ddt
Data-Driven/Decorated Tests
Decision gist · record as of 2026-08-14
Yes. ddt is a lightweight, dependency-free tool that solves a real unittest problem with a simple decorator pattern. It's stable, permissively licensed, and widely downloaded. The dormant maintenance status is not a concern for a mature utility with no external dependencies—there's little that needs updating. Install it if you use unittest and want to avoid writing repetitive parameterized test methods.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Installation is straightforward with no runtime dependencies.
- The project is dormant (last release 900 days ago) but the repository remains active and the package is stable at Beta status.
License · maintenance · safety
permissive license (permissive) — Licensed under MIT (permissive), so you can use it freely in commercial and open-source projects without restriction.
last release 2024-02-26 (900 days) · last repo commit 2024-07-16 · 442 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 1,611,131 downloads/mo, #3,719 on PyPI
Alternatives
Verify before relying
pip install ddt
import unittest
from ddt import ddt, data
@ddt
class TestExample(unittest.TestCase):
@data(1, 2, 3)
def test_value(self, value):
self.assertGreater(value, 0)- Whether ddt works with modern test frameworks beyond unittest (pytest, nose, etc.)
- Performance characteristics when running hundreds or thousands of parameterized test cases
What it is and what it does
ddt is a decorator-based test parameterization library for Python's unittest framework. It lets you write a single test method and run it repeatedly with different input data, with each dataset appearing as a separate test case in your test output. This eliminates the need to write multiple nearly-identical test methods or manually loop through test data within a single test.
The package has no runtime dependencies and installs as a pure Python wheel. It's been in Beta status since its first release in 2012 and receives infrequent updates, but the core functionality is stable and widely used. It integrates directly with unittest's test discovery and reporting, making parameterized tests visible in standard test runners.
Use it for
- Run the same test logic against multiple input datasets without duplicating test code
- Generate separate test results for each data variant to identify which inputs fail
- Test boundary conditions and edge cases by supplying a list of known problem values
- Reduce test file size when you have many similar test cases with only data differences
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
ddt is a lightweight, dependency-free tool that solves a real unittest problem with a simple decorator pattern. It's stable, permissively licensed, and widely downloaded. The dormant maintenance status is not a concern for a mature utility with no external dependencies—there's little that needs updating. Install it if you use unittest and want to avoid writing repetitive parameterized test methods.
Install
ddt on PyPI
Before you install
Installation is straightforward with no runtime dependencies. The project is dormant (last release 900 days ago) but the repository remains active and the package is stable at Beta status.
License in practice
Licensed under MIT (permissive), so you can use it freely in commercial and open-source projects without restriction.
Quickstart
pip install ddt
import unittest
from ddt import ddt, data
@ddt
class TestExample(unittest.TestCase):
@data(1, 2, 3)
def test_value(self, value):
self.assertGreater(value, 0)Verify before relying
- Whether ddt works with modern test frameworks beyond unittest (pytest, nose, etc.)
- Performance characteristics when running hundreds or thousands of parameterized test cases
Package facts
| License | permissive license permissive |
| Python support | Not specified |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | None |
| Maintenance | Dormant 900 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 1,611,131 / month, #3,719 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 4 - BetaIntended Audience :: DevelopersLicense :: OSI Approved :: MIT LicenseOperating System :: OS IndependentProgramming Language :: PythonProgramming Language :: Python :: 3Programming Language :: Python :: 3.10Programming Language :: Python :: 3.6Programming Language :: Python :: 3.7Programming Language :: Python :: 3.8Programming Language :: Python :: 3.9Topic :: Software Development :: Testing |
Evidence: ddt-1.7.2-py2.py3-none-any.whl
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