{"categories":[{"label":"Python Modules","url":"https://skillfed.io/packages/category/software-development-libraries-python-modules/12"},{"label":"Testing","url":"https://skillfed.io/packages/category/software-development-testing/3"}],"enrichment":{"capability":"Runs unittest test suites concurrently across multiple worker processes, distributing tests via round-robin or class-local partitioning to speed up test execution.","skillfed_tags":["test-parallelization","unittest-extension","performance-optimization"],"use_cases":["Speed up a large unittest suite that runs sequentially in 10+ seconds by distributing tests across CPU cores.","Run integration tests that are I/O-bound (database, network) in parallel to reduce total wall-clock time.","Preserve test class lifecycle (setUpClass/tearDownClass) while parallelizing by using partition_tests_by_class.","Distribute tests across a fixed number of worker processes (e.g., 4) to control resource usage on CI systems.","Benchmark test suite performance improvements by comparing sequential vs. concurrent execution times."],"what_it_does":"concurrencytest wraps the standard unittest TestSuite to run tests in parallel across multiple worker processes instead of sequentially. It uses fork-based process spawning and distributes individual tests or test classes to workers, defaulting to one process per CPU core. The package provides two partitioning strategies: round-robin (default) spreads tests evenly to avoid load imbalance, and class-local groups all tests from the same TestCase class onto a single worker to preserve setUpClass/tearDownClass semantics.\n\nThe package is designed for developers who want to speed up long-running test suites without rewriting their tests. It integrates directly with unittest's standard test loading and running infrastructure, so existing test code requires only a wrapper around the suite object. Dependencies on testtools and python-subunit provide the underlying test distribution and result aggregation machinery.","worth_installing":"Yes, if you use unittest and need faster test execution on Unix-like systems. Low install friction, active maintenance, no vulnerabilities, and straightforward integration make it a practical choice. No if you use Windows, pytest, or have a copyleft-incompatible license requirement. Yes-with-conditions if your tests depend on shared module state or require careful isolation\u2014verify that parallel execution doesn't break test assumptions."},"id":"concurrencytest","links":{"html":"https://skillfed.io/packages/concurrencytest","md":"https://skillfed.io/packages/concurrencytest.md","pypi":"https://pypi.org/project/concurrencytest/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-03-13","license_spdx":"GPL-2.0-or-later","license_treatment":"copyleft","name":"concurrencytest","python_support":"supports_current","summary":"Run unittest test suites concurrently"},"popularity":{"monthly_downloads":363276,"position":7224,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"0.1.11"}