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Couchbase contribution to PyPy

Hello everyone!

We always offer to put on the blog info about our sponsors who donate substantial amounts of money. So far most people decided to stay anonymous, so this is the first blog post describing our sponsor and his relationship to PyPy, hopefully not the last. We'll also publish a full blog post about the PSF-matched fundraiser soon. This is a guest post by Brent Woodruff from Couchbase.

Couchbase is a leading NoSQL document database that provides a flexible data model, high performance, scalability, and high availability. Couchbase is a commercially supported open source project. Visit us at https://www.couchbase.com and https://github.com/couchbase.

Couchbase Inc. donated $2000.00, and employees of Couchbase personally contributed a disclosed additional $230.00, towards Pypy progress during the September funding drive. These funds will see a match from the Python Software Foundation.

Pypy is primarily used by Couchbase employees to perform product analysis and troubleshooting using internally developed tools. Every customer of Couchbase benefits from the use of Pypy; both due to the rapid development provided by Python, and the speed of the resulting tools provided by the Pypy JIT interpreter.

“PyPy is great - it gave us a 4x speedup in our CPU-intensive internal application over CPython” -Dave Rigby and Daniel Owen, Couchbase Engineers

Additionally, Couchbase has a preliminary CFFI based Couchbase client available for Pypy users.


Comments

Unknown wrote on 2014-10-14 22:42:

Definitely wouldn't have thought to put PyPy and Couchbase in the same sentence, but this is very good of them! Glad to see the support.

Anonymous wrote on 2014-10-15 09:34:

Thanks for the donation. Could you give a bit more detail of how hard it was to make your code compatible with PyPy?

Anonymous wrote on 2014-10-15 13:28:

Hello from Couchbase. With regards to making our code compatible with PyPy, I can only comment on our internal tooling. Those are currently all pure Python, so it was trivial. We used modules that work with PyPy already: namely pyparsing, LEPL, and tornado. The tools all run under both CPython and PyPy unmodified.