Create files in Google Colaboratory local environment from files stored in Google Drive

colab_drive_files_create.py

"""## Pull data files from Google Drive

Install PyDrive which will be used to access Google Drive and kick off the process to authorize the notebook running in the Google Colaboratory environment to touch our Drive files. When this cell executes it'll provide a link to authenticate into a Google Drive account to instatiate a PyDrive client. The Drive account that is selected should be one which has access to our all variables dataset file that we'll use for training/testing our model.
"""

#!pip install -U -q PyDrive
 
from pydrive.auth import GoogleAuth
from pydrive.drive import GoogleDrive
from google.colab import auth
from oauth2client.client import GoogleCredentials
 
# Authenticate and create the PyDrive client.
auth.authenticate_user()
gauth = GoogleAuth()
gauth.credentials = GoogleCredentials.get_application_default()
drive = GoogleDrive(gauth)

"""Next we'll create dataset files within the Google Colaboratory environment corresponding to the flow and time tendency dataset files located on our Google Drive."""

filename_h0 = 'fv091x180L26_dry_HS.cam.h0.2000-12-27-00000.nc'
filename_h1 = 'fv091x180L26_dry_HS.cam.h1.2000-12-27-00000.nc'
id_h0 = '1vptBPguIMU4FrvkC91xAd7_wOxoylBW0'
id_h1 = '1ru8gmDKv8qPZGnfaTP2Sqv8Fsps48vAX'
file_h0 = drive.CreateFile({'id': id_h0})  # creates a file in the Colab env using the ID for file <filename_h0>
file_h1 = drive.CreateFile({'id': id_h1})  # creates a file in the Colab env using the ID for file <filename_h1>
file_h0.GetContentFile(filename_h0)  # gets the file's contents and saves it as a local file named <filename_h0>
file_h1.GetContentFile(filename_h1)  # gets the file's contents and saves it as a local file named <filename_h1>