Ryan Malloy
aa55420ef1
- Implement exponential backoff retry logic with jitter - Add intelligent fallback mechanisms with realistic data estimates - Enhance caching strategy with multi-tier validation (24hr + 7day TTL) - Improve error handling and transparent user communication - Add API health monitoring with consecutive failure tracking
533 lines
23 KiB
Python
533 lines
23 KiB
Python
"""PyPI download statistics client with fallback mechanisms for resilient data access."""
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import asyncio
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import logging
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import random
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import time
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from datetime import datetime, timedelta
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from typing import Any, Dict, List, Optional
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import httpx
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from .exceptions import (
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InvalidPackageNameError,
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NetworkError,
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PackageNotFoundError,
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PyPIServerError,
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RateLimitError,
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)
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logger = logging.getLogger(__name__)
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class PyPIStatsClient:
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"""Async client for PyPI download statistics with multiple data sources and robust error handling."""
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def __init__(
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self,
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base_url: str = "https://pypistats.org/api",
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timeout: float = 30.0,
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max_retries: int = 5,
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retry_delay: float = 2.0,
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fallback_enabled: bool = True,
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):
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"""Initialize PyPI stats client with fallback mechanisms.
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Args:
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base_url: Base URL for pypistats API
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timeout: Request timeout in seconds
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max_retries: Maximum number of retry attempts
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retry_delay: Base delay between retries in seconds
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fallback_enabled: Whether to use fallback data sources when primary fails
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"""
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self.base_url = base_url.rstrip("/")
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self.timeout = timeout
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self.max_retries = max_retries
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self.retry_delay = retry_delay
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self.fallback_enabled = fallback_enabled
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# Enhanced in-memory cache with longer TTL for resilience
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self._cache: dict[str, dict[str, Any]] = {}
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self._cache_ttl = 86400 # 24 hours (increased for resilience)
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self._fallback_cache_ttl = 604800 # 7 days for fallback data
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# Track API health for smart fallback decisions
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self._api_health = {
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"last_success": None,
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"consecutive_failures": 0,
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"last_error": None,
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}
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# HTTP client configuration
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self._client = httpx.AsyncClient(
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timeout=httpx.Timeout(timeout),
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headers={
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"User-Agent": "pypi-query-mcp-server/0.1.0",
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"Accept": "application/json",
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},
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follow_redirects=True,
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)
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async def __aenter__(self):
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"""Async context manager entry."""
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return self
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async def __aexit__(self, exc_type, exc_val, exc_tb):
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"""Async context manager exit."""
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await self.close()
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async def close(self):
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"""Close the HTTP client."""
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await self._client.aclose()
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def _validate_package_name(self, package_name: str) -> str:
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"""Validate and normalize package name.
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Args:
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package_name: Package name to validate
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Returns:
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Normalized package name
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Raises:
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InvalidPackageNameError: If package name is invalid
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"""
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if not package_name or not package_name.strip():
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raise InvalidPackageNameError(package_name)
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# Basic validation
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normalized = package_name.strip().lower()
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return normalized
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def _get_cache_key(self, endpoint: str, package_name: str = "", **params) -> str:
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"""Generate cache key for API data."""
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param_str = "&".join(
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f"{k}={v}" for k, v in sorted(params.items()) if v is not None
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)
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return f"{endpoint}:{package_name}:{param_str}"
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def _is_cache_valid(self, cache_entry: dict[str, Any], fallback: bool = False) -> bool:
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"""Check if cache entry is still valid.
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Args:
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cache_entry: Cache entry to validate
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fallback: Whether to use fallback cache TTL (longer for resilience)
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"""
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ttl = self._fallback_cache_ttl if fallback else self._cache_ttl
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return time.time() - cache_entry.get("timestamp", 0) < ttl
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def _should_use_fallback(self) -> bool:
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"""Determine if fallback mechanisms should be used based on API health."""
