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Pytest-pyvista package

Project description

PyPI version Python versions GitHub Actions: Unit Testing and Deployment

Plugin to test PyVista plot outputs.

This pytest plugin was generated with Cookiecutter along with @hackebrot’s cookiecutter-pytest-plugin template.


This plugin facilitates the comparison of the images produced by PyVista. It generates a cache of images from the tests, using the PyVista plotting function in its first execution. Then, further executions will compare its results against this cache, so if there are any changes in the code that break the image generation, the comparison against the cache will notice it. Note that there is an error tolerance in the comparison, so minor differences won’t fail.


You must have a Python version greater than 3.7, as well as PyVista installed in your environment.

pyvista version >=0.37.0 and vtk version >=9.0.0 required.


You can install “pytest-pyvista” via pip from PyPI:

$ pip install pytest-pyvista


Once installed, you only need to use the command in your test. The plugin will automatically manage the cache generation if it does not exist, and the image comparison itself. Make sure you enable pv.OFF_SCREEN when loading PyVista, so the doesn’t pop up any window while testing. By default, the verify_image_cache fixture should be used for each test for image comparison:

import pyvista as pv
pv.OFF_SCREEN = True
def test_succeeds(verify_image_cache):
    pl = pyvista.Plotter()
    pl.add_mesh(pyvista.Sphere(), show_edges=True)

If most tests utilize this functionality, possibly restricted to a module, a wrapped version could be used:

def wrapped_verify_image_cache(verify_image_cache):
    return verify_image_cache

If you need to use any flag inside the tests, you can modify the verify_image_cache object in the test:

import pyvista as pv
pv.OFF_SCREEN = True
def test_succeeds(verify_image_cache):
    verify_image_cache.windows_skip_image_cache = True
    pl = pyvista.Plotter()
    pl.add_mesh(pyvista.Sphere(), show_edges=True)

Global flags

These are the flags you can use when calling pytest in the command line:

  • --reset_image_cache creates a new image for each test in tests/plotting/ and is not recommended except for testing or for potentially a major or minor release.

  • You can use --ignore_image_cache if you want to temporarily ignore regression testing, e.g. on a particular CI action.

  • When using --fail_extra_image_cache if there is an extra image in the cache, it will report as an error.

  • --generated_image_dir <DIR> dumps all generated test images into <DIR>.

  • --add_missing_images adds any missing images from the test run to the cache.

  • --image_cache_dir <DIR> sets the image cache dir. This will override any configuration, see below.

Test specific flags

These are attributes of verify_image_cache. You can set them as True if needed in the beginning of your test function.

  • high_variance_test: If necessary, the threshold for determining if a test will pass or not is incremented to another predetermined threshold. This is currently done due to the use of an unstable version of VTK, in stable versions this shouldn’t be necessary.

  • windows_skip_image_cache: For test where the plotting in Windows is different from MacOS/Linux.

  • macos_skip_image_cache: For test where the plotting in MacOS is different from Windows/Linux.

  • skip: If you have a test that plots a figure, but you don’t want to compare its output against the cache, you can skip it with this flag.


If using pyproject.toml or any other pytest configuration section, consider configuring your test directory location to avoid passing command line arguments when calling pytest, for example in pyproject.toml

image_cache_dir = "tests/plotting/image_cache"


Contributions are always welcome. Tests can be run with tox, please ensure the coverage at least stays the same before you submit a pull request.


Distributed under the terms of the MIT license, pytest-pyvista is free and open source software.


If you encounter any problems, please file an issue along with a detailed description.

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