Use Dash to Build Web Apps on XML Data via CData Connect AI

Jerod Johnson
Jerod Johnson
Director, Technology Evangelism
Build interactive Dash web apps on live XML data using pandas and the CData Connect AI Python SDK.

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

The Connect AI Python SDK (cdata-connect-ai) is a DB-API 2.0 (PEP 249) compliant client, so pandas can read query results directly from the SDK connection object. There is no driver to install per source: connect with a Personal Access Token and build your app.

Connect to XML in Connect AI

CData Connect AI uses a straightforward, point-and-click interface to connect to data sources.

  1. Log into Connect AI, click Sources, and then click Add Connection
  2. Adding a Connection
  3. Select "XML" from the Add Connection panel
  4. Selecting a data source
  5. Enter the necessary authentication properties to connect to XML.

    Connecting to Local or Cloud-Stored (Box, Google Drive, Amazon S3, SharePoint) XML Files

    CData Drivers let you work with XML files stored locally and stored in cloud storage services like Box, Amazon S3, Google Drive, or SharePoint, right where they are.

    Setting connection properties for local files

    Set the URI property to local folder path.

    Setting connection properties for files stored in Amazon S3

    To connect to XML file(s) within Amazon S3, set the URI property to the URI of the Bucket and Folder where the intended XML files exist. In addition, at least set these properties:

    • AWSAccessKey: AWS Access Key (username)
    • AWSSecretKey: AWS Secret Key

    Setting connection properties for files stored in Box

    To connect to XML file(s) within Box, set the URI property to the URI of the folder that includes the intended XML file(s). Use the OAuth authentication method to connect to Box.

    Dropbox

    To connect to XML file(s) within Dropbox, set the URI proprerty to the URI of the folder that includes the intended XML file(s). Use the OAuth authentication method to connect to Dropbox. Either User Account or Service Account can be used to authenticate.

    SharePoint Online (SOAP)

    To connect to XML file(s) within SharePoint with SOAP Schema, set the URI proprerty to the URI of the document library that includes the intended XML file. Set User, Password, and StorageBaseURL.

    SharePoint Online REST

    To connect to XML file(s) within SharePoint with REST Schema, set the URI proprerty to the URI of the document library that includes the intended XML file. StorageBaseURL is optional. If not set, the driver will use the root drive. OAuth is used to authenticate.

    Google Drive

    To connect to XML file(s) within Google Drive, set the URI property to the URI of the folder that includes the intended XML file(s). Use the OAuth authentication method to connect and set InitiateOAuth to GETANDREFRESH.

    The DataModel property is the controlling property over how your data is represented into tables and toggles the following basic configurations.

    • Document (default): Model a top-level, document view of your XML data. The data provider returns nested elements as aggregates of data.
    • FlattenedDocuments: Implicitly join nested documents and their parents into a single table.
    • Relational: Return individual, related tables from hierarchical data. The tables contain a primary key and a foreign key that links to the parent document.

    See the Modeling XML Data chapter for more information on configuring the relational representation. You will also find the sample data used in the following examples. The data includes entries for people, the cars they own, and various maintenance services performed on those cars.

    Configuring a connection (Salesforce is shown)
  6. Click Save & Test
  7. Navigate to the Permissions tab and update the user-based permissions. Updating permissions

Generate a Personal Access Token (PAT)

The Python SDK authenticates to Connect AI with your account email and a Personal Access Token (PAT). It is best practice to create a separate PAT for each application to maintain granularity of access.

  1. Click the Gear icon () at the top right of the Connect AI app to open the Settings page.
  2. On the Settings page, go to the Access Tokens section and click Create PAT.
  3. Give the PAT a name and click Create. Creating a new PAT
  4. The PAT is only visible at creation, so copy it and store it securely.

Install Required Modules

Install the SDK (with the pandas extra), Dash, and Plotly using the pip utility:

pip install "cdata-connect-ai[full]"
pip install dash
pip install plotly

Build a Web App on XML Data in Python

Once the required modules are installed, you are ready to build the web app. Code snippets follow, but the full source code is available at the end of the article.

First, import the modules, then connect to Connect AI with your account email and PAT and read XML data into a DataFrame. Identifiers are three-part: <Connection>.<Schema>.<Table>, where the connection name defaults to the source name (for example, XML1).

import dash
from dash import dcc, html
import pandas as pd
import plotly.graph_objs as go
import cdata_connect_ai

conn = cdata_connect_ai.connect(
    username="[email protected]",
    password="<your_pat>",
)

df = pd.read_sql(
    "SELECT [ personal.name.first ], [ personal.name.last ] "
    "FROM [XML1].[XML].[people] "
    "WHERE [ personal.name.last ] = 'Roberts'",
    conn,
)

conn.close()

Configure the App and Layout

With the query results stored in a DataFrame, build a bar graph from the XML data and configure the app layout.

app = dash.Dash(__name__)
app.title = 'CData Connect AI + Dash'

trace = go.Bar(x=df['[ personal.name.first ]'], y=df['[ personal.name.last ]'], name='[ personal.name.first ]')

app.layout = html.Div(
    children=[
        html.H1("CData Connect AI + Dash", style={'textAlign': 'center'}),
        dcc.Graph(
            id='example-graph',
            figure={
                'data': [trace],
                'layout': go.Layout(title='XML people Data', barmode='stack'),
            },
        ),
    ],
    className="container",
)

Set the App to Run

With the connection, app, and layout configured, you are ready to run the app.

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

Now, use Python to run the web app and a browser to view the XML data.

python xml-dash.py
The Dash web app running in a browser (Salesforce is shown)

More Information and Free Trial

Now you can build interactive Dash web apps on live XML data using the CData Connect AI Python SDK. For more information on connecting to XML (and hundreds of other data sources), visit the Connect AI page. Sign up for a free trial and start building web apps on live XML data in Python.



Full Source Code

import dash
from dash import dcc, html
import pandas as pd
import plotly.graph_objs as go
import cdata_connect_ai

conn = cdata_connect_ai.connect(
    username="[email protected]",
    password="<your_pat>",
)

df = pd.read_sql(
    "SELECT [ personal.name.first ], [ personal.name.last ] "
    "FROM [XML1].[XML].[people] "
    "WHERE [ personal.name.last ] = 'Roberts'",
    conn,
)

conn.close()

app = dash.Dash(__name__)
app.title = 'CData Connect AI + Dash'

trace = go.Bar(x=df['[ personal.name.first ]'], y=df['[ personal.name.last ]'], name='[ personal.name.first ]')

app.layout = html.Div(
    children=[
        html.H1("CData Connect AI + Dash", style={'textAlign': 'center'}),
        dcc.Graph(
            id='example-graph',
            figure={
                'data': [trace],
                'layout': go.Layout(title='XML people Data', barmode='stack'),
            },
        ),
    ],
    className="container",
)

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

Ready to get started?

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