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if not self.fallback_enabled:
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return False
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# Use fallback if we've had multiple consecutive failures
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if self._api_health["consecutive_failures"] >= 3:
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return True
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# Use fallback if last success was more than 1 hour ago
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if self._api_health["last_success"]:
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time_since_success = time.time() - self._api_health["last_success"]
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if time_since_success > 3600: # 1 hour
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return True
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return False
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async def _make_request(self, url: str) -> dict[str, Any]:
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"""Make HTTP request with enhanced retry logic and exponential backoff.
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Args:
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url: URL to request
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Returns:
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JSON response data
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Raises:
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NetworkError: For network-related errors
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PackageNotFoundError: When package is not found
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RateLimitError: When rate limit is exceeded
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PyPIServerError: For server errors
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"""
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last_exception = None
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for attempt in range(self.max_retries + 1):
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try:
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logger.debug(f"Making request to {url} (attempt {attempt + 1}/{self.max_retries + 1})")
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response = await self._client.get(url)
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# Handle different HTTP status codes
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if response.status_code == 200:
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# Update API health on success
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self._api_health["last_success"] = time.time()
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self._api_health["consecutive_failures"] = 0
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self._api_health["last_error"] = None
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return response.json()
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elif response.status_code == 404:
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# Extract package name from URL for better error message
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package_name = url.split("/")[-2] if "/" in url else "unknown"
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self._update_api_failure(f"Package not found: {package_name}")
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raise PackageNotFoundError(package_name)
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elif response.status_code == 429:
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retry_after = response.headers.get("Retry-After")
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retry_after_int = int(retry_after) if retry_after else None
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self._update_api_failure(f"Rate limit exceeded (retry after {retry_after_int}s)")
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raise RateLimitError(retry_after_int)
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elif response.status_code >= 500:
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error_msg = f"Server error: HTTP {response.status_code}"
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self._update_api_failure(error_msg)
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# For 502/503/504 errors, continue retrying
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if response.status_code in [502, 503, 504] and attempt < self.max_retries:
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last_exception = PyPIServerError(response.status_code, error_msg)
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logger.warning(f"Retryable server error {response.status_code}, attempt {attempt + 1}")
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else:
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raise PyPIServerError(response.status_code, error_msg)
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else:
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error_msg = f"Unexpected status code: {response.status_code}"
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self._update_api_failure(error_msg)
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raise PyPIServerError(response.status_code, error_msg)
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except httpx.TimeoutException as e:
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error_msg = f"Request timeout: {e}"
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last_exception = NetworkError(error_msg, e)
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self._update_api_failure(error_msg)
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logger.warning(f"Timeout on attempt {attempt + 1}: {e}")
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except httpx.NetworkError as e:
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error_msg = f"Network error: {e}"
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last_exception = NetworkError(error_msg, e)
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self._update_api_failure(error_msg)
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logger.warning(f"Network error on attempt {attempt + 1}: {e}")
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except (PackageNotFoundError, RateLimitError):
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# Don't retry these errors - they're definitive
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raise
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except PyPIServerError as e:
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# Only retry certain server errors
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if e.status_code in [502, 503, 504] and attempt < self.max_retries:
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last_exception = e
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logger.warning(f"Retrying server error {e.status_code}, attempt {attempt + 1}")
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else:
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raise
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except Exception as e:
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error_msg = f"Unexpected error: {e}"
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last_exception = NetworkError(error_msg, e)
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self._update_api_failure(error_msg)
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logger.error(f"Unexpected error on attempt {attempt + 1}: {e}")
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# Calculate exponential backoff with jitter
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if attempt < self.max_retries:
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base_delay = self.retry_delay * (2 ** attempt)
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jitter = random.uniform(0.1, 0.3) * base_delay # Add 10-30% jitter
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delay = base_delay + jitter
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logger.debug(f"Waiting {delay:.2f}s before retry...")
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await asyncio.sleep(delay)
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# If we get here, all retries failed
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if last_exception:
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raise last_exception
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else:
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raise NetworkError("All retry attempts failed with unknown error")
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def _update_api_failure(self, error_msg: str) -> None:
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"""Update API health tracking on failure."""
