Ready to get started?

Learn more about the CData Python Connector for Salesforce Einstein or download a free trial:

Download Now

Use Dash to Build to Web Apps on Salesforce Einstein Data

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

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

Connecting to Salesforce Einstein Data

Connecting to Salesforce Einstein 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 Einstein Analytics uses the OAuth 2 authentication standard. You will need to obtain the OAuthClientId and OAuthClientSecret by registering an app with Salesforce Einstein Analytics.

See the Getting Started section of the CData data provider documentation for an authentication guide.

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

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

cnxn = mod.connect("OAuthClientId=MyConsumerKey;OAuthClientSecret=MyConsumerSecret;CallbackURL=http://localhost:portNumber;InitiateOAuth=GETANDREFRESH;OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")")

Execute SQL to Salesforce Einstein

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 Name, CloseDate FROM Dataset_Opportunity WHERE StageName = 'Closed Won'", 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-sfeinsteinanalyticsedataplot'

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 Einstein data and configure the app layout.

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

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 Einstein Dataset_Opportunity 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 Einstein data.

python sfeinsteinanalytics-dash.py

Free Trial & More Information

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

cnxn = mod.connect("OAuthClientId=MyConsumerKey;OAuthClientSecret=MyConsumerSecret;CallbackURL=http://localhost:portNumber;InitiateOAuth=GETANDREFRESH;OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")

df = pd.read_sql("SELECT Name, CloseDate FROM Dataset_Opportunity WHERE StageName = 'Closed Won'", cnxn)
app_name = 'dash-sfeinsteinanalyticsdataplot'

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

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 Einstein Dataset_Opportunity Data', barmode='stack')
		})
], className="container")

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