Buggy python submission (verdict: Time Limit Exceeded):
import bisect
import collections
from collections import defaultdict
import sys

sys.setrecursionlimit(100000)
input = sys.stdin.readline
ACMOD = 1000000007
INF = 1 << 32


def lmi():
    return list(map(int, input().split()))


def llmi(n):
    return [lmi() for _ in range(n)]


n, m, s, t = list(map(int, input().split()))

MAX_VAL = 10 ** 20
uvab = llmi(m)
jpy_cost = defaultdict(dict)
snuke_cost = defaultdict(dict)


def dijkstra2_scipy(adj, start, n=None, limit=None):
    """
    caution!  add 10**-10 to avoid 0 cost
    """
    from scipy.sparse import csr_matrix
    from scipy.sparse.csgraph._shortest_path import dijkstra
    if limit:
        limit += 0.5
    cost, row_ind, col_ind = [], [], []
    for k1, _v in adj.items():
        for k2, _cost in _v.items():
            row_ind.append(k1)
            col_ind.append(k2)
            cost.append(_cost + 10 ** -10)
    cost_matrix = csr_matrix((cost, (row_ind, col_ind)))
    return dijkstra(cost_matrix, indices=[start])[0]


for u, v, a, b in uvab:
    u = u - 1
    v = v - 1
    jpy_cost[u][v] = a
    jpy_cost[v][u] = a
    snuke_cost[u][v] = b
    snuke_cost[v][u] = b

jpy_dijk = dijkstra2_scipy(jpy_cost, start=s - 1)
snuke_dijk = dijkstra2_scipy(snuke_cost, start=t - 1)
res = []
min_val = MAX_VAL
for i in reversed(range(n)):
    # 都市  i で両替
    val = jpy_dijk[i] + snuke_dijk[i]
    assert val < MAX_VAL
    min_val = min(min_val, val)
    res.append(min_val)
for x in reversed(res):
    print(10 ** 15 - int(x))


Fixed submission:
from collections import defaultdict
from heapq import heapify, heappop
import heapq
n,m,s,t =list(map(int,input().split()))

MAX_VAL = 10**20
uvab =  [list(map(int,input().split())) for _ in range(m)]
jpy_cost = defaultdict(dict)
snuke_cost = defaultdict(dict)


for u,v,a,b in uvab:
    u=u-1
    v=v-1
    jpy_cost[u][v] = a
    jpy_cost[v][u] =a
    snuke_cost[u][v]=b
    snuke_cost[v][u]=b


# Dijktra's shortest path algorithm. Prints the path from source to target.


def dijkstra(adj, source):
    INF = MAX_VAL
    dist = [INF for x in range(n)]
    dist[source] = 0
    PQ = []
    heapq.heappush(PQ, [dist[source], source])

    while (PQ):
        u_dist,u_id = heapq.heappop(PQ)  # u is a tuple [u_dist, u_id]
        if u_dist == dist[u_id]:
            for v in adj[u_id]:
                w_uv = adj[u_id][v]
                if dist[u_id] + w_uv < dist[v]:
                    dist[v] = dist[u_id] + w_uv
                    heapq.heappush(PQ, [dist[v], v])
    return dist


jpy_dijk =  dijkstra(jpy_cost,s-1)
snuke_dijk = dijkstra(snuke_cost,t-1)
#
# print(s,t)
# print(jpy_dijk)
# print(snuke_dijk)
# print([jpy_dijk[i]+snuke_dijk[i] for i in range(n)])

#ord n
res = []
min_val = MAX_VAL
for i in reversed(range(n)):
    #都市  i で両替
    val = jpy_dijk[i]+ snuke_dijk[i]
    assert val < MAX_VAL
    min_val=min(min_val,val)
    res.append(min_val)
#ord n
for x in reversed(res):
    print(10**15-  x)

Buggy python submission (verdict: Time Limit Exceeded):
from collections import defaultdict
from heapq import heapify, heappop
import heapq
n,m,s,t =list(map(int,input().split()))

MAX_VAL = 10**20
uvab =  [list(map(int,input().split())) for _ in range(m)]
jpy_cost = defaultdict(dict)
snuke_cost = defaultdict(dict)


for u,v,a,b in uvab:
    u=u-1
    v=v-1
    jpy_cost[u][v] = a
    jpy_cost[v][u] =a
    snuke_cost[u][v]=b
    snuke_cost[v][u]=b


# Dijktra's shortest path algorithm. Prints the path from source to target.


def dijkstra(adj, source):
    INF = MAX_VAL
    dist = [INF for x in range(n)]
    dist[source] = 0
    PQ = []
    heapq.heappush(PQ, [dist[source], source])

    while (PQ):
        u_dist,u_id = heapq.heappop(PQ)  # u is a tuple [u_dist, u_id]
        if u_dist == dist[u_id]:
            for v in adj[u_id]:
                w_uv = adj[u_id][v]
                if dist[u_id] + w_uv < dist[v]:
                    dist[v] = dist[u_id] + w_uv
                    heapq.heappush(PQ, [dist[v], v])
    return dist


jpy_dijk =  dijkstra(jpy_cost,s-1)
snuke_dijk = dijkstra(snuke_cost,t-1)
#
# print(s,t)
# print(jpy_dijk)
# print(snuke_dijk)
# print([jpy_dijk[i]+snuke_dijk[i] for i in range(n)])

#ord n
res = []
min_val = MAX_VAL
for i in reversed(range(n)):
    #都市  i で両替
    val = jpy_dijk[i]+ snuke_dijk[i]
    assert val < MAX_VAL
    min_val=min(min_val,val)
    res.append(min_val)
#ord n
for x in reversed(res):
    print(10**15-  x)


Fixed submission:
from collections import defaultdict
from heapq import heapify, heappop
import heapq
n,m,s,t =list(map(int,input().split()))

MAX_VAL = 10**20
uvab =  [list(map(int,input().split())) for _ in range(m)]
jpy_cost = defaultdict(dict)
snuke_cost = defaultdict(dict)


for u,v,a,b in uvab:
    u=u-1
    v=v-1
    jpy_cost[u][v] = a
    jpy_cost[v][u] =a
    snuke_cost[u][v]=b
    snuke_cost[v][u]=b


# Dijktra's shortest path algorithm. Prints the path from source to target.


def dijkstra(adj, source):
    INF = MAX_VAL
    dist = [INF for x in range(n)]
    dist[source] = 0
    PQ = []
    heapq.heappush(PQ, [dist[source], source])

    while (PQ):
        u_dist,u_id = heapq.heappop(PQ)  # u is a tuple [u_dist, u_id]
        if u_dist == dist[u_id]:
            for v in adj[u_id]:
                w_uv = adj[u_id][v]
                if dist[u_id] + w_uv < dist[v]:
                    dist[v] = dist[u_id] + w_uv
                    heapq.heappush(PQ, [dist[v], v])
    return dist


jpy_dijk =  dijkstra(jpy_cost,s-1)
snuke_dijk = dijkstra(snuke_cost,t-1)
#
# print(s,t)
# print(jpy_dijk)
# print(snuke_dijk)
# print([jpy_dijk[i]+snuke_dijk[i] for i in range(n)])

#ord n
res = []
min_val = MAX_VAL
for i in reversed(range(n)):
    #都市  i で両替
    val = jpy_dijk[i]+ snuke_dijk[i]
    assert val < MAX_VAL
    min_val=min(min_val,val)
    res.append(min_val)
#ord n
for x in reversed(res):
    print(10**15-  x)

