pytest-rng
Fixtures for seeding tests and making randomness reproducible
Decision gist · record as of 2026-08-14
Yes, if your test suite targets Python 3.5–3.7 and pytest versions from around 2019. The low install friction and permissive license make adoption straightforward. However, if you need modern Python versions or recent pytest support, verify compatibility first or seek an actively maintained alternative, since this package is abandoned.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires numpy and pytest as runtime dependencies; requires Python >=3.5.
- Low install friction with a pure-Python wheel.
- However, the package is abandoned—last release was August 8, 2019.
License · maintenance · safety
MIT license (permissive) — MIT license (permissive) places no restrictions on use, modification, or distribution in proprietary or open-source projects.
last release 2019-08-08 (2563 days)
0 known vulnerabilities (OSV.dev, 2026-08-14) · 156,336 downloads/mo, #10,786 on PyPI
Alternatives
Verify before relying
pip install pytest-rng
# In your test file:
import numpy as np
def test_example(rng, seed):
random_values = rng.uniform(-1, 1, size=3)
print(random_values) # Same output every run- Compatibility with pytest versions released after August 2019 and Python 3.8+
- Whether the numpy.random.mtrand.RandomState interface remains stable in current numpy versions
- Active maintenance or community forks addressing modern test framework changes
What it is and what it does
pytest-rng is a pytest plugin that provides two fixtures—`rng` and `seed`—to make random number generation deterministic and reproducible in tests. The `rng` fixture returns a pre-seeded NumPy RandomState object, while the `seed` fixture provides an integer seed value. Both derive their seeds by hashing the test's node ID combined with an optional salt string, ensuring the same random sequence runs every time unless you explicitly change the salt to test robustness across different seeds.
The package depends on numpy and pytest. It was released once on August 8, 2019 and has not been updated since, making it a stable but unmaintained tool. It is most useful for test suites that need reproducible randomness—such as machine learning or numerical computing tests—where you want to verify that random variations don't mask real bugs, yet still want to change seeds periodically to catch seed-dependent failures.
Use it for
- Ensure machine learning model tests produce identical results across runs for CI/CD pipelines
- Test numerical algorithms with reproducible random inputs while rotating seeds to catch fragile tests
- Verify stochastic simulations behave consistently without hardcoding seed values in test code
- Generate deterministic test data from random distributions without manual seed management
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if your test suite targets Python 3.5–3.7 and pytest versions from around 2019.
The low install friction and permissive license make adoption straightforward. However, if you need modern Python versions or recent pytest support, verify compatibility first or seek an actively maintained alternative, since this package is abandoned.
Install
pytest-rng on PyPI
Before you install
Low install friction with a pure-Python wheel. However, the package is abandoned—last release was August 8, 2019. No recent maintenance or updates, so compatibility with modern pytest or Python versions is unverified.
Requires numpy and pytest as runtime dependencies; requires Python >=3.5.
License in practice
MIT license (permissive) places no restrictions on use, modification, or distribution in proprietary or open-source projects.
Quickstart
pip install pytest-rng
# In your test file:
import numpy as np
def test_example(rng, seed):
random_values = rng.uniform(-1, 1, size=3)
print(random_values) # Same output every runVerify before relying
- Compatibility with pytest versions released after August 2019 and Python 3.8+
- Whether the numpy.random.mtrand.RandomState interface remains stable in current numpy versions
- Active maintenance or community forks addressing modern test framework changes
Package facts
| License | MIT license permissive |
| Python support | Supports the current Python release >=3.5 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 2 packagesnumpypytest |
| Maintenance | Abandoned 2,563 days since the last release |
| First released | |
| Downloads | 156,336 / month, #10,786 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 5 - Production/StableFramework :: PytestLicense :: OSI Approved :: MIT LicenseProgramming Language :: Python :: 3 :: OnlyProgramming Language :: Python :: 3.5Programming Language :: Python :: 3.6Programming Language :: Python :: 3.7 |
Evidence: pytest_rng-1.0.0-py3-none-any.whl
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