Use Dash to Build to Web Apps on Google Spanner Data

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 Spanner, the pandas module, and the Dash framework, you can build Google Spanner-connected web applications for Google Spanner data. This article shows how to connect to Google Spanner with the CData Connector and use pandas and Dash to build a simple web app for visualizing Google Spanner data.

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

Connecting to Google Spanner Data

Connecting to Google Spanner 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.

Google Spanner uses the OAuth authentication standard. To authenticate using OAuth, you can use the embedded credentials or register an app with Google.

See the Getting Started guide in the CData driver documentation for more information.

After installing the CData Google Spanner Connector, follow the procedure below to install the other required modules and start accessing Google Spanner 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 Spanner 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.googlespanner as mod
import plotly.graph_objs as go

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

cnxn = mod.connect("ProjectId='project1';InstanceId='instance1';Database='db1';InitiateOAuth=GETANDREFRESH;")

Execute SQL to Google Spanner

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, TotalDue FROM Customer WHERE Id = '1'", 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-googlespanneredataplot'

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 Spanner data and configure the app layout.

trace = go.Bar(x=df.Name, y=df.TotalDue, 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 Spanner Customer 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 Spanner data.

python googlespanner-dash.py

👁 Google Spanner data in a Dash web app (Salesforce is shown).

Free Trial & More Information

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

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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.googlespanner as mod
import plotly.graph_objs as go

cnxn = mod.connect("ProjectId='project1';InstanceId='instance1';Database='db1';InitiateOAuth=GETANDREFRESH;")

df = pd.read_sql("SELECT Name, TotalDue FROM Customer WHERE Id = '1'", cnxn)
app_name = 'dash-googlespannerdataplot'

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.TotalDue, 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 Spanner Customer Data', barmode='stack')
		})
], className="container")

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