nimpy | mojo | |
---|---|---|
38 | 20 | |
1,416 | 21,199 | |
- | 17.9% | |
5.8 | 9.9 | |
3 months ago | 7 days ago | |
Nim | Mojo | |
MIT 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.
nimpy
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Mojo is now available on Mac
I mean honestly, the closest language to Mojo really is Nim. In the latest Lex Fridman interview [0] when he talks about his ideas behind Mojo it pretty much sounds like he's describing Nim. Ok fair, he wants Mojo to be a full superset of Python, but honestly with nimpy [1] our Python interop is about as seamless as it can really be (without being a superset, which Mojo clearly is not yet). Even the syntax of Mojo looks a damn lot like Nim imo. Anyway, I guess he has the ability to raise enough funds to hire enough people to write his own language within ~2 years so as not have to follow random peoples whim about where to take the language. So I guess I can't blame him. But as someone who's pretty invested in the Nim community it's quite a shame to see such a hyped language receive so much attention by people who should really check out Nim. ¯\_(ツ)_/¯
[0]: https://youtu.be/pdJQ8iVTwj8?si=LfPSNDq8UKKIsJd3
[1]: https://github.com/yglukhov/nimpy
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Show HN: Pip Imports in Deno
You can also do this in Nim, which basically means you can write any program you could in Python with libraries in Nim. https://github.com/yglukhov/nimpy
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Nim v2.0 Released
Ones that have not been mentioned so far:
nlvm is an unofficial LLVM backend: https://github.com/arnetheduck/nlvm
npeg lets you write PEGs inline in almost normal PEG notation: https://github.com/zevv/npeg
futhark provides for much more automatic C interop: https://github.com/PMunch/futhark
nimpy allows calling Python code from Nim and vice versa: https://github.com/yglukhov/nimpy
questionable provides a lot of syntax sugar surrounding Option/Result types: https://github.com/codex-storage/questionable
ratel is a framework for embedded programming: https://github.com/PMunch/ratel
cps allows arbitrary procedure rewriting to continuation passing style: https://github.com/nim-works/cps
chronos is an alternative async/await backend: https://github.com/status-im/nim-chronos
zero-functional fixes some inefficiencies when chaining list operations: https://github.com/zero-functional/zero-functional
owlkettle is a declarative macro-oriented library for GTK: https://github.com/can-lehmann/owlkettle
A longer list can be found at https://github.com/ringabout/awesome-nim.
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Prospects of utilising Nim in scientific computation?
I use Python daily for its massive momentum for scientific stuff, but I also use Nim for everything else. Nim compiles to C, and making Python native modules with Nim is easy with Nimpy.
- Can't run compiled nim code in Python
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Returning to Nim from Python and Rust
If are a data scientist and come from python take a look at nimpy, a great way to just import python libraries and use them! https://github.com/yglukhov/nimpy Numpy, pandas, pytorch all usable in Nim.
Nim is the ultimate glue language, use libraries from anything: python, c, js, objc.
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Python's “Disappointing” Superpowers
I've come to really enjoy programming in Nim. Note that Nim is very different language despite sharing a similar syntax. However, I feel it keeps a lot of the "feel" of Python 2 days of being a fairly simple neat language but that lets you do things at compile time (like compile time duck typing).
There's a good Python -> Nim bridge: https://github.com/yglukhov/nimpy
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Dunder methods in nimpy
See this nimpy issue about it: https://github.com/yglukhov/nimpy/issues/43
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What language to move to from python to speed up algo?
It has pretty good integration with python, either for having your main code in python and writing small hot functions as nim and importing via nimporter or using python libraries in nim via nimpy.
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ABI compatibility in Python: How hard could it be?
Related: Nimpy[0] provides an easy way to write Python extensions in Nim, which manages the ABI side very well.
Python 2 is now gone, but until it was, Nimpy was an easy way to write Python extension modules that only needed to be compiled once, and would work with any of your installed Python 2 and Python 3. Magic.
[0] https://github.com/yglukhov/nimpy
mojo
- The Mojo Programming Language
- Mojo language goes open source
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The Mojo programming language has changed its version numbering. Release v24.1.1
https://github.com/modularml/mojo/blob/main/LICENSE Is this not it?
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Dada, an Experiement by the Creators of Rust
Interesting, but the intent seems similar to Chris Lattner's new Mojo language which arguably has similar characteristics and is further along in its development.
https://docs.modular.com/mojo/
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Mojo - A New Programming Language for AI
Mojo is a programming language that combines the performance and control inherent in systems languages like C++ and Rust with the flexibility and simplicity of use typical of dynamic languages like Python. Because of its combination of performance, extensibility, and usability, its design makes it possible to construct high-performance systems, which makes it a good option for AI development.
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Mojo is now available on Mac
If you take a look at the optimized Mojo code doing the matrix multiply [1], it takes an expert to understand. It’s not just some simple for-loops in Mojo they’re comparing against.
[1] https://github.com/modularml/mojo/blob/5ce18c47a27c0c4123de1...
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Programming Languages Every Developer Should Watch Out For
Mojo truly unlocks a world of possibilities in high-performance computing.
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A Gentle Introduction to Liquid Types
For a concrete example of Liquid Haskell, see how Gabriella Gonzalez safely removed bound checks of high-performance protocol parsing, in "Scrap your Bounds Checks with Liquid Haskell" [1].
With Liquid Haskell, the bound checks are moved from runtime to compile time, semi-automatically handled by SMT-solvers. With static types, programmers can write correct programs faster, and the programs also run faster.
As an aside, speeding up programs with static analysis (constrained dynamism) are also present in Mojo (a variant of Python) or Swift [2].
[1]: https://github.com/Gabriella439/slides/blob/main/liquidhaske... "Scrap your Bounds Checks with Liquid Haskell"
[2]: https://github.com/modularml/mojo/discussions/466 "Mojo and Dynamism"
- Mojo and Dynamism
What are some alternatives?
Nim - Nim is a statically typed compiled systems programming language. It combines successful concepts from mature languages like Python, Ada and Modula. Its design focuses on efficiency, expressiveness, and elegance (in that order of priority).
Flask - The Python micro framework for building web applications.
Box - Python dictionaries with advanced dot notation access
node - Node.js JavaScript runtime ✨🐢🚀✨
nimporter - Compile Nim Extensions for Python On Import!
go - The Go programming language
scinim - The core types and functions of the SciNim ecosystem
CPython - The Python programming language
nimpylib - Some python standard library functions ported to Nim
Laravel - Laravel is a web application framework with expressive, elegant syntax. We’ve already laid the foundation for your next big idea — freeing you to create without sweating the small things.
nimskull - An in development statically typed systems programming language; with sustainability at its core. We, the community of users, maintain it.
mdbootstrap - React 18 & Bootstrap 5 & Material Design 2.0 UI KIT