89 private links
Allows you to instantly try any python packages from the command line.
Basically like pipx, just for python libraries (i.e. packages without a runnable executable).
A lot (and I mean a lot) of coding challenges preparing you for learning algorithms, data structures, some pointers on system design.
Also has Anki flashcards, though I do not know how effective they are considering a lot of the challenges amount to coding up a solution.
A deep dive 'problem solving report' of how to use property decorators (i.e. creating getters and setters) for python dataclasses. Not as easy as it seems! But in the end fairly elegant.
Pretty in-depth hexagonal world generator, taking temperature, moisture and more into account.
A useful early warning signal computing library which can detect, calculate and notify you of bifurcations in time series.
A framework for elegantly configuring complex applications.
Configuration management for python projects, may be useful to store simple and repeatable configurations for data science projects as well.
Open-source version control system for Data Science and Machine Learning projects. Git-like experience to organize your data, models, and experiments.
A way to track data - even if it is in different locations - alongside code, mimicking its version control. Seems a little complicated but really useful, especially with additional features like data pipelines that are contained
Another bibliography manager for the command line. This one seems fairly nice: It keeps everything in plain-text (unlike papis), seems fairly customizable and extensible (unlike bibman), has some quality of life features like doi/arxiv import, git versioning and a plugin system.
Having used it a little - it is fairly nice, except for two niggling issues: with around 1000 library entries it becomes pretty sloow and it does not allow for advanced query syntax, even though it seems like it would support it. Author search only search in last names and you can not use any boolean logic to search for anything not tagged a certain way for example. These two issues are pretty major for larger libraries.
Reproducible datasci - you create data ingestors, then create small modules of transformation (the engineering), then do whatever you want with the data (the science).
Seems quite nice for larger projects and like it could save you some time down the road (forking another project off an existing or returning to an old project with its standardized nature).
Poetry alternative, another package manager for python. Seems people are beginning to prefer it over poetry in many cases.
A whole recommendation flood of going about sql learning. Syntax, Fundamentals, some advanced advice. Can be used to comfortably build a personal learning path.
An exhaustive book, free and available online, on publishing workflow.
Getting, preparing, cleaning data. Exploratory analysis and modelling with regression. Creating reproducible documents with quarto. Seems really nice and good to delve into for data analysis.
Inspired by Gooey, just made for the click library. Does not currently have a pypi repository as far as I can see, which makes it a bit harder to integrate into projects.
A selection of data processing libraries for python - image, audio, video, text, tabular - it's all there.
Command line tool for improving typing skills - can do random sampling from entries you give it, or use machine learning training sets to give you typing tasks (for a variety of programming languages as well!)
Statistical inferrence, various python plot types and Correlation vs causation explained in a series of blog-posts. Very beginner-friendly with drawings etc
Python bindings for ripgrep. Seems simple enough!
RMarkdown for the python world, built on pandoc. This seems like an amazing alternative to the R world (though it includes support for R) and all the bookdown and blogdown alternatives.
A nicely compiled list, especially of de-facto fits-for-all standards for package/venv management, testing, linting and some learning resources thrown on top.