Problem:


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Single Source Shortest Path II

  For a given weighted graph $G = (V, E)$, find the shortest path from a source to each vertex. For each vertex $u$, print the total weight of edges on the shortest path from vertex $0$ to $u$.

Input

  In the first line, an integer $n$ denoting the number of vertices in $G$ is given. In the following $n$ lines, adjacency lists for each vertex $u$ are respectively given in the following format:

$u$ $k$ $v_1$ $c_1$ $v_2$ $c_2$ ... $v_k$ $c_k$

  Vertices in $G$ are named with IDs $0, 1, ..., n-1$. $u$ is ID of the target vertex and $k$ denotes its degree. $v_i (i = 1, 2, ... k)$ denote IDs of vertices adjacent to $u$ and $c_i$ denotes the weight of a directed edge connecting $u$ and $v_i$ (from $u$ to $v_i$).

Output

  For each vertex, print its ID and the distance separated by a space character in a line respectively. Print in order of vertex IDs.

Constraints

$1 \leq n \leq 10,000$

$0 \leq c_i \leq 100,000$

$|E| < 500,000$

All vertices are reachable from vertex $0$

Sample Input 1

5
0 3 2 3 3 1 1 2
1 2 0 2 3 4
2 3 0 3 3 1 4 1
3 4 2 1 0 1 1 4 4 3
4 2 2 1 3 3

Sample Output 1

0 0
1 2
2 2
3 1
4 3

Reference

Introduction to Algorithms, Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, and Clifford Stein. The MIT Press.



Sample input:
5
0 3 2 3 3 1 1 2
1 2 0 2 3 4
2 3 0 3 3 1 4 1
3 4 2 1 0 1 1 4 4 3
4 2 2 1 3 3


Sample output:
0 0
1 2
2 2
3 1
4 3

Submission status: Accepted

Solution code:
from sys import stdin
from collections import deque
import heapq

def read_graph(n):
    A = [ [] for _ in range(n) ]
    for _ in range(n):
        line = deque(stdin.readline().strip().split())
        u = line.popleft()
        line.popleft()
        for l, k in enumerate(line):
            if l % 2 == 0:
                v = k
            else:
                A[int(u)].append((int(v), int(k)))
    return A

def dijkstra(n, A, s):
    color = [ 'WHITE' for i in range(n) ]
    d = [ float('inf') for i in range(n) ]
    d[s] = 0
    pq = []

    heapq.heappush(pq, (s, 0))

    while pq:
        costu, u = heapq.heappop(pq)
        color[u] = 'BLACK'

        if d[u] < costu:
            continue

        for v, costv in A[u]:
            if color[v] != 'BLACK':
                if d[u] + costv < d[v]:
                    d[v] = d[u] + costv
                    color[v] = 'GRAY'
                    heapq.heappush(pq, (d[v], v))
    return d

n = int(input())
A = read_graph(n)
for i, k in enumerate(dijkstra(n, A, 0)):
    print(i, k)

Submission status: Accepted

Solution code:
import heapq

INFTY = 1<<20

N = int(input())
M = [[] for _ in range(N)]
for i in range(N):
    u, k, *adjacents = map(int, input().split())
    for j in range(k):
        edge = adjacents[2*j]
        weight = adjacents[2*j+1]
        M[i].append((weight, edge))

mst = [False for _ in range(N)]
d = [INFTY for _ in range(N)]
d[0] = 0
pq = []
heapq.heappush(pq, (0, 0))

while len(pq) != 0:
    u = heapq.heappop(pq)
    u_edge = u[1]
    u_cost = u[0]

    mst[u_edge] = True

    if d[u_edge] < u_cost:
        continue

    for v in M[u_edge]:
        v_edge = v[1]
        v_cost = v[0]
        if mst[v_edge] == True:
            continue
        if d[u_edge]+v_cost < d[v_edge]:
            d[v_edge] = d[u_edge]+v_cost
            heapq.heappush(pq, (d[v_edge], v_edge))

for i in range(N):
    print("{} {}".format(i, d[i]))