Buggy python submission (verdict: Time Limit Exceeded):
from collections import defaultdict
from heapq import heapify, heappop
import heapq
n,m,s,t =list(map(int,input().split()))

MAX_VAL = 10**20
uvab =  [list(map(int,input().split())) for _ in range(m)]
jpy_cost = defaultdict(lambda :defaultdict(lambda :MAX_VAL))
snuke_cost = defaultdict(lambda :defaultdict(lambda :MAX_VAL))


for u,v,a,b in uvab:
    u=u-1
    v=v-1
    jpy_cost[u][v] = a
    jpy_cost[v][u] =a
    snuke_cost[u][v]=b
    snuke_cost[v][u]=b


# Dijktra's shortest path algorithm. Prints the path from source to target.


def dijkstra(adj, source):
    INF = MAX_VAL
    dist = [INF for x in range(n)]
    dist[source] = 0
    PQ = []
    heapq.heappush(PQ, [dist[source], source])

    while (PQ):
        u_dist,u_id = heapq.heappop(PQ)  # u is a tuple [u_dist, u_id]
        if u_dist == dist[u_id]:
            for v in adj[u_id]:
                w_uv = adj[u_id][v]
                if dist[u_id] + w_uv < dist[v]:
                    dist[v] = dist[u_id] + w_uv
                    heapq.heappush(PQ, [dist[v], v])
    return dist


jpy_dijk =  dijkstra(jpy_cost,s-1)
snuke_dijk = dijkstra(snuke_cost,t-1)
#
# print(s,t)
# print(jpy_dijk)
# print(snuke_dijk)
# print([jpy_dijk[i]+snuke_dijk[i] for i in range(n)])

#ord n
res = []
min_val = MAX_VAL
for i in reversed(range(n)):
    #都市  i で両替
    val = jpy_dijk[i]+ snuke_dijk[i]
    assert val < MAX_VAL
    min_val=min(min_val,val)
    res.append(min_val)
#ord n
for x in reversed(res):
    print(10**15-  x)


Fixed submission:
from collections import defaultdict
from heapq import heapify, heappop
import heapq
n,m,s,t =list(map(int,input().split()))

MAX_VAL = 10**20
uvab =  [list(map(int,input().split())) for _ in range(m)]
jpy_cost = defaultdict(dict)
snuke_cost = defaultdict(dict)


for u,v,a,b in uvab:
    u=u-1
    v=v-1
    jpy_cost[u][v] = a
    jpy_cost[v][u] =a
    snuke_cost[u][v]=b
    snuke_cost[v][u]=b


# Dijktra's shortest path algorithm. Prints the path from source to target.


def dijkstra(adj, source):
    INF = MAX_VAL
    dist = [INF for x in range(n)]
    dist[source] = 0
    PQ = []
    heapq.heappush(PQ, [dist[source], source])

    while (PQ):
        u_dist,u_id = heapq.heappop(PQ)  # u is a tuple [u_dist, u_id]
        if u_dist == dist[u_id]:
            for v in adj[u_id]:
                w_uv = adj[u_id][v]
                if dist[u_id] + w_uv < dist[v]:
                    dist[v] = dist[u_id] + w_uv
                    heapq.heappush(PQ, [dist[v], v])
    return dist


jpy_dijk =  dijkstra(jpy_cost,s-1)
snuke_dijk = dijkstra(snuke_cost,t-1)
#
# print(s,t)
# print(jpy_dijk)
# print(snuke_dijk)
# print([jpy_dijk[i]+snuke_dijk[i] for i in range(n)])

#ord n
res = []
min_val = MAX_VAL
for i in reversed(range(n)):
    #都市  i で両替
    val = jpy_dijk[i]+ snuke_dijk[i]
    assert val < MAX_VAL
    min_val=min(min_val,val)
    res.append(min_val)
#ord n
for x in reversed(res):
    print(10**15-  x)

Buggy python submission (verdict: Time Limit Exceeded):
from collections import defaultdict
from heapq import heapify, heappop
import heapq
n,m,s,t =list(map(int,input().split()))

MAX_VAL = 10**20
uvab =  [list(map(int,input().split())) for _ in range(m)]
jpy_cost = defaultdict(lambda :defaultdict(lambda :MAX_VAL))
snuke_cost = defaultdict(lambda :defaultdict(lambda :MAX_VAL))


for u,v,a,b in uvab:
    u=u-1
    v=v-1
    jpy_cost[u][v] = a
    jpy_cost[v][u] =a
    snuke_cost[u][v]=b
    snuke_cost[v][u]=b


# Dijktra's shortest path algorithm. Prints the path from source to target.


def dijkstra(adj, source):
    INF = MAX_VAL
    dist = [INF for x in range(n)]
    dist[source] = 0
    PQ = []
    heapq.heappush(PQ, [dist[source], source])

    while (PQ):
        u = heapq.heappop(PQ)  # u is a tuple [u_dist, u_id]
        u_dist = u[0]
        u_id = u[1]
        if u_dist == dist[u_id]:
            # if u_id == target:
            #    break
            for v in adj[u_id]:
                v_id = v
                w_uv = adj[u_id][v]
                if dist[u_id] + w_uv < dist[v_id]:
                    dist[v_id] = dist[u_id] + w_uv
                    heapq.heappush(PQ, [dist[v_id], v_id])

    return dist


jpy_dijk =  dijkstra(jpy_cost,s-1)
snuke_dijk = dijkstra(snuke_cost,t-1)
#
# print(s,t)
# print(jpy_dijk)
# print(snuke_dijk)
# print([jpy_dijk[i]+snuke_dijk[i] for i in range(n)])

#ord n
res = []
min_val = MAX_VAL
for i in reversed(range(n)):
    #都市  i で両替
    val = jpy_dijk[i]+ snuke_dijk[i]
    assert val < MAX_VAL
    min_val=min(min_val,val)
    res.append(min_val)
#ord n
for x in reversed(res):
    print(10**15-  x)


Fixed submission:
from collections import defaultdict
from heapq import heapify, heappop
import heapq
n,m,s,t =list(map(int,input().split()))

MAX_VAL = 10**20
uvab =  [list(map(int,input().split())) for _ in range(m)]
jpy_cost = defaultdict(dict)
snuke_cost = defaultdict(dict)


for u,v,a,b in uvab:
    u=u-1
    v=v-1
    jpy_cost[u][v] = a
    jpy_cost[v][u] =a
    snuke_cost[u][v]=b
    snuke_cost[v][u]=b


# Dijktra's shortest path algorithm. Prints the path from source to target.


def dijkstra(adj, source):
    INF = MAX_VAL
    dist = [INF for x in range(n)]
    dist[source] = 0
    PQ = []
    heapq.heappush(PQ, [dist[source], source])

    while (PQ):
        u_dist,u_id = heapq.heappop(PQ)  # u is a tuple [u_dist, u_id]
        if u_dist == dist[u_id]:
            for v in adj[u_id]:
                w_uv = adj[u_id][v]
                if dist[u_id] + w_uv < dist[v]:
                    dist[v] = dist[u_id] + w_uv
                    heapq.heappush(PQ, [dist[v], v])
    return dist


jpy_dijk =  dijkstra(jpy_cost,s-1)
snuke_dijk = dijkstra(snuke_cost,t-1)
#
# print(s,t)
# print(jpy_dijk)
# print(snuke_dijk)
# print([jpy_dijk[i]+snuke_dijk[i] for i in range(n)])

