GreenLint: Energy-Aware Code Analyzer for Python
Maciej Wierzbicki, Mikołaj Magiera, Figen Ulusal, Radu Chiriac, Ibrahim Badr.
Group 9.
Paper.Source code.
GreenLint is a lightweight Python linter that detects energy-inefficient code patterns using static AST analysis. The tool focuses on common inefficiencies such as suboptimal loops, repeated operations, and non-vectorized data processing. Unlike existing tools that estimate overall energy consumption or focus on general code quality, GreenLint provides targeted, code-level feedback grounded in benchmark comparisons of inefficient and optimized implementations. By using runtime as a reproducible proxy for energy impact, the tool offers practical and interpretable insights without requiring specialized hardware measurements. GreenLint integrates seamlessly into existing development workflows and outputs linter-style warnings, including suggestions for improvement and an indicative energy impact score. Evaluation on both curated benchmarks and open-source repositories shows that the targeted patterns are consistently associated with higher runtime and occur in real-world code, although detection accuracy depends on context. The tool demonstrates how sustainability-oriented feedback can be incorporated into everyday software development.