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Use Dash to Build to Web Apps on Confluence Data

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

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

Connecting to Confluence Data

Connecting to Confluence 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.

Obtaining an API Token

An API token is necessary for account authentication. To generate one, login to your Atlassian account and navigate to API tokens > Create API token. The generated token will be displayed.

Connect Using a Confluence Cloud Account

To connect to a Cloud account, provide the following (Note: Password has been deprecated for connecting to a Cloud Account and is now used only to connect to a Server Instance.):

  • User: The user which will be used to authenticate with the Confluence server.
  • APIToken: The API Token associated with the currently authenticated user.
  • Url: The URL associated with your JIRA endpoint. For example, https://yoursitename.atlassian.net.

Connect Using a Confluence Server Instance

To connect to a Server instance, provide the following:

  • User: The user which will be used to authenticate with the Confluence instance.
  • Password: The password which will be used to authenticate with the Confluence server.
  • Url: The URL associated with your JIRA endpoint. For example, https://yoursitename.atlassian.net.

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

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

cnxn = mod.connect("User=admin;APIToken=myApiToken;Url=https://yoursitename.atlassian.net;Timezone=America/New_York;")

Execute SQL to Confluence

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 Key, Name FROM Pages WHERE Id = '10000'", 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-confluenceedataplot'

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 Confluence data and configure the app layout.

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

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='Confluence Pages 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 Confluence data.

python confluence-dash.py

Free Trial & More Information

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

cnxn = mod.connect("User=admin;APIToken=myApiToken;Url=https://yoursitename.atlassian.net;Timezone=America/New_York;")

df = pd.read_sql("SELECT Key, Name FROM Pages WHERE Id = '10000'", cnxn)
app_name = 'dash-confluencedataplot'

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

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='Confluence Pages Data', barmode='stack')
		})
], className="container")

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