AI SummaryPricingEngine provides GitHub Copilot with detailed instructions for a distributed pricing system built on PySpark and FastAPI, helping developers understand architecture, best practices, and implementation patterns for scalable price calculations.
Install
Copy this and paste it into Claude Code, Cursor, or any AI assistant:
I want to add the "PricingEngine — Copilot Instructions" prompt rules to my project. Repository: https://github.com/dmoriart/PricingEngine Please read the repo to find the rules/prompt file, then: 1. Download it to the correct location (.cursorrules, .windsurfrules, .github/prompts/, or project root — based on the file type) 2. If there's an existing rules file, merge the new rules in rather than overwriting 3. Confirm what was added
Description
A high-performance pricing engine built with PySpark and FastAPI for scalable price calculations and API services
PricingEngine Project Instructions
This is a PySpark-based pricing engine with FastAPI REST API endpoints. The project follows these key principles:
Architecture
• Core: Spark session management and shared utilities • Pricing: Business logic for price calculations using PySpark DataFrames • API: FastAPI-based REST endpoints for pricing operations • Config: Environment-based configuration management • Tests: Comprehensive test coverage for all components
Key Technologies
• PySpark: For distributed data processing and pricing calculations • FastAPI: For high-performance API endpoints with automatic documentation • Pydantic: For data validation and settings management • Uvicorn: ASGI server for running the API
Code Guidelines
• Use type hints throughout the codebase • Follow PEP 8 style guidelines • Implement proper error handling and logging • Write comprehensive tests for all business logic • Use dependency injection for testability
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Works With
Any AI assistant that accepts custom rules or system prompts