Ready to get started?

Learn more about the CData Python Connector for Freshdesk or download a free trial:

Download Now

Use Dash to Build to Web Apps on Freshdesk Data

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

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

Connecting to Freshdesk Data

Connecting to Freshdesk 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.

FreshDesk makes use of basic authentication. To connect to data, set the following connection properties:

  • Domain: Set this to the domain associated with your FreshDesk account. For example, in your URL: https://my_domain.freshdesk.com.
  • APIKey: Set this to the API key associated with your FreshDesk account. To retrieve your API key, Log into your support Portal -> Click on profile picture in the top right corner -> profile settings page. The API key will be available below the change password section to the right.

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

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

cnxn = mod.connect("Domain=MyDomain;APIKey=myAPIKey;")

Execute SQL to Freshdesk

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 Tickets WHERE Status = '2'", 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-freshdeskedataplot'

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 Freshdesk 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='Freshdesk Tickets 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 Freshdesk data.

python freshdesk-dash.py

Free Trial & More Information

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

cnxn = mod.connect("Domain=MyDomain;APIKey=myAPIKey;")

df = pd.read_sql("SELECT Id, Name FROM Tickets WHERE Status = '2'", cnxn)
app_name = 'dash-freshdeskdataplot'

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='Freshdesk Tickets Data', barmode='stack')
		})
], className="container")

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