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

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

Connecting to Gorgias Data

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

Gorgias API Profile Settings

Use your Gorgias login email as the User and your API key as the Password. Your Domain is the subdomain from your Gorgias portal URL.

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

cnxn = mod.connect("Profile=C:\profiles\Gorgias.apip;ProfileSettings='User=your_email;Password=your_api_key;Domain=your_subdomain';")

Create a SQL Statement to Query Gorgias

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

sql = "SELECT Id, Name FROM Customers WHERE Active = 'true'"

Extract, Transform, and Load the Gorgias Data

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

Loading Gorgias Data into a CSV File

table1 = etl.fromdb(cnxn,sql)

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

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

With the CData API Driver for Python, you can work with Gorgias 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 Gorgias 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\Gorgias.apip;ProfileSettings='User=your_email;Password=your_api_key;Domain=your_subdomain';")

sql = "SELECT Id, Name FROM Customers WHERE Active = 'true'"

table1 = etl.fromdb(cnxn,sql)

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

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