cpython/Lib/copy.py

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