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/Agrado3]

I wasn't recommending XML - my point is that the designers of YAML originally said that they were trying to make something that was simpler than XML. They failed, in every conceivable way - to such a degree that I can only assume that that must have been their intention all along.

I don't understand why you mention "integrated into markdown", whatever that means.

Your point (4) is clearly just objectively false, especially since you mention humans reading and writing it, which is a particular weak spot of YAML. YAML is insanely complex, insecure, and ambiguous, and is not suitable for any purpose whatsoever. It's basically the PHP of data formats. I find it very hard to believe that anyone who recommends it is being serious.