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Fixes #45 |
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fedireads | ||
.env.example | ||
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CODE_OF_CONDUCT.md | ||
init_db.py | ||
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manage.py | ||
README.md | ||
rebuilddb.sh | ||
requirements.txt |
Book Wyrm (aka FediReads)
Social reading and reviewing, decentralized with ActivityPub
Contents
The overall idea
What it is and isn't
FediReads is meant to be a platform for social reading; specifically, for tracking what you're reading and sharing your updates with friends, and reviewing and commenting on books. It isn't meant primarily for cataloguing or as a datasource for books, but it may incidentally act in that way even when that isn't the focus of the software. For example, listing books you've read can be a way for you to catalog their personal reading, even though the feature is designed with the intent of sharing updates on what you've read.
The role of federation
FediReads is built on ActivityPub and uses that standard to inter-operate between different instances of FediReads run on different servers by different people, and to inter-operate with other ActivityPub compliant services, like Mastodon and Pixelfed. This means, for example, that your friend on mastodon can read and comment on your Fedireads book review.
Federation also makes it possible to have small, self-determining communities, as opposed to a monolithic service like you find on GoodReads or Twitter. An instance could be focused on a particular type of literature, just for use by people who are in a book club together, or anything else that brings them together. Each community can choose what other instances they want to federate with, and moderate and run their community autonomously. Check out https://runyourown.social/ to get a sense of the philosophy I'm working from for how social networks out to be.
Features
This project is still in its very early stages, but these are the higher-level features it should have:
- Book reviews
- Post and comment on reviews
- Find reviews of a book across connected FediReads instances
- Differentiate local and federated reviews and rating
- Track reading activity
- Store "shelves" that list books a user wants to read/is reading/has read
- Allow users to create their own shelves
- Update followers about user activity (optionally, and with granular privacy controls)
- Allow users to comment on reading activity (optionally, and with granular privacy controls)
- Federation with ActivityPub
- Identify shared books across instances
- Follow and interact across FediReads instances
- Inter-operate with non-FediReads ActivityPub services
- Granular privacy controls
- Local-only, followers-only, and public posting
- Option for users to manually approve followers
- Allow blocking and flagging for moderation
- Control over which instances you want to federate with
But this isn't a set in stone, unchangeable list, so if you have ideas about how this could be tweaked, changed, or improved, please open an issue and start a conversation about it.
Setting up the developer environment
You will need postgres installed and running on your computer.
python3 -m venv venv
source venv/bin/activate
pip install -r requirements.txt
createdb fedireads
Create the psql user in psql fedireads
:
CREATE ROLE fedireads WITH LOGIN PASSWORD 'fedireads';
GRANT ALL PRIVILEGES ON DATABASE fedireads TO fedireads;
Initialize the database (or, more specifically, delete the existing database, run migrations, and start fresh):
./rebuilddb.sh
This creates two users, mouse
with password password123
and rat
with password ratword
.
And go to the app at localhost:8000
For most testing, you'll want to use ngrok. Remember to set the DOMAIN in .env
to your ngrok domain.
Project structure
All the url routing is in fedireads/urls.py
. This includes the application views (your home page, user page, book page, etc), application endpoints (things that happen when you click buttons), and federation api endpoints (inboxes, outboxes, webfinger, etc).
The application views and actions are in fedireads/views.py
. The internal actions call api handlers which deal with federating content. Outgoing messages (any action done by a user that is federated out), as well as outboxes, live in fedireads/outgoing.py
, and all handlers for incoming messages, as well as inboxes and webfinger, live in fedireads/incoming.py
. Connection to openlibrary.org to get book data is handled in fedireads/connectors/openlibrary.py
. ActivityPub serialization is handled in the activitypub/
directory.
There's some organization/refactoring work to be done to clarify the separation of concerns and keep the code readable and well organized.
The UI is all django templates because that is the default. You can replace it with a complex javascript framework over my dead body mild objections.
Book data
The application is set up to get book data from arbitary outside source -- right now, it's only able to connect to OpenLibrary, but other connectors could be written. By default, a book is non-canonical copy of an OpenLibrary book, and will be updated with OpenLibrary if the data there changes. However, theoretically a book can edited and decoupled from its original data source, or added locally with no external data source.
There are three structures for storing book data:
Book
, a general high-level concept that could mean either aWork
or anEdition
Work
, a theoretical umbrella concept of a book that encompasses every edition of the book, andEdition
, a concreet, actually published version of a book
Usually, a review is tied to a Work
, because your review is relevent regardless of whether you're talking about the hardcover, the paperback, the reprint or whatever. But in some cases a review is specfic to an Edition
-- if you're reviewing a particular translation, the voice acting on an audiobook, or whatever.
Contributing
There are many ways you can contribute to this project! You are welcome and encouraged to create or contribute a github issue to report a bug, request a feature, make a usability suggestion, or express a nevulous desire.
If you'd like to add to the codebase, the issues are a good place to start to get a sense of what needs to be done -- feel free to ask questions and tag @mouse-reeve. This isn't a formalized process at this point.