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https://leetcode.com/problems/daily-temperatures/discuss/1842807/Python-solution-using-namedtuple
class Solution: def dailyTemperatures(self, temperatures: List[int]) -> List[int]: temp_tuple = collections.namedtuple('Temp', ('temp', 'day')) ans = [0 for _ in range(len(temperatures))] stack = [temp_tuple(temperatures[0], 0)] for i, t in enumerate(temperatures): if i == 0: continue if t < stack[-1].temp: stack.append(temp_tuple(t, i)) else: while stack and stack[-1].temp < t: last = stack.pop() ans[last.day] = i - last.day # print(last.day, last.temp) stack.append(temp_tuple(t, i)) return ans
daily-temperatures
Python solution using namedtuple
mitani-reishi116
0
43
daily temperatures
739
0.666
Medium
12,100
https://leetcode.com/problems/daily-temperatures/discuss/1635721/Easy-Python-Solution-using-Stack-O(N)
class Solution: def dailyTemperatures(self, temperatures: List[int]) -> List[int]: n = len(temperatures) store = {} stack = [] result = [0]*n stack.append(0) for i in range(1,n): if temperatures[i]>temperatures[stack[-1]]: while len(stack)>0 and temperatures[i]>temperatures[stack[-1]]: popped = stack.pop() result[popped] = i - popped stack.append(i) else: stack.append(i) return result
daily-temperatures
Easy Python Solution using Stack O(N)
RG97
0
88
daily temperatures
739
0.666
Medium
12,101
https://leetcode.com/problems/daily-temperatures/discuss/1620977/Stack-Easy-Understanding-Python-Beats-63.65-of-python3-submissions
class Solution: def dailyTemperatures(self, temperatures: List[int]) -> List[int]: stack = [] n = len(temperatures) output = [None] * n for i in range(n-1,-1,-1): while stack and temperatures[stack[-1]] <= temperatures[i]: stack.pop() output[i] = stack[-1] - i if stack else 0 stack.append(i) return output
daily-temperatures
Stack, Easy Understanding, Python, Beats 63.65 % of python3 submissions
jasonguan0107
0
123
daily temperatures
739
0.666
Medium
12,102
https://leetcode.com/problems/daily-temperatures/discuss/1594896/Monotonic-Stack
class Solution: def dailyTemperatures(self, temperatures: List[int]) -> List[int]: stack = [] #monotonous stack n = len(temperatures) ans = [0]*n for i in range(n-1, -1, -1): while stack!=[] and temperatures[i]>=stack[-1][0]: stack.pop(-1) if stack==[]: ans[i] = 0 else: ans[i] = stack[-1][1]-i stack.append((temperatures[i], i)) #each entry is a value-index pair return ans
daily-temperatures
Monotonic Stack
steven0821
0
171
daily temperatures
739
0.666
Medium
12,103
https://leetcode.com/problems/daily-temperatures/discuss/1576122/Python-stack-solution-faster-than-79
class Solution: def dailyTemperatures(self, temperatures: List[int]) -> List[int]: stack = [] res = [0] * len(temperatures) for i, temp in enumerate(temperatures): while stack and temp > stack[-1][0]: res[stack[-1][1]] = i - stack[-1][1] stack.pop() stack.append((temp, i)) return res
daily-temperatures
Python stack solution faster than 79%
dereky4
0
99
daily temperatures
739
0.666
Medium
12,104
https://leetcode.com/problems/daily-temperatures/discuss/1574768/ez-python-stack-solution
class Solution: def dailyTemperatures(self, temperatures: List[int]) -> List[int]: stack = [] output_rev = [] day = len(temperatures) - 1 for temp in temperatures[::-1]: if not stack: output_rev.append(0) stack.append([temp,day]) else: while stack and temp >= stack[-1][0]: stack.pop() if stack: output_rev.append(stack[-1][1] - day) else: output_rev.append(0) stack.append([temp,day]) day -= 1 return output_rev[::-1]
daily-temperatures
ez python stack solution
yingziqing123
0
62
daily temperatures
739
0.666
Medium
12,105
https://leetcode.com/problems/daily-temperatures/discuss/1517688/Python-Simple-Stack-Solution-with-Explanation
class Solution: def dailyTemperatures(self, temperatures: List[int]) -> List[int]: n, stack = len(temperatures), [] res = [0] * n for i in reversed(range(n)): while stack and temperatures[stack[-1]] <= temperatures[i]: stack.pop() if stack: res[i] = stack[-1] - i stack.append(i) return res
daily-temperatures
[Python] Simple Stack Solution with Explanation
Saksham003
0
162
daily temperatures
739
0.666
Medium
12,106
https://leetcode.com/problems/daily-temperatures/discuss/1462642/Simply-monotonic-stack-in-Python
class Solution: def dailyTemperatures(self, temperatures: List[int]) -> List[int]: n, ms = len(temperatures), [0] r = [0] * n for i in range(1, n): while ms and temperatures[ms[-1]] < temperatures[i]: r[ms.pop()] = i - ms[-1] ms += i, return r
daily-temperatures
Simply monotonic stack in Python
mousun224
0
134
daily temperatures
739
0.666
Medium
12,107
https://leetcode.com/problems/daily-temperatures/discuss/1447283/Simple-Python-O(n)-monotonic-stack-solution
class Solution: def dailyTemperatures(self, temperatures: List[int]) -> List[int]: ret = [0]*len(temperatures) mono_stack = [] for i, t in enumerate(temperatures): while mono_stack and mono_stack[-1][0] < t: _, prev_i = mono_stack.pop() ret[prev_i] = i-prev_i mono_stack.append((t, i)) return ret
daily-temperatures
Simple Python O(n) monotonic stack solution
Charlesl0129
0
146
daily temperatures
739
0.666
Medium
12,108
https://leetcode.com/problems/daily-temperatures/discuss/1314388/Python3-solution-using-stack
class Solution: def dailyTemperatures(self, temperatures: List[int]) -> List[int]: ans = [0]*len(temperatures) st = [] for i,j in enumerate(temperatures): while st and j > st[-1][0]: x,y = st.pop() ans[y] = i - y st.append((j,i)) return ans
daily-temperatures
Python3 solution using stack
EklavyaJoshi
0
157
daily temperatures
739
0.666
Medium
12,109
https://leetcode.com/problems/daily-temperatures/discuss/761486/Python-or-Need-Suggestions-to-improve-complexity
class Solution: def dailyTemperatures(self, T: List[int]) -> List[int]: start = first = 0 res = [0]*len(T) while start<len(T)-1: first+=1 if T[first]>T[start]: res[start]=(first-start) start+=1 first = start if first==len(T)-1: start+=1 first = start return res
daily-temperatures
[Python] | Need Suggestions to improve complexity??
rachitsxn292
0
155
daily temperatures
739
0.666
Medium
12,110
https://leetcode.com/problems/daily-temperatures/discuss/343443/Python-3-self-explanatory-solution
class Solution: def dailyTemperatures(self, T: List[int]) -> List[int]: l=len(T) res=[0]*l stack=[(T[0],0)] i=1 while stack and i<l: while stack and T[i]>stack[-1][0]: res[stack[-1][1]]=i-stack[-1][1] stack.pop() stack.append((T[i],i)) i+=1 return res
daily-temperatures
Python 3 self explanatory solution
ketan35
0
439
daily temperatures
739
0.666
Medium
12,111
https://leetcode.com/problems/daily-temperatures/discuss/1435642/Python-Clean
class Solution: def dailyTemperatures(self, temperatures: List[int]) -> List[int]: N = len(temperatures) stack, answer = [], [0 for _ in range(N)] for index, value in enumerate(temperatures): while stack and stack[-1][1] < value: i = stack.pop()[0] answer[i] = index-i stack.append((index, value)) return answer
daily-temperatures
[Python] Clean
111989
-1
175
daily temperatures
739
0.666
Medium
12,112
https://leetcode.com/problems/delete-and-earn/discuss/916859/Python3-top-down-dp
class Solution: def deleteAndEarn(self, nums: List[int]) -> int: mp = {} for x in nums: mp[x] = x + mp.get(x, 0) @lru_cache(None) def fn(i): """Return maximum points one can earn from nums[i:].""" if i >= len(nums): return 0 if nums[i] + 1 not in mp: return mp[nums[i]] + fn(i+1) return max(mp[nums[i]] + fn(i+2), fn(i+1)) nums = sorted(set(nums)) return fn(0)
delete-and-earn
[Python3] top-down dp
ye15
7
273
delete and earn
740
0.573
Medium
12,113
https://leetcode.com/problems/delete-and-earn/discuss/916859/Python3-top-down-dp
class Solution: def deleteAndEarn(self, nums: List[int]) -> int: freq = Counter(nums) prev = -inf f0 = f1 = 0 for x in sorted(freq): if prev + 1 == x: f0, f1 = max(f0, f1), f0 + x*freq[x] else: f0, f1 = max(f0, f1), max(f0, f1) + x*freq[x] prev = x return max(f0, f1)
delete-and-earn
[Python3] top-down dp
ye15
7
273
delete and earn
740
0.573
Medium
12,114
https://leetcode.com/problems/delete-and-earn/discuss/2438160/Python-Solution-O(n)-similar-to-House-Robber-Faster-than-89.94-solutions
