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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.
		
			
				
	
	
		
			295 lines
		
	
	
	
		
			8.5 KiB
		
	
	
	
		
			Python
		
	
	
	
	
	
			
		
		
	
	
			295 lines
		
	
	
	
		
			8.5 KiB
		
	
	
	
		
			Python
		
	
	
	
	
	
| """Generic (shallow and deep) copying operations.
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| 
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| Interface summary:
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| 
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|         import copy
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| 
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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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| 
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| For module specific errors, copy.Error is raised.
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| 
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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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| 
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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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| 
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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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| 
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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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| 
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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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| 
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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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| 
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| Python's deep copy operation avoids these problems by:
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| 
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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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| 
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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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| 
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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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| 
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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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| 
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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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| 
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| class Error(Exception):
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|     pass
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| error = Error   # backward compatibility
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| 
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| __all__ = ["Error", "copy", "deepcopy", "replace"]
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| 
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| def copy(x):
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|     """Shallow copy operation on arbitrary Python objects.
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| 
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|     See the module's __doc__ string for more info.
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|     """
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| 
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|     cls = type(x)
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| 
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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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| 
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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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| 
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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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| 
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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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| 
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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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| 
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| 
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| _copy_dispatch = d = {}
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| 
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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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| 
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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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| 
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| del d, t
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| 
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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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| 
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|     See the module's __doc__ string for more info.
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|     """
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| 
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|     cls = type(x)
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| 
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|     if cls in _atomic_types:
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|         return x
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| 
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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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| 
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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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| 
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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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| 
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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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| 
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| _deepcopy_dispatch = d = {}
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| 
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| 
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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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| 
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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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| 
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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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| 
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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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| 
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| del d
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| 
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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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| 
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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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| 
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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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| 
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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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| 
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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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| 
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| del types, weakref
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| 
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| 
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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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| 
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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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