To run the services using compose:
$ docker-compose up --build -dTo stop the services:
$ docker-compose downYou must have the full pipeline running and requests library installed. Then, from this project root folder run:
$ python tests/test_integration.py
We make use of multi-stage docker builds so we can have into the same Dockerfile environments for testing and also for deploying our service.
Run:
$ cd api/
$ docker build -t flask_api_test --progress=plain --target test .You will only need to pay attention to the logs corresponding to the testing code which will look like this:
#10 [test 1/1] RUN ["pytest", "-v", "/src/tests"]
#10 sha256:707efc0d59d04744766193fe6873d212afc0f8e4b28d035a2d2e94b40826604f
#10 0.537 ============================= test session starts ==============================
#10 0.537 platform linux -- Python 3.8.13, pytest-7.1.1, pluggy-1.0.0 -- /usr/local/bin/python
#10 0.537 cachedir: .pytest_cache
#10 0.537 rootdir: /src
#10 0.537 collecting ... collected 4 items
#10 0.748
#10 0.748 tests/test_api.py::TestIntegration::test_bad_parameters PASSED [ 25%]
#10 0.757 tests/test_api.py::TestEnpointsAvailability::test_feedback PASSED [ 50%]
#10 0.769 tests/test_api.py::TestEnpointsAvailability::test_index PASSED [ 75%]
#10 0.772 tests/test_api.py::TestEnpointsAvailability::test_predict PASSED [100%]
#10 0.776
#10 0.776 ============================== 4 passed in 0.24s ===============================
#10 DONE 0.8sYou are good if all tests are passing.
Same as api, run:
$ cd model/
$ docker build -t model_test --progress=plain --target test .
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