LLVM JIT compiler as a function decorator
Project description
fastpy
Python made fast. Decorate your functions with @fast, we will infered the types you used, compile to machine code, and execute.
- Free software: MIT license
- Documentation: https://fastpy.readthedocs.io.
Biased test showing how fast fastpy is:
Initial code:
def long_loop(a): for i in range(100000): for j in range(10000): a += 1 return a print long_loop(0)
$ time python loop.py 1000000000 python test.py 39.24s user 0.01s system 99% cpu 39.420 total
$ time pypy loop.py 1000000000 pypy test.py 0.92s user 0.01s system 99% cpu 0.937 total
Now we modify the code to use fastpy
from fastpy import fast @fast def long_loop(a): for i in range(100000): for j in range(10000): a += 1 return a print long_loop(0)
$ time python loop.py 1000000000 python test.py 0.11s user 0.00s system 99% cpu 0.117 total
Credits
Based on this tutorial http://dev.stephendiehl.com/numpile/
History
0.1.0 (2016-07-09)
- First release on PyPI.
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