Noteworthy Packages

Non-exhaustive list of popular packages useful to scientists.

Scientific

• NumPy: multi-dimensional arrays and various numerical computing tools.

• SciPy: routines for numerical integration, interpolation, linear algebra etc.

• SymPy: symbolic mathematics.

• pandas: powerful data analysis with a 3500+ pages manual.

• matplotlib, seaborn, bokeh: plotting and data visualization.

• scikit-learn, TensorFlow, Keras, PyTorch: machine learning and deep learning.

• numba, dask: higher performance computing.

Not directly scientific

• sphinx: documentation generator (incl LaTeX export).

  • MyST: Markedly Structured Text is a Markdown flavor with extended features.

  • jupyterbook: create books and other documents from Jupyter notebooks.

• requests, httpx: make HTTP and API calls.

• click: command-line interface creation kit.

• jinja: templating engine to generate files from data, code and a template.

• cookiecutter: create projects and file structures from templates.

• flask, django: web frameworks to create APIs or web pages.

• SQLAlchemy: database toolkit and object relational mapper (ORM).

• pillow: “Python Imaging Library” for image processing.

• lxml, scrapy, beautifulsoup: web scraper and parser.

• pytest: testing framework.