How do I install a library permanently in Colab?

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.

Yes. You can install the library in Google Drive. Then add the path to sys.path.

import os, sys
from google.colab import drive
drive.mount('/content/drive')
nb_path = '/content/notebooks'
os.symlink('/content/drive/My Drive/Colab Notebooks', nb_path)
sys.path.insert(0,nb_path)

Then you can install a library, for example, jdc, and specify the target.

!pip install --target=$nb_path jdc

Later, when you run the notebook again, you can skip the !pip install line. You can just import jdc and use it. Here's an example notebook.

https://colab.research.google.com/drive/1KpMDi9CjImudrzXsyTDAuRjtbahzIVjq

BTW, I really like jdc's %%add_to. It makes working with a big class much easier.