10 Practical Python Libraries You Should Know

This article recommends ten practical Python libraries, providing brief introductions, key features, and links to their open‑source repositories.

1. Typer

Typer, built on the same principles as FastAPI, is a high‑performance framework for creating CLI applications, offering automatic code completion, editor integration, and easy validation when combined with Click.

Open‑source address: https://github.com/tiangolo/typer

2. Rich

Rich brings colorful, richly formatted output to the terminal, supporting tables, progress bars, syntax highlighting, and more, and works on Linux, macOS, and Windows (requires Python 3.6.1+).

Open‑source address: https://github.com/willmcgugan/rich

3. Dear PyGui

Dear PyGui is a powerful, easy‑to‑use Python GUI framework that uses an immediate‑mode paradigm and GPU rendering, supporting Windows, Linux, and macOS, and includes tools such as documentation viewers and loggers.

Open‑source address: https://github.com/hoffstadt/DearPyGui

4. PrettyErrors

PrettyErrors simplifies Python error messages with colored output, stack‑trace filtering, and highlights key information, improving debugging efficiency without requiring installation.

Open‑source address: https://github.com/onelivesleft/PrettyErrors

5. Diagrams

Diagrams lets you draw cloud‑architecture diagrams directly in Python code using Graphviz, supporting icons from AWS, Azure, GCP, and more.

Open‑source address: https://github.com/mingrammer/diagrams

6. Hydra and OmegaConf

Hydra simplifies configuration management for machine‑learning projects by allowing hierarchical overrides from the command line or config files; OmegaConf provides the underlying API for handling YAML, objects, and CLI arguments.

Open‑source addresses: https://github.com/facebookresearch/hydra , https://github.com/omry/omegaconf

7. PyTorch Lightning

PyTorch Lightning is a lightweight wrapper for PyTorch that separates research code from engineering, enabling scalable training on CPUs, GPUs, and TPUs, and supports exporting models to ONNX or TorchScript.

Open‑source address: https://github.com/PyTorchLightning/PyTorch-lightning

8. Hummingbird

Hummingbird, from Microsoft, compiles trained ML models into tensor operations, allowing existing PyTorch or scikit‑learn code to run efficiently on various back‑ends such as ONNX and TVM.

Open‑source address: https://github.com/microsoft/hummingbird

9. HiPlot

HiPlot is an interactive high‑dimensional data visualization tool from Facebook AI, offering parallel plots and web services that can ingest CSV/JSON or custom Python parsers for exploring model hyperparameters.

Open‑source address: https://github.com/facebookresearch/hiplot

10. Scalene

Scalene is a fast CPU and memory profiler for Python scripts that works with multithreaded code, distinguishing Python and native execution time, and produces line‑by‑line performance reports without code modification.

Open‑source address: https://github.com/emeryberger/scalene

Additional libraries such as Norfair, Quart, Alibi‑detect, and Einops are also mentioned for further exploration.