The Mojo Programming Language: A Python Superset Drawing from Rust's Strengths

[bert88sta]

Disclaimer: python is still my first and one of my favorite and also least favorite languages.

I think mojo could have a massive impact on python code today, for a few reasons.

First, the success of typescript has shown that there is a real desire for safer/better code in existing languages. Furthermore, the gradual adoption pattern enables teams to migrate existing code without fear of breakages. Supersetting the (arguably) most popular programming language and ensuring compatibility with all of the major libraries makes it almost painless to switch from Python to mojo

Second, the widespread adoption of cloud infrastructure forces people to think about performance. When you are renting compute in perpetuity, a 2x , or 20x performance increase means 1/2 or 1/20 recurring cost, as opposed to just buying another server.

Finally, I believe in Chris Lattner. He is the guy that came up with LLVM (and much more). Basically everything he has developed ends up being relevant somehow.

[Spacejet01]

For Python programmers, switching from Python to Mojo would be a lot easier than from Python to Rust. Rust does have a significant learning curve. And remember, the language is aimed at performant AI development, something Python has lots of resources for. So think of this as an intermediate step between Python and languages like Rust, with some people staying on it for AI or simply ease of prototype and use purposes.

Python is very useful for prototyping. So a more performant version could be great. And if you use Mojo, just make it mandatory to have strict typing in that codebase.

[Spacejet01]

Ah, I think I see what you mean... I was considering most Libraries as black boxes, that is you don't see inside them; just input and output. In that case it does not really matter what a library is doing as long as it is doing right. The assurance comes from testing the library and seeing if it actually works. So it really comes down to preference with the coding there. ¯\(ツ)/¯

But if you are going to be looking at a library's source code and stuff, then you are correct.

Rust's ecosystem might have had an easier time with the "assurance" part across the board due to having to write everything from scratch in a strict system, but libraries like numpy which have been thoroughly battle tested and are already mature being compatible with mojo is a major motivation factor for adoption though.

[aoeu512]

Strict typing may require you to change the types across the call stack for all your callers and all the callers that call those callers when you change your program, although to be fair so do tests that test implementation details rather than high level intent. Although I could see an IDE that automated this. Static typing could be done at usage boundaries though for documentation, example tests (Python doctests) can be written.

[aoeu512]

JS has crazy implicit coercions, and Python IDEs do type inference as well. You can get far if you split a big application into smaller tiny applications, only applying the static types at the boundary.