Welcome to Polus Notebooks Hub’s documentation!

Polus Notebooks Hub is a tool for Data Science explorative data analysis, collaboration and dissemination combining IDEs (JupyterLab, RStudio, VSCode) environment modules and dashboarding tools such as Streamlit, Voila and Shiny.

Users can create servers associated with particular application type (notebook or one of the dashboards), .ipynb file and a set of environment modules which allows reproducible analysis. Shared environments (create by administrators) and collaborative editor in JupyterLab enable sharing the results with the team. User-created custom environmnets enable freedom to install any packages needed in new projects while still retaining all required metadata to reproduce the results.

Notebooks Hub UI

• Managing environments
  • Creating a new user environment
    • Conda environment
    • Debian package

JupyterLab

• The JupyterLab Interface
  • Menu Bar
  • Left and Right Sidebar
  • Main Work Area
  • Tabs and Simple Interface Mode
  • Context Menus
  • Keyboard Shortcuts
• File Management
  • Open file
  • New tab
  • Multiple Viewers
  • Single Doc Sync
  • File Navigation
  • Share file
  • Copy File Path
  • Important folders
  • File uploads
  • File downloads
  • Deleting folders
• Git integration
  • Git Clone
  • Git Commit
    • See changes in the notebook
    • Commit changes
    • Push commit
• Notebooks
• Managing Kernels and Terminals
• Polyglot features
  • Available language kernels
    • Python 3
    • R
    • Julia
    • Java
    • Octave
    • C++
    • Bash
    • Scala
    • Javascript
    • Typescript
  • Polyglot notebooks
    • Create polyglot notebook
    • Variable exchange
• Installing new packages
  • Tips for different languages/package managers
    • Python 3
    • R
    • From CRAN
    • Julia
    • Java
    • Octave
    • C++
• Interactive widgets and visulizations
  • Python
    • Jupyter Widgets
    • Bokeh
    • Holoviews
    • bqplot
    • Altair
    • pythreejs
    • Plotly
    • itkwidgets
  • R
    • htmlwidgets
    • highcharter
    • visnetwork
    • rbokeh
    • dygraphs: time series charting
    • d3heatmap
    • plotly
    • networkd3
    • Data Table
    • threejs
    • rglwidget
  • C++
    • xwidgets
• Interactive Dashboards from notebooks with Voilà
  • Render with Voilà in the new tab within Jupyter
  • Render with Voila in the new browser tab
• Text Editor
• Code Consoles
• Terminals
  • Copy/Paste
• Command Palette
• Documents and Kernels
• File and Output Formats
  • Markdown
  • Images
  • Delimiter-separated Values
  • JSON
  • HTML
  • LaTeX
  • PDF
  • Vega/Vega-Lite
  • Virtual DOM
• Debugger
  • Usage
  • Tutorial Notebook
• Table Of Contents
  • Settings
• Exporting Notebooks
  • Reveal.js Slides
• Real Time Collaboration
• JupyterLab URLs
  • File Navigation with /tree
  • Managing Workspaces (UI)
  • Cloning Workspaces
  • Resetting a Workspace
  • Combining URL Functions
  • Managing Workspaces (CLI)
  • Workspace File Format

Voila

• Voila

Streamlit

• Streamlit
  • Launch VS Code
    • Generate VS Code Instance on Notebooks Hub
    • Open VS Code
    • Install Streamlit
    • Port Forwarding
    • Stop Application Run
  • Creating a Streamlit App
    • Create app.py File
    • Generate App
• Useful App Elements
  • Magic and st.write
  • Text Display
  • Interactive Widgets
    • Selection Widgets
    • Slider
    • File Uploader
  • Data Visualization
    • Dataframes
    • Data Editor
  • Plots
  • Chat Elements
    • Built-In Chat
    • Third-Party Chat
• Launch App Using Notebooks Hub
• Streamlit Examples on Notebooks Hub
  • Example: Polus Flatfield Comparison
  • Example: Polus Datasheet
  • Example: Polus Ask Athena
  • Example: Neural Networks Using Streamlit
• Additional Streamlit Examples
  • Example: Demonstration of Gradient Descent
  • Adapting Other Open-Source Examples