#ord n
res = []
min_val = MAX_VAL
for i in reversed(range(n)):
    #都市  i で両替
    val = jpy_dijk[i]+ snuke_dijk[i]
    assert val < MAX_VAL
    min_val=min(min_val,val)
    res.append(min_val)
#ord n
for x in reversed(res):
    print(10**15-  x)

Buggy python submission (verdict: Time Limit Exceeded):
from collections import defaultdict
from heapq import heapify, heappop
import heapq
n,m,s,t =list(map(int,input().split()))

MAX_VAL = 10**20
uvab =  [list(map(int,input().split())) for _ in range(m)]
jpy_cost = defaultdict(lambda :defaultdict(lambda :MAX_VAL))
snuke_cost = defaultdict(lambda :defaultdict(lambda :MAX_VAL))


for u,v,a,b in uvab:
    u=u-1
    v=v-1
    jpy_cost[u][v] = a
    jpy_cost[v][u] =a
    snuke_cost[u][v]=b
    snuke_cost[v][u]=b


# Dijktra's shortest path algorithm. Prints the path from source to target.


def dijkstra(adj, source):
    INF = MAX_VAL
    pred = [x for x in range(n)]
    dist = [INF for x in range(n)]
    dist[source] = 0
    PQ = []
    heapq.heappush(PQ, [dist[source], source])

    while (PQ):
        u = heapq.heappop(PQ)  # u is a tuple [u_dist, u_id]
        u_dist = u[0]
        u_id = u[1]
        if u_dist == dist[u_id]:
            # if u_id == target:
            #    break
            for v in adj[u_id]:
                v_id = v
                w_uv = adj[u_id][v]
                if dist[u_id] + w_uv < dist[v_id]:
                    dist[v_id] = dist[u_id] + w_uv
                    heapq.heappush(PQ, [dist[v_id], v_id])
                    pred[v_id] = u_id

    return dist


jpy_dijk =  dijkstra(jpy_cost,s-1)
snuke_dijk = dijkstra(snuke_cost,t-1)
#
# print(s,t)
# print(jpy_dijk)
# print(snuke_dijk)
# print([jpy_dijk[i]+snuke_dijk[i] for i in range(n)])

#ord n
res = []
min_val = MAX_VAL
for i in reversed(range(n)):
    #都市  i で両替
    val = jpy_dijk[i]+ snuke_dijk[i]
    assert val < MAX_VAL
    min_val=min(min_val,val)
    res.append(min_val)
#ord n
for x in reversed(res):
    print(10**15-  x)


Fixed submission:
from collections import defaultdict
from heapq import heapify, heappop
import heapq
n,m,s,t =list(map(int,input().split()))

MAX_VAL = 10**20
uvab =  [list(map(int,input().split())) for _ in range(m)]
jpy_cost = defaultdict(dict)
snuke_cost = defaultdict(dict)


for u,v,a,b in uvab:
    u=u-1
    v=v-1
    jpy_cost[u][v] = a
    jpy_cost[v][u] =a
    snuke_cost[u][v]=b
    snuke_cost[v][u]=b


# Dijktra's shortest path algorithm. Prints the path from source to target.


def dijkstra(adj, source):
    INF = MAX_VAL
    dist = [INF for x in range(n)]
    dist[source] = 0
    PQ = []
    heapq.heappush(PQ, [dist[source], source])

    while (PQ):
        u_dist,u_id = heapq.heappop(PQ)  # u is a tuple [u_dist, u_id]
        if u_dist == dist[u_id]:
            for v in adj[u_id]:
                w_uv = adj[u_id][v]
                if dist[u_id] + w_uv < dist[v]:
                    dist[v] = dist[u_id] + w_uv
                    heapq.heappush(PQ, [dist[v], v])
    return dist


jpy_dijk =  dijkstra(jpy_cost,s-1)
snuke_dijk = dijkstra(snuke_cost,t-1)
#
# print(s,t)
# print(jpy_dijk)
# print(snuke_dijk)
# print([jpy_dijk[i]+snuke_dijk[i] for i in range(n)])

#ord n
res = []
min_val = MAX_VAL
for i in reversed(range(n)):
    #都市  i で両替
    val = jpy_dijk[i]+ snuke_dijk[i]
    assert val < MAX_VAL
    min_val=min(min_val,val)
    res.append(min_val)
#ord n
for x in reversed(res):
    print(10**15-  x)

Buggy python submission (verdict: Time Limit Exceeded):
from collections import defaultdict
from heapq import heapify, heappop
import heapq
n,m,s,t =list(map(int,input().split()))

MAX_VAL = 10**20
uvab =  [list(map(int,input().split())) for _ in range(m)]
jpy_cost = defaultdict(lambda :defaultdict(lambda :MAX_VAL))
snuke_cost = defaultdict(lambda :defaultdict(lambda :MAX_VAL))


for u,v,a,b in uvab:
    u=u-1
    v=v-1
    jpy_cost[u][v] = a
    jpy_cost[v][u] =a
    snuke_cost[u][v]=b
    snuke_cost[v][u]=b


# Dijktra's shortest path algorithm. Prints the path from source to target.


def dijkstra(adj, source):
    INF = ((1 << 63) - 1) // 2
    pred = {x: x for x in range(n)}
    dist = {x: INF for x in range(n)}
    dist[source] = 0
    PQ = []
    heapq.heappush(PQ, [dist[source], source])

    while (PQ):
        u = heapq.heappop(PQ)  # u is a tuple [u_dist, u_id]
        u_dist = u[0]
        u_id = u[1]
        if u_dist == dist[u_id]:
            # if u_id == target:
            #    break
            for v in adj[u_id]:
                v_id = v
                w_uv = adj[u_id][v]
                if dist[u_id] + w_uv < dist[v_id]:
                    dist[v_id] = dist[u_id] + w_uv
                    heapq.heappush(PQ, [dist[v_id], v_id])
                    pred[v_id] = u_id

    return dist


jpy_dijk =  dijkstra(jpy_cost,s-1)
snuke_dijk = dijkstra(snuke_cost,t-1)
#
# print(s,t)
# print(jpy_dijk)
# print(snuke_dijk)
# print([jpy_dijk[i]+snuke_dijk[i] for i in range(n)])

#ord n
res = []
min_val = MAX_VAL
for i in reversed(range(n)):
    #都市  i で両替
    val = jpy_dijk[i]+ snuke_dijk[i]
    assert val < MAX_VAL
    min_val=min(min_val,val)
    res.append(min_val)
#ord n
for x in reversed(res):
    print(10**15-  x)


Fixed submission:
from collections import defaultdict
from heapq import heapify, heappop
import heapq
n,m,s,t =list(map(int,input().split()))

MAX_VAL = 10**20
uvab =  [list(map(int,input().split())) for _ in range(m)]
jpy_cost = defaultdict(dict)
snuke_cost = defaultdict(dict)


for u,v,a,b in uvab:
    u=u-1
    v=v-1
    jpy_cost[u][v] = a
    jpy_cost[v][u] =a
    snuke_cost[u][v]=b
    snuke_cost[v][u]=b


