[pypy-dev] Great experience with PyPy

[Phyo Arkar]

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 <mtasic85 at 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 at 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
> _______________________________________________
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>
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