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Use Dash to Build to Web Apps on Bing Search Results

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

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

Connecting to Bing Search Results

Connecting to Bing 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 connect to Bing, set the ApiKey connection property. To obtain the API key, sign into Microsoft Cognitive Services and register for the Bing Search APIs.

Two API keys are then generated; select either one.

When querying tables, the SearchTerms parameter must be supplied in the WHERE clause.

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

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

cnxn = mod.connect("APIKey=MyAPIKey;")

Execute SQL to Bing 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-bingedataplot'

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 Bing 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='Bing 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 Bing Search results.

python bing-dash.py

Free Trial & More Information

Download a free, 30-day trial of the Bing Search Python Connector to start building Python apps with connectivity to Bing Search results. 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.bing as mod
import plotly.graph_objs as go

cnxn = mod.connect("APIKey=MyAPIKey;")

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

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

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