{"categories":[{"label":"Linguistic","url":"https://skillfed.io/packages/category/text-processing-linguistic/2"}],"enrichment":{"capability":"Parses CoNLL-U formatted text (a standard NLP annotation format) into nested Python dictionaries with full type support, enabling programmatic access to linguistic dependency structures.","skillfed_tags":["nlp","parsing","linguistics"],"use_cases":["Parse output from dependency parsers (like spaCy or UDPipe) to extract and analyze syntactic relationships in text.","Filter linguistic annotations by part-of-speech, morphological features, or dependency relations for corpus analysis.","Modify or augment CoNLL-U annotations programmatically and write the results back to file.","Process large annotated corpora incrementally without loading entire files into memory.","Build NLP pipelines that consume Universal Dependencies formatted data as intermediate representations."],"what_it_does":"conllu is a lightweight parser that converts CoNLL-U formatted text\u2014a standard annotation format used in natural language processing and linguistic research\u2014into Python data structures. CoNLL-U is the output format of many NLP pipelines and dependency parsers, encoding tokens with their linguistic properties (part-of-speech tags, lemmas, morphological features, syntactic dependencies). The parser converts this text into nested dictionaries and TokenList objects that you can query, filter, and manipulate programmatically.\n\nThe package has zero runtime dependencies and is designed for simplicity: it's about 300 lines of code with full type hints for IDE autocompletion. It supports both one-shot parsing of entire files and incremental parsing via generators for memory efficiency on large datasets. You can filter tokens by field values (including nested features), modify parsed structures, and serialize them back to CoNLL-U format.","worth_installing":"Yes. Zero dependencies, active maintenance, no known vulnerabilities, and MIT licensing make it a safe, lightweight choice. Install it if you work with CoNLL-U data from NLP tools or linguistic corpora. The only gotcha is the Python 3.8+ requirement; if you're on an older version, pin to conllu==4.5.3 or earlier."},"id":"conllu","links":{"html":"https://skillfed.io/packages/conllu","md":"https://skillfed.io/packages/conllu.md","pypi":"https://pypi.org/project/conllu/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2024-10-13","license_spdx":null,"license_treatment":"unclear","name":"conllu","python_support":"supports_current","summary":"CoNLL-U Parser parses a CoNLL-U formatted string into a nested python dictionary"},"popularity":{"monthly_downloads":405897,"position":6898,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"6.0.0"}