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

Use Dash to Build to Web Apps on Salesforce Data



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

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

Connecting to Salesforce Data

Connecting to Salesforce 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.

There are several authentication methods available for connecting to Salesforce: Login, OAuth, and SSO. The Login method requires you to have the username, password, and security token of the user.

If you do not have access to the username and password or do not wish to require them, you can use OAuth authentication.

SSO (single sign-on) can be used by setting the SSOProperties, SSOLoginUrl, and TokenUrl connection properties, which allow you to authenticate to an identity provider. See the "Getting Started" chapter in the help documentation for more information.

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

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

cnxn = mod.connect("User=username;Password=password;SecurityToken=Your_Security_Token;")

Execute SQL to Salesforce

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 Industry, AnnualRevenue FROM Account WHERE Name = 'GenePoint'", 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-salesforceedataplot'

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 and configure the app layout.

trace = go.Bar(x=df.Industry, y=df.AnnualRevenue, name='Industry')

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 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.

python salesforce-dash.py

Free Trial & More Information

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

cnxn = mod.connect("User=username;Password=password;SecurityToken=Your_Security_Token;")

df = pd.read_sql("SELECT Industry, AnnualRevenue FROM Account WHERE Name = 'GenePoint'", cnxn)
app_name = 'dash-salesforcedataplot'

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.Industry, y=df.AnnualRevenue, name='Industry')

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

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