In an set of integers, find three elements summing to zero (3-sum, leetcode variant) The Next...

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In an set of integers, find three elements summing to zero (3-sum, leetcode variant)



The Next CEO of Stack OverflowGiven an array find any three numbers which sum to zero3-Sum Problem in PythonGiven a vector and a target sum, returns zero-based indices of any two distinct elements whose sum is equal to the target sumPython 3 two-sum performanceFind the pairs of integers that sum to NFind contiguous integers with a given sumFind all combinations of 4 elements whose sum equals a target in PythonLeetcode Mountain ArrayLeetcode Three Sum in PythonHash table solution to twoSum












1












$begingroup$


I use a dummy solution to solve the leetcode 3Sum problem.



I employ the set data type to handle duplicates, then transform back to list.




Given an array nums of n integers, are there elements a, b, c in nums such that a + b + c = 0? Find all unique triplets in the array which gives the sum of zero.



Note:



The solution set must not contain duplicate triplets.



Example:



Given array nums = [-1, 0, 1, 2, -1, -4],



A solution set is:



[
[-1, 0, 1],
[-1, -1, 2]
]



My codes:



from typing import List
import logging
import unittest
import random
from collections import defaultdict,Counter

##logging.disable(level=#logging.CRITICAL)
##logging.basicConfig(level=#logging.DEBUG, format="%(levelname)s %(message)s")

class Solution:
def threeSum(self, nums, target: int=0) -> List[List[int]]:
"""
:type nums: List[int]
:type target: int
"""
if len(nums) < 3: return []

triplets = []
if target == [0, 0, 0]:
triplets.append([0, 0, 0])
return triplets # finish fast

lookup = {nums[i]:i for i in range(len(nums))} #overwrite from the high
if len(lookup) == 1:#assert one identical element
keys = [k for k in lookup.keys()]
if keys[0] != 0:
return []
else:
triplets.append([0,0,0])
return triplets



triplets_set = set()

for i in range(len(nums)):
num_1 = nums[i]
sub_target = target - num_1
# #logging.debug(f"level_1_lookup: {lookup}")

for j in range(i+1, len(nums)):
num_2 = nums[j]
num_3 = sub_target - num_2
k = lookup.get(num_3) #
if k not in {None, i, j}: #don't reproduce itself
result = [num_1, num_2, num_3]
result.sort()
result = tuple(result)
triplets_set.add(result)

triplets = [list(t) for t in triplets_set]
return triplets


My solution gets this result:




Your runtime beats 28.86 % of python3 submissions.




Could anyone please give hints to improve?










share|improve this question









New contributor




Alice is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
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  • 1




    $begingroup$
    Can you check the problem description? It is about pairs (a, b) which sum to 9, but the examples are about triples which sum to zero. – Btw, if you beat 28.86 of other submissions then you are slower 71.14 percent, not slower than 80 percent :)
    $endgroup$
    – Martin R
    Mar 26 at 5:48








  • 1




    $begingroup$
    As set is a common verb in English, try to avoid confusion: set is a Python built-in data type. (Grant me the favour and never call any amount of program source code "codes".) How could target: int == [0, 0, 0]?
    $endgroup$
    – greybeard
    Mar 26 at 6:31












  • $begingroup$
    amazing, better than leetcode's big data testing. @greybeard
    $endgroup$
    – Alice
    Mar 26 at 10:25










  • $begingroup$
    Ah, before I forget again: Congrats on asking for a review, for hints to improve instead of a turn-key solution, on (seemingly) trying to come up with a solution of your own instead of scraping the web/SE/leetcode. Way to learn!
    $endgroup$
    – greybeard
    yesterday
















1












$begingroup$


I use a dummy solution to solve the leetcode 3Sum problem.



I employ the set data type to handle duplicates, then transform back to list.




Given an array nums of n integers, are there elements a, b, c in nums such that a + b + c = 0? Find all unique triplets in the array which gives the sum of zero.



Note:



The solution set must not contain duplicate triplets.