# Dijktra's shortest path algorithm. Prints the path from source to target.


def dijkstra(adj, source):
    INF = MAX_VAL
    dist = [INF for x in range(n)]
    dist[source] = 0
    PQ = []
    heapq.heappush(PQ, [dist[source], source])

    while (PQ):
        u_dist,u_id = heapq.heappop(PQ)  # u is a tuple [u_dist, u_id]
        if u_dist == dist[u_id]:
            for v in adj[u_id]:
                w_uv = adj[u_id][v]
                if dist[u_id] + w_uv < dist[v]:
                    dist[v] = dist[u_id] + w_uv
                    heapq.heappush(PQ, [dist[v], v])
    return dist


jpy_dijk =  dijkstra(jpy_cost,s-1)
snuke_dijk = dijkstra(snuke_cost,t-1)
#
# print(s,t)
# print(jpy_dijk)
# print(snuke_dijk)
# print([jpy_dijk[i]+snuke_dijk[i] for i in range(n)])

#ord n
res = []
min_val = MAX_VAL
for i in reversed(range(n)):
    #都市  i で両替
    val = jpy_dijk[i]+ snuke_dijk[i]
    assert val < MAX_VAL
    min_val=min(min_val,val)
    res.append(min_val)
#ord n
for x in reversed(res):
    print(10**15-  x)

Buggy python submission (verdict: Runtime Error):
from collections import defaultdict
from heapq import heapify, heappop

n,m,s,t =list(map(int,input().split()))

MAX_VAL = 10**20
uvab =  [list(map(int,input().split())) for _ in range(m)]
jpy_cost = defaultdict(lambda :defaultdict(lambda :MAX_VAL))
snuke_cost = defaultdict(lambda :defaultdict(lambda :MAX_VAL))


for u,v,a,b in uvab:
    u=u-1
    v=v-1
    jpy_cost[u][v] = a
    jpy_cost[v][u] =a
    snuke_cost[u][v]=b
    snuke_cost[v][u]=b


def dijkstra(glaph, start, goal,g_size):
    def get_path(start, goal, prev):
        path = []
        now = goal
        path.append(now)
        while True:
            path.append(prev[now])
            if prev[now] == start: break
            now = prev[now]
        path.reverse()
        return path
    #g_size = len(glaph)
    visited = [False] * g_size
    cost = [MAX_VAL] * g_size
    prev = [None] * g_size
    cost[start] = 0
    prev[start] = start
    now = start
    while True:
        min = MAX_VAL
        next = -1
        visited[now] = True
        for i in range(g_size):
        #for i in glaph[now]:
            if visited[i]: continue
            if glaph[now][i]:
                tmp_cost = glaph[now][i] + cost[now]
                if cost[i] > tmp_cost:
                    cost[i] = tmp_cost
                    prev[i] = now
            if min > cost[i]:
                min = cost[i]
                next = i
        if next == -1: break
        now = next

    return cost
    #return [get_path(start, goal, prev), cost[goal]]



def dijkstra2(graph, source):
    inf = float('inf')
    dist = defaultdict(lambda: inf)
    previous = {}
    visited = set()

    dist[source] = 0
    graph_nodes = [(dist[n], n) for n in graph.keys()]
    heapify(graph_nodes)
    while graph_nodes:
        _, u = heappop(graph_nodes)
        visited.add(u)
        if dist[u] == inf:
            break

        for v in graph[u]:
            if v in visited:
                continue
            alt = dist[u] + graph[u][v]
            if alt < dist[v]:
                i = graph_nodes.index((dist[v], v))
                graph_nodes[i] = (alt, v)
                heapify(graph_nodes)

                dist[v] = alt
                previous[v] = u

    return dist


#jpy_dijk = (dijkstra(jpy_cost,s-1,s-1,n))
#snuke_dijk = (dijkstra(snuke_cost,t-1,t-1,n))
jpy_dijk = (dijkstra2(jpy_cost,s-1))
raise
snuke_dijk = (dijkstra2(snuke_cost,t-1))
raise

#print(s,t)
#print(jpy_dijk)
#print(snuke_dijk)
#print([jpy_dijk[i]+snuke_dijk[i] for i in range(n)])

#ord n
res = []
min_val = MAX_VAL
for i in reversed(range(n)):
    #都市  i で両替
    val = jpy_dijk[i]+ snuke_dijk[i]
    assert val < MAX_VAL
    min_val=min(min_val,val)
    res.append(min_val)
#ord n
for x in reversed(res):
    print(10**15-  x)


Fixed submission:
from collections import defaultdict
from heapq import heapify, heappop
import heapq
n,m,s,t =list(map(int,input().split()))

MAX_VAL = 10**20
uvab =  [list(map(int,input().split())) for _ in range(m)]
jpy_cost = defaultdict(dict)
snuke_cost = defaultdict(dict)


for u,v,a,b in uvab:
    u=u-1
    v=v-1
    jpy_cost[u][v] = a
    jpy_cost[v][u] =a
    snuke_cost[u][v]=b
    snuke_cost[v][u]=b


# Dijktra's shortest path algorithm. Prints the path from source to target.


def dijkstra(adj, source):
    INF = MAX_VAL
    dist = [INF for x in range(n)]
    dist[source] = 0
    PQ = []
    heapq.heappush(PQ, [dist[source], source])

    while (PQ):
        u_dist,u_id = heapq.heappop(PQ)  # u is a tuple [u_dist, u_id]
        if u_dist == dist[u_id]:
            for v in adj[u_id]:
                w_uv = adj[u_id][v]
                if dist[u_id] + w_uv < dist[v]:
                    dist[v] = dist[u_id] + w_uv
                    heapq.heappush(PQ, [dist[v], v])
    return dist


jpy_dijk =  dijkstra(jpy_cost,s-1)
snuke_dijk = dijkstra(snuke_cost,t-1)
#
# print(s,t)
# print(jpy_dijk)
# print(snuke_dijk)
# print([jpy_dijk[i]+snuke_dijk[i] for i in range(n)])

#ord n
res = []
min_val = MAX_VAL
for i in reversed(range(n)):
    #都市  i で両替
    val = jpy_dijk[i]+ snuke_dijk[i]
    assert val < MAX_VAL
    min_val=min(min_val,val)
    res.append(min_val)
#ord n
for x in reversed(res):
    print(10**15-  x)

Buggy python submission (verdict: Runtime Error):
from collections import defaultdict
from heapq import heapify, heappop

n,m,s,t =list(map(int,input().split()))

