Current File : //opt/cloudlinux/venv/lib/python3.11/site-packages/wrapt/decorators.py
"""This module implements decorators for implementing other decorators
as well as some commonly used decorators.
"""
import sys
PY2 = sys.version_info[0] == 2
if PY2:
string_types = basestring,
def exec_(_code_, _globs_=None, _locs_=None):
"""Execute code in a namespace."""
if _globs_ is None:
frame = sys._getframe(1)
_globs_ = frame.f_globals
if _locs_ is None:
_locs_ = frame.f_locals
del frame
elif _locs_ is None:
_locs_ = _globs_
exec("""exec _code_ in _globs_, _locs_""")
else:
string_types = str,
import builtins
exec_ = getattr(builtins, "exec")
del builtins
from functools import partial
from inspect import isclass
from threading import Lock, RLock
from .arguments import formatargspec
try:
from inspect import signature
except ImportError:
pass
from .wrappers import (FunctionWrapper, BoundFunctionWrapper, ObjectProxy,
CallableObjectProxy)
# Adapter wrapper for the wrapped function which will overlay certain
# properties from the adapter function onto the wrapped function so that
# functions such as inspect.getargspec(), inspect.getfullargspec(),
# inspect.signature() and inspect.getsource() return the correct results
# one would expect.
class _AdapterFunctionCode(CallableObjectProxy):
def __init__(self, wrapped_code, adapter_code):
super(_AdapterFunctionCode, self).__init__(wrapped_code)
self._self_adapter_code = adapter_code
@property
def co_argcount(self):
return self._self_adapter_code.co_argcount
@property
def co_code(self):
return self._self_adapter_code.co_code
@property
def co_flags(self):
return self._self_adapter_code.co_flags
@property
def co_kwonlyargcount(self):
return self._self_adapter_code.co_kwonlyargcount
@property
def co_varnames(self):
return self._self_adapter_code.co_varnames
class _AdapterFunctionSurrogate(CallableObjectProxy):
def __init__(self, wrapped, adapter):
super(_AdapterFunctionSurrogate, self).__init__(wrapped)
self._self_adapter = adapter
@property
def __code__(self):
return _AdapterFunctionCode(self.__wrapped__.__code__,
self._self_adapter.__code__)
@property
def __defaults__(self):
return self._self_adapter.__defaults__
@property
def __kwdefaults__(self):
return self._self_adapter.__kwdefaults__
@property
def __signature__(self):
if 'signature' not in globals():
return self._self_adapter.__signature__
else:
return signature(self._self_adapter)
if PY2:
func_code = __code__
func_defaults = __defaults__
class _BoundAdapterWrapper(BoundFunctionWrapper):
@property
def __func__(self):
return _AdapterFunctionSurrogate(self.__wrapped__.__func__,
self._self_parent._self_adapter)
@property
def __signature__(self):
if 'signature' not in globals():
return self.__wrapped__.__signature__
else:
return signature(self._self_parent._self_adapter)
if PY2:
im_func = __func__
class AdapterWrapper(FunctionWrapper):
__bound_function_wrapper__ = _BoundAdapterWrapper
def __init__(self, *args, **kwargs):
adapter = kwargs.pop('adapter')
super(AdapterWrapper, self).__init__(*args, **kwargs)
self._self_surrogate = _AdapterFunctionSurrogate(
self.__wrapped__, adapter)
self._self_adapter = adapter
@property
def __code__(self):
return self._self_surrogate.__code__
@property
def __defaults__(self):
return self._self_surrogate.__defaults__
@property
def __kwdefaults__(self):
return self._self_surrogate.__kwdefaults__
if PY2:
func_code = __code__
func_defaults = __defaults__
@property
def __signature__(self):
return self._self_surrogate.__signature__
class AdapterFactory(object):
def __call__(self, wrapped):
raise NotImplementedError()
class DelegatedAdapterFactory(AdapterFactory):
def __init__(self, factory):
super(DelegatedAdapterFactory, self).__init__()
self.factory = factory
def __call__(self, wrapped):
return self.factory(wrapped)
adapter_factory = DelegatedAdapterFactory
# Decorator for creating other decorators. This decorator and the
# wrappers which they use are designed to properly preserve any name
# attributes, function signatures etc, in addition to the wrappers
# themselves acting like a transparent proxy for the original wrapped
# function so the wrapper is effectively indistinguishable from the
# original wrapped function.
def decorator(wrapper=None, enabled=None, adapter=None, proxy=FunctionWrapper):
