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> Like jython, and pypy and other implementations, it never caught on because compatibility with cpython is one of the most important criteria for people dealin

> Like jython, and pypy and other implementations, it never caught on because compatibility with cpython is one of the most important criteria for people dealing with lots of python code. I think this is more an issue of popular packages were developed and tested against cpython and there wasn't enough effort available to port/test them against anything else. There's no special magic in cpython that Python programmers love, they just want their code to run. If they've got a numpy dependency (IIRC it doesn't support pypy but I'm not going to look it up so I may be corrected on that point this is a long parenthetical) they can't use an interpreter that doesn't support it. Even if it worked but had bugs it didn't have in cpython, they're still going to use cpython. Most people aren't writing Python for its super duper fast performance so they're fine leaving a little performance on the table by using the interpreter that their dependencies support. Whatever that is.

dehrmann 3y ago
Jython doesn't have a good story for running native libraries like Numpy.
- giantrobot 3y ago
  Sure, I didn't claim it did. My point is that Python programmers don't tend to have a particular fondness for an interpreter. They tend to care only about the ecosystem. If you came up with a cxpython interpreter that was faster than cpython and supported all the modules the same way (including C interop) Python programmers would jump over to it. If your cxpython was faster than cpython but didn't support everything they'd ignore it. Case in point: Python 2.7. While 3.x offered a lot of improvements it took years for some popular modules to support it. No one bothered to look twice at Python 3 until their dependencies supported it. Python programmers don't tend to care much about the interpreter so much as the code they wrote or use running correctly.
- fulafel 3y ago
  Numpy also wasn't very prominent in those days among Python users, the explosion of data science Python use happened later. (Actually NumPy didn't even exist for most of Jython's active development, but some of its predecessors did)

dehrmann 3y ago

Jython doesn't have a good story for running native libraries like Numpy.

giantrobot 3y ago
Sure, I didn't claim it did. My point is that Python programmers don't tend to have a particular fondness for an interpreter. They tend to care only about the ecosystem. If you came up with a cxpython interpreter that was faster than cpython and supported all the modules the same way (including C interop) Python programmers would jump over to it. If your cxpython was faster than cpython but didn't support everything they'd ignore it. Case in point: Python 2.7. While 3.x offered a lot of improvements it took years for some popular modules to support it. No one bothered to look twice at Python 3 until their dependencies supported it. Python programmers don't tend to care much about the interpreter so much as the code they wrote or use running correctly.
fulafel 3y ago
Numpy also wasn't very prominent in those days among Python users, the explosion of data science Python use happened later. (Actually NumPy didn't even exist for most of Jython's active development, but some of its predecessors did)