MAX_VAL = 10**20
uvab =  [list(map(int,input().split())) for _ in range(m)]
jpy_cost = defaultdict(lambda :defaultdict(lambda :MAX_VAL))
snuke_cost = defaultdict(lambda :defaultdict(lambda :MAX_VAL))


for u,v,a,b in uvab:
    u=u-1
    v=v-1
    jpy_cost[u][v] = a
    jpy_cost[v][u] =a
    snuke_cost[u][v]=b
    snuke_cost[v][u]=b


def dijkstra(glaph, start, goal,g_size):
    def get_path(start, goal, prev):
        path = []
        now = goal
        path.append(now)
        while True:
            path.append(prev[now])
            if prev[now] == start: break
            now = prev[now]
        path.reverse()
        return path
    #g_size = len(glaph)
    visited = [False] * g_size
    cost = [MAX_VAL] * g_size
    prev = [None] * g_size
    cost[start] = 0
    prev[start] = start
    now = start
    while True:
        min = MAX_VAL
        next = -1
        visited[now] = True
        for i in range(g_size):
        #for i in glaph[now]:
            if visited[i]: continue
            if glaph[now][i]:
                tmp_cost = glaph[now][i] + cost[now]
                if cost[i] > tmp_cost:
                    cost[i] = tmp_cost
                    prev[i] = now
            if min > cost[i]:
                min = cost[i]
                next = i
        if next == -1: break
        now = next

    return cost
    #return [get_path(start, goal, prev), cost[goal]]



def dijkstra2(graph, source):
    inf = float('inf')
    dist = defaultdict(lambda: inf)
    previous = {}
    visited = set()

    dist[source] = 0
    graph_nodes = [(dist[n], n) for n in graph.keys()]
    heapify(graph_nodes)
    while graph_nodes:
        _, u = heappop(graph_nodes)
        visited.add(u)
        if dist[u] == inf:
            break

        for v in graph[u]:
            if v in visited:
                continue
            alt = dist[u] + graph[u][v]
            if alt < dist[v]:
                i = graph_nodes.index((dist[v], v))
                graph_nodes[i] = (alt, v)
                heapify(graph_nodes)

                dist[v] = alt
                previous[v] = u

    return dist


#jpy_dijk = (dijkstra(jpy_cost,s-1,s-1,n))
#snuke_dijk = (dijkstra(snuke_cost,t-1,t-1,n))
jpy_dijk = (dijkstra2(jpy_cost,s-1))
snuke_dijk = (dijkstra2(snuke_cost,t-1))
raise

#print(s,t)
#print(jpy_dijk)
#print(snuke_dijk)
#print([jpy_dijk[i]+snuke_dijk[i] for i in range(n)])

#ord n
res = []
min_val = MAX_VAL
for i in reversed(range(n)):
    #都市  i で両替
    val = jpy_dijk[i]+ snuke_dijk[i]
    assert val < MAX_VAL
    min_val=min(min_val,val)
    res.append(min_val)
#ord n
for x in reversed(res):
    print(10**15-  x)


Fixed submission:
from collections import defaultdict
from heapq import heapify, heappop
import heapq
n,m,s,t =list(map(int,input().split()))

MAX_VAL = 10**20
uvab =  [list(map(int,input().split())) for _ in range(m)]
jpy_cost = defaultdict(dict)
snuke_cost = defaultdict(dict)


for u,v,a,b in uvab:
    u=u-1
    v=v-1
    jpy_cost[u][v] = a
    jpy_cost[v][u] =a
    snuke_cost[u][v]=b
    snuke_cost[v][u]=b


# Dijktra's shortest path algorithm. Prints the path from source to target.


def dijkstra(adj, source):
    INF = MAX_VAL
    dist = [INF for x in range(n)]
    dist[source] = 0
    PQ = []
    heapq.heappush(PQ, [dist[source], source])

    while (PQ):
        u_dist,u_id = heapq.heappop(PQ)  # u is a tuple [u_dist, u_id]
        if u_dist == dist[u_id]:
            for v in adj[u_id]:
                w_uv = adj[u_id][v]
                if dist[u_id] + w_uv < dist[v]:
                    dist[v] = dist[u_id] + w_uv
                    heapq.heappush(PQ, [dist[v], v])
    return dist


jpy_dijk =  dijkstra(jpy_cost,s-1)
snuke_dijk = dijkstra(snuke_cost,t-1)
#
# print(s,t)
# print(jpy_dijk)
# print(snuke_dijk)
# print([jpy_dijk[i]+snuke_dijk[i] for i in range(n)])

#ord n
res = []
min_val = MAX_VAL
for i in reversed(range(n)):
    #都市  i で両替
    val = jpy_dijk[i]+ snuke_dijk[i]
    assert val < MAX_VAL
    min_val=min(min_val,val)
    res.append(min_val)
#ord n
for x in reversed(res):
    print(10**15-  x)

Buggy python submission (verdict: Time Limit Exceeded):
from collections import defaultdict
from heapq import heapify, heappop

n,m,s,t =list(map(int,input().split()))

MAX_VAL = 10**20
uvab =  [list(map(int,input().split())) for _ in range(m)]
jpy_cost = defaultdict(lambda :defaultdict(lambda :MAX_VAL))
snuke_cost = defaultdict(lambda :defaultdict(lambda :MAX_VAL))

class Graph:
  def __init__(self):
    self.nodes = set()
    self.edges = defaultdict(list)
    self.distances = {}

  def add_node(self, value):
    self.nodes.add(value)

  def add_edge(self, from_node, to_node, distance):
    self.edges[from_node].append(to_node)
    self.edges[to_node].append(from_node)
    self.distances[(from_node, to_node)] = distance

jpy_graph = Graph()
snuke_graph= Graph()

for i in range(n):
    jpy_graph.add_node(i)
    snuke_graph.add_node(i)

for u,v,a,b in uvab:
    u=u-1
    v=v-1
    jpy_cost[u][v] = a
    jpy_cost[v][u] =a
    snuke_cost[u][v]=b
    snuke_cost[v][u]=b
    jpy_graph.add_edge(u,v,a)
    jpy_graph.add_edge(v,u,a)
    snuke_graph.add_edge(u, v, b)
    snuke_graph.add_edge(v, u, b)

def dijsktra(graph, initial):
  visited = {initial: 0}
  path = {}

  nodes = set(graph.nodes)

  while nodes:
    min_node = None
    for node in nodes:
      if node in visited:
        if min_node is None:
          min_node = node
        elif visited[node] < visited[min_node]:
          min_node = node

    if min_node is None:
      break

    nodes.remove(min_node)
    current_weight = visited[min_node]

    for edge in graph.edges[min_node]:
      weight = current_weight + graph.distances[(min_node, edge)]
      if edge not in visited or weight < visited[edge]:
        visited[edge] = weight
        path[edge] = min_node

  return visited

jpy_dijk =  dijsktra(jpy_graph,s-1)
snuke_dijk = dijsktra(snuke_graph,t-1)

#print(s,t)
#print(jpy_dijk)
#print(snuke_dijk)
#print([jpy_dijk[i]+snuke_dijk[i] for i in range(n)])

#ord n
res = []
min_val = MAX_VAL
for i in reversed(range(n)):
    #都市  i で両替
    val = jpy_dijk[i]+ snuke_dijk[i]
    assert val < MAX_VAL
    min_val=min(min_val,val)
    res.append(min_val)
#ord n
for x in reversed(res):
    print(10**15-  x)


Fixed submission:
from collections import defaultdict
from heapq import heapify, heappop
import heapq
n,m,s,t =list(map(int,input().split()))

MAX_VAL = 10**20
uvab =  [list(map(int,input().split())) for _ in range(m)]
jpy_cost = defaultdict(dict)
snuke_cost = defaultdict(dict)


for u,v,a,b in uvab:
    u=u-1
    v=v-1
    jpy_cost[u][v] = a
    jpy_cost[v][u] =a
    snuke_cost[u][v]=b
    snuke_cost[v][u]=b


