udapi
Python framework for processing Universal Dependencies data
Decision gist · record as of 2026-08-14
Yes, if you work with Universal Dependencies treebanks or need to process CoNLL-U formatted linguistic data. The framework is actively maintained, has low install friction, and integrates well into NLP pipelines. The GPL-3.0-or-later license is suitable for research and open-source projects but requires review if used in proprietary software. No known vulnerabilities.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.9 or higher; optional ufal.udpipe parser requires separate installation for advanced parsing.
- Low friction installation via pip; active maintenance with recent commits and a stable release history since 2017.
- Requires Python 3.9 or higher.
License · maintenance · safety
GPL-3.0-or-later (copyleft) — GPL-3.0-or-later copyleft license: any derivative work or distribution must also be open-source under GPL-compatible terms. Suitable for research and open-source projects; check compatibility if integrating into proprietary software.
last release 2026-03-16 (151 days) · last repo commit 2026-06-26 · 58 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 248,173 downloads/mo, #8,673 on PyPI
Alternatives
Verify before relying
pip install udapi
import udapi
# Load and process UD data via the udapy command-line tool or programmatic API- Whether ufal.udpipe integration is required for core functionality or optional for advanced parsing features.
- Performance characteristics and scalability limits for large treebank datasets.
- Availability and completeness of API documentation beyond the GitHub repository.
What it is and what it does
Udapi is a Python framework designed for working with Universal Dependencies (UD) treebanks—standardized linguistic datasets that encode syntactic dependency structures for many languages. It provides tools to read, write, and manipulate UD data in CoNLL-U format, the standard interchange format for dependency trees. The framework is built on colorama and termcolor for terminal output and includes a command-line tool (udapy) for scripting common UD processing tasks.
Developers use Udapi to build NLP pipelines that analyze or transform syntactic structures, validate treebank data, or extract linguistic information from dependency trees. It's actively maintained, supports current Python versions, and integrates optionally with ufal.udpipe for parsing. The project is part of the broader UD ecosystem and is suitable for linguistic research, corpus annotation, and dependency-based NLP work.
Use it for
- Validate and clean Universal Dependencies treebank data before publication or use in training linguistic models.
- Extract syntactic patterns or linguistic features from UD-formatted corpora for linguistic analysis.
- Build custom NLP pipelines that read UD trees and transform or annotate them with additional linguistic information.
- Integrate UD parsing into larger language processing workflows using the optional ufal.udpipe parser.
- Automate batch processing of UD data across multiple treebanks or languages via the udapy command-line interface.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you work with Universal Dependencies treebanks or need to process CoNLL-U formatted linguistic data.
The framework is actively maintained, has low install friction, and integrates well into NLP pipelines. The GPL-3.0-or-later license is suitable for research and open-source projects but requires review if used in proprietary software. No known vulnerabilities.
Install
udapi on PyPI
Before you install
Low friction installation via pip; active maintenance with recent commits and a stable release history since 2017. Requires Python 3.9 or higher.
Requires Python 3.9 or higher; optional ufal.udpipe parser requires separate installation for advanced parsing.
License in practice
GPL-3.0-or-later copyleft license: any derivative work or distribution must also be open-source under GPL-compatible terms. Suitable for research and open-source projects; check compatibility if integrating into proprietary software.
Quickstart
pip install udapi
import udapi
# Load and process UD data via the udapy command-line tool or programmatic APIVerify before relying
- Whether ufal.udpipe integration is required for core functionality or optional for advanced parsing features.
- Performance characteristics and scalability limits for large treebank datasets.
- Availability and completeness of API documentation beyond the GitHub repository.
Package facts
| License | GPL-3.0-or-later copyleft |
| Python support | Supports the current Python release >=3.9 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 2 packagescoloramatermcolor |
| Maintenance | Actively maintained 151 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 248,173 / month, #8,673 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Operating System :: OS IndependentProgramming Language :: Python :: 3 |
Evidence: udapi-0.5.2-py3-none-any.whl
Tags
Let your AI agent find packages like this
Example. Real query, live index.
You found this page by searching. An agent finds it by wishing: SkillFed indexes 14,416 PyPI packages by what they can do, searchable in plain language.
wish › “universal dependencies processing”
- udapiUdapi is a Python framework for reading, processing, and manipulating…
- ginzaGiNZA is a Japanese NLP library that performs tokenization,…
- conlluParses CoNLL-U formatted text (a standard NLP annotation format) into…
Give your agent the search over MCP, or paste the wish link into any chat.
More Linguistic packages
Detects and normalizes text encoding from unknown or ambiguous sources, supporting all IANA character sets that Python's core library provides codecs for, with the ability to register custom codecs.
tiktoken is a fast BPE tokenizer that converts text into token sequences compatible with OpenAI models, supporting multiple encoding schemes including o200k_base and model-specific encodings.
Install it if you work with OpenAI APIs or need to understand token boundaries in GPT-family models.
Detects character encoding and language in byte sequences with high accuracy, supporting 99 encodings and returning confidence scores, language tags, and MIME types.
Install it if you need to detect character encoding or language in byte data; the rewrite makes it substantially faster and more accurate than its predecessors.
Converts Unicode text to ASCII by transliterating non-ASCII characters into their closest ASCII equivalents, with no runtime dependencies.
However, if transliteration quality or ongoing maintenance matters, consider unidecode instead despite its GPL-only license.
Lark is a parsing library that builds abstract syntax trees from context-free grammars, supporting multiple parsing algorithms (Earley, LALR(1), CYK) with automatic line and column tracking.
Python bindings to the tree-sitter parsing library, enabling incremental parsing and syntax tree analysis for source code.
See also udtools · conllu · lemminflect · simplemma · ginza · nltk · treelite · stanza · english · ubai-client