Extract, Transform, and Load X-Cart Data in Python

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X-Cart Python Connector

Python Connector Libraries for X-Cart Data Connectivity. Integrate X-Cart with popular Python tools like Pandas, SQLAlchemy, Dash & petl.



The CData Python Connector for X-Cart enables you to create ETL applications and pipelines for X-Cart data in Python with petl.

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

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

Connecting to X-Cart Data

Connecting to X-Cart 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.

An API Key must be created for your XCart Installation. In order to obtain the API Key, you need to install and configure the REST API Module for your X-Cart installation.

  • Login to your X-Cart Installation. Click on My addons on the bottom of the left side-bar navigation panel.
  • Search for REST API Module. Install the Module.
  • After the module has been installed, you need to set it up.
    • Go to the Settings section for the REST API Module.
    • On the settings page specify the API Key (only read)
  • Set the ApiKey and Url to the connection property to connect to data.

After installing the CData X-Cart Connector, follow the procedure below to install the other required modules and start accessing X-Cart 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 X-Cart 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.xcart as mod

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

cnxn = mod.connect("Url=https://example.com/shop;ApiKey=MyApiKey;")

Create a SQL Statement to Query X-Cart

Use SQL to create a statement for querying X-Cart. In this article, we read data from the PROFILES entity.

sql = "SELECT ProfileId, FirstName FROM PROFILES WHERE Language = 'en'"

Extract, Transform, and Load the X-Cart Data

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

Loading X-Cart Data into a CSV File

table1 = etl.fromdb(cnxn,sql)

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

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

With the CData Python Connector for X-Cart, you can work with X-Cart 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 X-Cart Python Connector to start building Python apps and scripts with connectivity to X-Cart 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.xcart as mod

cnxn = mod.connect("Url=https://example.com/shop;ApiKey=MyApiKey;")

sql = "SELECT ProfileId, FirstName FROM PROFILES WHERE Language = 'en'"

table1 = etl.fromdb(cnxn,sql)

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

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