Metadata-Version: 2.1
Name: sugardata
Version: 0.0.3
Summary: Generates synthetic datasets tailored for transformer-based models
Home-page: https://github.com/okanyenigun/sugardata
Author: Okan Yenigün
Author-email: okanyenigun@gmail.com
License: MIT
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Information Technology
Classifier: Intended Audience :: Education
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Topic :: Software Development :: Documentation
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Operating System :: OS Independent
Requires-Python: >=3.7
Description-Content-Type: text/markdown

# sugardata

`sugardata` is a Python package that helps you **generate synthetic datasets for NLP tasks**, enabling experimentation, prototyping, and training when labeled data is limited or unavailable.

# Installation

You can install **sugardata** via pip:

```bash
pip install sugardata
```

# Quick Start

`sugardata` supports multiple NLP tasks out of the box.

## Task 1: Sentiment Analysis

```python

import sugardata as su

results = su.generate_sentiments(concept="online shopping", n_samples=100)

```

## Task 2: Aspect-Based Sentiment Analysis (ABSA)

```python

import sugardata as su

results = su.generate_aspect_sentiments(concept="smartphones", aspects=["battery life", "camera", "price"], n_samples=100)

```

To learn more about configuration options, advanced parameters, and integration tips, please visit tutorials.
