autojanet/skills/understand/languages/python.md

Python Language Prompt Snippet

Key Concepts

• Decorators: Functions that wrap other functions or classes using @decorator syntax
• List/Dict Comprehensions: Concise syntax for creating collections from iterables
• Generators and Yield: Lazy iterators using yield for memory-efficient data processing
• Context Managers: with statement for resource management via __enter__/__exit__
• Type Hints and Typing Module: Optional static type annotations for tooling and documentation
• Dunder Methods: Special methods like __init__, __repr__, __eq__ defining object behavior
• Metaclasses: Classes that define how other classes are created (type as default metaclass)
• Dataclasses: @dataclass decorator auto-generating boilerplate from field annotations
• Protocols: Structural subtyping via typing.Protocol for duck-type-safe interfaces
• Descriptors: Objects defining __get__, __set__, __delete__ to customize attribute access
• Async/Await with Asyncio: Cooperative concurrency using coroutines and an event loop

Import Patterns

• from module import name — import specific name from module
• import module — import entire module, access via module.name
• from package.module import name — absolute import from nested package
• from . import relative — relative import within a package

File Patterns

• __init__.py — package initializer (barrel equivalent), can re-export public API
• __main__.py — package entry point when run with python -m package
• conftest.py — pytest shared fixtures and hooks (auto-discovered)
• setup.py / pyproject.toml — project configuration and build metadata
• requirements.txt — pinned dependency list

Common Frameworks

• Django — Full-stack web framework with ORM, admin, and batteries included
• FastAPI — Modern async API framework with automatic OpenAPI docs
• Flask — Lightweight WSGI micro-framework for web applications
• SQLAlchemy — SQL toolkit and ORM with unit-of-work pattern
• Celery — Distributed task queue for background job processing
• Pydantic — Data validation and settings management using type annotations

Example Language Notes

Uses @dataclass decorator to auto-generate __init__, __repr__, and __eq__ from field annotations. This eliminates boilerplate while keeping the class definition readable and the generated methods consistent.

When __init__.py re-exports symbols, it acts as the package's public API surface — consumers import from the package rather than reaching into internal modules.