Install dependencies

After you create a user-managed notebooks instance, you might need to install software that your notebook depends on. You can install dependencies using a terminal window, or by adding install commands in a file in your notebook.

An advantage to adding install commands in a file is that, when you share a notebook, the commands to install the dependencies have been saved with the notebook and are available to users that you share the notebook with.

Install dependencies from a notebook

Python packages

To install Python packages from a notebook:

  1. Go to the User-managed notebooks page in the Google Cloud Console.

    Go to the User-managed notebooks page

  2. Select Open JupyterLab for the Python instance where you want to install dependencies.

  3. Select File -> New -> Notebook. This creates a new notebook named "Untitled.ipynb." Select the kernel for your new notebook. For example, "Python 3." You can also create a Python notebook using the Launcher.

    Add a notebook file

  4. Select File -> Rename notebook and change the name of the untitled notebook to something meaningful, such as "install.ipynb."

  5. When you open your new notebook, there is a default code cell where you can enter code, in this case Python 3, to install dependencies. For example, to install the mxnet deep learning library in a Python 3 notebook, enter the following in the code cell: %pip install mxnet. To install the library in a Python 2 notebook, enter the following: !pip2 install mxnet.

    Add code to a notebook cell

  6. Press the run button to run the install command.

    Press run button

  7. When installation is complete, select Kernel -> Restart Kernel to restart the kernel and ensure the library is available for import.

  8. Select File -> Save Notebook to save the notebook.

R packages

To install R packages from a notebook:

  1. Go to the User-managed notebooks page in the Google Cloud Console.

    Go to the User-managed notebooks page

  2. Select Open JupyterLab for the R instance where you want to install dependencies.

  3. Select File -> New -> Notebook. This creates a new notebook named "Untitled.ipynb." Select the "R" kernel for your new notebook. You can also create an R notebook using the Launcher.

    Add a notebook file

  4. Select File -> Rename notebook and change the name of the untitled notebook to something meaningful, such as "install.ipynb."

  5. When you open your new notebook, there is a default code cell where you can enter code, in this case R, to install dependencies. For example, to install the deepnet deep learning neural network package in an R notebook, enter the following in the code cell: install.packages("deepnet").

    Add code to a notebook cell

  6. Press the run button to run the install command.

    Press run button

  7. Select File -> Save Notebook to save the notebook.

Install dependencies from a terminal

Python packages

To install Python packages from a terminal:

  1. Go to the User-managed notebooks page in the Google Cloud Console.

    Go to the User-managed notebooks page

  2. Select Open JupyterLab for the Python instance where you want to install dependencies.

  3. Select File -> New -> Terminal to open a terminal window. You can also open a terminal window using the Launcher.

    Open a terminal window

  4. In the terminal window, enter the command to install the software dependency for your user-managed notebooks instance. For example, to install the mxnet deep learning library for Python 3 notebooks, enter the following command: pip3 install mxnet. For Python 2 notebooks, enter: pip2 install mxnet.

  5. In any open Python notebooks, you may need to select Kernel -> Restart Kernel to restart the kernel and ensure the library is available for import.

R packages

To install R packages from a terminal:

  1. Go to the User-managed notebooks page in the Google Cloud Console.

    Go to the User-managed notebooks page

  2. Select Open JupyterLab for the R instance where you want to install dependencies.

  3. Select File -> New -> Terminal to open a terminal window. You can also open a terminal window using the Launcher.

    Open a terminal window

  4. In the terminal window, enter R to go to the R prompt.

  5. At the R prompt, enter the command to install the software dependency for your user-managed notebooks instance. For example, to install the deepnet deep learning neural network package, enter the following command: install.packages("deepnet").