Solara

• Solara
  • Launch VS Code
    • Generate VS Code Instance on Notebooks Hub
    • Open VS Code
  • Install Solara
    • Open a Terminal Window
    • Create a Virtual Environment (Recommended Method)
    • Using Custom Conda Environments
    • Using Built-In Conda Environments
    • Alternative Installation Methods
  • Creating a Solara App
    • Using Python Scripts
    • Using Jupyter Notebooks
    • Write App Code
  • Render App
    • Launch App From Python Script
    • Display App Inside Jupyter Notebook
    • Quit App
  • Additional Information
    • Port Forwarding
    • Solara App “Anatomy”
    • Reuse .py code inside .ipynb notebooks
    • Differences Between Solara and Streamlit
• Useful Solara Components (App Elements)
  • The Main Component
  • Hooks
  • Interactive Widgets
    • Button
    • Checkbox
    • Select
    • Slider
    • Toggle Switch
    • Toggle Buttons
    • Input Fields
  • File Handling
    • File Drop
    • File Browser
    • File Downloader
  • DataFrames
    • Basic Pandas DataFrame
    • DataFrames with Column Header Tools
    • Cross Filtering
  • Plots
    • Plotly and Plotly Express
    • Solara Express
    • Matplotlib
    • Altair
    • bqplot
    • Echarts
  • SQL Integration
• Using Solara for Data Science
  • Install Dependencies
  • Load Dataset
  • Add Reactive Variables
  • Define the Main Page Component
  • Enable Data Interaction
  • Execute Combined Code
• Solara Examples
  • From the Solara Community
    • Example: Wanderlust
    • Example: Solara Chatbot
    • Example: Bulk Labeling Tool
  • Examples on Notebooks Hub
    • Example: Solara Scatter
    • Example: Solara Trail
    • Example: Solara Tokenizer

R Shiny

• RShiny
• RStudio IDE
  • Launch RStudio Instance on Notebooks Hub
    • Method 1: Quick Launch
    • Method 2: Custom Server Instance
  • Open RStudio
  • Create a New Project
  • Create an R File
  • Helpful R Packages
    • Installing Packages from Comprehensive R Archive Network (CRAN)
    • Installing Packages from Other Repositories
  • Helpful R Cheatsheets
• Creating an RShiny App
  • Open RStudio
  • Create a New Shiny Project
  • Create New Shiny File(s) - alternative method
  • Install Shiny Package for R
  • Shiny Demos
  • Shiny App Components
  • Run App

Developer documentation

• User Image Stacks
  • Overview
  • Image Hierarchies
    • jupyter/docker-stacks Reference Hierarchy
    • Our Custom Hierarchy
  • Base Images
    • polusai/notebooks-hub-stacks-foundation
    • polusai/notebook
    • polusai/dashboard-base
  • Application-specific Images
  • Usage
    • Building a Dashboard Image
    • Running the Dashboard Container
    • Example
  • Customization
    • Prerequisites for New Applications
    • Steps to Integrate a New Application
    • Example: Integrating a Hypothetical Web App
    • Separation of dashboarding tools from the environment
    • Best Practices
• Application Flow
• Notebooks Hub Developing
  • Local Mongo Setup
  • Local API Setup
  • Local UI Setup
• Notebooks Hub Compose
  • Launch Mode - Runtime
    • Pre-Launch Steps
    • Launch Action
  • Launch Mode - Dev
    • Pre-Launch Steps
    • Launch Action
  • Post-Launch Steps
  • General FAQ
• Notebooks Hub API
  • ServerController
• Helm Charts
  • JupyterHub
• Polus-jupyterhub
  • Configuration
  • Notebooks Hub API
• Notebooks-hub-api
  • Configuration
  • Notebooks Hub UI
• Notebooks-hub-ui
  • Configuration
  • Minimal Test Deployment of JupyterHub
• Administrator Guide for configuring Notebooks Hub
  • Adding Launchers and Examples
    • Launchers
    • Examples
• Contributing
  • Commit messages
  • Versioning

Indices and tables

• Index

• Module Index

• Search Page