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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 Management, the pandas module, and the Dash framework, you can build Jira Service Management-connected web applications for Jira Service Management data. This article shows how to connect to Jira Service Management with the CData Connector and use pandas and Dash to build a simple web app for visualizing Jira Service Management data.
With built-in, optimized data processing, the CData Python Connector offers unmatched performance for interacting with live Jira Service Management data in Python. When you issue complex SQL queries from Jira Service Management, the driver pushes supported SQL operations, like filters and aggregations, directly to Jira Service Management and utilizes the embedded SQL engine to process unsupported operations client-side (often SQL functions and JOIN operations).
Connecting to Jira Service Management 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.
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:
To authenticate with a service account, supply the following connection properties:
Note: Password has been deprecated for connecting to a Cloud Account and is now used only to connect to a Server Instance.
By default, the connector only surfaces system fields. To access the custom fields for Issues, set IncludeCustomFields.
After installing the CData Jira Service Management Connector, follow the procedure below to install the other required modules and start accessing Jira Service Management through Python objects.
Use the pip utility to install the required modules and frameworks:
pip install pandas pip install dash pip install dash-daq
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 Management Connector to create a connection for working with Jira Service Management data.
cnxn = mod.connect("ApiKey=myApiKey;User=MyUser;InitiateOAuth=GETANDREFRESH;")
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)
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'
The next step is to create a bar graph based on our Jira Service Management 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 Management Requests Data', barmode='stack')
})
], className="container")
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 Management data.
python jiraservicedesk-dash.py👁 Jira Service Management data in a Dash web app (Salesforce is shown).
Download a free, 30-day trial of the CData Python Connector for Jira Service Management to start building Python apps with connectivity to Jira Service Management data. Reach out to our Support Team if you have any questions.
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;")
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 Management Requests Data', barmode='stack')
})
], className="container")
if __name__ == '__main__':
app.run_server(debug=True)
Download a Community License of the Jira Service Management Connector to get started:
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👁 Jira Service Management IconPython Connector Libraries for Jira Service Management Data Connectivity. Integrate Jira Service Management with popular Python tools like Pandas, SQLAlchemy, Dash & petl.