Creating Your Own Extensions for JupyterLab
07-11, 16:05–16:50 (Europe/Prague), Terrace 2A

Have you ever wished for a feature in Jupyter Notebooks or JupyterLab that wasn't already there? Or perhaps you've found yourself doing complex or repetitive tasks and realized that you, and others, could benefit from integrating those tasks into JupyterLab? This is your chance to learn how to add that feature, or integrate that task, yourself.

JupyterLab enables you to work with Jupyter notebooks, text editors, terminals, and custom components in a flexible, integrated, and extensible manner.

This talk presents a practical tutorial about how to extend JupyterLab. We focus on understanding the underlying extension support infrastructure, as we walk through a step-by-step example of creating an app in JupyterLab. We will learn, among other things, how to launch that app from different places within JupyterLab, how to style our app, and how to pass parameters to our app to modify its behavior.

Prerequisites:
- Attendees should have some familiarity with Jupyter Notebooks and/or JupyterLab.
- Attendees must have solid experience with any typical object-oriented programming language (i.e. a good understanding of classes, objects, and inheritance).


Expected audience expertise

Intermediate

Daniel is an engineer at Bloomberg with experience developing Trading Systems, Risk Analytics, and applications for Financial Analysis of Equities and Fixed Income securities. He holds a Ph.D. in Molecular Biophysics from the University of Virginia, and was a CFA charter holder and member of the Chartered Financial Analyst Institute for more than 10 years. He is the Open Source maintainer of Matplotlib's MPLFINANCE package, and the author of McGraw-Hill's "Biophysics Demystified."