EVOLUTION-NINJA

Edit File: decorator.py

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"""
Decorator module, see http://pypi.python.org/pypi/decorator
for the documentation.
"""
from __future__ import print_function

import re
import sys
import inspect
import operator
import itertools
import collections

__version__ = '4.2.1'

if sys.version >= '3':
    from inspect import getfullargspec

def get_init(cls):
        return cls.__init__
else:
    FullArgSpec = collections.namedtuple(
        'FullArgSpec', 'args varargs varkw defaults '
        'kwonlyargs kwonlydefaults')

def getfullargspec(f):
        "A quick and dirty replacement for getfullargspec for Python 2.X"
        return FullArgSpec._make(inspect.getargspec(f) + ([], None))

def get_init(cls):
        return cls.__init__.__func__

try:
    iscoroutinefunction = inspect.iscoroutinefunction
except AttributeError:
    # let's assume there are no coroutine functions in old Python
    def iscoroutinefunction(f):
        return False

# getargspec has been deprecated in Python 3.5
ArgSpec = collections.namedtuple(
    'ArgSpec', 'args varargs varkw defaults')

def getargspec(f):
    """A replacement for inspect.getargspec"""
    spec = getfullargspec(f)
    return ArgSpec(spec.args, spec.varargs, spec.varkw, spec.defaults)

DEF = re.compile(r'\s*def\s*([_\w][_\w\d]*)\s*\(')

# basic functionality
class FunctionMaker(object):
    """
    An object with the ability to create functions with a given signature.
    It has attributes name, doc, module, signature, defaults, dict and
    methods update and make.
    """

# Atomic get-and-increment provided by the GIL
    _compile_count = itertools.count()

# make pylint happy
    args = varargs = varkw = defaults = kwonlyargs = kwonlydefaults = ()

def __init__(self, func=None, name=None, signature=None,
                 defaults=None, doc=None, module=None, funcdict=None):
        self.shortsignature = signature
        if func:
            # func can be a class or a callable, but not an instance method
            self.name = func.__name__
            if self.name == '<lambda>':  # small hack for lambda functions
                self.name = '_lambda_'
            self.doc = func.__doc__
            self.module = func.__module__
            if inspect.isfunction(func):
                argspec = getfullargspec(func)
                self.annotations = getattr(func, '__annotations__', {})
                for a in ('args', 'varargs', 'varkw', 'defaults', 'kwonlyargs',
                          'kwonlydefaults'):
                    setattr(self, a, getattr(argspec, a))
                for i, arg in enumerate(self.args):
                    setattr(self, 'arg%d' % i, arg)
                allargs = list(self.args)
                allshortargs = list(self.args)
                if self.varargs:
                    allargs.append('*' + self.varargs)
                    allshortargs.append('*' + self.varargs)
                elif self.kwonlyargs:
                    allargs.append('*')  # single star syntax
                for a in self.kwonlyargs:
                    allargs.append('%s=None' % a)
                    allshortargs.append('%s=%s' % (a, a))
                if self.varkw:
                    allargs.append('**' + self.varkw)
                    allshortargs.append('**' + self.varkw)
                self.signature = ', '.join(allargs)
                self.shortsignature = ', '.join(allshortargs)
                self.dict = func.__dict__.copy()
        # func=None happens when decorating a caller
        if name:
            self.name = name
        if signature is not None:
            self.signature = signature
        if defaults:
            self.defaults = defaults
        if doc:
            self.doc = doc
        if module:
            self.module = module
        if funcdict:
            self.dict = funcdict
        # check existence required attributes
        assert hasattr(self, 'name')
        if not hasattr(self, 'signature'):
            raise TypeError('You are decorating a non function: %s' % func)

def update(self, func, **kw):
        "Update the signature of func with the data in self"
        func.__name__ = self.name
        func.__doc__ = getattr(self, 'doc', None)
        func.__dict__ = getattr(self, 'dict', {})
        func.__defaults__ = self.defaults
        func.__kwdefaults__ = self.kwonlydefaults or None
        func.__annotations__ = getattr(self, 'annotations', None)
        try:
            frame = sys._getframe(3)
        except AttributeError:  # for IronPython and similar implementations
            callermodule = '?'
        else:
            callermodule = frame.f_globals.get('__name__', '?')
        func.__module__ = getattr(self, 'module', callermodule)
        func.__dict__.update(kw)

def make(self, src_templ, evaldict=None, addsource=False, **attrs):
        "Make a new function from a given template and update the signature"
        src = src_templ % vars(self)  # expand name and signature
        evaldict = evaldict or {}
        mo = DEF.search(src)
        if mo is None:
            raise SyntaxError('not a valid function template\n%s' % src)
        name = mo.group(1)  # extract the function name
        names = set([name] + [arg.strip(' *') for arg in
                              self.shortsignature.split(',')])
        for n in names:
            if n in ('_func_', '_call_'):
                raise NameError('%s is overridden in\n%s' % (n, src))

if not src.endswith('\n'):  # add a newline for old Pythons
            src += '\n'

