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Previously, copying a super object returned a copy of the instance invoking super(). Pickling a super object could pickle the instance invoking super() or fail, depending on its type and protocol. Now deep copying returns a new super object and pickling pickles the super object. Shallow copying returns the same super object.
296 lines
8.5 KiB
Python
296 lines
8.5 KiB
Python
"""Generic (shallow and deep) copying operations.
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Interface summary:
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import copy
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x = copy.copy(y) # make a shallow copy of y
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x = copy.deepcopy(y) # make a deep copy of y
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x = copy.replace(y, a=1, b=2) # new object with fields replaced, as defined by `__replace__`
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For module specific errors, copy.Error is raised.
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The difference between shallow and deep copying is only relevant for
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compound objects (objects that contain other objects, like lists or
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class instances).
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- A shallow copy constructs a new compound object and then (to the
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extent possible) inserts *the same objects* into it that the
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original contains.
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- A deep copy constructs a new compound object and then, recursively,
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inserts *copies* into it of the objects found in the original.
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Two problems often exist with deep copy operations that don't exist
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with shallow copy operations:
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a) recursive objects (compound objects that, directly or indirectly,
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contain a reference to themselves) may cause a recursive loop
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b) because deep copy copies *everything* it may copy too much, e.g.
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administrative data structures that should be shared even between
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copies
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Python's deep copy operation avoids these problems by:
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a) keeping a table of objects already copied during the current
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copying pass
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b) letting user-defined classes override the copying operation or the
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set of components copied
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This version does not copy types like module, class, function, method,
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nor stack trace, stack frame, nor file, socket, window, nor any
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similar types.
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Classes can use the same interfaces to control copying that they use
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to control pickling: they can define methods called __getinitargs__(),
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__getstate__() and __setstate__(). See the documentation for module
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"pickle" for information on these methods.
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"""
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import types
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import weakref
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from copyreg import dispatch_table
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class Error(Exception):
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pass
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error = Error # backward compatibility
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__all__ = ["Error", "copy", "deepcopy", "replace"]
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def copy(x):
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"""Shallow copy operation on arbitrary Python objects.
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See the module's __doc__ string for more info.
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"""
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cls = type(x)
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copier = _copy_dispatch.get(cls)
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if copier:
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return copier(x)
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if issubclass(cls, type):
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# treat it as a regular class:
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return _copy_immutable(x)
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copier = getattr(cls, "__copy__", None)
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if copier is not None:
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return copier(x)
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reductor = dispatch_table.get(cls)
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if reductor is not None:
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rv = reductor(x)
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else:
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reductor = getattr(x, "__reduce_ex__", None)
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if reductor is not None:
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rv = reductor(4)
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else:
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reductor = getattr(x, "__reduce__", None)
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if reductor:
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rv = reductor()
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else:
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raise Error("un(shallow)copyable object of type %s" % cls)
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if isinstance(rv, str):
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return x
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return _reconstruct(x, None, *rv)
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_copy_dispatch = d = {}
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def _copy_immutable(x):
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return x
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for t in (types.NoneType, int, float, bool, complex, str, tuple,
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bytes, frozenset, type, range, slice, property,
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types.BuiltinFunctionType, types.EllipsisType,
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types.NotImplementedType, types.FunctionType, types.CodeType,
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weakref.ref, super):
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d[t] = _copy_immutable
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d[list] = list.copy
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d[dict] = dict.copy
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d[set] = set.copy
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d[bytearray] = bytearray.copy
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del d, t
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def deepcopy(x, memo=None, _nil=[]):
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"""Deep copy operation on arbitrary Python objects.
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See the module's __doc__ string for more info.
