Skip to main content

A simple Django app that tracks podcast feeds and provides some useful metrics about them.

Project description

Django Podcast Analyzer

A simple Django app that allows you to follow the feeds of various podcasts and glean interesting information from them.

PyPI PyPI - Python Version PyPI - Versions from Framework Classifiers Black code style Pre-commit License uv Ruff Security: bandit Checked with pyright Semantic Versions Test results Coverage Status Documentation

Warning

This is early stage! Things that still need to be done:

  • Better handling of duplicate people discovered from multiple feeds
  • Improved docs.

Installation

Via pip:

python -m pip install django-podcast-analyzer

Via uv:

uv pip install django-podcast-analyzer

Then add it and our dependencies to your list of installed apps.

# settings.py

# Your setup may vary.
INSTALLED_APPS = [
    "django.contrib.auth",
    "django.contrib.contenttypes",
    "django.contrib.sessions",
    "django.contrib.sites",
    "django.contrib.messages",
    "django.contrib.staticfiles",
    "django.contrib.admin",
    "django.forms",
    ...,
    # Here are our explict dependencies
    "tagulous",
    "django_q",
    "podcast_analyzer",
]

We use tagulous for tagging podcasts and django-q2 to handle the scheduled tasks related to fetching feeds and processing them. See the documentation for both of those projects to identify any additional configuration needed.

Add it to your urls.py:

# Your root urls.py

from django.urls import include, path

urlpatterns = [
    ...,
    path("podcasts/", include("podcast_analyzer.urls", namespace="podcasts")),
    ...,
]

Then run your migrations.

python manage.py migrate

You'll also want to seed the database with the known iTunes categories for podcasts. You can do this via the provided management command. It will only do so if the respective tables are empty so you won't get duplicates.

python manage.py seed_database_itunes

In order to run the application, you will also need to spawn a django-q cluster using python manage.py qcluster. You can also use a runner like honcho or a Supervisor app.

Other Recommendations

For storage of podcast art and other media, it's recommended you consider using something like django-storages.

Development

Contributions are welcome! See our contributing guide for details.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

django_podcast_analyzer-0.2.2.tar.gz (58.0 kB view details)

Uploaded Source

Built Distribution

django_podcast_analyzer-0.2.2-py3-none-any.whl (50.2 kB view details)

Uploaded Python 3

File details

Details for the file django_podcast_analyzer-0.2.2.tar.gz.

File metadata

File hashes

Hashes for django_podcast_analyzer-0.2.2.tar.gz
Algorithm Hash digest
SHA256 e8a2b510ee1a3f550ef0aff0fe98fdfc038f060f889fd41fd83a168b86475d7e
MD5 5423f19a7fd0f5445380589199351de1
BLAKE2b-256 daa2ee2ef702fca5004c312a97074384cf4e159fdbe774891fafeb9d9f729dd8

See more details on using hashes here.

File details

Details for the file django_podcast_analyzer-0.2.2-py3-none-any.whl.

File metadata

File hashes

Hashes for django_podcast_analyzer-0.2.2-py3-none-any.whl
Algorithm Hash digest
SHA256 5cfed49763520d85b89f5ee763466c154da50cc2209dbaf76210471564b7f3da
MD5 f7538dd9cca201f8d9e36a0e6285ef3b
BLAKE2b-256 65a6d5e9e56c42704aa2ed45677425dda72886b05634d1d1fbcdc44e269fdbac

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page