# Ensure each generated function has a unique filename for profilers
        # (such as cProfile) that depend on the tuple of (<filename>,
        # <definition line>, <function name>) being unique.
        filename = '<decorator-gen-%d>' % (next(self._compile_count),)
        try:
            code = compile(src, filename, 'single')
            exec(code, evaldict)
        except:
            print('Error in generated code:', file=sys.stderr)
            print(src, file=sys.stderr)
            raise
        func = evaldict[name]
        if addsource:
            attrs['__source__'] = src
        self.update(func, **attrs)
        return func

@classmethod
    def create(cls, obj, body, evaldict, defaults=None,
               doc=None, module=None, addsource=True, **attrs):
        """
        Create a function from the strings name, signature and body.
        evaldict is the evaluation dictionary. If addsource is true an
        attribute __source__ is added to the result. The attributes attrs
        are added, if any.
        """
        if isinstance(obj, str):  # "name(signature)"
            name, rest = obj.strip().split('(', 1)
            signature = rest[:-1]  # strip a right parens
            func = None
        else:  # a function
            name = None
            signature = None
            func = obj
        self = cls(func, name, signature, defaults, doc, module)
        ibody = '\n'.join('    ' + line for line in body.splitlines())
        caller = evaldict.get('_call_')  # when called from `decorate`
        if caller and iscoroutinefunction(caller):
            body = ('async def %(name)s(%(signature)s):\n' + ibody).replace(
                'return', 'return await')
        else:
            body = 'def %(name)s(%(signature)s):\n' + ibody
        return self.make(body, evaldict, addsource, **attrs)

def decorate(func, caller, extras=()):
    """
    decorate(func, caller) decorates a function using a caller.
    """
    evaldict = dict(_call_=caller, _func_=func)
    es = ''
    for i, extra in enumerate(extras):
        ex = '_e%d_' % i
        evaldict[ex] = extra
        es += ex + ', '
    fun = FunctionMaker.create(
        func, "return _call_(_func_, %s%%(shortsignature)s)" % es,
        evaldict, __wrapped__=func)
    if hasattr(func, '__qualname__'):
        fun.__qualname__ = func.__qualname__
    return fun

def decorator(caller, _func=None):
    """decorator(caller) converts a caller function into a decorator"""
    if _func is not None:  # return a decorated function
        # this is obsolete behavior; you should use decorate instead
        return decorate(_func, caller)
    # else return a decorator function
    defaultargs, defaults = '', ()
    if inspect.isclass(caller):
        name = caller.__name__.lower()
        doc = 'decorator(%s) converts functions/generators into ' \
            'factories of %s objects' % (caller.__name__, caller.__name__)
    elif inspect.isfunction(caller):
        if caller.__name__ == '<lambda>':
            name = '_lambda_'
        else:
            name = caller.__name__
        doc = caller.__doc__
        nargs = caller.__code__.co_argcount
        ndefs = len(caller.__defaults__ or ())
        defaultargs = ', '.join(caller.__code__.co_varnames[nargs-ndefs:nargs])
        if defaultargs:
            defaultargs += ','
        defaults = caller.__defaults__
    else:  # assume caller is an object with a __call__ method
        name = caller.__class__.__name__.lower()
        doc = caller.__call__.__doc__
    evaldict = dict(_call=caller, _decorate_=decorate)
    dec = FunctionMaker.create(
        '%s(func, %s)' % (name, defaultargs),
        'if func is None: return lambda func:  _decorate_(func, _call, (%s))\n'
        'return _decorate_(func, _call, (%s))' % (defaultargs, defaultargs),
        evaldict, doc=doc, module=caller.__module__, __wrapped__=caller)
    if defaults:
        dec.__defaults__ = (None,) + defaults
    return dec

