Use Dash to Build Web Apps on API 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 API-connected web applications for API data. This article shows how to connect to Connect AI and use pandas and Dash to build a simple web app for visualizing API 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 API 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 "API" from the Add Connection panel

3. Enter the necessary authentication properties to connect to your API.

   To connect to your API, configure the following properties on the Global Settings page:

   • In Authentication, select the Type and fill in the required properties
   • In Headers, add the required HTTP headers for your API
   • In Pagination, select the Type and fill in the required properties

   After the configuring the global settings, navigate to the Tables to add tables. For each table you wish to add:

   1. Click "+ Add"
   2. Set the Name for the table
   3. Set Request URL to the API endpoint you wish to work with
   4. (Optional) In Parameters, add the required URL Parameters for your API endpoint
   5. (Optional) In Headers, add the required HTTP headers for the API endpoint
   6. In Table Data click " Configure"
   7. Review the response from the API and click "Next"
   8. Select which element to use as the Repeated Elements and which elements to use as Columns and click "Next"
   9. Preview the tabular model of the API response and click "Confirm"
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 API 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 API data into a DataFrame. Identifiers are three-part: <Connection>.<Schema>.<Table>, where the connection name defaults to the source name (for example, API1).

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 title, body "
    "FROM [API1].[API].[posts] "
    "WHERE userId = '12345'",
    conn,
)

conn.close()

Configure the App and Layout

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

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

trace = go.Bar(x=df['title'], y=df['body'], name='title')

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='API posts 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 API data.

python api-dash.py

More Information and Free Trial

Now you can build interactive Dash web apps on live API data using the CData Connect AI Python SDK. For more information on connecting to API (and hundreds of other data sources), visit the Connect AI page. Sign up for a free trial and start building web apps on live API 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 title, body "
    "FROM [API1].[API].[posts] "
    "WHERE userId = '12345'",
    conn,
)

conn.close()

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

trace = go.Bar(x=df['title'], y=df['body'], name='title')

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='API posts Data', barmode='stack'),
            },
        ),
    ],
    className="container",
)

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