class Solution: def deleteAndEarn(self, nums: List[int]) -> int: # createed a dic to store value of a number i.e the dic[n] = n*(number of times it occurs) dic = defaultdict(int) for n in nums: dic[n] += n # made a list of unique num in nums, OR -> made a list so we can use it as House Robber newList = list(set(nums)) newList.sort() # point list contains all the indexes in newList where the difference between any two consicutive num is greater than 1. # newList = [2,3,4,6,7,8,11,12] then -> point = [3,6] + ( also append len(newList)) to process the last 11,12 as we did in House Robber. # points = [3,6,8] point = [] N = len(newList) for i in range(1,N): if newList[i] - newList[i-1] > 1: point.append(i) if len(point)==0 or point[-1] != N: point.append(N) # similar to House Robber. We try to get maximum for each sub array. # [2,3,4] , [6,7,8] , [11,12] ( prev = 0 ) earning,prev = 0,0 # earning = 0, prev = 0 ( index starting) for indx in point: # points = # points = [3,6,8].. for each index we want to calculate max contiribution of it subarray... [0,3], [3,6], [6,8] dp = [-10**20,-10**20] for i,n in enumerate(newList[prev:indx]): # lists -> [2,3,4] , [6,7,8] , [11,12] if i == 0: # BASE CONDITION dp[0] = max(dp[0], dic[n]) continue if i == 1: # BASE CONDITION dp[1] = max(dp[1], dic[n]) continue # UPDATING VALUES temp = dp[1] dp[1] = max(dic[n], dp[0]+dic[n],dp[1]) dp[0] = max(temp,dp[0]) earning += max(dp) # updating earings prev = indx #prev updated to 3,6,8 after subarrays return earning # FINAL ANSWER
delete-and-earn
Python Solution O(n) similar to House Robber Faster than 89.94% solutions
notxkaran
4
393
delete and earn
740
0.573
Medium
12,115
https://leetcode.com/problems/delete-and-earn/discuss/2438160/Python-Solution-O(n)-similar-to-House-Robber-Faster-than-89.94-solutions
class Solution: def deleteAndEarn(self, nums: List[int]) -> int: # c dic = defaultdict(int) for n in nums: dic[n] += n newList = list(set(nums)) newList.sort() point = [] N = len(newList) for i in range(1,N): if newList[i] - newList[i-1] > 1: point.append(i) if len(point)==0 or point[-1] != N: point.append(N) earning,prev = 0,0 for indx in point: dp = [-10**20,-10**20] for i,n in enumerate(newList[prev:indx]): if i == 0: dp[0] = max(dp[0], dic[n]) continue if i == 1: dp[1] = max(dp[1], dic[n]) continue temp = dp[1] dp[1] = max(dic[n], dp[0]+dic[n],dp[1]) dp[0] = max(temp,dp[0]) earning += max(dp) prev = indx return earning
delete-and-earn
Python Solution O(n) similar to House Robber Faster than 89.94% solutions
notxkaran
4
393
delete and earn
740
0.573
Medium
12,116
https://leetcode.com/problems/delete-and-earn/discuss/1820848/Python-3-or-DP-Greedy-O(NLogN)-House-Robber-or-Explanation
class Solution: def deleteAndEarn(self, nums: List[int]) -> int: c = collections.Counter(nums) keys = sorted(c.keys()) prev = 0 ans = cur = c[keys[0]] * keys[0] for i in range(1, len(keys)): if keys[i] == keys[i-1] + 1: prev, cur = cur, max(cur, prev + keys[i] * c[keys[i]]) else: prev, cur = cur, cur + keys[i] * c[keys[i]] ans = max(ans, cur) return ans
delete-and-earn
Python 3 | DP, Greedy, O(NLogN), House Robber | Explanation
idontknoooo
4
522
delete and earn
740
0.573
Medium
12,117
https://leetcode.com/problems/delete-and-earn/discuss/1666434/Delete-and-Earn-greater-House-Robber-variation-DP-bottom-up
class Solution: def deleteAndEarn(self, nums: List[int]) -> int: gold_houses = [0] * max(nums) for num in nums: gold_houses[num-1] += num # below is the House Robber question, with gold_houses as the input # recurrence relation: max_points(i) = max(nums[i] + max_points(i-2), max_points(i-1)) max_gold_i_minus_1, max_gold_i_minus_2 = 0, 0 for gold in gold_houses: max_gold_i = max(gold + max_gold_i_minus_2, max_gold_i_minus_1) max_gold_i_minus_1, max_gold_i_minus_2 = max_gold_i, max_gold_i_minus_1 return max_gold_i
delete-and-earn
Delete and Earn --> House Robber variation; DP bottom-up
NinjaBlack
3
155
delete and earn
740
0.573
Medium
12,118
https://leetcode.com/problems/delete-and-earn/discuss/1666434/Delete-and-Earn-greater-House-Robber-variation-DP-bottom-up
class Solution: def deleteAndEarn(self, nums: List[int]) -> int: gold = [0] * (max(nums)+1) for num in nums: gold[num] += num g0, g1 = 0, 0 for i in range(1, len(gold)): g1, g0 = max(gold[i] + g0, g1), g1 return g1
delete-and-earn
Delete and Earn --> House Robber variation; DP bottom-up
NinjaBlack
3
155
delete and earn
740
0.573
Medium
12,119
https://leetcode.com/problems/delete-and-earn/discuss/1541098/Python-Easy-House-Robber-variation
class Solution: def deleteAndEarn(self, nums: List[int]) -> int: d = [0]*(max(nums) + 1) for i in nums: d[i] += i p2, p1 = 0, 0 for i in range(len(d)): p1, p2 = max(d[i]+p2, p1), p1 return max(p1, p2)
delete-and-earn
[Python] Easy , House Robber variation
lokeshsenthilkumar
3
273
delete and earn
740
0.573
Medium
12,120
https://leetcode.com/problems/delete-and-earn/discuss/1189565/Well-Explained-(with-example)-oror-Python-oror-96-faster-oror-DP-oror-O(nlogn)
class Solution: def deleteAndEarn(self, nums: List[int]) -> int: m=max(nums) dic=Counter(nums) dp=[0]*(m+1) for k in dic: dp[k]=k*dic[k] for i in range(2,m+1): dp[i]=max(dp[i-1], dp[i-2]+ dp[i]) return dp[-1]
delete-and-earn
Well-Explained (with example) || Python || 96% faster || DP || O(nlogn)
abhi9Rai
3
263
delete and earn
740
0.573
Medium
12,121
https://leetcode.com/problems/delete-and-earn/discuss/2394588/python-oror-dp-oror-top-down-oror-recursion-oror-memoization
class Solution: def deleteAndEarn(self, nums: List[int]) -> int: count = Counter(nums) m = max(nums) memo = {} def choose(num): if num > m: return 0 if num not in count: count[num] = 0 if num in memo: return memo[num] memo[num] = max(choose(num + 1), num * count[num] + choose(num + 2)) return memo[num] return choose(1) # time and space complexity # n = max(nums) # time: O(n) # space: O(n)
delete-and-earn
python || dp || top down || recursion || memoization
Yared_betsega
2
134
delete and earn
740
0.573
Medium
12,122
https://leetcode.com/problems/delete-and-earn/discuss/1475424/PyPy3-Solution-using-House-Robber-Part-1-Logic-w-comments
class Solution: def deleteAndEarn(self, nums: List[int]) -> int: # Frequency of numbers freq = [0] * (max(nums)+1) for num in nums: freq[num] += num # House Robber Problem from here on # apply house robber logic on freq array # Init f = len(freq) # Base Case if f == 0: return 0 # Base Case if f <= 2: return max(freq) # Init t = dict() t[0] = freq[0] t[1] = max(freq[0], freq[1]) # DP: either you can take this element # and add it to the subproblem i-2 steps # before it, or you take subproblem i-1 steps # before it for i in range(2,f): t[i] = max(t[i-1], freq[i] + t[i-2]) return t[f-1]
delete-and-earn
[Py/Py3] Solution using House Robber Part 1 Logic w/ comments
ssshukla26
2
219
delete and earn
740
0.573
Medium
12,123
https://leetcode.com/problems/delete-and-earn/discuss/1323959/better-than-99.95
class Solution: def deleteAndEarn(self, nums: List[int]) -> int: dict=Counter(nums) m=max(nums) dp=[0]*(m+1) for i in range(1,m+1): if i in dict: if i==1: dp[i]=dict[i]*i else: dp[i]=max(dp[i-1],dp[i-2]+i*dict[i]) else: dp[i]=dp[i-1] return dp[-1]
delete-and-earn
better than 99.95%
pramodh18
2
204
delete and earn
740
0.573
Medium
12,124
https://leetcode.com/problems/delete-and-earn/discuss/2480368/Python-DP-Solution-with-DP
class Solution: def deleteAndEarn(self, nums: List[int]) -> int: points = defaultdict(lambda:0) max_number = max(nums) points = Counter(nums) max_points = [0] * (max_number + 2) for num in range(len(max_points)): max_points[num] = max(max_points[num - 1], max_points[num - 2] + points[num] * num) return max_points[max_number]
delete-and-earn
Python DP Solution with DP
Xiang-Pan
1
114
delete and earn
740
0.573
Medium
12,125
https://leetcode.com/problems/delete-and-earn/discuss/2104026/Python3-or-DP-or-Easy-Understand
class Solution: def deleteAndEarn(self, nums: List[int]) -> int: counter = Counter(nums) max_n = max(nums) dp = [0] * (max_n + 1) dp[1] = counter[1] for i in range(2, max_n + 1): dp[i] = max(dp[i-1], dp[i-2] + counter[i] * i) return dp[-1]
delete-and-earn
Python3 | DP | Easy-Understand
Yilin_Bai
1
92
delete and earn
740
0.573
Medium
12,126
https://leetcode.com/problems/delete-and-earn/discuss/1822613/Simple-Python3-Solution
class Solution: def deleteAndEarn(self, nums: List[int]) -> int: maps = Counter(nums) nums = sorted(list(set(nums))) prev = prevprev = 0 for i,num in enumerate(nums): currPoint = num*maps[num] tmp=prev if i>0 and num==nums[i-1]+1: prev=max(prev,prevprev+currPoint) else: prev+=currPoint prevprev=tmp return prev
delete-and-earn
Simple Python3 Solution
user6774u
1
67
delete and earn
740
0.573
Medium
12,127
https://leetcode.com/problems/delete-and-earn/discuss/1821143/Super-Easy-Super-Optimized
class Solution: def deleteAndEarn(self, nums: List[int]) -> int: dict1=dict() dp=[0]*(max(nums)+1) for i in nums: dict1[i]=dict1.get(i,0)+i for i in range(1,max(nums)+1): dp[i]=max(dp[i-1],dict1.get(i,0)+dp[i-2]) return dp[-1]
delete-and-earn
Super Easy, Super Optimized
vedank98
1
77
delete and earn
740
0.573
Medium
12,128
https://leetcode.com/problems/delete-and-earn/discuss/1820399/DP-oror-House-Robber-Variation
class Solution: def deleteAndEarn(self, nums: List[int]) -> int: points = [0] * (max(nums)+1) for num in nums: points[num] += num previous = points[0] current = points[1] for idx in range(2,len(points)): current, previous = max(current, previous + points[idx]), current return current O(N) space and time N : max element in array.
