icecream VS typer

Hey, very useful. Thanks! Similar to ic() for python, but with the nice ability to be used inline.

https://github.com/gruns/icecream

Icecream is great for this. Just calling ic(foo) gives you the same thing on stderr.

I get around this by using loguru (a wrapper around python's logger), so I get information like the calling function and line number with my debugging statements. I don't use it these days (and actually built something extremely similar around the same time), but icecream is another alternative that facilitates debugging-by-print

Most of the time I simply use icecream (a much better version of print()), and sometimes, I use pudb (a visual debugger) for tougher/trickier bugs.

We also have ice cream

I found icecream in a post on this subreddit and still use it as an alternative to print for debugging.

In the future using something like icecream might be interesting as well.

He is probably most well know for creating FastAPI that I taught to some of my clients and Typer that I've never used.

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/