How to Build an ETL App for DocuSign 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 DocuSign and the petl framework, you can build DocuSign-connected applications and pipelines for extracting, transforming, and loading DocuSign data. This article shows how to connect to DocuSign with the CData Python Connector and use petl and pandas to extract, transform, and load DocuSign data.

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

Connecting to DocuSign Data

Connecting to DocuSign 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.

To connect to DocuSign, set the following connection properties:

• UseSandbox: indicates whether current user account is sandbox or not (FALSE by default)
• AccountId (optional): set it in the connection string if you have access to multiple Account Ids

Authenticating to DocuSign

DocuSign uses the OAuth authentication standard. To authenticate using OAuth, you will need to create an app to obtain the OAuthClientId, OAuthClientSecret, and CallbackURL connection properties. See the Help documentation more information.

After installing the CData DocuSign Connector, follow the procedure below to install the other required modules and start accessing DocuSign 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 DocuSign 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.docusign as mod

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

cnxn = mod.connect("OAuthClientId=MyClientId; OAuthClientSecret=MyClientSecret; 
CallbackURL=http://localhost:33333;
InitiateOAuth=GETANDREFRESH;OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")")

Create a SQL Statement to Query DocuSign

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

sql = "SELECT DocumentId, DocumentName FROM Documents WHERE DocumentName = 'TPSReport'"

Extract, Transform, and Load the DocuSign Data

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

Loading DocuSign Data into a CSV File

table1 = etl.fromdb(cnxn,sql)

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

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

With the CData Python Connector for DocuSign, you can work with DocuSign 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 DocuSign to start building Python apps and scripts with connectivity to DocuSign data. Reach out to our Support Team if you have any questions.

Full Source Code

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

cnxn = mod.connect("OAuthClientId=MyClientId; OAuthClientSecret=MyClientSecret; 
CallbackURL=http://localhost:33333;
InitiateOAuth=GETANDREFRESH;OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")")

sql = "SELECT DocumentId, DocumentName FROM Documents WHERE DocumentName = 'TPSReport'"

table1 = etl.fromdb(cnxn,sql)

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

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