Python’s iterator protocol is a powerful tool in your arsenal.
Iterator is an object that returns streams of data.
To be an iterator an instance just have to have a next() method.
Repeated calls to the iterator’s next() method return successive items in the
stream. When no more data are available a StopIteration exception is
As iterators preserve state, take care reusing them.
As an example, the first loop below will print 1,2,3 where as the second
will print nothing.
>>> an_iter = iter([1, 2, 3]) >>> for x in an_iter: ... print x ... 1 2 3 >>> for x in an_iter: ... print x ...
Iterable is a class that can generate an
Iterator. For example
list, tuples and strings are all iterable. To be an iterable a class
just has to have an iter method that will return an iterator.
Iterables can be looped over multiple time as each time a new iter is generated;
>>> seq = (1, 2, 3) >>> for x in seq: ... print x ... 1 2 3 >>> for x in seq: ... print x ... 1 2 3
but once the iterator has been generated it can’t be reused.
>>> an_iter = iter(seq) >>> for x in an_iter: ... print x ... 1 2 3 >>> for x in an_iter: ... print x ...
If you’re currently returning a list from a function consider instead returning an iterator. For example;
# Bad def get_all_lines(): all_lines =  for filename in ALL_FILES: for line in open(filename): all_lines.append(line) return all_lines # Better is to achieve this with a generator. # This means calling the function below will return an iterator. def get_all_lines_iter(): for filename in ALL_FILES: for line in open(filename): yield line
If client code wants to search the lines for string all files will be read into memory even if the line were looking for is in the first file.
>>> for line in get_all_lines(): >>> if SEARCH_STRING in line: >>> print "YAY" YAY
This is far more efficient as we wont go through the steps of reading every file and storing it in a list when its not needed. It’s more flexible too. If the client code wants a list they can call;
listified = list(get_all_lines_iter())
or you might want a tuple instead;
tuplified = tuple(get_all_lines_iter())
The same applied with list comprehensions;
# Don't do def some_func(): return [x for x in some_other_iteratable] # Instead the following will again return an iterator def some_func(): return (x for x in some_other_iteratable)
Iterables can be used with the itertools package to do some cool things very efficiently;
>>> import itertools # Create some iterable objects >>> a = (1, 2, 3) >>> b = ('a', 'b', 'c') >>> c = (None, 0.3, False) # Create an iterable object containing iterables >>> seq_of_seq = (a, b, c) # Chain will iterate through each iterable in turn till all iterables run out # of items >>> for x in itertools.chain.from_iterable(seq_of_seq): ... print repr(x) ... 1 2 3 'a' 'b' 'c' None 0.3 False # izip takes one item from each iterable on each iteration. # It stops when the shortest iterator runs out of items. >>> for x, y in itertools.izip(a, b): ... print repr(x), repr(y) ... 1 'a' 2 'b' 3 'c' # cycle will loop over an iterator indefinitely. # It achieves this by caching results on first run around the iterator. >>> for n, x in itertools.izip( ... range(20), ... itertools.cycle(itertools.chain.from_iterable(seq_of_seq))): ... print n, repr(x) ... 0 1 1 2 2 3 3 'a' 4 'b' 5 'c' 6 None 7 0.3 8 False 9 1 10 2 11 3 12 'a' 13 'b' 14 'c' 15 None 16 0.3 17 False 18 1 19 2