Use SQLAlchemy ORMs to Access RSS Feeds in Python

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RSS Python Connector

Python Connector Libraries for RSS Feeds Data Connectivity. Integrate RSS Feeds with popular Python tools like Pandas, SQLAlchemy, Dash & petl.

The CData Python Connector for RSS enables you to create Python applications and scripts that use SQLAlchemy Object-Relational Mappings of RSS feeds.

The rich ecosystem of Python modules lets you get to work quickly and integrate your systems effectively. With the CData Python Connector for RSS and the SQLAlchemy toolkit, you can build RSS-connected Python applications and scripts. This article shows how to use SQLAlchemy to connect to RSS feeds to query 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 CData Connector 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.

Follow the procedure below to install SQLAlchemy and start accessing RSS through Python objects.

Install Required Modules

Use the pip utility to install the SQLAlchemy toolkit:

pip install sqlalchemy

Be sure to import the module with the following:

import sqlalchemy

Model RSS Feeds in Python

You can now connect with a connection string. Use the create_engine function to create an Engine for working with RSS feeds.

engine = create_engine("rss:///?URI=http://broadcastCorp/rss/")

Declare a Mapping Class for RSS Feeds

After establishing the connection, declare a mapping class for the table you wish to model in the ORM (in this article, we will model the Latest News table). Use the sqlalchemy.ext.declarative.declarative_base function and create a new class with some or all of the fields (columns) defined.

base = declarative_base()
class Latest News(base):
	__tablename__ = "Latest News"
	Author = Column(String,primary_key=True)
	Pubdate = Column(String)

Query RSS Feeds

With the mapping class prepared, you can use a session object to query the data source. After binding the Engine to the session, provide the mapping class to the session query method.

Using the query Method

engine = create_engine("rss:///?URI=http://broadcastCorp/rss/")
factory = sessionmaker(bind=engine)
session = factory()
for instance in session.query(Latest News).filter_by(Category="US"):
	print("Author: ", instance.Author)
	print("Pubdate: ", instance.Pubdate)

Alternatively, you can use the execute method with the appropriate table object. The code below works with an active session.

Using the execute Method

Latest News_table = Latest News.metadata.tables["Latest News"]
for instance in session.execute(Latest News_table.c.Category == "US")):
	print("Author: ", instance.Author)
	print("Pubdate: ", instance.Pubdate)

For examples of more complex querying, including JOINs, aggregations, limits, and more, refer to the Help documentation for the extension.

Free Trial & More Information

Download a free, 30-day trial of the RSS Python Connector to start building Python apps and scripts with connectivity to RSS feeds. Reach out to our Support Team if you have any questions.