use-goodreads-export

Query Goodreads CSV exports using the included Python library to retrieve books, reading status, ratings, and library insights. Load your goodreads_library_export.csv file and use methods like get_read_books, get_tbr_books, get_books_by_shelf, and get_rating_distribution to analyze your library without writing custom parsing code.

A Goodreads CSV export contains your complete library metadata—titles, authors, shelves, ratings, and read dates. You can assemble custom shelves like read, to-read, currently-reading, retrieve series progress, extract author statistics, and generate reading distribution reports for personal analytics.

Use the built-in Python toolkit to filter your Goodreads export by shelf or status. Call get_read_books for completed titles, get_tbr_books for your to-read list, get_books_by_shelf for any custom shelf, or get_series_books to track series progress across your library.

No. The included goodreads_lib.py handles CSV parsing and data extraction. Import the GoodreadsLibrary interface, point it to your export file, and use pre-built methods to query books, ratings, authors, and shelves—no ad-hoc parsing required.

Yes. Extract author statistics with get_author_stats and rating distributions with get_rating_distribution. The toolkit provides read-only access with robust handling for missing data, letting you analyze patterns across your entire library.

Export your library from Goodreads as a CSV file named goodreads_library_export.csv and place it in your working directory. The toolkit parses standard Goodreads CSV exports containing title, author, shelves, ratings, and date-read columns.