This package provides a Scrapy pipeline and items to generate a podcast RSS feed
from scraped information. It also allows to save the content locally or in an S3
bucket. You can then point your podcast player to the URL of the file and
listen to its content.
Installation
Install scrapy-podcast-rss using pip
:
$ pip install scrapy-podcast-rss
Configuration
- You need to define
OUTPUT_URI
in your settings.py
file, this will
determine where your feed will be stored. For example:
OUTPUT_URI = './my-podcast.xml'
OUTPUT_URI = 's3://my-bucket/my-podcast.xml'
- Add
PodcastPipeline
in ITEM_PIPELINES
in your settings.py
file:
ITEM_PIPELINES = {
'scrapy_podcast_rss.pipelines.PodcastPipeline': 300,
}
Usage
scrapy-podcast-rss defines two special items:
PodcastDataItem
: Stores information about the podcast.PodcastEpisodeItem
: Stores information about each episode of the podcast.
You must yield one PodcastDataItem
and one PodcastEpisodeItem
for each
episode you want to export, before your spider closes.
Here is the information you can currently store in each item (you need to use
the same names):
PodcastDataItem
:
title
: Title of the podcast.description
: Description of the podcast.url
: URL referencing the podcast.image_url
: Main image of the podcast.
PodcastDataItem
:
title
: Title of the episode.description
: Description of the episode.publication_date
: Date of publication (datetime
object with timezone).audio_url
: URL of the audio.guid
: Unique identifier of the episode.
Example
You can find a minimal example of a spider using this package here:
scrapy-podcast-rss-example.
You can also find an example of the package being used in an AWS Lambda function here: scrapy-podcast-rss-serverless.
Spider example
import datetime
import scrapy
import pytz
from scrapy_podcast_rss import PodcastEpisodeItem, PodcastDataItem
class SimpleSpider(scrapy.Spider):
name = "simple_spider"
start_urls = ['http://example.com/']
custom_settings = {
'OUTPUT_URI': './my-podcast.xml',
'ITEM_PIPELINES': {'scrapy_podcast_rss.pipelines.PodcastPipeline': 300, }
}
def parse(self, response):
podcast_data_item = PodcastDataItem()
podcast_data_item['title'] = "Podcast title"
podcast_data_item['description'] = "Description of the podcast."
podcast_data_item['url'] = "Podcast's URL"
podcast_data_item['image_url'] = "https://live.staticflickr.com/4211/35400224382_9edcb984e5_c.jpg"
yield podcast_data_item
episode_item = PodcastEpisodeItem()
episode_item['title'] = "Episode title"
episode_item['description'] = "Episode description"
pub_date_tz = datetime.datetime.strptime("01/01/2020", "%m/%d/%Y").replace(tzinfo=pytz.UTC)
episode_item['publication_date'] = pub_date_tz
episode_item['guid'] = "Episode guid"
episode_item['audio_url'] = "https://ia801803.us.archive.org/13/items/MOZARTSerenadeEineKleineNachtmusikK." \
"525-NEWTRANSFER01.I.Allegro/01.I.Allegro.mp3 "
yield episode_item
Note on using S3 as storage
To use S3 storage locations, you can install scrapy-podcast-rss by doing:
$ pip install scrapy-podcast-rss[s3_storage]
This will simply include boto3
in the dependencies.
Once installed, you will need to have your credentials configured
(boto3 quickstart guide).