Use Dash to Build to Web Apps on Google Search Results

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

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

Connecting to Google Search Results

Connecting to Google Search results 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.

To search with a Google custom search engine, you need to set the CustomSearchId and ApiKey connection properties.

To obtain the CustomSearchId property, sign into Google Custom Search Engine and create a new search engine.

To obtain the ApiKey property, you must enable the Custom Search API in the Google API Console.

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

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

cnxn = mod.connect("CustomSearchId=def456;ApiKey=abc123;")

Execute SQL to Google Search

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 Title, ViewCount FROM VideoSearch WHERE SearchTerms = 'WayneTech'", 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-googlesearchedataplot'

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 Search results and configure the app layout.

trace = go.Bar(x=df.Title, y=df.ViewCount, name='Title')

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 Search VideoSearch 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 Search results.

python googlesearch-dash.py

👁 Google Search results 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 Search to start building Python apps with connectivity to Google Search results. 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.googlesearch as mod
import plotly.graph_objs as go

cnxn = mod.connect("CustomSearchId=def456;ApiKey=abc123;")

df = pd.read_sql("SELECT Title, ViewCount FROM VideoSearch WHERE SearchTerms = 'WayneTech'", cnxn)
app_name = 'dash-googlesearchdataplot'

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.Title, y=df.ViewCount, name='Title')

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 Search VideoSearch Data', barmode='stack')
		})
], className="container")

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