Go: package main

import (
	"bufio"
	"fmt"
	"math"
	"os"
	"strconv"
)

type Matrix struct {
	r int // num of row
	c int // num of column
}

type Range struct {
	start int // index, inclusive
	end   int // index, inclusive
}

func (r Range) length() int {
	return r.end - r.start + 1
}

func calcMultiplication(x, y Matrix) (Matrix, int) {
	if x.c != y.r {
		panic("cannnot calculate")
	}
	return Matrix{x.r, y.c}, x.r * y.c * x.c
}

func calcMinMatrixChainMultiplication(matrices []Matrix, r Range, memo map[Range]int) (Matrix, int) {
	if v, ok := memo[r]; ok {
		return Matrix{matrices[r.start].r, matrices[r.end].c}, v
	}
	if r.length() == 0 {
		panic("must not be empty")
	} else if r.length() == 1 {
		return matrices[r.start], 0
	}

	var minCount int = math.MaxInt32

	for i := 0; i < r.length()-1; i++ {
		formerRange := Range{r.start, r.start + i}
		latterRange := Range{r.start + i + 1, r.end}
		matF, countF := calcMinMatrixChainMultiplication(matrices, formerRange, memo)
		matL, countL := calcMinMatrixChainMultiplication(matrices, latterRange, memo)
		_, countFL := calcMultiplication(matF, matL)
		count := countF + countL + countFL
		if count < minCount {
			minCount = count
		}
	}
	memo[r] = minCount
	return Matrix{matrices[r.start].r, matrices[r.end].c}, minCount
}

func main() {
	sc := bufio.NewScanner(os.Stdin)
	sc.Split(bufio.ScanWords)
	n, _ := nextInt(sc)
	matrices := make([]Matrix, n)
	for i := 0; i < n; i++ {
		r, _ := nextInt(sc)
		c, _ := nextInt(sc)
		matrices[i] = Matrix{r, c}
	}
	memo := make(map[Range]int)
	_, resultCount := calcMinMatrixChainMultiplication(matrices, Range{0, len(matrices) - 1}, memo)
	fmt.Println(resultCount)
}

func nextInt(sc *bufio.Scanner) (int, error) {
	sc.Scan()
	return strconv.Atoi(sc.Text())
}

Python: #!/usr/bin/env python3
# -*- coding: utf-8 -*-

import sys
import re
import math
import collections
import itertools
import functools
import logging

logging.basicConfig(level=logging.DEBUG, format="DBG: %(message)s")

def dbg(msg, *args, **kwargs):
    logging.debug(msg, *args, **kwargs)

Mat = collections.namedtuple("Mat", "r c")

def mat_mul(ms):
    return Mat(ms[0].r, ms[-1].c)

def cost(m1, m2):
    return m1.r * m1.c * m2.c

def solve(n, ms):
    if n == 1: return 0

    dp = {}
    for i in range(n):
        dp[(i,i)] = 0

    for l in range(2, n+1):
        for i in range(n-l+1):
            cost_min = math.inf
            for j in range(l-1):
                dbg("l, i, j: %d %d %d", l, i, j)
                m_lhs = mat_mul(ms[i:i+j+1])
                m_rhs = mat_mul(ms[i+j+1:i+l])
                dbg("m_lhs, m_rhs: %r %r", m_lhs, m_rhs)
                cost_lhs = dp[(i,i+j)]
                cost_rhs = dp[(i+j+1,i+l-1)]
                dbg("cost_lhs, cost_rhs: %d %d", cost_lhs, cost_rhs)
                cost_mul = cost(m_lhs, m_rhs)
                dbg("cost_mul: %d", cost_mul)
                cost_now = cost_mul + cost_lhs + cost_rhs
                dbg("cost_now: %d", cost_now)
                if cost_min > cost_now:
                    cost_min = cost_now
            dp[(i,i+l-1)] = cost_min

    dbg(dp)
    return dp[(0,n-1)]

def main():
    n = int(input())

    ms = []
    for _ in range(n):
        r,c = map(int, input().split())
        ms.append(Mat(r,c))

    print(solve(n, ms))

if __name__ == "__main__": main()

Python: # -*- coding: utf-8 -*-
import functools
INF = 10**9
n = int(input())
p = list(map(int, input().split()))
for i in range(n - 1):
    p.append(int(input().split()[1]))


@functools.lru_cache(maxsize=None)
def matrix_chain_multiplication(i, j):
    if i == j:
        return 0

    tmp = INF
    for k in range(i, j):
        tmp = min(
            tmp,
            matrix_chain_multiplication(i, k) +
            matrix_chain_multiplication(k + 1, j) + p[i - 1] * p[k] * p[j])
    return tmp


print(matrix_chain_multiplication(0, n - 1))

