Metadata-Version: 2.4
Name: additory
Version: 0.1.1a1
Summary: Data augmentation library with Polars backend
Author-email: Additory Team <team@additory.dev>
License: MIT
Project-URL: Homepage, https://github.com/additory/additory
Project-URL: Documentation, https://additory.readthedocs.io
Project-URL: Repository, https://github.com/additory/additory
Keywords: data,augmentation,polars,dataframe,synthetic
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
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: Programming Language :: Python :: 3.12
Requires-Python: >=3.8
Description-Content-Type: text/markdown
Requires-Dist: polars>=0.20.0
Requires-Dist: pandas>=2.0.0
Requires-Dist: numpy>=1.24.0
Provides-Extra: dev
Requires-Dist: pytest>=7.0.0; extra == "dev"
Requires-Dist: pytest-cov>=4.0.0; extra == "dev"
Requires-Dist: black>=23.0.0; extra == "dev"
Requires-Dist: mypy>=1.0.0; extra == "dev"
Requires-Dist: hypothesis>=6.0.0; extra == "dev"
Provides-Extra: gpu
Requires-Dist: cudf>=23.0.0; extra == "gpu"

# Additory v0.1.1a1

Data augmentation library with Polars backend.

## Installation

```bash
pip install additory
```

## Quick Start

```python
import additory
import polars as pl

# Add columns from reference DataFrame
result = additory.add.to(df, reference_df, on='id', bring='price')

# Transform columns
result = additory.add.transform(df, mode='onehotencoding', columns=['category'])

# Filter data
result = additory.add.snapshot(df, where='age > 18')

# Generate synthetic data
result = additory.add.synthetic(df, rows=1000)

# Analyze data
result = additory.add.analyze(df, preset='quick')

# Evaluate expressions
result = additory.add.expressions(df, 'inbuilt:bmi')
```

## Features

- **Blazing Fast**: Built on Polars for maximum performance
- **Simple API**: Clean, intuitive API with `additory.add.function()` pattern
- **Flexible**: Works with Polars, pandas, and cuDF
- **Comprehensive**: 6 main functions covering all data augmentation needs
- **Well Tested**: 1,023 tests with 90% coverage

## Documentation

Visit [https://additory.dev](https://additory.dev) for full documentation.

## License

MIT
