attrs

This is great recommendation, you can get very far by reading well written code. These have very well written Python, exposing much of the language expressiveness: - https://github.com/python-attrs/attrs - https://github.com/mahmoud/glom - https://github.com/pytoolz/toolz - https://github.com/Suor/funcy - https://github.com/dabeaz/curio ps: dabaez has great educational content on writing idiomatic python, definitely worth checking out An honorable mention of norvig's classic essays, which got me into python while I was in college, over 12y ago: https://norvig.com/spell-correct.html. Aside from reading code, _writing_ something that you know it exist (e.g glom) and then comparing it to how others have done it is also a great learning experience.

Anything requiring e.g. setattr, getattr, delattr? Without looking far, https://github.com/python-attrs/attrs/blob/main/src/attr/_ma...

It's parametric, sure. It's not "full" in that it can't express the types of many language features well enough that inference works. Something like the attrs package needs to use a kludge[1] to communicate types back to a validator. https://github.com/python-attrs/attrs/blob/4f74fbaca3cc12911...

In Python we sometimes differentiate the different meanings like "whatever", "default" or "not set yet" by defining a singleton object and comparing by identity, because None would be acceptable value and we need to differentiate the meaning. Examples: https://github.com/marshmallow-code/marshmallow/blob/c1506cc... https://github.com/python-attrs/attrs/blob/eda9f2de6f7026039...

Data Classes are a cool feature, useful, and a superior alternative to namedtuple. But while this was brewing, attrs ate their lunch. Data Classes just don't go far enough compared to what attrs [1] has provided for a while now. If there's a compelling reason to switch, I haven't found it yet. Can I use Data Classes in a library supporting Python 2.7, 3.4-3.7? I don't think the answer is yes today. [1]: https://github.com/python-attrs/attrs

Or https://github.com/python-attrs/attrs

Take a look at https://github.com/python-attrs/attrs which will let you do something like import attr @attr.s class Key(object): modifier = attr.ib() key = attr.ib() function = attr.ib() argument = attr.ib() keys = [ Key(MODKEY, XK_p, spawn, {'v': dmenucmd}), Key(MODKEY|ShiftMask, XK_Return, spawn, {'v': termcmd}), # ... ] which gets you the concise and readable syntax of C structs, while keeping these things as actual attributes as if they were classes (e.g., [key.modifier for key in keys] will work). And you get designated initializers via Python's usual keyword-argument syntax, the ability to specify attr.ib(default=...), and a few other things.

Much of the code in the post could be simplified by using the awesome `attrs` package [1]. Or if / when PEP 557 gets adopted. [1]: https://github.com/python-attrs/attrs [2]: https://www.python.org/dev/peps/pep-0557/

Agreed, I use the fact that "namedtuples are tuples" constantly. For one thing, you can pass them to 3rd party libraries that take tuples while maintaining readability on your end. I would be horrified if they dropped index access. It would break everything. I should say though, for simple POJO-style classes @attr.s (https://github.com/python-attrs/attrs) has replaced 90% of my namedtuple usage.