Example:



Given array nums = [-1, 0, 1, 2, -1, -4],



A solution set is:



[
[-1, 0, 1],
[-1, -1, 2]
]



My codes:



from typing import List
import logging
import unittest
import random
from collections import defaultdict,Counter

##logging.disable(level=#logging.CRITICAL)
##logging.basicConfig(level=#logging.DEBUG, format="%(levelname)s %(message)s")

class Solution:
def threeSum(self, nums, target: int=0) -> List[List[int]]:
"""
:type nums: List[int]
:type target: int
"""
if len(nums) < 3: return []

triplets = []
if target == [0, 0, 0]:
triplets.append([0, 0, 0])
return triplets # finish fast

lookup = {nums[i]:i for i in range(len(nums))} #overwrite from the high
if len(lookup) == 1:#assert one identical element
keys = [k for k in lookup.keys()]
if keys[0] != 0:
return []
else:
triplets.append([0,0,0])
return triplets



triplets_set = set()

for i in range(len(nums)):
num_1 = nums[i]
sub_target = target - num_1
# #logging.debug(f"level_1_lookup: {lookup}")

for j in range(i+1, len(nums)):
num_2 = nums[j]
num_3 = sub_target - num_2
k = lookup.get(num_3) #
if k not in {None, i, j}: #don't reproduce itself
result = [num_1, num_2, num_3]
result.sort()
result = tuple(result)
triplets_set.add(result)

triplets = [list(t) for t in triplets_set]
return triplets


My solution gets this result:




Your runtime beats 28.86 % of python3 submissions.




Could anyone please give hints to improve?










share|improve this question









New contributor




Alice is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.







$endgroup$








  • 1




    $begingroup$
    Can you check the problem description? It is about pairs (a, b) which sum to 9, but the examples are about triples which sum to zero. – Btw, if you beat 28.86 of other submissions then you are slower 71.14 percent, not slower than 80 percent :)
    $endgroup$
    – Martin R
    Mar 26 at 5:48








  • 1




    $begingroup$
    As set is a common verb in English, try to avoid confusion: set is a Python built-in data type. (Grant me the favour and never call any amount of program source code "codes".) How could target: int == [0, 0, 0]?
    $endgroup$
    – greybeard
    Mar 26 at 6:31












  • $begingroup$
    amazing, better than leetcode's big data testing. @greybeard
    $endgroup$
    – Alice
    Mar 26 at 10:25










  • $begingroup$
    Ah, before I forget again: Congrats on asking for a review, for hints to improve instead of a turn-key solution, on (seemingly) trying to come up with a solution of your own instead of scraping the web/SE/leetcode. Way to learn!
    $endgroup$
    – greybeard
    yesterday














1












1








1





$begingroup$


I use a dummy solution to solve the leetcode 3Sum problem.



I employ the set data type to handle duplicates, then transform back to list.




Given an array nums of n integers, are there elements a, b, c in nums such that a + b + c = 0? Find all unique triplets in the array which gives the sum of zero.



Note:



The solution set must not contain duplicate triplets.



Example:



Given array nums = [-1, 0, 1, 2, -1, -4],



A solution set is:



[
[-1, 0, 1],
[-1, -1, 2]
]



My codes:



from typing import List
import logging
import unittest
import random
from collections import defaultdict,Counter

##logging.disable(level=#logging.CRITICAL)
##logging.basicConfig(level=#logging.DEBUG, format="%(levelname)s %(message)s")

class Solution:
def threeSum(self, nums, target: int=0) -> List[List[int]]:
"""
:type nums: List[int]
:type target: int
"""
if len(nums) < 3: return []

triplets = []
if target == [0, 0, 0]:
triplets.append([0, 0, 0])
return triplets # finish fast

lookup = {nums[i]:i for i in range(len(nums))} #overwrite from the high
if len(lookup) == 1:#assert one identical element
keys = [k for k in lookup.keys()]
if keys[0] != 0:
return []
else:
triplets.append([0,0,0])
return triplets



triplets_set = set()

for i in range(len(nums)):
num_1 = nums[i]
sub_target = target - num_1
# #logging.debug(f"level_1_lookup: {lookup}")

for j in range(i+1, len(nums)):
num_2 = nums[j]
num_3 = sub_target - num_2
k = lookup.get(num_3) #
if k not in {None, i, j}: #don't reproduce itself
result = [num_1, num_2, num_3]
result.sort()
result = tuple(result)
triplets_set.add(result)

triplets = [list(t) for t in triplets_set]
return triplets


My solution gets this result:




Your runtime beats 28.86 % of python3 submissions.




Could anyone please give hints to improve?










share|improve this question









New contributor




Alice is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.







$endgroup$




I use a dummy solution to solve the leetcode 3Sum problem.



I employ the set data type to handle duplicates, then transform back to list.




Given an array nums of n integers, are there elements a, b, c in nums such that a + b + c = 0? Find all unique triplets in the array which gives the sum of zero.



