https://en.wikibooks.org/wiki/Haskell/Category_theory
This article is also nice:
https://www.haskellforall.com/2012/08/the-category-design-pa...
It explins how Haskell's monad laws follow directly from how categories work.
Category Theory has birthed some useful abstraction, but you don't really need any of CT to learn and use the abstractions.
The basics of Abstract Algebra on the otherhand are absolutely worth the bit of time it takes to learn them.
Groups, semi-groups, rings, fields, monoids - distribution, identity, zeros, associstivity, communitavity are pretty trivia to learn - most people already know the underlying concepts and they pop up all the time in programing.
Monoids are incredibly useful - most people already know them, and intuitively use them, but it's helpful naming and understanding the pattern.
Category Therory just doesn't have the same return on investment for software development.
- PUSH(n) where n is a floating-point number
- POP
- CLEAR
- ADD, SUB, MUL, DIV
- ID
These can be interpreted as operations on a stack of floating-point numbers in the obvious way, PUSH(1.2) * [3.14] == [1.2, 3.14], POP * [1, 2, 3] == [2, 3], ADD * [1, 2, 5] == [3, 5], CLEAR * [1, 2, 3] == [], ID * [1, 2, 3] == [1, 2, 3], etc. However, not all of the compositions of stack operations are legal. For example, ADD * PUSH(1) * PUSH(2) is fine and equivalent to PUSH(3), but ADD * PUSH(1) * CLEAR is illegal.
Ok, so our stack operations don't form a monoid. But they obviously can still be composed, sometimes, so what do we have if not a monoid? They form a category! There is one object for each natural number, representing the height of the stack. So there are arrows like PUSH(3.14) : Height_{n} -> Height_{n+1} for all n, and POP : Height_{n} -> Height_{n-1} whenever n >= 1, and ADD : Height_{n} -> Height_{n-2} whenever n >= 2.
Another common example is matrices. Square matrices form a monoid, but what about arbitrary rectangular matrices? They don't form a monoid, but they do form a category where the objects are natural numbers, and the arrows N -> M are just the MxN matrices. You can't multiply any two matrices, but if you have a P -> Q matrix (QxP) and a Q -> R (RxQ) matrix then you can multiply them to get a P -> R matrix (RxP).
Category theory envelopes relations as well, as well as arguably anything else that can be formalized.