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

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

Connecting to Respond.io Data

Connecting to Respond.io 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 Respondio Profile on disk (e.g. C:\profiles\Respondio.apip). Next, set the ProfileSettings connection property to the connection string for Respondio (see below).

Respondio API Profile Settings

Respond.io uses API key authentication. To obtain an API key:

1. Log in to your Respond.io account.
2. Navigate to Settings in your workspace.
3. Select Developer under the Integrations section.
4. Copy the API key displayed on the page.

After obtaining your API key, set the following connection properties:

• AuthScheme: Set this to APIKey.

Set the following in the ProfileSettings connection property:

• APIKey: Set this to your Respond.io API key.

After installing the CData Respond.io Connector, follow the procedure below to install the other required modules and start accessing Respond.io 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 Respond.io 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 Respond.io Connector to create a connection for working with Respond.io data.

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

Create a SQL Statement to Query Respond.io

Use SQL to create a statement for querying Respond.io. In this article, we read data from the Contacts entity.

sql = "SELECT Id, Email FROM Contacts WHERE Identifier = 'id:438180634'"

Extract, Transform, and Load the Respond.io Data

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

Loading Respond.io Data into a CSV File

table1 = etl.fromdb(cnxn,sql)

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

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

With the CData API Driver for Python, you can work with Respond.io 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 Respond.io 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\Respondio.apip;AuthScheme=APIKey;ProfileSettings='APIKey=your_api_key';")

sql = "SELECT Id, Email FROM Contacts WHERE Identifier = 'id:438180634'"

table1 = etl.fromdb(cnxn,sql)

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

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