API Error Handling: Best Practices for Robust Applications

Building robust applications that consume financial APIs requires thoughtful error handling. In this guide, we'll cover strategies to handle failures gracefully and maintain reliable data flows.

Common API Errors

HTTP Status Codes

• 400 Bad Request: Invalid parameters—check your request format
• 401 Unauthorized: Invalid or expired API key
• 429 Too Many Requests: Rate limit exceeded
• 500 Internal Server Error: Server-side issue—retry with backoff
• 503 Service Unavailable: Temporary outage—implement retry logic

Implementing Retry Logic

import time
import random

def retry_with_backoff(func, max_retries=3, base_delay=1):
    for attempt in range(max_retries):
        try:
            return func()
        except (TimeoutError, ServiceUnavailable) as e:
            if attempt == max_retries - 1:
                raise
            delay = base_delay * (2 ** attempt) + random.uniform(0, 1)
            time.sleep(delay)

Rate Limit Handling

Respect rate limits by:

• Monitoring X-RateLimit headers in responses
• Implementing request queuing
• Using exponential backoff after 429 errors
• Caching responses where appropriate

Graceful Degradation

Design your application to continue functioning even when the API is unavailable. Use cached data, display stale prices with timestamps, and notify users of connectivity issues.