---
id: concurrencytest
version: "0.1.11"
license: GPL-2.0-or-later
license_treatment: copyleft
maintenance: active
---

# concurrencytest — Run unittest test suites concurrently

License: copyleft · Maintenance: active · Downloads: 363.3K/mo

## What it is and 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.

The 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.

Use it for:

- 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.

## Worth the install?

AI-flagged interpretation of the facts above — verify before relying.

Runs unittest test suites concurrently across multiple worker processes, distributing tests via round-robin or class-local partitioning to speed up test execution.

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—verify that parallel execution doesn't break test assumptions.

## Install

pip install concurrencytest
uv add concurrencytest
poetry add concurrencytest

## Installing concurrencytest

Before you install: Low install friction; pure Python wheel with only two runtime dependencies (testtools and python-subunit). Actively maintained with recent commits and no known vulnerabilities.

License in practice: GPL-2.0-or-later (copyleft) means any code that links this package must be distributed under compatible terms. Acceptable for internal tools and open-source projects, but problematic for proprietary software.

Quickstart:

import unittest
from concurrencytest import ConcurrentTestSuite

suite = unittest.defaultTestLoader.loadTestsFromTestCase(MyTestCase)
concurrent_suite = ConcurrentTestSuite(suite)
unittest.TextTestRunner().run(concurrent_suite)

Requires Unix-like OS with os.fork() support (Linux, macOS, BSD); does not work on Windows. Requires Python 3.10 or later.

Verify before relying:

- Whether test isolation is guaranteed when tests share module-level state or fixtures across worker processes.
- Performance characteristics with very large test suites or tests with significant setup/teardown overhead.
- Compatibility with pytest or other test runners beyond unittest.

## Package facts

- License: GPL-2.0-or-later (copyleft)
- Python support: supports_current
- Install friction: low
- Maintenance: active
- Downloads: 363.3K/month (top 15,000 on PyPI)
- Known vulnerabilities: none known

## Tags

parallel unittest execution, concurrent test runner, unittest multiprocess, speed up test suite, distributed test execution, fork-based test parallelization, unittest load balancing, test-parallelization, unittest-extension, performance-optimization

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