Note:



The solution set must not contain duplicate triplets.



Example:



Given array nums = [-1, 0, 1, 2, -1, -4],



A solution set is:



[
[-1, 0, 1],
[-1, -1, 2]
]



My codes:



from typing import List
import logging
import unittest
import random
from collections import defaultdict,Counter

##logging.disable(level=#logging.CRITICAL)
##logging.basicConfig(level=#logging.DEBUG, format="%(levelname)s %(message)s")

class Solution:
def threeSum(self, nums, target: int=0) -> List[List[int]]:
"""
:type nums: List[int]
:type target: int
"""
if len(nums) < 3: return []

triplets = []
if target == [0, 0, 0]:
triplets.append([0, 0, 0])
return triplets # finish fast

lookup = {nums[i]:i for i in range(len(nums))} #overwrite from the high
if len(lookup) == 1:#assert one identical element
keys = [k for k in lookup.keys()]
if keys[0] != 0:
return []
else:
triplets.append([0,0,0])
return triplets



triplets_set = set()

for i in range(len(nums)):
num_1 = nums[i]
sub_target = target - num_1
# #logging.debug(f"level_1_lookup: {lookup}")

for j in range(i+1, len(nums)):
num_2 = nums[j]
num_3 = sub_target - num_2
k = lookup.get(num_3) #
if k not in {None, i, j}: #don't reproduce itself
result = [num_1, num_2, num_3]
result.sort()
result = tuple(result)
triplets_set.add(result)

triplets = [list(t) for t in triplets_set]
return triplets


My solution gets this result:




Your runtime beats 28.86 % of python3 submissions.




Could anyone please give hints to improve?







python performance algorithm programming-challenge k-sum






share|improve this question









New contributor




Alice is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.











share|improve this question









New contributor




Alice is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.









share|improve this question




share|improve this question








edited yesterday









Toby Speight

26.8k742118




26.8k742118






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asked Mar 26 at 3:28









AliceAlice

2164




2164




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Alice is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
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New contributor





Alice is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.






Alice is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.








  • 1




    $begingroup$
    Can you check the problem description? It is about pairs (a, b) which sum to 9, but the examples are about triples which sum to zero. – Btw, if you beat 28.86 of other submissions then you are slower 71.14 percent, not slower than 80 percent :)
    $endgroup$
    – Martin R
    Mar 26 at 5:48








  • 1




    $begingroup$
    As set is a common verb in English, try to avoid confusion: set is a Python built-in data type. (Grant me the favour and never call any amount of program source code "codes".) How could target: int == [0, 0, 0]?
    $endgroup$
    – greybeard
    Mar 26 at 6:31












  • $begingroup$
    amazing, better than leetcode's big data testing. @greybeard
    $endgroup$
    – Alice
    Mar 26 at 10:25










  • $begingroup$
    Ah, before I forget again: Congrats on asking for a review, for hints to improve instead of a turn-key solution, on (seemingly) trying to come up with a solution of your own instead of scraping the web/SE/leetcode. Way to learn!
    $endgroup$
    – greybeard
    yesterday














  • 1




    $begingroup$
    Can you check the problem description? It is about pairs (a, b) which sum to 9, but the examples are about triples which sum to zero. – Btw, if you beat 28.86 of other submissions then you are slower 71.14 percent, not slower than 80 percent :)
    $endgroup$
    – Martin R
    Mar 26 at 5:48








  • 1




    $begingroup$
    As set is a common verb in English, try to avoid confusion: set is a Python built-in data type. (Grant me the favour and never call any amount of program source code "codes".) How could target: int == [0, 0, 0]?
    $endgroup$
    – greybeard
    Mar 26 at 6:31












  • $begingroup$
    amazing, better than leetcode's big data testing. @greybeard
    $endgroup$
    – Alice
    Mar 26 at 10:25










  • $begingroup$
    Ah, before I forget again: Congrats on asking for a review, for hints to improve instead of a turn-key solution, on (seemingly) trying to come up with a solution of your own instead of scraping the web/SE/leetcode. Way to learn!
    $endgroup$
    – greybeard
    yesterday








1




1




$begingroup$
Can you check the problem description? It is about pairs (a, b) which sum to 9, but the examples are about triples which sum to zero. – Btw, if you beat 28.86 of other submissions then you are slower 71.14 percent, not slower than 80 percent :)
$endgroup$
– Martin R
Mar 26 at 5:48






