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

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

Connecting to HelloSign Data

Connecting to HelloSign 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.

Start by setting the Profile connection property to the location of the HelloSign Profile on disk (e.g. C:\profiles\HelloSign.apip). Next, set the ProfileSettings connection property to the connection string for HelloSign (see below).

HelloSign API Profile Settings

Navigate to Settings > API > API Key in your HelloSign (Dropbox Sign) account to obtain your API key.

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

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

cnxn = mod.connect("Profile=C:\profiles\HelloSign.apip;ProfileSettings='APIKey=your_api_key';")

Create a SQL Statement to Query HelloSign

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

sql = "SELECT AccountId, EmailAddress FROM Account WHERE IsPaidHs = 'true'"

Extract, Transform, and Load the HelloSign Data

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

Loading HelloSign Data into a CSV File

table1 = etl.fromdb(cnxn,sql)

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

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

With the CData API Driver for Python, you can work with HelloSign 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 API Driver for Python to start building Python apps and scripts with connectivity to HelloSign 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.api as mod

cnxn = mod.connect("Profile=C:\profiles\HelloSign.apip;ProfileSettings='APIKey=your_api_key';")

sql = "SELECT AccountId, EmailAddress FROM Account WHERE IsPaidHs = 'true'"

table1 = etl.fromdb(cnxn,sql)

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

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