{"categories":[{"label":"Software Development","url":"https://skillfed.io/packages/category/software-development/8"},{"label":"Debuggers","url":"https://skillfed.io/packages/category/software-development-debuggers"}],"enrichment":{"capability":"Scalene profiles Python code to measure CPU, GPU, and memory consumption at the line level, and can generate AI-powered optimization suggestions for identified bottlenecks.","skillfed_tags":["performance-profiling","ai-assisted-optimization","gpu-profiling"],"use_cases":["Identify CPU and memory bottlenecks in data science pipelines and get AI-suggested rewrites before optimization effort","Profile GPU-accelerated code to see where computation time is spent and detect memory leaks on device","Integrate profiling into CI/CD to catch performance regressions at the line level across Python versions","Debug slow web services or batch jobs by profiling specific functions with the @profile decorator","Generate shareable performance reports as self-contained HTML files for code review and documentation"],"what_it_does":"Scalene is a sampling-based profiler that measures CPU, GPU, and memory usage in Python programs at the line and function level. Unlike traditional profilers that instrument code or rely on Python's tracing hooks, Scalene uses sampling to keep overhead low while delivering detailed per-line breakdowns of where execution time and memory are consumed. It runs on macOS, Linux, and Windows, supports modern Python versions (3.8\u20133.14), and integrates with Jupyter, IPython, and VS Code.\n\nThe package's distinguishing feature is AI-powered optimization suggestions: after profiling, users can click on specific lines or code regions to request optimization proposals from GPT-4, Azure, Amazon Bedrock, or local models via Ollama. Results are displayed in an interactive web-based GUI (or CLI) that works fully offline. Configuration is flexible\u2014via command-line flags, YAML files, or programmatic decorators\u2014making it suitable for one-off profiling runs and integrated performance monitoring in development workflows.","worth_installing":"Yes. Scalene is actively maintained, well-established (13k+ GitHub stars, top 15k PyPI packages), carries no known vulnerabilities, and solves a real problem\u2014low-overhead, detailed profiling with AI-assisted optimization. The 9 runtime dependencies are standard and widely available. Install friction is moderate but manageable. Recommended for developers who need to understand and optimize Python performance without high profiling overhead."},"id":"scalene","links":{"html":"https://skillfed.io/packages/scalene","md":"https://skillfed.io/packages/scalene.md","pypi":"https://pypi.org/project/scalene/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-05-12","license_spdx":null,"license_treatment":"permissive","name":"scalene","python_support":"supports_current","summary":"Scalene: A high-resolution, low-overhead CPU, GPU, and memory profiler for Python with AI-powered optimization suggestions"},"popularity":{"monthly_downloads":396130,"position":6972,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"2.3.0"}