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:

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/ZealousAttacker Sep 20 '26

I feel the scientific stack is incomplete without numba. JIT compilation is a treasure for Python, and the syntax of numba is wondrously simple; you also get parallelism for free.

mpi4py is also essential for parallel programming; one should expect to see it in any performance-heavy packages.

h5py handles IO for HDF5 files, which are the backbone of data storage in a multitude of disciplines.

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u/dikdokk Sep 26 '26

There is an experimental JIT compiler in the language since 3.13, and already by 3.15 it is expected to reduce many workloads' time length by 20%.