Optimize the Merge Sort

[30November]

Describe your change:

After reviewing the code, I noticed that while storing the sorted elements in the result one by one by comparing two lists, left and right, the pop() function was used to reduce the lines of code. I wanted to highlight a concern about the pop() function. In Python, the pop() function removes an element at a specified valid index from the list (defaulting to the last element if no index is provided). However, popping the first element has a time complexity of O(n) (where n is the length of the list), leading to additional time complexity and potentially creating a worst-case scenario for an already sorted list.

• 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.
• Documentation change?

Checklist:

• I have read 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".

[MrittikaDutta]

Docstring Edge Case Note
You could note in the main docstring that this implementation is not in-place and uses additional memory due to list slicing and merging.

[30November]

Docstring Edge Case Note You could note in the main docstring that this implementation is not in-place and uses additional memory due to list slicing and merging.

Yeah true
Actually, I am focusing on the time complexity (TC), rather than the space complexity (SC).
Anyhow, SC will remain O(n) weather it is using slicing or not.
Great that you have observed and analysis it in detail, earlier I also knew to this situation about using extra minimal space which can be avoid. But it doesn't harm the complexity mention inside the file by comment.

Thus, it is just about to spread knowledge that correctly matches with the practical (code) one.