Numba
Nim
Our great sponsors
Numba | Nim | |
---|---|---|
124 | 346 | |
9,404 | 16,048 | |
1.6% | 0.7% | |
9.9 | 9.9 | |
7 days ago | 3 days ago | |
Python | Nim | |
BSD 3-clause "New" or "Revised" License | GNU General Public License v3.0 or later |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Numba
-
Mojo🔥: Head -to-Head with Python and Numba
Around the same time, I discovered Numba and was fascinated by how easily it could bring huge performance improvements to Python code.
-
Is anyone using PyPy for real work?
Simulations are, at least in my experience, numba’s [0] wheelhouse.
-
Any data folks coding C++ and Java? If so, why did you leave Python?
That's very cool. Numba introduces just-in-time compilation to Python via decorators and its sole reason for being is to turn everything it can into abstract syntax trees.
- Using Matplotlib with Numba to accelerate code
-
Python Algotrading with Machine Learning
A super-fast backtesting engine built in NumPy and accelerated with Numba.
-
PYTHON vs OCTAVE for Matlab alternative
Regarding speed, I don't agree this is a good argument against Python. For example, it seems no one here has yet mentioned numba, a Python JIT compiler. With a simple decorator you can compile a function to machine code with speeds on par with C. Numba also allows you to easily write cuda kernels for GPU computation. I've never had to drop down to writing C or C++ to write fast and performant Python code that does computationally demanding tasks thanks to numba.
-
Codon: Python Compiler
Just for reference,
* Nuitka[0] "is a Python compiler written in Python. It's fully compatible with Python 2.6, 2.7, 3.4, 3.5, 3.6, 3.7, 3.8, 3.9, 3.10, and 3.11."
* Pypy[1] "is a replacement for CPython" with builtin optimizations such as on the fly JIT compiles.
* Cython[2] "is an optimising static compiler for both the Python programming language and the extended Cython programming language... makes writing C extensions for Python as easy as Python itself."
* Numba[3] "is an open source JIT compiler that translates a subset of Python and NumPy code into fast machine code."
* Pyston[4] "is a performance-optimizing JIT for Python, and is drop-in compatible with ... CPython 3.8.12"
-
This new programming language has the potential to make python (the dominant language for AI) run 35,000X faster.
For the benefit of future readers: https://numba.pydata.org/
-
Two-tier programming language
Taichi (similar to numba) is a python library that allows you to write high speed code within python. So your program consists of slow python that gets interpreted regularly, and fast python (fully type annotated and restricted to a subset of the language) that gets parallellized and jitted for CPU or GPU. And you can mix the two within the same source file.
- Numba Supports Python 3.11
Nim
-
Top Paying Programming Technologies 2024
22. Nim - $80,000
-
"14 Years of Go" by Rob Pike
I think the right answer to your question would be NimLang[0]. In reality, if you're seeking to use this in any enterprise context, you'd most likely want to select the subset of C++ that makes sense for you or just use C#.
- Odin Programming Language
-
Ask HN: Interest in a Rust-Inspired Language Compiling to JavaScript?
I don't think it's a rust-inspired language, but since it has strong typing and compiles to javascript, did you give a look at nim [0] ?
For what it takes, I find the language very expressive without the verbosity in rust that reminds me java. And it is also very flexible.
[0] : https://nim-lang.org/
-
The nim website and the downloads are insecure
I see a valid cert for https://nim-lang.org/
-
Nim
FYI, on the front page, https://nim-lang.org, in large type you have this:
> Nim is a statically typed compiled systems programming language. It combines successful concepts from mature languages like Python, Ada and Modula.
-
Things I've learned about building CLI tools in Python
You better off with using a compiled language.
If you interested in a language that's compiled, fast, but as easy and pleasant as Python - I'd recommend you take a look at [Nim](https://nim-lang.org).
And to prove what Nim's capable of - here's a cool repo with 100+ cli apps someone wrote in Nim: [c-blake/bu](https://github.com/c-blake/bu)
-
Mojo is now available on Mac
Chapel has at least several full-time developers at Cray/HPE and (I think) the US national labs, and has had some for almost two decades. That's much more than $100k.
Chapel is also just one of many other projects broadly interested in developing new programming languages for "high performance" programming. Out of that large field, Chapel is not especially related to the specific ideas or design goals of Mojo. Much more related are things like Codon (https://exaloop.io), and the metaprogramming models in Terra (https://terralang.org), Nim (https://nim-lang.org), and Zig (https://ziglang.org).
But Chapel is great! It has a lot of good ideas, especially for distributed-memory programming, which is its historical focus. It is more related to Legion (https://legion.stanford.edu, https://regent-lang.org), parallel & distributed Fortran, ZPL, etc.
- NIR: Nim Intermediate Representation
What are some alternatives?
NetworkX - Network Analysis in Python
zig - General-purpose programming language and toolchain for maintaining robust, optimal, and reusable software.
jax - Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
go - The Go programming language
Dask - Parallel computing with task scheduling
Odin - Odin Programming Language
cupy - NumPy & SciPy for GPU
rust - Empowering everyone to build reliable and efficient software.
Pyjion - Pyjion - A JIT for Python based upon CoreCLR
crystal - The Crystal Programming Language
SymPy - A computer algebra system written in pure Python
v - Simple, fast, safe, compiled language for developing maintainable software. Compiles itself in <1s with zero library dependencies. Supports automatic C => V translation. https://vlang.io