LazyLibrarian
Follow authors and grab metadata for all your digital reading needs. It uses a combination of Goodreads, Librarything and optionally GoogleBooks as sources for author info and book info.
Developed outside the platforms our data source measures, so there is no activity history to score. This says nothing about the project — many unrated projects are actively maintained.
Activity data
Not available for this project. Our source collects commit history from GitHub only, and LazyLibrarian is developed elsewhere.
| Stars | not measured |
|---|---|
| Latest release | — |
| Repo updated | 27 Sept 2026 |
| Licence | GPL-3.0 |
| Built with | Python |
Is LazyLibrarian actively maintained?
We cannot measure this one. LazyLibrarian is developed outside the platforms our data source collects activity from, and its repository lives at gitlab.com — so there is no commit history or release cadence here to score.
Read that as missing data, not as a warning. Several of the best-maintained projects in this catalogue are unrated for exactly this reason. To judge it, open the repository and look at the date of the most recent commit yourself.
Note that LazyLibrarian depends on a third-party service to work fully. It is self-hosted, but not self-contained.
What LazyLibrarian actually does
LazyLibrarian is a Python-based automation tool that tracks your favourite authors and gathers metadata for digital reading materials. It integrates with external literature platforms such as Goodreads, LibraryThing, and Google Books to manage your reading lists and bibliographic data.
Best fit: Self-hosters looking for a dedicated automation utility to track author bibliographies and aggregate reading metadata from multiple external sources.
Worth knowing: The repository shows no recent release tags or commits, suggesting development may be stagnant or that you might need to run directly from the main branch. It occupies a niche space that heavily overlaps with broader, more actively maintained media organisation stacks.
Deployment notes
As a Python application, you will typically need to ensure a persistent storage volume for configuration and metadata, along with a reverse proxy if you require TLS termination. Dependencies are generally managed via pip within a virtual environment or containerised setup.
Links
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