delete-and-earn
DP || House Robber Variation
beginne__r
1
34
delete and earn
740
0.573
Medium
12,129
https://leetcode.com/problems/delete-and-earn/discuss/1764708/Java-Python3-Simple-DP-Solution-(Top-Down-and-Bottom-Up)
class Solution: def deleteAndEarn(self, nums: List[int]) -> int: nums_counter = Counter(nums) prev = -1 avoid = using = 0 for i in sorted(nums_counter): if i - 1 != prev: avoid, using = max(avoid, using), i * \ nums_counter[i] + max(avoid, using) else: avoid, using = max(avoid, using), i*nums_counter[i]+avoid prev = i return max(avoid, using)
delete-and-earn
✅ [Java / Python3] Simple DP Solution (Top-Down & Bottom-Up)
JawadNoor
1
153
delete and earn
740
0.573
Medium
12,130
https://leetcode.com/problems/delete-and-earn/discuss/1764708/Java-Python3-Simple-DP-Solution-(Top-Down-and-Bottom-Up)
class Solution: def deleteAndEarn(self, nums: List[int]) -> int: memo = {} counter = Counter(nums) sorted_nums = sorted(counter) def dp(i: int) -> int: if i == 0: return sorted_nums[0]*counter[sorted_nums[0]] if i == 1: if sorted_nums[1] == sorted_nums[0]+1: return max(sorted_nums[0]*counter[sorted_nums[0]], sorted_nums[1]*counter[sorted_nums[1]]) else: return sorted_nums[0]*counter[sorted_nums[0]]+sorted_nums[1]*counter[sorted_nums[1]] if i not in memo: if sorted_nums[i-1] == sorted_nums[i]-1: memo[i] = max( sorted_nums[i]*counter[sorted_nums[i]]+dp(i-2), dp(i-1)) else: memo[i] = sorted_nums[i] * \ counter[sorted_nums[i]]+dp(i-1) return memo[i] return dp(len(sorted_nums)-1)
delete-and-earn
✅ [Java / Python3] Simple DP Solution (Top-Down & Bottom-Up)
JawadNoor
1
153
delete and earn
740
0.573
Medium
12,131
https://leetcode.com/problems/delete-and-earn/discuss/1716577/Python-4-Approaches-or-Brute-Force-to-Optimal-or-Time-and-Space-Complexity
class Solution: def deleteAndEarn(self, nums: List[int]) -> int: def helper(ind,nums): if ind==0: return nums[0] if ind<0: return 0 #TAKE take=nums[ind]+helper(ind-2,nums) #NOT TAKE not_take=helper(ind-1,nums) return max(take,not_take) def delete_and_earn(nums): maxi=max(nums) count=[0]*(maxi+1) for num in nums: count[num]+=num n=len(count) return helper(n-1,count) return delete_and_earn(nums)
delete-and-earn
Python 4 Approaches | Brute Force to Optimal | Time and Space Complexity
aryanagrawal2310
1
283
delete and earn
740
0.573
Medium
12,132
https://leetcode.com/problems/delete-and-earn/discuss/1716577/Python-4-Approaches-or-Brute-Force-to-Optimal-or-Time-and-Space-Complexity
class Solution: def deleteAndEarn(self, nums: List[int]) -> int: def helper(ind,nums,dp): if ind==0: return nums[0] if ind<0: return 0 if dp[ind]!=-1: return dp[ind] #TAKE take=nums[ind]+helper(ind-2,nums,dp) #NOT TAKE not_take=helper(ind-1,nums,dp) dp[ind]=max(take,not_take) return dp[ind] def delete_and_earn(nums): maxi=max(nums) count=[0]*(maxi+1) for num in nums: count[num]+=num n=len(count) dp=[-1]*n return helper(n-1,count,dp) return delete_and_earn(nums)
delete-and-earn
Python 4 Approaches | Brute Force to Optimal | Time and Space Complexity
aryanagrawal2310
1
283
delete and earn
740
0.573
Medium
12,133
https://leetcode.com/problems/delete-and-earn/discuss/1716577/Python-4-Approaches-or-Brute-Force-to-Optimal-or-Time-and-Space-Complexity
class Solution: def deleteAndEarn(self, nums: List[int]) -> int: def helper(arr): n=len(arr) dp=[-1]*(n) dp[0]=arr[0] for i in range(1,n): first=dp[i-1] second=arr[i] if i>1: second=arr[i]+dp[i-2] dp[i]=max(first,second) return dp[n-1] def delete_and_earn(nums): maxi=max(nums) count=[0]*(maxi+1) for num in nums: count[num]+=num return helper(count) return delete_and_earn(nums)
delete-and-earn
Python 4 Approaches | Brute Force to Optimal | Time and Space Complexity
aryanagrawal2310
1
283
delete and earn
740
0.573
Medium
12,134
https://leetcode.com/problems/delete-and-earn/discuss/1716577/Python-4-Approaches-or-Brute-Force-to-Optimal-or-Time-and-Space-Complexity
class Solution: def deleteAndEarn(self, nums: List[int]) -> int: def helper(arr): n=len(arr) prev2=0 prev=arr[0] for i in range(1,n): ans=max(prev,prev2+arr[i]) prev2=prev prev=ans return prev def delete_and_earn(nums): maxi=max(nums) count=[0]*(maxi+1) for num in nums: count[num]+=num return helper(count) return delete_and_earn(nums)
delete-and-earn
Python 4 Approaches | Brute Force to Optimal | Time and Space Complexity
aryanagrawal2310
1
283
delete and earn
740
0.573
Medium
12,135
https://leetcode.com/problems/delete-and-earn/discuss/1628981/Python3-oror-Dynamic-Programming-oror-O(nlogn)-time-complexity
class Solution: def deleteAndEarn(self, nums: List[int]) -> int: if len(nums) == 1: return nums[0] occurences = dict() for i in nums: if i in occurences: occurences[i] += 1 else: occurences[i] = 1 #remove repeating elements and sort nums = list(set(nums)) nums.sort() first = nums[0] * occurences[nums[0]] if nums[1] - nums[0] == 1: #we can't include the previous element second = max(first,nums[1] * occurences[nums[1]]) else: second = first + nums[1] * occurences[nums[1]] dp = [0] * len(nums) dp[0] = first dp[1] = second for i in range(2,len(dp)): if nums[i] - nums[i-1] == 1: # we can't include nums[i-1], we'll include nums[i] dp[i] = max(dp[i-2] + nums[i] * occurences[nums[i]],dp[i-1]) else: dp[i] = dp[i-1]+ nums[i] * occurences[nums[i]] return dp[-1]
delete-and-earn
Python3 || Dynamic Programming || O(nlogn) time complexity
s_m_d_29
1
239
delete and earn
740
0.573
Medium
12,136
https://leetcode.com/problems/delete-and-earn/discuss/1562760/Python3-solution-97.44-faster
class Solution: def deleteAndEarn(self, nums: List[int]) -> int: maximum: int = max(nums) count: List[int] = [0] * (maximum + 1) for num in nums: count[num] += num previous: int = 0 current: int = 0 for i in range(0, len(count)): previous, current = current, max(previous + count[i], current) return current
delete-and-earn
Python3 solution 97.44% faster
sirenescx
1
308
delete and earn
740
0.573
Medium
12,137
https://leetcode.com/problems/delete-and-earn/discuss/1512397/Any-optimisation-suggestions
class Solution: def deleteAndEarn(self, nums: List[int]) -> int: if len(set(nums)) == 1: return sum(nums) count = dict(collections.Counter(sorted(nums))) num, freq = [], [] for i, j in count.items(): num.append(i) freq.append(j) dp = [0]*len(num) dp[0] = num[0]*freq[0] if num[1] - 1 in num: dp[1] = max(dp[0], num[1]*freq[1]) else: dp[1] = dp[0] + (num[1]*freq[1]) for i in range(2, len(num)): if num[i]-1 in num: dp[i] = max(dp[i-1], (num[i]*freq[i])+dp[i-2]) else: dp[i] = dp[i-1] + (num[i]*freq[i]) return dp[-1]
delete-and-earn
Any optimisation suggestions ??
siddp6
1
422
delete and earn
740
0.573
Medium
12,138
https://leetcode.com/problems/delete-and-earn/discuss/1467110/python-O(n)-time-O(n)-space-solution-no-sorting
class Solution: def deleteAndEarn(self, nums: List[int]) -> int: count = defaultdict(int) for num in nums: count[num] += 1 dp = [0 for _ in range(max(nums) + 1)] for k in count: dp[k] = k*count[k] def rob(nums: List[int]) -> int: n = len(nums) if n == 1: return nums[0] elif n ==2: return max(nums[0], nums[1]) elif n== 3: return max(nums[0]+nums[2], nums[1]) a = nums[0] b = nums[1] c = nums[0] + nums[2] maxv = max(a, b, c) for i in range(3, n): d = nums[i] + max(a, b) maxv = max(maxv, d) a = b b = c c = d return maxv return rob(dp)
delete-and-earn
python O(n) time / O(n) space solution, no sorting
byuns9334
1
99
delete and earn
740
0.573
Medium
12,139
https://leetcode.com/problems/delete-and-earn/discuss/2822124/Python-Like-House-Robber-or-Track-Max-By-Adding-Last-OR-Max-of-Skipping-Last-or-Curr
class Solution: def deleteAndEarn(self, nums: List[int]) -> int: # We get a hash map of counts and sort the values counts = {} for num in nums: counts[num] = counts.get(num, 0) + 1 points = sorted(counts.keys()) ''' Rest is similar to House Robber series: https://leetcode.com/problems/house-robber/discuss/2821870/Python-Current-%2B-LastLast-OR-Last.-Rinse-and-Repeat-) At every position, we track the max earned up to that point, where: We start the earnings with current number * frequency (in counts map) Then if the previous number is not 1 less than current, add it Otherwise, take the maximum of current + last-last (skipping last) or just the last (skipping current and taking the max up to last) ''' last_last, last = 0, 0 for i in range(len(points)): earned = (points[i] * counts[points[i]]) if i > 0 and points[i] == points[i-1] + 1: earned = max(earned + last_last, last) else: earned += last last_last, last = last, earned return last
delete-and-earn
[Python] Like House Robber | Track Max By Adding Last OR Max of Skipping Last or Curr
graceiscoding
0
2
delete and earn
740
0.573
Medium
12,140
https://leetcode.com/problems/delete-and-earn/discuss/2711752/Python-DP-solution
class Solution: def deleteAndEarn(self, arr: List[int]) -> int: arr = sorted(arr)[::-1] uniq = [arr[0]] for i in range(1, len(arr)): if arr[i] != arr[i - 1]: uniq.append(arr[i]) hm = dict(Counter(arr)) d = [-1] * len(uniq) def dp(i): if i >= len(uniq): return 0 if d[i] != -1: return d[i] if uniq[i] - 1 not in hm: d[i] = hm[uniq[i]] * uniq[i] + dp(i + 1) else: d[i] = max(dp(i + 1), hm[uniq[i]] * uniq[i] + dp(i + 2)) return d[i] dp(0) return d[0]
delete-and-earn
Python DP solution
JSTM2022
0
5
delete and earn
740
0.573
Medium
12,141
https://leetcode.com/problems/delete-and-earn/discuss/2702659/Easy-to-understand-Python-DP-solution-based-on-House-Robber
class Solution: def deleteAndEarn(self, nums: List[int]) -> int: count = collections.Counter(nums) dp = [0]*(max(nums)+1) #max len is 10001 #base cases dp[0] = 0*count[0] dp[1] = 1*count[1] for i in range(2, len(dp)): #recurrence relation dp[i] = max(i*count[i] + dp[i-2], dp[i-1]) return dp[-1]
delete-and-earn
Easy to understand Python DP solution based on House Robber
sc1233
0
9
delete and earn
740
0.573
Medium
12,142
https://leetcode.com/problems/delete-and-earn/discuss/2686768/python-working-solution-or-dp-or-memoization
class Solution: def deleteAndEarn(self, nums: List[int]) -> int: d= {} for i in nums: d[i] = 1 + d.get(i,0) l = list(d.keys()) l.sort() dp = {} def dfs(i,s): if i>=len(l): return 0 if l[i] in s: return dfs(i+1,s) if i in dp: return dp[i] s.add(l[i]+1) k = (l[i] * d[l[i]]) + dfs(i+1,s) s.remove(l[i]+1) dp[i] = max(k , dfs(i+1,s)) return dp[i] return dfs(0,set())
