PyPy is your Past, Present, and Future¶
- There are 2 things faster than C
- Armin wanted to write a JIT for Python (Psyco)
- Psyco was the written by Armin.
- Kind of messing.
- Generators came along, and not supported
- 64-bit computers weren’t supported either
- Started writing Python in Python
- About 2000x slower than CPython
- Somethings in the standard library were in python
- Copied some optimizations over (TimSort)
- Writing JITs sucked.
- Writing a JIT generator for arbitrary languages is much simpler than writing a JIT for Python
- ~2-3 years ago Alex got into Pypy
- Beat C in str_cmp ~1 month ago
- Tries to show example of real time video analysis, mplayer broke.
- Science likes big datasets, use Numpy
- Numpy is in C
- Numpy likes speed, so does pypy
- Started reimplementing Numpy in Pypy
Humans are bad at detecting slow downs
- Pypy has a JITViewer
- Allows you to view code in levels
- Python, Assembler, etc.
Shows demo fo JITViewer
- Look into code
- “I think that’s too many instructions”
- Optimize code!
Shows example of sum(x**3 for x in xrange(10000))
JVM Community has good tooling
Python could use that too.
- Usually benchmark against C
- Experimenting with using C extensions.
Where we’re going¶
- Many projects are being migrated
Porting to Python3
- Because they use a JIT Generator, can improve constantly
- Speedups in Python3 will improve Python2
- Wrote a blogpost on STM (Software Transactional Memory).
Think STM would be slower for single core
STM for multicore workloads
GIL for single core.
What People Are Doing with Pypy¶
- Researchers getting results over lunch, instead of over night.
- Financial company for market analysis
- Engineers at CERN
What Pypy Needs from the Community¶
- Encourages use of pypy if you are CPU bound
- Requests for slow code, and they’ll use it in benchmarks
- Want to make Python the right tool for the job in more places
- Work on the ecosystem and tools