Submission status: Accepted

Solution code:
import queue

INFTY = 1 << 21
WHITE = 0
GRAY = 1
BLACK = 2

def dijkstra(n, adj):
    pq = queue.PriorityQueue()
    d = [INFTY] * n
    color = [WHITE] * n

    d[0] = 0
    pq.put((0, 0))
    color[0] == GRAY

    while not pq.empty():
        f = pq.get()
        u = f[1]
        color[u] = BLACK

        if d[u] < f[0]:
            continue

        for j in range(len(adj[u])):
            v = adj[u][j][0]
            if color[v] == BLACK:
                continue
            if d[v] > d[u] + adj[u][j][1]:
                d[v] = d[u] + adj[u][j][1]
                pq.put((d[v], v))
                color[v] = GRAY

    for i in range(n):
        out = d[i]
        if out == INFTY:
            out = -1
        print('{0} {1}'.format(i, out))


n = int(input())
adj = [[] for i in range(n)]
for i in range(n):
    line = [int(v) for v in input().split()]
    u = line[0]
    k = line[1]
    for j in range(k):
        v = line[2*j + 2]
        c = line[2*j + 3]
        adj[u].append((v, c))

dijkstra(n, adj)

Submission status: Accepted

Solution code:
# Graph II - Single Source Shortest Path II
def dijkstra(length, adj_list):
    INFTY = float('inf')
    d = [INFTY for _ in range(length)]
    d[0] = 0
    Q = [i for i in range(length)]
    while Q:
        idx = INFTY
        minv = INFTY
        for q in Q:
            if d[q] < minv:
                idx, minv = q, d[q]
        u = Q.pop(Q.index(idx))
        for v in adj_list[u]:
            if d[v[0]] > d[u] + v[1]:
                d[v[0]] = d[u] + v[1]
    return d

n = int(input())
adj_list = [set() for _ in range(n)]
for _ in range(n):
    ss = list(map(int, input().split()))
    u, k = ss[0], ss[1]
    for i in range(k):
        vi,ci = ss[2*i+2], ss[2*i+3]
        adj_list[u].add((vi,ci))
d = dijkstra(n, adj_list)
for i,v in enumerate(d): print(i,v)

Submission status: Runtime Error

Solution code:
#coding:utf-8
import numpy as np

n = int(input())
inf = 1000000000000000

def minHeapify(Q,i):
    H = len(Q)
    l = 2*i
    r = 2*i + 1
    if l < H and Q[l][1] < Q[i][1]:
        smallest = l
    else:
        smallest = i
    if r < H and Q[r][1] < Q[smallest][1]:
        smallest = r

    if smallest != i:
        Q[i], Q[smallest] = Q[smallest], Q[i]
        minHeapify(Q,smallest)

def buildMinHeap(Q):
    H = len(Q)
    for i in range(H // 2, -1, -1):
        minHeapify(Q,i)

def Insert(Q,key):
    v = key[0]
    Q.append([v,inf])
    lens = len(Q)
    heapIncreaseKey(Q,lens-1,key)

def heapIncreaseKey(Q,i,key):
    Q[i][1] = key[1]
    while i > 0 and Q[i // 2][1] > Q[i][1]:
        Q[i], Q[i // 2] = Q[i // 2], Q[i]
        i //= 2

def heapExtractMin(Q):
    H = len(Q)
    minv = Q[0][0]
    Q[0] = Q[H-1]
    Q.pop()
    minHeapify(Q,0)
    return minv




def dijkstra(s):
    color = ["white" for i in range(n)]
    d = [inf for i in range(n)]
    d[s] = 0
    Q = [[s,0]]
    while Q != []:
        u = heapExtractMin(Q)
        color[u] = "black"
        for vw in mtrx[u]:
            [v,w] = vw
            if color[v] != "black":
                if d[u] + w < d[v]:
                    d[v] = d[u] + w
                    color[v] = "gray"
                    Insert(Q,[v,d[v]])
    return d



mtrx = [[] for i in range(n)]
for i in range(n):
    col = list(map(int,input().split()))
    u,k = col[0], col[1]
    for j in range(k):
        [v,w] = col[2*j+2: 2*j+4]
        mtrx[u].append([v,w])



d = dijkstra(0)
for i,j in enumerate(d):
    print(i,j)

Submission status: Runtime Error

Solution code:
# -*- coding: utf-8 -*-
from collections import defaultdict
from heapq import heappop, heappush


def dijkstra(edges, start, *, adj_matrix=False, default_value=float('inf')):
    '''
    Returns best costs to each node from 'start' node in the given graph.
    (Single Source Shortest Path - SSSP)

    If edges is given as an adjacency list including costs and destination nodes on possible edges, adj_matrix should be False(default), and it is generally when this functions works much faster.

