4730c37915
- Created FastAPI application with transaction ingestion endpoints - Built dynamic rule engine supporting velocity checks and aggregations - Implemented real-time and batch screening capabilities - Added rule management with versioning and rollback functionality - Created comprehensive audit and reporting endpoints with pagination - Set up SQLite database with proper migrations using Alembic - Added intelligent caching for aggregate computations - Included extensive API documentation and example rule definitions - Configured CORS, health endpoints, and proper error handling - Added support for time-windowed aggregations (sum, count, avg, max, min) - Built background processing for high-volume batch screening - Implemented field-agnostic rule conditions with flexible operators Features include transaction ingestion, rule CRUD operations, real-time screening, batch processing, aggregation computations, and comprehensive reporting capabilities suitable for fintech fraud monitoring systems.
36 lines
904 B
Python
36 lines
904 B
Python
from fastapi import FastAPI
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from fastapi.middleware.cors import CORSMiddleware
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from app.api.routes import router as api_router
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app = FastAPI(
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title="Transaction Fraud Monitoring API",
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description="API-driven transaction monitoring system for fraud detection",
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version="1.0.0",
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openapi_url="/openapi.json"
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)
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app.add_middleware(
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CORSMiddleware,
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allow_origins=["*"],
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allow_credentials=True,
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allow_methods=["*"],
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allow_headers=["*"],
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)
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app.include_router(api_router, prefix="/api/v1")
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@app.get("/")
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async def root():
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return {
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"title": "Transaction Fraud Monitoring API",
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"documentation": "/docs",
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"health": "/health"
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}
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@app.get("/health")
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async def health_check():
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return {"status": "healthy", "service": "transaction-fraud-monitoring"}
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if __name__ == "__main__":
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import uvicorn
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uvicorn.run(app, host="0.0.0.0", port=8000) |