$begingroup$
Can you check the problem description? It is about pairs (a, b) which sum to 9, but the examples are about triples which sum to zero. – Btw, if you beat 28.86 of other submissions then you are slower 71.14 percent, not slower than 80 percent :)
$endgroup$
– Martin R
Mar 26 at 5:48






1




1




$begingroup$
As set is a common verb in English, try to avoid confusion: set is a Python built-in data type. (Grant me the favour and never call any amount of program source code "codes".) How could target: int == [0, 0, 0]?
$endgroup$
– greybeard
Mar 26 at 6:31






$begingroup$
As set is a common verb in English, try to avoid confusion: set is a Python built-in data type. (Grant me the favour and never call any amount of program source code "codes".) How could target: int == [0, 0, 0]?
$endgroup$
– greybeard
Mar 26 at 6:31














$begingroup$
amazing, better than leetcode's big data testing. @greybeard
$endgroup$
– Alice
Mar 26 at 10:25




$begingroup$
amazing, better than leetcode's big data testing. @greybeard
$endgroup$
– Alice
Mar 26 at 10:25












$begingroup$
Ah, before I forget again: Congrats on asking for a review, for hints to improve instead of a turn-key solution, on (seemingly) trying to come up with a solution of your own instead of scraping the web/SE/leetcode. Way to learn!
$endgroup$
– greybeard
yesterday




$begingroup$
Ah, before I forget again: Congrats on asking for a review, for hints to improve instead of a turn-key solution, on (seemingly) trying to come up with a solution of your own instead of scraping the web/SE/leetcode. Way to learn!
$endgroup$
– greybeard
yesterday










1 Answer
1






active

oldest

votes


















3












$begingroup$

Multi-part answer: [0) these preliminaries] 1) review of code presented 2) hints for improvement excluding personal, from programming over python and accepting a programming challenge to k-sum and leetcode 3Sum.



One general principle to follow is do as expected, in programming, it has been formulated in many guises, including Principle of Least Surprise. Every other route leaves you under pressure to justify, at risk of being misunderstood.



In coding, document, in the program source code:

What is "everything" there for?



Such rules often have been gathered into guide lines, for Python, follow the Style Guide for Python Code.






  • Instead of a docstring, your module starts with imports - most of them unused.


  • If your code mentioned leetcode, the presentation of a class Solution with just one function definition wouldn't beg justification.

  • the definition of threeSum() shows (a cute addition of target&default and) a curious mix of leetcode's templates for Python 2&3, lacking a proper docstring

  • comparing "the int" target to the list literal [0, 0, 0] is dangerous given Python's zeal to allow operations: do you know by heart when that evaluates to True?

    (Do you expect most every reader of your code to?)

    (Belatedly, it occurred to me that you may have intended to compare nums to [0, 0, 0] - bogus if target != 0)

  • verbosity -
    you can denote a tuple containing a single literal list like ([v, v, v],)

  • 2nd early out:

    with only one key→value in the dict, there's no need to access it:
    every key will equal nums[0]

    You need to check for 3*nums[0] != target

  • naming (Not your fault: Solution and threeSum are substandard.
    nums/_1-3 don't feel bad enough to change):

    - target, triplets, sub_target: right on!

    - given Python's "duck typing", I'd stick with triplets (, never introducing triplets_set)

    - lookup is a horrible name → value_to_index (or, in a suitably small context, just index)

    (- there's one thing wrong with k: it gets in the way when extending three_sum() to k_sum()…)


  • pythonic or not (or exploiting library functions, rather?):
    value_to_index = { value: index for index, value in enumerate(nums) }

    (same for for i, num_1 in enumerate(nums), for j, num_2 in enumerate(nums[i+1:], i+1))

  • commenting

    - you did comment, and I find half of the comments helpful

    - I don't get #overwrite from the high (that may just be me)

    - #don't reproduce itself: probably use any element/index once, at most rather than don't repeat an element/index

    - you did not comment the outer for loop, arguably the most profitable place:
    how is what the execution constructs a solution?:

    for each value, value_to_index keeps just the last index: how does this not prevent any valid triple to show up in the solution?

  • checking k: nice!

    (I'd go for in (None, i, j))


  • you don't provide a "tinker harness"



    if __name__ == '__main__':
    object_disoriented = Solution()
    print(object_disoriented.threeSum([-1, 0, 1, 2, -1, -4]))
    print(object_disoriented.threeSum([1, 1, 1], 3))





(Something else to follow is make (judicious) use of every help you can: if you use an IDE supporting Python, chances are it can help you with PEP8.)
(Running low on steam, this part will start more frugal than expected.)



