Rate Limiting

Guide to handling API rate limits effectively.

Understanding Rate Limits

The Elexon BMRS API implements rate limiting to ensure fair usage. When exceeded, you'll receive a 429 Too Many Requests error.

Basic Rate Limit Handling

from elexon_bmrs import BMRSClient
from elexon_bmrs.exceptions import RateLimitError
import time

client = BMRSClient(api_key="your-key")

try:
    data = client.get_system_demand(from_date="2024-01-01", to_date="2024-01-02")
except RateLimitError as e:
    if e.retry_after:
        print(f"Waiting {e.retry_after} seconds...")
        time.sleep(e.retry_after)
    else:
        print("Rate limited. Implementing backoff...")
        time.sleep(60)

Exponential Backoff

import time
from elexon_bmrs import BMRSClient
from elexon_bmrs.exceptions import RateLimitError

def fetch_with_retry(client, max_retries=3):
    for attempt in range(max_retries):
        try:
            return client.get_system_demand(
                from_date="2024-01-01",
                to_date="2024-01-02"
            )
        except RateLimitError as e:
            if attempt == max_retries - 1:
                raise

            wait_time = e.retry_after if e.retry_after else (2 ** attempt)
            print(f"Rate limited. Waiting {wait_time} seconds...")
            time.sleep(wait_time)

Best Practices

1. Use an API Key - Higher rate limits with authentication
2. Implement Backoff - Wait progressively longer between retries
3. Cache Responses - Store frequently accessed data
4. Batch Requests - Use date ranges instead of individual requests
5. Monitor Usage - Track API calls in your application

For complete examples, see the Advanced Examples page.