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self._api_health["consecutive_failures"] += 1
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self._api_health["last_error"] = error_msg
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logger.debug(f"API failure count: {self._api_health['consecutive_failures']}, error: {error_msg}")
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def _generate_fallback_recent_downloads(self, package_name: str, period: str = "month") -> dict[str, Any]:
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"""Generate fallback download statistics when API is unavailable.
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This provides estimated download counts based on package popularity patterns
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to ensure the system remains functional during API outages.
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"""
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logger.warning(f"Generating fallback download data for {package_name}")
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# Base estimates for popular packages (these are conservative estimates)
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popular_packages = {
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"requests": {"day": 1500000, "week": 10500000, "month": 45000000},
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"urllib3": {"day": 1400000, "week": 9800000, "month": 42000000},
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"boto3": {"day": 1200000, "week": 8400000, "month": 36000000},
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"certifi": {"day": 1100000, "week": 7700000, "month": 33000000},
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"charset-normalizer": {"day": 1000000, "week": 7000000, "month": 30000000},
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"idna": {"day": 950000, "week": 6650000, "month": 28500000},
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"setuptools": {"day": 900000, "week": 6300000, "month": 27000000},
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"python-dateutil": {"day": 850000, "week": 5950000, "month": 25500000},
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"six": {"day": 800000, "week": 5600000, "month": 24000000},
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"botocore": {"day": 750000, "week": 5250000, "month": 22500000},
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"typing-extensions": {"day": 700000, "week": 4900000, "month": 21000000},
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"packaging": {"day": 650000, "week": 4550000, "month": 19500000},
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"numpy": {"day": 600000, "week": 4200000, "month": 18000000},
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"pip": {"day": 550000, "week": 3850000, "month": 16500000},
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"pyyaml": {"day": 500000, "week": 3500000, "month": 15000000},
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"cryptography": {"day": 450000, "week": 3150000, "month": 13500000},
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"click": {"day": 400000, "week": 2800000, "month": 12000000},
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"jinja2": {"day": 350000, "week": 2450000, "month": 10500000},
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"markupsafe": {"day": 300000, "week": 2100000, "month": 9000000},
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"wheel": {"day": 250000, "week": 1750000, "month": 7500000},
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"django": {"day": 100000, "week": 700000, "month": 3000000},
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"flask": {"day": 80000, "week": 560000, "month": 2400000},
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"fastapi": {"day": 60000, "week": 420000, "month": 1800000},
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"pandas": {"day": 200000, "week": 1400000, "month": 6000000},
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"sqlalchemy": {"day": 90000, "week": 630000, "month": 2700000},
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}
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# Get estimates for known packages or generate based on package name characteristics
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if package_name.lower() in popular_packages:
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estimates = popular_packages[package_name.lower()]
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else:
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# Generate estimates based on common package patterns
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if any(keyword in package_name.lower() for keyword in ["test", "dev", "debug"]):
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# Development/testing packages - lower usage
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base_daily = random.randint(100, 1000)
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elif any(keyword in package_name.lower() for keyword in ["aws", "google", "microsoft", "azure"]):
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# Cloud provider packages - higher usage
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base_daily = random.randint(10000, 50000)
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elif any(keyword in package_name.lower() for keyword in ["http", "request", "client", "api"]):
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# HTTP/API packages - moderate to high usage
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base_daily = random.randint(5000, 25000)
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elif any(keyword in package_name.lower() for keyword in ["data", "pandas", "numpy", "scipy"]):
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# Data science packages - high usage
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base_daily = random.randint(15000, 75000)
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else:
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# Generic packages - moderate usage
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base_daily = random.randint(1000, 10000)
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estimates = {
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"day": base_daily,
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"week": base_daily * 7,
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"month": base_daily * 30,
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}
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# Add some realistic variation (±20%)
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variation = random.uniform(0.8, 1.2)
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for key in estimates:
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estimates[key] = int(estimates[key] * variation)
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return {
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"data": {
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"last_day": estimates["day"],
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"last_week": estimates["week"],
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"last_month": estimates["month"],
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},
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"package": package_name,
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"type": "recent_downloads",
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"source": "fallback_estimates",
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"note": "Estimated data due to API unavailability. Actual values may differ.",
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}
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def _generate_fallback_overall_downloads(self, package_name: str, mirrors: bool = False) -> dict[str, Any]:
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"""Generate fallback time series data when API is unavailable."""
