pep-0203.txt

PEP: 203
Title: Augmented Assignments
Version: $Revision$
Author: thomas@xs4all.net (Thomas Wouters)
Status: Draft
Type: Standards Track
Python-Version: 2.0
Created: 13-Jul-2000
Post-History: 14-Aug-2000


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.


Proposed semantics

    The proposed patch that adds augmented assignment to Python
    introduces the following new operators:
    
       += -= *= /= %= **= <<= >>= &= ^= |=
    
    They implement the same operator as their normal binary form,
    except that the operation is done `in-place' when the left-hand
    side object supports it, and that the left-hand side is only
    evaluated once.
    
    They truly behave as augmented assignment, in that they perform
    all of the normal load and store operations, in addition to the
    binary operation they are intended to do. So, given the expression:
    
       x += y
    
    The object `x' is loaded, then `y' is added to it, and the
    resulting object is stored back in the original place. The precise
    action performed on the two arguments depends on the type of `x',
    and possibly of `y'.

    The idea behind augmented assignment in Python is that it isn't
    just an easier way to write the common practice of storing the
    result of a binary operation in its left-hand operand, but also a
    way for the left-hand operand in question to know that it should
    operate `on itself', rather than creating a modified copy of
    itself.

    To make this possible, a number of new `hooks' are added to Python
    classes and C extension types, which are called when the object in
    question is used as the left hand side of an augmented assignment
    operation. If the class or type does not implement the `in-place'
    hooks, the normal hooks for the particular binary operation are
    used.
    
    So, given an instance object `x', the expression
    
        x += y
    
    tries to call x.__add_ab__(y), which is the `in-place' variant of
    __add__. If __add_ab__ is not present, x.__add__(y) is
    attempted, and finally y.__radd__(x) if __add__ is missing too. 
    There is no `right-hand-side' variant of __add_ab__, because that
    would require for `y' to know how to in-place modify `x', which is
    unsafe to say the least. The __add_ab__ hook should behave similar
    to __add__, returning the result of the operation (which could be
    `self') which is to be stored in the variable `x'.
 
    For C extension types, the `hooks' are members of the
    PyNumberMethods and PySequenceMethods structures, and are called
    in exactly the same manner as the existing non-inplace operations,
    including argument coercion. C methods should also take care to
    return a new reference to the result object, whether it's the same
    object or a new one. So if the original object is returned, it
    should be INCREF()'d appropriately.


Rationale

    There are two main reasons for adding this feature to Python:
    simplicity of expression, and support for in-place operations. The
    end result is a tradeoff between simplicity of syntax and
    simplicity of expression; like most new features, augmented
    assignment doesn't add anything that was previously impossible. It
    merely makes these things easier to do.
    
    Adding augmented assignment will make Python's syntax more complex. 
    Instead of a single assignment operation, there are now twelve
    assignment operations, eleven of which also perform an binary
    operation. However, these eleven new forms of assignment are easy
    to understand as the coupling between assignment and the binary
    operation, and they require no large conceptual leap to
    understand. Furthermore, languages that do have augmented
    assignment have shown that they are a popular, much used feature.
    Expressions of the form
    
        <x> = <x> <operator> <y>
        
    are common enough in those languages to make the extra syntax
    worthwhile, and Python does not have significantly fewer of those
    expressions. Quite the opposite, in fact, since in Python you can
    also concatenate lists with a binary operator, something that is
    done quite frequently. Writing the above expression as
    
        <x> <operator>= <y> 
    
    is both more readable and less error prone, because it is
    instantly obvious to the reader that it is <x> that is being
    changed, and not <x> that is being replaced by something almost,
    but not quite, entirely unlike <x>.
    
    The new in-place operations are especially useful to matrix
    calculation and other applications that require large objects. In
    order to efficiently deal with the available program memory, such
    packages cannot blindly use the current binary operations. Because
    these operations always create a new object, adding a single item
    to an existing (large) object would result in copying the entire
    object (which may cause the application to run out of memory), add
    the single item, and then possibly delete the original object,
    depending on reference count.
    
    To work around this problem, the packages currently have to use
    methods or functions to modify an object in-place, which is
    definitely less readable than an augmented assignment expression. 
    Augmented assignment won't solve all the problems for these
    packages, since some operations cannot be expressed in the limited
    set of binary operators to start with, but it is a start. A
    different PEP[3] is looking at adding new operators.


New methods

    The proposed implementation adds the following 11 possible `hooks'
    which Python classes can implement to overload the augmented
    assignment operations:
    
        __add_ab__
        __sub_ab__
        __mul_ab__
        __div_ab__
        __mod_ab__
        __pow_ab__
        __lshift_ab__
        __rshift_ab__
        __and_ab__
        __xor_ab__
        __or_ab__
    
    The `__add_ab__' name is one proposed by Guido[1], and stands for
    `and becomes'. Other proposed names include `__iadd__',
    `__add_in__' and `__inplace_add__'. A firm decision by the BDFL is
    probably needed to finalize this issue.

