Rate Limits FLTR uses rate limiting to ensure fair usage and system stability.
Overview Rate limits are enforced per account based on authentication method:
Authentication Rate Limit Reset Period Anonymous 50 requests 1 hour API Key 1,000 requests 1 hour OAuth/Session 15,000 requests 1 hour
Every API response includes rate limit information:
X-RateLimit-Limit: 1000 X-RateLimit-Remaining: 847 X-RateLimit-Reset: 1704657600 Total requests allowed per hour
Requests remaining in current window
Unix timestamp when limit resets
Check Your Usage response = requests.get( "https://api.fltr.com/v1/datasets" , headers = { "Authorization" : "Bearer YOUR_API_KEY" } ) print ( f "Limit: { response.headers[ 'X-RateLimit-Limit' ] } " ) print ( f "Remaining: { response.headers[ 'X-RateLimit-Remaining' ] } " ) print ( f "Resets at: { response.headers[ 'X-RateLimit-Reset' ] } " ) When Rate Limited If you exceed your limit, you’ll receive a 429 status code:
{ "error" : "Rate limit exceeded" , "code" : "rate_limit_exceeded" , "retry_after" : 3600 } The retry_after field indicates seconds until you can retry.
Best Practices 1. Implement Exponential Backoff import time from tenacity import retry, stop_after_attempt, wait_exponential @retry ( stop = stop_after_attempt( 3 ), wait = wait_exponential( multiplier = 1 , min = 2 , max = 10 ) ) def make_request (): response = requests.post(url, headers = headers, json = data) if response.status_code == 429 : retry_after = int (response.headers.get( 'Retry-After' , 60 )) time.sleep(retry_after) raise Exception ( "Rate limited" ) response.raise_for_status() return response.json() 2. Cache Frequent Queries from functools import lru_cache import hashlib @lru_cache ( maxsize = 100 ) def cached_query ( query_hash ): return query_dataset(query) # Use hash for cache key query_hash = hashlib.md5(query.encode()).hexdigest() results = cached_query(query_hash) 3. Use Batch Endpoints # ❌ Multiple requests for query in queries: results.append(query_dataset(query)) # 10 requests # ✅ Single batch request results = batch_query_dataset(queries) # 1 request 4. Monitor Usage Track your usage to avoid hitting limits:
import time class RateLimitTracker : def __init__ ( self ): self .requests = [] def track_request ( self , response ): limit = int (response.headers[ 'X-RateLimit-Limit' ]) remaining = int (response.headers[ 'X-RateLimit-Remaining' ]) reset = int (response.headers[ 'X-RateLimit-Reset' ]) usage_pct = ((limit - remaining) / limit) * 100 if usage_pct > 80 : print ( f "⚠️ Warning: { usage_pct :.0f} % of rate limit used" ) if remaining == 0 : wait_time = reset - int (time.time()) print ( f "⛔ Rate limited. Waiting { wait_time } s" ) time.sleep(wait_time) tracker = RateLimitTracker() response = requests.get(url, headers = headers) tracker.track_request(response) 5. Spread Requests Instead of bursting requests, spread them out:
import time for item in items: make_request(item) time.sleep( 1 ) # 1 second delay between requests Increase Your Limits Upgrade to OAuth OAuth authentication provides 15x higher limits:
API Key: 1,000 requests/hour
OAuth: 15,000 requests/hour
OAuth Setup Upgrade to OAuth for higher limits →
Enterprise Plans Need even higher limits? Contact sales for:
Custom rate limits
Dedicated infrastructure
SLA guarantees
Priority support
Contact Sales Discuss enterprise pricing →
Rate Limit Scope Per Account Rate limits are per account , not per API key.
# These share the same 1,000/hour limit api_key_1 = "fltr_sk_abc123..." api_key_2 = "fltr_sk_def456..." Creating multiple API keys does not increase your limit.
Per Hour Limits reset every hour on a rolling basis:
12:00 - 13:00: 1,000 requests 13:00 - 14:00: 1,000 requests (limit resets) Separate Limits Each service has independent limits:
FLTR API: 1,000/hour
Webhooks: Unlimited (deliveries don’t count)
Endpoint-Specific Limits Some endpoints have additional constraints:
Endpoint Additional Limit Batch Query Max 10 queries per request Upload Max 10MB per file List Max 100 items per page
Fair Use Policy While there are technical rate limits, we also have a fair use policy:
Allowed:
Production applications
Automated workflows
Integration services
Testing and development
Not Allowed:
Excessive scraping
DoS attacks
Reselling API access
Violating ToS
Accounts violating fair use may be suspended.
Monitoring in Production Log Rate Limit Metrics import logging def log_rate_limit ( response ): logging.info({ 'rate_limit' : response.headers[ 'X-RateLimit-Limit' ], 'remaining' : response.headers[ 'X-RateLimit-Remaining' ], 'reset_at' : response.headers[ 'X-RateLimit-Reset' ], 'timestamp' : time.time() }) Alert on High Usage def check_rate_limit ( response ): remaining = int (response.headers[ 'X-RateLimit-Remaining' ]) limit = int (response.headers[ 'X-RateLimit-Limit' ]) if remaining < limit * 0.1 : # Less than 10% remaining send_alert( f "Rate limit warning: { remaining } / { limit } " ) Dashboard Metrics Track over time:
Requests per hour
Peak usage times
Rate limit hit frequency
Average remaining quota
Testing Rate Limits Simulate Rate Limiting def rate_limited_request (): """Test app behavior when rate limited""" class MockResponse : status_code = 429 headers = { 'Retry-After' : '60' } def json ( self ): return { 'error' : 'Rate limit exceeded' , 'retry_after' : 60 } return MockResponse() # Test your error handling response = rate_limited_request() handle_rate_limit(response) Load Testing Test your implementation:
import concurrent.futures def load_test (): with concurrent.futures.ThreadPoolExecutor( max_workers = 10 ) as executor: futures = [executor.submit(make_request) for _ in range ( 100 )] for future in concurrent.futures.as_completed(futures): try : result = future.result() except Exception as e: print ( f "Error: { e } " ) load_test() FAQ Q: Can I request a temporary limit increase? A: Yes, contact support@fltr.com with your use case.
Q: Do failed requests count toward the limit? A: Yes, all requests count including 4xx and 5xx errors.
Q: Does listing datasets use the same limit as queries? A: Yes, all API endpoints share the same rate limit.
Q: Can I purchase additional requests? A: We offer enterprise plans with custom limits. Contact sales.
Q: How long are limits enforced after exceeding them? A: Limits reset hourly on a rolling basis.
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