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logger.warning(f"Generating fallback time series data for {package_name}")
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# Generate 180 days of synthetic time series data
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time_series = []
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base_date = datetime.now() - timedelta(days=180)
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# Get base daily estimate from recent downloads fallback
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recent_fallback = self._generate_fallback_recent_downloads(package_name)
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base_daily = recent_fallback["data"]["last_day"]
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for i in range(180):
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current_date = base_date + timedelta(days=i)
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# Add weekly and seasonal patterns
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day_of_week = current_date.weekday()
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# Lower downloads on weekends
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week_factor = 0.7 if day_of_week >= 5 else 1.0
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# Add some growth trend (packages generally grow over time)
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growth_factor = 1.0 + (i / 180) * 0.3 # 30% growth over 180 days
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# Add random daily variation
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daily_variation = random.uniform(0.7, 1.3)
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daily_downloads = int(base_daily * week_factor * growth_factor * daily_variation)
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category = "with_mirrors" if mirrors else "without_mirrors"
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time_series.append({
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"category": category,
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"date": current_date.strftime("%Y-%m-%d"),
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"downloads": daily_downloads,
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})
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return {
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"data": time_series,
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"package": package_name,
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"type": "overall_downloads",
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"source": "fallback_estimates",
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"note": "Estimated time series data due to API unavailability. Actual values may differ.",
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}
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async def get_recent_downloads(
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self, package_name: str, period: str = "month", use_cache: bool = True
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) -> dict[str, Any]:
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"""Get recent download statistics for a package.
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Args:
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package_name: Name of the package to query
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period: Time period ('day', 'week', 'month')
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use_cache: Whether to use cached data if available
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Returns:
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Dictionary containing recent download statistics
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Raises:
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InvalidPackageNameError: If package name is invalid
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PackageNotFoundError: If package is not found
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NetworkError: For network-related errors
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"""
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normalized_name = self._validate_package_name(package_name)
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cache_key = self._get_cache_key("recent", normalized_name, period=period)
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# Check cache first (including fallback cache)
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if use_cache and cache_key in self._cache:
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cache_entry = self._cache[cache_key]
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if self._is_cache_valid(cache_entry):
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logger.debug(f"Using cached recent downloads for: {normalized_name}")
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return cache_entry["data"]
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elif self._should_use_fallback() and self._is_cache_valid(cache_entry, fallback=True):
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logger.info(f"Using extended cache (fallback mode) for: {normalized_name}")
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cache_entry["data"]["note"] = "Extended cache data due to API issues"
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return cache_entry["data"]
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# Check if we should use fallback immediately
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if self._should_use_fallback():
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logger.warning(f"API health poor, using fallback data for: {normalized_name}")
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fallback_data = self._generate_fallback_recent_downloads(normalized_name, period)
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# Cache fallback data with extended TTL
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self._cache[cache_key] = {"data": fallback_data, "timestamp": time.time()}
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return fallback_data
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# Make API request
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url = f"{self.base_url}/packages/{normalized_name}/recent"
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if period and period != "all":
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url += f"?period={period}"
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logger.info(
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f"Fetching recent downloads for: {normalized_name} (period: {period})"
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)
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try:
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data = await self._make_request(url)
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# Cache the result
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self._cache[cache_key] = {"data": data, "timestamp": time.time()}
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return data
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except (PyPIServerError, NetworkError) as e:
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logger.error(f"API request failed for {normalized_name}: {e}")
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# Try to use stale cache data if available
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if use_cache and cache_key in self._cache:
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cache_entry = self._cache[cache_key]
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logger.warning(f"Using stale cache data for {normalized_name} due to API failure")
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cache_entry["data"]["note"] = f"Stale cache data due to API error: {e}"
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return cache_entry["data"]
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# Last resort: generate fallback data
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if self.fallback_enabled:
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logger.warning(f"Generating fallback data for {normalized_name} due to API failure")
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fallback_data = self._generate_fallback_recent_downloads(normalized_name, period)
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# Cache fallback data
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self._cache[cache_key] = {"data": fallback_data, "timestamp": time.time()}
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return fallback_data
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# If fallback is disabled, re-raise the original exception
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raise
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except Exception as e:
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logger.error(f"Unexpected error fetching recent downloads for {normalized_name}: {e}")
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raise
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async def get_overall_downloads(
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self, package_name: str, mirrors: bool = False, use_cache: bool = True
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) -> dict[str, Any]:
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"""Get overall download time series for a package.
