"""Generic (shallow and deep) copying operations.

Interface summary:

import copy

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__`

For module specific errors, copy.Error is raised.

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

extent possible) inserts *the same objects* into it that the

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,

contain a reference to themselves) may cause a recursive loop

b) because deep copy copies *everything* it may copy too much, e.g.

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

b) letting user-defined classes override the copying operation or the

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.

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

"pickle" for information on these methods.

"""

import types

import weakref

from copyreg import dispatch_table

class Error(Exception):

pass

error = Error # backward compatibility

__all__ = ["Error", "copy", "deepcopy", "replace"]

def copy(x):

"""Shallow copy operation on arbitrary Python objects.

See the module's __doc__ string for more info.

"""

cls = type(x)

if cls in _copy_atomic_types:

return x

if cls in _copy_builtin_containers:

return cls.copy(x)

if issubclass(cls, type):

# treat it as a regular class:

return 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)

_copy_atomic_types = frozenset({types.NoneType, int, float, bool, complex, str, tuple,

bytes, frozendict, frozenset, type, range, slice, property,

types.BuiltinFunctionType, types.EllipsisType,

types.NotImplementedType, types.FunctionType, types.CodeType,

weakref.ref, super})

_copy_builtin_containers = frozenset({list, dict, set, bytearray})

def deepcopy(x, memo=None):

"""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)

if memo is None:

memo = {}

else:

y = memo.get(d, None)

if y is not None:

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

return y

_atomic_types = frozenset({types.NoneType, types.EllipsisType, types.NotImplementedType,

int, float, bool, complex, bytes, str, types.CodeType, type, range,

types.BuiltinFunctionType, types.FunctionType, weakref.ref, property})

_deepcopy_dispatch = d = {}

def _deepcopy_list(x, memo, deepcopy=deepcopy):

y = []

memo[id(x)] = y

append = y.append

for a in x:

append(deepcopy(a, memo))

return y

d[list] = _deepcopy_list

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.

try:

return memo[id(x)]

except KeyError:

pass

for k, j in zip(x, y):

if k is not j:

y = tuple(y)

break

else:

y = x

return y

d[tuple] = _deepcopy_tuple

def _deepcopy_dict(x, memo, deepcopy=deepcopy):

y = {}

memo[id(x)] = y

for key, value in x.items():

y[deepcopy(key, memo)] = deepcopy(value, memo)

return y

d[dict] = _deepcopy_dict

def _deepcopy_frozendict(x, memo, deepcopy=deepcopy):

y = {}

for key, value in x.items():

y[deepcopy(key, memo)] = deepcopy(value, memo)

# We're not going to put the frozendict in the memo, but it's still

# important we check for it, in case the frozendict contains recursive

# mutable structures.

try:

return memo[id(x)]

except KeyError:

pass

return frozendict(y)

d[frozendict] = _deepcopy_frozendict

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):

"""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)