Use Dash to Build to Web Apps on Salesforce Data Cloud Data



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

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

Connecting to Salesforce Data Cloud Data

Connecting to Salesforce Data Cloud 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.

Salesforce Data Cloud supports authentication via the OAuth standard.

OAuth

Set AuthScheme to OAuth.

Desktop Applications

CData provides an embedded OAuth application that simplifies authentication at the desktop.

You can also authenticate from the desktop via a custom OAuth application, which you configure and register at the Salesforce Data Cloud console. For further information, see Creating a Custom OAuth App in the Help documentation.

Before you connect, set these properties:

  • InitiateOAuth: GETANDREFRESH. You can use InitiateOAuth to avoid repeating the OAuth exchange and manually setting the OAuthAccessToken.
  • OAuthClientId (custom applications only): The Client ID assigned when you registered your custom OAuth application.
  • OAuthClientSecret (custom applications only): The Client Secret assigned when you registered your custom OAuth application.

When you connect, the driver opens Salesforce Data Cloud's OAuth endpoint in your default browser. Log in and grant permissions to the application.

The driver then completes the OAuth process as follows:

  • Extracts the access token from the callback URL.
  • Obtains a new access token when the old one expires.
  • Saves OAuth values in OAuthSettingsLocation so that they persist across connections.
  • For other OAuth methods, including Web Applications and Headless Machines, refer to the Help documentation.

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

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

    cnxn = mod.connect("InitiateOAuth=GETANDREFRESH;OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")")
    

    Execute SQL to Salesforce Data Cloud

    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 [Account ID], [Account Name] FROM Account WHERE EmployeeCount = '250'", 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-salesforcedatacloudedataplot'
    
    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 Salesforce Data Cloud data and configure the app layout.

    trace = go.Bar(x=df.[Account ID], y=df.[Account Name], name='[Account ID]')
    
    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='Salesforce Data Cloud Account 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 Salesforce Data Cloud data.

    python salesforcedatacloud-dash.py
    

    Free Trial & More Information

    Download a free, 30-day trial of the CData Python Connector for Salesforce Data Cloud to start building Python apps with connectivity to Salesforce Data Cloud 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.salesforcedatacloud as mod
    import plotly.graph_objs as go
    
    cnxn = mod.connect("InitiateOAuth=GETANDREFRESH;OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")
    
    df = pd.read_sql("SELECT [Account ID], [Account Name] FROM Account WHERE EmployeeCount = '250'", cnxn)
    app_name = 'dash-salesforcedataclouddataplot'
    
    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.[Account ID], y=df.[Account Name], name='[Account ID]')
    
    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='Salesforce Data Cloud Account Data', barmode='stack')
    		})
    ], className="container")
    
    if __name__ == '__main__':
        app.run_server(debug=True)
    

Ready to get started?

Download a free trial of the Salesforce Data Cloud Connector to get started:

 Download Now

Learn more:

Salesforce Data Cloud Icon Salesforce Data Cloud Python Connector

Python Connector Libraries for Salesforce Data Cloud Data Connectivity. Integrate Salesforce Data Cloud with popular Python tools like Pandas, SQLAlchemy, Dash & petl.