We use a dictionary seen to keep track of the number of times each number has appeared so far. For each number num in the array, we calculate its complement (req_sum - num). If this complement has been seen before, then it means there are pairs that sum up to req_sum, and we add the count of such complements to our count. Efficiency:
This approach processes each element of the array exactly once and performs operations in constant time for each element. Thus, the time complexity is π
(
π
)
O(n), where
π
n is the number of elements in the array.
Readability:
The code is more straightforward and easier to understand compared to generating combinations. It leverages hash maps for efficient lookups and counting.
Describe your change:
[ ] Add an algorithm?
[ ] Fix a bug or typo in an existing algorithm?
[ ] Add or change doctests? -- Note: Please avoid changing both code and tests in a single pull request.
[x] This pull request is all my own work -- I have not plagiarized.
[x] I know that pull requests will not be merged if they fail the automated tests.
[x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
[x] All new Python files are placed inside an existing directory.
[x] All filenames are in all lowercase characters with no spaces or dashes.
[x] All functions and variable names follow Python naming conventions.
[x] All function parameters and return values are annotated with Python type hints.
[x] All functions have doctests that pass the automated testing.
[x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
[x] If this pull request resolves one or more open issues then the description above includes the issue number(s) with a closing keyword: "Fixes #ISSUE-NUMBER".
Dictionary Usage:
We use a dictionary seen to keep track of the number of times each number has appeared so far. For each number num in the array, we calculate its complement (req_sum - num). If this complement has been seen before, then it means there are pairs that sum up to req_sum, and we add the count of such complements to our count. Efficiency:
This approach processes each element of the array exactly once and performs operations in constant time for each element. Thus, the time complexity is π ( π ) O(n), where π n is the number of elements in the array. Readability:
The code is more straightforward and easier to understand compared to generating combinations. It leverages hash maps for efficient lookups and counting.
Describe your change:
Checklist: