Download an RSS or Atom feed and save it to a SQLite database. This is meant to work well with datasette.
pip install feed-to-sqlite
Let's grab the ATOM feeds for items I've shared on NewsBlur and my instapaper favorites save each its own table.
feed-to-sqlite feeds.db http://chrisamico.newsblur.com/social/rss/35501/chrisamico https://www.instapaper.com/starred/rss/13475/qUh7yaOUGOSQeANThMyxXdYnho
This will use a SQLite database called feeds.db
, creating it if necessary. By default, each feed gets its own table, named based on a slugified version of the feed's title.
To load all items from multiple feeds into a common (or pre-existing) table, pass a --table
argument:
feed-to-sqlite feeds.db --table links <url> <url>
That will put all items in a table called links
.
Each feed also creates an entry in a feeds
table containing top-level metadata for each feed. Each item will have a foreign key to the originating feed. This is especially useful if combining feeds into a shared table.
One function, ingest_feed
, does most of the work here. The following will create a database called feeds.db
and download my NewsBlur shared items into a new table called links
.
from feed_to_sqlite import ingest_feed
url = "http://chrisamico.newsblur.com/social/rss/35501/chrisamico"
ingest_feed("feeds.db", url=url, table_name="links")
When working in Python directly, it's possible to pass in a function to transform rows before they're saved to the database.
The normalize
argument to ingest_feed
is a function that will be called on each feed item, useful for fixing links or doing additional work.
It's signature is normalize(table, entry, feed_details, client)
:
table
is a SQLite table (from sqlite-utils)entry
is one feed item, as a dictionaryfeed_details
is a dictionary of top-level feed information, as a dictionaryclient
is an instance ofhttpx.Client
, which can be used for outgoing HTTP requests during normalization
That function should return a dictionary representing the row to be saved. Returning a falsey value for a given row will cause that row to be skipped.
Tests use pytest. Run pytest tests/
to run the test suite.