Accelerating PyPy development by funding

PyPy has recently made some great speed and memory progress towards providing the most efficient Python interpreter out there. We also just announced our plans for the pypy-1.2 release. Much of this is driven by personal commitment, by individuals and companies investing time and money. Now we'd appreciate some feedback and help regarding getting money into the PyPy project to help its core members (between 5 and 15 people depending how you count) to sustain themselves. We see several options:

• use a foundation structure and ask for tax-exempt donations to the project, its developers and infrastructure. We just got a letter from the Software Freedom Conservancy that they view our application favourably so this option becomes practical hopefully soon.
• offer to implement certain features like a 64bit JIT-backend, Numpy for PyPy or a streamlined installation in exchange for money, contributed in small portions/donations. Do you imagine you or your company would sponsor PyPy on a small scale for efforts like this? Any other bits you'd like to see?
• offer to implement larger scale tasks by contracting PyPy related companies, namely Open End and merlinux who have successfully done such contracts in the past. Please don't hesitate to contact holger@merlinux.eu and bea@openend.se if you want to start a conversation on this.
• apply for public/state funding - in fact we are likely to get some funding through Eurostars, more on that separately. Such funding is usually only a 50-60% percentage of actual employment and project costs, and is tied to research questions rather than to make PyPy a production-useable interpreter, though.

Anything else we should look out for?

cheers & thanks for any feedback, Maciej and Holger

Planning a next release of PyPy

The PyPy core team is planning to make a new release before the next Pycon US.

The main target of the 1.2 release is packaging the good results we have achieved applying our current JIT compiler generator to our Python interpreter. Some of that progress has been chronicled in recent posts on the status blog. By releasing them in a relatively stable prototype we want to encourage people to try them with their own code and to gather feedback in this way. By construction the JIT compiler should support all Python features, what may vary are the speedups achieved (in some cases the JIT may produce worse results than the PyPy interpreter which we would like to know) and the extra memory required by it.

For the 1.2 release we will focus on the JIT stability first, less on improving non-strictly JIT areas. The JIT should be good at many things as shown by previous blog postings. We want the JIT compiler in the release to work well on Intel 32 bits on Linux, with Mac OS X and Windows being secondary targets. Which compilation targets work will depend a bit on contributions.

In order to finalize the release we intend to have a concentrated effort ("virtual sprint") from the 22nd to the 29th of January. Coordination will happen as usual through the #pypy irc channel on freenode. Samuele Pedroni will take the role of release manager as he already did in the past.

Leysin Winter Sprint: reported

Update: the sprint has been reported to some later date. The next PyPy sprint will probably still be in Leysin, Switzerland, for the seventh time.