delete-and-earn
python working solution | dp | memoization
Sayyad-Abdul-Latif
0
19
delete and earn
740
0.573
Medium
12,143
https://leetcode.com/problems/delete-and-earn/discuss/2681690/Python-oror-Memoization-Solution-oror-93.77-Faster
class Solution: def deleteAndEarn(self, nums: List[int]) -> int: n = len(nums) m = max(nums) # arr is used to store count of each element in nums with respect to index arr = [0 for i in range(m+1)] dp = [-1 for i in range(m+1)] for i in range(len(nums)): arr[nums[i]] += 1 # Memoization Solution def helper(index): nonlocal m if index > m: return 0 if dp[index] != -1: return dp[index] pick = 0 if arr[index] > 0: pick = arr[index] * index + helper(index+2) notpick = helper(index+1) dp[index] = max(pick, notpick) return max(pick, notpick) # ans1 indicates if we start from 1st element ans1 = helper(1) # ans2 indicates if we start from 2nd element ans2 = helper(2) return max(ans1, ans2)
delete-and-earn
Python || Memoization Solution || 93.77% Faster
shreya_pattewar
0
9
delete and earn
740
0.573
Medium
12,144
https://leetcode.com/problems/delete-and-earn/discuss/2665074/Python-or-O(n)-solution-with-comments
class Solution: def deleteAndEarn(self, nums: List[int]) -> int: # First step is simple count sort stat = [0]*(10**4 + 1) for num in nums: stat[num] += 1 # For second step we use dynamic programming approach # We can either choose previous value or pre-previous value plus value from count array dp = [0]*(10**4 + 1) dp[1] = stat[1] for i in range(2, 10**4 + 1): dp[i] = max(dp[i - 1], dp[i - 2] + stat[i]*i) return dp[-1]
delete-and-earn
Python | O(n) solution with comments
LordVader1
0
22
delete and earn
740
0.573
Medium
12,145
https://leetcode.com/problems/delete-and-earn/discuss/2458019/python3-easy-solution-(change-to-leetcode-198)
class Solution: def deleteAndEarn(self, nums: List[int]) -> int: house=[] temp=0 nums.sort() for i in range(len(nums)): #create house list, nums[i] as index of house if i!=len(nums)-1: if nums[i]==nums[i+1]: temp+=nums[i] else: temp+=nums[i] house.append(temp) temp=0 for j in range(nums[i+1]-nums[i]-1): house.append(0) else: temp+=nums[i] house.append(temp) @cache def dp(n :int) -> int: if n<0: return 0 return max(house[n]+dp(n-2),dp(n-1)) return dp(len(house)-1)
delete-and-earn
python3 easy solution (change to leetcode 198)
kyoko0810
0
94
delete and earn
740
0.573
Medium
12,146
https://leetcode.com/problems/delete-and-earn/discuss/2413530/Python3-or-Can't-Figure-Out-Bug-in-My-Bottom-UP-DP-Code
class Solution: def deleteAndEarn(self, nums: List[int]) -> int: #if you think about this problem recursively, basically this problem exhibits both #optimal substructure property as well as overlapping subproblems! #For example, let's take first test case! #nums = [3, 4, 2] #Draw out rec. tree! # [3, 4, 2] #. /. |. \ #. 3. 4. 2 #. /. |. \ #. [] [2] [4] #. | \ #. 2 4 #. | \ #. [] [] #basically, every edge represents the number I choose to delete to get points! #You can see that the remaining elements in the array compose each and every subproblem! #If you notice, for any given subproblem, if you know the maximized points you can get #from deleting each and every distinct integer that appears in that given subproblem array, #then, you can take each of those subproblem results' and add the edge value and get the max across! #this will be the answer -> Solving subproblems optimally leads to optimal overall solution!(Optimal #substructure property) #Clearly, there is possibility of subarrays of original array of numbers being considered #multiple times across different places in rec. tree! -> Possibility of overlapping subproblems! #I'll try solving bottom-up this time! #Here, the state paramter is only going to be index position i! #Since our input array is allowed to have duplicates, we will simply the array we are #traversing by removing any duplicates and have frequency count info stored in hashmap! hashmap = {} for num in nums: if num not in hashmap: hashmap[num] = 1 else: hashmap[num] += 1 distinct = list(set(nums)) #dp table: store the maximized points I can get for elements up to index i if I choose #to delete index i for points! if(len(distinct) == 1): return distinct[0] * hashmap[distinct[0]] n = len(distinct) dp = [0] * n #we have to sort the array of distinct numbers so that we can check for any index i, if the previous element #is 1 less in value -> If that's the case, we just delete it and not take its value into account for points! distinct.sort() #add the dp base case dp[0] = distinct[0] * hashmap[distinct[0]] dp[1] = (distinct[1] * hashmap[distinct[1]]) + dp[0] if distinct[1] - 1 != distinct[0] else distinct[1] * hashmap[distinct[1]] #iterate through subproblems or state paramter i! for i in range(2, n): #if the previous number is not equal to nums[i] - 1, then max. points we can get for #all elements up to index i is going to be maximized points up to index i-1, if we delete #nums[i-1] + nums[i] cur = distinct[i] cur_freq = hashmap[cur] dp[i] = (cur * cur_freq) + dp[i-1] if distinct[i-1] != cur - 1 else (cur * cur_freq + dp[i-2]) return dp[n-1]
delete-and-earn
Python3 | Can't Figure Out Bug in My Bottom-UP DP Code
JOON1234
0
15
delete and earn
740
0.573
Medium
12,147
https://leetcode.com/problems/delete-and-earn/discuss/2413109/Python3-or-Question-on-Top-Down-Approach%3A-How-to-Memo-Array-Instances!
class Solution: def deleteAndEarn(self, nums: List[int]) -> int: #if you think about this problem recursively, basically this problem exhibits both #optimal substructure property as well as overlapping subproblems! #For example, let's take first test case! #nums = [3, 4, 2] #Draw out rec. tree! # [3, 4, 2] #. /. |. \ #. 3. 4. 2 #. /. |. \ #. [] [2] [4] #. | \ #. 2 4 #. | \ #. [] [] #basically, every edge represents the number I choose to delete to get points! #You can see that the remaining elements in the array compose each and every subproblem! #If you notice, for any given subproblem, if you know the maximized points you can get #from deleting each and every distinct integer that appears in that given subproblem array, #then, you can take each of those subproblem results' and add the edge value and get the max across! #this will be the answer -> Solving subproblems optimally leads to optimal overall solution!(Optimal #substructure property) #Clearly, there is possibility of subarrays of original array of numbers being considered multiple times #across different places in rec. tree! -> Possibility of overlapping subproblems! hashmap = {} for num in nums: if(num not in hashmap): hashmap[num] = 1 else: hashmap[num] += 1 def helper(arr, d): #Try implementing top down dp approach! #base case: array with just 1 element -> go delete that element and get the points! if(len(arr) == 1): return arr[0] #let s represent set of distinct numbers present in nums arr! s = set(arr) #for each and every number in set s, we consider all remaining elements as arr, recurse on #it and add the element in s we are currently iterating on, element we remove and get points #for! Take the max across all possible paths spanning from current subproblem dedicated to #arr! ans = 0 for e in s: copy = d.copy() #we delete element e so it appears 1 less in rem. elements! if(copy[e] == 1): copy.pop(e) else: copy[e] -= 1 #remove e+1 and e-1 numbers as keys from dictionary! if(e+1 in copy): #save original key value pair before removing it b/c we need it for next iteration! copy.pop(e + 1) if(e-1 in copy): copy.pop(e - 1) #once we have correct remaining numbers and their freq. count in dictionary d, #iterate through each key-value pair and put their elements in one overall arr #to recurse on! overall_arr = [] #copy dict should tell what are rem distinct numbers and their each freq. count! for k,v in copy.items(): overall_arr = overall_arr + [k for _ in range(v)] #pass along overall_arr, which is remaining numbers in rec. call along with #current state of copy! #update answer if the recursive call result + element e value we get as points #for removing exceeds current ans! ans = max(ans,helper(overall_arr, copy) + e) #restore the original state of dictionary before next iteration of for loop! return ans return helper(nums, hashmap)
delete-and-earn
Python3 | Question on Top-Down Approach: How to Memo Array Instances!
JOON1234
0
31
delete and earn
740
0.573
Medium
12,148
https://leetcode.com/problems/delete-and-earn/discuss/2305019/Python-DP-easy
class Solution: def deleteAndEarn(self, nums: List[int]) -> int: count = collections.Counter(nums) nums = sorted(set(nums)) n = len(count) dp = [0]*n dp[0] = nums[0]*count[nums[0]] print(nums) for i in range(1,n): if nums[i] -1 == nums[i-1]: dp[i] = max(nums[i]*count[nums[i]]+dp[i-2], dp[i-1]) else: dp[i] = nums[i]*count[nums[i]]+dp[i-1] return dp[-1]
delete-and-earn
Python DP easy
Abhi_009
0
79
delete and earn
740
0.573
Medium
12,149
https://leetcode.com/problems/delete-and-earn/discuss/1941502/Python3-oror-Bottom-Up-Solution
class Solution: def deleteAndEarn(self, nums: List[int]) -> int: max_val = max(nums) dp = [0] * ( max_val + 1 ) for i in nums : dp[i] += i for i in range(2,len(dp)): dp[i] = max(dp[i-1],dp[i] + dp[i-2]) return dp[max_val]
delete-and-earn
Python3 || Bottom Up Solution
subhamsubhasispatra
0
151
delete and earn
740
0.573
Medium
12,150
https://leetcode.com/problems/delete-and-earn/discuss/1821905/Python-easy-and-clean-solution-or-Explained
class Solution: def deleteAndEarn(self, nums: List[int]) -> int: dic, prev = defaultdict(int), -1 prevMax = leftMax = 0 # prevMax: maximum till the previous, leftMax: maximum just before the prevous for i in nums: dic[i] += 1 # counting the frequency get = lambda i: i * dic.get(i, 0) # I took this for better readability, it will return the product of the number and its frequency for i in sorted(dic): # traversing the sorted dictionary, sorting is used because smaller values must be processed first. temp = prevMax # prevMax value will change but we need that value to update the leftMax. if i - 1 == prev: prevMax = max(prevMax ,get(i) + leftMax) # important point: if i - 1 is equal to prev, it is obvious that prevMax was calculated with the help of i-1, and we can't add it, so we will add leftMax beacuse leftMax is not caculated with the help of i-1, then we calculate the maximum out of it. else: prevMax = get(i) + prevMax # if they are not equal, we have no issue in adding the prevMax. leftMax = temp # update the leftMax to temp prev = i # upadte the prev, so that we remember prevMax was calculated with this i return prevMax
