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Merge pull request #80 from mongodb/docsp-57250-movie-year #79

Merge pull request #80 from mongodb/docsp-57250-movie-year

Merge pull request #80 from mongodb/docsp-57250-movie-year #79

name: Run Python Tests
on:
pull_request:
branches:
- development
paths:
- 'mflix/server/python-fastapi/**'
push:
branches:
- development
paths:
- 'mflix/server/python-fastapi/**'
jobs:
test:
name: Run Python Tests
runs-on: ubuntu-latest
steps:
- name: Checkout code
uses: actions/checkout@v5
- name: Install Atlas CLI
run: |
curl https://fastdl.mongodb.org/mongocli/mongodb-atlas-cli_1.47.0_linux_x86_64.deb --output atlas-cli.deb
sudo apt install ./atlas-cli.deb
- name: Set up a local deployment using Atlas CLI
run: |
atlas deployments setup myLocalRs1 --type local --port 27017 --force
- name: Install MongoDB Database Tools to load sample data
run: |
curl https://fastdl.mongodb.org/tools/db/mongodb-database-tools-ubuntu2204-x86_64-100.13.0.deb --output mdb-db-tools.deb
sudo apt install ./mdb-db-tools.deb
- name: Download sample data
run: curl https://atlas-education.s3.amazonaws.com/sampledata.archive -o sampledata.archive
- name: Setup Database (Data & Indexes)
run: |
# 1. Restore the data
mongorestore --archive=sampledata.archive --port=27017
# 2. Prepare the Search Index Definition
echo '{
"name": "movieSearchIndex",
"database": "sample_mflix",
"collectionName": "movies",
"mappings": {
"dynamic": false,
"fields": {
"plot": {"type": "string", "analyzer": "lucene.standard"},
"fullplot": {"type": "string", "analyzer": "lucene.standard"},
"directors": {"type": "string", "analyzer": "lucene.standard"},
"writers": {"type": "string", "analyzer": "lucene.standard"},
"cast": {"type": "string", "analyzer": "lucene.standard"}
}
}
}' > search_index.json
# 3. Create the Search Index
atlas deployments search indexes create \
--deploymentName myLocalRs1 \
--file search_index.json
# 4. Prepare the Vector Index Definition
echo '{
"name": "vector_index",
"database": "sample_mflix",
"collectionName": "embedded_movies",
"type": "vectorSearch",
"fields": [
{
"type": "vector",
"path": "plot_embedding_voyage_3_large",
"numDimensions": 2048,
"similarity": "cosine"
}
]
}' > vector_index.json
# 5. Create the Vector Index
atlas deployments search indexes create \
--deploymentName myLocalRs1 \
--file vector_index.json
# 6. Wait for indexes to build
echo "Waiting for indexes to build..."
sleep 20
- name: Set up Python
uses: actions/setup-python@v5
with:
python-version: '3.13'
cache: 'pip'
cache-dependency-path: mflix/server/python-fastapi/requirements.txt
- name: Install dependencies
working-directory: mflix/server/python-fastapi
run: |
python -m pip install --upgrade pip
pip install -r requirements.txt
- name: Run unit tests
working-directory: mflix/server/python-fastapi
run: pytest -m unit --verbose --tb=short --junit-xml=test-results-unit.xml
env:
MONGO_URI: mongodb://localhost:27017
MONGO_DB: sample_mflix
- name: Run integration tests
working-directory: mflix/server/python-fastapi
run: pytest -m integration --verbose --tb=short --junit-xml=test-results-integration.xml
env:
MONGO_URI: mongodb://localhost:27017/?directConnection=true
MONGO_DB: sample_mflix
- name: Upload test results
uses: actions/upload-artifact@v4
if: always()
with:
name: test-results
path: |
mflix/server/python-fastapi/test-results-unit.xml
mflix/server/python-fastapi/test-results-integration.xml
mflix/server/python-fastapi/htmlcov/
retention-days: 30
- name: Generate Test Summary
if: always()
run: |
chmod +x .github/scripts/generate-test-summary-pytest.sh
.github/scripts/generate-test-summary-pytest.sh \
mflix/server/python-fastapi/test-results-unit.xml \
mflix/server/python-fastapi/test-results-integration.xml