# ####################### contextmanager ####################### #

try:  # Python >= 3.2
    from contextlib import _GeneratorContextManager
except ImportError:  # Python >= 2.5
    from contextlib import GeneratorContextManager as _GeneratorContextManager

class ContextManager(_GeneratorContextManager):
    def __call__(self, func):
        """Context manager decorator"""
        return FunctionMaker.create(
            func, "with _self_: return _func_(%(shortsignature)s)",
            dict(_self_=self, _func_=func), __wrapped__=func)

init = getfullargspec(_GeneratorContextManager.__init__)
n_args = len(init.args)
if n_args == 2 and not init.varargs:  # (self, genobj) Python 2.7
    def __init__(self, g, *a, **k):
        return _GeneratorContextManager.__init__(self, g(*a, **k))
    ContextManager.__init__ = __init__
elif n_args == 2 and init.varargs:  # (self, gen, *a, **k) Python 3.4
    pass
elif n_args == 4:  # (self, gen, args, kwds) Python 3.5
    def __init__(self, g, *a, **k):
        return _GeneratorContextManager.__init__(self, g, a, k)
    ContextManager.__init__ = __init__

_contextmanager = decorator(ContextManager)

def contextmanager(func):
    # Enable Pylint config: contextmanager-decorators=decorator.contextmanager
    return _contextmanager(func)

# ############################ dispatch_on ############################ #

def append(a, vancestors):
    """
    Append ``a`` to the list of the virtual ancestors, unless it is already
    included.
    """
    add = True
    for j, va in enumerate(vancestors):
        if issubclass(va, a):
            add = False
            break
        if issubclass(a, va):
            vancestors[j] = a
            add = False
    if add:
        vancestors.append(a)

# inspired from simplegeneric by P.J. Eby and functools.singledispatch
def dispatch_on(*dispatch_args):
    """
    Factory of decorators turning a function into a generic function
    dispatching on the given arguments.
    """
    assert dispatch_args, 'No dispatch args passed'
    dispatch_str = '(%s,)' % ', '.join(dispatch_args)

def check(arguments, wrong=operator.ne, msg=''):
        """Make sure one passes the expected number of arguments"""
        if wrong(len(arguments), len(dispatch_args)):
            raise TypeError('Expected %d arguments, got %d%s' %
                            (len(dispatch_args), len(arguments), msg))

def gen_func_dec(func):
        """Decorator turning a function into a generic function"""

# first check the dispatch arguments
        argset = set(getfullargspec(func).args)
        if not set(dispatch_args) <= argset:
            raise NameError('Unknown dispatch arguments %s' % dispatch_str)

typemap = {}

def vancestors(*types):
            """
            Get a list of sets of virtual ancestors for the given types
            """
            check(types)
            ras = [[] for _ in range(len(dispatch_args))]
            for types_ in typemap:
                for t, type_, ra in zip(types, types_, ras):
                    if issubclass(t, type_) and type_ not in t.mro():
                        append(type_, ra)
            return [set(ra) for ra in ras]

def ancestors(*types):
            """
            Get a list of virtual MROs, one for each type
            """
            check(types)
            lists = []
            for t, vas in zip(types, vancestors(*types)):
                n_vas = len(vas)
                if n_vas > 1:
                    raise RuntimeError(
                        'Ambiguous dispatch for %s: %s' % (t, vas))
                elif n_vas == 1:
                    va, = vas
                    mro = type('t', (t, va), {}).mro()[1:]
                else:
                    mro = t.mro()
                lists.append(mro[:-1])  # discard t and object
            return lists

def register(*types):
            """
            Decorator to register an implementation for the given types
            """
            check(types)

def dec(f):
                check(getfullargspec(f).args, operator.lt, ' in ' + f.__name__)
                typemap[types] = f
                return f
            return dec

def dispatch_info(*types):
            """
            An utility to introspect the dispatch algorithm
            """
            check(types)
            lst = []
            for anc in itertools.product(*ancestors(*types)):
                lst.append(tuple(a.__name__ for a in anc))
            return lst

def _dispatch(dispatch_args, *args, **kw):
            types = tuple(type(arg) for arg in dispatch_args)
            try:  # fast path
                f = typemap[types]
            except KeyError:
                pass
            else:
                return f(*args, **kw)
            combinations = itertools.product(*ancestors(*types))
            next(combinations)  # the first one has been already tried
            for types_ in combinations:
                f = typemap.get(types_)
                if f is not None:
                    return f(*args, **kw)

# else call the default implementation
            return func(*args, **kw)

return FunctionMaker.create(
            func, 'return _f_(%s, %%(shortsignature)s)' % dispatch_str,
            dict(_f_=_dispatch), register=register, default=func,
            typemap=typemap, vancestors=vancestors, ancestors=ancestors,
            dispatch_info=dispatch_info, __wrapped__=func)

gen_func_dec.__name__ = 'dispatch_on' + dispatch_str
    return gen_func_dec