Initial unit testing for scaffolding file Part 0

.github/workflows/test_with_docker.yml

@@ -0,0 +1,36 @@
+# This is a basic workflow to help you get started with Actions
+
+name: test-with-docker
+
+# Controls when the action will run. Triggers the workflow on push or pull request 
+# events but only for the master branch
+on:
+  push:
+    branches: [ main ]
+  pull_request:
+    branches: [ main ]
+  schedule:
+    # * is a special character in YAML so you have to quote this string
+    - cron:  '5 4 * * 0'
+
+# A workflow run is made up of one or more jobs that can run sequentially or in parallel
+jobs:
+  # This workflow contains a single job called "build"
+  build:
+    # The type of runner that the job will run on
+    runs-on: ubuntu-latest
+
+    # Steps represent a sequence of tasks that will be executed as part of the job
+    steps:
+    # Checks-out your repository under $GITHUB_WORKSPACE, so your job can access it
+    - name: Checkout
+      uses: actions/checkout@v2
+
+    - name: Make sure that the workflow works
+      run: echo Smoke test
+
+    - name: Run the tests using docker-compose
+      working-directory: .github/workflows
+       run:  |
+         docker compose -f ../../docker-compose.tests.yml build
+         docker compose -f ../../docker-compose.tests.yml up --exit-code-from notebook-server

docker-compose.tests.yml

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+version: "3"
+services:
+  dashboard:
+    image: em-pub-dash-dev/frontend
+    build:
+        context: frontend
+        dockerfile: docker/Dockerfile.dev
+    depends_on:
+      - db
+    ports:
+      # DASH in numbers
+      - "3274:6060"
+    volumes:
+      - ./frontend:/public
+      - ./plots:/public/plots
+    networks:
+       - emission
+  notebook-server:
+    image: em-pub-dash-dev/viz-scripts
+    build:
+      context: viz_scripts
+      dockerfile: docker/Dockerfile.test
+      args:
+        SERVER_IMAGE_TAG: ${SERVER_IMAGE_TAG}
+    depends_on:
+      - db
+    environment:
+      - DB_HOST=db
+      - WEB_SERVER_HOST=0.0.0.0
+      - CRON_MODE=
+      - STUDY_CONFIG=stage-program
+    ports:
+      # ipynb in numbers
+      - "47962:47962"
+    networks:
+      - emission
+    volumes:
+      - ./viz_scripts:/usr/src/app/saved-notebooks
+      - ./plots:/plots
+  db:
+    image: mongo:4.4.0
+    volumes:
+      - mongo-data:/data/db
+    networks:
+       - emission
+
+networks:
+  emission:
+
+volumes:
+  mongo-data:

viz_scripts/docker/Dockerfile.test

@@ -0,0 +1,19 @@
+# python 3
+ARG SERVER_IMAGE_TAG
+FROM shankari/e-mission-server:master_${SERVER_IMAGE_TAG}
+
+VOLUME /plots
+
+ADD docker/environment36.dashboard.additions.yml /
+
+WORKDIR /usr/src/app
+
+RUN /bin/bash -c "source setup/activate.sh && conda env update --name emission --file setup/environment36.notebook.additions.yml"
+RUN /bin/bash -c "source setup/activate.sh && conda env update --name emission --file /environment36.dashboard.additions.yml"
+
+ADD docker/start_tests.sh /usr/src/app/.docker/start_tests.sh
+RUN chmod u+x /usr/src/app/.docker/start_tests.sh
+
+EXPOSE 8888
+
+CMD ["/bin/bash", "/usr/src/app/.docker/start_tests.sh"]

viz_scripts/docker/environment36.dashboard.additions.yml

@@ -4,6 +4,8 @@ channels:
 - defaults
 dependencies:
 - seaborn=0.11.1
+- pytest
+- coverage
 - pip:
   - nbparameterise==0.6
   - devcron==0.4

viz_scripts/docker/start_tests.sh

@@ -0,0 +1,13 @@
+#!/bin/bash
+set -e  # Exit on error
+
+# change python environment
+pwd
+source setup/activate.sh || exit 1
+conda env list
+cd saved-notebooks/tests || exit 1
+
+echo "Starting unit tests..."
+PYTHONPATH=../.. coverage run -m pytest . -v
+
+coverage report

viz_scripts/plots.py

@@ -9,7 +9,17 @@
 
 sns.set_style("whitegrid")
 sns.set()
-get_ipython().run_line_magic('matplotlib', 'inline')
+
+try:
+    # Import the function
+    from IPython import get_ipython
+    # Check if running in an IPython environment (like Jupyter Notebook)
+    if get_ipython() is not None:
+        get_ipython().run_line_magic('matplotlib', 'inline')
+except ImportError:
+    # Handle the case where IPython is not installed
+    # We are running in regular Python (likely pytest), not Jupyter/IPython
+    pass
 
