Python Iterators: Difference between revisions
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When no more data are available a <code>StopIteration</code> exception is raised instead. At this point, the iterator object is exhausted and any further calls to its <code>__next__()</code> method just raise <code>StopIteration</code> again. | When no more data are available a <code>StopIteration</code> exception is raised instead. At this point, the iterator object is exhausted and any further calls to its <code>__next__()</code> method just raise <code>StopIteration</code> again. | ||
There's no <code>has_next()</code> method that tests the availability of a next item without consuming it. Unavailability of a next item is tested by checking the <code>StopIteration</code> exception. | |||
If you are OK to always consume the next item, the end of the iterator can be tested with: |
Revision as of 05:06, 7 July 2022
External
Internal
TODO
TO PROCESS PyOOP "The Iterator Pattern" + "Iterators" + "The iterator protocol"
Overview
An iterator instance represents a stream of data.
The iterator instances are created from iterable objects with the built-in function iter()
:
l = ['a', 'b', 'c']
i = iter(l)
Once created, repeated invocations of the iterator's __next__()
method, or by passing it to the built-in function next()
, return successive items in the stream:
assert next(i) == 'a'
assert next(i) == 'b'
assert next(i) == 'c'
When no more data are available a StopIteration
exception is raised instead. At this point, the iterator object is exhausted and any further calls to its __next__()
method just raise StopIteration
again.
There's no has_next()
method that tests the availability of a next item without consuming it. Unavailability of a next item is tested by checking the StopIteration
exception.
If you are OK to always consume the next item, the end of the iterator can be tested with: