DataScience Workbook / 04. Development Environment / 1. Integrated & Interactive Development Environment (IDE) / 1.2 Jupyter: Interactive Web-Based Multi-Kernel DE / 1.2.3 Sharing Jupyter-based reproducible pipline via MyBinder
Sharing Jupyter Notebooks via MyBinder
Last Update: 9 Dec 2020
Learn how to publish Jupyter Notebooks on MyBinder. Launch an example of a shared Jupyter Notebook in binder here:
Analysis pipelines written in Python can be shared in an interactive document called a Jupyter Notebook. Notebook sections are usually one of two types:
- Markdown - text/documentation of your analysis
- Code - Python code chunks that run the analysis
Providing one document (notebook) of executable code and documentation eases reproducible research, where other scientists can verify, understand, and possibly extend your analysis.
To demonstrate these benefits, this tutorial will walk you through:
- creating a minimal Jupyter Notebook
- pushing it to a public github
- and linking the notebook to a mybinder.org to be shared
We will assume you have a GitHub account and are using
conda to manage python environments.
Step 1: GitHub
We will assume you have a GitHub account. If not, please register a free account.
- Sign in to Github - https://github.com/
- Create a
- Clone the repo, to create a copy on your local compuer.
Code and the clipboard icon, to copy the git repo path. That way you can type
git clone and paste the git repo path.
git clone https://github.com/YOUR_USER_NAME/jupyter_binder.git cd jupyter_binder
We will be adding a basic notebook to this folder, and pushing (publishing) it to GitHub.
Step 2: Create a minimal Jupyter Notebook
Creating and hosting a local Jupyter Notebook requires the
Use your favorite Text Editor and copy the following file, saving it as a environment.yml file. Notice how we’ve named the environment
name: ntbk_env channels: - conda-forge - bioconda - defaults dependencies: - python=3.8 #<= python version - jupyter #<= list any python packages here
Create the python environment. From terminal, we can use
conda env createto create a python environment. The
-fflag means we are reading in dependencies from a file
environment.yml. Creating an environment may take several minutes.
conda env create -f environment.yml
Activate the environment.
conda env list # List all created environments #> conda environments: #> ntbk_env /Users/User_Name/miniconda/envs/ntbk_env conda activate ntbk_env # Start the ntbk_env conda deactivate # Stop the ntbk_env
Start the local Jupyter Notebook
cd jupyter_binder/ # Navigate to git repo mkdir tutorials # Create a folder conda activate ntbk_env # Start ntbk_env jupyter notebook # Starts notebook, should open a browser window
Create a Jupyter Notebook via
We will try to recreate the Jupyter Notebook shown in the figure.
For the moment, create one Markdown section and paste the following. It doesn’t matter what it says right now since we are testing the system out.
## Hello Jupyter Notebook This is a quick introduction to Jupyter Notebooks. * Markdown * Code
Runbutton to render the markdown.
Now let’s create a Code section and paste the following.
Runbutton and the words “Hello World” should show up under the Code section. Now save this Notebook (ipynb file) by going to
File/Save As. Put the notebook in a
At this point, your
jupyter_binderfolder should look similar to:
jupyter_binder/ |_ tutorials/ | |_ Intro_to_Jupyter_Notebooks.ipynb |_ environment.yml |_ README.md
Save and commit to GitHub
git add tutorials/Intro_to_Jupyter_Notebooks.ipynb git add environment.yml git commit -m "minimal notebook" tutorials/Intro_to_Jupyter_Notebooks.ipynb environment.yml git push origin main
Check GitHub to make sure the new files are online.
Link to binder
- Visit https://mybinder.org/
- Input the github name and any subfolder if ipynb files are in a subfolder. Note: Instead of
test_binder, your repo will be called
Launch and you should see your jupyter notebook in the browser. Congratulations, your binder is published!
Add the “Launch Binder” badge
The last thing is to add a badge that launches the binder. Notice in the above image, before you hit launch, there’s a “Copy the text, then paste into your README…”, expand that section and copy the badge code…which will look similar to:
j23414 with your GitHub username, and
jupyter_binder. Then when you add it to the README.md, you should have a working binder launch badge.
Congratulations! You have completed the Jupyter Notebook + Binder Tutorial.
Your Turn to Explore
From here on you are free to explore modifying the jupyter notebook. We recommend looking at some tutorials in Markdown and Python.
Note: About Python Module Dependencies
environment.yml file we used earlier? MyBinder will look for an
environment.yml or a
requirements.txt to find a list of python modules to install and make available in the notebook. This file needs to be at the base of the github repo (can’t find it inside of subfolder
For example, if you want to use the Python package
numpy then the
environment.yml should look like:
name: ntbk_env channels: - conda-forge - bioconda - defaults dependencies: - python=3.8 - jupyter - numpy #<= new numpy package
numpy into the docker container, and you’ll be able to load the
numpy package in a Code section:
import numpy as np
Together, the Jupyter Notebook + MyBinder + environment.yml provides a way to sharing a reproducible Python analysis pipeline.