Use Dash to Build to Web Apps on Talkdesk 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 Talkdesk, the pandas module, and the Dash framework, you can build Talkdesk-connected web applications for Talkdesk data. This article shows how to connect to Talkdesk with the CData Connector and use pandas and Dash to build a simple web app for visualizing Talkdesk data.

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

Connecting to Talkdesk Data

Connecting to Talkdesk 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.

Talkdesk uses the OAuth 2.0 Client Credentials grant. There is no browser-based authorization step and no callback URL.

Set the following connection properties:

• AccountName: The name of your Talkdesk account.
• Region: The region where your Talkdesk instance is deployed. Supported values are US (default), EU, CA, AU, UK, and FedRamp.
• OAuthClientId: The Client Id assigned when you registered your custom OAuth application.
• OAuthClientSecret: The Client Secret assigned to your custom OAuth application.

Creating a Custom OAuth Application

1. Log in to your Talkdesk account and select OAuth Clients from the navigation menu.
2. Click Create OAuth Client and give the client a descriptive name.
3. Set Grant Type to Client Credentials.
4. Click Add scopes and select the scopes for the data you want to access.
5. Click Create and copy the Client Id and Client Secret.

When you connect, the driver automatically requests an access token from Talkdesk, caches it, and refreshes it when it expires. Make sure the scopes selected for the application match the views you plan to query, or the token request can fail.

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

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

cnxn = mod.connect("AccountName=myAccount;Region=US;OAuthClientId=myClientId;OAuthClientSecret=myClientSecret;")

Execute SQL to Talkdesk

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 Id, Name FROM Users WHERE Active = '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-talkdeskedataplot'

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 Talkdesk data and configure the app layout.

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

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='Talkdesk Users 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 Talkdesk data.

python talkdesk-dash.py

Free Trial & More Information

Download a free, 30-day trial of the CData Python Connector for Talkdesk to start building Python apps with connectivity to Talkdesk 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.talkdesk as mod
import plotly.graph_objs as go

cnxn = mod.connect("AccountName=myAccount;Region=US;OAuthClientId=myClientId;OAuthClientSecret=myClientSecret;")

df = pd.read_sql("SELECT Id, Name FROM Users WHERE Active = 'true'", cnxn)
app_name = 'dash-talkdeskdataplot'

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.Id, y=df.Name, name='Id')

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='Talkdesk Users Data', barmode='stack')
		})
], className="container")

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