Is Python Fast Now??! | Python 3.13 Released

IMPORTANT: mistake at 3:27 (see pinned comment)

Let's take a look at performance improvements of the new Python 3.13 release!
Let's also check two interesting implementations of Python: Codon and LPython.

Sources:

[pretro]

3:27 okay, I love your content, but maybe try and learn more before you say something that is just false.

an interpreter takes in code and runs it, a COMPILER (not a JIT compiler) takes in code and turns it into machine code, and a JIT compiler runs in the background and updates the existing machine code according to the changes made.

usually interperters are fast during build-time, but requires every client to also have a copy of the interperter, a compiler is slower than interperters, but works for every client with the same OS/architecture as you, and a JIT compiler is slower than both for the first compilation, but becomes extremely fast for every compilation after.

[zoom]

1:05 and 2:34, GIL was not introduced just for simplicity but for the SPEED! Without a global lock you'd need to introduce many local ones which make single-threaded processing slower. Your example proves that!

[vidal]

Python is similar to Fortran in concept. Fortran was easy to use (much easier than Assembly, which were prevalent at the time or C, that came after a while.), so researchers and people who are not computer scientists but need to code liked it. Python, when using the right libraries, is fast enough for a lot of scientific computing. The problem is that, like Fortran, you have to pull up C when you need to do something more advanced or if Python is too slow for your purpose. Python is still a very good glue between various languages. Basically, if Python is faster, researchers in every area that isn't computer science are going to have a better time with their code. Fortran was easy to use and fast. If python becomes fast, even if it is not as fast as Fortran, it will keep being used. Julia was born with this premise.

[MrAlanCristhian]

The biggest drawback of mojo is the same one when python 3 came out: it's a different language. The python 2 to 3 transition should be a good reminder of why backward compatibility is important. In an interview with Lex Fiedman, Guido Said cpython incompatibility was the main reason that killed those project that tried to make python faster. And mojo is doing the same mistake. So, I don't see a bight future for mojo.

Maybe I am wrong, time will tell.

The Faster-CPython team has some great optimization ideas that (hopefully) will be implemented on 3.14. Look at 701 issue on the faster-cpython repository for a quick recap of what they are doing.

[fraidoonhu]

I don't care about speed. But Python syntax is the unforgiven mistake human beings ever made. Specially when u use lambda function.

[tonylangworthy]

Stop right here bro... Until Pyton syntax changes, idc how fast it is. Facts!

[surajmandal_]

Waiting for Mojo to get some more mature.