Functional programming
Pure functions
Given same argument to the function, it should always return same output
Pure functions
Should not mutate anything that can be seen outside function
some_global_list = []
def not_so_pure(mutable_object):
mutable_object.append(1)
def also_not_so_pure(mutable_object):
mutable_object.append(2)
Pure functions
also_not_so_pure(some_global_list)
not_so_pure(some_global_list)not_so_pure(some_global_list)
also_not_so_pure(some_global_list)
Function invocations are not connected in any way, but order matters
mutated_list = much_purer(some_global_list)
mutated_list = also_much_purer(mutated_list)
mutated_list = also_much_purer(much_purer(some_global_list))Explicit connections between function calls
some_global_mess = []
def dirty_one():
some_global_mess.append("lol")
def dirty_two():
some_global_mess.append("kek")
dirty_one()
dirty_two()
print(some_global_mess)
Even more global variables
print()
random.random()
input()
def sum(a, b):
print(f"I added {b} to {a}!")
return a + b
Dirty functions
def sum(log: List[str], a: int, b: int) -> Tuple[int, List[str]]:
return a + b, [*log, f"I added {b} to {a}!"]We can lift side effects as far as possible
Pure functions
- Predictable
- Readable
- Cacheable
Functions as first class objects
Functions are usual objects that can be saved in variable or passed as function argument
Higher order functions
Functions that take as argument or return other function
- map
- reduce
- filter
- sorted
deck
By Aleksandr Slepchenkov
