Python, data, docs¶

This site lists my findings about programming, economic data and writing documentation.

Python:

I recommend these three resources as good introductions to Python.
Lectures like “Beyond PEP8” by Raymond Herringer appeal to you as a better Python developper.
Check trending on Github and JetBrains annual user surveys to see what is cool and popular in Python.
just and pytest are my friends for project housekeeping and unit testing
I maintain two Python packages for economic statistics:
- boo - get annual accounting reports of 1.2+ million Russian firms
- weo - get IMF WEO semi-annual releases as pandas dataframes

Julia:

I wrote Julia, surprise me! blog post when learning Julia (things improved since).
Russian and Kazakh telegram channels on Julia are thrillingly active and accept questions in English too.

Haskell:

7 classes of Haskell, a curated introduction to Haskell by Yuras Shumovich and a follow-up reading list.

Software engineering. See a list of essential books and thought-provoking quotes.

Static site generators. This site is built with Jupyter Book, a recent tool that uses Sphinx and a custom variety of Markdown (MyST) with emphasis on interactivity, code execution and, hopefully, PDF rendering. Other popular static site generators described here.

Add more stuff: contacts, mid-tech data science, optimizations, reproducible research, missed-semester, tools for economists, Econometrics Navigator, technical writing, Nim/Rust, and a time-keeping tool I often forget about.

Twitter. This site release announcement is pinned here.