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.
22 lines
512 B
Python
22 lines
512 B
Python
from pathlib import Path
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from sqlalchemy import create_engine
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from sqlalchemy.orm import sessionmaker
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DB_DIR = Path("/app/storage/db")
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DB_DIR.mkdir(parents=True, exist_ok=True)
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SQLALCHEMY_DATABASE_URL = f"sqlite:///{DB_DIR}/db.sqlite"
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engine = create_engine(
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SQLALCHEMY_DATABASE_URL,
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connect_args={"check_same_thread": False}
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)
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SessionLocal = sessionmaker(autocommit=False, autoflush=False, bind=engine)
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def get_db():
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db = SessionLocal()
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try:
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yield db
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finally:
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db.close() |