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

Use Dash to Build to Web Apps on Marketo Data



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

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

Connecting to Marketo Data

Connecting to Marketo 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.

Both the REST and SOAP APIs are supported and can be chosen by using the Schema property.

For the REST API: The OAuthClientId, OAuthClientSecret, and RESTEndpoint properties, under the OAuth and REST Connection sections, must be set to valid Marketo user credentials.

For the SOAP API: The UserId, EncryptionKey, and SOAPEndpoint properties, under the SOAP Connection section, must be set to valid Marketo user credentials.

See the "Getting Started" chapter of the help documentation for a guide to obtaining these values.

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

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

cnxn = mod.connect("Schema=REST;RESTEndpoint=https://311-IFS-929.mktorest.com/rest;OAuthClientId=MyOAuthClientId;OAuthClientSecret=MyOAuthClientSecret;")

Execute SQL to Marketo

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 Email, AnnualRevenue FROM Leads WHERE Country = 'U.S.A.'", 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-marketoedataplot'

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 Marketo data and configure the app layout.

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

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='Marketo Leads 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 Marketo data.

python marketo-dash.py

Free Trial & More Information

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

cnxn = mod.connect("Schema=REST;RESTEndpoint=https://311-IFS-929.mktorest.com/rest;OAuthClientId=MyOAuthClientId;OAuthClientSecret=MyOAuthClientSecret;")

df = pd.read_sql("SELECT Email, AnnualRevenue FROM Leads WHERE Country = 'U.S.A.'", cnxn)
app_name = 'dash-marketodataplot'

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

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

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