monty.functools — monty 2021.8.17 documentation

# Source code for monty.functools

    """
    functools, especially backported from Python 3.
    """

    import signal
    import sys
    import cProfile
    import pstats
    import tempfile
    from collections import namedtuple
    from functools import update_wrapper, wraps, partial
    from threading import RLock

    _CacheInfo = namedtuple("_CacheInfo", ["hits", "misses", "maxsize", "currsize"])

    class _HashedSeq(list):  # pylint: disable=C0205
        """
        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, hashfunc=hash):
            """
            :param tup: Tuple.
            :param hashfunc: Hash function.
            """
            self[:] = tup
            self.hashvalue = hashfunc(tup)

        def __hash__(self):
            return self.hashvalue

    def _make_key(args, kwds, typed, kwd_mark=(object(),), fasttypes={int, str, frozenset, type(None)}):
        """
        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 isinstance(key[0], fasttypes):
            return key[0]
        return _HashedSeq(key)

    def lru_cache(maxsize=128, typed=False):
        """
        Least-recently-used cache decorator, which is a backport of the same
        function in Python >= 3.2.

        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")

        # 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

        def decorating_function(user_function):
            cache = {}
            hits = [0]
            misses = [0]
            full = [False]
            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
            r = [root]

            if maxsize == 0:

                def wrapper(*args, **kwds):
                    # No caching - just a statistics update after a successful call
                    result = user_function(*args, **kwds)
                    misses[0] += 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[0] += 1
                        return result
                    result = user_function(*args, **kwds)
                    cache[key] = result
                    misses[0] += 1
                    return result

            else:

                def wrapper(*args, **kwds):
                    # Size limited caching that tracks accesses by recency
                    key = make_key(args, kwds, typed)
                    with lock:
                        link = cache_get(key)
                        if link is not None:
                            # Move the link to the front of the circular queue
                            link_prev, link_next, _key, result = link
                            link_prev[NEXT] = link_next
                            link_next[PREV] = link_prev
                            last = r[0][PREV]
                            last[NEXT] = r[0][PREV] = link
                            link[PREV] = last
                            link[NEXT] = r[0]
                            hits[0] += 1
                            return result
                    result = user_function(*args, **kwds)
                    with lock:
                        if key in cache:
                            # Getting here means that this same key was added to
                            # 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 full[0]:
                            # Use the old root to store the new key and result.
                            oldroot = r[0]
                            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
                            # update. That will prevent arbitrary object
                            # clean-up code (i.e. __del__) from running while we're
                            # still adjusting the links.
                            r[0] = oldroot[NEXT]
                            oldkey = r[0][KEY]
                            r[0][KEY] = r[0][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.
                            last = r[0][PREV]
                            link = [last, r[0], key, result]
                            last[NEXT] = r[0][PREV] = cache[key] = link
                            full[0] = len(cache) >= maxsize
                        misses[0] += 1
                    return result

            def cache_info():
                """Report cache statistics"""
                with lock:
                    return _CacheInfo(hits[0], misses[0], maxsize, len(cache))

            def cache_clear():
                """Clear the cache and cache statistics"""
                with lock:
                    cache.clear()
                    root[:] = [root, root, None, None]
                    r[0] = root
                    hits[0] = 0
                    misses[0] = 0
                    full[0] = False

            wrapper.cache_info = cache_info
            wrapper.cache_clear = cache_clear
            return update_wrapper(wrapper, user_function)

        return decorating_function

    class lazy_property:
        """
        lazy_property descriptor

        Used as a decorator to create lazy attributes. Lazy attributes
        are evaluated on first use.
        """

        def __init__(self, func):
            """
            :param func: Function to decorate.
            """
            self.__func = func
            wraps(self.__func)(self)

        def __get__(self, inst, inst_cls):
            if inst is None:
                return self

            if not hasattr(inst, "__dict__"):
                raise AttributeError("'%s' object has no attribute '__dict__'" % (inst_cls.__name__,))

            name = self.__name__  # pylint: disable=E1101
            if name.startswith("__") and not name.endswith("__"):
                name = "_%s%s" % (inst_cls.__name__, name)

            value = self.__func(inst)
            inst.__dict__[name] = value
            return value

        @classmethod
        def invalidate(cls, inst, name):
            """Invalidate a lazy attribute.

