zeitsprung 0.1.0

Scraper for www.zeitsprung.fm, a great history podcast.

zeitsprung

This package provides a scraper for www.zeitsprung.fm, a great history podcast. To get the metadata of all episodes from the website, simply start the scraper:

from zeitsprung.scraping import Scraper
s = Scraper('path/to/folder/for/database')
s.run()

The scraper then downloads the all episode metadata and audio files. The metadata is written to the ‘meta’ table in the database. The audio files are converted to ‘.wav’ files and saved separately to a folder, while a link to the file is stored in the ‘audio’ table in the database.

To access the data, create a SQLiteEngine:

from zeitsprung.database import SQLiteEngine
db = SQLiteEngine('path/to/folder/for/database/zeitsprung.db')

Query the meta data from the database:

db.query_all_meta()

And the audio file paths and meta data:

db.query_all_audio()

Now have fun with analysing the episodes of zeitsprung!

Features

• Scraper class to download the meta data and audio files of all episodes.

• Database class to setup and access the SQLite database containing the meta data of the episodes.

To Do

• Processing class to conduct speech recognition on the audio files and build an index for clustering the topics.

• Visualize up to date statistics.

References

• https://www.zeitsprung.fm, check it out!

• This package is licensed under MIT, see the LICENSE file for details.

History

0.1.0 (2020-09-22)

• First release on PyPI.

• Scraper class to download the meta data and audio files of all episodes.

• Database class to setup and access the SQLite database containing the meta data of the episodes.

• Documentation using readthedocs: https://zeitsprung.readthedocs.io/en/latest/

• Github action for building and testing the package.

• Coverage tests using codecov.io.