Using mock_code
¶
mock_code
provides two components:
A command-line script
aiida-mock-code
(the mock executable) that is executed instead of the actual executable and acts as a cache for the outputs of the actual executableA pytest fixture
mock_code_factory()
that sets up an AiiDA InstalledCode pointing to the mock executable
In the following, we will set up a mock code for the diff
executable in three simple steps.
First, we want to define a fixture for our mocked code in the conftest.py
:
import os
import pytest
# Directory where to store outputs for known inputs (usually tests/data)
DATA_DIR = os.path.join(os.path.dirname(os.path.abspath(__file__)), 'data')
@pytest.fixture(scope='function')
def mocked_diff(mock_code_factory):
"""
Create mocked "diff" code
"""
return mock_code_factory(
label='diff',
data_dir_abspath=DATA_DIR,
entry_point='diff',
# files *not* to copy into the data directory
ignore_paths=('_aiidasubmit.sh', 'file*')
)
Second, we need to tell the mock executable where to find the actual diff
executable by creating a .aiida-test-cache-config.yml
file in the top level of our plugin.
Note
This step is needed only when we want to use the actual executable to (re)generate test data. As long as the mock code receives data inputs whose corresponding outputs have already been stored in the data directory, the actual executable is not used.
mock_code:
# code-label: absolute path
diff: /usr/bin/diff
Note
Why yet another configuration file?
The location of the actual executables will differ from one computer to the next, so hardcoding their location is not an option. Even the names of the executables may differ, making searching for executables in the PATH fragile. Finally, one could use dedicated environment variables to specify the locations of the executables, but there may be many of them, making this approach cumbersome. Ergo, a configuration file.
Finally, we can use our fixture in our tests as if it would provide a normal InstalledCode
:
def test_diff(mocked_diff):
# ... set up test inputs
inputs = {
'code': mocked_diff,
'parameters': parameters,
'file1': file1,
'file2': file2,
}
results, node = run_get_node(CalculationFactory('diff'), **inputs)
assert node.is_finished_ok
When running the test via pytest
for the first time, aiida-mock-code
will pipe through to the actual diff
executable.
The next time, it will recognise the inputs and directly use the outputs cached in the data directory.
Note
aiida-mock-code
“recognizes” calculations by computing a hash of the working directory of the calculation (as prepared by the calculation input plugin).
It does not rely on the hashing mechanism of AiiDA.
Running continuous integration (CI) tests on your repository:
Don’t forget to commit changes to your data directory to make the cache available on CI
Run tests on CI with
pytest --mock-fail-on-missing
to force a test failure when it fails when the committed cache is incomplete
Since the .aiida-test-cache-config.yml
file is usually specific to your machine, there is no need to commit it.
As long as the test cache is complete, tests will run fine without it, and if other developers need to change test inputs, they can easily regenerate a template for it using pytest --testing-config-action=generate
.
For further documentation on the pytest commandline options added by mock code, see:
$ pytest -h
...
custom options:
--testing-config-action=TESTING_CONFIG_ACTION
Read .aiida-test-cache-config.yml config file if present
('read'), require config file ('require') or generate
new config file ('generate').
--mock-regenerate-test-data
Regenerate test data.
--mock-fail-on-missing
Fail if cached data is not found, rather than regenerating it.
--mock-disable-mpi Run all calculations with `metadata.options.usempi=False`.
Limitations¶
No support for remote codes yet
Not tested with MPI