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

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

Connecting to RSS Feeds

Connecting to RSS feeds 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.

You can connect to RSS and Atom feeds, as well as feeds with custom extensions. To connect to a feed, set the URL property. You can also access secure feeds. A variety of authentication mechanisms are supported. See the help documentation for details.

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

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

cnxn = mod.connect("URI=http://broadcastCorp/rss/;")

Create a SQL Statement to Query RSS

Use SQL to create a statement for querying RSS. In this article, we read data from the Latest News entity.

sql = "SELECT Author, Pubdate FROM Latest News WHERE Category = 'US'"

Extract, Transform, and Load the RSS Feeds

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

Loading RSS Feeds into a CSV File

table1 = etl.fromdb(cnxn,sql)

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

etl.tocsv(table2,'latest news_data.csv')

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

Full Source Code

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

cnxn = mod.connect("URI=http://broadcastCorp/rss/;")

sql = "SELECT Author, Pubdate FROM Latest News WHERE Category = 'US'"

table1 = etl.fromdb(cnxn,sql)

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

etl.tocsv(table2,'latest news_data.csv')