
- 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.
3 lines
82 B
Python
3 lines
82 B
Python
from sqlalchemy.ext.declarative import declarative_base
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Base = declarative_base() |