Top 10 Must‑Know Python Libraries of 2020 (Plus Bonus Picks)

This is the sixth annual Python library ranking, focusing on libraries released or popularized in 2020, well‑maintained, and notably impressive.

1. Typer

Typer, created by Sebastián Ramírez after FastAPI’s success, leverages Python 3.6+ type hints to build command‑line interfaces with minimal effort, offering auto‑completion and validation while being built on the robust Click library.

Its documentation is exemplary and the project is available at GitHub .

2. Rich

Rich transforms terminal output with colors, styles, tables, progress bars, Markdown, and emojis, dramatically improving the visual experience of CLI applications.

Project link: GitHub .

3. Dear PyGui

Dear PyGui is a Python port of the popular Dear ImGui C++ library, using an immediate‑mode paradigm that renders GUI frames independently, delivering high performance via GPU acceleration on Windows, Linux, and macOS.

Project link: GitHub .

4. PrettyErrors

PrettyErrors enhances traceback readability in color‑supported terminals, turning cryptic stack traces into clear, human‑friendly messages.

Project link: GitHub .

5. Diagrams

Diagrams lets developers draw cloud architecture diagrams directly in Python code, supporting AWS, Azure, GCP icons and enabling version‑controlled, code‑first infrastructure visuals.

Project link: GitHub .

6. Hydra & OmegaConf

Hydra enables composable configuration management for machine‑learning experiments, allowing hierarchical overrides via CLI or config files.

Example usage:

python train_model.py variation=option_a,option_b

OmegaConf provides a consistent API for layered configurations, supporting YAML, config files, objects, and CLI arguments.

7. PyTorch Lightning

PyTorch Lightning separates scientific research from engineering concerns, offering a structured framework that maintains full PyTorch flexibility while improving productivity and scalability across GPUs, TPUs, and CPUs.

Project link: GitHub .

8. Hummingbird

Hummingbird compiles traditional scikit‑learn models (e.g., random forests, LightGBM, XGBoost) into tensor operations, enabling fast inference on PyTorch, TorchScript, ONNX, and TVM backends without rewriting code.

Project link: GitHub .

9. HiPlot

HiPlot visualizes high‑dimensional data with parallel coordinates and other interactive plots, usable within Jupyter notebooks or via a standalone server.

Project link: GitHub .

10. Scalene

Scalene is a CPU and memory profiler for Python that accurately handles multithreaded and native extensions, producing detailed per‑line performance reports without code modification.

Project link: GitHub .

Bonus: Norfair

Norfair is a lightweight, customizable Python library for real‑time object tracking, assigning unique IDs to detections across frames and allowing user‑defined distance functions.

Project link: GitHub .

Honorable Mentions

quart – async web framework compatible with Flask APIs.

alibi‑detect – monitors production models for anomalies and data drift.

einops – readable tensor operations for NumPy, PyTorch, TensorFlow, etc.

stanza – Stanford NLP toolkit for 60+ languages.

datasets – HuggingFace library for sharing and accessing datasets.

pytorch‑forecasting – simplifies time‑series forecasting with neural nets.

sktime – scikit‑learn‑compatible time‑series algorithms and deep‑learning extensions.

netron – visualizer for neural‑network models supporting many formats.

pycaret – high‑level wrapper that streamlines common machine‑learning workflows.

tensor‑sensor – improves tensor math error messages and visualizations.