Dev Container for Microsoft Fabric Casino/Gaming POC¶

This directory contains the configuration for a VS Code Dev Container that provides a complete, consistent development environment for the Microsoft Fabric Casino/Gaming POC.

What is a Dev Container?¶

A Dev Container is a Docker container specifically configured for development. It ensures that every developer on the team has the same tools, dependencies, and configuration, eliminating "works on my machine" issues.

Quick Start¶

Using VS Code (Recommended)¶

1. Prerequisites:
2. Docker Desktop installed and running
3. VS Code installed

4. Dev Containers extension installed

5. Open in Container:

6. Open this repository folder in VS Code
7. When prompted, click "Reopen in Container"

8. Or use Command Palette: Dev Containers: Reopen in Container

9. Wait for Setup:

10. First build takes 5-10 minutes (subsequent opens are faster)

11. Watch the terminal for setup progress

12. Start Coding:

13. All dependencies are pre-installed
14. Run python data_generation/generate.py --help to verify

Using GitHub Codespaces¶

1. Open in Codespaces:
2. Navigate to the repository on GitHub
3. Click the green "Code" button
4. Select "Codespaces" tab

5. Click "Create codespace on main"

6. Wait for Setup:

7. Codespace builds automatically

8. Environment is ready when terminal shows welcome message

9. Access:

10. Codespace opens in browser-based VS Code
11. Or connect from local VS Code using Codespaces extension

What's Included¶

Languages & Runtimes¶

Development Tools¶

Python Packages¶

Core: - pandas, numpy - Data manipulation - faker - Test data generation - pyarrow - Parquet file support - pydantic - Data validation - great-expectations - Data quality

Azure: - azure-identity - Authentication - azure-storage-blob - Blob storage - azure-keyvault-secrets - Secrets management - azure-eventhub - Event streaming

Development: - pytest - Testing framework - black, isort - Code formatting - ruff, mypy - Linting & type checking - jupyter, jupyterlab - Notebook support

VS Code Extensions¶

Python Development: - Python, Pylance, Black Formatter - Jupyter notebooks support - Ruff linter, MyPy type checker

Azure & Infrastructure: - Azure Tools pack - Bicep language support - Azure Pipelines

Productivity: - GitLens, Git Graph - Markdown support with Mermaid diagrams - Code spell checker - TODO highlighting

Configuration¶

Environment Variables¶

Create a .env file (copy from .env.sample):

# Copy the sample environment file
cp .env.sample .env

# Edit with your values
code .env

Azure Authentication¶

# Login to Azure (uses device code flow in container)
az login --use-device-code

# Verify login
az account show

# Set subscription (if needed)
az account set --subscription "Your-Subscription-Name"

Jupyter Notebooks¶

# Start Jupyter Lab
jupyter lab --no-browser --port 8888

# Access via forwarded port in VS Code

Common Tasks¶

Generate Test Data¶

# Show help
python data_generation/generate.py --help

# Generate slot machine events
python data_generation/generate.py --type slot_events --records 1000

# Generate all data types
python data_generation/generate.py --type all --records 5000

Run Tests¶

# All tests
pytest validation/ -v

# Specific test categories
pytest validation/unit_tests/ -v
pytest validation/integration_tests/ -v
pytest validation/deployment_tests/ -v

# With coverage
pytest validation/ --cov=data_generation --cov-report=html

Validate Infrastructure¶

# Validate Bicep templates
az bicep build --file infra/main.bicep

# What-if deployment
az deployment sub what-if \
  --location eastus \
  --template-file infra/main.bicep \
  --parameters infra/parameters/dev.bicepparam

Customization¶

Adding Python Packages¶

1. Add to requirements.txt or requirements-dev.txt
2. Rebuild container: Dev Containers: Rebuild Container

Adding VS Code Extensions¶

1. Edit .devcontainer/devcontainer.json
2. Add extension ID to customizations.vscode.extensions
3. Rebuild container

Modifying Container¶

1. Edit .devcontainer/Dockerfile
2. Rebuild container: Dev Containers: Rebuild Container

Troubleshooting¶

Container Won't Start¶

Symptom: Container fails to build or start

Solutions: 1. Ensure Docker Desktop is running 2. Try Dev Containers: Rebuild Container Without Cache 3. Check Docker has enough resources (4GB+ RAM) 4. Review Docker Desktop logs

Slow Performance¶

Symptom: Container is slow, especially file operations

Solutions: 1. Ensure repo is cloned to a case-sensitive filesystem 2. On Windows, use WSL 2 backend for Docker 3. Increase Docker resource allocation 4. Consider using named volumes for node_modules

Azure CLI Issues¶

Symptom: az commands fail or authentication issues

Solutions:

# Re-login
az logout
az login --use-device-code

# Clear cached credentials
rm -rf ~/.azure

# Reinstall CLI
az upgrade

Python Import Errors¶

Symptom: ImportError for installed packages

Solutions:

# Reinstall dependencies
pip install -r requirements.txt -r requirements-dev.txt

# Check Python path
python -c "import sys; print(sys.path)"

# Verify installation
pip list | grep <package-name>

Jupyter Kernel Issues¶

Symptom: Kernel not found or crashes

Solutions:

# Reinstall kernel
python -m ipykernel install --user --name fabric-casino-poc

# List available kernels
jupyter kernelspec list

# Remove and reinstall
jupyter kernelspec remove fabric-casino-poc
python -m ipykernel install --user --name fabric-casino-poc

File Structure¶

.devcontainer/
├── devcontainer.json    # Main configuration
├── Dockerfile           # Container image definition
├── post-create.sh       # Post-creation setup script
└── README.md           # This file

Best Practices¶

1. Always rebuild after changes to devcontainer files
2. Commit devcontainer changes so team gets updates
3. Use .env for secrets - never commit secrets
4. Test in clean container before pushing changes
5. Document customizations in this README

Resources¶

• VS Code Dev Containers Documentation
• Dev Container Specification
• GitHub Codespaces Documentation
• Microsoft Python Dev Containers

Support¶

If you encounter issues:

1. Check this troubleshooting guide
2. Review Docker Desktop logs
3. Check VS Code Dev Containers output panel
4. Create an issue in the repository