How to Build an ETL App for Salesloft Data in Python with CData

The rich ecosystem of Python modules lets you get to work quickly and integrate your systems more effectively. With the CData Python Connector for Salesloft and the petl framework, you can build Salesloft-connected applications and pipelines for extracting, transforming, and loading Salesloft data. This article shows how to connect to Salesloft with the CData Python Connector and use petl and pandas to extract, transform, and load Salesloft data.

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

Connecting to Salesloft Data

Connecting to Salesloft 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.

SalesLoft authenticates using the OAuth authentication standard or an API Key. OAuth requires the authenticating user to interact with SalesLoft using the browser.

Using OAuth

For OAuth authentication, create an OAuth app to obtain the OAuthClientId, OAuthClientSecret, and CallbackURL connection properties. See the OAuth section in the Help documentation for an authentication guide.

Using APIKey

Alternatively, you can authenticate with an APIKey. Provision an API key from the SalesLoft user interface: https://accounts.salesloft.com/oauth/applications/. You will receive a Key which will be used when issuing requests.

After installing the CData Salesloft Connector, follow the procedure below to install the other required modules and start accessing Salesloft through Python objects.

Install Required Modules

Use the pip utility to install the required modules and frameworks:

pip install petl
pip install pandas

Build an ETL App for Salesloft Data in Python

Once the required modules and frameworks are installed, we are ready to build our ETL 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 petl as etl
import pandas as pd
import cdata.salesloft as mod

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

cnxn = mod.connect("AuthScheme=OAuth;OAuthClientId=MyOAuthClientId;OAuthClientSecret=MyOAuthClientSecret;CallbackUrl=http://localhost:33333;InitiateOAuth=GETANDREFRESH;")

Create a SQL Statement to Query Salesloft

Use SQL to create a statement for querying Salesloft. In this article, we read data from the Accounts entity.

sql = "SELECT Id, Name FROM Accounts WHERE Country = 'Canada'"

Extract, Transform, and Load the Salesloft Data

With the query results stored in a DataFrame, we can use petl to extract, transform, and load the Salesloft data. In this example, we extract Salesloft data, sort the data by the Name column, and load the data into a CSV file.

Loading Salesloft Data into a CSV File

table1 = etl.fromdb(cnxn,sql)

table2 = etl.sort(table1,'Name')

etl.tocsv(table2,'accounts_data.csv')

In the following example, we add new rows to the Accounts table.

Adding New Rows to Salesloft

table1 = [ ['Id','Name'], ['NewId1','NewName1'], ['NewId2','NewName2'], ['NewId3','NewName3'] ]

etl.appenddb(table1, cnxn, 'Accounts')

With the CData Python Connector for Salesloft, you can work with Salesloft data just like you would with any database, including direct access to data in ETL packages like petl.

Free Trial & More Information

Download a free, 30-day trial of the CData Python Connector for Salesloft to start building Python apps and scripts with connectivity to Salesloft data. Reach out to our Support Team if you have any questions.

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Full Source Code

import petl as etl
import pandas as pd
import cdata.salesloft as mod

cnxn = mod.connect("AuthScheme=OAuth;OAuthClientId=MyOAuthClientId;OAuthClientSecret=MyOAuthClientSecret;CallbackUrl=http://localhost:33333;InitiateOAuth=GETANDREFRESH;")

sql = "SELECT Id, Name FROM Accounts WHERE Country = 'Canada'"

table1 = etl.fromdb(cnxn,sql)

table2 = etl.sort(table1,'Name')

etl.tocsv(table2,'accounts_data.csv')

table3 = [ ['Id','Name'], ['NewId1','NewName1'], ['NewId2','NewName2'], ['NewId3','NewName3'] ]

etl.appenddb(table3, cnxn, 'Accounts')