guides
Dynamic Programming Patterns
Compile classic DP solutions for Fibonacci, knapsack, LCS, and pathfinding.
Published May 30, 2026
Fibonacci (Bottom-Up)
def fib_dp(n: int) -> int:
if n < 2:
return n
a, b = 0, 1
for _ in range(2, n + 1):
a, b = b, a + b
return b
0/1 Knapsack
def knapsack(weights: list[int], values: list[int], capacity: int) -> int:
n = len(weights)
dp = [[0] * (capacity + 1) for _ in range(n + 1)]
for i in range(1, n + 1):
for w in range(capacity + 1):
if weights[i - 1] <= w:
dp[i][w] = max(dp[i - 1][w], dp[i - 1][w - weights[i - 1]] + values[i - 1])
else:
dp[i][w] = dp[i - 1][w]
return dp[n][capacity]
Longest Common Subsequence
def lcs(a: str, b: str) -> int:
m, n = len(a), len(b)
dp = [[0] * (n + 1) for _ in range(m + 1)]
for i in range(1, m + 1):
for j in range(1, n + 1):
if a[i - 1] == b[j - 1]:
dp[i][j] = dp[i - 1][j - 1] + 1
else:
dp[i][j] = max(dp[i - 1][j], dp[i][j - 1])
return dp[m][n]