urduhack

What it is and what it does

Urduhack is a NLP library tailored for the Urdu language, offering a pipeline-based approach to common text processing tasks. It wraps TensorFlow models for part-of-speech tagging and named entity recognition, alongside utilities for normalization, preprocessing, and tokenization. The library is designed to lower the barrier to entry for academic researchers, NLP beginners, and developers building production applications with Urdu text.

The package depends on tf2crf, tensorflow-datasets, Click, and regex. It ships as a pure Python wheel with low install friction. However, the project is dormant—no releases since 2020 and commits only through early 2024—meaning you should expect no active maintenance, bug fixes, or compatibility updates for newer Python or TensorFlow versions.

Use it for:

• Extract part-of-speech tags and named entities from Urdu text documents for linguistic analysis or information extraction tasks.
• Preprocess and normalize Urdu text at scale before feeding it into downstream machine learning models.
• Build a rapid prototype of an Urdu NLP application using pre-trained models without implementing tokenization and tagging from scratch.
• Conduct academic research on Urdu language processing with production-quality code structure and pre-built datasets.
• Tokenize Urdu sentences and words for text analysis, search indexing, or language study applications.

Worth the install?

AI-flagged interpretation of the facts on this page — verify before relying

Urduhack provides NLP preprocessing, tokenization, part-of-speech tagging, and named entity recognition for Urdu text, built on TensorFlow and designed to work with Urdu language datasets.

Yes, if you are working specifically with Urdu text and can tolerate dormant maintenance. The library offers genuine value for NLP tasks on Urdu data and has low install friction. However, verify that its TensorFlow dependencies and pre-trained models work in your environment—no active maintenance means you may need to patch compatibility issues yourself or pin older dependency versions. Not suitable if you need ongoing support or expect regular updates.

Install

urduhack on PyPI

pip install urduhack

uv add urduhack

poetry add urduhack

Installing urduhack

Before you install

Low install friction with a pure-wheel distribution. Maintenance is dormant—the last release was in 2020 and the last commit in January 2024—so expect no active bug fixes or updates, though the repository remains open.

License in practice

MIT License permits commercial and private use with minimal restrictions, making it safe to adopt from a licensing standpoint.

Quickstart

pip install urduhack[tf]

import urduhack

urduhack.download()
nlp = urduhack.Pipeline()
doc = nlp("your urdu text here")
for sentence in doc.sentences:
    for token in sentence.tokens:
        print(token.text, token.ner)

Requires TensorFlow (cpu or gpu variant) and model download via urduhack.download() before first use.

Verify before relying

• Whether TensorFlow dependency versions are compatible with Python 3.8+ environments
• Current status of pre-trained models and whether they remain downloadable and functional
• Compatibility of tf2crf and tensorflow-datasets with recent TensorFlow releases

Package facts

Evidence: urduhack-1.1.1-py3-none-any.whl

Keywords: urdu, machine, learning, text, pre-processing, tensorflow, nlp

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