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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