4 ms·

I suppose no-GIL Python will be here in no less than 3/4 release cycles. 3.11 has been out for a year and most Python code in prod is what, 3.8? So I guess we w

I suppose no-GIL Python will be here in no less than 3/4 release cycles. 3.11 has been out for a year and most Python code in prod is what, 3.8? So I guess we won’t have to deal with this at scale before idk 2030 is approaching. I also don’t see Python runtimes in prod being updated from whatever they’re on now to newest releases. I don’t want to sound harsh, but the SC stated they don’t want to have another 2-to-3 migration, so people won’t update lightly. Yes, most of the content online right now might be dangerous to copy paste

sgarland 3y ago
Tangentially, 3.11 was the first release in quite some time to have major speed improvements across the board. The average is 25%, sometimes far more. Anyone who hasn’t upgraded to it by now is needlessly spending extra on compute.
- sapiogram 3y ago
  It's only 25% speedup in actual Python code, in domains like data science this won't matter much, because your cpu cycles are mostly spent inside numpy.
  - evolutionas 3y ago
    It does matter if you run your ML models in production. After we upgraded to 3.12 the average response time ~4-6ms decreased to stable sub 2ms. Latency decrease for p95 and p99 were even more significant
  - sgarland 3y ago
    There are plenty of web apps running in pure Python. It matters a great deal for them.
dragonwriter 3y ago
> most Python code in prod is what, 3.8? 3.8 is the oldest supported version, so I would hope not, but probably.
- scbrg 3y ago
  Python versions I have to target (occasionally): 2.5, 2.7, 3.5, 3.8. Not the whole world has the luxury to upgrade all their systems all the time. Excuse me, would you mind stopping this factory for a few hours so we can replace this perfectly functioning system with an untested one that may or may not work in roughly the same way? is not a question that is generally met with wild enthusiasm.

sgarland 3y ago

Tangentially, 3.11 was the first release in quite some time to have major speed improvements across the board. The average is 25%, sometimes far more. Anyone who hasn’t upgraded to it by now is needlessly spending extra on compute.

sapiogram 3y ago
It's only 25% speedup in actual Python code, in domains like data science this won't matter much, because your cpu cycles are mostly spent inside numpy.
- evolutionas 3y ago
  It does matter if you run your ML models in production. After we upgraded to 3.12 the average response time ~4-6ms decreased to stable sub 2ms. Latency decrease for p95 and p99 were even more significant
- sgarland 3y ago
  There are plenty of web apps running in pure Python. It matters a great deal for them.

dragonwriter 3y ago

> most Python code in prod is what, 3.8? 3.8 is the oldest supported version, so I would hope not, but probably.

scbrg 3y ago
Python versions I have to target (occasionally): 2.5, 2.7, 3.5, 3.8. Not the whole world has the luxury to upgrade all their systems all the time. Excuse me, would you mind stopping this factory for a few hours so we can replace this perfectly functioning system with an untested one that may or may not work in roughly the same way? is not a question that is generally met with wild enthusiasm.