Python: import sys

sys.setrecursionlimit(10 ** 6)
int1 = lambda x: int(x) - 1
p2D = lambda x: print(*x, sep="\n")

def main():
    def get_cost(l,r):
        if r-l==1:return 0
        if r-l==2:return rc[l][0]*rc[r-1][0]*rc[r-1][1]
        if cost[l][r]!=-1:
            return cost[l][r]
        res=cost[l][r]=min(get_cost(l,m)+get_cost(m,r)
                           +rc[l][0]*rc[m][0]*rc[r-1][1] for m in range(l+1,r))
        return res

    n=int(input())
    rc=[list(map(int,input().split())) for _ in range(n)]
    cost=[[-1]*(n+1) for _ in range(n)]
    print(get_cost(0,n))

main()

Python: n = int(input())
p = [item for sublist in [[int(input().split()[1])] if i != 0 else list(map(int, input().split())) for i in range(n)] for item in sublist]

def memolize(f):
    cache = {}

    def helper(x, y):
        if (x, y) not in cache:
            cache[(x, y)] = f(x, y)
        return cache[(x, y)]
    return helper

@memolize
def calcMatrixOrder(i, j):
    if i == j :
        return 0
    return min([calcMatrixOrder(i, k) + calcMatrixOrder(k + 1, j) + p[i]*p[k+1]*p[j + 1] for k in range(i, j)])

print(calcMatrixOrder(0, n - 1))

Python: global memo

def find_memo(m,l):#memoのm行l列の値を返す.data
                            #data[l]から続くm+1個の要素からなる部分リスト
    if(memo[m][l]!=0):
        return memo[m][l]
    
    if(m<2):
        return memo[m][l]
    

    tmp_min=999999999
    for i in range(1,m):
        left=find_memo(i,l)
        right=find_memo(m-i,l+i)
        middle=memo[0][l]*memo[0][l+i]*memo[0][l+m]
        if(left + right + middle< tmp_min):
            tmp_min = left + right + middle
    memo[m][l]=tmp_min
    return tmp_min




tmp_min=9999999999
n=int(input())
memo=[[0]*(n+1-i) for i in range(n+1)]#memo[i][j]はdata[j]から続くi+1個の要素からなる部分リストの最小計算コストを表す

memo[0][0],memo[0][1]=map(int,input().split())
for i in range(2,n+1):
    dummy,memo[0][i]= map(int,input().split())

for i in range(n-1):
    memo[2][i] = memo[0][i]*memo[0][i+1]*memo[0][i+2]

print(find_memo(n,0))

Python: def matrixChainMultiplication(n):
    # for i in range(1, n+1):
    #     m[i][i] = 0
    for l in range(2, n+1):
        for i in range(1, n-l+1+1):
            j = i + l - 1
            m[i][j] = 999999999
            for k in range(i, j):
                m[i][j] = min(m[i][j], m[i][k] + m[k+1][j] + p[i-1]*p[k]*p[j])
    return m[1][n]

n = int(input())
squareM = [input().split(" ") for _ in range(n)]
p = [int(squareM[i][0]) for i in range(n)]
p.append(int(squareM[n-1][1]))
m = [[0]*(n+1) for _ in range(n+1)]
print(matrixChainMultiplication(n))

Python: n = int(input())
m = [[0 for j in range(n + 1)] for i in range(n + 1)]
z = [0] * (n + 1)
for i in range(1, n + 1):
    z[i - 1], z[i] = map(int, input().split())
j = 0
for l in range(2, n + 1):
    for i in range(1, n - l + 2):
        j = i + l - 1
        m[i][j] = int(1e8)
        for k in range(i, j):
            m[i][j] = min(m[i][j], m[i][k] + m[k + 1][j] + z[i - 1] * z[k] * z[j])
print(m[1][n])

Python: def matrixChainMultiplication(p):
    # p = [p_0, p_1, ..., p_n]
    n = len(p) - 1
    # n+1 x n+1 zero matrix?????????(0,...,n)
    # cost(i,j): (M_i...M_j)???????°??????????
    cost = [[0 for _ in range(n + 1)] for _ in range(n + 1)]
    for numOfMatrices in range(2, n + 1):
        for i in range(1, n - numOfMatrices + 2):
            j = i + numOfMatrices - 1
            cost[i][j] = float('inf')
            for k in range(i, j):
                cost[i][j] = min(cost[i][j], cost[i][k] + cost[k + 1][j] + p[i - 1] * p[k] * p[j])
    print(cost[1][n])

p = []
n = int(input())

for _ in range(n):
    listed_input = input().split()
    p.append(int(listed_input[0]))
p.append(int(listed_input[1]))

matrixChainMultiplication(p)

Python: n = int(input())
p = [list(map(int, input().split())) for i in range(n)]

m = [[0] * n for i in range(n)]

for l in range(2, n + 1):
  for i in range(n - l + 1):
    j = i + l - 1
    m[i][j] = float('inf')
    for k in range(i, j):
      cost = m[i][k] + m[k + 1][j] + p[i][0] * p[k][1] * p[j][1]
      m[i][j] = min(m[i][j], cost)

print(m[0][n - 1])