Awesome

Bokeh tutorial notebooks

This repository contains a series of Jupyter notebooks. These notebooks are available as an interactive tutorial at https://mybinder.org/v2/gh/bokeh/tutorial/main?filepath=notebooks%2F01_introduction.ipynb

To learn about Bokeh, please use the tutorial on mybinder.org.

You can also install and run the notebooks on a local machine. This is helpful if you can't access mybinder.org, or if you want to contribute to this tutorial.

Setup for SciPy US 2024

This tutorial will be presented at the SciPy 2024 conference, where you can use Nebari (JupterHub) hosted at scipy.quansight.dev to follow along.

Follow this participant's guide to register, sign-in, and download the tutorial materials.

In the tutorials/tutorial folder that's created with all material, navigate to the notebooks folder, and open 01_introduction.ipynb.

The environment for this tutorial is scipy-scipy-interactive-dataviz-bokeh, and it is automatically selected for you.

Previous presentations

SciPy US 2023

This tutorial was presented live during the SciPy 2023 conference. The state of the repository, as presented, can be accessed through the designated git tag, available here.

Additionally, the tutorial presentation is accessible on YouTube via the following link: https://youtu.be/G0Yc3ck4lC8?si=ZGqatTPnZBwjtdXO

Local setup

Follow these steps to run the tutorial notebooks on your local machine:

To run the tutorial locally, first clone this repository to your local machine. For example:
```
git clone git@github.com:bokeh/tutorial.git
```
After cloning the repository, enter the folder that contains the repository contents:
```
cd tutorial
```
Next, you need to set up your environment. This tutorial uses the conda package manager. Please make sure conda or Miniconda are installed and configured correctly on your system.

Run the following command inside your local repository folder to create your environment:
```
conda env create -f environment.yml
```
After the environment is set up, activate it with the following command:
```
conda activate bk-tutorial
```
Before opening the tutorial notebooks, you need to install the Bokeh sampledata. Make sure the bk-tutorial environment is activated, then run the following command:
```
bokeh sampledata
```
From inside the bk-tutorial environment, you can now start the Jupyter notebook server:
```
jupyter notebook
```
After opening Jupyter notebooks in a browser, go to the folder notebooks. Open the first notebook in this folder. It is called 01_introduction.ipynb.

Contributing to this tutorial

Thank you for helping to make this tutorial a better resource for everyone!

Everyone active in the Bokeh project’s codebases, issue trackers, and discussion forums is expected to follow the Code of Conduct. This includes working on these tutorials!

Preparing your environment

The bk-tutorial environment includes the necessary dependencies to contribute to this repository.

For consistency, we ask that you generally follow the Black code style wherever possible.

Making changes

Contributing to this tutorial repository works similarly to contributing to Bokeh itself:

Open an issue in the issue tracker of this repository
Make PR and link it to the issue you created

Once you have created a pull request, a member of the Bokeh core team will begin reviewing your pull request and may request changes or additions. If so, they will help you along the way with any questions you may have.