Testfixtures

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Testfixtures is a collection of helpers and mock objects that are useful when writing automated tests in Python.

The areas of testing this package can help with are listed below:

Comparing, asserting equality and explaining differences

The compare function gives readable feedback when results aren’t as expected, with clear diffs for deeply nested data structures and for objects that don’t normally support comparison. This includes first-class support for pandas and polars dataframes and numpy arrays. Flexible placeholder objects and helpers such as like, sequence, generator, Comparison, RoundComparison, RangeComparison, StringComparison and SequenceComparison let you assert that only part of a value matters, that a number is within a range or rounded to a precision, or that a string matches a pattern.

Mocking out objects and methods

Replacer makes it easy to swap out objects, classes or individual methods for the duration of a test, restoring the originals automatically when it ends. You point them at the thing being replaced directly rather than at a dotted string, so your type checker verifies the target and the replacement survives refactoring. replace_on_class, replace_in_module and replace_in_environ cover common cases such as methods, module globals and environment variables.

Mocking dates and times

mock_datetime, mock_date and mock_time are drop-in replacements for the datetime and time APIs, for testing code that depends on the current date or time. They cover the thorny issues of timezones, non-uniform sequences of mock time increments, explicit ticking and freezing a point in time so you don’t have to invent them from scratch.

Testing subprocesses

MockPopen lets you test code that uses subprocess.Popen without running real processes.

Testing command-line scripts

Command drives entry-point scripts end to end and checks their output, logging, mock calls and return code.

Testing logging

LogCapture captures log messages so you can check what was logged is what you expected, including from the loguru and structlog libraries.

Testing stream output

OutputCapture captures stream output, such as that from print calls or even writes made directly to file descriptors, and makes it easy to assert about.

Testing with files and directories

TempDirectory gives you a sandboxed directory to work in. It makes it easy to read and write files, serialise and deserialise structured data in formats such as JSON, YAML and TOML, create directory trees, and assert on the contents of both individual files and whole directories.

Testing exceptions and warnings

ShouldRaise, ShouldAssert, ShouldWarn and ShouldNotWarn check that a particular exception is raised, that an assertion fails with a particular message, or that a warning is issued, down to the parameters involved.

Testing when using Django

Helpers for comparing instances of Django models.

Testing when using Twisted

Helpers for making assertions about logging when using Twisted.

The sections below describe the use of the various tools included:

If you’re looking for a description of a particular tool, please see the API reference:

For details of how to install the package or get involved in its development, please see the sections below:

Indices and tables