Functional Programming Introduction
Functional Programming (FP) focuses on using functions and immutability. Python, although not purely functional, supports key FP principles, allowing developers to mix paradigms for clean and efficient code.
First-Class Functions
In Python, functions are first-class citizens. This means they can be passed around as arguments, returned from other functions, and assigned to variables, allowing for higher-order functions.
Pure Functions
Pure functions are the heart of FP. They have no side effects and return the same output for the same inputs. Python's lambda functions often exemplify this, though not exclusively.
Immutability in Python
Immutability is less enforced in Python than in other FP languages. However, Python's 'tuple' data structure and the 'frozenset' type are immutable, promoting FP practices.
List Comprehensions and FP
List comprehensions are a functional way to create lists in Python. They're concise, readable, and often faster than traditional loops, resembling the map and filter functions in FP.
Recursion Over Iteration
FP often favors recursion over loops. Python supports recursion, but be mindful of the recursion limit and the lack of tail-call optimization, which can lead to stack overflow errors.
Functional Libraries
Python's 'functools' module extends the language's FP abilities. Libraries like 'toolz' and 'fn.py' can further empower functional programming, offering utilities for function composition, currying, and more sophisticated functional constructs.
What is Python's stance on FP?
Python is purely functional.
Python does not support FP.
Supports FP principles, not purely functional.
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