episodix 0.5.3

Tool to automate preparing podcast episode documents with Readeck

episodix

episodix assists with preparing podcast episode documents. It reads bookmarks from multiple users stored on Readeck instances and groups links by their labels. Every bookmark needs to have only one label set.

The script can create commonly used labels and prepare a Markdown document (links and shownotes) using Jinja2.

Prerequisites

Create an API token for your Readeck account:

Setting	Value
Name	uiu
Roles	Bookmarks Read/Write, Profile Read

Copy the (opinionated) sample.episodixrc example configuration to .episodixrc and add URLs and API tokens for all the users that you want to include.

Installation

pip

Install locally:

$ pip3 install -e .

Or install over PyPi:

$ pip3 install episodix

Manual

Install Python requirements:

$ pip3 install -u -r requirements.txt

Usage

Initialize workflow. This creates a dummy link with commonly used labels so you have to enter them manually:

$ episodix init
Initialize Readeck for user Paula
Initialize Readeck for user Simone

Prepare an episode document. This will read all the bookmarks from all configured users and render a template:

$ episodix prepare E123.md --template episode.md.j2
Get bookmarks from user Paula
Get bookmarks from user Simone
Render and save template

After the document has been created, you can remove all the collected bookmarks:

$ episodix nuke
Nuke bookmarks from user 'Paula'
Nuke bookmarks from user 'Simone'

Templating

Episode documents are prepared using a Jinja2 template - see episode.md.j2 for an example.

The variable user_bookmarks contains information derived from Readeck per user as dictionary, e.g. user_bookmarks['Paula'].

Every dictionary contains raw Readeck information per label, e.g. user_bookmarks['Paula']['tooltipps'].

Readeck keys include information like:

Key	Description
href, url	URL
title	Page title
description	Longer page description
site	Short site URL
type, document_type	Document type (e.g. article)
lang	Language (e.g. en)
word_count	Number of words
authors	Document authors (if supplied)
reading_time	Reading time in minutes (e.g. 3)
labels	List of attached labels
created, updated	Timestamp of creation and last update

Note: You can see all the information when running the tool with the --debug / -d parameter.