Exploratory data work, teaching material, and research code all live in the same browser tab with JupyterLab, the web workspace of Project Jupyter. Notebooks combine runnable code cells, Markdown, and rich output such as images, JSON, and Vega charts, and they use the same notebook format as the classic Jupyter Notebook. Any Jupyter kernel can execute the code, so Python, R, and other languages share one interface, and code inside plain text files such as Markdown or LaTeX can be run interactively as well. Tabs and splitters arrange documents side by side, and a notebook's cell outputs can be mirrored into their own tab to build a simple dashboard with interactive controls. Code consoles serve as scratchpads linked to a notebook kernel, while full terminals run system shells such as bash on the server. A visual debugger offers breakpoints, a call stack, and a variable explorer for kernels that support the Jupyter debug protocol. Markdown, CSV, and Vega documents show a live preview as they are edited, and built-in viewers handle images, JSON, and PDF files. The Extension Manager installs themes, editors, and renderers from PyPI, and real-time collaboration becomes available by adding the jupyter-collaboration extension. Access is protected by a generated token unless a password is set. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. BSD-3-Clause licensed.

Marimo is a reactive Python notebook that treats cells like spreadsheet formulas: change one cell or interact with a UI widget and every dependent cell automatically re-executes, eliminating the hidden state bugs that make traditional notebooks unreliable. Backed by over 22,000 GitHub stars, notebooks are stored as pure Python files with PEP 723 inline metadata, making them Git-diffable, importable as modules, executable as CLI scripts with parameterized arguments, and testable with PyTest. Built-in SQL cells query Polars, Pandas, PyArrow, DuckDB, SQLite, PostgreSQL, and MySQL databases, with results automatically flowing into the reactive dependency graph. The AI-native editor provides GitHub Copilot autocomplete, context-aware assistants that access live runtime variables, inline code edits powered by configurable models from OpenAI, Anthropic, or local Ollama instances, and a pair mode that lets external AI agents connect over WebSocket. Notebooks become read-only interactive web applications with marimo run, collaborative authoring environments with marimo edit, or embedded flows inside existing FastAPI applications through ASGI middleware. Gallery mode serves multiple notebooks from a single instance with an auto-generated index page. The Docker image ships with SQL support, token-based authentication, health check endpoints at /health and /api/status, and configurable WebSocket or SSE kernel transport for proxy compatibility. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. Apache 2.0 licensed.

Backed by Y Combinator with 4,300 GitHub stars and growing rapidly since its September 2024 launch, Briefer delivers the first truly unified notebook-and-dashboard platform that eliminates the fragmented workflow of juggling Jupyter for analysis, Tableau for visualization, and Notion for documentation — combining all three in a single Notion-like workspace where SQL query results automatically become Python DataFrames accessible in subsequent code blocks. The built-in AI analyst understands your database schema and notebook context to generate SQL queries, write Python transformations, create visualizations, and fix errors on demand using configurable OpenAI or private LLM backends. Connect directly to PostgreSQL, MySQL, BigQuery, Redshift, Snowflake, and Amazon Athena as data sources, or upload CSV files for immediate analysis. Native point-and-click visualizations produce charts, tables, and dashboards without writing code, while interactive data apps use inputs, dropdowns, and date pickers to create parameterized reports for non-technical stakeholders. Scheduled execution runs notebooks and dashboards periodically with results delivered via Slack integration or public shareable links. Write-back queries modify production data directly from notebooks for ad-hoc pipeline testing. The architecture runs as three Docker containers — web frontend, API server, and optional AI service — backed by PostgreSQL and a Jupyter server for Python execution, deployable via single Docker command, Docker Compose, or Helm charts for Kubernetes. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. AGPLv3 licensed.

Livebook is an interactive notebook for Elixir where you write code alongside rich Markdown prose, execute it cell by cell with reactive dependency tracking, and deploy finished notebooks as standalone web applications with a single click. Nearly 6,000 GitHub stars reflect the Elixir core team's investment in a platform where code cells run on demand alongside Mermaid diagrams and KaTeX mathematical formulas. The Kino visualization library renders Vega-Lite charts, interactive data tables with sorting and pagination, Leaflet maps, and Mermaid diagrams directly within notebook output cells, while custom Kino components enable building interactive controls with sliders, text inputs, and buttons that feed values back into running code. Smart cells abstract high-level tasks into configurable UI widgets: query PostgreSQL, MySQL, SQLite, and BigQuery databases, train machine learning models with Axon, plot charts, and build map visualizations without writing boilerplate code. Real-time collaboration lets multiple users edit the same notebook simultaneously with cursor presence indicators and synchronized cell evaluation. Notebooks are stored as .livemd files, a Markdown-compatible format that renders cleanly on GitHub and integrates with standard version control workflows. Custom runtimes connect Livebook to existing Elixir applications for live introspection and documentation of running systems. The Docker image at ghcr.io/livebook-dev/livebook exposes ports 8080 and 8081 with password or token authentication. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. Apache 2.0 licensed.