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installationpipgoogle-colaboratory

How do I install a library permanently in Colab?


In Google Colaboratory, I can install a new library using !pip install package-name. But when I open the notebook again tomorrow, I need to re-install it every time.

Is there a way to install a library permanently? No need to spend time installing every time to use?


Solution

  • If you want a no-authorization solution. You can use mounting with gcsfuse + service-account key embedded in your notebook. Like this:

    # first install gcsfuse
    %%capture
    !echo "deb http://packages.cloud.google.com/apt gcsfuse-bionic main" > /etc/apt/sources.list.d/gcsfuse.list
    !curl https://packages.cloud.google.com/apt/doc/apt-key.gpg | apt-key add -
    !apt update
    !apt install gcsfuse
    

    Then get your service account credential from google cloud console and embed it in the notebook

    %%writefile /key.json
    {
      "type": "service_account",
      "project_id": "kora-id",
      "private_key_id": "xxxxxxx",
      "private_key": "-----BEGIN PRIVATE KEY-----\nxxxxxxx==\n-----END PRIVATE KEY-----\n",
      "client_email": "[email protected]",
      "client_id": "100380920993833371482",
      "auth_uri": "https://accounts.google.com/o/oauth2/auth",
      "token_uri": "https://oauth2.googleapis.com/token",
      "auth_provider_x509_cert_url": "https://www.googleapis.com/oauth2/v1/certs",
      "client_x509_cert_url": "https://www.googleapis.com/robot/v1/metadata/x509/colab-7%40kora-id.iam.gserviceaccount.com"
    }
    

    Then set environment to look for this credential file

    %env GOOGLE_APPLICATION_CREDENTIALS=/key.json
    

    You must then create (or have it already) a gcs bucket. And mount it to a made-up directory.

    !mkdir /content/my-bucket
    !gcsfuse my-bucket /content/my-bucket
    

    Then finally, install the library there. Like my above answer.

    import sys
    nb_path = '/content/my-bucket'
    sys.path.insert(0, nb_path)
    # Do this just once
    !pip install --target=$nb_path jdc
    

    You can now import jdc without !pip install it next time.