awesome-music VS nbdev

Next to read the music you need a player library. Here is list of useful ones per your case/framework https://github.com/ciconia/awesome-music

https://github.com/ciconia/awesome-music

reaper is another DAW that is not free but its only 60 or something so its practically nothing compared to others. i used it for 3 or so years without paying and the only drawback is you have to wait 5 seconds for the nag screen at the start to close.

i don't want to sound like im on commission for reaper but i really love how fast it is to open a project and get started (once you have a licence that is), it has no bs logins that need to connect to a server before it will work. its insanely customisable and its also portable so you can run it from a usb drive. you can also have different versions that can run side by side and be set up in different ways with different settings etc.

One example I've seen is ML/DL folks using jupyter notebooks to develop DL libraries in jupyter notebooks, see https://github.com/fastai/nbdev

- https://github.com/fastai/nbdev: Increase developer productivity by 10x with a new exploratory programming workflow.

9. Nbdev: Boost developer productivity with an exploratory programming workflow - https://nbdev.fast.ai/

See if you like nbdev way of working with data through python and jupyter. nbdev is an optional part that will create python packages from jupyter notebooks. Also even the simple tutorials are opinionated and will guide you to unit test your code and write CICD pipelines.

You probably don’t have time for this for the purposes of your task, but I will also throw in the recommendation of nbdev especially if you’re a Python person. I haven’t had a project to use it on yet, but I’ve gone through the docs and the walkthrough and it seems like a great framework for starting potential projects with all the infrastructure needed for if/when they eventually get big and need all the packaging and stuff

nbdev: jupyter notebooks -> python package

Take a look at https://github.com/fastai/nbdev - haven't used it but supposedly the whole if fast.ai library was written that way. It sounds like a natural direction in your scenario - allowing your to keep working in a familiar environment and still producing production ready code (will, at least in paper 😅)