Real Programming is the creation of a language that simplifies the solution of the problem at hand.



With Python providing most mechanisms needed in programming challenges, that leaves:




  • Code readably.

  • Create elements easy to use correctly.


I bickered you some about having a consistent problem description.

This is another place where Test First shines:

As long as you find yourself not knowing what to test, you are not in a position to implement anything, yet. (Inconsistencies in specification tend to stand out in test design & implementation.)



Programming challenges à la leetcode.com typically build on simpler challenges - you met 2sum, which puts you in a favourable position to tackle 3sum.

The performance part of these challenges is about not doing things over, not discarding knowledge more often than about algebraic insight.



The generic solution to 2sum is to take values and find the complement (1sum?).

The extension to k-sum is to split k into smaller numbers.



Ways to have information about the order of a set or sequence (say, elements) of instances of a type with ordering reusable is to have them ordered (ordered = sorted(elements)) or sorted (histogram = Counter(elements)).

For 2sum, you could search for target/2 and work inside-out.

For 3sum, one value will be no greater, another no smaller than both others. The third one will not "lie outside" the former two.






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    $begingroup$

    Multi-part answer: [0) these preliminaries] 1) review of code presented 2) hints for improvement excluding personal, from programming over python and accepting a programming challenge to k-sum and leetcode 3Sum.



    One general principle to follow is do as expected, in programming, it has been formulated in many guises, including Principle of Least Surprise. Every other route leaves you under pressure to justify, at risk of being misunderstood.



    In coding, document, in the program source code:

    What is "everything" there for?



    Such rules often have been gathered into guide lines, for Python, follow the Style Guide for Python Code.






    • Instead of a docstring, your module starts with imports - most of them unused.


    • If your code mentioned leetcode, the presentation of a class Solution with just one function definition wouldn't beg justification.

    • the definition of threeSum() shows (a cute addition of target&default and) a curious mix of leetcode's templates for Python 2&3, lacking a proper docstring

    • comparing "the int" target to the list literal [0, 0, 0] is dangerous given Python's zeal to allow operations: do you know by heart when that evaluates to True?

      (Do you expect most every reader of your code to?)

      (Belatedly, it occurred to me that you may have intended to compare nums to [0, 0, 0] - bogus if target != 0)

    • verbosity -
      you can denote a tuple containing a single literal list like ([v, v, v],)

    • 2nd early out:

      with only one key→value in the dict, there's no need to access it:
      every key will equal nums[0]

      You need to check for 3*nums[0] != target

    • naming (Not your fault: Solution and threeSum are substandard.
      nums/_1-3 don't feel bad enough to change):

      - target, triplets, sub_target: right on!

      - given Python's "duck typing", I'd stick with triplets (, never introducing triplets_set)

      - lookup is a horrible name → value_to_index (or, in a suitably small context, just index)

      (- there's one thing wrong with k: it gets in the way when extending three_sum() to k_sum()…)


    • pythonic or not (or exploiting library functions, rather?):
      value_to_index = { value: index for index, value in enumerate(nums) }

      (same for for i, num_1 in enumerate(nums), for j, num_2 in enumerate(nums[i+1:], i+1))

    • commenting

      - you did comment, and I find half of the comments helpful

      - I don't get #overwrite from the high (that may just be me)

      - #don't reproduce itself: probably use any element/index once, at most rather than don't repeat an element/index

      - you did not comment the outer for loop, arguably the most profitable place:
      how is what the execution constructs a solution?:

      for each value, value_to_index keeps just the last index: how does this not prevent any valid triple to show up in the solution?

    • checking k: nice!

      (I'd go for in (None, i, j))


    • you don't provide a "tinker harness"



      if __name__ == '__main__':
      object_disoriented = Solution()
      print(object_disoriented.threeSum([-1, 0, 1, 2, -1, -4]))
      print(object_disoriented.threeSum([1, 1, 1], 3))





    (Something else to follow is make (judicious) use of every help you can: if you use an IDE supporting Python, chances are it can help you with PEP8.)
    (Running low on steam, this part will start more frugal than expected.)



    Real Programming is the creation of a language that simplifies the solution of the problem at hand.



    With Python providing most mechanisms needed in programming challenges, that leaves:




    • Code readably.

    • Create elements easy to use correctly.


    I bickered you some about having a consistent problem description.