delete-and-earn
✅ Python easy and clean solution | Explained
dhananjay79
0
70
delete and earn
740
0.573
Medium
12,151
https://leetcode.com/problems/delete-and-earn/discuss/1821397/Python3-Dynamic-Programming-Bottom-Up-Approach
class Solution: def deleteAndEarn(self, nums: List[int]) -> int: d=Counter(nums) N = len(d) temp = [[None]*2 for _ in range(N+1)] # Base case temp[0][0]=0 # j=0 --> Exclude temp[0][1]=0 # j=1 --> Include # Choice diagram # Traverse dict instead of array keys = list(d.keys()) keys.sort() for i in range(1,N+1): for j in range(2): if j==0: # If you wanna exclude take max(prev_include,prev_exclude) temp[i][j] = max(temp[i-1][0],temp[i-1][1]) if j==1: # If you wanna include if i==0: # Blind include(as it is first element) temp[i][j] = keys[i-1]*d[keys[i-1]] else: # check if curr_element is consecutive to prev_element if keys[i-1]==keys[i-2]+1: # If yes,consider prev_exclude + curr_element temp[i][j] = temp[i-1][0]+keys[i-1]*d[keys[i-1]] else: # Consider max(prev_include,prev_exclude)+curr_element temp[i][j] = max(temp[i-1][0],temp[i-1][1])+keys[i-1]*d[keys[i-1]] return max(temp[-1])
delete-and-earn
Python3 Dynamic Programming Bottom Up Approach
KiranRaghavendra
0
39
delete and earn
740
0.573
Medium
12,152
https://leetcode.com/problems/delete-and-earn/discuss/1820561/Python-Simple-Python-Solution-Using-Dynamic-Programming-and-Dictionary
class Solution: def deleteAndEarn(self, nums: List[int]) -> int: count_frequency = defaultdict(int) max_number = max(nums) for num in nums: count_frequency[num] = count_frequency[num] + num dp = [0]*(max_number + 1) dp[1] = count_frequency[1] for j in range(2,len(dp)): dp[j] = max(dp[j-1], dp[j-2] + count_frequency[j]) return dp[max_number]
delete-and-earn
[ Python ] ✔✔ Simple Python Solution Using Dynamic Programming and Dictionary 🔥✌
ASHOK_KUMAR_MEGHVANSHI
0
114
delete and earn
740
0.573
Medium
12,153
https://leetcode.com/problems/delete-and-earn/discuss/1792477/Easily-understanding-DP-solution-in-python-3
class Solution: def deleteAndEarn(self, nums: List[int]) -> int: cnt = [0] * (max(nums) + 1) for num in nums: cnt[num] += 1 # record the occurrence of each num dp = [[0, 0] for i in range(max(nums)+1)] res = 0 #Base case: dp[0][0], dp[0][1] = 0 for i in range(1, max(nums)+1): # 0 means select the current num, 1 means not select #F[i, 0] not select i: max(F(i-1, 0) F(i-1, 1)) #F[i, 1] select i: max(F(i - 2, 0), i*count(i)) dp[i][0] = max(dp[i-1][0], dp[i-1][1]) dp[i][1] = dp[i-1][0] + i*cnt[i] res = max(res, max(dp[i][0], dp[i][1])) return res
delete-and-earn
Easily understanding DP solution in python 3
WhATEVERnameIS
0
115
delete and earn
740
0.573
Medium
12,154
https://leetcode.com/problems/delete-and-earn/discuss/1771319/Python-easy-to-read-and-understand-or-DP
class Solution: def solve(self, nums): n = len(nums) t = [[0 for _ in range(n)] for _ in range(2)] t[0][0] = nums[0] for i in range(1, n): t[0][i] = t[1][i-1] + nums[i] t[1][i] = max(t[0][i-1], t[1][i-1]) return max(t[0][n-1], t[1][n-1]) def deleteAndEarn(self, nums: List[int]) -> int: d = {} for num in nums: d[num] = d.get(num, 0) + num t = [0 for _ in range(max(nums)+1)] for i in range(len(t)): t[i] = d.get(i, 0) return self.solve(t)
delete-and-earn
Python easy to read and understand | DP
sanial2001
0
131
delete and earn
740
0.573
Medium
12,155
https://leetcode.com/problems/delete-and-earn/discuss/1748290/Python-O(nlogn)-solution
class Solution: def deleteAndEarn(self, nums: List[int]) -> int: sortedNums = sorted(nums) aggr = {} result = {} prev = (0,0) prev2 = (0,0) for e in sortedNums: aggr[e] = aggr.get(e, 0) + e for key,val in aggr.items(): result[key] = max(result.get(key - 1, 0), result.get(key - 2, 0) + val, 0 if prev[0] == (key - 1) else prev[1] + val, prev2[1] + val) prev2 = prev prev = (key, result[key]) return result[key]
delete-and-earn
Python O(nlogn) solution
ganyue246
0
116
delete and earn
740
0.573
Medium
12,156
https://leetcode.com/problems/delete-and-earn/discuss/1592417/Python3-Iterative-dp-solution
class Solution: def deleteAndEarn(self, nums: List[int]) -> int: count = collections.defaultdict(int) _min, _max = float('inf'), float('-inf') for num in nums: count[num] += 1 _min = min(_min, num) _max = max(_max, num) cur = prev = 0 for i in range(_min, _max + 1): prev, cur = cur, max(cur, prev + count[i] * i) return cur
delete-and-earn
[Python3] Iterative dp solution
maosipov11
0
115
delete and earn
740
0.573
Medium
12,157
https://leetcode.com/problems/delete-and-earn/discuss/1460541/Easy-python-solutionoror-dict-and-dporor-Python3
class Solution: def deleteAndEarn(self, nums: List[int]) -> int: nums = sorted(nums,reverse=True) dct = {} for i in nums: if i in dct: dct[i]+=i else: dct[i] = i lst = list(dct.keys()) dp = [0]*len(lst) dp[0] = dct[lst[0]] for i in range(1,len(lst)): if lst[i] < lst[i-1]-1: dp[i] = dp[i-1]+dct[lst[i]] else: dp[i] = max(dp[i-2]+dct[lst[i]],dp[i-1]) print(dp) return dp[-1]
delete-and-earn
Easy python solution|| dict & dp|| Python3
ce17b127
0
84
delete and earn
740
0.573
Medium
12,158
https://leetcode.com/problems/delete-and-earn/discuss/1422008/Python-Clean
class Solution: def deleteAndEarn(self, nums: List[int]) -> int: if len(nums) == 1: return nums[0] elif len(nums) == 2: return max(nums) if nums[0]+1 == nums[1] else sum(nums) count = collections.Counter(nums) elements = sorted(count.keys()) dp = [0]*len(elements) dp[0] = elements[0]*count[elements[0]] if elements[0]+1 == elements[1]: dp[1] = max(dp[0], elements[1]*count[elements[1]]) else: dp[1] = dp[0] + elements[1]*count[elements[1]] for i in range(2, len(elements)): if elements[i-1]+1 == elements[i]: dp[i] = max(dp[i-2] + elements[i]*count[elements[i]], dp[i-1]) else: dp[i] = dp[i-1] + elements[i]*count[elements[i]] return dp[-1]
delete-and-earn
[Python] Clean
soma28
0
91
delete and earn
740
0.573
Medium
12,159
https://leetcode.com/problems/delete-and-earn/discuss/367890/Solution-in-Python-3-(beats-~100)-(four-lines)
class Solution: def deleteAndEarn(self, n: List[int]) -> int: if not n: return 0 a, b, C = 0, n.count(1), collections.Counter(n) for i in range(2,max(n)+1): b, a = max(C[i]*i + a, b), b return b - Junaid Mansuri (LeetCode ID)@hotmail.com
delete-and-earn
Solution in Python 3 (beats ~100%) (four lines)
junaidmansuri
0
414
delete and earn
740
0.573
Medium
12,160
https://leetcode.com/problems/cherry-pickup/discuss/699169/Python3-dp
class Solution: def cherryPickup(self, grid: List[List[int]]) -> int: n = len(grid) @lru_cache(None) def fn(t, i, ii): """Return maximum cherries collected at kth step when two robots are at ith and iith row""" j, jj = t - i, t - ii #columns if not (0 <= i < n and 0 <= j < n) or t < i or grid[ i][ j] == -1: return -inf #robot 1 not at proper location if not (0 <= ii < n and 0 <= jj < n) or t < ii or grid[ii][jj] == -1: return -inf #robot 2 not at proper location if t == 0: return grid[0][0] #starting from 0,0 return grid[i][j] + (i != ii)*grid[ii][jj] + max(fn(t-1, x, y) for x in (i-1, i) for y in (ii-1, ii)) return max(0, fn(2*n-2, n-1, n-1))
cherry-pickup
[Python3] dp
ye15
2
241
cherry pickup
741
0.363
Hard
12,161
https://leetcode.com/problems/cherry-pickup/discuss/2798148/(Pythong)-Simplify-the-input-%3A-dp(x1-y1-x2)-with-%40cache
class Solution: def cherryPickup(self, grid: List[List[int]]) -> int: @cache def dp(x1, y1, x2): y2 = x1+y1-x2 if not(0 <= x1 < len(grid) and 0 <= y1 < len(grid[0]) and 0 <= x2 < len(grid) and 0 <= y2 < len(grid[0])): return -float('inf') if grid[x1][y1] == -1 or grid [x2][y2] == -1 : return -float('inf') if x1 == len(grid)-1 and x2 == len(grid)-1 and y1 == len(grid[0])-1 and y1 == len(grid[0])-1 : if grid[x1][y1] == 1 : return 1 else : return 0 if x1 == x2 and y1 == y2 : if grid[x1][y1] == 1 : return 1+max(dp(x1+1, y1, x2+1), dp(x1+1, y1, x2), dp(x1, y1+1, x2+1), dp(x1, y1+1, x2)) else: return max(dp(x1+1, y1, x2+1), dp(x1+1, y1, x2), dp(x1, y1+1, x2+1), dp(x1, y1+1, x2)) else : if grid[x1][y1] == 1 and grid[x2][y2] == 1: return 2+max(dp(x1+1, y1, x2+1), dp(x1+1, y1, x2), dp(x1, y1+1, x2+1), dp(x1, y1+1, x2)) elif grid[x1][y1] == 1: return 1+max(dp(x1+1, y1, x2+1), dp(x1+1, y1, x2), dp(x1, y1+1, x2+1), dp(x1, y1+1, x2)) elif grid[x2][y2] == 1: return 1+max(dp(x1+1, y1, x2+1), dp(x1+1, y1, x2), dp(x1, y1+1, x2+1), dp(x1, y1+1, x2)) else: return max(dp(x1+1, y1, x2+1), dp(x1+1, y1, x2), dp(x1, y1+1, x2+1), dp(x1, y1+1, x2)) if dp(0,0,0) == -float('inf'): return 0 else : return dp(0,0,0)
cherry-pickup
(Pythong) Simplify the input : dp(x1, y1, x2) with @cache
SooCho_i
0
7
cherry pickup
741
0.363
Hard
12,162
https://leetcode.com/problems/cherry-pickup/discuss/1676191/Python3-or-Top-down-solution-or-DP
class Solution: def cherryPickup(self, grid: List[List[int]]) -> int: rows = len(grid) cols = len(grid[0]) #Go down or go right directions = [(1, 0), (0, 1)] #Enables cache for our dp @lru_cache(None) def dp(row_1, row_2, col_1, col_2): #if we hit a wall or we go out of the grid if col_1 >= cols or col_2 >= cols or row_1 >= rows or row_2 >= rows or grid[row_1][col_1] == -1 or grid[row_2][col_2] == -1: return -inf #Pick current cherries result = grid[row_1][col_1] #Do not double cherries if both paths are the same if col_1 != col_2 or row_1 != row_2: result += grid[row_2][col_2] # If we are at the end of the grid stop if not (row_1 == rows - 1 and col_1 == cols - 1): result += max(dp(new_row_1 + row_1, new_row_2 + row_2, new_col_1 + col_1, new_col_2 + col_2) for new_row_1, new_col_1 in directions for new_row_2, new_col_2 in directions) return result ans = dp(0, 0, 0, 0) return 0 if ans == -inf else ans
cherry-pickup
Python3 | Top-down solution | DP
Jujusp
0
135
cherry pickup
741
0.363
Hard
12,163
https://leetcode.com/problems/network-delay-time/discuss/2036405/Python-Simple-Dijkstra-Beats-~90
