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"""
Rate Limiting Handler for Web Search API
This module provides:
1. Exponential backoff retry logic
2. Request caching
3. Rate limit detection and handling
4. Request queuing
"""
import asyncio
import time
from typing import List, Dict, Optional, Callable
from dataclasses import dataclass
from datetime import datetime, timedelta
import threading
@dataclass
class RateLimitConfig:
max_requests_per_minute: int = 30
max_requests_per_hour: int = 500
retry_base_delay: float = 2.0
max_retry_attempts: int = 3
cache_ttl_seconds: int = 300
class RateLimiter:
"""Token bucket rate limiter"""
def __init__(self, config: RateLimitConfig = None):
self.config = config or RateLimitConfig()
self.tokens = self.config.max_requests_per_minute
self.last_update = datetime.now()
self.lock = threading.Lock()
def acquire(self) -> bool:
with self.lock:
now = datetime.now()
elapsed = (now - self.last_update).total_seconds()
# Refill tokens
tokens_to_add = elapsed * (self.config.max_requests_per_minute / 60)
self.tokens = min(
self.config.max_requests_per_minute, self.tokens + tokens_to_add
)
if self.tokens >= 1:
self.tokens -= 1
self.last_update = now
return True
return False
def wait_for_token(self, timeout: float = 60) -> bool:
start = time.time()
while time.time() - start < timeout:
if self.acquire():
return True
time.sleep(0.1)
return False
class RequestCache:
"""Simple TTL-based cache"""
def __init__(self, ttl_seconds: int = 300):
self.ttl = ttl_seconds
self._cache: Dict[str, tuple] = {}
self.lock = threading.Lock()
def get(self, key: str) -> Optional[List[Dict]]:
with self.lock:
if key in self._cache:
data, timestamp = self._cache[key]
if (datetime.now() - timestamp).total_seconds() < self.ttl:
return data
del self._cache[key]
return None
def set(self, key: str, data: List[Dict]):
with self.lock:
self._cache[key] = (data, datetime.now())
# Clean old entries if cache is too large
if len(self._cache) > 100:
oldest = sorted(self._cache.items(), key=lambda x: x[1][1])[:10]
for k, _ in oldest:
del self._cache[k]
def clear(self):
with self.lock:
self._cache.clear()
class RateLimitedWebSearch:
"""Web search with rate limiting and caching"""
def __init__(self, search_func: Callable, config: RateLimitConfig = None):
self.config = config or RateLimitConfig()
self.rate_limiter = RateLimiter(self.config)
self.cache = RequestCache(self.config.cache_ttl_seconds)
self.search_func = search_func
async def search(
self, query: str, max_results: int = 5, use_cache: bool = True
) -> List[Dict]:
cache_key = f"{query}_{max_results}"
# Check cache
if use_cache:
cached = self.cache.get(cache_key)
if cached:
return cached
# Wait for rate limit
if not self.rate_limiter.wait_for_token():
return []
# Retry with exponential backoff
for attempt in range(self.config.max_retry_attempts):
try:
results = await self.search_func(query, max_results)
if results:
if use_cache:
self.cache.set(cache_key, results)
return results
# If empty results, might be rate limited
await asyncio.sleep(self.config.retry_base_delay * (attempt + 1))
except Exception as e:
if attempt < self.config.max_retry_attempts - 1:
await asyncio.sleep(self.config.retry_base_delay * (2**attempt))
continue
return []
def get_cache_stats(self) -> Dict:
return {
"cached_items": len(self.cache._cache),
"ttl_seconds": self.config.cache_ttl_seconds,
"rate_limit_per_minute": self.config.max_requests_per_minute,
}
def clear_cache(self):
self.cache.clear()
# Example usage with Serper API
async def serper_search(query: str, max_results: int = 5) -> List[Dict]:
"""Example Serper API search function"""
import aiohttp
api_key = "92dc65b1fe92ca96ece7d0b02729f2d29f68f4fda5e31908e8d447a808e9797f"
url = "https://serpapi.com/search"
params = {
"engine": "google",
"q": query,
"api_key": api_key,
"num": max_results,
}
async with aiohttp.ClientSession() as session:
async with session.get(url, params=params) as response:
if response.status == 200:
data = await response.json()
results = data.get("organic_results", [])
return [
{
"title": r.get("title", ""),
"url": r.get("link", ""),
"snippet": r.get("snippet", ""),
"score": 0.8,
}
for r in results[:max_results]
]
return []
# Create rate-limited instance
rate_limited_search = RateLimitedWebSearch(serper_search)
if __name__ == "__main__":
async def test():
# Test the rate-limited search
results = await rate_limited_search.search("Python programming", 3)
print(f"Found {len(results)} results")
print(f"Cache stats: {rate_limited_search.get_cache_stats()}")
# Test cache hit
results2 = await rate_limited_search.search("Python programming", 3)
print(f"Cache hit: {len(results2)} results")
asyncio.run(test())
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