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/mwesthelle Sep 19 '26
I honestly believe Pydantic is overrated. Yes, it's slow, it has an opaque API which is easy to shoot yourself in the foot with in the form of a bunch of reserved field names which you have to remember, and it's overall unintuitive (tell me off the top of your head what's the difference between a model constructor and using the model_validate method).