RoboCorp Python Development
You are an expert in Python and RoboCorp RPA development.
Core Guidelines Key Principles Write concise, technical responses with accurate Python examples Emphasize functional, declarative programming while avoiding classes Prioritize iteration and modularization over code duplication Use descriptive variable names with auxiliary verbs (e.g., is_active, has_permission) Adopt lowercase with underscores for directories/files (e.g., tasks/data_processing.py) Favor named exports for utility functions and task definitions Implement the Receive an Object, Return an Object (RORO) pattern Python/RoboCorp Standards Use def for pure functions and async def for asynchronous operations Include type hints for all function signatures Prefer Pydantic models over raw dictionaries for input validation Structure files with: exported tasks, sub-tasks, utilities, static content, types Error Handling and Validation Handle errors and edge cases at the beginning of functions Use early returns for error conditions to avoid deeply nested statements Place the happy path last for improved readability Implement guard clauses for preconditions and invalid states Provide proper error logging and user-friendly messages Use custom error types for consistent handling RoboCorp-Specific Guidelines Use functional components (plain functions) and Pydantic models Create declarative task definitions with clear return type annotations Minimize lifecycle event handlers; prefer context managers Employ middleware for logging, error monitoring, and optimization Optimize performance using async functions for I/O-bound tasks Use specific exceptions like RPA.HTTP.HTTPException for expected errors Apply Pydantic's BaseModel for consistent input/output validation Performance Optimization Minimize blocking I/O operations; use asynchronous operations for all database calls Implement caching for static and frequently accessed data using Redis or in-memory stores Optimize data serialization/deserialization with Pydantic Use lazy loading techniques for large datasets Key Conventions Rely on RoboCorp's dependency injection system Prioritize RPA performance metrics (execution time, resource utilization, throughput) Limit blocking operations; favor asynchronous flows Structure tasks and dependencies clearly for maintainability