class Solution: def networkDelayTime(self, times: List[List[int]], n: int, k: int) -> int: adj_list = defaultdict(list) for x,y,w in times: adj_list[x].append((w, y)) visited=set() heap = [(0, k)] while heap: travel_time, node = heapq.heappop(heap) visited.add(node) if len(visited)==n: return travel_time for time, adjacent_node in adj_list[node]: if adjacent_node not in visited: heapq.heappush(heap, (travel_time+time, adjacent_node)) return -1
network-delay-time
Python Simple Dijkstra Beats ~90%
constantine786
39
2,200
network delay time
743
0.515
Medium
12,164
https://leetcode.com/problems/network-delay-time/discuss/1614297/Python-3-or-Different-4-Methods-or-No-Explanation
class Solution: def networkDelayTime(self, times: List[List[int]], n: int, k: int) -> int: dp = [sys.maxsize] * n dp[k-1] = 0 graph = collections.defaultdict(list) for s, e, w in times: graph[s].append((e, w)) visited = set() heap = [(0, k)] while heap: cur, node = heapq.heappop(heap) dp[node-1] = cur if node not in visited: visited.add(node) n -= 1 for nei, w in graph[node]: if dp[nei-1] > cur + w: dp[nei-1] = cur + w if nei not in visited: heapq.heappush(heap, (cur + w, nei)) if not n: return cur return -1
network-delay-time
Python 3 | Different 4 Methods | No Explanation
idontknoooo
6
512
network delay time
743
0.515
Medium
12,165
https://leetcode.com/problems/network-delay-time/discuss/1614297/Python-3-or-Different-4-Methods-or-No-Explanation
class Solution: def networkDelayTime(self, times: List[List[int]], n: int, k: int) -> int: dp = [[sys.maxsize] * n for _ in range(n)] graph = collections.defaultdict(list) for s, e, w in times: graph[s].append((e, w)) dp[s-1][e-1] = w for i in range(n): dp[i][i] = 0 for kk in range(n): for i in range(n): for j in range(n): if dp[i][kk] != sys.maxsize and dp[kk][j] != sys.maxsize: dp[i][j] = min(dp[i][j], dp[i][kk] + dp[kk][j]) ans = 0 for j in range(n): ans = max(ans, dp[k-1][j]) return ans if ans != sys.maxsize else -1
network-delay-time
Python 3 | Different 4 Methods | No Explanation
idontknoooo
6
512
network delay time
743
0.515
Medium
12,166
https://leetcode.com/problems/network-delay-time/discuss/1614297/Python-3-or-Different-4-Methods-or-No-Explanation
class Solution: def networkDelayTime(self, times: List[List[int]], n: int, k: int) -> int: dp = [sys.maxsize] * n dp[k-1] = 0 for _ in range(n-1): for s, e, w in times: if dp[e-1] > dp[s-1] + w: dp[e-1] = dp[s-1] + w ans = 0 for i in range(n): if i != k-1: ans = max(ans, dp[i]) return ans if ans != sys.maxsize else -1
network-delay-time
Python 3 | Different 4 Methods | No Explanation
idontknoooo
6
512
network delay time
743
0.515
Medium
12,167
https://leetcode.com/problems/network-delay-time/discuss/1614297/Python-3-or-Different-4-Methods-or-No-Explanation
class Solution: def networkDelayTime(self, times: List[List[int]], n: int, k: int) -> int: dp = [sys.maxsize] * n dp[k-1] = 0 graph = collections.defaultdict(list) for s, e, w in times: graph[s].append((e, w)) dq = collections.deque([k]) visited = set([k]) while dq: node = dq.popleft() cost = dp[node-1] visited.remove(node) for nei, w in graph[node]: if dp[nei-1] > cost + w: dp[nei-1] = cost + w if nei not in visited: visited.add(nei) dq.append(nei) ans = 0 for i in range(n): if i != k-1: ans = max(ans, dp[i]) return ans if ans != sys.maxsize else -1
network-delay-time
Python 3 | Different 4 Methods | No Explanation
idontknoooo
6
512
network delay time
743
0.515
Medium
12,168
https://leetcode.com/problems/network-delay-time/discuss/2004199/Python3%3A-Dijkstra's-Algorithm-(easy-to-understand)
class Solution: def networkDelayTime(self, times: List[List[int]], n: int, k: int) -> int: # This problem requires dijkstra's algorithm, where we find the shortest # distance between a source vertex to all the other vertices. # If any of the other vertices could not be reached, return -1. # Else return the largest distance. # Construct an adjacency list. # Note: ignore 0th index because there is no node 0. adjList = [[] for _ in range(n + 1)] for edge in times: # edge[0] is src, edge[1] is dest, edge[2] is time taken. adjList[edge[0]].append([edge[1], edge[2]]) # Initialise the queue and dist array. queue = {} dist = [float('inf')] * (n + 1) # Set the distances of all vertices to be initially inf (not found). for vertex in range(n): queue[vertex] = float('inf') # Set the distance of the source vertex to be 0. dist[k] = 0 queue[k] = 0 # While queue is not empty. while (len(queue) > 1): # Remove the vertex with the smallest edge from the queue. v = min(queue, key = queue.get) queue.pop(v) # If the smallest-distance vertex has a distance of float('inf'), # then there's no path between source to the rest of the vertices. if dist[v] == float('inf'): break # Loop through the neighbours of v. for w in adjList[v]: # w[0] is the neighbour vertex, w[1] is the distance between # v and w. if (w[0] == k): continue newDist = dist[v] + w[1] if (newDist < dist[w[0]]): dist[w[0]] = newDist queue[w[0]] = newDist # If a node is unreachable, return -1. if float('inf') in dist[1:]: return -1 # Else, return max dist in the list. return max(dist[1:])
network-delay-time
Python3: Dijkstra's Algorithm (easy to understand)
anjerraa
2
137
network delay time
743
0.515
Medium
12,169
https://leetcode.com/problems/network-delay-time/discuss/2767908/Python-Dijkstra-Algorithm-(-Simple-Soln-with-comments)
class Solution: def networkDelayTime(self, times: List[List[int]], n: int, k: int) -> int: #create adjacency list adjList = {i:[] for i in range(1, n+1)} #node: [neighbour, weight] for src, dest, weight in times: adjList[src].append([dest, weight]) #create minHeap minHeap = [] minHeap.append([0, k]) heapq.heapify(minHeap) #dikjstra dist = [float("inf")] * (n+1) dist[k] = 0 while minHeap: dis, node = heapq.heappop(minHeap) for it in adjList[node]: edgeWeight = it[1] edgeNode = it[0] if (dis+edgeWeight) < dist[edgeNode]: dist[edgeNode] = dis+edgeWeight heapq.heappush(minHeap, [dist[edgeNode], edgeNode]) #result return max(dist[1:]) if max(dist[1:]) != float("inf") else -1
network-delay-time
Python - Dijkstra Algorithm ( Simple Soln with comments)
logeshsrinivasans
1
123
network delay time
743
0.515
Medium
12,170
https://leetcode.com/problems/network-delay-time/discuss/2176431/Python3-3-solutions-DFS-BFS-Dijkstra
class Solution: def networkDelayTime(self, times: List[List[int]], n: int, k: int) -> int: ## RC ## ## APPROACH 1 : DFS + Visited ## ## Not optimized method, barely passed, always use BFS for shortest path algorithms ## graph = collections.defaultdict(list) visited = {} for u, v, w in times: graph[u].append((v, w)) visited[u] = float('inf') visited[v] = float('inf') if len(visited) != n: return -1 def dfs(node, weight): if weight < visited[node]: visited[node] = weight for v, w in graph[node]: dfs(v, weight + w) # dfs(k, 0) # if max(visited.values()) == float('inf'): # return -1 # return max(visited.values()) ## APPROACH 2 : BFS ## queue = collections.deque([(k, 0)]) while(queue): node, weight = queue.popleft() if weight < visited[node]: visited[node] = weight for v, w in graph[node]: queue.append((v, weight + w)) if max(visited.values()) == float('inf'): return -1 return max(visited.values()) ## APPROACH 3: Dijkstra Algorithm ## ## Application: Single source shortest path ( weighted ) ## pq=[(0, k)] # (weight, start-node) visited = {} while(pq): weight, node = heapq.heappop(pq) if node not in visited: visited[node] =weight for v, w in graph[node]: heapq.heappush(pq, (weight + w, v)) if len(visited) != n: return -1 return max(visited.values())
network-delay-time
[Python3] 3 solutions DFS, BFS, Dijkstra
101leetcode
1
71
network delay time
743
0.515
Medium
12,171
https://leetcode.com/problems/network-delay-time/discuss/1590202/Python-Solution-Beats-96.99-Of-python-Solution-(-DIJKSTRA-Algo)
class Solution: def networkDelayTime(self, times: List[List[int]], n: int, k: int) -> int: distance=[float('inf')]*n distance[k-1]=0 visited=[False]*n heap=[(0,k-1)] adj=defaultdict(list) for u,v,w in times:adj[u-1].append((v-1,w)) while heap: mi,u=heapq.heappop(heap) visited[u]=True for v,w in adj[u]: if not visited[v]: if mi+w<distance[v]: distance[v]=mi+w heapq.heappush(heap,(mi+w,v)) ans=max(distance) #print(distance) #print(adj) return ans if ans!=float('inf') else -1
network-delay-time
Python Solution Beats 96.99% Of python Solution ( DIJKSTRA Algo)
reaper_27
1
77
network delay time
743
0.515
Medium
12,172
https://leetcode.com/problems/network-delay-time/discuss/1214552/Python3-Solution-using-Djikstra-and-heap
class Solution: def networkDelayTime(self, times: List[List[int]], n: int, k: int) -> int: # implemented using dijkstra's shortest path graph = {} # create graph for u, v, w in times: if u not in graph.keys(): graph[u] = [(v, w)] else: graph[u].append((v, w)) min_heap = [(0, k)] # push starting node k into heap, cost is 0 costs = {} while len(min_heap) != 0: cost, node = heapq.heappop(min_heap) # pop node with smallest cost if node in costs.keys(): # check for duplicates continue costs[node] = cost if node not in graph.keys(): # prevent key error continue for neighbor, c in graph[node]: if neighbor not in costs.keys(): heapq.heappush(min_heap, (cost + c, neighbor)) # push all the neighbors into heap (may push duplicate nodes) if len(costs) == n: return max(costs.values()) else: return -1
network-delay-time
Python3 Solution using Djikstra and heap
JensonC0012
1
85
network delay time
743
0.515
Medium
12,173
https://leetcode.com/problems/network-delay-time/discuss/1137280/Python-or-Dijkstra's-Algorithm-or-Beats-99
class Solution: def networkDelayTime(self, times: List[List[int]], n: int, k: int) -> int: graph = {i:dict() for i in range(1, n+1)} for u,v,w in times: graph[u][v] = w dist = [float('inf') for i in range(n+1)] dist[0], dist[k] = 0, 0 visited = [False]*(n+1) queue = [(0, k)] heapify(queue) while len(queue): minNode = heappop(queue)[1] if visited[minNode]: continue visited[minNode] = True for node in graph[minNode]: if not visited[node] and dist[minNode] + graph[minNode][node] < dist[node]: dist[node] = dist[minNode] + graph[minNode][node] heappush(queue, (dist[node], node)) ans = max(dist) return ans if ans != float('inf') else -1
