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
40 lines
1.5 KiB
Python
40 lines
1.5 KiB
Python
#!/usr/bin/env python3
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"""Direct test of fallback mechanisms."""
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import asyncio
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import sys
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import os
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sys.path.insert(0, os.path.abspath("."))
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from pypi_query_mcp.core.stats_client import PyPIStatsClient
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async def test_fallback():
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"""Test fallback data generation directly."""
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print("Testing fallback data generation...")
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async with PyPIStatsClient() as client:
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# Force API failure tracking to trigger fallback
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client._api_health["consecutive_failures"] = 5 # Force fallback mode
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# Test recent downloads fallback
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fallback_recent = client._generate_fallback_recent_downloads("requests", "month")
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print(f"✅ Fallback recent downloads generated for requests:")
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print(f" Source: {fallback_recent.get('source')}")
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print(f" Downloads: {fallback_recent['data']['last_month']:,}")
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print(f" Note: {fallback_recent.get('note')}")
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# Test overall downloads fallback
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fallback_overall = client._generate_fallback_overall_downloads("numpy", False)
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print(f"\n✅ Fallback time series generated for numpy:")
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print(f" Source: {fallback_overall.get('source')}")
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print(f" Data points: {len(fallback_overall['data'])}")
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print(f" Note: {fallback_overall.get('note')}")
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# Test the should_use_fallback logic
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should_fallback = client._should_use_fallback()
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print(f"\n✅ Fallback logic working: {should_fallback}")
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if __name__ == "__main__":
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asyncio.run(test_fallback()) |