What is Orange used for?

Orange is a visual data mining and machine learning toolbox where analyses are built as workflows of widgets, so users need little programming. Built in Python. It is a good fit for teaching data science without coding, exploratory analysis of tabular data and prototyping machine learning workflows.

Is Orange open source?

Yes. Orange is open source under a custom licence. Its source code is on GitHub at biolab/orange3 and is written mainly in Python.

Yes. Orange is open source, so the software itself is free to use under the terms of its own licence.

Can I self-host Orange?

Yes. Orange can be self-hosted on your own server or infrastructure; there is no official hosted version.

What is Orange an alternative to?

Orange is an open-source alternative to IBM SPSS Statistics, Alteryx, Dataiku and Spotfire. Other open-source alternatives to IBM SPSS Statistics include RStudio.

Is Orange actively maintained?

Yes. The most recent commit to Orange was on 13 October 2026, and the latest release is 3.40.0, published on 20 December 2025. The project has 5.7k stars on GitHub.

Orange (biolab/orange3): open-source analytics

About Orange

Orange is a data mining and visualization toolbox aimed at both beginners and experienced analysts. Instead of writing code, users assemble analyses as workflows on a canvas, which hides the underlying mechanics and exposes intuitive concepts. The project's stated goal is that anyone who owns data should be able to explore it.

The toolbox covers interactive data visualization along with classic machine learning methods such as classification, regression, clustering, decision trees and random forests. It is written in Python on top of scikit-learn, NumPy, SciPy and pandas, and extra functionality is added through add-ons installed from the menu bar; developers can write their own widgets from an example template.

Windows and macOS users can download a standalone installer, while Linux users and developers can install with conda, pip or uv, and winget is available on Windows. The project is open source, welcomes new widgets and contributions, and has a community on Discord.

Key features

Visual workflow canvas built from widgets
Interactive data visualization
Classification, regression and clustering
Decision trees and random forests
Add-ons installable from the menu bar
Custom widgets written in Python
Standalone installers for Windows and macOS

Good fit for

Teaching data science without coding
Exploratory analysis of tabular data
Prototyping machine learning workflows

Built with: Python tools
Tags: data-mining; data-science; machine-learning; visualization; visual-programming; python; clustering; classification

Orange: questions and answers

What is Orange used for?: Orange is a visual data mining and machine learning toolbox where analyses are built as workflows of widgets, so users need little programming. Built in Python. It is a good fit for teaching data science without coding, exploratory analysis of tabular data and prototyping machine learning workflows.
Is Orange open source?: Yes. Orange is open source under a custom licence. Its source code is on GitHub at biolab/orange3 and is written mainly in Python.
Is Orange free?: Yes. Orange is open source, so the software itself is free to use under the terms of its own licence.
Can I self-host Orange?: Yes. Orange can be self-hosted on your own server or infrastructure; there is no official hosted version.
What is Orange an alternative to?: Orange is an open-source alternative to IBM SPSS Statistics, Alteryx, Dataiku and Spotfire. Other open-source alternatives to IBM SPSS Statistics include RStudio.
Is Orange actively maintained?: Yes. The most recent commit to Orange was on 13 October 2026, and the latest release is 3.40.0, published on 20 December 2025. The project has 5.7k stars on GitHub.