copy — Shallow and deep copy operations

地址：http://docs.python.org/3/library/copy.html

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).

>>> import copy

>>> d = {'user':'lq', 'name':['huhu','hengheng']}

>>> d

{'name': ['huhu', 'hengheng'], 'user': 'lq'}

>>> d1 = copy.copy(d)

>>> d2 = copy.copy(d)

>>> d1

{'user': 'lq', 'name': ['huhu', 'hengheng']}

>>> d2

{'user': 'lq', 'name': ['huhu', 'hengheng']}

>>> d1['name'].append('huahua')

>>> d1

{'user': 'lq', 'name': ['huhu', 'hengheng', 'huahua']}

>>> d2

{'user': 'lq', 'name': ['huhu', 'hengheng', 'huahua']}

>>> d

{'name': ['huhu', 'hengheng', 'huahua'], 'user': 'lq'}

>>> 

Interface summary:

copy. copy ( x )

Return a shallow copy of x.

copy. deepcopy ( x )

Return a deep copy of x.

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.

>>> d

{'name': ['huhu', 'hengheng', 'huahua'], 'user': 'lq'}

>>> d3 = copy.deepcopy(d)

>>> d4 = copy.deepcopy(d)

>>> d3

{'user': 'lq', 'name': ['huhu', 'hengheng', 'huahua']}

>>> d4

{'user': 'lq', 'name': ['huhu', 'hengheng', 'huahua']}

>>> d3['name'].remove('huahua')

>>> d3

{'user': 'lq', 'name': ['huhu', 'hengheng']}

>>> d4

{'user': 'lq', 'name': ['huhu', 'hengheng', 'huahua']}

>>> d

{'name': ['huhu', 'hengheng', 'huahua'], 'user': 'lq'}

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, e.g., administrative data structures that should be shared even between copies.

The deepcopy() function avoids these problems by:

• keeping a “memo” dictionary of objects already copied during the current copying pass; and
• letting 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, array, 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, copy module uses the registered pickle functions from copyreg module.

In order for a class to define its own copy implementation, it can define special methods __copy__() and __deepcopy__(). The former is called to implement the shallow copy operation; no additional arguments are passed. The latter is 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 the deepcopy() function with the component as first argument and the memo dictionary as second argument.