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| Filename | /usr/lib64/python2.6/copy.pyo |
| Size | 11.31 kb |
| Permission | rw-r--r-- |
| Owner | apache |
| Create time | 23-Dec-2025 17:41 |
| Last modified | 20-Jun-2019 19:45 |
| Last accessed | 22-Apr-2026 05:32 |
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o n Xe) e e <e) e e <e) e e i <e) e e i <e) e e i <d � Z/ e/ e e! <d � Z0 e0 e e <d � Z1 e1 e e" <e d j o e1 e e <n d � Z2 e2 e( e i3 <d � Z4 d � Z5 e5 e e i& <d d � Z6 [ [ d d d � � YZ7 d � Z8 e9 d j o e8 � n d S( sÍ 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
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 array, 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.
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See the module's __doc__ string for more info.
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See the module's __doc__ string for more info.
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Because we remember objects by their id, we have
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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...
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§ÚêLc @ s� d Z d d k Z d d k l Z d e f d � � YZ e Z y d d k l Z Wn e j
o
d Z n Xd d d g Z d � Z h Z
Z d
� Z xW e d � e e e e e e e e e e i e i e e � e i f D] Z e e e <qß Wx; d D]3 Z e e e d � Z e d j o e e e <qú qú Wd � Z x! e! e" e# f D] Z e e e <qJWd � Z$ e d j o e$ e e <n d � Z% e% e e i& <[ d g d � Z' h Z( Z d � Z) e) e e d � <e) e e e � <e) e e <e) e e <e) e e <e) e e <y e) e e* <Wn e+ j
o n Xe) e e <y e) e e, <Wn e+ j
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o n Xe) e e <e) e e <e) e e i <e) e e i <e) e e i <d � Z/ e/ e e! <d � Z0 e0 e e <d � Z1 e1 e e" <e d j o e1 e e <n d � Z2 e2 e( e i3 <d � Z4 d � Z5 e5 e e i& <d d � Z6 [ [ d d d � � YZ7 d � Z8 e9 d j o e8 � n d S( sÍ 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
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 array, 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.
iÿÿÿÿN( t dispatch_tablet Errorc B s e Z RS( ( t __name__t
__module__( ( ( s /usr/lib64/python2.6/copy.pyR 6 s ( t PyStringMapt copyt deepcopyc C sæ t | � } t i | � } | o | | � St | d d � } | o | | � St i | � } | o | | � } n` t | d d � } | o | d � } n7 t | d d � } | o
| � } n t d | � � t | | d � S( sl Shallow copy operation on arbitrary Python objects.
See the module's __doc__ string for more info.
t __copy__t
__reduce_ex__i t
__reduce__s% un(shallow)copyable object of type %si N( t typet _copy_dispatcht gett getattrt NoneR R t _reconstruct( t xt clst copiert reductort rv( ( s /usr/lib64/python2.6/copy.pyR A s$
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See the module's __doc__ string for more info.
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o | g | t | � <n Xd S( sM 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...
N( R( R2 R5 ( R R. ( ( s /usr/lib64/python2.6/copy.pyR- s
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