I did a couple of experiments compiling itertools with the new generator support in Cython. In CPython, the itertools module is actually written in hand tuned C and does very little computation in its generators, so I knew it would be hard to reach with generated code. But Cython does a pretty good job.
Something as trivial as
chain() is exactly as fast as in the C implementation, but compared to the more than 60 lines of C code, it is certainly a lot more readable in Cython:
def 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. """ for it in iterables: for element in it: yield element
Other functions, like
islice(), are faster in C, partly because CPython actually takes a couple of shortcuts, e.g. by only looking up the iterator slot method once. You cannot do that in Python code, and I wanted to keep the implementation compatible with regular Python. Specifically, the C speed advantage for
islice() is currently about 30-50% in general, although the Cython implementation can also be up to 10% faster for some cases, e.g. when extracting only a couple of items from the middle of a longer sequence. The C implementation is about 90 lines, here is the Cython implementation:
import sys import cython # Python 2/3 compatibility _max_size = cython.declare(cython.Py_ssize_t, getattr(sys, "maxsize", getattr(sys, "maxint", None))) @cython.locals(i=cython.Py_ssize_t, nexti=cython.Py_ssize_t, start=cython.Py_ssize_t, stop=cython.Py_ssize_t, step=cython.Py_ssize_t) def islice(iterable, *args): """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). """ s = slice(*args) start = s.start or 0 stop = s.stop or _max_size step = s.step or 1 if start = stop: return nexti = start for i, element in enumerate(iterable): if i == nexti: yield element nexti += step if nexti >= stop or nexti Here is one that is conceptually quite simple:
count(). I had to optimise it quite a bit, because the iteration code in the C code is extremely tight. Even the tuned version below runs about 10% slower than the hand tuned C version, which is about 230 lines long.@cython.locals(i=cython.Py_ssize_t) def count(n=0): """Make an iterator that returns consecutive integers starting with n. If not specified n defaults to zero. Often used as an argument to imap() to generate consecutive data points. Also, used with zip() to add sequence numbers. """ try: i = n except OverflowError: i = _max_size # skip i-loop else: n = _max_size # first value after i-loop while i Note that all of the above generators execute in the order of microseconds, so even a slow-down of 50% will likely not be measurable in real world code. So far, I did not try any of the more fancy functions in itertools (those that actually do something). The Cython project has announced a Google Summer of Code project with exactly the intent to rewrite some of the C stdlib modules of CPython in pure Python code with Cython compiler hints. So I leave this exercise to interested readers for now.