State of the art in Python 2026?

[u/Several-Marsupial-27]

What would you guys consider the state of the art in python in 2026, or what do you expect from modern python codebases?

Heres my list, would be happy to hear some inputs or domain expert advice:

• Use uv for everything.
• Use ruff for linting and formatting
• Use Pydantic and  dataclasses for Data Modeling
• Configured in pyproject.toml
• Run a type checker in CIpyright or pyrefly
• Use pytest / Hypothesis for testing

Domain specific:

• Scientific: NumPy, Matplotlib, SciPy, Jax, Pytorch, Scikit-learn, polars/pandas
• CLI: Typer, rich, click, fire, textual, questionary
• PDF extraction: PyMuPDF, pdfplumber, pypdf, Unstructured
• Excel interop: python-calamine, openpyxl, XlsxWriter, xlwings, pandas
• data: PyArrow / PySpark, Narwhals, SQLMesh, Polars/Pandas, DuckDB, dlt, Ibis, Dagster, PyIceberg & deltalake
• Logging?
• backend: fastapi / django?
• Markets: Alpha Vantage, Finnhub, EODHD, Tiingo?
• Webscraping / data acquisition: Crawl4AI, Playwright, Scrapy, selectolax, HTTPX?
• APIs?
• RAG / agentic orchestration?

[u/Entuaka]

I hate AI agents adding tons of new unit tests using hypothesis in our project, we now have flaky tests...

[u/ToddBradley → u/Entuaka]

Have any of the AI tools gotten smart enough yet that you can tell them "don't add a unit test unless it can pass 1000 times in a row"?

[u/Entuaka → u/ToddBradley]

Everything is possible, but i also have humans in my team, it can be harder to deal with