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.__iadd__(y), which is the `in-place' variant of
__add__. If __iadd__ 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 __iadd__, because that would require
for `y' to know how to in-place modify `x', which is unsafe to say
the least. The __iadd__ hook should behave similar to __add__,
returning the result of the operation (which could be `self')
which is to be assigned to the variable `x'.
For C extension types, the `hooks' are members of the
PyNumberMethods and PySequenceMethods structures. Some special
semantics apply to make the use of these methods, and the mixing
of Python instance objects and C types, as unsurprising as
possible.
In the generic case of `x <augop> y' (or a similar case using the
PyNumber_InPlace API functions) the principal object being
operated on is `x'. This differs from normal binary operations,
where `x' and `y' could be considered `co-operating', because
unlike in binary operations, the operands in an in-place operation
cannot be swapped. However, in-place operations do fall back to
normal binary operations when in-place modification is not
supported, resuling in the following rules:
- If the left-hand object (`x') is an instance object, and it
has a `__coerce__' method, call that function with `y' as the
argument. If coercion succeeds, and the resulting left-hand
object is a different object than `x', stop processing it as
in-place and call the appropriate function for the normal binary
operation, with the coerced `x' and `y' as arguments. The result
of the operation is whatever that function returns.
If coercion does not yield a different object for `x', or `x'
does not define a `__coerce__' method, and `x' has the
appropriate `__ihook__' for this operation, call that method
with `y' as the argument, and the result of the operation is
whatever that method returns.
- Otherwise, if the left-hand object is not an instance object,
but its type does define the in-place function for this
operation, call that function with `x' and `y' as the arguments,
and the result of the operation is whatever that function
returns.
Note that no coercion on either `x' or `y' is done in this case,
and it's perfectly valid for a C type to receive an instance
object as the second argument; that is something that cannot
happen with normal binary operations.
- Otherwise, process it exactly as a normal binary operation (not
in-place), including argument coercion. In short, if either
argument is an instance object, resolve the operation through
`__coerce__', `__hook__' and `__rhook__'. Otherwise, both
objects are C types, and they are coerced and passed to the
appropriate function.
- If no way to process the operation can be found, raise a
TypeError with an error message specific to the operation.
- Some special casing exists to account for the case of `+' and
`*', which have a special meaning for sequences: for `+',
sequence concatenation, no coercion what so ever is done if a C
type defines sq_concat or sq_inplace_concat. For `*', sequence
repeating, `y' is converted to a C integer before calling either
sq_inplace_repeat and sq_repeat. This is done even if `y' is an
instance, though not if `x' is an instance.
The in-place function should always return a new reference, either
to the old `x' object if the operation was indeed performed
in-place, or to a new object.
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[2] 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:
__iadd__
__isub__
__imul__
__idiv__
__imod__
__ipow__
__ilshift__
__irshift__
__iand__
__ixor__
__ior__
The `i' in `__iadd__' stands for `in-place'.
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[1] 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_InPlace API is only a subset of the normal PyNumber
API: only those functions that are required to support the
augmented assignment syntax are included. If other in-place API
functions are needed, they can be added later.
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.
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 A New Outer Product Operator, Wilson
http://www.python.org/peps/pep-0211.html