    For C extension types, the following struct members are added:
    
    To PyNumberMethods:
        binaryfunc nb_inplace_add;
        binaryfunc nb_inplace_subtract;
        binaryfunc nb_inplace_multiply;
        binaryfunc nb_inplace_divide;
        binaryfunc nb_inplace_remainder;
        binaryfunc nb_inplace_power;
        binaryfunc nb_inplace_lshift;
        binaryfunc nb_inplace_rshift;
        binaryfunc nb_inplace_and;
        binaryfunc nb_inplace_xor;
        binaryfunc nb_inplace_or;

    To PySequenceMethods:
        binaryfunc sq_inplace_concat;
        intargfunc sq_inplace_repeat;

    In order to keep binary compatibility, the tp_flags TypeObject
    member is used to determine whether the TypeObject in question has
    allocated room for these slots. Until a clean break in binary
    compatibility is made (which may or may not happen before 2.0)
    code that wants to use one of the new struct members must first
    check that they are available with the `PyType_HasFeature()'
    macro:
    
    if (PyType_HasFeature(x->ob_type, Py_TPFLAGS_HAVE_INPLACE_OPS) &&
        x->ob_type->tp_as_number && x->ob_type->tp_as_number->nb_inplace_add) {
            /* ... */

    This check must be made even before testing the method slots for
    NULL values! The macro only tests whether the slots are available,
    not whether they are filled with methods or not.


Implementation

    The current implementation of augmented assignment[2] adds, in
    addition to the methods and slots already covered, 13 new bytecodes
    and 13 new API functions.
    
    The API functions are simply in-place versions of the current
    binary-operation API functions:
    
        PyNumber_InPlaceAdd(PyObject *o1, PyObject *o2);
        PyNumber_InPlaceSubtract(PyObject *o1, PyObject *o2);
        PyNumber_InPlaceMultiply(PyObject *o1, PyObject *o2);
        PyNumber_InPlaceDivide(PyObject *o1, PyObject *o2);
        PyNumber_InPlaceRemainder(PyObject *o1, PyObject *o2);
        PyNumber_InPlacePower(PyObject *o1, PyObject *o2);
        PyNumber_InPlaceLshift(PyObject *o1, PyObject *o2);
        PyNumber_InPlaceRshift(PyObject *o1, PyObject *o2);
        PyNumber_InPlaceAnd(PyObject *o1, PyObject *o2);
        PyNumber_InPlaceXor(PyObject *o1, PyObject *o2);
        PyNumber_InPlaceOr(PyObject *o1, PyObject *o2);
        PySequence_InPlaceConcat(PyObject *o1, PyObject *o2);
        PySequence_InPlaceRepeat(PyObject *o, int count);

    They call either the Python class hooks (if either of the objects
    is a Python class instance) or the C type's number or sequence
    methods.

    The new bytecodes are:
        INPLACE_ADD
        INPLACE_SUBTRACT
        INPLACE_MULTIPLY
        INPLACE_DIVIDE
        INPLACE_REMAINDER
        INPLACE_POWER
        INPLACE_LEFTSHIFT
        INPLACE_RIGHTSHIFT
        INPLACE_AND
        INPLACE_XOR
        INPLACE_OR
        ROT_FOUR
        DUP_TOPX
    
    The INPLACE_* bytecodes mirror the BINARY_* bytecodes, except that
    they are implemented as calls to the `InPlace' API functions. The
    other two bytecodes are `utility' bytecodes: ROT_FOUR behaves like
    ROT_THREE except that the four topmost stack items are rotated.
    
    DUP_TOPX is a bytecode that takes a single argument, which should
    be an integer between 1 and 5 (inclusive) which is the number of
    items to duplicate in one block. Given a stack like this (where
    the right side of the list is the `top' of the stack):

        [1, 2, 3, 4, 5]
    
    "DUP_TOPX 3" would duplicate the top 3 items, resulting in this
    stack:
    
        [1, 2, 3, 4, 5, 3, 4, 5]

    DUP_TOPX with an argument of 1 is the same as DUP_TOP. The limit
    of 5 is purely an implementation limit. The implementation of
    augmented assignment requires only DUP_TOPX with an argument of 2
    and 3, and could do without this new opcode at the cost of a fair
    number of DUP_TOP and ROT_*.


Open Issues

    The PyNumber_InPlacePower() function only takes two arguments, not
    one like PyNumber_Power(). This is because there is no way to do
    an inplace three-argument-power trough the augmented assignment
    syntax or the power() function.
    

    Possibly a more obvious name for the Python hooks can be found. 
    `_ab_' is what Guido proposed[1] as a working name, and comes from
    an old Algol-68 naming convention.


    Documentation needs to be written. The reference manual, the `dis'
    section of the library manual, and possibly the tutorial.
    

    The DUP_TOPX bytecode is a conveniency bytecode, and is not
    actually necessary. It should be considered whether this bytecode
    is worth having. There seems to be no other possible use for this
    bytecode at this time.
    

    The standard library should be adjusted to provide augmented
    assignment hooks, where sensible.


    It is not possible to do an inplace operation in the variant of
    
       <builtin type> += <instance object>

    Instead, the instance objects' __radd__ hook is called, with the
    builtin type as argument. The same goes for the other operations.
    It might necessary to add a right-hand version of __add_ab__ after
    all, to support something like that.


Copyright

    This document has been placed in the public domain.


References

    [1] http://www.python.org/pipermail/python-list/2000-June/059556.html
    [2]
http://sourceforge.net/patch?func=detailpatch&patch_id=100699&group_id=5470
    [3] PEP 211, Adding New Linear Algebra Operators,
        http://python.sourceforge.net/peps/pep-0211.html



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