nimic is a lightweight pure Python package that emulates Nim types and constructions, making it straightforward to transpile to Nim and compile AOT. Key principle: nimic code is valid Python that runs unmodified in CPython and also transpiles to equivalent Nim code.
Because nimic code is just standard Python with type hints and ctypes shims, it is a fully valid CPython script, so you can use the Python REPL during development, drop a breakpoint in the middle of a heavy algorithmic loop and inspect the variables natively.
Zero Lock-In: You don't need a special runtime engine. If the Nim compiler is not available, your script still runs (albeit slower than standard Python due to some emulation overhead) on any machine with Python installed.
Seamless Distribution: You can use this to develop high-performance logic natively in Python, debug it with Python tooling, and then compile to a native executable or C-extension via Nim.
Why Nim? Its syntax maps well to Python, it is rather clear how to emulate its constructions in Python, and its performance is comparable to C (as it compiles to C). Port of the "trace-of-radiance" Nim project to nimic can be found in "ndsl_raytracer" in my GitHub repo (dima-quant). With the compiled executable the render time for a single 512x288 scene dropped from many hours in Python to just 10 minutes on a single M1 CPU core. The repo also includes nimic ppm to mp4 converter.
Similar projects: - Pyccel (https://github.com/pyccel/pyccel): Python extension language using accelerators - SPy (https://github.com/spylang/spy) is a variant of Python specifically designed to be statically compilable while retaining a lot of the "useful" dynamic parts of Python. - Codon (https://github.com/exaloop/codon) is a high-performance Python implementation that compiles to native machine code without any runtime overhead.
It is still work in progress, e.g. there is no JIT and multiprocessing support yet, but now I'm not sure what functionality would be best to implement next. Any suggestions?
If it's possible and you intended for it to be a long-term project, I would suggest looking at designing an MIR for the Python to lower to and then lowering it to Nim, and that is probably the most valuable feature you can add to Nimic. That's what Rust had to learn the hard way, and that's how LLVM works, and having an intermediate representation means your compiler is going run into a lot less edge cases during development.
so it is what https://github.com/mypyc/mypyc was supposed to be ... i can just use write my python code add some type hints and it should run faster ... like cython but without learning a new dsl?
Yeah, indeed, I actually read about mypyc a few years ago before starting nimic. Though the goal is very similar, mypyc does not support compilation to a native executable and the performance gains were somehow limited to 2x-4x, as reported in https://sichard.ca/blog/2022/05/compiling-black-with-mypyc-p...
cython uses type hints now
So the big advantage of nimic is that code remains valid Python and all valid Python cam be compiled?
The transpile to a language that transpiles to C approach is unusual. Downsides of that other than slower compilation?
Not quite "all valid Python." Just to be clear: nimic is a strict, statically typed subset of Python. At this stage, the downside of having Nim as an intermediate step is not really a slower compilation, as Nim compiler is very fast, but more like: debugging executable, might involve line numbers of the intermediate Nim or C source code; the need to install Nim compiler for development; memory management (currently it is ORC/ARC or manual in Nim, no borrow checker yet)
Sorry, missed the word "subset"!
I would start with a human-written README and benchmarks?
Yeh, indeed, the README was mostly generated, though the introduction is largely human-written :-) Is some specific description missing? I can provide more practical code examples directly in README. The benchmarks are mostly on runtime performance I assume?
> Is some specific description missing?
No, the problems are a) you get the same exact AI "voice" that is tedious to keep reading, b) it's verbose and focuses on the wrong things (the whole Module Architecture section doesn't belong there), and c) it's a sign that it's slop and not well tested.
> The benchmarks are mostly on runtime performance I assume?
You tell me! You (or Claude) make performance claims - "aiming to get C-level performance without leaving Python". Does it actually get anywhere near that claim?
Fully fair, I'd need to spend more time on the text. The nimic was mostly tested on the raytracer project dima-quant/ndsl_raytracer, and the performance was indeed quite near the C-level.