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Use Dash to Build to Web Apps on Google Drive Data

The CData Python Connector for Google Drive enables you to create Python applications that use pandas and Dash to build Google Drive-connected web apps.

The rich ecosystem of Python modules lets you get to work quickly and integrate your systems more effectively. With the CData Python Connector for Google Drive, the pandas module, and the Dash framework, you can build Google Drive-connected web applications for Google Drive data. This article shows how to connect to Google Drive with the CData Connector and use pandas and Dash to build a simple web app for visualizing Google Drive data.

With built-in, optimized data processing, the CData Python Connector offers unmatched performance for interacting with live Google Drive data in Python. When you issue complex SQL queries from Google Drive, the driver pushes supported SQL operations, like filters and aggregations, directly to Google Drive and utilizes the embedded SQL engine to process unsupported operations client-side (often SQL functions and JOIN operations).

Connecting to Google Drive Data

Connecting to Google Drive data looks just like connecting to any relational data source. Create a connection string using the required connection properties. For this article, you will pass the connection string as a parameter to the create_engine function.

You can connect to Google APIs on behalf of individual users or on behalf of a domain. Google uses the OAuth authentication standard. See the "Getting Started" section of the help documentation for a guide.

After installing the CData Google Drive Connector, follow the procedure below to install the other required modules and start accessing Google Drive through Python objects.

Install Required Modules

Use the pip utility to install the required modules and frameworks:

pip install pandas
pip install dash
pip install dash-daq

Visualize Google Drive Data in Python

Once the required modules and frameworks are installed, we are ready to build our web app. Code snippets follow, but the full source code is available at the end of the article.

First, be sure to import the modules (including the CData Connector) with the following:

import os
import dash
import dash_core_components as dcc
import dash_html_components as html
import pandas as pd
import cdata.googledrive as mod
import plotly.graph_objs as go

You can now connect with a connection string. Use the connect function for the CData Google Drive Connector to create a connection for working with Google Drive data.

cnxn = mod.connect("InitiateOAuth=GETANDREFRESH;OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")")

Execute SQL to Google Drive

Use the read_sql function from pandas to execute any SQL statement and store the result set in a DataFrame.

df = pd.read_sql("SELECT Name, Size FROM Files WHERE Starred = 'true'", cnxn)

Configure the Web App

With the query results stored in a DataFrame, we can begin configuring the web app, assigning a name, stylesheet, and title.

app_name = 'dash-googledriveedataplot'

external_stylesheets = ['https://codepen.io/chriddyp/pen/bWLwgP.css']

app = dash.Dash(__name__, external_stylesheets=external_stylesheets)
app.title = 'CData + Dash'

Configure the Layout

The next step is to create a bar graph based on our Google Drive data and configure the app layout.

trace = go.Bar(x=df.Name, y=df.Size, name='Name')

app.layout = html.Div(children=[html.H1("CData Extension + Dash", style={'textAlign': 'center'}),
	dcc.Graph(
		id='example-graph',
		figure={
			'data': [trace],
			'layout':
			go.Layout(title='Google Drive Files Data', barmode='stack')
		})
], className="container")

Set the App to Run

With the connection, app, and layout configured, we are ready to run the app. The last lines of Python code follow.

if __name__ == '__main__':
    app.run_server(debug=True)

Now, use Python to run the web app and a browser to view the Google Drive data.

python googledrive-dash.py

Free Trial & More Information

Download a free, 30-day trial of the Google Drive Python Connector to start building Python apps with connectivity to Google Drive data. Reach out to our Support Team if you have any questions.



Full Source Code

import os
import dash
import dash_core_components as dcc
import dash_html_components as html
import pandas as pd
import cdata.googledrive as mod
import plotly.graph_objs as go

cnxn = mod.connect("InitiateOAuth=GETANDREFRESH;OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")

df = pd.read_sql("SELECT Name, Size FROM Files WHERE Starred = 'true'", cnxn)
app_name = 'dash-googledrivedataplot'

external_stylesheets = ['https://codepen.io/chriddyp/pen/bWLwgP.css']

app = dash.Dash(__name__, external_stylesheets=external_stylesheets)
app.title = 'CData + Dash'
trace = go.Bar(x=df.Name, y=df.Size, name='Name')

app.layout = html.Div(children=[html.H1("CData Extension + Dash", style={'textAlign': 'center'}),
	dcc.Graph(
		id='example-graph',
		figure={
			'data': [trace],
			'layout':
			go.Layout(title='Google Drive Files Data', barmode='stack')
		})
], className="container")

if __name__ == '__main__':
    app.run_server(debug=True)