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Pythran as a bridge between fast prototyping and code deployment

serge-sans-paille.github.io

1–10 of 27 posts

Re: Pythran as a bridge between fast prototyping and code deployment

#2
Looks pretty nice. Unfortunately, I never run into this issue because I only get to write research code.

The Julia language was designed to target the two language problem and at least from these benchmarks it looks pretty competitive [1]. I imagine over time, pythran may fix some limitations and beat Julia in most benchmarks.

[1] https://github.com/fluiddyn/BenchmarksPythonJuliaAndCo/tree/...

Re: Pythran as a bridge between fast prototyping and code deployment

#3

Looks pretty nice. Unfortunately, I never run into this issue because I only get to write research code. The Julia language was designed to target the two language problem and at least from these benchmarks it looks pretty competitive [1]. I imagine over time, pythran may fix some limitations and beat Julia in most benchmarks. [1] https://github.com/fluiddyn/BenchmarksPythonJuliaAndCo/tree/...

Thanks for that benchmark link - puts the claims of the article in perspective.

That said, I want to try Pythran to see how it works for one of my at-home side projects.

I had to learn a bit of Julia about 20 months ago - an old customer got in a pinch when somewhen left before a deliverable so I was immersed using Julia for two weeks. At first I liked the idea of Julia but I didn’t fall in love with the language.

Re: Pythran as a bridge between fast prototyping and code deployment

#4

Looks pretty nice. Unfortunately, I never run into this issue because I only get to write research code. The Julia language was designed to target the two language problem and at least from these benchmarks it looks pretty competitive [1]. I imagine over time, pythran may fix some limitations and beat Julia in most benchmarks. [1] https://github.com/fluiddyn/BenchmarksPythonJuliaAndCo/tree/...

Thanks for that benchmark link - puts the claims of the article in perspective. That said, I want to try Pythran to see how it works for one of my at-home side projects. I had to learn a bit of Julia about 20 months ago - an old customer got in a pinch when somewhen left before a deliverable so I was immersed using Julia for two weeks. At first I liked the idea of Julia but I didn’t fall in love with the language.

I used to only use MATLAB, which for a lot of research code applications is actually nice for getting a prototype running quickly. Now that I have the freedom to choose, I typically use Julia as I'm trying to gain skills in opensource languages that are actually valuable in the job market. The choice of Julia over python is probably due to my nature of going against the grain, which flies in the face of my previous point.

Was there anything specific that turned you off from Julia?

Re: Pythran as a bridge between fast prototyping and code deployment

#5

Looks pretty nice. Unfortunately, I never run into this issue because I only get to write research code. The Julia language was designed to target the two language problem and at least from these benchmarks it looks pretty competitive [1]. I imagine over time, pythran may fix some limitations and beat Julia in most benchmarks. [1] https://github.com/fluiddyn/BenchmarksPythonJuliaAndCo/tree/...

Was also going to mention Julia, it aims to solve this problem and has a really great community

Re: Pythran as a bridge between fast prototyping and code deployment

#6

Earlier quoted context omitted.

Thanks for that benchmark link - puts the claims of the article in perspective. That said, I want to try Pythran to see how it works for one of my at-home side projects. I had to learn a bit of Julia about 20 months ago - an old customer got in a pinch when somewhen left before a deliverable so I was immersed using Julia for two weeks. At first I liked the idea of Julia but I didn’t fall in love with the language.

I used to only use MATLAB, which for a lot of research code applications is actually nice for getting a prototype running quickly. Now that I have the freedom to choose, I typically use Julia as I'm trying to gain skills in opensource languages that are actually valuable in the job market. The choice of Julia over python is probably due to my nature of going against the grain, which flies in the face of my previous p…

One major issue with Julia is that it only recently reached 1.0, with a lot of breaking changes, that make a lot of libraries incompatible.

Another issue is that it's not always that fast, for a recent project I never managed to exceed 100 MFLOPS, at which point I switched to C++ and got 3 GFLOPS. But the python version stalled out at 4 MFLOPS though...

Re: Pythran as a bridge between fast prototyping and code deployment

#7

Looks pretty nice. Unfortunately, I never run into this issue because I only get to write research code. The Julia language was designed to target the two language problem and at least from these benchmarks it looks pretty competitive [1]. I imagine over time, pythran may fix some limitations and beat Julia in most benchmarks. [1] https://github.com/fluiddyn/BenchmarksPythonJuliaAndCo/tree/...

Note that the blog post is also about deployment, not just about performance. Does Julia support statically compiled executables without dependencies or GC?

Re: Pythran as a bridge between fast prototyping and code deployment

#8
post #6

Earlier quoted context omitted.

I used to only use MATLAB, which for a lot of research code applications is actually nice for getting a prototype running quickly. Now that I have the freedom to choose, I typically use Julia as I'm trying to gain skills in opensource languages that are actually valuable in the job market. The choice of Julia over python is probably due to my nature of going against the grain, which flies in the face of my previous p…

One major issue with Julia is that it only recently reached 1.0, with a lot of breaking changes, that make a lot of libraries incompatible. Another issue is that it's not always that fast, for a recent project I never managed to exceed 100 MFLOPS, at which point I switched to C++ and got 3 GFLOPS. But the python version stalled out at 4 MFLOPS though...

Very roughly without knowing details: probably the Julia implementation can be tuned to get close to 3 GFLOPS; it's not that the language has limitations to get above this 100MFLOPS whereas in Python 4MFLOPS might potentially be the best you can get.

Care to share your code and see if it can be improved upon?

Re: Pythran as a bridge between fast prototyping and code deployment

#10
post #9

Was Cython given a consideration for this project? I see that you are involved with the Pythran project, so could you tell us the shortcomings of Cython? As I understand it, before Pythran didn't support Python 3, but seems like that has changed

Can't edit on my app, but the first question was for the blog post writer and my second to the submitter
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