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Outline

1:30pm to 5:30pm Rooom 201

These notes are for the presenters.

For the last several years the Jupyter team has been working on a new Jupyter frontend: JupyterLab. While JupyterLab does of course allow the use of Jupyter Notebooks, it goes beyond the classic Jupyter Notebook by providing a flexible and extensible web application with a set of reusable components. Users can arrange multiple notebooks, text editors, terminals, output areas, and custom components using tabs and collapsible sidebars. These components are carefully designed to enable the user to use them together or separately (for example, a user can send code from a file to a console with a keystroke, or can pop out an output from a notebook to work with it alone).

JupyterLab is based on a flexible application plugin system provided by PhosphorJS that makes it easy to customize existing components or extend it with new components. For example, users can install or write third-party plugins to view custom file formats, such as GeoJSON, interact with external services, such as Dask or Apache Spark, or display their data in effective and useful ways, such as interactive maps, tables, or plots.

In this tutorial we’ll walk users thought the best way to make use of JupyterLab, how to transition from the “classic” Jupyter Notebook frontend to JupyterLab, and how to make the best use of the new powerful features of JupyterLab.

If you have any question and concern or need help, fell free to speak up. A helper will come see you, or the speaker will take time to get questions.

This can serve as a quick read through summary of what we talked about (with links) and a rough timeline if you want to follow up on the video later.

Overview of JupyterLab

Introduction (Stephanie, 1:30pm, 20 min)

Today this tutorial will be presented to you by Stephanie Stattel, Jason Grout, and Matthias Bussonnier.

  • Poll Audience (yes/no) Have people used Classic Notebook? Have people used JupyterLab? Coding Languages (python/R/etc.)

By now you should have installed JupyterLab following the instructions in the readme. For this tutorial, we are standardizing on a conda-based python distribution (miniconda or Anaconda). We may not be able to help with installation issues if you are using a different python distribution.

JupyterLab is still evolving, and we are still refining the usability and user experience. When trying to do any task in an exercise, please let us know if something was not intuitive, or what surprised you.

  • Introduction to JupyterLab (slide) Go over context/design of JupyterLab (pull from JupyterCon 'Terraforming' introduction content)

  • FAQ:

    • Why JupyterLab?
    • Can you get Lab and notebook at the same time: YES
    • No difference in file format; Notebooks files are the same

(possible slide material in https://github.com/jupyterlab/jupyterlab-demo)

Tour of User Interface (Stephanie, 1:50, 30 min)

look at changelog in master to highlight new features in interface

Installation and Exercise 1 (Matthias, 2:30, 30 min)

Look into the Exercise 1 folder, and follow the instruction in Exercise-1.md

  1. Arranging tabs through dragging
  2. How to author markdown and equations
  3. Collapsible cells
  4. drag cells, inside notebook and between views of files. (perhaps also dragging between notebooks and consoles and files)
  5. Enable scrolling on outputs
  6. creating new view of outputs
  7. javascript rendering restrictions

BREAK + QA 3:00 (15 min)

Write one good thing on the green sticky note, one bad on the red one.

(+5 minutes to finish Exercise 1)

Workflows around executing code

Attaching kernels to multiple documents (Matthias, 3:15, 15 min)

  1. Executing code in a markdown file using an attached console.
  2. Developing libraries with notebook and Python files attached to same kernel
  3. Reloading modules?
  4. Create terminal, work with terminal next to code file and console. Maybe using ipython in terminal.
  5. Attaching a code console to the same kernel as a notebook.
  6. Stepping through code from a notebook cell (look at Bo Peng's PRs to 1.0)

Exercise 2 (Matthias, 3:30, 15 min)

  • binding multiple documents to the same kernel
    • New Console for Notebook
    • Markdown file + console workflow
    • Python code file + console workflow (notice the completions in the python code file!)
    • Open a notebook in classic notebook, modify, save and reopen in Lab.

Customizing JupyterLab

Settings (Stephanie, 3:45, 10 min)

  1. Changing editor settings
  2. Changing theme
  3. Json config system overview
  4. Changing keyboard shortcuts

Exercise 3 (Stephanie, 3:55, 10 min)

  1. change a keyboard shortcut
  2. Assign existing shortcut to new action.
  3. Assign new Keyboard shortcut to an existing action.
  4. Disable an existing keyboard shortcut
  5. add a keyboard shortcut (restart and run all)
    1. execute code from a notebook cell in console: see https://jupyterlab.readthedocs.io/en/latest/getting_started/changelog.html#command-palette-items [cntrl-shift-enter, or cntrl-G]
  6. change an editor setting

Break (4:05, 15 min)

Extensions (Jason, 4:20, 50 min)

  1. Everything is an extension - show the package.json
  2. Installing/listing/enabling/disabling plugins. jupyter lab build
  3. --core-mode
  4. Exercise 5 - writing your own extension

General QA period (Everyone, 5:10, 20 min)

Things we can do if we have time:

Widgets workflows

JupyterLab in JupyterHub

Sprint Saturday and Sunday

Poster session