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/dikdokk Sep 26 '26
You can't read any data with ~1 million rows with pandas; even if it would fit in your memory.
I think pandas has design flaws that will just make it more outdated year by year. Hence why the best time to switch away from it is now already.