# Dijktra's shortest path algorithm. Prints the path from source to target.


def dijkstra(adj, source):
    INF = MAX_VAL
    dist = [INF for x in range(n)]
    dist[source] = 0
    PQ = []
    heapq.heappush(PQ, [dist[source], source])

    while (PQ):
        u_dist,u_id = heapq.heappop(PQ)  # u is a tuple [u_dist, u_id]
        if u_dist == dist[u_id]:
            for v in adj[u_id]:
                w_uv = adj[u_id][v]
                if dist[u_id] + w_uv < dist[v]:
                    dist[v] = dist[u_id] + w_uv
                    heapq.heappush(PQ, [dist[v], v])
    return dist


jpy_dijk =  dijkstra(jpy_cost,s-1)
snuke_dijk = dijkstra(snuke_cost,t-1)
#
# print(s,t)
# print(jpy_dijk)
# print(snuke_dijk)
# print([jpy_dijk[i]+snuke_dijk[i] for i in range(n)])

#ord n
res = []
min_val = MAX_VAL
for i in reversed(range(n)):
    #都市  i で両替
    val = jpy_dijk[i]+ snuke_dijk[i]
    assert val < MAX_VAL
    min_val=min(min_val,val)
    res.append(min_val)
#ord n
for x in reversed(res):
    print(10**15-  x)

Buggy python submission (verdict: Time Limit Exceeded):
from collections import defaultdict
from heapq import heapify, heappop

n,m,s,t =list(map(int,input().split()))

MAX_VAL = 10**20
uvab =  [list(map(int,input().split())) for _ in range(m)]
jpy_cost = defaultdict(lambda :defaultdict(lambda :MAX_VAL))
snuke_cost = defaultdict(lambda :defaultdict(lambda :MAX_VAL))


for u,v,a,b in uvab:
    u=u-1
    v=v-1
    jpy_cost[u][v] = a
    jpy_cost[v][u] =a
    snuke_cost[u][v]=b
    snuke_cost[v][u]=b


def dijkstra(glaph, start, goal,g_size):
    def get_path(start, goal, prev):
        path = []
        now = goal
        path.append(now)
        while True:
            path.append(prev[now])
            if prev[now] == start: break
            now = prev[now]
        path.reverse()
        return path
    #g_size = len(glaph)
    visited = [False] * g_size
    cost = [MAX_VAL] * g_size
    prev = [None] * g_size
    cost[start] = 0
    prev[start] = start
    now = start
    while True:
        min = MAX_VAL
        next = -1
        visited[now] = True
        for i in range(g_size):
        #for i in glaph[now]:
            if visited[i]: continue
            if glaph[now][i]:
                tmp_cost = glaph[now][i] + cost[now]
                if cost[i] > tmp_cost:
                    cost[i] = tmp_cost
                    prev[i] = now
            if min > cost[i]:
                min = cost[i]
                next = i
        if next == -1: break
        now = next

    return cost
    #return [get_path(start, goal, prev), cost[goal]]



def dijkstra2(graph, source):
    inf = float('inf')
    dist = defaultdict(lambda: inf)
    previous = {}
    visited = set()

    dist[source] = 0
    graph_nodes = [(dist[n], n) for n in graph.keys()]
    heapify(graph_nodes)
    while graph_nodes:
        _, u = heappop(graph_nodes)
        visited.add(u)
        if dist[u] == inf:
            break

        for v in graph[u]:
            if v in visited:
                continue
            alt = dist[u] + graph[u][v]
            if alt < dist[v]:
                i = graph_nodes.index((dist[v], v))
                graph_nodes[i] = (alt, v)
                heapify(graph_nodes)

                dist[v] = alt
                previous[v] = u

    return dist


#jpy_dijk = (dijkstra(jpy_cost,s-1,s-1,n))
#snuke_dijk = (dijkstra(snuke_cost,t-1,t-1,n))
jpy_dijk = (dijkstra2(jpy_cost,s-1))
snuke_dijk = (dijkstra2(snuke_cost,t-1))

#print(s,t)
#print(jpy_dijk)
#print(snuke_dijk)
#print([jpy_dijk[i]+snuke_dijk[i] for i in range(n)])

#ord n
res = []
min_val = MAX_VAL
for i in reversed(range(n)):
    #都市  i で両替
    val = jpy_dijk[i]+ snuke_dijk[i]
    assert val < MAX_VAL
    min_val=min(min_val,val)
    res.append(min_val)
#ord n
for x in reversed(res):
    print(10**15-  x)


Fixed submission:
from collections import defaultdict
from heapq import heapify, heappop
import heapq
n,m,s,t =list(map(int,input().split()))

MAX_VAL = 10**20
uvab =  [list(map(int,input().split())) for _ in range(m)]
jpy_cost = defaultdict(dict)
snuke_cost = defaultdict(dict)


for u,v,a,b in uvab:
    u=u-1
    v=v-1
    jpy_cost[u][v] = a
    jpy_cost[v][u] =a
    snuke_cost[u][v]=b
    snuke_cost[v][u]=b


# Dijktra's shortest path algorithm. Prints the path from source to target.


def dijkstra(adj, source):
    INF = MAX_VAL
    dist = [INF for x in range(n)]
    dist[source] = 0
    PQ = []
    heapq.heappush(PQ, [dist[source], source])

    while (PQ):
        u_dist,u_id = heapq.heappop(PQ)  # u is a tuple [u_dist, u_id]
        if u_dist == dist[u_id]:
            for v in adj[u_id]:
                w_uv = adj[u_id][v]
                if dist[u_id] + w_uv < dist[v]:
                    dist[v] = dist[u_id] + w_uv
                    heapq.heappush(PQ, [dist[v], v])
    return dist


jpy_dijk =  dijkstra(jpy_cost,s-1)
snuke_dijk = dijkstra(snuke_cost,t-1)
#
# print(s,t)
# print(jpy_dijk)
# print(snuke_dijk)
# print([jpy_dijk[i]+snuke_dijk[i] for i in range(n)])

#ord n
res = []
min_val = MAX_VAL
for i in reversed(range(n)):
    #都市  i で両替
    val = jpy_dijk[i]+ snuke_dijk[i]
    assert val < MAX_VAL
    min_val=min(min_val,val)
    res.append(min_val)
#ord n
for x in reversed(res):
    print(10**15-  x)

Buggy python submission (verdict: Time Limit Exceeded):
from collections import defaultdict
n,m,s,t =list(map(int,input().split()))

MAX_VAL = 10**20
uvab =  [list(map(int,input().split())) for _ in range(m)]
jpy_cost = defaultdict(lambda :defaultdict(lambda :MAX_VAL))
snuke_cost = defaultdict(lambda :defaultdict(lambda :MAX_VAL))


for u,v,a,b in uvab:
    u=u-1
    v=v-1
    jpy_cost[u][v] = a
    jpy_cost[v][u] =a
    snuke_cost[u][v]=b
    snuke_cost[v][u]=b


def dijkstra(glaph, start, goal,g_size):
    def get_path(start, goal, prev):
        path = []
        now = goal
        path.append(now)
        while True:
            path.append(prev[now])
            if prev[now] == start: break
            now = prev[now]
        path.reverse()
        return path
    #g_size = len(glaph)
    visited = [False] * g_size
    cost = [MAX_VAL] * g_size
    prev = [None] * g_size
    cost[start] = 0
    prev[start] = start
    now = start
    while True:
        min = MAX_VAL
        next = -1
        visited[now] = True
        for i in range(g_size):
        #for i in glaph[now]:
            if visited[i]: continue
            if glaph[now][i]:
                tmp_cost = glaph[now][i] + cost[now]
                if cost[i] > tmp_cost:
                    cost[i] = tmp_cost
                    prev[i] = now
            if min > cost[i]:
                min = cost[i]
                next = i
        if next == -1: break
        now = next

    return cost
    #return [get_path(start, goal, prev), cost[goal]]


jpy_dijk = (dijkstra(jpy_cost,s-1,s-1,n))
snuke_dijk = (dijkstra(snuke_cost,t-1,t-1,n))