            This obviously violates the lazy contract. A subclass of lazy
            may however have a contract where invalidation is appropriate.
            """
            inst_cls = inst.__class__

            if not hasattr(inst, "__dict__"):
                raise AttributeError("'%s' object has no attribute '__dict__'" % (inst_cls.__name__,))

            if name.startswith("__") and not name.endswith("__"):
                name = "_%s%s" % (inst_cls.__name__, name)

            if not isinstance(getattr(inst_cls, name), cls):
                raise AttributeError("'%s.%s' is not a %s attribute" % (inst_cls.__name__, name, cls.__name__))

            if name in inst.__dict__:
                del inst.__dict__[name]

    def return_if_raise(exception_tuple, retval_if_exc, disabled=False):
        """
        Decorator for functions, methods or properties. Execute the callable in a
        try block, and return retval_if_exc if one of the exceptions listed in
        exception_tuple is raised (se also ``return_node_if_raise``).

        Setting disabled to True disables the try except block (useful for
        debugging purposes). One can use this decorator to define properties.

        Example::

            @return_if_raise(ValueError, None)
            def return_none_if_value_error(self):
                pass

            @return_if_raise((ValueError, KeyError), "hello")
            def another_method(self):
                pass

            @property
            @return_if_raise(AttributeError, None)
            def name(self):
                "Name of the object, None if not set."
                return self._name

        """
        # we need a tuple of exceptions.
        if isinstance(exception_tuple, list):
            exception_tuple = tuple(exception_tuple)
        elif not isinstance(exception_tuple, tuple):
            exception_tuple = (exception_tuple,)
        else:
            raise TypeError("Wrong exception_tuple %s" % type(exception_tuple))

        def decorator(func):
            @wraps(func)
            def wrapper(*args, **kwargs):
                if disabled:
                    return func(*args, **kwargs)
                try:
                    return func(*args, **kwargs)
                except exception_tuple:  # pylint: disable=E0712
                    return retval_if_exc

            return wrapper

        return decorator

    # One could use None as default value in return_if_raise but this one is
    # explicit and  more readable
    return_none_if_raise = partial(return_if_raise, retval_if_exc=None)
    """
    This decorator returns None if one of the exceptions is raised.

        @return_none_if_raise(ValueError)
        def method(self):
    """

    class timeout:
        """
        Timeout function. Use to limit matching to a certain time limit. Note that
        this works only on Unix-based systems as it uses signal. Usage:

        try:
            with timeout(3):
                do_stuff()
        except TimeoutError:
            do_something_else()
        """

        def __init__(self, seconds=1, error_message="Timeout"):
            """
            Args:
                seconds (int): Allowed time for function in seconds.
                error_message (str): An error message.

            """
            self.seconds = seconds
            self.error_message = error_message

        def handle_timeout(self, signum, frame):
            """
            :param signum: Return signal from call.
            :param frame:
            """
            raise TimeoutError(self.error_message)

        def __enter__(self):
            signal.signal(signal.SIGALRM, self.handle_timeout)
            signal.alarm(self.seconds)

        def __exit__(self, type, value, traceback):
            signal.alarm(0)

    class TimeoutError(Exception):
        """
        Exception class for timeouts.
        """

        def __init__(self, message):
            """
            :param message: Error message
            """
            self.message = message

    def prof_main(main):
        """
        Decorator for profiling main programs.

        Profiling is activated by prepending the command line options
        supported by the original main program with the keyword `prof`.
        Example:

            $ script.py arg --foo=1

        becomes

            $ script.py prof arg --foo=1

        The decorated main accepts two new arguments:

            prof_file: Name of the output file with profiling data
                If not given, a temporary file is created.
            sortby: Profiling data are sorted according to this value.
                default is "time". See sort_stats.
        """

        @wraps(main)
        def wrapper(*args, **kwargs):
            try:
                do_prof = sys.argv[1] == "prof"
                if do_prof:
                    sys.argv.pop(1)
            except Exception:
                do_prof = False

            if not do_prof:
                sys.exit(main())
            else:
                print("Entering profiling mode...")
                prof_file = kwargs.get("prof_file", None)
                if prof_file is None:
                    _, prof_file = tempfile.mkstemp()
                    print("Profiling data stored in %s" % prof_file)

                sortby = kwargs.get("sortby", "time")
                cProfile.runctx("main()", globals(), locals(), prof_file)
                s = pstats.Stats(prof_file)
                s.strip_dirs().sort_stats(sortby).print_stats()
                if "retval" not in kwargs:
                    sys.exit(0)
                else:
                    return kwargs["retval"]

        return wrapper