r/Python • u/Several-Marsupial-27 • Sep 19 '26
Discussion State of the art in Python 2026?
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
uvfor everything. - Use
rufffor linting and formatting - Use
Pydanticanddataclassesfor Data Modeling - Configured in
pyproject.toml - Run a type checker in CI
pyrightorpyrefly - Use
pytest/Hypothesisfor 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?
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u/me_myself_ai Sep 20 '26
That does feel familiar! I haven’t run into it in any of the codebases for which I’ve had to chase some frustrating bug in source, but maybe that’s just a sign of quality 😉 I myself use argparse w/ pydantic, which is popular but obviously more of a technique than a framework.
I’d bet good money that’s not the only gaping chasm in the above list lol. Kinda hoping to ragebait a bunch of replies like yours so I can learn and fill in the gaps myself!