TUI-apps VS typer

Hello!

I am pleased to announce a new version of my "CLI text processing with GNU sed" ebook. This book heavily leans on examples to present features one by one. In addition to sed commands and options, regular expressions are also discussed in detail.

Links:

* PDF/EPUB versions: https://learnbyexample.gumroad.com/l/gnu_sed (free for a few days)

* Web version: https://learnbyexample.github.io/learn_gnused/ (always free)

* Markdown source, example files, etc: https://github.com/learnbyexample/learn_gnused

* Interactive TUI app for exercises: https://github.com/learnbyexample/TUI-apps/blob/main/SedExercises

I would highly appreciate it if you'd let me know how you felt about this book. It could be anything from a simple thank you, pointing out a typo, mistakes in code snippets, which aspects of the book worked for you (or didn't!) and so on. Reader feedback is essential and especially so for self-published authors.

Happy learning :)

I also wrote an interactive TUI app based on some of the exercises from the ebook. Reference solutions are provided for both GNU grep and ripgrep.

These days I prefer coding TUI apps using Textual (see my repo https://github.com/learnbyexample/TUI-apps for examples) since I find this framework easier to work with and I don't need full GUI features for my projects.

This year I started updating my existing books and I'm also creating interactive apps. Here's one for Python regex: https://github.com/learnbyexample/TUI-apps/blob/main/PyRegexExercises. Next is grep.

Having an interactive program that automatically loads questions and checks the solution is wonderful to have while learning a topic. I wrote a TUI app that has beginner to advanced level exercises for Python regular expressions. There are more than 100 exercises covering both the builtin re and third-party regex modules.

I have been using Typer on every one of my CLI projects which uses Click under the hood. The documentation is fantastic, the CLI app it produces looks great and lets you create things quickly. I high recommend it.

https://typer.tiangolo.com/

Adding CLI capabilities. My preferred library here is typer.

I just heard about this but it seems to be pretty much the type of thing you want and want fast.

Docstrings are for documenting how a function/ class/ method/ module works. Often you don't need to add a docstring to your main function because no one will be importing it to use elsewhere. And if you want it to run as a CLI, then there are better ways to document the available options. For example, typer does most of it for you, or in click you add the help text to the decorator.

Most computing tasks in airflow DAGs are KubernetesPodOperator containing a CLI (Python Typer). It allows us to pass arguments easily to run DAG manually if needed (the new UI to pass arguments to DAG in airflow 2.6 is really nice). Arguments allow us to replay DAG easily (change start / end dates for instance).

So it's basically the main .gitlab-ci.yml file plus a separate Python CI app using Typer for the AWS instrumentation.

Similarly for Typer, which is literally "the FastAPI of CLIs"[1]. Handy to type your `main` parameters and have CLI argument parsing. For more complicated cases, it's a wrapper around Click.

[1] https://typer.tiangolo.com/

interesting that you hate python, but love Click. Did you try Typer which uses Click underneath?