 # Module for pretty-printing outputs (e.g. head) to help users
 # understand what is going on

viz_scripts/tests/test_plots.py

@@ -0,0 +1,58 @@
+import pytest as pytest
+import pandas as pd
+import numpy as np
+# Using import_module, as we have saved-notebooks as the directory
+import importlib
+plots = importlib.import_module('saved-notebooks.plots')
+
+# Test Data Fixtures
+@pytest.fixture
+def sample_labels():
+    return ['Car', 'Bus', 'Train', 'Walk']
+
+@pytest.fixture
+def sample_values():
+    return [100, 50, 3, 1]
+
+@pytest.fixture
+def sample_labels_no_small():
+    return ['Car', 'Bus']
+
+
+@pytest.fixture
+def sample_values_no_small():
+    return [100, 100]
+
+class TestCalculatePct:
+    def test_calculate_pct_basic(self, sample_labels, sample_values):
+        labels, values, pcts = plots.calculate_pct(sample_labels, sample_values)
+        assert len(labels) == len(sample_labels)
+        assert len(values) == len(sample_values)
+        assert sum(pcts) == pytest.approx(100.0, abs=0.1)
+
+    def test_calculate_pct_empty(self):
+        labels, values, pcts = plots.calculate_pct([],[])
+        assert len(labels) == 0
+        assert len(values) == 0
+        assert len(pcts) == 0
+
+    def test_calculate_pct_single(self):
+        labels, values, pcts = plots.calculate_pct(['Car'], [100])
+        assert pcts == [100.0]
+
+class TestMergeSmallEntries:
+    def test_merge_small_entries_basic(self, sample_labels, sample_values):
+        labels, values, pcts = plots.merge_small_entries(sample_labels, sample_values)
+        assert all(pct > 2.0 for pct in pcts)
+
+    def test_merge_small_entries_no_small(self, sample_labels_no_small, sample_values_no_small):
+        result_labels, result_values, result_pcts = plots.merge_small_entries(sample_labels_no_small, sample_values_no_small)
+        assert len(result_labels) == 2
+        assert 'other' not in result_labels
+        assert 'OTHER' not in result_labels
+
+    def test_merge_small_entries_some_small(self, sample_labels, sample_values):
+        result_labels, result_values, result_pcts = plots.merge_small_entries(sample_labels, sample_values)
+        print(result_labels)
+        assert len(result_labels) == 3
+        assert result_labels[0] in ['Car', 'Bus','other', 'OTHER']

viz_scripts/tests/test_scaffolding.py

@@ -0,0 +1,74 @@
+import unittest.mock as mock
+import emission.core.wrapper.localdate as ecwl
+import emission.storage.timeseries.tcquery as esttc
+import importlib
+import pandas as pd
+import numpy as np
+import collections as colls
+import pytest
+
+# Dynamically import saved-notebooks.plots
+scaffolding = importlib.import_module('saved-notebooks.scaffolding')
+
+def test_get_time_query():
+    # Test with both year and month
+    result = scaffolding.get_time_query(2022, 6)
+    assert result is not None
+    assert isinstance(result, esttc.TimeComponentQuery)
+
+    # Test with year and no month
+    result = scaffolding.get_time_query(2023, None)
+    assert result is not None
+    assert isinstance(result, esttc.TimeComponentQuery)
+
+    # Test with month and no year
+    with pytest.raises(Exception) as e_info:
+        result = scaffolding.get_time_query(None, 12)
+
+    # Test with no year or month
+    result = scaffolding.get_time_query(None, None)
+    assert result is None
+
+def test_mapping_labels():
+    dynamic_labels = {
+        "MODE": [
+            {"value":"gas_car", "base_mode": "CAR",
+            "baseMode":"CAR", "met_equivalent":"IN_VEHICLE", "kgCo2PerKm": 0.22031},
+            {"value":"motorcycle", "base_mode": "MOPED", "footprint": { "gasoline": { "wh_per_km": 473.17 }},
+            "baseMode":"MOPED", "met_equivalent":"IN_VEHICLE", "kgCo2PerKm": 0.113143309},
+            {"value":"walk", "base_mode": "WALKING",
+            "baseMode":"WALKING", "met_equivalent":"WALKING", "kgCo2PerKm": 0},
+            {"value":"e_car", "base_mode": "E_CAR",
+            "baseMode":"E_CAR", "met_equivalent":"IN_VEHICLE", "kgCo2PerKm": 0.08216},
+            {"value":"taxi", "base_mode": "TAXI",
+            "baseMode":"TAXI", "met_equivalent":"IN_VEHICLE", "kgCo2PerKm": 0.30741},
+            {"value":"bike", "base_mode": "BICYCLING",
+            "baseMode":"BICYCLING", "met_equivalent":"BICYCLING", "kgCo2PerKm": 0},
+            {"value":"air", "base_mode": "AIR",
+            "baseMode":"AIR", "met_equivalent":"IN_VEHICLE", "kgCo2PerKm": 0.09975}
+        ],
+        "translations": {
+            "en": {
+            "walk": "Walk",
+            "motorcycle":"Motorcycle",
+            "bike": "Bicycle",
+            "gas_car": "Car",
+            "e_car": "Electric Car",
+            "taxi": "Taxi",
+            "air": "Airplane"
+            }
+        }
+    }
+
+    result_mode = scaffolding.mapping_labels(dynamic_labels, "MODE")
+
+    expected_result_mode = colls.defaultdict(lambda: 'Other', {
+        "gas_car": "Car",
+        "motorcycle": "Motorcycle",
+        "walk": "Walk",
+        "e_car": "Electric Car",
+        "taxi": "Taxi",
+        "bike": "Bicycle",
+        "air": "Airplane"
+    })
+    assert result_mode == expected_result_mode