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

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

Connecting to Jira Service Desk Data

Connecting to Jira Service Desk 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.

You can establish a connection to any Jira Service Desk Cloud account or Server instance.

Connecting with a Cloud Account

To connect to a Cloud account, you'll first need to retrieve an APIToken. To generate one, log in to your Atlassian account and navigate to API tokens > Create API token. The generated token will be displayed.

Supply the following to connect to data:

• User: Set this to the username of the authenticating user.
• APIToken: Set this to the API token found previously.

Connecting with a Service Account

To authenticate with a service account, you will need to supply the following connection properties:

• User: Set this to the username of the authenticating user.
• Password: Set this to the password of the authenticating user.
• URL: Set this to the URL associated with your JIRA Service Desk endpoint. For example, https://yoursitename.atlassian.net.

Note: Password has been deprecated for connecting to a Cloud Account and is now used only to connect to a Server Instance.

Accessing Custom Fields

By default, the connector only surfaces system fields. To access the custom fields for Issues, set IncludeCustomFields.

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

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

cnxn = mod.connect("ApiKey=myApiKey;User=MyUser;InitiateOAuth=GETANDREFRESH;OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")")

Execute SQL to Jira Service Desk

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 RequestId, ReporterName FROM Requests WHERE CurrentStatus = 'Open'", 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-jiraservicedeskedataplot'

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 Jira Service Desk data and configure the app layout.

trace = go.Bar(x=df.RequestId, y=df.ReporterName, name='RequestId')

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='Jira Service Desk Requests 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 Jira Service Desk data.

python jiraservicedesk-dash.py

Free Trial & More Information

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

cnxn = mod.connect("ApiKey=myApiKey;User=MyUser;InitiateOAuth=GETANDREFRESH;OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")

df = pd.read_sql("SELECT RequestId, ReporterName FROM Requests WHERE CurrentStatus = 'Open'", cnxn)
app_name = 'dash-jiraservicedeskdataplot'

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.RequestId, y=df.ReporterName, name='RequestId')

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='Jira Service Desk Requests Data', barmode='stack')
		})
], className="container")

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