Jupyter Lab

Interactive development environment for notebooks, code, and data

JupyterLab is a web-based interactive development environment for notebooks, code, and data, backed by remote compute. This image bundles JupyterLab on top of Miniconda, served straight to the browser — no desktop or VNC.

Usage

1. Deploy

dxflow workflow create --identity jupyter hub://jupyter

# Start with defaults, or tune per run with --override
dxflow workflow start jupyter
dxflow workflow start jupyter \
    --override env.app.PASSWORD=my-strong-pass \
    --override env.app.WORKING_DIR=projects/analysis

# Publish the web port on an HTTPS link
dxflow workflow start jupyter --link

2. Open the notebook

Open your browser at http://localhost:8888 and sign in with the password you set in PASSWORD. JupyterLab opens on the working directory. A start given --link publishes port 8888 at an HTTPS URL printed on the start line, opening JupyterLab from anywhere.

3. Persist data

Notebooks and data live under /volume, so your work survives restarts — mount a local directory there to keep it.

Configuration

name: jupyter
tags:
    - analytics
steps:
    - name: app
      runtime: docker
      mode: parallel
      image: ghcr.io/dxflow-ai/jupyter:latest
      volumes:
          - name: volume
            host: ./volume
            container: /volume
      ports:
          - name: web
            host: "8888"
            container: "8888"
      env:
          - PASSWORD=dxflow
          - WORKING_DIR=
      resources:
          cpu: "4"
          memory: 8G
      link: web

[volume]
app.volume = ./volume

[port]
app.web = 8888

[env]
app.PASSWORD = dxflow
app.WORKING_DIR =

[resource]
app.cpu = 4
app.memory = 8G

{
    "arch": ["amd64", "arm64"],
    "image": "ghcr.io/dxflow-ai/jupyter:latest",
    "version": "4.2",
    "minimum": {
        "cpu": 4,
        "memory": "8G",
        "storage": "50G"
    }
}

Notes

WORKING_DIR is resolved under /volume (empty opens /volume). Set it to a subpath like projects/analysis to open straight into a project.
Set a strong PASSWORD; it defaults to dxflow, which every reader of this page knows. JupyterLab asks for it on a sign-in page and the token is disabled, so the password is the only way in.
Miniconda is at /opt/miniconda and on the PATH — use conda and pip from a notebook terminal to add libraries such as numpy, pandas, scikit-learn, or extensions like jupyterlab-git.

Analytics

Pre-configured workflows for interactive computing, data analysis, and machine learning

RStudio Server

Browser-based IDE for R statistical computing and graphics