##
5.13.1 Itertool functions

The following module functions all construct and return iterators. Some provide streams of infinite length, so they should only be accessed by functions or loops that truncate the stream.

`chain`( | *iterables)

  Make an iterator that returns elements from the first iterable until it is exhausted, then proceeds to the next iterable, until all of the iterables are exhausted. Used for treating consecutive sequences as a single sequence. Equivalent to:

           def chain(*iterables):
               for it in iterables:
                   for element in it:
                       yield element

`count`( | [n])

  Make an iterator that returns consecutive integers starting with n. Does not currently support python long integers. Often used as an argument to `imap()` to generate consecutive data points. Also, used in `izip()` to add sequence numbers. Equivalent to:

           def count(n=0):
               while True:
                   yield n
                   n += 1

  Note, `count()` does not check for overflow and will return negative numbers after exceeding `sys.maxint`. This behavior may change in the future.

`cycle`( | iterable)

  Make an iterator returning elements from the iterable and saving a copy of each. When the iterable is exhausted, return elements from the saved copy. Repeats indefinitely. Equivalent to:

           def cycle(iterable):
               saved = []
               for element in iterable:
                   yield element
                   saved.append(element)
               if len(saved) == 0:
                   return
               while True:
                   for element in saved:
                         yield element

  Note, this is the only member of the toolkit that may require significant auxiliary storage (depending on the length of the iterable).

`dropwhile`( | predicate, iterable)

  Make an iterator that drops elements from the iterable as long as the predicate is true; afterwards, returns every element. Note, the iterator does not produce any output until the predicate is true, so it may have a lengthy start-up time. Equivalent to:

           def dropwhile(predicate, iterable):
               iterable = iter(iterable)
               while True:
                   x = iterable.next()
                   if predicate(x): continue # drop when predicate is true
                   yield x
                   break
               while True:
                   yield iterable.next()

`ifilter`( | predicate, iterable)

  Make an iterator that filters elements from iterable returning only those for which the predicate is `True`. If predicate is `None`, return the items that are true. Equivalent to:

           def ifilter(predicate, iterable):
               if predicate is None:
                   def predicate(x):
                       return x
               for x in iterable:
                   if predicate(x):
                       yield x

`ifilterfalse`( | predicate, iterable)

  Make an iterator that filters elements from iterable returning only those for which the predicate is `False`. If predicate is `None`, return the items that are false. Equivalent to:

           def ifilterfalse(predicate, iterable):
               if predicate is None:
                   def predicate(x):
                       return x
               for x in iterable:
                   if not predicate(x):
                       yield x

`imap`( | function, *iterables)

  Make an iterator that computes the function using arguments from each of the iterables. If function is set to `None`, then `imap()` returns the arguments as a tuple. Like `map()` but stops when the shortest iterable is exhausted instead of filling in `None` for shorter iterables. The reason for the difference is that infinite iterator arguments are typically an error for `map()` (because the output is fully evaluated) but represent a common and useful way of supplying arguments to `imap()`. Equivalent to:

           def imap(function, *iterables):
               iterables = map(iter, iterables)
               while True:
                   args = [i.next() for i in iterables]
                   if function is None:
                       yield tuple(args)
                   else:
                       yield function(*args)

`islice`( | iterable, [start,] stop [, step])

  Make an iterator that returns selected elements from the iterable. If start is non-zero, then elements from the iterable are skipped until start is reached. Afterward, elements are returned consecutively unless step is set higher than one which results in items being skipped. If stop is `None`, then iteration continues until the iterator is exhausted, if at all; otherwise, it stops at the specified position. Unlike regular slicing, `islice()` does not support negative values for start, stop, or step. Can be used to extract related fields from data where the internal structure has been flattened (for example, a multi-line report may list a name field on every third line). Equivalent to:

           def islice(iterable, *args):
               s = slice(*args)
               next = s.start or 0
               stop = s.stop
               step = s.step or 1
               for cnt, element in enumerate(iterable):
                   if cnt < next:
                       continue
                   if stop is not None and cnt >= stop:
                       break
                   yield element
                   next += step

`izip`( | *iterables)

  Make an iterator that aggregates elements from each of the iterables. Like `zip()` except that it returns an iterator instead of a list. Used for lock-step iteration over several iterables at a time. Equivalent to:

           def izip(*iterables):
               iterables = map(iter, iterables)
               while True:
                   result = [i.next() for i in iterables]
                   yield tuple(result)

`repeat`( | object[, times])

  Make an iterator that returns object over and over again. Runs indefinitely unless the times argument is specified. Used as argument to `imap()` for invariant parameters to the called function. Also used with `izip()` to create an invariant part of a tuple record. Equivalent to:

           def repeat(object, times=None):
               if times is None:
                   while True:
                       yield object
               else:
                   for i in xrange(times):
                       yield object

`starmap`( | function, iterable)

  Make an iterator that computes the function using arguments tuples obtained from the iterable. Used instead of `imap()` when argument parameters are already grouped in tuples from a single iterable (the data has been ``pre-zipped''). The difference between `imap()` and `starmap()` parallels the distinction between `function(a,b)` and `function(*c)`. Equivalent to:

           def starmap(function, iterable):
               iterable = iter(iterable)
               while True:
                   yield function(*iterable.next())

`takewhile`( | predicate, iterable)

  Make an iterator that returns elements from the iterable as long as the predicate is true. Equivalent to:

           def takewhile(predicate, iterable):
               iterable = iter(iterable)
               while True:
                   x = iterable.next()
                   if predicate(x):
                       yield x
                   else:
                       break