Running and writing tests#


This document assumes you are working from an in-development checkout of Python. If you are not then some things presented here may not work as they may depend on new features not available in earlier versions of Python.


The shortest, simplest way of running the test suite is the following command from the root directory of your checkout (after you have built Python):

./python -m test
./python.exe -m test

This works on most macOS systems.

.\python.bat -m test

This will run the majority of tests, but exclude a small portion of them; these excluded tests use special kinds of resources: for example, accessing the Internet, or trying to play a sound or to display a graphical interface on your desktop. They are disabled by default so that running the test suite is not too intrusive. To enable some of these additional tests (and for other flags which can help debug various issues such as reference leaks), read the help text:

./python -m test -h
./python.exe -m test -h
.\python.bat -m test -h

If you want to run a single test file, simply specify the test file name (without the extension) as an argument. You also probably want to enable verbose mode (using -v), so that individual failures are detailed:

./python -m test -v test_abc
./python.exe -m test -v test_abc
.\python.bat -m test -v test_abc

To run a single test case, use the unittest module, providing the import path to the test case:

./python -m unittest -v test.test_abc.TestABC_Py
./python.exe -m unittest -v test.test_abc.TestABC_Py
.\python.bat -m unittest -v test.test_abc.TestABC_Py

Some test modules also support direct invocation, which might be useful for IDEs and local debugging:

./python Lib/test/
./python.exe Lib/test/
.\python.bat Lib/test/

But, there are several important notes:

  1. This way of running tests exists only for local developer needs and is discouraged for anything else

  2. Some modules do not support it at all. One example is test_importlib. In other words: if some module does not have unittest.main(), then most likely it does not support direct invocation.

If you have a multi-core or multi-CPU machine, you can enable parallel testing using several Python processes so as to speed up things:

./python -m test -j0
./python.exe -m test -j0
.\python.bat -m test -j0

If you are running a version of Python prior to 3.3 you must specify the number of processes to run simultaneously (e.g. -j2).

Finally, if you want to run tests under a more strenuous set of settings, you can run test as:

./python -bb -E -Wd -m test -r -w -uall
./python.exe -bb -E -Wd -m test -r -w -uall
.\python.bat -bb -E -Wd -m test -r -w -uall

The various extra flags passed to Python cause it to be much stricter about various things (the -Wd flag should be -W error at some point, but the test suite has not reached a point where all warnings have been dealt with and so we cannot guarantee that a bug-free Python will properly complete a test run with -W error). The -r flag to the test runner causes it to run tests in a more random order which helps to check that the various tests do not interfere with each other. The -w flag causes failing tests to be run again to see if the failures are transient or consistent. The -uall flag allows the use of all available resources so as to not skip tests requiring, e.g., Internet access.

To check for reference leaks (only needed if you modified C code), use the -R flag. For example, -R 3:2 will first run the test 3 times to settle down the reference count, and then run it 2 more times to verify if there are any leaks.

You can also execute the Tools/scripts/ script as found in a CPython checkout. The script tries to balance speed with thoroughness. But if you want the most thorough tests you should use the strenuous approach shown above.

Locale support#

Some tests require specific locales to run successfully. These locales are often non-default, non-English, non-UTF-8 locales. If a necessary locale is unavailable, the test is skipped or runs in the dry-run mode. Additional locales that you may find helpful to set up on developer’s machines or buildbots include:

  • en_US (en_US.utf8, en_US.iso88591) — the standard default

  • de_DE (de_DE.UTF-8) or fr_FR (fr_FR.utf8, fr_FR.iso88591, fr_FR.iso885915@euro) — common non-English locales

  • tr_TR (tr_TR.iso88599) — Turkish has different rules for upper/lower cases of “i” and “I”.

  • ps_AF — used in test_decimal

On Linux and macOS, the locale command can be used to list available locales and change the settings. Environment variables LANG and those prefixed with LC_ can be used to set the locale.

Unexpected skips#

Sometimes when running the test suite, you will see “unexpected skips” reported. These represent cases where an entire test module has been skipped, but the test suite normally expects the tests in that module to be executed on that platform.

Often, the cause is that an optional module hasn’t been built due to missing build dependencies. In these cases, the missing module reported when the test is skipped should match one of the modules reported as failing to build when Compile and build.

In other cases, the skip message should provide enough detail to help figure out and resolve the cause of the problem (for example, the default security settings on some platforms will disallow some tests)


Writing tests for Python is much like writing tests for your own code. Tests need to be thorough, fast, isolated, consistently repeatable, and as simple as possible. We try to have tests both for normal behaviour and for error conditions. Tests live in the Lib/test directory, where every file that includes tests has a test_ prefix.

One difference with ordinary testing is that you are encouraged to rely on the module. It contains various helpers that are tailored to Python’s test suite and help smooth out common problems such as platform differences, resource consumption and cleanup, or warnings management. That module is not suitable for use outside of the standard library.

When you are adding tests to an existing test file, it is also recommended that you study the other tests in that file; it will teach you which precautions you have to take to make your tests robust and portable.

For tests of the C API, see Tests sections in Changing Python’s C API.


Benchmarking is useful to test that a change does not degrade performance.

The Python Benchmark Suite has a collection of benchmarks for all Python implementations. Documentation about running the benchmarks is in the README.txt of the repo.