Optimize ASCII lowercase conversion performance by Miladkhoshdel · Pull Request #15203 · TheAlgorithms/Python · GitHub
Skip to content

Optimize ASCII lowercase conversion performance - #15203

Open
Miladkhoshdel wants to merge 1 commit into
TheAlgorithms:masterfrom
Miladkhoshdel:perf/optimize-lower
Open

Optimize ASCII lowercase conversion performance#15203
Miladkhoshdel wants to merge 1 commit into
TheAlgorithms:masterfrom
Miladkhoshdel:perf/optimize-lower

Conversation

@Miladkhoshdel

Copy link
Copy Markdown
Contributor

Describe your change:

Improve the performance of the existing ASCII lowercase conversion by replacing the generator expression with an explicit loop.

The updated implementation:

  • Computes each character's ASCII value only once.
  • Uses module-level constants for the ASCII uppercase range and case offset to improve readability and avoid magic numbers.
  • Builds the result using a list and joins it at the end.
  • Preserves the existing behavior and doctests.

Benchmark using:

python -m timeit \
  -s "from strings.lower import lower; s = 'Hello WORLD 123!' * 1000" \
  "lower(s)"

Results on my machine:

  • Previous implementation: ~1.08 ms per loop
  • Updated implementation: ~772 µs per loop
  • Runtime reduction: ~28.5%
  • 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".

@algorithms-keeper algorithms-keeper Bot added awaiting reviews This PR is ready to be reviewed enhancement This PR modified some existing files labels Sep 6, 2026
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment

Labels

awaiting reviews This PR is ready to be reviewed enhancement This PR modified some existing files

Projects

None yet

Development

Successfully merging this pull request may close these issues.

1 participant