#python
4 skillsModern Python Project Instructions (uv + ruff + pytest)CLAUDE.md for Python projects managed with uv: dependency rules, ruff lint/format gates, pytest conventions, and a no-untyped-code policy agents can verify.Claude Code · CodingClaude CodeCLAUDE.mdModern Python Project Instructions (uv + ruff + pytest)CLAUDE.md for Python projects managed with uv: dependency rules, ruff lint/format gates, pytest conventions, and a no-untyped-code policy agents can verify.Use in any Python 3.12+ project that uses uv for environments and packaging, so agents run the right commands and never reach for pip, poetry, or unformatted code.@libraryCodingFastAPI Project RulesFastAPI conventions for Pydantic v2 schemas, Depends-based wiring, async discipline, and a predictable router layout.Cursor · CodingCursor.cursorrulesFastAPI Project RulesFastAPI conventions for Pydantic v2 schemas, Depends-based wiring, async discipline, and a predictable router layout.Use in FastAPI services with Pydantic v2 to keep routers thin, dependencies explicit, and blocking calls out of the event loop.@libraryCodingDjango Project InstructionsCLAUDE.md for Django projects: app structure, ORM query rules, migration workflow, layered settings, and pytest-django conventions agents must follow before touching models.Claude Code · CodingClaude CodeCLAUDE.mdDjango Project InstructionsCLAUDE.md for Django projects: app structure, ORM query rules, migration workflow, layered settings, and pytest-django conventions agents must follow before touching models.Use in a Django 5.x codebase so agents handle migrations safely, keep business logic out of views, and avoid N+1 queries when writing or reviewing ORM code.@libraryCodingWindsurf Rules for Python Data PipelinesOpinionated rules for pandas/polars pipelines: validate schemas at every boundary, process incrementally by partition, and never mutate a DataFrame in place.Windsurf · CodingWindsurf.windsurfrulesWindsurf Rules for Python Data PipelinesOpinionated rules for pandas/polars pipelines: validate schemas at every boundary, process incrementally by partition, and never mutate a DataFrame in place.Use in Python repos that move data through ETL/ELT stages with pandas or polars, especially when silent schema drift or full-table reprocessing has burned you before.@libraryCoding