copy
— Shallow and deep copy operations¶
Source code: Lib/copy.py
Assignment statements in Python do not copy objects, they create bindings between a target and an object. For collections that are mutable or contain mutable items, a copy is sometimes needed so one can change one copy without changing the other. This module provides generic shallow and deep copy operations (explained below).
Interface summary:
- copy.copy(obj)¶
Return a shallow copy of obj.
- copy.deepcopy(obj[, memo])¶
Return a deep copy of obj.
- copy.replace(obj, /, **changes)¶
Creates a new object of the same type as obj, replacing fields with values from changes.
New in version 3.13.
- exception copy.Error¶
Raised for module specific errors.
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 references into it to the objects found in the original.
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:
Recursive objects (compound objects that, directly or indirectly, contain a reference to themselves) may cause a recursive loop.
Because deep copy copies everything it may copy too much, such as data which is intended to be shared between copies.
The deepcopy()
function avoids these problems by:
keeping a
memo
dictionary of objects already copied during the current copying pass; andletting user-defined classes override the copying operation or the set of components copied.
This module does not copy types like module, method, stack trace, stack frame,
file, socket, window, or any similar types. It does “copy” functions and
classes (shallow and deeply), by returning the original object unchanged; this
is compatible with the way these are treated by the pickle
module.
Shallow copies of dictionaries can be made using dict.copy()
, and
of lists by assigning a slice of the entire list, for example,
copied_list = original_list[:]
.
Classes can use the same interfaces to control copying that they use to control
pickling. See the description of module pickle
for information on these
methods. In fact, the copy
module uses the registered
pickle functions from the copyreg
module.
In order for a class to define its own copy implementation, it can define
special methods __copy__()
and __deepcopy__()
.
- object.__copy__(self)¶
Called to implement the shallow copy operation; no additional arguments are passed.
- object.__deepcopy__(self, memo)¶
Called to implement the deep copy operation; it is passed one argument, the memo dictionary. If the
__deepcopy__
implementation needs to make a deep copy of a component, it should call thedeepcopy()
function with the component as first argument and the memo dictionary as second argument. The memo dictionary should be treated as an opaque object.
Function copy.replace()
is more limited
than copy()
and deepcopy()
,
and only supports named tuples created by namedtuple()
,
dataclasses
, and other classes which define method __replace__()
.
- object.__replace__(self, /, **changes)¶
This method should create a new object of the same type, replacing fields with values from changes.
See also
- Module
pickle
Discussion of the special methods used to support object state retrieval and restoration.