API Integration Best Practices
Learn how to efficiently integrate BullishAI's API into your applications with proper error handling and rate limiting.
Authentication & Security
Always use secure authentication methods when integrating BullishAI's API. Store API keys in environment variables, never commit them to version control.
Implement proper token refresh mechanisms and handle authentication errors gracefully. Use HTTPS for all API requests to ensure data security.
Rate Limiting & Caching
Respect API rate limits to avoid service interruptions. Implement exponential backoff for retry logic and cache responses when appropriate to reduce API calls.
Use request batching when possible to fetch multiple symbols in a single API call. This improves efficiency and reduces the number of requests.
Error Handling
Implement comprehensive error handling for network failures, API errors, and data validation issues. Provide meaningful error messages to users.
Handle different HTTP status codes appropriately: retry on 5xx errors, handle 4xx errors with user-friendly messages, and implement circuit breakers for persistent failures.
Performance Optimization
- Use WebSocket connections for real-time data when available
- Implement request debouncing for user-triggered API calls
- Cache frequently accessed data with appropriate TTL values
- Use pagination for large data sets
- Monitor API response times and optimize slow endpoints