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k
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Z x] e d e e e e e e e e e e j e j e e e j e j f D] Z e e e <qï Wx9 d D]1 Z e! e e d Z e d k r
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e e e <q
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Wd Z" x! e# e$ e% f D] Z e" e e <qXWd Z& e d k re& e e <n d Z' e' e e j( <[ d g d Z) i 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- k
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r2n Xe+ e e <y e+ e e. <Wn e- k
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r^n Xy e+ e e j/ <Wn e0 k
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rn Xe+ e e <e+ e e <e+ e e j <e+ e e j <e+ e e j <e+ e e j <d Z1 e1 e e# <d Z2 e2 e e <d Z3 e3 e e$ <e d k r e3 e e <n d Z4 e4 e* e j5 <d Z6 d Z7 e7 e e j( <d d Z8 [ [ d d d YZ9 d Z: e; d k re: n d S( sÍ 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
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x = copy.deepcopy(y) # make a deep copy of y
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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
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compound objects (objects that contain other objects, like lists or
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class instances).
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- 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.
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- A deep copy constructs a new compound object and then, recursively,
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inserts *copies* into it of the objects found in the original.
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Two problems often exist with deep copy operations that don't exist
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with shallow copy operations:
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a) recursive objects (compound objects that, directly or indirectly,
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contain a reference to themselves) may cause a recursive loop
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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
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copies
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Python's deep copy operation avoids these problems by:
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a) keeping a table of objects already copied during the current
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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
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This version does not copy types like module, class, function, method,
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nor stack trace, stack frame, nor file, socket, window, nor array, nor
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any similar types.
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Classes can use the same interfaces to control copying that they use
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to control pickling: they can define methods called __getinitargs__(),
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__getstate__() and __setstate__(). See the documentation for module
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"pickle" for information on these methods.
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iÿÿÿÿN( t dispatch_tablet Errorc B s e Z RS( ( t __name__t
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__module__( ( ( sL /tmp/ndk-User/buildhost/install/prebuilt/darwin-x86_64/lib/python2.7/copy.pyR 7 s ( t PyStringMapt copyt deepcopyc C sÜ t | } t j | } | r+ | | St | d d } | rM | | St j | } | rq | | } n[ t | d d } | r | d } n4 t | d d } | r¼ | } 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
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C s | d k r i } n t | } | j | | } | | k rC | St | } t j | } | rv | | | } n y t | t } Wn t k
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d | t | | d | } | | | <t | | | S( si Deep copy operation on arbitrary Python objects.
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|
See the module's __doc__ string for more info.
|
i t __deepcopy__R i R s" un(deep)copyable object of type %si N( R t idR R
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c C s( t | | j t | j | | j S( N( R
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t im_funcR t im_selft im_class( R R. ( ( sL /tmp/ndk-User/buildhost/install/prebuilt/darwin-x86_64/lib/python2.7/copy.pyt _deepcopy_method s c C sF y | t | j | Wn$ t k
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rA | 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...
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3
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7 ?
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