Python compared to C++ - machine performanceSomeone posted to LinkedIn's Python Professionals forum with the subject "Why Python is so slow?" and said Python is 10x slower than C++ (on one specific microbenchmark). You can guess what the rest of it was like.
- even though machine efficiency rarely matters anymore
- even though algorithm improvements are usually better than worrying about using the fastest language available (assembler anyone? I used to love it, but not anymore)
- even though microbenchmarks are poor indicators of overall performance
- even though the innermost loop of a program is usually the only part that makes a difference (if any part at all) for performance
First off, we probably mostly know by now that Python != CPython anymore.
The code I used for this comparison can be viewed using a web browser or checked out using Subversion at http://stromberg.dnsalias.org/svn/why-is-python-slow/trunk/ .
BTW, the OP used range in Python 2.x; this should of course be xrange. range is fine in 3.x, but in 2.x it's awful.
Anyway, here are the results. Lower numbers are better:
Some interesting things to note (all relative to g++ -O3) :
- clang++ was slightly faster than g++ sometimes. The two C++'s were practically the same.
- Naive Cython was slower than CPython.
- Typed Cython was faster than CPython.
- CPython was around 4.9 and 5.6x slower on this particular microbenchmark, not 10x (but perhaps using the wrong range would've made it 10x, I didn't check that).
- Numba was faster once, and slower once than CPython - but not by a lot in either case.
- pypy was a touch less than 2x slower, but that's for pure python code!
- shedskin was only a hair slower than the pure C++ compilers.
We perhaps should also measure how long it takes to debug undefined memory references in the two languages - that's developer efficiency, and it's usually more important than machine efficiency. ^(^
2018-02-10: I updated this here.