nimpylib
viroiddb
Our great sponsors
| nimpylib | viroiddb | |
|---|---|---|
| 1 | 2 | |
| 182 | 5 | |
| - | - | |
| 3.4 | 0.0 | |
| 3 months ago | about 1 year ago | |
| Nim | Vue | |
| MIT License | MIT License |
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nimpylib
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Why I Use Nim instead of Python for Data Processing
Another nim & python thread that has not been mentioned yet here
https://news.ycombinator.com/item?id=28506531 - project allows creating pythonic bindings for your nim libraries pretty easily, which can be useful if you still want to write most of your toplevel code in python, but leverage nim's speed when it matters.
If you want to make your nim code even more "pythonic" there is a https://github.com/Yardanico/nimpylib, and for calling some python code from nim there is a https://github.com/yglukhov/nimpy
viroiddb
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Why I Use Nim instead of Python for Data Processing
That's great. However the method that you use to find the canonical representative [1] is quadratic (when the string has length N, there are N rotations and for each rotation you need to check N characters to determine whether this is earlier than the best on that you have found so far). For large strings you would probably want to switch to one of the linear minimal string rotation algorithms [2].
[1] https://github.com/Benjamin-Lee/viroiddb/blob/main/scripts/c...
[2] https://en.wikipedia.org/wiki/Lexicographically_minimal_stri...
What are some alternatives?
nimpy - Nim - Python bridge
benchmarks - Some benchmarks of different languages
Primes - Prime Number Projects in C#/C++/Python
scikit-bio - scikit-bio: a community-driven Python library for bioinformatics, providing versatile data structures, algorithms and educational resources.
nim-playground-frontend - The front-end for https://play.nim-lang.org
nimtorch - PyTorch - Python + Nim
boomer - Zoomer application for Linux
PrimesResult - The results of the Dave Plummer's Primes Drag Race
nim-fswatch - Nim wrapper for the fswatch library
Arraymancer - A fast, ergonomic and portable tensor library in Nim with a deep learning focus for CPU, GPU and embedded devices via OpenMP, Cuda and OpenCL backends