Fix kahns algo sparse vertex performance

[Kanika0306]

Describe your change:

• Fixes the O(N) queue operation caused by list.pop(0) by using collections.deque and queue.popleft(), ensuring constant-time dequeue operations and preserving the expected O(V + E) time complexity of Kahn's topological sort algorithm.

• Fixes an IndexError for sparse/non-contiguous integer vertex IDs by changing indegree from a list to a dictionary keyed by the graph vertices.

• Adds doctests covering topological sorting with sparse/non-contiguous integer vertex IDs.

• Adds doctests covering cycle detection with non-contiguous vertex IDs.

• Add an algorithm?

• Fix a bug or typo in an existing algorithm?

• Add or change doctests?

• Documentation change?

Checklist:

• I have read https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md.
• This pull request is all my own work -- I have not plagiarized.
• I know that pull requests will not be merged if they fail the automated tests.
• This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
• All new Python files are placed inside an existing directory.
• All filenames are in all lowercase characters with no spaces or dashes.
• All functions and variable names follow Python naming conventions.
• All function parameters and return values are annotated with Python type hints.
• All functions have doctests that pass the automated testing.
• All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
• 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>".

Fixes #15071

[Copilot]

Copilot was unable to review this pull request because the user who requested the review has reached their quota limit.

[Kanika0306]

@cclauss kindly review

[Kanika0306]

@cclauss kindly review

[Kanika0306]

@mindaugl
could you kindly review this pr
Thankyou

[cclauss]

Please add a benchmark that proves that the proposed modification could save significant runtime.

[Kanika0306]

Please add a benchmark that proves that the proposed modification could save significant runtime.

Sure I will do that

[cclauss]

What are the benchmark results on your machine?

[Kanika0306]

What are the benchmark results on your machine?

Here are the benchmark results on my machine comparing the pre-optimization implementation (list.pop(0)) against the current implementation (deque.popleft()) for topological_sort() on a 30,000-vertex DAG across 5 runs:

Benchmark results for topological_sort with 30000 vertices over 5 runs:

Pre-optimization (list.pop(0)): 0.29597 seconds
Current (deque.popleft): 0.04935 seconds

Speedup ratio: 6.00x faster

The benchmark directly measures topological_sort() on the exact same graph input and programmatically asserts that both implementations return valid, complete topological sorts.