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- Astroquery Testing

# Astroquery Testing

Testing in astroquery is a bit more complicated than in other modules since we depend on remote servers to supply data. In order to keep the tests green and fast, we use monkeypatching to test most functions on local copies of the data.

In order to set up testing for any given module, you therefore need to have local copies of the data.

The testing directory structure should look like:

    module/tests/__init__.py
    module/tests/test_module.py
    module/tests/test_module_remote.py
    module/tests/setup_package.py
    module/tests/data/
    module/tests/data/test_data.xml

## `test_module.py`

This file should contain only tests that do not require an internet connection. It also contains the tricky monkeypatching components. At a minimum, monkeypatching requires a few methods that are defined locally in the test file for each module.

### Monkeypatching

At a minimum, monkeypatching will require these changes:

    class MockResponse(object):

        def __init__(self, content):
            self.content = content

`MockResponse` is an object intended to have any of the attributes that a normal `requests.Response` object would have. However, it only needs to implement the methods that are actually used within the tests.

The tricky bits are in the `pytest.fixture`.

The first little magical function is the `patch_x` function, where `x` should either be `post` or `get`.

    @pytest.fixture
    def patch_get(request):
        mp = request.getfixturevalue("monkeypatch")

        mp.setattr(requests.Session, 'request', get_mockreturn)
        return mp

This function, when called, changes the `requests.Session`’s `request` method to call the `get_mockreturn` function, defined below. `@pytest.fixture` means that, if any function in this `test_module.py` file accepts `patch_get` as an argument, `patch_get` will be called prior to running that function.

`get_mockreturn` is simple but important: this is where you define a function to return the appropriate data stored in the `data/` directory as a readable object within the `MockResponse` class:

    def get_mockreturn(url, params=None, timeout=10):
        filename = data_path(DATA_FILES['votable'])
        with open(filename, 'r') as infile:
            content = infile.read()
        return MockResponse(content)

`data_path` is a simple function that looks for the `data` directory local to the `test_module.py` file.

    def data_path(filename):
        data_dir = os.path.join(os.path.dirname(__file__), 'data')
        return os.path.join(data_dir, filename)

## `test_module_remote.py`

The remote tests are much easier. The file must contain the following:

    import pytest

    pytestmark = pytest.mark.remote_data

This ensures that the test functions in remote test module are only executed if the `--remote-data` flag is used.

## `setup_package.py`

This file only needs the `get_package_data()` function, which will tell `setup.py` to include the relevant files when installing.

    import os

    def get_package_data():
        paths_test = [os.path.join('data', '*.xml')]

        return {'astroquery.module.tests': paths_test}

## Doctesting

Narrative documentation should also be tested, the `doctest-remote-data` directive provides a way to mark code snippets that relies on remote data access.

If any of the examples include saving data files locally, use the `testcleanup` directive and the `cleanup_saved_downloads` function at the end of the narrative documentation.

## Running only the remote-data tests

We should aim to have a reasonably complete test coverage for all the code using the actual servers (as opposed to mocked tests). To check the remote-data test coverage you can opt to run only those marked with `remote_data`. Do remember to change `<module_you_want_to_test>` to the module name you actually work on:

    pytest -P <module_you_want_to_test> -m remote_data --remote-data=any --cov astroquery/<module_you_want_to_test> --cov-config=setup.cfg