mirror of
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173 lines
3.5 KiB
Markdown
173 lines
3.5 KiB
Markdown
# Redis and Celery Configuration
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This document explains how to set up and use Redis and Celery for background task processing in the LiveGraphs application.
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## Overview
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The data integration module uses Celery to handle:
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- Periodic data fetching from external APIs
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- Processing and storing CSV data
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- Downloading and parsing transcript files
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- Manual data refresh triggered by users
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## Installation
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### Redis (Recommended)
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Redis is the recommended message broker for Celery due to its performance and reliability:
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#### Ubuntu/Debian
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```bash
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sudo apt update
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sudo apt install redis-server
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sudo systemctl start redis-server
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sudo systemctl enable redis-server
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# Verify that Redis is running
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redis-cli ping # Should output PONG
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```
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After installation, check if Redis is properly configured:
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1. Open Redis configuration file:
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```bash
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sudo nano /etc/redis/redis.conf
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```
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2. Ensure the following settings:
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```bash
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# For development (localhost only)
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bind 127.0.0.1
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# For production (accept connections from specific IP)
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# bind 127.0.0.1 your.server.ip.address
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# Protected mode (recommended)
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protected-mode yes
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# Port
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port 6379
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```
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3. Restart Redis after any changes:
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```bash
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sudo systemctl restart redis-server
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```
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#### macOS
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```bash
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brew install redis
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brew services start redis
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```
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#### Windows
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Download and install from [microsoftarchive/redis](https://github.com/microsoftarchive/redis/releases)
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### SQLite Fallback
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If Redis is not available, the application will automatically fall back to using SQLite for Celery tasks. This works well for development but is not recommended for production.
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## Configuration
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### Environment Variables
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Set these environment variables in your `.env` file or deployment environment:
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```env
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# Redis Configuration
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REDIS_HOST=localhost
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REDIS_PORT=6379
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REDIS_DB=0
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CELERY_BROKER_URL=redis://localhost:6379/0
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CELERY_RESULT_BACKEND=redis://localhost:6379/0
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# Task Scheduling
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CHAT_DATA_FETCH_INTERVAL=3600 # In seconds (1 hour)
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FETCH_DATA_TIMEOUT=300 # In seconds (5 minutes)
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```
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### Testing Redis Connection
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To test if Redis is properly configured:
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```bash
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cd dashboard_project
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python manage.py test_redis
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```
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### Testing Celery
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To test if Celery is working correctly:
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```bash
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# Start a Celery worker in one terminal
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make celery
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# In another terminal, run the test task
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cd dashboard_project
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python manage.py test_celery
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```
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## Running with Docker
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The included `docker-compose.yml` file sets up Redis, Celery worker, and Celery beat for you:
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```bash
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docker-compose up -d
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```
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## Running in Development
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Development requires multiple terminal windows:
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1. **Django Development Server**:
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```bash
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make run
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```
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2. **Redis Server** (if needed):
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```bash
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make run-redis
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```
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3. **Celery Worker**:
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```bash
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make celery
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```
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4. **Celery Beat** (for scheduled tasks):
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```bash
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make celery-beat
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```
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Or use the combined command:
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```bash
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make run-all
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```
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## Common Issues
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### Redis Connection Failures
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If you see connection errors:
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1. Check that Redis is running: `redis-cli ping` should return `PONG`
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2. Verify firewall settings are not blocking port 6379
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3. Check Redis binding in `/etc/redis/redis.conf` (should be `bind 127.0.0.1` for local dev)
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### Celery Workers Not Processing Tasks
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1. Ensure the worker is running with the correct app name: `celery -A dashboard_project worker`
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2. Check the Celery logs for errors
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3. Verify broker URL settings in both code and environment variables
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