memoization.py
· 492 B · Python
原始檔案
# example of memoization in pythong for fibonacci
# Memoization: Let’s Be Efficient, Shall We?
# Ever ask the same question over and over? Annoying, right? That’s what your computer thinks too. Memoization fixes this by storing results so you don’t have to repeat expensive calculations.
def fib(n, memo={}):
if n in memo:
return memo[n]
if n < 2:
return n
memo[n] = fib(n - 1, memo) + fib(n - 2, memo)
return memo[n]
fib(100)
# 354224848179261915075
| 1 | # example of memoization in pythong for fibonacci |
| 2 | |
| 3 | # Memoization: Let’s Be Efficient, Shall We? |
| 4 | # Ever ask the same question over and over? Annoying, right? That’s what your computer thinks too. Memoization fixes this by storing results so you don’t have to repeat expensive calculations. |
| 5 | def fib(n, memo={}): |
| 6 | if n in memo: |
| 7 | return memo[n] |
| 8 | if n < 2: |
| 9 | return n |
| 10 | memo[n] = fib(n - 1, memo) + fib(n - 2, memo) |
| 11 | return memo[n] |
| 12 | |
| 13 | fib(100) |
| 14 | |
| 15 | # 354224848179261915075 |
| 16 |