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Pycaret

PyCaret is a self-hosted AutoML and machine-learning platform combining a scikit-learn-based Python engine, a FastAPI control plane and a React web interface.

Explore the practical guide ↓

Independent OpenViST project profile, based on linked sources.

Pycaret — OpenViST project profile in AI Data & Analytics.
OpenViST project illustration. See the linked sources for product details.
Understand the project

Practical overview

When it fits

Use PyCaret when you want to explore self-hosted, low-code machine-learning workflows through a web interface and can run the documented Docker Compose setup.

Who it is for

  • Python practitioners setting up classification, clustering or anomaly-detection workflows.
  • Teams seeking a local interface to organize machine-learning projects, experiments and runs.

Documented uses

  • Configure machine-learning workflows through a point-and-click interface.
  • Organize workspaces, projects, experiments and runs.
  • Use a model registry as part of the documented platform.
Before you choose

Requirements & limits

The repository documents local self-hosting through Docker Compose and says the first administrator account and workspace are created in the initial setup screen.

  • The repository identifies the 4.0 line as work in progress.
  • The documented local arrangement uses a React web container and a FastAPI container with in-process scheduling and compute, plus SQLite in a Docker volume.
  • The repository says that separating storage, database, secrets, queue and compute is an architectural aim, while many protocol extractions remain ahead.

Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.

Source-based practical guide

Set up PyCaret locally with Docker Compose

Start the documented local PyCaret platform and reach its initial setup screen.

Before you start

  • Docker Desktop 4.27 or later, or Docker Engine 25.0 or later with Compose v2.24 or later.

Steps

  1. Clone the PyCaret repository: git clone https://github.com/pycaret/pycaret.git

  2. Change into the repository directory: cd pycaret

  3. Start the build and services: docker compose up --build

  4. After the API reports startup complete and the web container starts nginx, open http://localhost:3020 and create the first administrator account and workspace.

Expected outcome

A local web interface opens at port 3020 and presents the initial administrator and workspace setup.

Guide limitations

  • The first build is described as taking about five minutes.
  • The repository identifies the 4.0 line on main as work in progress.
  • The documented local setup uses a compact two-container arrangement with SQLite persisted in a Docker volume.
Documentation 1 ↗
Evidence and transparency

Sources & review

Official repository ↗
Source record details
Source availability
Active
Sources checked
17 October 2026
Original website title
pycaret/pycaret · Official homepage title · retained in its source language
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