Uses multiple pipelines to test several versions of Python. A few
things to note:
- I use the -slim Python packages, which are smaller and yet still
have no problem installing psycopg2-binary with pip
- I have to start a PostgreSQL database service for each pipeline
separately
Generated with poetry export:
$ poetry export --without-hashes -f requirements.txt > requirements.txt
$ poetry export --without-hashes --dev -f requirements.txt > requirements-dev.txt
The `--without-hashes` is required to work around an issue with
gunicorn pulling in a dependency on setuptools that poetry ignores.
See: https://github.com/python-poetry/poetry/issues/1584
Minor change to bot filtering. We should use a negated match for
documents that have `isBot:true` rather than looking for documents
that are tagged with `isBot:false` (the distinction is subtle, but
important).
Generated with poetry export:
$ poetry export --without-hashes -f requirements.txt > requirements.txt
$ poetry export --without-hashes --dev -f requirements.txt > requirements-dev.txt
The `--without-hashes` is required to work around an issue with
gunicorn pulling in a dependency on setuptools that poetry ignores.
See: https://github.com/python-poetry/poetry/issues/1584
Generated with poetry export:
$ poetry export --no-hashes -f requirements.txt > requirements.txt
$ poetry export --no-hashes --dev -f requirements.txt > requirements-dev.txt
The `--no-hashes` is required to work around an issue with gunicorn
pulling in a dependency on setuptools that poetry ignores.
See: https://github.com/python-poetry/poetry/issues/1584
This adds tests for the new /items POST handler, both with mocked
data and a live connection to a Solr statistics core. Tests that
only work when Solr is available are marked with XFAIL so that they
don't turn the whole test suite red.
In each test I try to assert as many parameters as we can know for
each response so that we cover all expectations. For example, when
we test a valid limit parameter we should test whether the response
not only has the same limit parameter, but that the number of items
has actually been limited and the number of pages has been adjusted
accordingly.
See: https://docs.pytest.org/en/stable/skipping.html
Move util import from global scope because it causes tests to fail.
We don't need the set up the Solr connection unless we're actually
trying to use the get_views and get_downloads methods, either when
running the API in production or during tests where the connection
has been set up.
I was having issues with re-creating an environment from scratch:
ModuleNotFoundError: No module named 'virtualenv.seed.via_app_data'
Switching to Poetry for now.
I thought it was clever to only import these in the on_post handler
because they aren't needed elsewhere, but it turns out that this is
not a common pattern and even causes problems with testability.
First, if the imports are at the top of the file as PEP8 recommends,
then the WSGI server will import them once when it loads the app and
they remain in memory for the lifecycle of the app. If the imports
are in the on_post handler they would be re-imported on every request!
Second, this pattern of importing in a method makes it tricky to use
object patching in mocks.
See: https://www.python.org/dev/peps/pep-0008/#imports
According to flake8 we need to use a different syntax for strings
with backslash escape sequences:
> As of Python 3.6, a backslash-character pair that is not a valid
> escape sequence now generates a DeprecationWarning. This will
> eventually become a SyntaxError.
The warning was:
W605 invalid escape sequence '\-'
See: https://www.flake8rules.com/rules/W605.html
I don't remember why we needed the stats, but it seems that it was
because without them there is no way to know how many results were
returned and therefore no way to know how many pages we'll need to
iterate over. Having the total number allows us to use a limit and
and offset to page through them deterministically.