Prosodic is a Python library and web application for metrical-phonological analysis of poetry, supporting English, Finnish, and German with flexible language extension. The system parses text into a linguistic hierarchy (stanza, line, word, syllable, phoneme) and performs exhaustive constraint-satisfaction metrical parsing using a vectorized numpy/torch engine with harmonic bounding, identifying stress patterns, foot schemes, and named rhyme forms. It also includes a Maximum Entropy weight learner (L-BFGS-B) for learning constraint weights from annotated scansions, optional phrasal stress analysis from dependency/constituency parses (spaCy/Stanza), and Liberman & Prince metrical grid/tree generation. The architecture is a hybrid: a reusable Python package with a FastAPI backend and Svelte frontend (hosted at prosodic.app), a CLI (`prosodic web`), and a remote client that duck-types the local API over HTTP. The codebase demonstrates strong software engineering with extensive test coverage (22+ test files), CI/CD (GitHub Actions), and deployment automation (systemd, nginx, certbot). Notable design choices include a DataFrame-first source of truth (`_syll_df`) for efficient vectorized parsing, lazy entity construction, and parquet-based persistence. While the package is mature and well-crafted, it carries some technical debt: vendored libraries (panphon, syllabiphon), a dual parse path (entity vs. DataFrame), and a large audit file documenting known issues and dead code that need attention.
This is the largest structured Chinese classical poetry dataset on GitHub, containing ~55,000 Tang poems, ~260,000 Song poems, ~21,000 Song ci (lyric poetry), and additional classical texts (Four Books and Five Classics, Book of Songs, Chu Ci, Yuan opera, etc.). The data is distributed as JSON files organized by dynasty and genre, with each poem containing author, title, and paragraph fields. The repository serves as a foundational dataset for Chinese NLP, digital humanities, and cultural heritage projects. The codebase is minimal — essentially a data repository with a JSON validation test (test_poetry.py), a simple data loader (loader/data_loader.py), and a web scraper for Song ci (宋词/UpdateCi.py). The data itself is the product of web scraping from sources like ctext.org and other online repositories, with manual curation and error correction over time. The repository includes an 'error' directory containing records with data quality issues (corrupted characters, missing content, etc.), which demonstrates transparency about data limitations. The data loader provides a basic abstraction for extracting poem bodies across different datasets, but the overall engineering is straightforward. The value lies entirely in the data breadth and accessibility — no complex transformations, feature engineering, or analytical pipelines are present. The repository is widely used (52K+ stars) as a reference dataset for Chinese poetry generation, analysis, and educational applications.