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

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 Azure Synapse-connected web applications for Azure Synapse data. This article shows how to connect to Connect AI and use pandas and Dash to build a simple web app for visualizing Azure Synapse 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 Azure Synapse 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. Select "Azure Synapse" from the Add Connection panel

3. Enter the necessary authentication properties to connect to Azure Synapse.

   Connecting to Azure Synapse

   In addition to providing authentication (see below), set the following properties to connect to a Azure Synapse database:

   • Server: The server running Azure. You can find this by logging into the Azure portal and navigating to Azure Synapse Analytics -> Select your database -> Overview -> Server name.
   • Database: The name of the database, as seen in the Azure portal on the Azure Synapse Analytics page.

   Authenticating to Azure Synapse

   Connect to Azure Synapse using the following properties:

   • User: The username provided for authentication with Azure.
   • Password: The password associated with the authenticating user.
   
4. Click Save & Test
5. Navigate to the Permissions tab and update the user-based 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.
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 Azure Synapse 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 Azure Synapse data into a DataFrame. Identifiers are three-part: <Connection>.<Schema>.<Table>, where the connection name defaults to the source name (for example, AzureSynapse1).

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 Id, ProductName "
    "FROM [AzureSynapse1].[AzureSynapse].[Products] "
    "WHERE ProductName = 'Konbu'",
    conn,
)

conn.close()

Configure the App and Layout

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

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

trace = go.Bar(x=df['Id'], y=df['ProductName'], name='Id')

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='Azure Synapse Products 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 Azure Synapse data.

python azuresynapse-dash.py

More Information and Free Trial

Now you can build interactive Dash web apps on live Azure Synapse data using the CData Connect AI Python SDK. For more information on connecting to Azure Synapse (and hundreds of other data sources), visit the Connect AI page. Sign up for a free trial and start building web apps on live Azure Synapse 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 Id, ProductName "
    "FROM [AzureSynapse1].[AzureSynapse].[Products] "
    "WHERE ProductName = 'Konbu'",
    conn,
)

conn.close()

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

trace = go.Bar(x=df['Id'], y=df['ProductName'], name='Id')

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='Azure Synapse Products Data', barmode='stack'),
            },
        ),
    ],
    className="container",
)

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