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        "description": "# Jovian\n\n[Jovian](www.jvn.io) is a platform that helps data scientists and ML engineers\n\n- track & reproduce data science projects\n- collaborate easily with friends/colleagues, and\n- automate repetitive tasks in their day-to-day workflow.\n\n## Uploading your work to Jovian\n\nIt's really easy to get started with Jovian!\n\n### Step 1: Install the `jovian` python library\n\nYou can do this from the terminal, or directly within a Jupyter notebook.\n\n```\n!pip install jovian -q\n```\n\n### Step 2: Import the library\n\n```\nimport jovian\n```\n\n### Step 3: Run jovian.commit\n\nAfter writing some code, running some experiments, training some models and plotting some charts, you can save and commit your Jupyter notebook.\n\n```\njovian.commit()\n```\n\nHere's what `jovian.commit` does:\n\n- It saves and uploads the Jupyter notebook to your [Jovian](https://jvn.io) account.\n- It captures and uploads the python virtual environment containing the list of libraries required to run your notebook.\n- It returns a link that you can use to view and share your notebook with friends or colleagues.\n\n**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](https://jvn.io).\n\n## Reproducing uploaded notebooks\n\nOnce 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.\n\n```\npip install jovian --upgrade\njovian clone 903a04b17036436b843d70443ef5d7ad\n```\n\nOnce cloned, you can enter the directly and setup the virtual environment using `jovian install`.\n\n```\ncd jovian-demo\njovian install\n```\n\nJovian uses [conda](https://conda.io) 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:\n\n```\nconda activate jovian-demo\njupyter notebook\n```\n\nIn this way, Jovian seamlessly ensures the end-to-end reproducibility of your Jupyter notebooks.\n\n## Updating existing notebooks\n\nUpdating 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.\n\n```\n# Updating the notebook\njovian.commit()\n```\n\nJovian 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.\n\nIf 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`.\n\n```\njovian.commit(notebook_id=\"903a04b17036436b843d70443ef5d7ad\")\n```\n\n## Getting new changes on cloned notebooks\n\nOnce a notebook has been updated, the new changes can be retrieved at any cloned location using the `jovian pull` command.\n\n```\ncd jovian-demo # Enter cloned directory\njovian pull    # Pull the latest changes\n```\n\n## Coming Soon\n\n- Callbacks for Tensorflow, Keras, PyTorch and FastAI to record hyperparameters and metrics automatically\n- Full support for Windows, Python 2.7+, non-Anaconda environments and `.py` script files\n- Real time monitoring and email/Slack notifications for long running training jobs\n- Check out and reproduce tracked experiments on any machine with a single command\n\nFor feedback, suggestions and feature requests, drop us a line at hello@jvn.io or create a ticket in the [issues tab](https://github.com/jvn-io/jovian-py/issues) .\n\n## Development and Testing\n\nTo run the tests, run the following command in the project root:  \n`python -m unittest discover` [`-v` for verbose]\n\n\n",
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