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HighCostDrugsDemo/docs/DEPLOYMENT.md
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Andrew Charlwood 54b4a0f743 docs: update all documentation for Dash migration (Phase 6)
Rewrote README.md, USER_GUIDE.md, and DEPLOYMENT.md to reflect
the Dash application. Updated RALPH_PROMPT.md, guardrails.md, and
DESIGN_SYSTEM.md to remove Reflex references. All non-archive
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# Deployment Guide
This guide covers deployment options for the Patient Pathway Analysis web application built with Dash.
## Overview
The application is a single-process Python Dash app that serves both the frontend and API from one server. It reads pre-computed data from a local SQLite database.
## Development Mode
For local development:
```bash
# Start development server with hot reload
python run_dash.py
# Access the application at http://localhost:8050
```
## Production Deployment Options
### Option 1: Simple Production (Single Server)
The simplest approach for internal deployments:
```bash
# Run with Gunicorn (Linux/macOS)
gunicorn dash_app.app:server -b 0.0.0.0:8050 --workers 4
# Or directly with Python
python run_dash.py
```
For background execution:
```bash
# Using nohup (Linux/macOS)
nohup gunicorn dash_app.app:server -b 0.0.0.0:8050 --workers 4 > dash.log 2>&1 &
# Using PowerShell (Windows)
Start-Process -NoNewWindow -FilePath "python" -ArgumentList "run_dash.py"
```
### Option 2: Docker Deployment
Create a `Dockerfile` for containerized deployment:
```dockerfile
FROM python:3.11-slim
WORKDIR /app
# Install uv for fast dependency management
RUN pip install uv
# Copy dependency files
COPY pyproject.toml uv.lock ./
# Install dependencies
RUN uv sync --no-dev
# Copy application code
COPY src/ src/
COPY dash_app/ dash_app/
COPY data/ data/
COPY run_dash.py setup_dev.py ./
# Set up Python path
RUN uv run python setup_dev.py
# Expose port
EXPOSE 8050
# Start the application
CMD ["uv", "run", "gunicorn", "dash_app.app:server", "-b", "0.0.0.0:8050", "--workers", "4"]
```
Build and run:
```bash
# Build the image
docker build -t pathway-analysis .
# Run the container
docker run -p 8050:8050 \
-v $(pwd)/data:/app/data \
pathway-analysis
```
### Option 3: Docker Compose
```yaml
version: '3.8'
services:
app:
build: .
ports:
- "8050:8050"
volumes:
- ./data:/app/data
- ./src/config:/app/src/config
restart: unless-stopped
```
Run with:
```bash
docker-compose up -d
```
## Reverse Proxy Configuration
### Nginx
For production deployments behind nginx:
```nginx
server {
listen 80;
server_name your-server.nhs.uk;
location / {
proxy_pass http://localhost:8050;
proxy_set_header Host $host;
proxy_set_header X-Real-IP $remote_addr;
proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
proxy_set_header X-Forwarded-Proto $scheme;
}
}
```
Enable the site:
```bash
sudo ln -s /etc/nginx/sites-available/pathway-analysis /etc/nginx/sites-enabled/
sudo nginx -t && sudo systemctl reload nginx
```
## Process Management
### Systemd (Linux)
```ini
# /etc/systemd/system/pathway-analysis.service
[Unit]
Description=Pathway Analysis Dash App
After=network.target
[Service]
Type=simple
User=www-data
WorkingDirectory=/opt/pathway-analysis
ExecStart=/opt/pathway-analysis/.venv/bin/gunicorn dash_app.app:server -b 0.0.0.0:8050 --workers 4
Restart=always
RestartSec=10
[Install]
WantedBy=multi-user.target
```
Enable and start:
```bash
sudo systemctl daemon-reload
sudo systemctl enable pathway-analysis
sudo systemctl start pathway-analysis
```
### Windows Service
Use NSSM (Non-Sucking Service Manager) on Windows:
```powershell
# Install NSSM
choco install nssm
# Create service
nssm install PathwayAnalysis "C:\Path\To\python.exe" "run_dash.py"
nssm set PathwayAnalysis AppDirectory "C:\Path\To\pathway-analysis"
nssm start PathwayAnalysis
```
## Environment Configuration
### Production Environment Variables
```bash
# Database path (if using custom location)
export PATHWAY_DB_PATH=/var/data/pathways.db
# Snowflake (for data refresh only — not needed for the web app)
export SNOWFLAKE_ACCOUNT=your-account
export SNOWFLAKE_WAREHOUSE=your-warehouse
```
### Snowflake Configuration
Snowflake is only needed for the data refresh CLI command, not for running the web application. Ensure `src/config/snowflake.toml` is configured:
```toml
[snowflake]
account = "your-production-account"
warehouse = "ANALYTICS_WH"
database = "DATA_HUB"
schema = "CDM"
authenticator = "externalbrowser"
```
## Data Refresh
The web application reads pre-computed data from SQLite. To update the data:
```bash
# Full refresh (both chart types, all date filters)
python -m cli.refresh_pathways --chart-type all
# The app will serve new data immediately — no restart needed
```
Schedule this as a cron job or Windows Task Scheduler task for periodic updates.
## Security Considerations
### Network Security
1. **Firewall Rules**: Only expose port 8050 (or 80/443 behind reverse proxy)
2. **HTTPS**: Use TLS certificates via reverse proxy (nginx, Caddy)
3. **VPN**: Consider restricting access to NHS network only
### Data Security
1. **Database Access**: The app uses read-only SQLite access
2. **No file uploads**: The Dash app does not accept file uploads
3. **No authentication built in**: Add authentication via reverse proxy or middleware if needed
## Monitoring
### Health Checks
The application serves at `/` — a 200 response indicates the app is running.
### Logging
Dash outputs request logs to stdout. Configure log aggregation as needed:
```bash
# Redirect logs to file
gunicorn dash_app.app:server -b 0.0.0.0:8050 --access-logfile /var/log/pathway-analysis/access.log --error-logfile /var/log/pathway-analysis/error.log
```
## Troubleshooting
### Port already in use
```bash
# Find process using port 8050
lsof -i :8050 # Linux/macOS
netstat -ano | findstr :8050 # Windows
```
### Database not found
```bash
# Verify database exists
ls -la data/pathways.db
sqlite3 data/pathways.db ".tables"
# Recreate if needed
python -m data_processing.migrate
python -m cli.refresh_pathways --chart-type all
```
### Import errors
```bash
# Ensure src/ is on Python path
uv run python setup_dev.py
# Verify imports
uv run python -c "from dash_app.app import app; print('OK')"
```
---
## Quick Reference
| Environment | Command | Port |
|-------------|---------|------|
| Development | `python run_dash.py` | 8050 |
| Production | `gunicorn dash_app.app:server -b 0.0.0.0:8050 --workers 4` | 8050 |
| Docker | `docker run -p 8050:8050 pathway-analysis` | 8050 |
For more information, see:
- [Dash Documentation](https://dash.plotly.com/)
- [Gunicorn Deployment](https://docs.gunicorn.org/en/stable/deploy.html)