    This is another place where Test First shines:

    As long as you find yourself not knowing what to test, you are not in a position to implement anything, yet. (Inconsistencies in specification tend to stand out in test design & implementation.)



    Programming challenges à la leetcode.com typically build on simpler challenges - you met 2sum, which puts you in a favourable position to tackle 3sum.

    The performance part of these challenges is about not doing things over, not discarding knowledge more often than about algebraic insight.



    The generic solution to 2sum is to take values and find the complement (1sum?).

    The extension to k-sum is to split k into smaller numbers.



    Ways to have information about the order of a set or sequence (say, elements) of instances of a type with ordering reusable is to have them ordered (ordered = sorted(elements)) or sorted (histogram = Counter(elements)).

    For 2sum, you could search for target/2 and work inside-out.

    For 3sum, one value will be no greater, another no smaller than both others. The third one will not "lie outside" the former two.






    share|improve this answer









    $endgroup$


















      3












      $begingroup$

      Multi-part answer: [0) these preliminaries] 1) review of code presented 2) hints for improvement excluding personal, from programming over python and accepting a programming challenge to k-sum and leetcode 3Sum.



      One general principle to follow is do as expected, in programming, it has been formulated in many guises, including Principle of Least Surprise. Every other route leaves you under pressure to justify, at risk of being misunderstood.



      In coding, document, in the program source code:

      What is "everything" there for?



      Such rules often have been gathered into guide lines, for Python, follow the Style Guide for Python Code.






      • Instead of a docstring, your module starts with imports - most of them unused.


      • If your code mentioned leetcode, the presentation of a class Solution with just one function definition wouldn't beg justification.

      • the definition of threeSum() shows (a cute addition of target&default and) a curious mix of leetcode's templates for Python 2&3, lacking a proper docstring

      • comparing "the int" target to the list literal [0, 0, 0] is dangerous given Python's zeal to allow operations: do you know by heart when that evaluates to True?

        (Do you expect most every reader of your code to?)

        (Belatedly, it occurred to me that you may have intended to compare nums to [0, 0, 0] - bogus if target != 0)

      • verbosity -
        you can denote a tuple containing a single literal list like ([v, v, v],)

      • 2nd early out:

        with only one key→value in the dict, there's no need to access it:
        every key will equal nums[0]

        You need to check for 3*nums[0] != target

      • naming (Not your fault: Solution and threeSum are substandard.
        nums/_1-3 don't feel bad enough to change):

        - target, triplets, sub_target: right on!

        - given Python's "duck typing", I'd stick with triplets (, never introducing triplets_set)

        - lookup is a horrible name → value_to_index (or, in a suitably small context, just index)

        (- there's one thing wrong with k: it gets in the way when extending three_sum() to k_sum()…)


      • pythonic or not (or exploiting library functions, rather?):
        value_to_index = { value: index for index, value in enumerate(nums) }

        (same for for i, num_1 in enumerate(nums), for j, num_2 in enumerate(nums[i+1:], i+1))

      • commenting

        - you did comment, and I find half of the comments helpful

        - I don't get #overwrite from the high (that may just be me)

        - #don't reproduce itself: probably use any element/index once, at most rather than don't repeat an element/index

        - you did not comment the outer for loop, arguably the most profitable place:
        how is what the execution constructs a solution?:

        for each value, value_to_index keeps just the last index: how does this not prevent any valid triple to show up in the solution?

      • checking k: nice!

        (I'd go for in (None, i, j))


      • you don't provide a "tinker harness"



        if __name__ == '__main__':
        object_disoriented = Solution()
        print(object_disoriented.threeSum([-1, 0, 1, 2, -1, -4]))
        print(object_disoriented.threeSum([1, 1, 1], 3))





      (Something else to follow is make (judicious) use of every help you can: if you use an IDE supporting Python, chances are it can help you with PEP8.)
      (Running low on steam, this part will start more frugal than expected.)



      Real Programming is the creation of a language that simplifies the solution of the problem at hand.



      With Python providing most mechanisms needed in programming challenges, that leaves:




      • Code readably.

      • Create elements easy to use correctly.


      I bickered you some about having a consistent problem description.

      This is another place where Test First shines:

      As long as you find yourself not knowing what to test, you are not in a position to implement anything, yet. (Inconsistencies in specification tend to stand out in test design & implementation.)



      Programming challenges à la leetcode.com typically build on simpler challenges - you met 2sum, which puts you in a favourable position to tackle 3sum.