#print(s,t)
#print(jpy_dijk)
#print(snuke_dijk)
#print([jpy_dijk[i]+snuke_dijk[i] for i in range(n)])

#ord n
res = []
min_val = MAX_VAL
for i in reversed(range(n)):
    #都市  i で両替
    val = jpy_dijk[i]+ snuke_dijk[i]
    assert val < MAX_VAL
    min_val=min(min_val,val)
    res.append(min_val)
#ord n
for x in reversed(res):
    print(10**15-  x)


Fixed submission:
from collections import defaultdict
from heapq import heapify, heappop
import heapq
n,m,s,t =list(map(int,input().split()))

MAX_VAL = 10**20
uvab =  [list(map(int,input().split())) for _ in range(m)]
jpy_cost = defaultdict(dict)
snuke_cost = defaultdict(dict)


for u,v,a,b in uvab:
    u=u-1
    v=v-1
    jpy_cost[u][v] = a
    jpy_cost[v][u] =a
    snuke_cost[u][v]=b
    snuke_cost[v][u]=b


# Dijktra's shortest path algorithm. Prints the path from source to target.


def dijkstra(adj, source):
    INF = MAX_VAL
    dist = [INF for x in range(n)]
    dist[source] = 0
    PQ = []
    heapq.heappush(PQ, [dist[source], source])

    while (PQ):
        u_dist,u_id = heapq.heappop(PQ)  # u is a tuple [u_dist, u_id]
        if u_dist == dist[u_id]:
            for v in adj[u_id]:
                w_uv = adj[u_id][v]
                if dist[u_id] + w_uv < dist[v]:
                    dist[v] = dist[u_id] + w_uv
                    heapq.heappush(PQ, [dist[v], v])
    return dist


jpy_dijk =  dijkstra(jpy_cost,s-1)
snuke_dijk = dijkstra(snuke_cost,t-1)
#
# print(s,t)
# print(jpy_dijk)
# print(snuke_dijk)
# print([jpy_dijk[i]+snuke_dijk[i] for i in range(n)])

#ord n
res = []
min_val = MAX_VAL
for i in reversed(range(n)):
    #都市  i で両替
    val = jpy_dijk[i]+ snuke_dijk[i]
    assert val < MAX_VAL
    min_val=min(min_val,val)
    res.append(min_val)
#ord n
for x in reversed(res):
    print(10**15-  x)

Buggy python submission (verdict: Runtime Error):
from collections import defaultdict
n,m,s,t =list(map(int,input().split()))

MAX_VAL = 10**20
uvab =  [list(map(int,input().split())) for _ in range(m)]
jpy_cost = defaultdict(lambda :defaultdict(lambda :MAX_VAL))
snuke_cost = defaultdict(lambda :defaultdict(lambda :MAX_VAL))


for u,v,a,b in uvab:
    u=u-1
    v=v-1
    jpy_cost[u][v] = a
    jpy_cost[v][u] =a
    snuke_cost[u][v]=b
    snuke_cost[v][u]=b


def dijkstra(glaph, start, goal,g_size):
    def get_path(start, goal, prev):
        path = []
        now = goal
        path.append(now)
        while True:
            path.append(prev[now])
            if prev[now] == start: break
            now = prev[now]
        path.reverse()
        return path
    #g_size = len(glaph)
    visited = [False] * g_size
    cost = [MAX_VAL] * g_size
    prev = [None] * g_size
    cost[start] = 0
    prev[start] = start
    now = start
    while True:
        min = MAX_VAL
        next = -1
        visited[now] = True
        #for i in range(g_size):
        for i in glaph[now]:
            if visited[i]: continue
            if glaph[now][i]:
                tmp_cost = glaph[now][i] + cost[now]
                if cost[i] > tmp_cost:
                    cost[i] = tmp_cost
                    prev[i] = now
            if min > cost[i]:
                min = cost[i]
                next = i
        if next == -1: break
        now = next

    return cost
    #return [get_path(start, goal, prev), cost[goal]]


jpy_dijk = (dijkstra(jpy_cost,s-1,s-1,n))
snuke_dijk = (dijkstra(snuke_cost,t-1,t-1,n))

#print(s,t)
#print(jpy_dijk)
#print(snuke_dijk)
#print([jpy_dijk[i]+snuke_dijk[i] for i in range(n)])

#ord n
res = []
min_val = MAX_VAL
for i in reversed(range(n)):
    #都市  i で両替
    val = jpy_dijk[i]+ snuke_dijk[i]
    assert val < MAX_VAL
    min_val=min(min_val,val)
    res.append(min_val)
#ord n
for x in reversed(res):
    print(10**15-  x)


Fixed submission:
from collections import defaultdict
from heapq import heapify, heappop
import heapq
n,m,s,t =list(map(int,input().split()))

MAX_VAL = 10**20
uvab =  [list(map(int,input().split())) for _ in range(m)]
jpy_cost = defaultdict(dict)
snuke_cost = defaultdict(dict)


for u,v,a,b in uvab:
    u=u-1
    v=v-1
    jpy_cost[u][v] = a
    jpy_cost[v][u] =a
    snuke_cost[u][v]=b
    snuke_cost[v][u]=b


# Dijktra's shortest path algorithm. Prints the path from source to target.


def dijkstra(adj, source):
    INF = MAX_VAL
    dist = [INF for x in range(n)]
    dist[source] = 0
    PQ = []
    heapq.heappush(PQ, [dist[source], source])

    while (PQ):
        u_dist,u_id = heapq.heappop(PQ)  # u is a tuple [u_dist, u_id]
        if u_dist == dist[u_id]:
            for v in adj[u_id]:
                w_uv = adj[u_id][v]
                if dist[u_id] + w_uv < dist[v]:
                    dist[v] = dist[u_id] + w_uv
                    heapq.heappush(PQ, [dist[v], v])
    return dist


jpy_dijk =  dijkstra(jpy_cost,s-1)
snuke_dijk = dijkstra(snuke_cost,t-1)
#
# print(s,t)
# print(jpy_dijk)
# print(snuke_dijk)
# print([jpy_dijk[i]+snuke_dijk[i] for i in range(n)])

#ord n
res = []
min_val = MAX_VAL
for i in reversed(range(n)):
    #都市  i で両替
    val = jpy_dijk[i]+ snuke_dijk[i]
    assert val < MAX_VAL
    min_val=min(min_val,val)
    res.append(min_val)
#ord n
for x in reversed(res):
    print(10**15-  x)

Buggy python submission (verdict: Runtime Error):
from collections import defaultdict
n,m,s,t =list(map(int,input().split()))