network-delay-time
Python | Dijkstra's Algorithm | Beats 99%
anuraggupta29
1
118
network delay time
743
0.515
Medium
12,174
https://leetcode.com/problems/network-delay-time/discuss/491792/Python3-Dijkstra's-algo
class Solution: def networkDelayTime(self, times: List[List[int]], N: int, K: int) -> int: graph = dict() #digraph in contingency list for u, v, w in times: graph.setdefault(u, []).append((w, v)) dist = [float("inf")]*N stack = [(0, K)] #depth-first-search while stack: d, n = stack.pop() if dist[n-1] <= d: continue dist[n-1] = d for w, v in sorted(graph.get(n, []), reverse=True): stack.append((d+w, v)) ans = max(dist) return ans if ans < float("inf") else -1
network-delay-time
[Python3] Dijkstra's algo
ye15
1
181
network delay time
743
0.515
Medium
12,175
https://leetcode.com/problems/network-delay-time/discuss/491792/Python3-Dijkstra's-algo
class Solution: def networkDelayTime(self, times: List[List[int]], N: int, K: int) -> int: """bellman-ford algorithm""" dist = [float("inf")]*N dist[K-1] = 0 for _ in range(N-1): for u, v, w in times: dist[v-1] = min(dist[v-1], dist[u-1]+w) ans = max(dist) return ans if ans < float("inf") else -1
network-delay-time
[Python3] Dijkstra's algo
ye15
1
181
network delay time
743
0.515
Medium
12,176
https://leetcode.com/problems/network-delay-time/discuss/491792/Python3-Dijkstra's-algo
class Solution: def networkDelayTime(self, times: List[List[int]], N: int, K: int) -> int: """floyd-warshall algorithm""" dist = [[float("inf")]*N for _ in range(N)] for i in range(N): dist[i][i] = 0 for u, v, w in times: dist[u-1][v-1] = w for k in range(N): for i in range(N): for j in range(N): dist[i][j] = min(dist[i][j], dist[i][k] + dist[k][j]) ans = max(dist[K-1]) return ans if ans < float("inf") else -1
network-delay-time
[Python3] Dijkstra's algo
ye15
1
181
network delay time
743
0.515
Medium
12,177
https://leetcode.com/problems/network-delay-time/discuss/2786606/Python-Dijkstra
class Solution: # main challenge is that it seems like the value of the queue needs to change. # solved by ignoring any queue item that has been updated. def networkDelayTime(self, times: List[List[int]], n: int, k: int): # build adjacency list graph = [{} for _ in range(n)] for edge in times: source, target, delay = edge[0], edge[1], edge[2] # minus 1 to change from 1 - n to 0 - (n - 1) graph[source - 1][target - 1] = delay temp_received_time = [float('inf') for i in range(n)] # set as start node temp_received_time[k - 1] = 0 # heap for possible smallest next node h = [] heapq.heappush(h, (0, k - 1)) while h: cur_time, cur_node = heapq.heappop(h) if cur_time > temp_received_time[cur_node]: # this node has been updated and dealt before(since it has smaller time, which means higher precedence) continue for neighbour in graph[cur_node]: neighbour_time = cur_time + graph[cur_node][neighbour] if neighbour_time < temp_received_time[neighbour]: temp_received_time[neighbour] = neighbour_time heapq.heappush(h, (neighbour_time, neighbour)) # get the max time max_time = 0 for time in temp_received_time: if time == float('inf'): return -1 max_time = max(max_time, time) return max_time
network-delay-time
[Python] Dijkstra
i-hate-covid
0
4
network delay time
743
0.515
Medium
12,178
https://leetcode.com/problems/network-delay-time/discuss/2043011/Python-DjikstraBFS-or-O(E-log-V)
class Solution: def networkDelayTime(self, times: List[List[int]], n: int, k: int) -> int: edges = collections.defaultdict(list) for u, v, w in times: edges[u].append((v, w)) minHeap = [(0, k)] visited = set() t = 0 while minHeap: w1, n1 = heapq.heappop(minHeap) if n1 in visited: continue visited.add(n1) t = max(t, w1) for n2, w2 in edges[n1]: if n2 not in visited: heapq.heappush(minHeap, (t + w2, n2)) return t if len(visited) == n else -1
network-delay-time
[Python] Djikstra/BFS | O(E log V)
tejeshreddy111
0
24
network delay time
743
0.515
Medium
12,179
https://leetcode.com/problems/network-delay-time/discuss/2039595/Python-Dijkstra-algorithm
class Solution: def networkDelayTime(self, times: List[List[int]], n: int, k: int) -> int: adj = defaultdict(list) for u, v, w in times: adj[u].append((v, w)) q = [(0, k)] seen = set() while q: if q[0][1] in seen: heapq.heappop(q) continue time, node = heapq.heappop(q) seen.add(node) for adj_node, w in adj[node]: if adj_node not in seen: heapq.heappush(q, (time + w, adj_node)) return time if len(seen) == n else -1
network-delay-time
Python, Dijkstra algorithm
blue_sky5
0
22
network delay time
743
0.515
Medium
12,180
https://leetcode.com/problems/network-delay-time/discuss/2038547/Python3-Solution-with-using-dfsbfs
class Solution: def networkDelayTime(self, times: List[List[int]], n: int, k: int) -> int: g = collections.defaultdict(list) # build graph for src, dst, weight in times: g[src].append((dst, weight)) # k - node, v - weight (src to k) node2ws = {i: float('inf') for i in range(1, n + 1)} def dfs(source, cur_weight): if cur_weight < node2ws[source]: node2ws[source] = cur_weight for neigb, w in g[source]: dfs(neigb, cur_weight + w) dfs(k, 0) ws = node2ws.values() _max = max(ws) return _max if _max != float('inf') else -1
network-delay-time
[Python3] Solution with using dfs/bfs
maosipov11
0
25
network delay time
743
0.515
Medium
12,181
https://leetcode.com/problems/network-delay-time/discuss/2038547/Python3-Solution-with-using-dfsbfs
class Solution: def networkDelayTime(self, times: List[List[int]], n: int, k: int) -> int: g = collections.defaultdict(list) # build graph for src, dst, weight in times: g[src].append((dst, weight)) # k - node, v - weight (src to k) node2ws = {i: float('inf') for i in range(1, n + 1)} node2ws[k] = 0 q= collections.deque() q.append((k, 0)) while q: cur_node, cur_w = q.popleft() for neigb, neigb_w in g[cur_node]: if cur_w + neigb_w < node2ws[neigb]: node2ws[neigb] = cur_w + neigb_w q.append((neigb, cur_w + neigb_w)) ws = node2ws.values() _max = max(ws) return _max if _max != float('inf') else -1
network-delay-time
[Python3] Solution with using dfs/bfs
maosipov11
0
25
network delay time
743
0.515
Medium
12,182
https://leetcode.com/problems/network-delay-time/discuss/2036541/python3-shortest-path-algo-%2B-BFS
class Solution: def networkDelayTime(self, times: List[List[int]], n: int, k: int) -> int: # n = num of nodes, k = source group = collections.defaultdict(list) # source: list of [target, time] for u, v, w in times: group[u].append([v, w]) node2time = collections.defaultdict(int) queue = collections.deque([[k, 0]]) ans = 0 node2time[k] = 0 while queue: cur, total_time = queue.popleft() if cur in group: for nxt, time_taken in group[cur]: t = total_time + time_taken if nxt in node2time and t >= node2time[nxt]: # shorter path is found already continue else: node2time[nxt] = t queue.append([nxt, t]) if len(node2time) != n: return -1 else: return max(node2time.values())
network-delay-time
[python3] shortest path algo + BFS
sshinyy
0
15
network delay time
743
0.515
Medium
12,183
https://leetcode.com/problems/network-delay-time/discuss/2036352/Simple-Python-Solution-oror-Dijkstra
class Solution: def networkDelayTime(self, times: List[List[int]], n: int, k: int) -> int: d=defaultdict(list) for src,dst,t in times: d[src].append((dst,t)) q=[(0,k)] visited=set() max_cost=0 while q: cost,node=heapq.heappop(q) if node in visited: continue visited.add(node) max_cost=max(max_cost,cost) neighbours=d[node] for neighbour in neighbours: new_node,new_cost=neighbour if new_node not in visited: curr_cost=cost+new_cost heapq.heappush(q,(curr_cost,new_node)) return max_cost if len(visited)==n else -1
network-delay-time
Simple Python Solution || Dijkstra
a_dityamishra
0
36
network delay time
743
0.515
Medium
12,184
https://leetcode.com/problems/network-delay-time/discuss/2036341/Python-Dijkstra's-Algorithm-oror-O(E.logV)-Time-Complexity-oror-Simple-and-Easy-Solution
class Solution: def networkDelayTime(self, times: List[List[int]], n: int, k: int) -> int: edges = collections.defaultdict(list) for u, v, w in times: edges[u].append((v, w)) t = 0 minHeap = [(0, k)] visit = set() while minHeap: w1, n1 = heapq.heappop(minHeap) if n1 in visit: continue visit.add(n1) t = max(t, w1) for n2, w2 in edges[n1]: if n2 not in visit: heapq.heappush(minHeap, (w2 + w1, n2)) return t if len(visit) == n else -1
network-delay-time
Python - Dijkstra's Algorithm || O(E.logV) Time Complexity || Simple and Easy Solution
dayaniravi123
0
17
network delay time
743
0.515
Medium
12,185
https://leetcode.com/problems/network-delay-time/discuss/2036240/Python-Solution-min-heap-defaultdict(dict)-dijkstras-algorithm
class Solution(object): def networkDelayTime(self, times, n, k): """ :type times: List[List[int]] :type n: int :type k: int :rtype: int """ dic = defaultdict(dict) for x, y, t in times: dic[x][y] = t heap = [(0, k)] seen = set() res = 0 while heap: time, curr = heapq.heappop(heap) seen.add(curr) if len(seen) == n: return time for other in dic[curr]: if other not in seen: heapq.heappush(heap, (dic[curr][other] + time, other)) return -1
network-delay-time
Python Solution min-heap defaultdict(dict) dijkstras algorithm
Kennyyhhu
0
50
network delay time
743
0.515
Medium
12,186
https://leetcode.com/problems/network-delay-time/discuss/2036231/beat-all
class Solution: def networkDelayTime(self, times: List[List[int]], n: int, k: int) -> int: visited, matrix = [float('inf')] * n, [[float('inf')] * n for _ in range(n)] for u, v, w in times: matrix[u-1][v-1] = w q = [(0, k-1)] visited[k-1] = 0 while q: cur_v, cur_n = heapq.heappop(q) for nei_n, nei_v in enumerate(matrix[cur_n]): if visited[nei_n] > cur_v + nei_v: visited[nei_n] = cur_v + nei_v heapq.heappush(q, (visited[nei_n], nei_n)) ret = max(visited) return ret if ret != float('inf') else -1
network-delay-time
beat all
BichengWang
0
24
network delay time
743
0.515
Medium
12,187
https://leetcode.com/problems/network-delay-time/discuss/1847181/Python-Dijkstra