# The decorator should be supplied with a single positional argument
# which is the wrapper function to be used to implement the
# decorator. This may be preceded by a step whereby the keyword
# arguments are supplied to customise the behaviour of the
# decorator. The 'adapter' argument is used to optionally denote a
# separate function which is notionally used by an adapter
# decorator. In that case parts of the function '__code__' and
# '__defaults__' attributes are used from the adapter function
# rather than those of the wrapped function. This allows for the
# argument specification from inspect.getfullargspec() and similar
# functions to be overridden with a prototype for a different
# function than what was wrapped. The 'enabled' argument provides a
# way to enable/disable the use of the decorator. If the type of
# 'enabled' is a boolean, then it is evaluated immediately and the
# wrapper not even applied if it is False. If not a boolean, it will
# be evaluated when the wrapper is called for an unbound wrapper,
# and when binding occurs for a bound wrapper. When being evaluated,
# if 'enabled' is callable it will be called to obtain the value to
# be checked. If False, the wrapper will not be called and instead
# the original wrapped function will be called directly instead.
# The 'proxy' argument provides a way of passing a custom version of
# the FunctionWrapper class used in decorating the function.
if wrapper is not None:
# Helper function for creating wrapper of the appropriate
# time when we need it down below.
def _build(wrapped, wrapper, enabled=None, adapter=None):
if adapter:
if isinstance(adapter, AdapterFactory):
adapter = adapter(wrapped)
if not callable(adapter):
ns = {}
# Check if the signature argument specification has
# annotations. If it does then we need to remember
# it but also drop it when attempting to manufacture
# a standin adapter function. This is necessary else
# it will try and look up any types referenced in
# the annotations in the empty namespace we use,
# which will fail.
annotations = {}
if not isinstance(adapter, string_types):
if len(adapter) == 7:
annotations = adapter[-1]
adapter = adapter[:-1]
adapter = formatargspec(*adapter)
exec_('def adapter{}: pass'.format(adapter), ns, ns)
adapter = ns['adapter']
# Override the annotations for the manufactured
# adapter function so they match the original
# adapter signature argument specification.
if annotations:
adapter.__annotations__ = annotations
return AdapterWrapper(wrapped=wrapped, wrapper=wrapper,
enabled=enabled, adapter=adapter)
return proxy(wrapped=wrapped, wrapper=wrapper, enabled=enabled)
# The wrapper has been provided so return the final decorator.
# The decorator is itself one of our function wrappers so we
# can determine when it is applied to functions, instance methods
# or class methods. This allows us to bind the instance or class
# method so the appropriate self or cls attribute is supplied
# when it is finally called.
def _wrapper(wrapped, instance, args, kwargs):
# We first check for the case where the decorator was applied
# to a class type.
#
# @decorator
# class mydecoratorclass(object):
# def __init__(self, arg=None):
# self.arg = arg
# def __call__(self, wrapped, instance, args, kwargs):
# return wrapped(*args, **kwargs)
#
# @mydecoratorclass(arg=1)
# def function():
# pass
#
# In this case an instance of the class is to be used as the
# decorator wrapper function. If args was empty at this point,
# then it means that there were optional keyword arguments
# supplied to be used when creating an instance of the class
# to be used as the wrapper function.
if instance is None and isclass(wrapped) and not args:
# We still need to be passed the target function to be
# wrapped as yet, so we need to return a further function
# to be able to capture it.
def _capture(target_wrapped):
# Now have the target function to be wrapped and need
# to create an instance of the class which is to act
# as the decorator wrapper function. Before we do that,
# we need to first check that use of the decorator
# hadn't been disabled by a simple boolean. If it was,
# the target function to be wrapped is returned instead.
_enabled = enabled
if type(_enabled) is bool:
if not _enabled:
return target_wrapped
_enabled = None
# Now create an instance of the class which is to act
# as the decorator wrapper function. Any arguments had
# to be supplied as keyword only arguments so that is
# all we pass when creating it.
target_wrapper = wrapped(**kwargs)
# Finally build the wrapper itself and return it.
return _build(target_wrapped, target_wrapper,
_enabled, adapter)
return _capture
# We should always have the target function to be wrapped at
# this point as the first (and only) value in args.
target_wrapped = args[0]
# Need to now check that use of the decorator hadn't been
# disabled by a simple boolean. If it was, then target
# function to be wrapped is returned instead.
_enabled = enabled
if type(_enabled) is bool:
if not _enabled:
return target_wrapped
_enabled = None
# We now need to build the wrapper, but there are a couple of
# different cases we need to consider.
if instance is None:
if isclass(wrapped):
# In this case the decorator was applied to a class
# type but optional keyword arguments were not supplied
# for initialising an instance of the class to be used
# as the decorator wrapper function.
#
# @decorator
# class mydecoratorclass(object):
# def __init__(self, arg=None):
# self.arg = arg
# def __call__(self, wrapped, instance,
# args, kwargs):
# return wrapped(*args, **kwargs)
#
# @mydecoratorclass
# def function():
# pass
#
# We still need to create an instance of the class to
# be used as the decorator wrapper function, but no
# arguments are pass.
target_wrapper = wrapped()
else:
# In this case the decorator was applied to a normal
# function, or possibly a static method of a class.
#
# @decorator
# def mydecoratorfuntion(wrapped, instance,
# args, kwargs):
# return wrapped(*args, **kwargs)
#
# @mydecoratorfunction
# def function():
# pass
#
# That normal function becomes the decorator wrapper
# function.
target_wrapper = wrapper
else:
if isclass(instance):
