- Marseille, France
-
12:45
(UTC +01:00) - https://pauldufosse.xyz/
- in/paulduf
Stars
An extensible, state of the art columnar file format. Formerly at @spiraldb, now an Incubation Stage project at LFAI&Data, part of the Linux Foundation.
🎉 PyTorch efficient farthest point sampling (FPS) library.
A python package for qPCR primers design, check, annotate and visualize.
gReLU is a python library to train, interpret, and apply deep learning models to DNA sequences.
A curated list of Polars talks, tools, examples & articles. Contributions welcome !
Apache Hamilton helps data scientists and engineers define testable, modular, self-documenting dataflows, that encode lineage/tracing and metadata. Runs and scales everywhere python does.
Template to create python libraries out-of-the box
plakar is a backup solution powered by Kloset and ptar
Run pytest against markdown files/docstrings.
An open-source, self-hostable PaaS alternative to Vercel, Heroku & Netlify that lets you easily deploy static sites, databases, full-stack applications and 280+ one-click services on your own servers.
A library for easy, fast, and efficient reading & writing of PLINK Bed files
An extremely fast LaTeX formatter written in Rust
Reads key-value pairs from a .env file and can set them as environment variables. It helps in developing applications following the 12-factor principles.
A library that makes Evolutionary Strategies (ES) simple to use.
Python library for converting Python calculations into rendered latex.
A Python library to sanitize/validate a string such as filenames/file-paths/etc.
More routines for operating on iterables, beyond itertools
Hot and cold colormap for diverging data
This is code for introduction to casual inference
Polars extension for general data science use cases
🏆 A ranked list of awesome Jupyter Notebook, Hub and Lab projects (extensions, kernels, tools). Updated weekly.
Build custom inference engines for models, agents, multi-modal systems, RAG, pipelines and more.
A data modelling layer built on top of polars and pydantic
Experimental design and (multi-objective) bayesian optimization.