Rate Limiting Best Practices

Learn how to handle rate limits gracefully and optimize your API usage for maximum efficiency

Intermediate•15-20 minutes•All Frameworks

Understanding Rate Limits

FXRateSync implements rate limiting to ensure fair usage and maintain optimal performance for all users. Understanding these limits helps you build efficient applications that scale.

Free

1,000 requests/month

10 req/min

Startup

50,000 requests/month

100 req/min

Enterprise

Unlimited requests

Custom limits

Reading Rate Limit Headers

Every API response includes headers that tell you about your current rate limit status:

HTTP/1.1 200 OK
X-RateLimit-Limit: 100
X-RateLimit-Remaining: 95
X-RateLimit-Reset: 1640995200
X-RateLimit-Window: 60

Header Meanings

X-RateLimit-Limit - Max requests per window
X-RateLimit-Remaining - Requests left in window
X-RateLimit-Reset - When window resets (Unix timestamp)
X-RateLimit-Window - Window duration (seconds)

Best Practice

Always check these headers in your application and implement logic to pause requests when you're approaching the limit.

Implementation Examples

JavaScript/TypeScript

class RateLimitedAPIClient {
  private apiKey: string
  private baseURL = 'https://api.fxratesync.io/v1'
  private requestQueue: Array<() => Promise<any>> = []
  private isProcessing = false

  constructor(apiKey: string) {
    this.apiKey = apiKey
  }

  private async makeRequest(url: string): Promise<any> {
    const response = await fetch(url, {
      headers: {
        'X-API-Key': this.apiKey
      }
    })

    // Check rate limit headers
    const remaining = parseInt(response.headers.get('X-RateLimit-Remaining') || '0')
    const reset = parseInt(response.headers.get('X-RateLimit-Reset') || '0')

    if (response.status === 429) {
      // Rate limited - calculate retry delay
      const retryAfter = (reset * 1000) - Date.now()
      throw new Error(`Rate limited. Retry after ${retryAfter}ms`)
    }

    if (remaining < 5) {
      // Approaching limit - add delay
      console.warn('Approaching rate limit, adding delay')
      await this.delay(1000)
    }

    return response.json()
  }

  private delay(ms: number): Promise<void> {
    return new Promise(resolve => setTimeout(resolve, ms))
  }

  async convertCurrency(from: string, to: string, amount: number) {
    return this.makeRequest(
      `${this.baseURL}/convert?from=${from}&to=${to}&amount=${amount}`
    )
  }
}

Python

import time
import requests
from typing import Dict, Any

class RateLimitedClient:
    def __init__(self, api_key: str):
        self.api_key = api_key
        self.base_url = "https://api.fxratesync.io/v1"
        self.session = requests.Session()
        self.session.headers.update({"X-API-Key": api_key})
    
    def _handle_rate_limit(self, response: requests.Response) -> None:
        """Handle rate limit headers and implement backoff"""
        remaining = int(response.headers.get('X-RateLimit-Remaining', 0))
        reset_time = int(response.headers.get('X-RateLimit-Reset', 0))
        
        if response.status_code == 429:
            # Calculate delay until reset
            delay = max(0, reset_time - int(time.time()))
            print(f"Rate limited. Waiting {delay} seconds...")
            time.sleep(delay + 1)  # Add 1 second buffer
            
        elif remaining < 5:
            # Approaching limit, add small delay
            print("Approaching rate limit, adding delay")
            time.sleep(1)
    
    def convert_currency(self, from_currency: str, to_currency: str, amount: float) -> Dict[Any, Any]:
        url = f"{self.base_url}/convert"
        params = {
            "from": from_currency,
            "to": to_currency,
            "amount": amount
        }
        
        max_retries = 3
        for attempt in range(max_retries):
            try:
                response = self.session.get(url, params=params)
                self._handle_rate_limit(response)
                
                if response.status_code == 200:
                    return response.json()
                elif response.status_code == 429 and attempt < max_retries - 1:
                    continue  # Retry after delay
                else:
                    response.raise_for_status()
                    
            except requests.exceptions.RequestException as e:
                if attempt < max_retries - 1:
                    time.sleep(2 ** attempt)  # Exponential backoff
                    continue
                raise e

Rate Limiting Strategies

Request Queueing

Queue requests when approaching limits and process them at a controlled rate.

• Prevents request failures
• Maintains consistent performance
• Better user experience

Exponential Backoff

Gradually increase delays between retries when encountering rate limits.

• Reduces server load
• Improves success rate
• Industry standard practice

Response Caching

Cache API responses to reduce the number of requests needed.

• Faster response times
• Reduced API usage
• Cost optimization

Batch Processing

Use batch endpoints to convert multiple currencies in one request.

• Efficient resource usage
• Lower rate limit impact
• Better for bulk operations

Monitoring & Alerting

Set Up Monitoring

Track daily/monthly API usage
Set alerts at 80% of monthly limit
Monitor error rates for 429 responses
Log rate limit headers for analysis

Common Pitfalls to Avoid

Ignoring Rate Limit Headers

Always check and respect the rate limit headers. Ignoring them leads to failed requests and poor user experience.

No Retry Logic

Implementing proper retry logic with backoff is essential for handling temporary rate limits gracefully.

Inefficient Request Patterns

Making individual requests for data that could be batched wastes your rate limit allowance.

Master API Usage

Continue learning with our other guides and best practices

Error Handling Guide Build Currency App