Notebooks in Neptune¶
Notebooks are essential tool for data scientists, regardless their area of specialization. They allow data scientists to work interactively, keeping code and results - like visualizations - in a single document. Neptune builds on top of this experience and comes with Jupyter and JupyterLab extensions that let you track Notebooks in Neptune.
Notebooks in Neptune - key features:
In Neptune, each notebook consist of collection of checkpoints that you upload directly from the Jupyter User interface.
In the project, unlimited number of notebooks and checkpoints is allowed.
Browse checkpoints history across all notebooks in the project,
Share notebook as a link,
Compare two notebooks side-by-side like source code.
To start working with notebooks in Neptune, install and configure open source extension for Jupyter or JupyterLab. When you have it done, you can start working with notebooks immediately.
To try it now, without registering to Neptune, look at example notebooks in public project onboarding. Use public user’s API token (username: neptuner) to upload some snapshots to this project (you still need to install and configure Jupyter extension).
Notebooks view is a collection of all notebooks in the project - each can have multiple checkpoints.
See what your team members are working on now.
Review details and checkpoints associated with Notebook.
Share, compare or download notebook.
Once you entered notebook, you can see all its content, that is: code and markdown cells, outputs and execution count.
Look at the snapshot of the work with notebook.
Download, share or compare this checkpoint.
Select two notebooks and compare their contents - code and markdown cells, outputs and execution count - side-by-side just like source code. Compare view let you look at diff between checkpoints of the same notebook, or two entirely different notebooks (Try yourself here).
Code, markdown, output and execution count differences highlighted.
Top bar displays summary information about diff.