Another significant addition to 2.2 is an iteration interface at both the C and Python levels. Objects can define how they can be looped over by callers.
In Python versions up to 2.1, the usual way to make for item in
obj
work is to define a __getitem__() method that looks
something like this:
def __getitem__(self, index): return <next item>
__getitem__() is more properly used to define an indexing
operation on an object so that you can write obj[5]
to retrieve
the sixth element. It's a bit misleading when you're using this only
to support for loops. Consider some file-like object that
wants to be looped over; the index parameter is essentially
meaningless, as the class probably assumes that a series of
__getitem__() calls will be made with index
incrementing by one each time. In other words, the presence of the
__getitem__() method doesn't mean that using file[5]
to randomly access the sixth element will work, though it really should.
In Python 2.2, iteration can be implemented separately, and
__getitem__() methods can be limited to classes that really
do support random access. The basic idea of iterators is
simple. A new built-in function, iter(obj) or
iter(C, sentinel)
, is used to get an iterator.
iter(obj) returns an iterator for the object obj,
while iter(C, sentinel)
returns an iterator that
will invoke the callable object C until it returns
sentinel to signal that the iterator is done.
Python classes can define an __iter__() method, which should
create and return a new iterator for the object; if the object is its
own iterator, this method can just return self
. In particular,
iterators will usually be their own iterators. Extension types
implemented in C can implement a tp_iter function in order to
return an iterator, and extension types that want to behave as
iterators can define a tp_iternext function.
So, after all this, what do iterators actually do? They have one required method, next(), which takes no arguments and returns the next value. When there are no more values to be returned, calling next() should raise the StopIteration exception.
>>> L = [1,2,3] >>> i = iter(L) >>> print i <iterator object at 0x8116870> >>> i.next() 1 >>> i.next() 2 >>> i.next() 3 >>> i.next() Traceback (most recent call last): File "<stdin>", line 1, in ? StopIteration >>>
In 2.2, Python's for statement no longer expects a sequence;
it expects something for which iter() will return an iterator.
For backward compatibility and convenience, an iterator is
automatically constructed for sequences that don't implement
__iter__() or a tp_iter slot, so for i in
[1,2,3]
will still work. Wherever the Python interpreter loops over
a sequence, it's been changed to use the iterator protocol. This
means you can do things like this:
>>> L = [1,2,3] >>> i = iter(L) >>> a,b,c = i >>> a,b,c (1, 2, 3)
Iterator support has been added to some of Python's basic types. Calling iter() on a dictionary will return an iterator which loops over its keys:
>>> m = {'Jan': 1, 'Feb': 2, 'Mar': 3, 'Apr': 4, 'May': 5, 'Jun': 6, ... 'Jul': 7, 'Aug': 8, 'Sep': 9, 'Oct': 10, 'Nov': 11, 'Dec': 12} >>> for key in m: print key, m[key] ... Mar 3 Feb 2 Aug 8 Sep 9 May 5 Jun 6 Jul 7 Jan 1 Apr 4 Nov 11 Dec 12 Oct 10
That's just the default behaviour. If you want to iterate over keys,
values, or key/value pairs, you can explicitly call the
iterkeys(), itervalues(), or iteritems()
methods to get an appropriate iterator. In a minor related change,
the in operator now works on dictionaries, so
key in dict
is now equivalent to
dict.has_key(key)
.
Files also provide an iterator, which calls the readline() method until there are no more lines in the file. This means you can now read each line of a file using code like this:
for line in file: # do something for each line ...
Note that you can only go forward in an iterator; there's no way to get the previous element, reset the iterator, or make a copy of it. An iterator object could provide such additional capabilities, but the iterator protocol only requires a next() method.
See Also:
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