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Jovian Python SDK

Project description


Jovian is a platform that helps data scientists and ML engineers

  • track & reproduce data science projects
  • collaborate easily with friends/colleagues, and
  • automate repetitive tasks in their day-to-day workflow.

Uploading your work to Jovian

It's really easy to get started with Jovian!

Step 1: Install the jovian python library

You can do this from the terminal, or directly within a Jupyter notebook.

!pip install jovian -q

Step 2: Import the library

import jovian

Step 3: Run jovian.commit

After writing some code, running some experiments, training some models and plotting some charts, you can save and commit your Jupyter notebook.


Here's what jovian.commit does:

  • It saves and uploads the Jupyter notebook to your Jovian account.
  • It captures and uploads the python virtual environment containing the list of libraries required to run your notebook.
  • It returns a link that you can use to view and share your notebook with friends or colleagues.

NOTE: When you run jovian.commit for the first time, you'll be asked to provide an API, which you can find on your Jovian account.

Reproducing uploaded notebooks

Once a notebook is uploaded to Jovian, anyone (including you) can download the notebook and it's Python dependencies by running jovian clone <notebook_id> command on the Linux/Mac terminal or Windows Command Prompt. Try clicking the 'Clone' button at the top of this page to copy the command (including notebook ID) to clipboard.

pip install jovian --upgrade
jovian clone 903a04b17036436b843d70443ef5d7ad

Once cloned, you can enter the directly and setup the virtual environment using jovian install.

cd jovian-demo
jovian install

Jovian uses conda internally, so make sure you have it installed before running the above commands. Once the libraries are installed, you can activate the environment and start Jupyter in the usual way:

conda activate jovian-demo
jupyter notebook

In this way, Jovian seamlessly ensures the end-to-end reproducibility of your Jupyter notebooks.

Updating existing notebooks

Updating existing notebooks is really easy too! Just run jovian.commit once again, and Jovian will automatically identify and update the current notebook on your Jovian account.

# Updating the notebook

Jovian keeps track of existing notebooks using a .jovianrc file next to your notebook. If you don't want to update the current notebook, but create a new notebook instead, simply delete the .jovianrc file. Note that if you rename your notebook, Jovian will upload a new notebook when you commit, instead of updating the old one.

If you run into issues with updating a notebook, or want to replace a notebook in your account using a new/renamed notebook, you can provide the notebook_id argument to jovian.commit.


Getting new changes on cloned notebooks

Once a notebook has been updated, the new changes can be retrieved at any cloned location using the jovian pull command.

cd jovian-demo # Enter cloned directory
jovian pull    # Pull the latest changes

Coming Soon

  • Callbacks for Tensorflow, Keras, PyTorch and FastAI to record hyperparameters and metrics automatically
  • Full support for Windows, Python 2.7+, non-Anaconda environments and .py script files
  • Real time monitoring and email/Slack notifications for long running training jobs
  • Check out and reproduce tracked experiments on any machine with a single command

For feedback, suggestions and feature requests, drop us a line at or create a ticket in the issues tab .

Development and Testing

To run the tests, run the following command in the project root:
python -m unittest discover [-v for verbose]

Project details

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