{"categories":[{"label":"Libraries","url":"https://skillfed.io/packages/category/software-development-libraries/3"},{"label":"Python Modules","url":"https://skillfed.io/packages/category/software-development-libraries-python-modules/5"}],"enrichment":{"capability":"Yappi is a deterministic profiler for Python that tracks CPU and wall-clock time across multithreaded, asyncio, and gevent applications, reporting per-function and per-thread statistics.","skillfed_tags":["profiling","concurrency","performance-analysis"],"use_cases":["Profile multithreaded applications to find which threads and functions consume the most CPU or wall time","Measure asyncio coroutine performance and identify context-switch overhead in async code","Profile gevent greenlet applications to track per-greenlet execution time and call counts","Export profiling results to callgrind format for visualization in kcachegrind or other analysis tools","Continuously profile long-running services by starting and stopping yappi on demand without restarting the application"],"what_it_does":"Yappi is a tracing profiler written in C that measures both CPU time and wall-clock time in Python programs. Unlike the standard library's cProfile, it is designed from the ground up to handle multithreaded applications, asyncio coroutines, and gevent greenlets, allowing you to start, stop, and retrieve profiling results at any point from any thread. It reports statistics per function and per thread, and can export results in callgrind or pstat formats for analysis in external tools.\n\nYou use yappi by calling start() before your code runs, then calling get_func_stats() or get_thread_stats() to retrieve results. It supports filtering and sorting by module, function name, or custom callbacks, making it practical for identifying bottlenecks in complex concurrent applications where standard profilers either fail or produce misleading timings.","worth_installing":"Yes, if you need to profile multithreaded, asyncio, or gevent applications. Yappi is the standard choice for these workloads because the standard library profilers do not handle them correctly. If you only profile single-threaded code, cProfile is simpler. No security vulnerabilities are known, maintenance is active, and the MIT license poses no restrictions."},"id":"yappi","links":{"html":"https://skillfed.io/packages/yappi","md":"https://skillfed.io/packages/yappi.md","pypi":"https://pypi.org/project/yappi/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-03-17","license_spdx":null,"license_treatment":"permissive","name":"yappi","python_support":"supports_current","summary":"Yet Another Python Profiler"},"popularity":{"monthly_downloads":4257062,"position":2346,"tier":"top_5000"},"security":{"n_vulnerabilities":0},"version":"1.7.6"}