Loop Anti-Pattern Linter: Turn Slow Python Loops Into Ranked Fixes

Pipeline Architecture

Most performance bugs in Python are obvious only after profiling, and by then they are already production incidents. This linter shifts that left by finding common loop anti-patterns statically and ranking them by projected impact.

Instead of dumping flat warnings, it gives you a practical order of operations: fix the highest estimated slowdown first, then move down the list if needed.

What It Detects

Nested loops over the same iterable
String concatenation in loops
List membership tests inside loops
append patterns that are better expressed as comprehensions
len() use in loop guards where precomputation helps

Run the Project

git clone https://github.com/dakshjain-1616/Loop-Anti-Pattern-Linter
cd Loop-Anti-Pattern-Linter
pip install -r requirements.txt

python loop_antipattern_lint.py ./src
python loop_antipattern_lint.py ./src --json
python loop_antipattern_lint.py ./src --min-slowdown 30
OPENROUTER_API_KEY=sk-or-... python loop_antipattern_lint.py ./src --explain

The --explain mode can call OpenRouter to add human-readable context for each finding, which helps when onboarding developers who are less familiar with algorithmic complexity.

Architecture Walkthrough

The loop anti pattern linter repository is organized around a clear pipeline, so you can trace the full flow from input handling to final output without guesswork. This makes onboarding easier for new contributors and helps teams debug faster when behavior changes after updates.

Practical Use Cases

If you are evaluating loop anti pattern linter for production, start with a small real-world dataset, run the included commands end to end, and compare output quality, latency, and operational complexity. This gives a practical signal that is stronger than a toy demo.

Implementation Notes

The project is useful as both a standalone tool and a reference implementation. You can copy patterns from this codebase into your own stack, especially around evaluation discipline, reproducibility, and operator visibility.

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