python-peps/pep-0203.txt

PEP: 203
Title: Augmented Assignments
Version: $Revision$
Owner: thomas@xs4all.net (Thomas Wouters)
Python-Version: 2.0
Status: Incomplete



Introduction

    This PEP describes the `augmented assignment' proposal for Python
    2.0.  This PEP tracks the status and ownership of this feature,
    slated for introduction in Python 2.0.  It contains a description
    of the feature and outlines changes necessary to support the
    feature.  This PEP summarizes discussions held in mailing list
    forums, and provides URLs for further information, where
    appropriate.  The CVS revision history of this file contains the
    definitive historical record.



The Origin of Augmented Assignment

    Augmented assignment refers to binary operators that combine two
    existing operators: the assignment operator, and one of the binary
    operators. Its origins lie in other programming languages, most
    notably `C', where it was defined for performance reasons. They
    are meant to replace the repetetive syntax of, for instance,
    adding the number '1' to a variable:
    
      x = x + 1;
      
    with an expression that is shorter, less error-prone and easier to
    optimize (by the compiler):
    
      x += 1;
      
    The same goes for all other binary operands, resulting in the
    following augmented assignment operator list, based on Python's
    current binary operator list:

      +=, -=, /=, *=, %=, **=, >>=, <<=, &=, |=, ^=
    
    See the documentation of each operator on what they do.

     

Augmented Assignment in Python

    The traditional reasons for augmented assignment, readability and
    optimization, are not as obvious in Python, for several reasons.
    
     - Numbers are immutable, they cannot be changed. In other
       programming languages, a variable holds a value, and altering
       the variable changes the value it holds. In Python, variables
       hold `references' to values, and altering an immutable value
       means changing the variable, not what it points to.

     - Assignment is a different operation in Python. In most
       languages, variables are containers, and assignment copies a
       value into that container. In Python, assignment binds a value
       to a name, it does not copy the value into a new storage space.
       
     - The augmented assignment operators map fairly directly into the
       underlying hardware. Python does not deal directly with the
       hardware it runs on, so this `natural inclusion' does not make
       sense.

     - The augmented assigment syntax is subtly different in more
       complex expressions. What to do, for instance, in a case such
       as this:
       
       seq[i:calc(seq, i)] *= r
       
       It is unclear whether 'seq' gets indexed once or twice, and
       whether 'calc' gets called once or twice.



Normal operators

    There are, however, good reasons to include augented assignment. 
    One of these has to do with Python's way of handling operators. In
    Python, a user defined class can implement one or more of the
    binary operators by supplying a 'magic' method name. For instance,
    for a class to support '<instance> + <object>', the '__add__'
    method should be defined. This method should return a new object,
    which is the result of the expression.
    
    For the case of '<object> + <instance>', where 'object' does not
    have an '__add__' method, the class can define a '__radd__'
    method, which then should behave exactly as '__add__'. Indeed,
    '__radd__' is often a different name for the same method.
    
    For C extention types, a similar technique is available, through
    the PyNumberMethods and PySequenceMethods members of the PyType
    structure.

    However, the problem with this approach is that the '__add__'
    method cannot know in what context it is called. It cannot tell
    whether it should create a new object, or whether it is allowed to
    modify itself. (As would be the case in 'x = x + 1') As a result,
    the '__add__' method, and all other such 'magic' methods, should
    always return a new object. For large objects, this can be very
    inefficient.
    
    This inefficiency is often solved by adding a method that does the
    appropriate modification 'in-place'. List objects, for instance,
    have the 'extend' method that behaves exactly as the '+' operator,
    except the operation is done on the list itself, instead of on a
    copy.

    The augmented assignment syntax can support this behaviour
    explicitly. When the magic method for 'in-place' operation are
    missing, it can fall back to the normal methods for that
    operation, maintaining full backward compatibility even when
    mixing the new syntax with old objects.

    The other benifit of augmented assignment is readability. After
    the general concept of augmented assignment is grasped, all the
    augmented assigment operators instantly become obvious. There is
    no need for non-obvious and non-standard method names to implement
    efficient, in-place operations, and there is no need to check the
    type of an object before operating on it: the augmented assignment
    will work for all types that implement that basic operation, not
    merely those that implement the augmented variant.
    
    And the last problem with augmented assignment, what to do with
    indexes and function calls in the expression, can be solved in a
    very Pythonic manner: if it looks like it's only called once, it
    *is* only called once. Taking this expression:
    
    seq[func(x)] += x
    
    The function 'func' is called once, and 'seq' is indexed twice:
    once to retrieve the value (__getitem__), and once to store it
    (__setitem__). So the expression can be rewritten as:
    
    tmp = func(x)
    seq[tmp] = seq[tmp] + x
    
    The augmented assignment form of this expression is much more
    readable.
    






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