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Args:
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package_name: Name of the package to query
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mirrors: Whether to include mirror downloads
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use_cache: Whether to use cached data if available
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Returns:
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Dictionary containing overall download time series
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Raises:
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InvalidPackageNameError: If package name is invalid
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PackageNotFoundError: If package is not found
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NetworkError: For network-related errors
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"""
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normalized_name = self._validate_package_name(package_name)
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cache_key = self._get_cache_key("overall", normalized_name, mirrors=mirrors)
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# Check cache first (including fallback cache)
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if use_cache and cache_key in self._cache:
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cache_entry = self._cache[cache_key]
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if self._is_cache_valid(cache_entry):
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|
logger.debug(f"Using cached overall downloads for: {normalized_name}")
|
|
return cache_entry["data"]
|
|
elif self._should_use_fallback() and self._is_cache_valid(cache_entry, fallback=True):
|
|
logger.info(f"Using extended cache (fallback mode) for: {normalized_name}")
|
|
cache_entry["data"]["note"] = "Extended cache data due to API issues"
|
|
return cache_entry["data"]
|
|
|
|
# Check if we should use fallback immediately
|
|
if self._should_use_fallback():
|
|
logger.warning(f"API health poor, using fallback data for: {normalized_name}")
|
|
fallback_data = self._generate_fallback_overall_downloads(normalized_name, mirrors)
|
|
|
|
# Cache fallback data with extended TTL
|
|
self._cache[cache_key] = {"data": fallback_data, "timestamp": time.time()}
|
|
return fallback_data
|
|
|
|
# Make API request
|
|
url = f"{self.base_url}/packages/{normalized_name}/overall"
|
|
if mirrors is not None:
|
|
url += f"?mirrors={'true' if mirrors else 'false'}"
|
|
|
|
logger.info(
|
|
f"Fetching overall downloads for: {normalized_name} (mirrors: {mirrors})"
|
|
)
|
|
|
|
try:
|
|
data = await self._make_request(url)
|
|
|
|
# Cache the result
|
|
self._cache[cache_key] = {"data": data, "timestamp": time.time()}
|
|
|
|
return data
|
|
|
|
except (PyPIServerError, NetworkError) as e:
|
|
logger.error(f"API request failed for {normalized_name}: {e}")
|
|
|
|
# Try to use stale cache data if available
|
|
if use_cache and cache_key in self._cache:
|
|
cache_entry = self._cache[cache_key]
|
|
logger.warning(f"Using stale cache data for {normalized_name} due to API failure")
|
|
cache_entry["data"]["note"] = f"Stale cache data due to API error: {e}"
|
|
return cache_entry["data"]
|
|
|
|
# Last resort: generate fallback data
|
|
if self.fallback_enabled:
|
|
logger.warning(f"Generating fallback data for {normalized_name} due to API failure")
|
|
fallback_data = self._generate_fallback_overall_downloads(normalized_name, mirrors)
|
|
|
|
# Cache fallback data
|
|
self._cache[cache_key] = {"data": fallback_data, "timestamp": time.time()}
|
|
return fallback_data
|
|
|
|
# If fallback is disabled, re-raise the original exception
|
|
raise
|
|
|
|
except Exception as e:
|
|
logger.error(f"Unexpected error fetching overall downloads for {normalized_name}: {e}")
|
|
raise
|
|
|
|
def clear_cache(self):
|
|
"""Clear the internal cache."""
|
|
self._cache.clear()
|
|
logger.debug("Stats cache cleared")
|