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15.6: Copying

  • Page ID
    40820
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    Aliasing can make a program difficult to read because changes in one place might have unexpected effects in another place. It is hard to keep track of all the variables that might refer to a given object.

    Copying an object is often an alternative to aliasing. The copy module contains a function called copy that can duplicate any object:

    >>> p1 = Point()
    >>> p1.x = 3.0
    >>> p1.y = 4.0
    
    >>> import copy
    >>> p2 = copy.copy(p1)
    

    p1 and p2 contain the same data, but they are not the same Point.

    >>> print_point(p1)
    (3, 4)
    >>> print_point(p2)
    (3, 4)
    >>> p1 is p2
    False
    >>> p1 == p2
    False
    

    The is operator indicates that p1 and p2 are not the same object, which is what we expected. But you might have expected == to yield True because these points contain the same data. In that case, you will be disappointed to learn that for instances, the default behavior of the == operator is the same as the is operator; it checks object identity, not object equivalence. That’s because for programmer-defined types, Python doesn’t know what should be considered equivalent. At least, not yet.

    If you use copy.copy to duplicate a Rectangle, you will find that it copies the Rectangle object but not the embedded Point.

    >>> box2 = copy.copy(box)
    >>> box2 is box
    False
    >>> box2.corner is box.corner
    True
    Object diagram.
    Figure \(\PageIndex{1}\): Object diagram.

    Figure \(\PageIndex{1}\) shows what the object diagram looks like. This operation is called a shallow copy because it copies the object and any references it contains, but not the embedded objects.

    For most applications, this is not what you want. In this example, invoking grow_rectangle on one of the Rectangles would not affect the other, but invoking move_rectangle on either would affect both! This behavior is confusing and error-prone.

    Fortunately, the copy module provides a method named deepcopy that copies not only the object but also the objects it refers to, and the objects they refer to, and so on. You will not be surprised to learn that this operation is called a deep copy.

    >>> box3 = copy.deepcopy(box)
    >>> box3 is box
    False
    >>> box3.corner is box.corner
    False
    

    box3 and box are completely separate objects.

    As an exercise, write a version of move_rectangle that creates and returns a new Rectangle instead of modifying the old one.


    This page titled 15.6: Copying is shared under a CC BY-NC 3.0 license and was authored, remixed, and/or curated by Allen B. Downey (Green Tea Press) via source content that was edited to the style and standards of the LibreTexts platform.

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