      The performance part of these challenges is about not doing things over, not discarding knowledge more often than about algebraic insight.



      The generic solution to 2sum is to take values and find the complement (1sum?).

      The extension to k-sum is to split k into smaller numbers.



      Ways to have information about the order of a set or sequence (say, elements) of instances of a type with ordering reusable is to have them ordered (ordered = sorted(elements)) or sorted (histogram = Counter(elements)).

      For 2sum, you could search for target/2 and work inside-out.

      For 3sum, one value will be no greater, another no smaller than both others. The third one will not "lie outside" the former two.






      share|improve this answer









      $endgroup$
















        3












        3








        3





        $begingroup$

        Multi-part answer: [0) these preliminaries] 1) review of code presented 2) hints for improvement excluding personal, from programming over python and accepting a programming challenge to k-sum and leetcode 3Sum.



        One general principle to follow is do as expected, in programming, it has been formulated in many guises, including Principle of Least Surprise. Every other route leaves you under pressure to justify, at risk of being misunderstood.



        In coding, document, in the program source code:

        What is "everything" there for?



        Such rules often have been gathered into guide lines, for Python, follow the Style Guide for Python Code.






        • Instead of a docstring, your module starts with imports - most of them unused.


        • If your code mentioned leetcode, the presentation of a class Solution with just one function definition wouldn't beg justification.

        • the definition of threeSum() shows (a cute addition of target&default and) a curious mix of leetcode's templates for Python 2&3, lacking a proper docstring

        • comparing "the int" target to the list literal [0, 0, 0] is dangerous given Python's zeal to allow operations: do you know by heart when that evaluates to True?

          (Do you expect most every reader of your code to?)

          (Belatedly, it occurred to me that you may have intended to compare nums to [0, 0, 0] - bogus if target != 0)

        • verbosity -
          you can denote a tuple containing a single literal list like ([v, v, v],)

        • 2nd early out:

          with only one key→value in the dict, there's no need to access it:
          every key will equal nums[0]

          You need to check for 3*nums[0] != target

        • naming (Not your fault: Solution and threeSum are substandard.
          nums/_1-3 don't feel bad enough to change):

          - target, triplets, sub_target: right on!

          - given Python's "duck typing", I'd stick with triplets (, never introducing triplets_set)

          - lookup is a horrible name → value_to_index (or, in a suitably small context, just index)

          (- there's one thing wrong with k: it gets in the way when extending three_sum() to k_sum()…)


        • pythonic or not (or exploiting library functions, rather?):
          value_to_index = { value: index for index, value in enumerate(nums) }

          (same for for i, num_1 in enumerate(nums), for j, num_2 in enumerate(nums[i+1:], i+1))

        • commenting

          - you did comment, and I find half of the comments helpful

          - I don't get #overwrite from the high (that may just be me)

          - #don't reproduce itself: probably use any element/index once, at most rather than don't repeat an element/index

          - you did not comment the outer for loop, arguably the most profitable place:
          how is what the execution constructs a solution?:

          for each value, value_to_index keeps just the last index: how does this not prevent any valid triple to show up in the solution?

        • checking k: nice!

          (I'd go for in (None, i, j))


        • you don't provide a "tinker harness"



          if __name__ == '__main__':
          object_disoriented = Solution()
          print(object_disoriented.threeSum([-1, 0, 1, 2, -1, -4]))
          print(object_disoriented.threeSum([1, 1, 1], 3))





        (Something else to follow is make (judicious) use of every help you can: if you use an IDE supporting Python, chances are it can help you with PEP8.)
        (Running low on steam, this part will start more frugal than expected.)



        Real Programming is the creation of a language that simplifies the solution of the problem at hand.



        With Python providing most mechanisms needed in programming challenges, that leaves:




        • Code readably.

        • Create elements easy to use correctly.


        I bickered you some about having a consistent problem description.

        This is another place where Test First shines:

        As long as you find yourself not knowing what to test, you are not in a position to implement anything, yet. (Inconsistencies in specification tend to stand out in test design & implementation.)



        Programming challenges à la leetcode.com typically build on simpler challenges - you met 2sum, which puts you in a favourable position to tackle 3sum.

        The performance part of these challenges is about not doing things over, not discarding knowledge more often than about algebraic insight.



        The generic solution to 2sum is to take values and find the complement (1sum?).

        The extension to k-sum is to split k into smaller numbers.



        Ways to have information about the order of a set or sequence (say, elements) of instances of a type with ordering reusable is to have them ordered (ordered = sorted(elements)) or sorted (histogram = Counter(elements)).