# In this case the decorator was applied to a class
# method.
#
# class myclass(object):
# @decorator
# @classmethod
# def decoratorclassmethod(cls, wrapped,
# instance, args, kwargs):
# return wrapped(*args, **kwargs)
#
# instance = myclass()
#
# @instance.decoratorclassmethod
# def function():
# pass
#
# This one is a bit strange because binding was actually
# performed on the wrapper created by our decorator
# factory. We need to apply that binding to the decorator
# wrapper function that the decorator factory
# was applied to.
target_wrapper = wrapper.__get__(None, instance)
else:
# In this case the decorator was applied to an instance
# method.
#
# class myclass(object):
# @decorator
# def decoratorclassmethod(self, wrapped,
# instance, args, kwargs):
# return wrapped(*args, **kwargs)
#
# instance = myclass()
#
# @instance.decoratorclassmethod
# def function():
# pass
#
# This one is a bit strange because binding was actually
# performed on the wrapper created by our decorator
# factory. We need to apply that binding to the decorator
# wrapper function that the decorator factory
# was applied to.
target_wrapper = wrapper.__get__(instance, type(instance))
# Finally build the wrapper itself and return it.
return _build(target_wrapped, target_wrapper, _enabled, adapter)
# We first return our magic function wrapper here so we can
# determine in what context the decorator factory was used. In
# other words, it is itself a universal decorator. The decorator
# function is used as the adapter so that linters see a signature
# corresponding to the decorator and not the wrapper it is being
# applied to.
return _build(wrapper, _wrapper, adapter=decorator)
else:
# The wrapper still has not been provided, so we are just
# collecting the optional keyword arguments. Return the
# decorator again wrapped in a partial using the collected
# arguments.
return partial(decorator, enabled=enabled, adapter=adapter,
proxy=proxy)
# Decorator for implementing thread synchronization. It can be used as a
# decorator, in which case the synchronization context is determined by
# what type of function is wrapped, or it can also be used as a context
# manager, where the user needs to supply the correct synchronization
# context. It is also possible to supply an object which appears to be a
# synchronization primitive of some sort, by virtue of having release()
# and acquire() methods. In that case that will be used directly as the
# synchronization primitive without creating a separate lock against the
# derived or supplied context.
def synchronized(wrapped):
# Determine if being passed an object which is a synchronization
# primitive. We can't check by type for Lock, RLock, Semaphore etc,
# as the means of creating them isn't the type. Therefore use the
# existence of acquire() and release() methods. This is more
# extensible anyway as it allows custom synchronization mechanisms.
if hasattr(wrapped, 'acquire') and hasattr(wrapped, 'release'):
# We remember what the original lock is and then return a new
# decorator which accesses and locks it. When returning the new
# decorator we wrap it with an object proxy so we can override
# the context manager methods in case it is being used to wrap
# synchronized statements with a 'with' statement.
lock = wrapped
@decorator
def _synchronized(wrapped, instance, args, kwargs):
# Execute the wrapped function while the original supplied
# lock is held.
with lock:
return wrapped(*args, **kwargs)
class _PartialDecorator(CallableObjectProxy):
def __enter__(self):
lock.acquire()
return lock
def __exit__(self, *args):
lock.release()
return _PartialDecorator(wrapped=_synchronized)
# Following only apply when the lock is being created automatically
# based on the context of what was supplied. In this case we supply
# a final decorator, but need to use FunctionWrapper directly as we
# want to derive from it to add context manager methods in case it is
# being used to wrap synchronized statements with a 'with' statement.
def _synchronized_lock(context):
# Attempt to retrieve the lock for the specific context.
lock = vars(context).get('_synchronized_lock', None)
if lock is None:
# There is no existing lock defined for the context we
# are dealing with so we need to create one. This needs
# to be done in a way to guarantee there is only one
# created, even if multiple threads try and create it at
# the same time. We can't always use the setdefault()
# method on the __dict__ for the context. This is the
# case where the context is a class, as __dict__ is
# actually a dictproxy. What we therefore do is use a
# meta lock on this wrapper itself, to control the
# creation and assignment of the lock attribute against
# the context.
with synchronized._synchronized_meta_lock:
# We need to check again for whether the lock we want
# exists in case two threads were trying to create it
# at the same time and were competing to create the
# meta lock.
lock = vars(context).get('_synchronized_lock', None)
if lock is None:
lock = RLock()
setattr(context, '_synchronized_lock', lock)
return lock
def _synchronized_wrapper(wrapped, instance, args, kwargs):
# Execute the wrapped function while the lock for the
# desired context is held. If instance is None then the
# wrapped function is used as the context.
with _synchronized_lock(instance if instance is not None else wrapped):
return wrapped(*args, **kwargs)
class _FinalDecorator(FunctionWrapper):
def __enter__(self):
self._self_lock = _synchronized_lock(self.__wrapped__)
self._self_lock.acquire()
return self._self_lock
def __exit__(self, *args):
self._self_lock.release()
return _FinalDecorator(wrapped=wrapped, wrapper=_synchronized_wrapper)
synchronized._synchronized_meta_lock = Lock()
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