pythonic

name	pythonic
description	Python, asyncio, typed Python, data processing, SQL, pandas, document extraction, notebooks, scraping, APIs, and scientific computing.
when_to_use	Writing or reviewing Python for tooling, data work, or quick prototypes around chan; pushing work to the right engine (SQL, NumPy/pandas, asyncio).

Pythonic

Write modern, typed, idiomatic Python. Push work to the right engine: SQL for sets, NumPy/pandas for vectorized data work, asyncio for I/O concurrency.

Code

• Type public function signatures and complex data structures.
• Use dataclasses for internal structured data.
• Use Pydantic at validation boundaries when the project already uses it or the boundary is complex enough to justify it.
• Prefer context managers for files, sockets, database connections, and temp resources.
• Catch specific exceptions and re-raise with context.

Async

• Use asyncio.TaskGroup on Python 3.11+ for structured concurrency.
• Track created tasks; avoid fire-and-forget.
• Do not confuse CPU-bound work with I/O concurrency.

Data And SQL

• Validate shape and types at pipeline boundaries.
• Prefer vectorized pandas/NumPy operations over row-wise apply.
• Push filtering and aggregation into SQL before loading DataFrames.
• Use parameterized SQL. Never format user input into SQL strings.

Verification

• Use project tooling first: pytest, ruff, mypy, uv, or equivalents.
• Add focused tests for bug fixes, parsing boundaries, and error paths.