jupytersketcher/Lib/site-packages/nltk/decorators.py

"""
Decorator module by Michele Simionato <michelesimionato@libero.it>
Copyright Michele Simionato, distributed under the terms of the BSD License (see below).
http://www.phyast.pitt.edu/~micheles/python/documentation.html

Included in NLTK for its support of a nice memoization decorator.
"""

__docformat__ = "restructuredtext en"

## The basic trick is to generate the source code for the decorated function
## with the right signature and to evaluate it.
## Uncomment the statement 'print >> sys.stderr, func_src'  in _decorator
## to understand what is going on.

__all__ = ["decorator", "new_wrapper", "getinfo"]

import sys

# Hack to keep NLTK's "tokenize" module from colliding with the "tokenize" in
# the Python standard library.
OLD_SYS_PATH = sys.path[:]
sys.path = [p for p in sys.path if p and "nltk" not in p]
import inspect

sys.path = OLD_SYS_PATH

def __legacysignature(signature):
    """
    For retrocompatibility reasons, we don't use a standard Signature.
    Instead, we use the string generated by this method.
    Basically, from a Signature we create a string and remove the default values.
    """
    listsignature = str(signature)[1:-1].split(",")
    for counter, param in enumerate(listsignature):
        if param.count("=") > 0:
            listsignature[counter] = param[0:param.index("=")].strip()
        else:
            listsignature[counter] = param.strip()
    return ", ".join(listsignature)


def getinfo(func):
    """
    Returns an info dictionary containing:
    - name (the name of the function : str)
    - argnames (the names of the arguments : list)
    - defaults (the values of the default arguments : tuple)
    - signature (the signature : str)
    - fullsignature (the full signature : Signature)
    - doc (the docstring : str)
    - module (the module name : str)
    - dict (the function __dict__ : str)

    >>> def f(self, x=1, y=2, *args, **kw): pass

    >>> info = getinfo(f)

    >>> info["name"]
    'f'
    >>> info["argnames"]
    ['self', 'x', 'y', 'args', 'kw']

    >>> info["defaults"]
    (1, 2)

    >>> info["signature"]
    'self, x, y, *args, **kw'

    >>> info["fullsignature"]
    <Signature (self, x=1, y=2, *args, **kw)>
    """
    assert inspect.ismethod(func) or inspect.isfunction(func)
    argspec = inspect.getfullargspec(func)
    regargs, varargs, varkwargs = argspec[:3]
    argnames = list(regargs)
    if varargs:
        argnames.append(varargs)
    if varkwargs:
        argnames.append(varkwargs)
    fullsignature = inspect.signature(func)
    # Convert Signature to str
    signature = __legacysignature(fullsignature)


    # pypy compatibility
    if hasattr(func, "__closure__"):
        _closure = func.__closure__
        _globals = func.__globals__
    else:
        _closure = func.func_closure
        _globals = func.func_globals

    return dict(
        name=func.__name__,
        argnames=argnames,
        signature=signature,
        fullsignature=fullsignature,
        defaults=func.__defaults__,
        doc=func.__doc__,
        module=func.__module__,
        dict=func.__dict__,
        globals=_globals,
        closure=_closure,
    )


def update_wrapper(wrapper, model, infodict=None):
    " akin to functools.update_wrapper "
    infodict = infodict or getinfo(model)
    wrapper.__name__ = infodict["name"]
    wrapper.__doc__ = infodict["doc"]
    wrapper.__module__ = infodict["module"]
    wrapper.__dict__.update(infodict["dict"])
    wrapper.__defaults__ = infodict["defaults"]
    wrapper.undecorated = model
    return wrapper


def new_wrapper(wrapper, model):
    """
    An improvement over functools.update_wrapper. The wrapper is a generic
    callable object. It works by generating a copy of the wrapper with the
    right signature and by updating the copy, not the original.
    Moreovoer, 'model' can be a dictionary with keys 'name', 'doc', 'module',
    'dict', 'defaults'.
    """
    if isinstance(model, dict):
        infodict = model
    else:  # assume model is a function
        infodict = getinfo(model)
    assert (
        not "_wrapper_" in infodict["argnames"]
    ), '"_wrapper_" is a reserved argument name!'
    src = "lambda %(signature)s: _wrapper_(%(signature)s)" % infodict
    funcopy = eval(src, dict(_wrapper_=wrapper))
    return update_wrapper(funcopy, model, infodict)


# helper used in decorator_factory
def __call__(self, func):
    return new_wrapper(lambda *a, **k: self.call(func, *a, **k), func)


def decorator_factory(cls):
    """
    Take a class with a ``.caller`` method and return a callable decorator
    object. It works by adding a suitable __call__ method to the class;
    it raises a TypeError if the class already has a nontrivial __call__
    method.
    """
    attrs = set(dir(cls))
    if "__call__" in attrs:
        raise TypeError(
            "You cannot decorate a class with a nontrivial " "__call__ method"
        )
    if "call" not in attrs:
        raise TypeError("You cannot decorate a class without a " ".call method")
    cls.__call__ = __call__
    return cls


def decorator(caller):
    """
    General purpose decorator factory: takes a caller function as
    input and returns a decorator with the same attributes.
    A caller function is any function like this::

     def caller(func, *args, **kw):
         # do something
         return func(*args, **kw)

    Here is an example of usage:

    >>> @decorator
    ... def chatty(f, *args, **kw):
    ...     print("Calling %r" % f.__name__)
    ...     return f(*args, **kw)

    >>> chatty.__name__
    'chatty'

    >>> @chatty
    ... def f(): pass
    ...
    >>> f()
    Calling 'f'

    decorator can also take in input a class with a .caller method; in this
    case it converts the class into a factory of callable decorator objects.
    See the documentation for an example.
    """
    if inspect.isclass(caller):
        return decorator_factory(caller)

    def _decorator(func):  # the real meat is here
        infodict = getinfo(func)
        argnames = infodict["argnames"]
        assert not (
            "_call_" in argnames or "_func_" in argnames
        ), "You cannot use _call_ or _func_ as argument names!"
        src = "lambda %(signature)s: _call_(_func_, %(signature)s)" % infodict
        # import sys; print >> sys.stderr, src # for debugging purposes
        dec_func = eval(src, dict(_func_=func, _call_=caller))
        return update_wrapper(dec_func, func, infodict)

    return update_wrapper(_decorator, caller)


def getattr_(obj, name, default_thunk):
    "Similar to .setdefault in dictionaries."
    try:
        return getattr(obj, name)
    except AttributeError:
        default = default_thunk()
        setattr(obj, name, default)
        return default


@decorator
def memoize(func, *args):
    dic = getattr_(func, "memoize_dic", dict)
    # memoize_dic is created at the first call
    if args in dic:
        return dic[args]
    result = func(*args)
    dic[args] = result
    return result


##########################     LEGALESE    ###############################

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