Pypy should have a page for "Success Stories!" Now with this and Quora proving Power of PyPy , i am beginning to start converting my projects into PyPy soon! I am only withholding right now because my projects uses a lot of C Libraries and Numpy/Matplotlib/scilit-learn.
Thanks Phyo. On Thursday, February 7, 2013, Maciej Fijalkowski wrote: > On Thu, Feb 7, 2013 at 1:55 PM, Marko Tasic <mtasi...@gmail.com<javascript:;>> > wrote: > > Hi, > > > > I would like to share short story with you and share what we have > > accomplished with PyPy and its friends so far. > > > > Company that I have worked for last 7 months (intentionally unnamed) > > gave me absolute permission to pick up technologies on which we based > > our solution. What we do is: crawl for PDFs and newspapers articles, > > download, translate them if needed, OCR if needed, do extensive > > analysis of downloaded PDFs and articles, store them in more organized > > structures for faster querying, search for them and generate bunch of > > complex reports. > > > > From very beginning I decided to go with PyPy no matter what. What we > > picked is following: > > * Flask for web framework, and few of its extensions such as > > Flask-Login, Flask-Principal, Flask-WTF, Flask-Mail, etc. > > * Cassandra as database because of its features and great experience > > with it. PyCassa is used as client to talk to Cassandra server. > > * ElasticSearch as distributed search engine, and its client library > pyes. > > * Whoosh as search engine, but with some modifications to support > > Cassandra as storage and distributed locking. > > * Redis, and its client library redis-py, for caching and to speed up > > common auto-completion patterns. > > * ZooKeeper, and its client library Kazoo, for distributed locking > > which plays essential role in system for transaction-like behavior > > over many services at once. > > * Celery in conjunction with RabbitMQ for task distribution. > > * Sentry for error logging. > > > > What we have developed on our own are wrappers and clients for: > > * Moses which is language translator > > * Tesseract which is OCR engine > > * Cassandra store for Whoosh > > * wkhtmltopdf and wkhtmltoimage which are used for conversion of HTML > > to PDF/Image > > * etc > > > > Now when product is finished and in final testing phase, I can say > > that we did not regret because we used PyPy and stack around it. > > Typical speed improvement is 2x-3x over CPython in our case, but > > anyway we are mostly IO and memory bound, expect for Celery workers > > where we do analysis which are again many small CPU intensive tasks > > that are exchanged via RabbitMQ. Another reason why we don't see > > speedup us is that we are dependent on external software (servers) > > written in Erlang and Java. > > > > I'm already planing to do Cassandra (distributed key/value only > > database without index features), ZooKeeper, Redis and ElasticSearch > > ports in Python for next projects, and hopefully opensource them. > > > > Regards, > > Marko Tasic > > _______________________________________________ > > pypy-dev mailing list > > pypy-dev@python.org <javascript:;> > > http://mail.python.org/mailman/listinfo/pypy-dev > > Awesome! > > I'm glad people can make pypy work for non-trivial tasks which require > a lot of dependencies. We're trying to lower the bar, however it takes > time. > > Cheers, > fijal > _______________________________________________ > pypy-dev mailing list > pypy-dev@python.org <javascript:;> > http://mail.python.org/mailman/listinfo/pypy-dev >
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