Indeed. while my bash-fu is redimentary at best, I don’t think Bash can be used for web scrapping ? But I think he could use RSS to get the posts, then extract youtube links with Regex and use the dump feature of yt-dlp* to get the video category, title,etc by using jq to parse the json. Then, it’s probably just a matter of using curl to do the API calls and voilà.

*yt-dlp is better maintained than youtube-dl, or so I heard.

It was just a recommendation. If you feel like python isn’t for you, you can try any other language and the only difference will be how much time it’ll take to make it, but otherwise you can use C if you want. Maybe you’re so used to low level programming like managing memory and having to declare types everywhere that python dumb proof approach is difficult for you. Just don’t think too hard about it, if it’s a personal use script then there’s no need to think about it’s efficiency or ugliness. If it works, it works.

If you work in bash and don’t like python, maybe it’s too strict. Look into Ruby. It was inspired by Perl. I found it more to my style in that there are many correct solutions and not one implied correct solution.

Python is basically runnable pseudo code that you would write on a napkin to explain stuff to somebody. There you don’t care about curly backets and naturally indent to show scope. It’s way simpler C and if you want to, you can add type hints (aka faux static typing).

Package management is done with pip although nowadays poetry is better as it uses one file to define everything about your project and configure the tools (linter, tester, autoformatter, static type checking)

The advantage of python is that it has lots and lots of libraries. You don’t need to fiddle around with the lemmy API - use a library:

• https://pypi.org/project/pylemmy/ - slightly newer
• https://pypi.org/project/Lemmy.py/ - looks abandoned but might suit your needs

Want to connect to musicbrainz? https://pypi.org/project/musicbrainzngs/ is probably the best.

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Create a virtual env (basically allows you to install all your project dependencies in an environment separate from the global one): python3 -m venv .venv.

Activate the virtual in your shell source .venv/bin/activate.

Now you can start installing dependencies. If you want it super simple, use pip install $package, but updating the list of packages you want in your project is manual: pip freeze > requirements.txt (install them again with pip install -r requirements.txt after rm -rf .venv should you want to start fresh) and you can run into problems with clashing dependencies.
So, I recommend using poetry pip install poetry. poetry new . to setup basic project structure, then add runtime dependencies with poetry add $package e.g poetry add pylemmy musicbrainzngs.

It’s possible to add dev dependencies with poetry like ruff for linting and autoformatting your code and mypy for static type checking. Your unit tests can be written using unittest from the standard library.

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If you have experience with COBOL why use anything else?

I hear it’s very popular and nice to use.

Another (mostly) retired Unix sysadmin here. I never could make Python work in my brain, but last year discovered Svelte/SvelteKit and really like it. I’d always kinda hated on JS, but actually it’s pretty nice these days.

I don’t like Python either. But I use it because it’s widely used because many others find it easy to learn and work with (I guess people like us think a bit differently). Maybe you should forge ahead with PHP (it’s having a mini resurgence in popularity).

If you’re sticking with Python, make sure you use the built in json module. If you need a plain English tutorial, this tutorial on the json module is solid. If you want some real time help you can always chat in the Python Matrix Room (#python:matrix.org).

The way that I see it is that some languages will “click” while others may not. Nothing wrong with that. I like your determination!

I’d say, from your stated problem, that you may be selling yourself short a bit. My colleagues and I frequently run into the same when debugging. And the approach that you are using to work through it is exactly what I’d recommend as well (along with type hinting). I also find the Python interactive shell great for testing concepts and do one-off things that are easier in Python than Bash.