MAX_VAL = 10**20
uvab =  [list(map(int,input().split())) for _ in range(m)]
jpy_cost = defaultdict(lambda :defaultdict(lambda :MAX_VAL))
snuke_cost = defaultdict(lambda :defaultdict(lambda :MAX_VAL))


for u,v,a,b in uvab:
    u=u-1
    v=v-1
    jpy_cost[u][v] = a
    jpy_cost[v][u] =a
    snuke_cost[u][v]=b
    snuke_cost[v][u]=b


def dijkstra(glaph, start, goal,g_size):
    def get_path(start, goal, prev):
        path = []
        now = goal
        path.append(now)
        while True:
            path.append(prev[now])
            if prev[now] == start: break
            now = prev[now]
        path.reverse()
        return path
    #g_size = len(glaph)
    visited = [False] * g_size
    cost = [MAX_VAL] * g_size
    prev = [None] * g_size
    cost[start] = 0
    prev[start] = start
    now = start
    while True:
        min = MAX_VAL
        next = -1
        visited[now] = True
        #for i in range(g_size):
        for i in glaph[now]:
            if visited[i]: continue
            if glaph[now][i]:
                tmp_cost = glaph[now][i] + cost[now]
                if cost[i] > tmp_cost:
                    cost[i] = tmp_cost
                    prev[i] = now
            if min > cost[i]:
                min = cost[i]
                next = i
        if next == -1: break
        now = next

    return cost
    #return [get_path(start, goal, prev), cost[goal]]


jpy_dijk = (dijkstra(jpy_cost,s-1,0,n))
snuke_dijk = (dijkstra(snuke_cost,t-1,0,n))

#print(jpy_dijk)
#print(snuke_dijk)
#print([jpy_dijk[i]+snuke_dijk[i] for i in range(n)])

#ord n
res = []
min_val = MAX_VAL
for i in reversed(range(n)):
    #都市  i で両替
    val = jpy_dijk[i]+ snuke_dijk[i]
    assert val < MAX_VAL
    min_val=min(min_val,val)
    res.append(min_val)
#ord n
for x in reversed(res):
    print(10**15-  x)


Fixed submission:
from collections import defaultdict
from heapq import heapify, heappop
import heapq
n,m,s,t =list(map(int,input().split()))

MAX_VAL = 10**20
uvab =  [list(map(int,input().split())) for _ in range(m)]
jpy_cost = defaultdict(dict)
snuke_cost = defaultdict(dict)


for u,v,a,b in uvab:
    u=u-1
    v=v-1
    jpy_cost[u][v] = a
    jpy_cost[v][u] =a
    snuke_cost[u][v]=b
    snuke_cost[v][u]=b


# Dijktra's shortest path algorithm. Prints the path from source to target.


def dijkstra(adj, source):
    INF = MAX_VAL
    dist = [INF for x in range(n)]
    dist[source] = 0
    PQ = []
    heapq.heappush(PQ, [dist[source], source])

    while (PQ):
        u_dist,u_id = heapq.heappop(PQ)  # u is a tuple [u_dist, u_id]
        if u_dist == dist[u_id]:
            for v in adj[u_id]:
                w_uv = adj[u_id][v]
                if dist[u_id] + w_uv < dist[v]:
                    dist[v] = dist[u_id] + w_uv
                    heapq.heappush(PQ, [dist[v], v])
    return dist


jpy_dijk =  dijkstra(jpy_cost,s-1)
snuke_dijk = dijkstra(snuke_cost,t-1)
#
# print(s,t)
# print(jpy_dijk)
# print(snuke_dijk)
# print([jpy_dijk[i]+snuke_dijk[i] for i in range(n)])

#ord n
res = []
min_val = MAX_VAL
for i in reversed(range(n)):
    #都市  i で両替
    val = jpy_dijk[i]+ snuke_dijk[i]
    assert val < MAX_VAL
    min_val=min(min_val,val)
    res.append(min_val)
#ord n
for x in reversed(res):
    print(10**15-  x)

Buggy python submission (verdict: Time Limit Exceeded):
from collections import defaultdict
n,m,s,t =list(map(int,input().split()))

uvab =  [list(map(int,input().split())) for _ in range(m)]
jpy_cost = defaultdict(lambda :defaultdict(lambda :10000000000))
snuke_cost = defaultdict(lambda :defaultdict(lambda :10000000000))


for u,v,a,b in uvab:
    u=u-1
    v=v-1
    jpy_cost[u][v]= a
    jpy_cost[v][u] =a
    snuke_cost[u][v]=b
    snuke_cost[v][u]=b


def dijkstra(glaph, start, goal,g_size):
    def get_path(start, goal, prev):
        path = []
        now = goal
        path.append(now)
        while True:
            path.append(prev[now])
            if prev[now] == start: break
            now = prev[now]
        path.reverse()
        return path

    MAX_VAL = 0x1000000000000000
    #g_size = len(glaph)
    visited = [False] * g_size
    cost = [MAX_VAL] * g_size
    prev = [None] * g_size
    cost[start] = 0
    prev[start] = start
    now = start
    while True:
        min = MAX_VAL
        next = -1
        visited[now] = True
        for i in range(g_size):
            if visited[i]: continue
            if glaph[now][i]:
                tmp_cost = glaph[now][i] + cost[now]
                if cost[i] > tmp_cost:
                    cost[i] = tmp_cost
                    prev[i] = now
            if min > cost[i]:
                min = cost[i]
                next = i
        if next == -1: break
        now = next

    return cost
    #return [get_path(start, goal, prev), cost[goal]]


jpy_dijk = (dijkstra(jpy_cost,s-1,0,n))
snuke_dijk = (dijkstra(snuke_cost,t-1,0,n))

res = []
min_val = 1000000000000
for i in reversed(range(n)):
    val = jpy_dijk[i]+ snuke_dijk[i]
    min_val=min(min_val,val)
    res.append(min_val)

for x in reversed(res):
    print(10**15-  x)


Fixed submission:
from collections import defaultdict
from heapq import heapify, heappop
import heapq
n,m,s,t =list(map(int,input().split()))

MAX_VAL = 10**20
uvab =  [list(map(int,input().split())) for _ in range(m)]
jpy_cost = defaultdict(dict)
snuke_cost = defaultdict(dict)


for u,v,a,b in uvab:
    u=u-1
    v=v-1
    jpy_cost[u][v] = a
    jpy_cost[v][u] =a
    snuke_cost[u][v]=b
    snuke_cost[v][u]=b


# Dijktra's shortest path algorithm. Prints the path from source to target.


def dijkstra(adj, source):
    INF = MAX_VAL
    dist = [INF for x in range(n)]
    dist[source] = 0
    PQ = []
    heapq.heappush(PQ, [dist[source], source])

    while (PQ):
        u_dist,u_id = heapq.heappop(PQ)  # u is a tuple [u_dist, u_id]
        if u_dist == dist[u_id]:
            for v in adj[u_id]:
                w_uv = adj[u_id][v]
                if dist[u_id] + w_uv < dist[v]:
                    dist[v] = dist[u_id] + w_uv
                    heapq.heappush(PQ, [dist[v], v])
    return dist


jpy_dijk =  dijkstra(jpy_cost,s-1)
snuke_dijk = dijkstra(snuke_cost,t-1)
#
# print(s,t)
# print(jpy_dijk)
# print(snuke_dijk)
# print([jpy_dijk[i]+snuke_dijk[i] for i in range(n)])

#ord n
res = []
min_val = MAX_VAL
for i in reversed(range(n)):
    #都市  i で両替
    val = jpy_dijk[i]+ snuke_dijk[i]
    assert val < MAX_VAL
    min_val=min(min_val,val)
    res.append(min_val)
#ord n
for x in reversed(res):
    print(10**15-  x)