pytest-incremental 0.2.0

pytest-incremental

an incremental test runner (pytest plug-in)

What is an “incremental test runner” ?

The idea is to execute your tests faster by executing not all of them but only the “required” ones.

When talking about build-tools it is common to refer to the terms:

• initial (full) build - all files are compiled

• incremental build (or partial rebuild) - just changed files are compiled

• no-op build - no files are compiled (none changed since last execution)

So an “incremental test runner” will only re-execute tests that were affected by changes in the source code since last successful execution.

How it works ?

pytest-incremental is a pytest plug-in. So if you can run your test suite with pytest you can use pytest-incremental.

Note that pytest has support to run standard unittest’s and nose’s tests. So even if you don’t use pytest as a test framework you might be able to use it as a test runner.

The plug-in will analyze your python source files and through its imports define the dependencies of the modules. doit is used to keep track of the dependencies and save results. The plug-in will modify how pytest collect your tests. pytest do the rest of the job of actually running the tests and reporting the results.

Install

pytest-incremental is tested on python 2.6, 2.7.

pip install pytest-incremental`

python setup.py install

Usage

Just pass the parameter --incremental when calling from the command line:

$ py.test --incremental

You can also enable it by default adding the following line to your pytest.ini:

[pytest]
addopts = --incremental

$ py.test --incremental --watch-pkg my_lib --watch-pkg ../py3rd-trunk/py3rd

$ py.test  tests/test_foo.py

$ py.test --incremental --watch-pkg my_lib tests/test_foo.py

$ py.test --list-dependencies

$ py.test --graph-dependencies
$ dot -Tpng -o imports.png imports.dot

$ py.test --list-outdated

Limitations

pytest-incremental looks for imports recursively to find dependencies (using AST). But given the very dynamic nature of python there are still some cases that a module can be affected by a module that are not detected.

• from package import * modules imported from __all__ in a package are not counted as a dependency

• modules imported not using the import statement

• modules not explicitly imported but used at run-time (i.e. conftest.py when running your tests with pytest)

• monkey-patching. (i.e. A imports X. B monkey-patches X. In this case A might depend on B)

• others ?

Project Details

• Project code + issue track on bitbucket

• Discussion group