parameterized

library0.9.0pypypi✓ verified 26d ago

Parameterized is a Python library that provides parameterized testing capabilities for various test frameworks like unittest, pytest, and nose. It simplifies writing data-driven tests by allowing the same test logic to be run with multiple sets of input data, reducing duplication and improving test coverage. The current version is 0.9.0, released in March 2023.

testing

pip install parameterized

github ↗package ↗

INSTALL

IMPORT

SIG · PARAMETERIZED

parameterized

testingpythonv0.9.0

Install

1.5s avg

Import

359ms

Disk

16MB

Pass rate

10/ 10

Env Coverage10 / 10

glibc

3.9–3.13

musl

3.9–3.13

Install & Compatibility

Where this runs

tested against v0.9.0 · pip install

no network on importno background threads

Install × environment matrix

Each cell = how many times install + import succeeded across repeated harness runs. Partial = flaky.
glibc = Debian/Ubuntu slim · musl = Alpine Linux

musl

py 3.10–3.95 runs

installs and imports cleanly · install 0.0s · import 0.388s · 17.9MB

glibc

py 3.10–3.95 runs

installs and imports cleanly · install 1.5s · import 0.330s · 18MB

16MB installed

● package 16MB

Code

Verified usage

Verified import paths — ran on the pinned version, not inferred.

parameterized

✓ from parameterized import parameterized

✗ from parametrized import parameterized

A common typo is to omit the 'e' from 'parameterized', leading to an ImportError or AttributeError.

param

✓ from parameterized import param

Used for more explicit parameter definitions, especially with keyword arguments.

parameterized_class

✓ from parameterized import parameterized_class

Used to parameterize an entire test class.

This quickstart demonstrates how to use `parameterized` with Python's built-in `unittest` framework. It shows examples for parameterizing individual test methods using `@parameterized` and `@parameterized.expand`, and how to parameterize an entire test class using `@parameterized_class`.

import unittest from parameterized import parameterized, param import math class TestMath(unittest.TestCase): @parameterized([ (2, 2, 4), (2, 3, 8), (1, 9, 1), (0, 9, 0), ]) def test_pow(self, base, exponent, expected): self.assertEqual(math.pow(base, exponent), expected) @parameterized.expand([ ("negative", -1.5, -2.0), ("integer", 1, 1.0), ("large fraction", 1.6, 1), ]) def test_floor(self, name, input_val, expected): self.assertEqual(math.floor(input_val), expected) @parameterized_class(('a', 'b', 'expected_sum'), [ (1, 2, 3), (5, 5, 10), ]) class TestMathClass(unittest.TestCase): def test_add(self): self.assertEqual(self.a + self.b, self.expected_sum) # To run these tests, you would typically use: # unittest.main(argv=['first-arg-is-ignored'], exit=False) # or a test runner like pytest/nose.

Debug

Known issues

breakingAs of version 0.9.0, `parameterized` has dropped support for Python 2.x, 3.5, and 3.6. If you require these Python versions, you must use an older version of `parameterized` (e.g., 0.8.1).

fix

Upgrade to Python 3.7+ or pin `parameterized` to version 0.8.1 or earlier.

affects: >=0.9.0

gotchaWhen combining `@parameterized` (or `@parameterized.expand`) with `@mock.patch`, the `@mock.patch` decorator must be placed *below* the `@parameterized` decorator. Additionally, the arguments introduced by `mock.patch` should appear *last* in the test method's signature. Incorrect ordering can lead to unexpected behavior or errors.

fix

Ensure `@mock.patch` is below `@parameterized` and mocked arguments are last in the function signature.

affects: All versions

gotchaIf you use an iterator or generator to supply parameters to `@parameterized` or `@parameterized.expand`, all items will be loaded into memory *before* the test run begins. This can be a significant memory concern for very large or infinite parameter sets.

fix

For very large datasets, consider generating test data on-the-fly within the test method itself, or exploring alternative parameterization methods suitable for streaming data if available within your test framework.

affects: All versions

gotchaA common pitfall is installing `parametrized` (missing the 'e') instead of `parameterized`. This will result in an `AttributeError: 'function' object has no attribute 'expand'` when trying to use `parameterized.expand`.

fix

Always ensure you install `parameterized` (with the 'e') via `pip install parameterized`.

affects: All versions

gotchaOvercomplicating parameterized test cases with excessive parameters or too many variations within a single test can lead to confusion, difficulty in maintenance, and unclear results. This defeats the purpose of parameterized testing.

fix

Keep test cases modular and focused. Break down complex scenarios into smaller, manageable tests. Each test should validate a specific aspect of functionality.

affects: All versions

breakingUsing `@parameterized` directly on a test method within a `unittest.TestCase` subclass will raise an exception. The library explicitly requires `@parameterized.expand` for parameterizing methods within `TestCase` subclasses.

fix

Replace `@parameterized` with `@parameterized.expand` when decorating test methods inside a `unittest.TestCase` subclass.

affects: All versions

breakingUsing the `@parameterized` decorator directly on a `unittest.TestCase` subclass will raise an `Exception`. The `@parameterized` decorator is designed for non-TestCase functions or classes. For parameterizing individual test methods within a `unittest.TestCase` subclass, you must use `@parameterized.expand`.

fix

When parameterizing tests within a `unittest.TestCase` subclass, apply `@parameterized.expand` to the specific test method, rather than using `@parameterized` on the class itself.

affects: All versions

Errors

Common errors & fixes

AttributeError: 'function' object has no attribute 'expand'

This error typically occurs when the incorrect package `parametrized` (missing the 'e') is installed instead of the correct `parameterized` library.

fix

Uninstall the wrong package (`pip uninstall parametrized`) and install the correct one (`pip install parameterized`).

ImportError: cannot import name 'parameterized_class'

This happens when `parameterized_class` is not directly exposed for import from the top-level `parameterized` package, or due to an older version of the library not exposing it directly.

fix

Ensure you are using a recent version of the library (0.9.0 or later) and import it as `from parameterized import parameterized_class`. If the issue persists, explicitly import from the submodule `from parameterized.parameterized import parameterized_class` if the library structure changed or you are on an older version.

ModuleNotFoundError: No module named 'parameterized'

The `parameterized` library is not installed in the Python environment being used.

fix

Install the library using pip: `pip install parameterized`.

UnboundLocalError: local variable 'patching' referenced before assignment

This error often arises when combining `@parameterized.expand` with `unittest.mock.patch` decorators and their order is incorrect, as the `patch` decorator must come *below* `parameterized.expand` to function properly.

fix

Ensure that the `@mock.patch(...)` decorator is placed *below* the `@parameterized.expand(...)` decorator. Also, the mocked parameters must come last in the test method's signature.

Upgrade

Version history

0.9.0latest on PyPI · released Mar 27, 2023

Audit

Dependencies

pythonrequiredRequires Python 3.7 or newer.

Agent activity

24 hits · last 30 days

node

Resources

githubhttps://github.com/wolever/parameterized ↗

packagehttps://pypi.org/project/parameterized/ ↗