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

Use Dash to Build to Web Apps on Sugar CRM Data



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

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

Connecting to Sugar CRM Data

Connecting to Sugar CRM 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.

The User and Password properties, under the Authentication section, must be set to valid SugarCRM user credentials. This will use the default OAuth token created to allow client logins. OAuthClientId and OAuthClientSecret are required if you do not wish to use the default OAuth token.

You can generate a new OAuth consumer key and consumer secret in Admin -> OAuth Keys. Set the OAuthClientId to the OAuth consumer key. Set the OAuthClientSecret to the consumer secret.

Additionally, specify the URL to the SugarCRM account.

Note that retrieving SugarCRM metadata can be expensive. It is advised that you store the metadata locally as described in the "Caching Metadata" chapter of the help documentation.

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

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

cnxn = mod.connect("User=MyUser;Password=MyPassword;URL=MySugarCRMAccountURL;CacheMetadata=True;")

Execute SQL to Sugar CRM

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, AnnualRevenue FROM Accounts WHERE Name = 'Bob'", 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-sugarcrmedataplot'

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 Sugar CRM data and configure the app layout.

trace = go.Bar(x=df.Name, y=df.AnnualRevenue, 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='Sugar CRM Accounts 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 Sugar CRM data.

python sugarcrm-dash.py

Free Trial & More Information

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

cnxn = mod.connect("User=MyUser;Password=MyPassword;URL=MySugarCRMAccountURL;CacheMetadata=True;")

df = pd.read_sql("SELECT Name, AnnualRevenue FROM Accounts WHERE Name = 'Bob'", cnxn)
app_name = 'dash-sugarcrmdataplot'

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.AnnualRevenue, 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='Sugar CRM Accounts Data', barmode='stack')
		})
], className="container")

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