python object initialization speed

On the Cython mailing list, I saw this mentioned for avoiding init overhead, so i wrote up some code to try it. Basically, instead of using an __init__, it uses the PY_NEW macro (which I don't pretend to understand fully).
I ran a benchmark with 5 cases:

  1. PY_NEW macro (still has python overhead for each call to the creator function)

  2. regular python init

  3. python init using __slots__

  4. cython init (cdef'ed class)

  5. batch PY_NEW: calling PY_NEW from inside cython to avoid python call overhead

  6. batch init on cython class


the timings look like this:

PY_NEW on Cython class: 1.160
__init__ on Python class: 30.414
__init__ on Python class with slots: 10.242
__init__ on Cython class 1.185
batch PY_NEW total: 0.855 , interval only: 0.383
batch __init__ on Cython class total 0.998 , interval_only: 0.540


So, the PY_NEW is .383 compared to .540 for using a __init__ on a Cython class, but both are much faster than python. I was surprised that using slots gives a 3x speed improvement over a regular python class. That Cython is faster is no surprise.
Stefan Behnel explains better than I could.

All the code is smashed uncomfortably into this gist.

for kicks, i tried with unladen-swallow. It comes out almost 2x faster on the python times both with and without slots. I didn't use the optimization stuff. Cython even works with unladen-swallow--just have to rebuild the .so--and the timings are the same as Cython-with-CPython.

Comments

Post a Comment

Popular posts from this blog

python interval tree

EDIT: added a couple points inline. I'm obsessed with trees lately -- of the CS variety, not the plant variety. Although we are studying poplar, so I'll be using trees to study trees . I'd tried a couple times to implement an interval tree from scratch following the Wikipedia entry . Today I more or less did that in python. It's the simplest possible form. There's no insertion (though that's trivial to add), it just takes a list of 'things' with start and stop attributes and creates a tree with a .find() method. The wikipedia entry that baffled me was about storing 2 copies of each node's intervals --one sorted by start and the other by stop. I didn't do that as I think in most cases it won't improve lookup time. I figure if you have 1 million elements and a tree of depth 16, then you have on average 15 intervals per node (actually fewer since there are the non-leaf nodes). So I just brute force each of those nodes and move to the next. I th...
Read more

levenshtein in cython

EDIT(2): fix markup for <char *> casts ... fix malloc (see comments. thanks Bao). NOTE: using a kwarg for limit slows things down. setting that to a required arg and using calloc for m2 speed things up to nearly as fast as the pylevenshtein. Well, it seems to be popular to code up the levenshtein . I actually have a use for this and wanted to practice some Cython , so I've written a version. I used bearophile's recipe , wikibooks , this (from k4st on reddit) and this for reference. It follows bearophile's code closely, using only O(m) space instead of O(mn). cdef extern from "stdlib.h": ctypedef unsigned int size_t size_t strlen(char *s) void *malloc(size_t size) void free(void *ptr) int strcmp(char *a, char *b) cdef inline size_t imin(int a, int b, int c): if a if c return c return a if c return c return b cpdef int levenshtein(char *a, char *b, int limit=100): cdef int m = strlen(a),...
Read more

synteny mapping

Image
Living in Synteny I've been working on automating synteny mapping between any pairs of genomes. Synteny is where there's a stretch of DNA or genes in some order on chromosomeA of organismX and due to a shared evolutionary history, you can find a similar stretch of genes in order on chromosomeB of organismY. Often there are small losses and inversions, but between closely related organisms like man and mouse , there's still a lot of synteny. Plants can undergo polyploidy , following which, a species can have 2 entire copies of its genome. Over time, much of the duplicated cruft is lost, and the homologous chromosomes diverge, but if the divergence is not too great, it's still possible (actually common) to find synteny within the genome of a single organism--as well as between organisms. I've written my own algorithm to find synteny which uses python sets, and numpy array slicing to do the heavy lifting. It is quite clever [wink]. And it _almost_ works but it'...
Read more