    Note that costs in edges should follow the rules below
    1. The cost from a node itself should be 0,
    2. If there is no edge between nodes, the cost between them should be default_value
    3. The costs can't be negative

    # sample input when given as adjacency list (adj_matrix=False)
    edges = [[(1, 2), (2, 5), (3, 4)],         # node 0
             [(0, 2), (3, 3), (4, 6)],         # node 1
             [(0, 5), (3, 2), (5, 6)],         # node 2
             [(0, 4), (1, 3), (2, 2), (4, 2)], # node 3
             [(1, 6), (3, 2), (5, 4)],         # node 4
             [(2, 6), (4, 4)]]                 # node 5

    # sample input when given as adjacency matrix (adj_matrix=True)
    edges = [[0, 2, 5, 4, inf, inf],           # node 0
             [2, 0, inf, 3, 6, inf],           # node 1
             [5, inf, 0, 2, inf, 6],           # node 2
             [4, 3, 2, 0, 2, inf],             # node 3
             [inf, 6, inf, 2, 0, 4],           # node 4
             [inf, inf, 6, inf, 4, 0]]         # node 5
    '''

    n = len(edges)

    inf = float('inf')
    # costs = [inf] * n
    costs = defaultdict(lambda: inf)
    costs[start] = 0
    pq, rem = [(0, start)], n - 1

    while pq and rem:
        tmp_cost, tmp_node = heappop(pq)
        if costs[tmp_node] < tmp_cost:
            continue
        rem -= 1

        nxt_edges = ((node, cost) for node, cost in enumerate(edges[tmp_node]) if cost != default_value) if adj_matrix else\
                    edges[tmp_node]

        for nxt_node, nxt_cost in nxt_edges:
            new_cost = tmp_cost + nxt_cost
            if costs[nxt_node] > new_cost:
                costs[nxt_node] = new_cost
                heappush(pq, (new_cost, nxt_node))

    return costs


def dijkstra_route(edges,
                   start,
                   goal,
                   *,
                   adj_matrix=False,
                   default_value=float('inf'),
                   verbose=False):
    '''
    Trys to find the best route to the 'goal' from the 'start'
    '''

    n = len(edges)

    inf = float('inf')
    # costs = [inf] * n
    costs = defaultdict(lambda: inf)
    costs[start] = 0
    pq, rem = [(0, start)], n - 1
    # prevs = [-1 for _ in [None] * n]
    prevs = defaultdict(lambda: -1)

    while pq and rem:
        tmp_cost, tmp_node = heappop(pq)
        if costs[tmp_node] < tmp_cost:
            continue
        rem -= 1

        nxt_edges = ((node, cost) for node, cost in enumerate(edges[tmp_node]) if cost != default_value) if adj_matrix else\
                    edges[tmp_node]

        for nxt_node, nxt_cost in nxt_edges:
            new_cost = tmp_cost + nxt_cost
            if costs[nxt_node] > new_cost:
                costs[nxt_node] = new_cost
                heappush(pq, (new_cost, nxt_node))
                prevs[nxt_node] = tmp_node

    min_route = []
    prev = goal
    cnt = 0
    while prev != start:
        min_route.append(prev)
        prev = prevs[prev]

        cnt += 1
        if prev == -1 or cnt > n:
            raise NoRouteError(
                'There is no possible route in this graph \nedges: {} \nstart: {} \ngoal: {}'.
                format(edges, start, goal))

    else:
        min_route.append(prev)
    min_route = min_route[::-1]
    min_cost = costs[goal]

