bibtex-autocomplete VS red-mail

In the long tradition of automating things that take less than 5 minutes to do manually, I've made a CLI script to autocomplete BibTeX entries (open source on github). A lot of work but now I can just copy/paste the title of any article I stumbled upon and the script will often do the rest.

I made a command-line tool to autocomplete bibtex entries in python : https://github.com/dlesbre/bibtex-autocomplete. It works by auto-querying a bunch of online databases (www.crossref.org, arxiv.org, dlbp.org, researchr.org, and unpaywall.org)

These two are more user friendly alternatives for sending and receiving emails: - Red Mail - Red Box

It's the creator of Rocketry, Red Mail and Red Box again. This week I thought to make it easier to integrate command-line programs to your Python applications.

Some of you might know my other project, Red Mail, advanced email sender. This time I have quite a similar library to show, I just released a sister library for it: Red Box, the advanced email reader.

For example, you can send emails using built-in smtplib and email, but there is also Red Mail. Which provides you simpler interface.

I'm actually the author of Red Mail (email sending library) and Rocketry (Pythonic statement-based scheduler). I'm actually looking for example projects to create some practical tutorials of how one could use the libraries. Not sure which kind would be appealing to most and what kind of problems people have with alternative options (which I could address).

This can be easily achieved with Red Mail (for email sending), Red Bird (for handling the data in an abstract way) and Rocketry (for scheduling):

I have made a pretty handy SMTP sender for Python if the language is a bit familiar (the lib is extremely easy to use): https://github.com/Miksus/red-mail

Pandas gets rid of those tedious Excel tasks and then I use Red Mail for automating sending emails (disclaimer, I'm the author). To schedule things, you can use cron and Windows scheduler on simple things but Rocketry is also built for automating such tasks (disclaimer, I'm also the author). Then I use SQLAlchemy to pull data from databases and scheduled Jupyter notebooks for quick controls and checking commonly occurring problems. And Flask/FastAPI to build partial automation on tasks that still require manual step to inspect data etc.

Documentation: https://red-mail.readthedocs.io/en/latest/