220 lines
7.6 KiB
Python
220 lines
7.6 KiB
Python
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"""
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Decorator module by Michele Simionato <michelesimionato@libero.it>
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Copyright Michele Simionato, distributed under the terms of the BSD License (see below).
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http://www.phyast.pitt.edu/~micheles/python/documentation.html
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Included in NLTK for its support of a nice memoization decorator.
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"""
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from __future__ import print_function
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__docformat__ = 'restructuredtext en'
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## The basic trick is to generate the source code for the decorated function
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## with the right signature and to evaluate it.
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## Uncomment the statement 'print >> sys.stderr, func_src' in _decorator
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## to understand what is going on.
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__all__ = ["decorator", "new_wrapper", "getinfo"]
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import sys
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# Hack to keep NLTK's "tokenize" module from colliding with the "tokenize" in
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# the Python standard library.
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old_sys_path = sys.path[:]
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sys.path = [p for p in sys.path if "nltk" not in p]
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import inspect
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sys.path = old_sys_path
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try:
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set
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except NameError:
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from sets import Set as set
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def getinfo(func):
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"""
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Returns an info dictionary containing:
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- name (the name of the function : str)
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- argnames (the names of the arguments : list)
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- defaults (the values of the default arguments : tuple)
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- signature (the signature : str)
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- doc (the docstring : str)
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- module (the module name : str)
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- dict (the function __dict__ : str)
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>>> def f(self, x=1, y=2, *args, **kw): pass
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>>> info = getinfo(f)
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>>> info["name"]
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'f'
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>>> info["argnames"]
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['self', 'x', 'y', 'args', 'kw']
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>>> info["defaults"]
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(1, 2)
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>>> info["signature"]
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'self, x, y, *args, **kw'
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"""
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assert inspect.ismethod(func) or inspect.isfunction(func)
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if sys.version_info[0] >= 3:
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argspec = inspect.getfullargspec(func)
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else:
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argspec = inspect.getargspec(func)
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regargs, varargs, varkwargs, defaults = argspec[:4]
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argnames = list(regargs)
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if varargs:
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argnames.append(varargs)
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if varkwargs:
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argnames.append(varkwargs)
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signature = inspect.formatargspec(regargs, varargs, varkwargs, defaults,
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formatvalue=lambda value: "")[1:-1]
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# pypy compatibility
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if hasattr(func, '__closure__'):
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_closure = func.__closure__
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_globals = func.__globals__
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else:
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_closure = func.func_closure
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_globals = func.func_globals
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return dict(name=func.__name__, argnames=argnames, signature=signature,
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defaults = func.__defaults__, doc=func.__doc__,
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module=func.__module__, dict=func.__dict__,
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globals=_globals, closure=_closure)
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# akin to functools.update_wrapper
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def update_wrapper(wrapper, model, infodict=None):
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infodict = infodict or getinfo(model)
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wrapper.__name__ = infodict['name']
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wrapper.__doc__ = infodict['doc']
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wrapper.__module__ = infodict['module']
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wrapper.__dict__.update(infodict['dict'])
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wrapper.__defaults__ = infodict['defaults']
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wrapper.undecorated = model
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return wrapper
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def new_wrapper(wrapper, model):
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"""
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An improvement over functools.update_wrapper. The wrapper is a generic
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callable object. It works by generating a copy of the wrapper with the
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right signature and by updating the copy, not the original.
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Moreovoer, 'model' can be a dictionary with keys 'name', 'doc', 'module',
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'dict', 'defaults'.
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"""
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if isinstance(model, dict):
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infodict = model
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else: # assume model is a function
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infodict = getinfo(model)
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assert not '_wrapper_' in infodict["argnames"], (
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'"_wrapper_" is a reserved argument name!')
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src = "lambda %(signature)s: _wrapper_(%(signature)s)" % infodict
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funcopy = eval(src, dict(_wrapper_=wrapper))
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return update_wrapper(funcopy, model, infodict)
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# helper used in decorator_factory
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def __call__(self, func):
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return new_wrapper(lambda *a, **k : self.call(func, *a, **k), func)
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def decorator_factory(cls):
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"""
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Take a class with a ``.caller`` method and return a callable decorator
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object. It works by adding a suitable __call__ method to the class;
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it raises a TypeError if the class already has a nontrivial __call__
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method.
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"""
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attrs = set(dir(cls))
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if '__call__' in attrs:
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raise TypeError('You cannot decorate a class with a nontrivial '
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'__call__ method')
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if 'call' not in attrs:
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raise TypeError('You cannot decorate a class without a '
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'.call method')
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cls.__call__ = __call__
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return cls
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def decorator(caller):
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"""
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General purpose decorator factory: takes a caller function as
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input and returns a decorator with the same attributes.
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A caller function is any function like this::
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def caller(func, *args, **kw):
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# do something
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return func(*args, **kw)
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Here is an example of usage:
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>>> @decorator
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... def chatty(f, *args, **kw):
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... print("Calling %r" % f.__name__)
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... return f(*args, **kw)
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>>> chatty.__name__
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'chatty'
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>>> @chatty
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... def f(): pass
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...
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>>> f()
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Calling 'f'
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decorator can also take in input a class with a .caller method; in this
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case it converts the class into a factory of callable decorator objects.
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See the documentation for an example.
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"""
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if inspect.isclass(caller):
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return decorator_factory(caller)
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def _decorator(func): # the real meat is here
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infodict = getinfo(func)
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argnames = infodict['argnames']
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assert not ('_call_' in argnames or '_func_' in argnames), (
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'You cannot use _call_ or _func_ as argument names!')
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src = "lambda %(signature)s: _call_(_func_, %(signature)s)" % infodict
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# import sys; print >> sys.stderr, src # for debugging purposes
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dec_func = eval(src, dict(_func_=func, _call_=caller))
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return update_wrapper(dec_func, func, infodict)
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return update_wrapper(_decorator, caller)
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def getattr_(obj, name, default_thunk):
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"Similar to .setdefault in dictionaries."
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try:
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return getattr(obj, name)
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except AttributeError:
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default = default_thunk()
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setattr(obj, name, default)
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return default
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@decorator
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def memoize(func, *args):
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dic = getattr_(func, "memoize_dic", dict)
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# memoize_dic is created at the first call
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if args in dic:
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return dic[args]
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else:
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result = func(*args)
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dic[args] = result
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return result
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########################## LEGALESE ###############################
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## Redistributions of source code must retain the above copyright
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## notice, this list of conditions and the following disclaimer.
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## Redistributions in bytecode form must reproduce the above copyright
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## notice, this list of conditions and the following disclaimer in
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## the documentation and/or other materials provided with the
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## distribution.
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## THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
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## "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
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## LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
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## A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
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## HOLDERS OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
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## INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
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## BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS
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## OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
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## ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR
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## TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE
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## USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH
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## DAMAGE.
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