Is Python Fast Now??! | Python 3.13 Released

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.

i hate python its an ass language

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

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

Snake lang has some of the nicest syntax imo. It is far easier to read and comprehend existing code than other languages that have more complex syntax (e.g. Rust Thing[Something]<T<W>>'A), which is important if you care about maintaining code bases. The main downside to Python is the low performance compared to all the other languages -- for example, when I ported my bluegenes library from Python to Go, I got a 100x speed improvement before doing any Go-specific performance tuning and memory optimization. But I still love Python and write the majority of my FOSS projects in it, so I'm kind of stuck with it for now. Hopefully they figure out a solution that removes the GIL without making the runtime twice as slow. Iirc, Guido said that the GIL was a solution for a time when single-core performance was all that mattered, and More's Law was still in effect for individual CPU cores.

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.

GIL doesn't look that tough. I could kick his ass.

Waiting for Mojo to get some more mature.

Lua/LuaJIT >>>>>>>

is this going to be a experimental feature or in the future will it be default?

We have mojo for speed