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"""
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cls = type(x)
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if cls in _atomic_types:
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return x
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d = id(x)
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if memo is None:
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memo = {}
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else:
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y = memo.get(d, _nil)
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if y is not _nil:
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return y
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copier = _deepcopy_dispatch.get(cls)
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if copier is not None:
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y = copier(x, memo)
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else:
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if issubclass(cls, type):
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y = x # atomic copy
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else:
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copier = getattr(x, "__deepcopy__", None)
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if copier is not None:
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y = copier(memo)
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else:
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reductor = dispatch_table.get(cls)
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if reductor:
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rv = reductor(x)
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else:
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reductor = getattr(x, "__reduce_ex__", None)
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if reductor is not None:
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rv = reductor(4)
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else:
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reductor = getattr(x, "__reduce__", None)
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if reductor:
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rv = reductor()
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else:
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raise Error(
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"un(deep)copyable object of type %s" % cls)
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if isinstance(rv, str):
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y = x
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else:
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y = _reconstruct(x, memo, *rv)
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# If is its own copy, don't memoize.
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if y is not x:
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memo[d] = y
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_keep_alive(x, memo) # Make sure x lives at least as long as d
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return y
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_atomic_types = {types.NoneType, types.EllipsisType, types.NotImplementedType,
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int, float, bool, complex, bytes, str, types.CodeType, type, range,
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types.BuiltinFunctionType, types.FunctionType, weakref.ref, property}
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_deepcopy_dispatch = d = {}
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def _deepcopy_list(x, memo, deepcopy=deepcopy):
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y = []
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memo[id(x)] = y
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append = y.append
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for a in x:
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append(deepcopy(a, memo))
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return y
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d[list] = _deepcopy_list
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def _deepcopy_tuple(x, memo, deepcopy=deepcopy):
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y = [deepcopy(a, memo) for a in x]
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# We're not going to put the tuple in the memo, but it's still important we
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# check for it, in case the tuple contains recursive mutable structures.
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try:
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return memo[id(x)]
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except KeyError:
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pass
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for k, j in zip(x, y):
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if k is not j:
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y = tuple(y)
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break
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else:
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y = x
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return y
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d[tuple] = _deepcopy_tuple
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def _deepcopy_dict(x, memo, deepcopy=deepcopy):
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y = {}
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memo[id(x)] = y
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for key, value in x.items():
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y[deepcopy(key, memo)] = deepcopy(value, memo)
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return y
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d[dict] = _deepcopy_dict
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def _deepcopy_method(x, memo): # Copy instance methods
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return type(x)(x.__func__, deepcopy(x.__self__, memo))
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d[types.MethodType] = _deepcopy_method
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del d
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def _keep_alive(x, memo):
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"""Keeps a reference to the object x in the memo.
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Because we remember objects by their id, we have
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to assure that possibly temporary objects are kept
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alive by referencing them.
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We store a reference at the id of the memo, which should
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normally not be used unless someone tries to deepcopy
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the memo itself...
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"""
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try:
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memo[id(memo)].append(x)
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except KeyError:
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# aha, this is the first one :-)
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memo[id(memo)]=[x]
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def _reconstruct(x, memo, func, args,
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state=None, listiter=None, dictiter=None,
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*, deepcopy=deepcopy):
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deep = memo is not None
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if deep and args:
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args = (deepcopy(arg, memo) for arg in args)
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y = func(*args)
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if deep:
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memo[id(x)] = y
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if state is not None:
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if deep:
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state = deepcopy(state, memo)
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if hasattr(y, '__setstate__'):
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y.__setstate__(state)
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else:
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if isinstance(state, tuple) and len(state) == 2:
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state, slotstate = state
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else:
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slotstate = None
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if state is not None:
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y.__dict__.update(state)
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if slotstate is not None:
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for key, value in slotstate.items():
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setattr(y, key, value)
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if listiter is not None:
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if deep:
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for item in listiter:
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item = deepcopy(item, memo)
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y.append(item)
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else:
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for item in listiter:
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y.append(item)
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if dictiter is not None:
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if deep:
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for key, value in dictiter:
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key = deepcopy(key, memo)
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value = deepcopy(value, memo)
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y[key] = value
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else:
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for key, value in dictiter:
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y[key] = value
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return y
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del types, weakref
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def replace(obj, /, **changes):
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"""Return a new object replacing specified fields with new values.
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This is especially useful for immutable objects, like named tuples or
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frozen dataclasses.
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"""
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cls = obj.__class__
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func = getattr(cls, '__replace__', None)
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if func is None:
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raise TypeError(f"replace() does not support {cls.__name__} objects")
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return func(obj, **changes)
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