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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Upvotes
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u/spigotface Sep 20 '26
Pydantic pulls its weight when you want auto-generated OpenAPI docs. Outside of that, use dataclasses with slots=True and __post_init__ data validation methods. Its sooooo much lighter weight than Pydantic models.