hamilton VS avendish

And find the repository here: https://github.com/dagworks-inc/hamilton/

Python - https://github.com/stitchfix/hamilton (author here). It's great if you want your code to be always unit testable and documentation friendly, and you want to be able to visualize execution. Blog post on using it with Pandas https://link.medium.com/XhyYD9BAntb.

Yes! As one of the creators of https://github.com/stitchfix/hamilton this was one of the aims. Simplifying the cognitive burden for those developing and managing data transforms over the course of years, and in particular for ones they didn't write!

For example in Hamilton -- we force people to write "declarative functions" which then are stitched together to create a dataflow.

E.g. example function -- my guess is that you can read and understand/guess what it does very easily.

For (1) there are quite a few options - prefect is one, metaflow is another, airflow, dagster, even https://github.com/stitchfix/hamilton (core contributor here), etc.

If you're want to do more python https://github.com/stitchfix/hamilton allows you to model dependencies at a columnar (field) level.

Take a look at https://github.com/stitchfix/hamilton - we're after contributors who can help us grow the project, e.g. make documentation great, dog fooding features and suggesting/contributing usability improvements.

For a real world example of their power, we built an entire framework (https://github.com/stitchfix/hamilton) at Stitch Fix, where a lot of cool magic is provide via decorators - see https://hamilton-docs.gitbook.io/docs/reference/api-reference/available-decorators and these two source files (https://github.com/stitchfix/hamilton/blob/main/hamilton/function_modifiers_base.py, https://github.com/stitchfix/hamilton/blob/main/hamilton/function_modifiers.py ). Note we do some non-trivial stuff via them.

For data processing/transform code, I would recommend looking at https://github.com/stitchfix/hamilton, especially if you're trying to test pandas code. Short getting started here - https://towardsdatascience.com/how-to-use-hamilton-with-pandas-in-5-minutes-89f63e5af8f5 (disclaimer: I'm one of the authors).

The python package, hamilton, from Stitch Fix (https://hamilton-docs.gitbook.io/docs/) can help manage transformations on pandas dataframes. This DAG of transformations is managed separately in a file - so it can be versioned, in case the transformations change. The memory required is reduced, because only the API call tables and mapping parameter table have to be in memory. The calculated columns can be produced as needed. Just like dbt, transformations are separate from the source tables - but hamilton can be used on any python object - not just dataframes. dbt is SQL based.

Happy to introduce you to https://ossia.io there are a lots of tasks open! You can check the projects for the general development axes: https://github.com/ossia/score/projects?query=is%3Aopen ; e.g. Audio, Musicality, Integrations, JACK & Linux integration (some are in Classic projects mode) all have audio-related tasks, some easy, some hard.

Creating new Avendish plug-ins (docs: https://celtera.github.io/avendish/) could also be fairly useful, here's a very basic example one: https://github.com/celtera/avendish/blob/main/examples/Advan...

If you are interested in making max, pd, etc... extension you can look into https://github.com/celtera/avendish : it's made exactly for this and tries to stay very close from standard C++ unlike most existing audio frameworks which often come with their own bespoke standard library reimplementation. The documentation also tries to explain the c++ features it used, you might find this useful!

to automatically generate safe dlopen stubs for runtime dynamic library loading from header files

and through the C++ one (this one is an extremely quick and dirty prototype):

https://github.com/ossia/score/blob/master/src/plugins/score...

to pre-instantiate get(aggregate), for_each(aggregate, f) and other similar functions in https://github.com/celtera/avendish because of how slow it is when done through TMP (doing it that way removed literally dozens of megabytes from my .o and had a positive performance impact even with -O3) ; so I weep a lot when I read that people in the committee object to pack...[indexing]

I really don't know about this, I'm writing audio & media effects in a fairly declarative style with https://github.com/celtera/avendish and I'm so much more productive that it's not even funny - I can rewrite entire effects from scratch in the time that it used to take me to find a bug somewhere

For anyone using c++, my declarative system has some amount of support for clap: https://github.com/celtera/avendish / https://celtera.github.io/avendish/

But unlike clap, targetting this also gives direct access to a few other environments, namely Max, Pd, ossia score, with the list hopefully growing.

Here is an example minimal plugin : https://github.com/celtera/avendish/blob/main/examples/Raw/M...

Note that unlike pretty much every other c/c++ plugin API, the plugin code does not need to include any header, everything is done through reflection of struct members at compile-time.

Here's a per-sample noise generator which uses a small library of pre-made ports: https://github.com/celtera/avendish/blob/main/examples/Helpe...

And a very naive buffer-based audio filter : https://github.com/celtera/avendish/blob/main/examples/Helpe...

UI is supported without relying on a specific UI library, only on a canvas painter concept which can then target Qt, NanoVG, and others to come: https://github.com/celtera/avendish/blob/main/examples/Helpe...

since it binds directly to audio APIs at compile time, it has pretty much zero code size in itself, the smallest plugin it generates for VST2 is around 7kb IIRC

I've ported my lib https://github.com/celtera/avendish to P1061's experimental clang implementation to replace boost.pfr (https://github.com/celtera/avendish/blob/main/include/avnd/common/aggregates.hpp#L67) and it works great, it's only missing pack indexing because right now one still needs to do something like

Working on a sunset of this with https://github.com/celtera/avendish - C++ reflection makes this very easy

so interesting, as a mostly C++ dev, UE's C++ style feels absolutely awful aha. Of course they have to be here because c++ used to not have reflection but I think that nowadays one could use similar principles as the ones I've tried to develop for audio / media objects in https://github.com/celtera/avendish to implement game objects / UObject in a much cleaner way and with better compile times