[cardanome]

This is absolute key advice.

Another way to look at it is the functional core, imperative shell pattern.

Wrapping up your dict in a value object (dataclass or whatever that is in you language) early on means you handle the ugly stuff first. Parse don't validate. Resist the temptation of optional fields. Is there really anything you can do if the field is null? No, then don't make it optional. Let it crash early on. Clearly define you data.

If you have put your data in a neat value objects you know what is in it. You know the types. You know all required fields are there. You will be so much happier. No checking for null throughout the code, no checking for empty strings. You can just focus on the business logic.

Seriously so much suffering can be avoided by just following this pattern.

[sevensor]

I like to think about this as securing the perimeter. Inside, everything is typed, static analysis constrains what can happen, and I am never surprised as long as the code type checks. Outside, data is probably garbage. All the effort goes into locking down the interface. Pydantic is ok for this, although I find it too intrusive for my taste, and I think mixing arbitrary validity predicates with structural correctness is a mistake. Still, I’d much rather walk into a codebase that uses Pydantic than one that assumes its inputs are valid, because confidently writing business logic that can assume its inputs are correct is incredibly liberating.

[aequitas]

> Another way to look at it is the functional core, imperative shell pattern.

A good explanation of this is: https://www.destroyallsoftware.com/talks/boundaries

[cruffle_duffle]

Pydantic makes that stuff super simple too. It has all manner of data validation hooks as well as (de)serialization help.

[mcdeltat]

The "loosey-goosey" approach to data in coding is one of my biggest pet peeves. Some people absolutely insist on making everything as dynamic as possible, and then wonder why we end up with a buggy mess. I always found it very natural to move as much as possible into the type system, because why wouldn't I want the machine to find all my inevitable mistakes for me?

[majewsky]

My personal favorite of this has got to be a particular mess of a Python API that led to me implementing "type veryFlexibleUint64": https://github.com/sapcc/limes/blob/9ea9d1f86383f8a5fe0fa1d1...

[pbronez]

So brutal

[Kinrany]

There's little to disagree with here, and yet this comment reads like a slogan soup.