The Best NumPy Alternatives in 2026

Apache Hama was a big data and high-performance computing project that has retired.

Chips-n-Salsa provides Java implementations of customizable stochastic and adaptive local search algorithms.

Wind data sources can be accessed from Python with windML, a framework built on NumPy, SciPy, scikit-learn, and Matplotlib.

Jupyter Notebook combines live code, equations, explanatory text, visualizations, and interactive computing in a web platform.

Mars provides tensor-based tools for large-scale computation with NumPy, Pandas, and scikit-learn.

Build native interfaces with Slint, a declarative GUI toolkit for Rust, C++, JavaScript, and Python.

Beautiful Soup provides documentation and downloads for a Python library used to parse HTML.

Ruffus provides a Python library for building computation pipelines used in science and bioinformatics.

TextBlob offers Python natural language processing tools, including tagging, noun phrase extraction, and sentiment analysis.

KoNLPy provides Korean natural language processing tools for Python applications.

Astropy provides a core Python package for astronomy and an ecosystem of affiliated packages.

Statsmodels provides Python tools for inferential statistics, hypothesis testing, and regression.

Use LLM, a command-line utility and Python library, to interact with large language models.

Jupyter Widgets provides interactive Python objects for notebook interfaces, including controls such as sliders and text boxes.

This utility converts cURL commands into code for languages including Python and JavaScript.

spaCy provides Python natural language processing tools for entity recognition, tagging, parsing, and word vectors.

The pandas project provides open-source Python tools for analyzing and manipulating data.

SmartScripter generates custom scripts in Excel VBA, Google Apps Script, Bash, JavaScript, PowerShell, and Python.

PyDy provides Python tools for modeling the dynamics of multibody mechanical systems.

Vaex provides out-of-core DataFrames for Python to explore and visualize large tabular datasets, with support for machine learning workflows.

Jupytext lets users represent Jupyter notebooks as Markdown documents or Julia, Python, and R scripts.

Python developers can use Zipline’s event-driven library to backtest algorithmic trading strategies.

Exploratory data analysis in Python is the focus of Dora, a library with functions for cleaning, feature selection, visualization, and validation.

Build native user interfaces with Slint, an open-source declarative GUI toolkit for Rust, C++, JavaScript, and Python.