Functions & basics
Reusable building blocks — parameters, returns, scope, and clear function design.
Cache expensive function with lru_cache in Python
Use functools.lru_cache to memoize an expensive recursive function and show the dramatic speedup on repeated calls.
from functools import lru_cache
import time
@lru_cache(maxsize=128)
def expensive_operation(n):
"""Simulate an expensive Fibonacci-like calculation."""
if n < 2:
return n
return expensive_operation(n - 1) + expensive_operation(n - 2)
if __name__ == "__main__":
# First call (uncached) - take…
How to Implement Memoized Fibonacci in Python with functools.cache
Use functools.cache to memoize a recursive Fibonacci function, avoiding repeated computation and dramatically speeding up the calculation.
from functools import cache
@cache
def fibonacci(n: int) -> int:
"""Return the n-th Fibonacci number (0-indexed)."""
if n < 2:
return n
return fibonacci(n - 1) + fibonacci(n - 2)
if __name__ == "__main__":
for i in range(10):
print(f"fibonacci({i}) = {fibonacci(i)}")
print(f"Cache…
How to Implement a Trampoline for Tail Recursion in Python
This code implements a trampoline decorator that converts tail-recursive functions into iterative loops, allowing deep recursion without hitting Python's recursion limit.
def trampoline(fn):
"""Convert a tail-recursive function into an iterative loop."""
def wrapper(*args, **kwargs):
result = fn(*args, **kwargs)
while callable(result):
result = result()
return result
return wrapper
@trampoline
def factorial(n, acc=1):
"""Tail-recursi…
Mutual Recursion for Even/Odd Check in Python
Implements even and odd checks using two functions that call each other recursively, demonstrating base cases and alternating calls.
def is_even(n):
if n == 0:
return True
return is_odd(n - 1)
def is_odd(n):
if n == 0:
return False
return is_even(n - 1)
if __name__ == "__main__":
for num in range(0, 11):
print(f"{num}: even={is_even(num)}, odd={is_odd(num)}")
Write a Recursive Factorial Function in Python
Define a recursive factorial function that handles edge cases and returns the product of all positive integers up to n.
def factorial(n):
"""Return the factorial of n using recursion."""
if n < 0:
raise ValueError("Factorial is not defined for negative numbers")
if n == 0 or n == 1:
return 1
return n * factorial(n - 1)
if __name__ == "__main__":
print(factorial(5))
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