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Rate Limiting Guide

Understand and manage API rate limits for optimal performance.

Rate Limits by Plan​

YODI implements rate limiting to ensure fair usage and service stability.

Rate Limits Per Plan​

PlanRequests/MinuteRequests/HourMonthly Limit
Freemium530010 API calls
Dev Pass201,2001,000 API calls
SMME Pass--10,000 API calls
Pro Pass50030,000100,000 API calls
EnterpriseCustomCustomUnlimited

Understanding Rate Limit Headers​

Every API response includes rate limit information in the headers:

X-RateLimit-Limit: 20
X-RateLimit-Remaining: 18
X-RateLimit-Reset: 1624881234

Header Meanings​

  • X-RateLimit-Limit: Maximum requests allowed in current window
  • X-RateLimit-Remaining: Requests remaining before hitting limit
  • X-RateLimit-Reset: Unix timestamp when the limit resets

Handling Rate Limit Errors​

429 Too Many Requests​

When you exceed the rate limit, you'll receive a 429 status code:

{
  "message": "RATE_LIMITED",
  "error": true,
  "data": null,
  "status": 429
}

How to Handle It​

  1. Check the response header for Retry-After value
  2. Wait the specified time before retrying
  3. Use exponential backoff for multiple retries

Exponential Backoff Example (Python)​

import time
import requests

def retry_with_backoff(url, headers, data, max_retries=5):
    for attempt in range(max_retries):
        response = requests.post(url, headers=headers, json=data)
        
        if response.status_code == 429:
            retry_after = int(response.headers.get('Retry-After', 2 ** attempt))
            print(f"Rate limited. Waiting {retry_after}s...")
            time.sleep(retry_after)
            continue
        
        return response
    
    raise Exception("Max retries exceeded")

Best Practices​

1. Monitor Your Limits​

response = requests.get(url, headers=headers)

# Check remaining requests
remaining = int(response.headers.get('X-RateLimit-Remaining', 0))
if remaining < 10:
    print(f"Warning: Only {remaining} requests remaining!")

2. Batch Requests When Possible​

Instead of making individual requests:

#  Bad - Multiple requests
for text in texts:
    response = requests.post(url, data={'text': text})

#  Good - Batch requests
batch = [{'text': t} for t in texts]
response = requests.post(url, data={'batch': batch})

3. Cache Results​

from functools import lru_cache

@lru_cache(maxsize=128)
def translate_cached(text, language):
    return api.translate(text, language)

4. Implement Queuing​

For high-volume applications, use a queue system:

from queue import Queue
import threading

class APIQueue:
    def __init__(self, rate_limit_per_sec=5):
        self.queue = Queue()
        self.rate_limit = rate_limit_per_sec
        self.worker = threading.Thread(target=self._process)
        self.worker.daemon = True
        self.worker.start()
    
    def _process(self):
        last_request = 0
        while True:
            item = self.queue.get()
            # Ensure minimum time between requests
            time.sleep(max(0, last_request + (1/self.rate_limit) - time.time()))
            self._make_request(item)
            last_request = time.time()

Upgrade Your Plan​

If you consistently hit rate limits, consider upgrading:

  • Dev Pass: 20 req/min ($19/month)
  • Pro Pass: 500 req/min ($399/month)
  • Enterprise: Custom limits (Contact sales)

View Plans →

Troubleshooting​

Q: Why am I getting 429 errors?​

A: You've exceeded the rate limit for your plan. Either:

  1. Wait before making more requests
  2. Upgrade to a higher plan
  3. Implement request batching

Q: Can I request a higher rate limit?​

A: Yes! Contact our support team or upgrade to Pro/Enterprise plan for higher limits.

Q: Does the rate limit reset hourly or daily?​

A: Rate limits reset on a rolling window basis. The X-RateLimit-Reset header tells you exactly when.

Next Steps​