Note about maintenance: This project is maintained and bug reports or pull requests will be addressed. There is little activity because it simply works and no changes are required.
This plugin allows you to specify one or several files/directories that are copied to a temporary directory (tmp_path) before the execution of the test. This means the original files are not modified and every test runs on its own version of the same files.
Files/directories can be specified either as strings or as pathlib.Path objects.
To take advantage of the datafiles fixture in a test function, add datafiles as one of the test function parameters (per usual with pytest fixtures) and decorate the test function with @pytest.mark.datafiles(file1, file2, dir1, dir2, ...). See the examples below.
The datafiles variable in your test function is a pathlib.Path object (tmp_path) where the copied files are located. Under Linux systems this will most likely be some subdirectory of /tmp/.
The following options can be specified as keyword arguments (kwargs) to the @pytest.mark.datafiles decorator function:
- keep_top_dir: For all parameters that represent directories, keep that directory instead of only (recursively) copying its content. Possible values are True or False. False is the default value.
on_duplicate: Specify the action to take when duplicate files/directories
are found. Possible values are: exception, ignore and replace. The
default value is exception.
- exception: An exception is raised instead of copying the duplicate file/directory.
- ignore: The second (or subsequent) files/directories with the same name as the first one are simply ignored (i.e., the first file/directory with the duplicate name is kept).
- replace: The second (or subsequent) files/directories with the same name replace the previous ones (i.e., the last file/directory with the duplicate name is kept).
See below for some examples.
pip install pytest-datafiles
Upgrade to 3.0
Version 3 now uses tmp_path, resulting in pathlib.Path objects instead of py.path.
Your tests may need to be adjusted. In examples/example_upgradev3.py you see some possible variations.
The full code with more details for the examples can be found in examples/.
One possible use case is when you are running tests on very big files that are not included or packaged with your tests. For example, your test files are large video files stored under /opt/big_files/ . You don't want your tests modifying the original files, but the files are required by the tests. You can reference these data files in your test method as follows:
# more details in `examples/example_1.py` @pytest.mark.datafiles('/opt/big_files/film1.mp4') def test_fast_forward(datafiles): # ...
Now for another use case: let's say in the directory where your tests are located, you place a directory named test_files. Here you have a lot of images you want to run tests on. By using this plugin, you make sure the original files under test_files are not modified by every test.
# more details in `examples/example_2.py` @pytest.mark.datafiles( FIXTURE_DIR / 'img1.jpg', FIXTURE_DIR / 'img2.jpg', FIXTURE_DIR / 'img3.jpg', ) def test_find_borders(datafiles): # ...
If all (or many) of your tests rely on the same files it can be easier to define one decorator beforehand and apply it to every test like this example:
# more details in `examples/example_3.py` ALL_IMGS = pytest.mark.datafiles( FIXTURE_DIR / 'img1.jpg', FIXTURE_DIR / 'img2.jpg', FIXTURE_DIR / 'img3.jpg', ) @ALL_IMGS def test_something1(datafiles): # ...
Imagine you have 3 directories (dir1, dir2, dir3) each containing the files (fileA and fileB).
This example clarifies the options on_duplicate and keep_top_dir.
You can also use a str paths.
# more details in `examples/example_5.py` @pytest.mark.datafiles( os.path.join(FIXTURE_DIR, 'img1.jpg'), os.path.join(FIXTURE_DIR, 'img2.jpg'), os.path.join(FIXTURE_DIR, 'img3.jpg'), ) def test_str(datafiles): # ...
Contributions are very welcome. Tests can be run with tox. Please ensure the coverage stays at least the same before you submit a pull request.
To create and upload a new package first update the version number and then:
pip3 install --user -U twine make clean make dist twine upload --repository-url https://test.pypi.org/legacy/ dist/* # Verify the package is usable virtualenv -p python3 test-venv test-venv/bin/pip install pytest test-venv/bin/pip install --index-url https://test.pypi.org/simple/ pytest-datafiles # Create some test_example.py (e.g. with one of the examples above) test-venv/bin/pytest test_example.py # Set the git tag for final release git tag -a 3.0 git push --tags # Upload the package for final release twine upload dist/*
Finally create a release on GitHub and add the packages from dist/* to it.
Of course this will only work if you have the necessary PyPI credentials for this package.
Distributed under the terms of the MIT license, "pytest-datafiles" is free and open source software.
If you encounter any problems, please file an issue along with a detailed description.