Urduhack: A Python NLP library for the Urdu language

Urduhack is an NLP library for the Urdu language. It comes with a lot of battery included features to help you process Urdu data in the easiest way possible.

Our Goal

• Academic users Easier experimentation to prove their hypothesis without coding from scratch.
• NLP beginners Learn how to build an NLP project with production-level code quality.
• NLP developers Build a production-level application within minutes.

🔥 Features Support

• [x] Normalization
• [x] Tokenization
• [x] Preprocessing
• [x] Pipeline Module
• [x] Models
  • [x] Pos tagger
  • [ ] Sentimental analysis
  • [ ] Sentence classification
  • [ ] Documents classification
  • [ ] Name entity recognition
  • [ ] Image to text
  • [ ] Speech to text
• [x] Datasets loader

🛠 Installation

Urduhack officially supports Python 3.6–3.7 and runs great on PyPy.

Installing with tensorflow cpu version.

$ pip install urduhack[tf]

Installing with tensorflow gpu version.

$ pip install urduhack[tf-gpu]

Usage

import urduhack

# Downloading models
urduhack.download()

nlp = urduhack.Pipeline()
text = ""
doc = nlp(text)

for sentence in doc.sentences:
    print(sentence.text)
    for word in sentence.words:
        print(word)

🔗 Documentation

Fantastic documentation is available at https://urduhack.readthedocs.io/

How to Contribute

1. Check for open issues or open a fresh issue to start a discussion
   around a feature idea or a bug. There is a Contributor Friendly
   tag for issues that should be ideal for people who are not very
   familiar with the codebase yet.
2. Write a test which shows that the bug was fixed or that the feature
   works as expected.
3. Send a pull request and bug the maintainer until it gets merged and
   published. :)

👍 Contributors

Special thanks to everyone who contributed to getting the UrduHack to the current state.