        For 2sum, you could search for target/2 and work inside-out.

        For 3sum, one value will be no greater, another no smaller than both others. The third one will not "lie outside" the former two.






        share|improve this answer









        $endgroup$



        Multi-part answer: [0) these preliminaries] 1) review of code presented 2) hints for improvement excluding personal, from programming over python and accepting a programming challenge to k-sum and leetcode 3Sum.



        One general principle to follow is do as expected, in programming, it has been formulated in many guises, including Principle of Least Surprise. Every other route leaves you under pressure to justify, at risk of being misunderstood.



        In coding, document, in the program source code:

        What is "everything" there for?



        Such rules often have been gathered into guide lines, for Python, follow the Style Guide for Python Code.






        • Instead of a docstring, your module starts with imports - most of them unused.


        • If your code mentioned leetcode, the presentation of a class Solution with just one function definition wouldn't beg justification.

        • the definition of threeSum() shows (a cute addition of target&default and) a curious mix of leetcode's templates for Python 2&3, lacking a proper docstring

        • comparing "the int" target to the list literal [0, 0, 0] is dangerous given Python's zeal to allow operations: do you know by heart when that evaluates to True?

          (Do you expect most every reader of your code to?)

          (Belatedly, it occurred to me that you may have intended to compare nums to [0, 0, 0] - bogus if target != 0)

        • verbosity -
          you can denote a tuple containing a single literal list like ([v, v, v],)

        • 2nd early out:

          with only one key→value in the dict, there's no need to access it:
          every key will equal nums[0]

          You need to check for 3*nums[0] != target

        • naming (Not your fault: Solution and threeSum are substandard.
          nums/_1-3 don't feel bad enough to change):

          - target, triplets, sub_target: right on!

          - given Python's "duck typing", I'd stick with triplets (, never introducing triplets_set)

          - lookup is a horrible name → value_to_index (or, in a suitably small context, just index)

          (- there's one thing wrong with k: it gets in the way when extending three_sum() to k_sum()…)


        • pythonic or not (or exploiting library functions, rather?):
          value_to_index = { value: index for index, value in enumerate(nums) }

          (same for for i, num_1 in enumerate(nums), for j, num_2 in enumerate(nums[i+1:], i+1))

        • commenting

          - you did comment, and I find half of the comments helpful

          - I don't get #overwrite from the high (that may just be me)

          - #don't reproduce itself: probably use any element/index once, at most rather than don't repeat an element/index

          - you did not comment the outer for loop, arguably the most profitable place:
          how is what the execution constructs a solution?:

          for each value, value_to_index keeps just the last index: how does this not prevent any valid triple to show up in the solution?

        • checking k: nice!

          (I'd go for in (None, i, j))


        • you don't provide a "tinker harness"



          if __name__ == '__main__':
          object_disoriented = Solution()
          print(object_disoriented.threeSum([-1, 0, 1, 2, -1, -4]))
          print(object_disoriented.threeSum([1, 1, 1], 3))





        (Something else to follow is make (judicious) use of every help you can: if you use an IDE supporting Python, chances are it can help you with PEP8.)
        (Running low on steam, this part will start more frugal than expected.)



        Real Programming is the creation of a language that simplifies the solution of the problem at hand.



        With Python providing most mechanisms needed in programming challenges, that leaves:




        • Code readably.

        • Create elements easy to use correctly.


        I bickered you some about having a consistent problem description.

        This is another place where Test First shines:

        As long as you find yourself not knowing what to test, you are not in a position to implement anything, yet. (Inconsistencies in specification tend to stand out in test design & implementation.)



        Programming challenges à la leetcode.com typically build on simpler challenges - you met 2sum, which puts you in a favourable position to tackle 3sum.

        The performance part of these challenges is about not doing things over, not discarding knowledge more often than about algebraic insight.



        The generic solution to 2sum is to take values and find the complement (1sum?).

        The extension to k-sum is to split k into smaller numbers.



        Ways to have information about the order of a set or sequence (say, elements) of instances of a type with ordering reusable is to have them ordered (ordered = sorted(elements)) or sorted (histogram = Counter(elements)).

        For 2sum, you could search for target/2 and work inside-out.

        For 3sum, one value will be no greater, another no smaller than both others. The third one will not "lie outside" the former two.







        share|improve this answer












        share|improve this answer



        share|improve this answer










        answered yesterday









        greybeardgreybeard

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