cats VS mypy

A functional programming library: https://typelevel.org/cats/

Learn something that pays the bill first - nowadays it's Golang/Rust react/typescript. Then you can try some pure fp libs like fp-ts and fp-core.rs, and look through existing scala cats docs. If you'll feel bad about it - that's totally fine and expectable, fp takes a paradigm shift and not that many dev able to shift their brains way of thought due to basic psychological rigidity) (inability to change habits and to modify concepts/attitudes once developed). And that's purely a staffing and management issue - folks hired randoms out of the blue, and called 'em a team.

I'm sorry, but have you ever done functional programming for a real company, like in a functional programming language like Haskell, Scala, or F#? Have you ever used Scala cats or scalaz? Have you ever learned category theory and how to apply its abstractions in software? Listen u/judethedude2106 this person hasn't gone as far down the functional programming rabbit hole as I have. Beyond learning the basics like the difference between pure and impure functions, what are closures, what higher order functions are and the most common ones like .map, .filter, and .flatmap, the immutable collections like immutable linked lists and trees, and what a Monad is and common monads like those used for futures/promises, async programming, and Option (Some or None, which is used instead of null checking), the more advanced functional programming stuff like category theory based abstractions are totally useless for real jobs and is just a giant time suck. Don't waste years on functional programming, spend at most a few months on it and no more.

As a former functional programmer in Scala, please do not go deep into the Category Theory programming. Scala has libraries like this one called "Cats", a cute shortened name for "Category Theory", but code that makes heavy use of these constructs is not understandable to other programmers. Other than using Monads as a design pattern for things like Options (which can be "Some" or "None"), Futures or Promises (which is used for asynchronous programming), and a few other things, please do not make heavy use of category theory constructs in real programming projects that will have other developers working on them. It is a rabbit hole that may be fun but is not super practical. Sure, write pure functions without side effects, but do not use the words "Bimonad", "Invariant Monoidal", and "Semigroup" in your code. The most common, practical application/use of functional programming is basic things like closures, .map, .filter, maybe chaining maps with like a .flatmap or whatever your programming language uses instead of chain or flatmap, and SQL that uses keywords like WHERE which can be represented in code by using a call to .filter. Like the place where these constructs are used most is in data processing like with SQL, ETL (Extract Transform, Load) jobs, Java's MapReduce on Hadoop, Scala's Apache Spark, and other data processing type things. Haskell is not a popular programming language in real world projects for a number of reasons and one of them is the heavy and sometimes impractical use of Category Theory.

At a previous job of mine we actually had an entirely pure Scala ecosystem using cats which instead uses typeclasses, referential transparency, and other FP concepts as the foundations for how to code. So a lot of flexibility to the language.

Thanks! It's used heavily here

I did work in Scala for a few years. We employed Cats[1], and even a bit of Matryoshka[2] though most of the work I do today is in Python.

Nowadays I think about computational requirements in terms of relations among behavioral dependencies. Like, "I want to perform operation O on input A and return a B. To do this, I'll need a way to a -> b and a way to b -> b -> b." I often pass these behavioral dependencies in as arguments and it tends to make the inner core of my programs pretty abstract and built up as layers of specificity.

Zooming out nearly all the way, it makes me feel tethered in a qualitatively unique way to certain deep truths of the universe. In a Platonic sense, invoking certain ideas like a monad make me feel like I'm approaching the divine or at least one instantiation of a timeless universal that operates outside of material existence.

I'd imagine some mathematicians might see the universe in a similar way - one where immortal relations between ontological forms exist beyond time and space and at the same time can be threaded through the material world by intellectual observation and when those two meet a beautiful collision occurs.

1. https://typelevel.org/cats/

2. https://github.com/precog/matryoshka

Our second type class example attempted to illustrate one last perk: type safety at compile time. It did so with a simplified example of the cats core library for type safety equality comparison between objects. If you're not familiar with cats, go ahead and give it go.

It's got type annotations and mypy has a discussion about it here as well: https://github.com/python/mypy/issues/1282

There is already an AOT compiler for Python: Nuitka[0]. But I don't think it's much faster.

And then there is mypyc[1] which uses mypy's static type annotations but is only slightly faster.

And various other compilers like Numba and Cython that work with specialized dialects of Python to achieve better results, but then it's not quite Python anymore.

[0] https://nuitka.net/

[1] https://github.com/python/mypy/tree/master/mypyc

In Python there is MyPy that can help with this. https://www.mypy-lang.org/

It's funny you should say this.

Reading this article prompted me to future-proof a program I maintain for fun that deals with time; it had one use of utcnow, which I fixed.

And then I tripped over a runtime type problem in an unrelated area of the code, despite the code being green under "mypy --strict". (and "100% coverage" from tests, except this particular exception only occured in a "# pragma: no-cover" codepath so it wasn't actually covered)

It turns out that because of some core decisions about how datetime objects work, `datetime.date.today() < datetime.datetime.now()` type-checks but gives a TypeError at runtime. Oops. (cause discussed at length in https://github.com/python/mypy/issues/9015 but without action for 3 years)

One solution is apparently to use `datetype` for type annotations (while continuing to use `datetime` objects at runtime): https://github.com/glyph/DateType

PEP 695 is great. I've been using mypy every day at work in last couple years or so with very strict parameters (no any type etc) and I have experience writing real life programs with Rust, Agda, and some Haskell before, so I'm familiar with strict type systems. I'm sure many will disagree with me but these are my very honest opinions as a professional who uses Python types every day:

* Some types are better than no types. I love Python types, and I consider them required. Even if they're not type-checked they're better than no types. If they're type-checked it's even better. If things are typed properly (no any etc) and type-checked that's even better. And so on...

* Having said this, Python's type system as checked by mypy feels like a toy type system. It's very easy to fool it, and you need to be careful so that type-checking actually fails badly formed programs.

* The biggest issue I face are exceptions. Community discussed this many times [1] [2] and the overall consensus is to not check exceptions. I personally disagree as if you have a Python program that's meticulously typed and type-checked exceptions still cause bad states and since Python code uses exceptions liberally, it's pretty easy to accidentally go to a bad state. E.g. in the linked github issue JukkaL (developer) claims checking things like "KeyError" will create too many false positives, I strongly disagree. If a function can realistically raise a "KeyError" the program should be properly written to accept this at some level otherwise something that returns type T but 0.01% of the time raises "KeyError" should actually be typed "Raises[T, KeyError]".

* PEP 695 will help because typing things particularly is very helpful. Often you want to pass bunch of Ts around but since this is impractical some devs resort to passing "dict[str, Any]"s around and thus things type-check but you still get "KeyError" left and right. It's better to have "SomeStructure[T]" types with "T" as your custom data type (whether dataclass, or pydantic, or traditional class) so that type system has more opportunities to reject bad programs.

* Overall, I'm personally very optimistic about the future of types in Python!

[1] https://github.com/python/mypy/issues/1773

# is fixed: https://github.com/python/mypy/issues/12987.

You probably already know but you can add type hints and then check for consistency with https://github.com/python/mypy in python.

Modern Python with things like https://learnpython.com/blog/python-match-case-statement/ + mypy + Ruff for linting https://github.com/astral-sh/ruff can get pretty good results.

I found typed dataclasses (https://docs.python.org/3/library/dataclasses.html) in python using mypy to give me really high confidence when building data representations.