Use Dash to Build to Web Apps on Gong Data

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

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

Connecting to Gong Data

Connecting to Gong 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.

To authenticate to Gong, you can use API Key authentication with your Gong API Key and API Secret.

Authentication

To authenticate to Gong, you must provide your Gong API Key and API Secret, along with your tenant Domain. These credentials are combined and Base64-encoded to form the Basic authentication header used for all API requests.

Using API Key Authentication

To authenticate using an API Key, you need to obtain your API Key and API Secret from your Gong account settings.

You can then connect by setting the AuthScheme to APIKey and providing your credentials:

• AuthScheme: Set this to APIKey.
• APIKey: Set this to your Gong API Key.
• APISecret: Set this to your Gong API Secret.
• Domain: Set this to your Gong tenant domain (e.g., us-36533.api.gong.io).

Example connection string

Profile=C:\profiles\Gong.apip;AuthScheme=APIKey;ProfileSettings='APIKey=your_api_key;APISecret=your_api_secret;Domain=your-tenant.api.gong.io';

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

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

cnxn = mod.connect("Profile=C:\profiles\Gong.apip;AuthScheme=APIKey;ProfileSettings='APIKey=your_api_key;APISecret=your_api_secret;Domain=your-tenant.api.gong.io';")

Execute SQL to Gong

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 ,  FROM AnsweredScorecards WHERE  = ''", 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-apiedataplot'

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 Gong data and configure the app layout.

trace = go.Bar(x=df., y=df., 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='Gong AnsweredScorecards 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 Gong data.

python api-dash.py

Free Trial & More Information

Download a free, 30-day trial of the CData API Driver for Python to start building Python apps with connectivity to Gong 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.api as mod
import plotly.graph_objs as go

cnxn = mod.connect("Profile=C:\profiles\Gong.apip;AuthScheme=APIKey;ProfileSettings='APIKey=your_api_key;APISecret=your_api_secret;Domain=your-tenant.api.gong.io';")

df = pd.read_sql("SELECT ,  FROM AnsweredScorecards WHERE  = ''", cnxn)
app_name = 'dash-apidataplot'

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., y=df., 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='Gong AnsweredScorecards Data', barmode='stack')
		})
], className="container")

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