Datamancer VS nimpy

I have been using Nim for all of my recent data munging and analysis. There's https://github.com/Vindaar/ggplotnim for plots (among others) and everything else has just been normal code. There's also https://github.com/SciNim/Datamancer if you need something more like tidyverse.

Check out Datamancer for your Pandas equivalent. If I recall correctly it does have the ability to read/write csv. If that doesn't suite you, there is a Python/Nim bridge called Nimpy. I do a lot of machine learning projects and have to use OpenCV and some other things from python because it doesn't exist yet. It's a pretty damn cool library.

worked on the roadmap https://github.com/nim-lang/Nim/pull/19388 (enable -d:nimPreviewFloatRoundtrip and -d:nimPreviewDotLikeOps) and found that an important_packages (datamancer) failed. So I made a PR (https://github.com/SciNim/Datamancer/pull/23). It is not a bug of nimPreviewFloatRoundtrip(It seems like a precision problem to me) so alternatively datamancer can be disabled transiently.

There seems to be two major ones for Nim, NimData and Datamancer. Which one is better?

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

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

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.

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.

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.

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

See this nimpy issue about it: https://github.com/yglukhov/nimpy/issues/43

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.

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