finally:
                lock.release()
            return result

    def cache_clear():
        """Clear the cache and cache statistics"""
        lock.acquire()
        try:
            cache.clear()
            root = hits_misses_full_root[ROOT]
            root[:] = [root, root, None, None]
            hits_misses_full[HITS] = 0
            hits_misses_full[MISSES] = 0
            hits_misses_full[FULL] = False
        finally:
            lock.release()

    wrapper.cache_clear = cache_clear
    return wrapper