Fixed and rearranged unit tests (#184)

* Fixed test_train_model test in code_test.py
* Renamed code_test.py to train_test.py
* Moved train_test.py under diabetes_regression directory
* Moved data_test.py under data directory
* Added lint and unit test tasks to azdo-base-pipeline.yml
* Deleted lint-and-test.sh and tox.ini
* Removed test/unit directory


Co-authored-by: David Tesar <[email protected]>

Author: bjcmit

.pipelines/azdo-base-pipeline.yml

@@ -1,7 +1,11 @@
 steps:
-- script: |
-    ./lint-and-test.sh
-  displayName: 'Linting & unit tests'
+- script: |   
+   flake8 --output-file=lint-testresults.xml --format junit-xml
+  displayName: 'Run lint tests'
+
+- script: |   
+   python -m pytest . --cov=diabetes_regression --cov-report=html --cov-report=xml --junitxml=unit-testresults.xml
+  displayName: 'Run unit tests'
 
 - task: PublishTestResults@2
   condition: succeededOrFailed()

tests/unit/data_test.py renamed to data/data_test.py

@@ -35,7 +35,7 @@ def get_absPath(filename):
     path = os.path.abspath(
         os.path.join(
             os.path.dirname(
-                __file__), os.path.pardir, os.path.pardir, "data", filename
+                __file__), os.path.pardir, "data", filename
         )
     )
     return path

diabetes_regression/ci_dependencies.yml

@@ -25,4 +25,3 @@ dependencies:
       - flake8==3.7.9
       - flake8_formatter_junit_xml==0.0.6
       - azure-cli==2.0.81
-      - tox==3.14.3

tests/unit/code_test.py renamed to diabetes_regression/training/test_train.py

@@ -15,8 +15,13 @@ def test_train_model():
     run = Mock(Run)
     reg = train_model(run, data, alpha=1.2)
 
-    run.log.assert_called_with("mse", 0.029843893480257067,
-                               description='Mean squared error metric')
+    _, call2 = run.log.call_args_list
+    nameValue, descriptionDict = call2
+    name, value = nameValue
+    description = descriptionDict['description']
+    assert (name == 'mse')
+    np.testing.assert_almost_equal(value, 0.029843893480257067)
+    assert (description == 'Mean squared error metric')
 
     preds = reg.predict([[1], [2]])
     np.testing.assert_equal(preds, [9.93939393939394, 9.03030303030303])

docs/development_setup.md

@@ -38,7 +38,3 @@ BUILD_BUILDID is a variable used to uniquely identify the ML pipeline between th
 set to the current build number. In a local environment, we can use a command such as
 `uuidgen` so set a different random identifier on each run, ensuring there are 
 no collisions.
-
-### Local testing
-
-Before committing, run `tox` to execute linter and unit test checks.