Add comprehensive test suite for image processing and related services
- Implement tests for database generator to ensure proper session handling. - Create tests for EXIF extraction and conversion functions. - Add tests for image-related endpoints, ensuring proper data retrieval and isolation between clients. - Develop tests for OCR functionality, including language detection and text extraction. - Introduce tests for the image processing pipeline, covering success and failure scenarios. - Validate rate limiting functionality and ensure independent counters for different clients. - Implement scraper tests to verify HTML content fetching and error handling. - Add unit tests for various services, including storage and filename generation. - Establish worker entry point for ARQ to handle background image processing tasks.
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"""
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Middleware de logging HTTP — enregistre chaque requête avec structlog.
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Exclut les endpoints de santé (/health, /metrics) pour réduire le bruit.
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"""
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import time
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import logging
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from starlette.middleware.base import BaseHTTPMiddleware
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from starlette.requests import Request
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from starlette.responses import Response
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logger = logging.getLogger("http")
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# Chemins exclus du logging
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_EXCLUDED_PATHS = {"/health", "/health/detailed", "/metrics", "/favicon.ico"}
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class LoggingMiddleware(BaseHTTPMiddleware):
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async def dispatch(self, request: Request, call_next) -> Response:
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if request.url.path in _EXCLUDED_PATHS:
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return await call_next(request)
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start = time.monotonic()
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client_id = getattr(request.state, "client_id", "anonymous")
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response = await call_next(request)
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duration_ms = int((time.monotonic() - start) * 1000)
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logger.info(
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"http.request",
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extra={
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"method": request.method,
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"path": request.url.path,
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"status": response.status_code,
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"duration_ms": duration_ms,
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"client_id": str(client_id),
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},
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)
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return response
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