    if verbose:
        print('---route---')
        for node in min_route[:-1]:
            print('{} -> '.format(node), end='')
        else:
            print(min_route[-1])

        print('---distance---')
        print(min_cost)

    return costs, min_route


class NoRouteError(Exception):
    pass


if __name__ == '__main__':
    '''
    an example of using this function
    AIZU ONLINE JUDGE - ALDS_1_12_C
    '''

    n = int(input())
    edges = [[] for i in range(n)]
    for i in range(n):
        i, k, *kedges = map(int, input().split())
        for edge in zip(kedges[::2], kedges[1::2]):
            edges[i].append(edge)

    # for i, cost in enumerate(dijkstra(edges, 0)):
    #     print(i, cost)
    for i, cost in dijkstra(edges, 0):
        print(i, cost)

Submission status: Runtime Error

Solution code:
import io, sys, itertools
f = sys.stdin
 
 
def take2(iterable):
    i = iter(iterable)
    while True:
        yield next(i), next(i)
 
 
n = int(f.readline())
adj =[[(v, c) for v, c in take2(map(int, f.readline().split()[2:]))] for _ in range(n)]
d = [100000 * 100 + 1] * n
 
d[0] = 0
def search(parent, children):
    global d
    for v, c in children:
        if d[v] > d[parent] + c:
            d[v] = d[parent] + c
            search(v, adj[v])
     
search(0, adj[0])
     
for i in range(n):
    print(i, d[i])

Submission status: Runtime Error

Solution code:
MAX = 100
INF = 1000000
WHITE = 0
GRAY = 1
BLACK = 2
n = int(raw_input())

M = [[INF for i in range(n)]for j in range(n)]
d = [INF for i in range(MAX)]
Color = [WHITE for i in range(MAX)]
for i in range(n):
    tmp = map(int,raw_input().split())
    u = tmp[0]
    k = tmp[1]
    for j in range(1, k + 1):
        v = tmp[j * 2]
        c = tmp[j * 2 + 1]
        M[u][v] = c

#def dijkstra():
d[0] = 0
Color[0] = GRAY
    
while True:
    minv = INF
    u = -1
    for i in range(n):
        if minv > d[i] and Color[i] != BLACK:
            u = i
            minv = d[i]
    if u == -1:
        break
    Color[u] = BLACK
    for v in range(n):
        if Color[v] != BLACK and M[u][v] != INF:
            if d[v] > d[u] + M[u][v]:
                d[v] = d[u] + M[u][v]
                Color[v] = GRAY
for i in range(n):
    print i,
    if d[i] == INF:
        print -1
    else:
        print d[i]

Submission status: Runtime Error

Solution code:
V=int(input())
 
G=[[] for i in range(V)]
d=[1001001001 for i in range(V)]
used=[False for i in range(V)]
 
import heapq
 
def dijkstra(s):
    q=[]
    d[s]=0
    heapq.heappush(q,(0, s))
     
    while(len(q)):
         
        p=heapq.heappop(q)
        v=p[1]
        used[v]=true
        if d[v]<p[0]:
            continue
        for e in G[v]:
            if (not used[e[0]]) and d[e[0]]>d[v]+e[1]:
                d[e[0]]=d[v]+e[1]
                 
                heapq.heappush(q, (d[e[0]], e[0]))
 
import sys
for l in sys.stdin:
    l=list(map(int,l.split()))
    u=l[0]
    k=l[1]
    G[u]=zip(*[iter(l[2:])]*2)
     
dijkstra(0)
for i, c in enumerate(d):
    print(i, d[i])

Submission status: Runtime Error

Solution code:
from collections import defaultdict
import heapq
v_num = int(input())
connect = defaultdict(list)

for _ in range(v_num):
    que = [int(n) for n in input().split(" ")]
    connect[que[0]] = [[v, w] for v, w in zip(que[2:len(que):2], que[3:len(que):2])
    # weight_edge[que[0]] = {k:v for k, v in zip(que[2:len(que):2], que[3:len(que):2])}
queue = []
heapq.heapify(queue)
heapq.heappush(queue, [0, 0])
distance = [-1 for n in range(v_num)]
went = 0
visited = set()
while went < v_num:
    q = heapq.heappop(queue)
    weight, here = q
    if here in visited:
        continue
    visited |= {here}
    went += 1
    distance[here] = weight
    for conn in connect[here]:
        if conn[0] not in visited:
            heapq.heappush(queue, [weight + conn[1], conn[0]])
for i in range(v_num):
    print(i, distance[i])

