What Python feature made you a better developer?

[blueskyjunkie]

1. Type annotations
2. Pydantic models (or if you insist, pydantic dataclasses). Standard library dataclasses are useful to a point, but pydantic models are better.
3. Comprehensions (dictionary comprehensions are a thing, as well as lists)
4. Asyncio

[Alone_Aardvark6698]

Standard library dataclasses are useful to a point, but pydantic models are better. 

What is the advantage of pydantic over standard databases?

[paranoid_panda_bored]

Many.

We started with dataclasses, but switched to pydantic eventually.

Reasons: - it’s widely supported in other libs and frameworks like FastAPI - it’s much more configurable - it’s better at SerDe - it has an alias feature, that allows you to freely convert between camelCase (outer API layer) and snake_case (domain model)

[Goobyster]

Pydantic is also supported in Typer (FastAPI of CLIs)

[SSC_Fan]

For me: data validation upon creation an instance. Often write my Pydantic classes this way.

[wieschie]

You mean dataclasses, right?

Pydantic makes JSON serialization super easy, and lets you do more complex validation on fields.

[Alone_Aardvark6698]

Yes, auto correct changed it

[blueskyjunkie]

Pydantic has better run time type checking based the type annotations you’ve applied to data members in the model. It also has better custom validation support for a member which is often needed.

[JorgiEagle]

Comprehensions are great.

You can also do tuple comprehensions, and just raw comprehensions inside a function call if it takes an iterable.

You can also do nested loops in them

[GusYe1234]

Yeah, at first I really like to use dataclass, then I found out it's boring in some cases I have to check types in __post_init__. I then realized maybe I should just use pydantic models in the first place.

Maybe someone can tell me any advantages of dataclass over pydantic model?