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API Rate Limit Calculator - Parse Rate Limit Headers

API Rate Limit Calculator

Parse rate limit headers from API responses and calculate your usage.

Paste response headers containing X-RateLimit-* or Retry-After

Understanding API Rate Limits

API rate limiting is a technique used to control the number of requests a client can make to an API within a specific time period. It prevents abuse and ensures fair usage.

How to Use This Tool:

  1. Make an API request: Use cURL, Postman, or your browser
  2. Copy response headers: Look for X-RateLimit-* or Retry-After headers
  3. Paste headers: Into the text area above
  4. Calculate: Click "Calculate Rate Limit" to see your usage
  5. Monitor usage: Check if you're approaching the limit

Common Rate Limit Headers:

  • X-RateLimit-Limit: Maximum number of requests allowed in the time window
  • X-RateLimit-Remaining: Number of requests remaining in current window
  • X-RateLimit-Reset: Unix timestamp when the rate limit resets
  • Retry-After: Seconds to wait before making another request (after 429 error)

Example API Response Headers:

HTTP/1.1 200 OK
Content-Type: application/json
X-RateLimit-Limit: 1000
X-RateLimit-Remaining: 750
X-RateLimit-Reset: 1640000000
Date: Mon, 20 Dec 2024 12:00:00 GMT

HTTP 429 Too Many Requests:

When you exceed the rate limit, APIs typically return a 429 status code:

HTTP/1.1 429 Too Many Requests
Content-Type: application/json
Retry-After: 3600
X-RateLimit-Limit: 1000
X-RateLimit-Remaining: 0
X-RateLimit-Reset: 1640003600

{
  "error": "rate_limit_exceeded",
  "message": "You have exceeded your request quota"
}

Getting Headers with cURL:

# Show only headers
curl -I https://api.github.com/users/octocat

# Show headers and body
curl -i https://api.github.com/users/octocat

# Verbose output with timing
curl -v https://api.github.com/users/octocat

Common Rate Limiting Strategies:

  • Fixed Window: X requests per hour (resets at fixed times)
  • Sliding Window: X requests in any rolling hour period
  • Token Bucket: Tokens refill over time, allows bursts
  • Leaky Bucket: Constant rate processing with queue

Best Practices to Avoid Rate Limiting:

  • Cache responses: Don't re-fetch unchanged data
  • Implement exponential backoff: Retry with increasing delays
  • Use webhooks: Instead of polling for updates
  • Batch requests: Combine multiple operations when possible
  • Monitor headers: Check X-RateLimit-Remaining proactively
  • Request higher limits: Contact API provider for increased quota
  • Implement client-side throttling: Limit your own request rate

Example: Handling Rate Limits in Python

import requests
import time

def make_api_request(url):
    response = requests.get(url)

    # Check rate limit headers
    remaining = int(response.headers.get('X-RateLimit-Remaining', 999))
    reset_time = int(response.headers.get('X-RateLimit-Reset', 0))

    if response.status_code == 429:
        retry_after = int(response.headers.get('Retry-After', 60))
        print(f"Rate limited. Waiting {retry_after} seconds...")
        time.sleep(retry_after)
        return make_api_request(url)  # Retry

    if remaining < 10:
        wait_time = reset_time - time.time()
        if wait_time > 0:
            print(f"Approaching limit. Waiting {wait_time} seconds...")
            time.sleep(wait_time)

    return response.json()

Popular API Rate Limits:

  • GitHub: 5,000 requests/hour (authenticated), 60/hour (unauthenticated)
  • Twitter: Varies by endpoint, typically 15-900 requests per 15 minutes
  • Google APIs: Varies widely, often 10,000+ per day
  • Stripe: 100 requests per second in test mode

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