how to collab for free in gitbook code example

Example 1: documentation for https://www.googleapis.com/oauth2/v4/token

>>> # Credentials you get from registering a new application
>>> client_id = '<the id you get from google>.apps.googleusercontent.com'
>>> client_secret = '<the secret you get from google>'
>>> redirect_uri = 'https://your.registered/callback'

>>> # OAuth endpoints given in the Google API documentation
>>> authorization_base_url = "https://accounts.google.com/o/oauth2/v2/auth"
>>> token_url = "https://www.googleapis.com/oauth2/v4/token"
>>> scope = [
...     "https://www.googleapis.com/auth/userinfo.email",
...     "https://www.googleapis.com/auth/userinfo.profile"
... ]

>>> from requests_oauthlib import OAuth2Session
>>> google = OAuth2Session(client_id, scope=scope, redirect_uri=redirect_uri)

>>> # Redirect user to Google for authorization
>>> authorization_url, state = google.authorization_url(authorization_base_url,
...     # offline for refresh token
...     # force to always make user click authorize
...     access_type="offline", prompt="select_account")
>>> print 'Please go here and authorize,', authorization_url

>>> # Get the authorization verifier code from the callback url
>>> redirect_response = raw_input('Paste the full redirect URL here:')

>>> # Fetch the access token
>>> google.fetch_token(token_url, client_secret=client_secret,
...         authorization_response=redirect_response)

>>> # Fetch a protected resource, i.e. user profile
>>> r = google.get('https://www.googleapis.com/oauth2/v1/userinfo')
>>> print r.content

Example 2: python download sklearm model.joblib from google stroage

from google.cloud import storage
from sklearn.externals import joblib
from io import BytesIO

storage_client = storage.Client()
bucket_name=<bucket name>
model_bucket='model.joblib'

bucket = storage_client.get_bucket(bucket_name)
#select bucket file
blob = bucket.blob(model_bucket)
#download blob into an in-memory file object
model_file = BytesIO()
blob.download_to_file(model_file)
#load into joblib
model=joblib.load(model_local)