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The last two-ish years have been insane for Python performance. Something clicked with the core team and they obviously made this a serious goal of theirs and t
by jjice 3y ago
The last two-ish years have been insane for Python performance. Something clicked with the core team and they obviously made this a serious goal of theirs and the last few years have been incredible to see.
- pletnes 3y agoMicrosoft are paying core devs to work on it full time, for one.
- treyd 3y agoWhich is strange considering how bad the tooling to use Python on Windows is. There's a few workflows where people have gone down the beaten path before (Conda, etc.), but outside of that you have to just pretend you're on Linux and use the cygwin toolchains and even that doesn't always work so well. Better support on Linux was a top 5 reason for me making the switch to using it full time when I went off to college, and it hasn't changed substantially in the 8 years since then.
- BeetleB 3y agoNot sure what you mean. I use Python for Windows all the time at work, and on Linux at home. I've not noticed any meaningful difference in my workflow.
- deleted 3y ago[deleted]
- eigenvalue 3y agoIt’s because the total dollars of capitalized software deployed in the world using Python has absolutely exploded from AI stuff. Just like how the total dollars of business conducted on the web was a big driver of JS performance earlier.
- dehrmann 3y agoBut all the AI heavy lifting is done in native code.
- dron57 3y agoAI heavy lifting isn't just model training. There's about a million data pipelines and processes before the training data gets loaded into a PyTorch tensor.
- HDThoreaun 3y agoalso done in native code
- tomjakubowski 3y agoEhhh... if you're lucky. I've seen (and maybe even written) plenty of we-didn't-have-time-to-write-this-properly-with-dataframes Python data munging code, banged out once and then deployed to production. I'll take performance gains there.
- janalsncm 3y agoFrom personal experience, no. I ended up writing rust bindings to call from python that turned minutes of loading into seconds.
- ElectronCharge 3y agoThat is the exact value proposition of Mojo. Pythonesque (sane) syntax, great AOTC language features, great performance, memory safety, excellent Python interoperability. What’s not to like? If you think of something, contact Modular…
- eternityforest 3y agoWhen Node.js started really taking off, I was actually a bit worried that Python would become No Longer Best Practice, but now it definitely seems to be still going strong.
- crabbone 3y ago[flagged]
- attractivechaos 3y ago> There were no noticeable performance improvements in the course of the last two years. In fairness, Python did get faster. Python 3.9 took 82 seconds for sudoku solving and 62 seconds for interval query. Python 3.11 took 53 and 43 seconds, respectively [1]. v3.12 may be better. That said, whether the speedup is noticeable can be subjective. 10x vs 15x slower than v8 may not make much difference mentally. [1] https://github.com/attractivechaos/plb2 https://github.com/attractivechaos/plb2
- mattgruskin 3y agoMicrosoft already tried Python on the CLR! They didn't stick with it. https://en.wikipedia.org/wiki/IronPython https://en.wikipedia.org/wiki/IronPython
- crabbone 3y agoThat's why I said another. It was a different time. Microsoft had a different strategy towards languages not developed by Microsoft. Similar to how there also used to be JScript, but now Node.js is basically a Microsoft's pet project. There are actually plenty of popular Microsoft's projects that took even more than two tries. Azure is like their third attempt at cloud services, iirc. Credit where credit is due, they learn from mistakes... unfortunately, that only makes them more insidious.
- Dylan16807 3y agoYou did not, in fact, say "another".
- smabie 3y ago[flagged]
- deleted 3y ago[deleted]