Submission status: Runtime Error

Solution code:
import sys
from heapq import*
e=sys.stdin.readline
I=float("inf")
def m():
 n=int(e())
 A=[]
 for _ in[0]*n:
  e=list(map(int,e().split()))
  A+=[zip(e[2::2],e[3::2])]
 d=[0]+[I]*n
 H=[(0,0)]
 while H:
  u=heappop(H)[1]
  for v,c in A[u]:
   t=d[u]+c
   if d[v]>t:
    d[v]=t
    heappush(H,(t,v))
 print('\n'.join(f'{i} {d[i]}'for i in range(n)))
m()

Submission status: Runtime Error

Solution code:
N = int(input())
G = [[] for i in range(N)]
for nod in range(N):
    tmp = list(map(int, input().split()))
    for i in range(2, tmp[1]*2+1, 2):
        edge, cos = tmp[i], tmp[i+1]
        G[nod].append([edge, cos])



import heapq


def dijkstra(x):
    d = [float('inf')] * N
    d[x] = 0
    visited = {x}

    # d, u
    hq = [(0, x)]

    while hq:
        u = heapq.heappop(hq)[1]
        visited.add(u)

        for node, cost in G[u]:
            if (node not in visited) and d[node] > d[u] + cost:
                d[node] = d[u] + cost
                heapq.heappush(hq, (d[u]+cost, node))
    return d


distance = dijkstra(0)
#print(distance)
for i in range(N):
    print(i, distance[i])

N = int(input())
G = [[] for i in range(N)]
for nod in range(N):
    tmp = list(map(int, input().split()))
    for i in range(2, tmp[1]*2+1, 2):
        edge, cos = tmp[i], tmp[i+1]
        G[nod].append([edge, cos])



import heapq


def dijkstra(x):
    d = [float('inf')] * N
    d[x] = 0
    visited = {x}

    # d, u
    hq = [(0, x)]

    while hq:
        u = heapq.heappop(hq)[1]
        visited.add(u)

        for node, cost in G[u]:
            if (node not in visited) and d[node] > d[u] + cost:
                d[node] = d[u] + cost
                heapq.heappush(hq, (d[u]+cost, node))
    return d


distance = dijkstra(0)
#print(distance)
for i in range(N):
    print(i, distance[i])

Submission status: Runtime Error

Solution code:
from heapq import heappush, heappop
from enum import Enum, auto

INFTY = float('inf')

class Color(Enum):
    WHITE = auto()
    GRAY = auto()
    BLACK = auto()

n = int(input())
M = [[-1 for i in range(n)] for i in range(n)]
adj_list = []
for i in range(n):
    u, k, *kv = list(map(int, input().split(' ')))
    if k == 0: continue
    adj_list.append(kv)
    for j in range(0,2*k,2):
        M[i][kv[j]] = kv[j+1]
colors = []
d = []

def dijkstra(s):
    global d
    colors = [Color.WHITE for i in range(n)]
    d = [INFTY for i in range(n)]
    pque = []
    d[0] = 0

    heappush(pque, (0, s))

    while len(pque) >= 1:
        vert_u = heappop(pque)
        u = vert_u[1]
        colors[u] = Color.BLACK
        if d[u] < vert_u[0]: continue
        i = 0
        while i <= len(adj_list[u])-2:
            v = adj_list[u][i]
            if colors[v] != Color.BLACK:
                if d[u] + adj_list[u][i+1] < d[v]:
                    d[v] = d[u] + adj_list[u][i+1]
                    colors[v] = Color.GRAY
                    heappush(pque, (d[v], v))
            i += 2

dijkstra(0)
for i in range(n):
    print(i, d[i])