class Solution: def networkDelayTime(self, times: List[List[int]], n: int, k: int) -> int: import heapq graph = defaultdict(dict) for i,j,w in times: graph[i][j] = w dist = [float("inf")]*(n+1) dist[k] = 0 que = [(0,k)] visited = [False]*(n+1) while que: d, node = heapq.heappop(que) if visited[node]: continue visited[node] = True for child in graph[node]: if graph[node][child] + d < dist[child]: dist[child] = graph[node][child] + d heapq.heappush( que, (dist[child],child) ) ret = max(dist[1:]) return ret if ret!=float("inf") else -1
network-delay-time
[Python] Dijkstra
haydarevren
0
85
network delay time
743
0.515
Medium
12,188
https://leetcode.com/problems/network-delay-time/discuss/1490760/Python-Dijkstra's-with-array-and-self-made-heap
class Solution: def networkDelayTime(self, times: List[List[int]], n: int, k: int) -> int: graph = [[] for _ in range(n)] self.createGraph(times, graph) minDist = [float('inf') for _ in range(n)] minDist[k - 1] = 0 visited = set() while len(visited) != n: currDist, currVertex = self.explore(visited, minDist) if currDist == float('inf'): break visited.add(currVertex) for node in graph[currVertex]: vertex, cost = node if vertex in visited: continue newCost = cost + currDist if newCost < minDist[vertex]: minDist[vertex] = newCost return -1 if float('inf') in minDist else max(minDist) def explore(self, visited, minDist): smallestDist = float('inf') smallestNode = -1 for i in range(len(minDist)): if i in visited: continue weight = minDist[i] if weight <= smallestDist: smallestDist = weight smallestNode = i return smallestDist, smallestNode def createGraph(self, times, graph): for time in times: source, dest, cost = time graph[source - 1].append((dest - 1, cost))
network-delay-time
Python Dijkstra's with array and self-made heap
SleeplessChallenger
0
142
network delay time
743
0.515
Medium
12,189
https://leetcode.com/problems/network-delay-time/discuss/1490760/Python-Dijkstra's-with-array-and-self-made-heap
class Solution: def networkDelayTime(self, times: List[List[int]], n: int, k: int) -> int: graph = [[] for _ in range(n)] self.createGraph(graph, times) minDist = [float('inf') for _ in range(n)] minDist[k - 1] = 0 min_heap = MinHeap([(idx, float('inf')) for idx in range(n)]) min_heap.update(k - 1, 0) while not min_heap.check(): vertex, cost = min_heap.remove() if cost == float('inf'): break for i in graph[vertex]: node, dist = i newDist = dist + cost if newDist < minDist[node]: minDist[node] = newDist min_heap.update(node, newDist) return -1 if float('inf') in minDist else max(minDist) def createGraph(self, graph, times): for time in times: source, dest, cost = time graph[source - 1].append((dest - 1, cost)) class MinHeap: def __init__(self, arr): self.vertex = {idx: idx for idx in range(len(arr))} self.heap = self.buildHeap(arr) def check(self): return len(self.heap) == 0 def buildHeap(self, arr): parentIdx = (len(arr) - 2) // 2 for i in reversed(range(parentIdx + 1)): self.siftDown(i, len(arr) - 1, arr) return arr def remove(self): if self.check(): return self.swapValues(0, len(self.heap) - 1, self.heap) idx, node = self.heap.pop() del self.vertex[idx] self.siftDown(0, len(self.heap) - 1, self.heap) return idx, node def siftDown(self, idx, length, arr): idxOne = idx * 2 + 1 while idxOne <= length: idxTwo = idx * 2 + 2 if idx * 2 + 2 <= length else -1 if idxTwo != -1 and arr[idxOne][1] > arr[idxTwo][1]: swap = idxTwo else: swap = idxOne if arr[swap][1] < arr[idx][1]: self.swapValues(swap, idx, arr) idx = swap idxOne = idx * 2 + 1 else: return def swapValues(self, i, j, arr): self.vertex[arr[i][0]] = j self.vertex[arr[j][0]] = i arr[i], arr[j] = arr[j], arr[i] def siftUp(self, curr_idx): parentIdx = (curr_idx - 1) // 2 while curr_idx > 0: if self.heap[curr_idx][1] < self.heap[parentIdx][1]: self.swapValues(curr_idx, parentIdx, self.heap) curr_idx = parentIdx parentIdx = (curr_idx - 1) // 2 else: return def update(self, idx, value): curr_idx = self.vertex[idx] self.heap[curr_idx] = (idx, value) self.siftUp(curr_idx)
network-delay-time
Python Dijkstra's with array and self-made heap
SleeplessChallenger
0
142
network delay time
743
0.515
Medium
12,190
https://leetcode.com/problems/network-delay-time/discuss/1174211/python-4-methods%3A-Dijkstra's-Bellman-Ford-bfs-dfs
class Solution(object): def networkDelayTime(self, times, N, K): graph = collections.defaultdict(list) for u, v, w in times: graph[u].append((w, v)) pq = [(0, K)] dist = {} while pq: d, node = heapq.heappop(pq) if node in dist: continue dist[node] = d for d2, nei in graph[node]: if nei not in dist: heapq.heappush(pq, (d+d2, nei)) return max(dist.values()) if len(dist) == N else -1
network-delay-time
python 4 methods: Dijkstra's, Bellman Ford, bfs, dfs
dustlihy
0
185
network delay time
743
0.515
Medium
12,191
https://leetcode.com/problems/network-delay-time/discuss/1174211/python-4-methods%3A-Dijkstra's-Bellman-Ford-bfs-dfs
# class Solution: # def networkDelayTime(self, times: List[List[int]], N: int, K: int) -> int: # INF = float('inf') # dist = [INF] * N # dist[K-1] = 0 # for i in range(N): # for time in times: # 1, time[1] - 1, time[2] # dist[v] = min(dist[v], dist[u] + w) # ans = max(dist) # return ans if ans < INF else -1
network-delay-time
python 4 methods: Dijkstra's, Bellman Ford, bfs, dfs
dustlihy
0
185
network delay time
743
0.515
Medium
12,192
https://leetcode.com/problems/network-delay-time/discuss/1174211/python-4-methods%3A-Dijkstra's-Bellman-Ford-bfs-dfs
# class Solution(object): # def networkDelayTime(self, times, N, K): # graph = collections.defaultdict(list) # for u, v, w in times: # graph[u].append((w, v)) # u --> v # INF = float('inf') # dist = {i: INF for i in range(1, N+1)} # queue = collections.deque([(K, 0)]) # while queue: # node, elasped = queue.popleft() # if elasped < dist[node]: # dist[node] = elasped # for time, nei in sorted(graph[node]): # queue.append((nei, elasped+time)) # ans = max(dist.values()) # return ans if ans < INF else -1
network-delay-time
python 4 methods: Dijkstra's, Bellman Ford, bfs, dfs
dustlihy
0
185
network delay time
743
0.515
Medium
12,193
https://leetcode.com/problems/network-delay-time/discuss/1174211/python-4-methods%3A-Dijkstra's-Bellman-Ford-bfs-dfs
# class Solution(object): # def networkDelayTime(self, times, N, K): # graph = collections.defaultdict(list) # for u, v, w in times: # graph[u].append((w, v)) # u --> v # INF = float('inf') # dist = {node: INF for node in range(1, N+1)} # def dfs(node, elasped): # if dist[node] <= elasped: return # dist[node] = elasped # for time, nei in sorted(graph[node]): # dfs(nei, time+elasped) # dfs(K, 0) # ans = max(dist.values()) # return ans if ans < INF else -1
network-delay-time
python 4 methods: Dijkstra's, Bellman Ford, bfs, dfs
dustlihy
0
185
network delay time
743
0.515
Medium
12,194
https://leetcode.com/problems/network-delay-time/discuss/625942/Python-Solution-Djikstra's-Algorithm
class Solution: def extractMin(self,visited,dist): mind=float("inf") mini=0 for i in range(len(visited)): if not visited[i] and dist[i]<mind: mini=i mind=dist[i] return mini def djikstra(self,visited,dist,K,times): for i in range(len(visited)): curr=self.extractMin(visited,dist) visited[curr]=1 for j in range(len(times)): if times[j][0]==(curr+1) and dist[curr]+times[j][2]<dist[times[j][1]-1]: dist[times[j][1]-1]=dist[curr]+times[j][2] def networkDelayTime(self, times: List[List[int]], n: int, K: int) -> int: visited=[0]*n dist=[float("inf")]*n dist[K-1]=0 self.djikstra(visited,dist,K,times) ans=max(dist) if ans==float("inf"): return -1 return ans
network-delay-time
Python Solution- Djikstra's Algorithm
Ayu-99
0
80
network delay time
743
0.515
Medium
12,195
https://leetcode.com/problems/network-delay-time/discuss/1456874/Python3-solution-using-Dijkstra's-Algorithm
class Solution: def networkDelayTime(self, times: List[List[int]], n: int, k: int) -> int: d = {} graph = [[] for _ in range(n)] for i in times: d[(i[0]-1,i[1]-1)] = i[2] graph[i[0]-1].append(i[1]-1) parent = [-1]*n cost = [10**9]*n visited = [False]*n cost[k-1] = 0 x = 0 while x <= n-1: m = (-1,10**9) for i in range(n): if not visited[i] and m[1] > cost[i]: m = (i,cost[i]) for i,j in enumerate(graph[m[0]]): if (m[0],j) in d and cost[j] > cost[m[0]] + d[(m[0],j)]: cost[j] = cost[m[0]] + d[(m[0],j)] parent[j] = m[0] visited[m[0]] = True x += 1 return -1 if (max(cost)) == 10**9 else max(cost)
network-delay-time
Python3 solution using Dijkstra's Algorithm
EklavyaJoshi
-1
38
network delay time
743
0.515
Medium
12,196
https://leetcode.com/problems/find-smallest-letter-greater-than-target/discuss/1568523/Python-easy-solution-with-detail-explanation-(modified-binary-search)
class Solution(object): def nextGreatestLetter(self, letters, target): """ :type letters: List[str] :type target: str :rtype: str """ # if the number is out of bound if target >= letters[-1] or target < letters[0]: return letters[0] low = 0 high = len(letters)-1 while low <= high: mid = (high+low)//2 if target >= letters[mid]: # in binary search this would be only greater than low = mid+1 if target < letters[mid]: high = mid-1 return letters[low]
find-smallest-letter-greater-than-target
Python easy solution with detail explanation (modified binary search)
Abeni
71
3,300
find smallest letter greater than target
744
0.448
Easy
12,197
https://leetcode.com/problems/find-smallest-letter-greater-than-target/discuss/2507850/4-lines-of-code-easy-understandable-in-Python
class Solution: def nextGreatestLetter(self, letters: List[str], target: str) -> str: t_ord = ord(target) - ord('a') for i in letters: l_ord = ord(i) - ord('a') if l_ord > t_ord: return i return letters[0] # if no chrater is gte that target then return 0 index element
find-smallest-letter-greater-than-target
4 lines of code easy understandable in Python
ankurbhambri
7
79
find smallest letter greater than target
744
0.448
Easy
12,198
https://leetcode.com/problems/find-smallest-letter-greater-than-target/discuss/2176655/Python3-solution-O(log-n)
class Solution: def nextGreatestLetter(self, letters: List[str], target: str) -> str: low, high = 0, len(letters) - 1 while low < high: mid = (low+high) // 2 if letters[mid] <= target: low = mid + 1 else: high = mid return letters[low] if letters[low] > target else letters[0]
find-smallest-letter-greater-than-target
📌 Python3 solution O(log n)
Dark_wolf_jss
6
154
find smallest letter greater than target
744
0.448
Easy
12,199