4 ms·

Would like to see a benchmark of common algorithms or server-side functions between PyPy3, NodeJS, & Go.

mangecoeur 10y ago
If its server-side performance you are interested in you might also be interested in uvloop, which brings node's event loop library to async python with impressive results https://magic.io/blog/uvloop-blazing-fast-python-networking/ https://magic.io/blog/uvloop-blazing-fast-python-networking/ Personally while I appreciate what PyPy are trying to do, for a lot of real world use cases you can get really impressive performance out of python using the right libraries (see: the entire Python scientific computing stack).
- sreque 10y ago
  You get impressive performance out of python the same way you get impressive performance out of any dynamic language (with few exceptions): make sure your hot paths are executed by code written in C. The nice thing about PyPy is that it makes your pure Python code a lot faster. For instance, I wrote some log-parsing code in pure Python that got a 2.5x speedup when ran from PyPy.
  - dom0 10y ago
    I have to disagree somewhat. Efficient algorithms matter a lot, too.
goatlover 10y ago
Add Julia to the list, since it's directly competing with Python on scientific computing, and the other two aren't really that much (maybe Go a little).
- krastanov 10y ago
  If you are talking about scientific computing, sure, compare PyPy, R, and Julia (and probably add cython, numba and company to make a meaningful comparison). But the OP seems to be interested in web dev where Julia does not deserve the same attention as PyPy, node, and Go.
  - sn9 10y ago
    Julia might be intended for a scientific audience, but there doesn't appear to be any reason why it couldn't address server-side needs. It just needs the right library (like Python did). By the time Julia hits 1.0, I wouldn't be surprised if someone had developed a decent networking library.

If its server-side performance you are interested in you might also be interested in uvloop, which brings node's event loop library to async python with impressive results https://magic.io/blog/uvloop-blazing-fast-python-networking/ https://magic.io/blog/uvloop-blazing-fast-python-networking/ Personally while I appreciate what PyPy are trying to do, for a lot of real world use cases you can get really impressive performance out of python using the right libraries (see: the entire Python scientific computing stack).

sreque 10y ago
You get impressive performance out of python the same way you get impressive performance out of any dynamic language (with few exceptions): make sure your hot paths are executed by code written in C. The nice thing about PyPy is that it makes your pure Python code a lot faster. For instance, I wrote some log-parsing code in pure Python that got a 2.5x speedup when ran from PyPy.
- dom0 10y ago
  I have to disagree somewhat. Efficient algorithms matter a lot, too.

goatlover 10y ago

Add Julia to the list, since it's directly competing with Python on scientific computing, and the other two aren't really that much (maybe Go a little).

krastanov 10y ago
If you are talking about scientific computing, sure, compare PyPy, R, and Julia (and probably add cython, numba and company to make a meaningful comparison). But the OP seems to be interested in web dev where Julia does not deserve the same attention as PyPy, node, and Go.
- sn9 10y ago
  Julia might be intended for a scientific audience, but there doesn't appear to be any reason why it couldn't address server-side needs. It just needs the right library (like Python did). By the time Julia hits 1.0, I wouldn't be surprised if someone had developed a decent networking library.