Metadata-Version: 2.1
Name: pada
Version: 0.1.0
Summary: a ligthweight feature manage framework
Home-page: https://github.com/eleveyuan/pada
Author: Eleve Yuan
Author-email: eleveyuane@gmail.com
License: MIT license
Keywords: pada
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Requires-Python: >=3.7.0
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: cookiecutter
Requires-Dist: Click (>=6.0)
Requires-Dist: funcy (>=1.14)
Requires-Dist: scikit-learn (>=0.20)
Requires-Dist: sklearn-pandas (~=1.0)
Requires-Dist: stacklog
Requires-Dist: pandas (~=1.0)
Requires-Dist: numpy
Provides-Extra: all
Requires-Dist: category-encoders (>=2.2.2) ; extra == 'all'
Requires-Dist: feature-engine (~=1.0) ; extra == 'all'
Requires-Dist: featuretools-sklearn-transformer (>=0.1) ; extra == 'all'
Requires-Dist: skits (>=0.1.2) ; extra == 'all'
Requires-Dist: tsfresh (>=0.16) ; extra == 'all'
Provides-Extra: category_encoders
Requires-Dist: category-encoders (>=2.2.2) ; extra == 'category_encoders'
Provides-Extra: feature_engine
Requires-Dist: feature-engine (~=1.0) ; extra == 'feature_engine'
Provides-Extra: featuretools
Requires-Dist: featuretools-sklearn-transformer (>=0.1) ; extra == 'featuretools'
Provides-Extra: skits
Requires-Dist: skits (>=0.1.2) ; extra == 'skits'
Provides-Extra: tsfresh
Requires-Dist: tsfresh (>=0.16) ; extra == 'tsfresh'

# pada

pada is an onomatopoeia, like the sound we make when building blocks.

a ligthweight feature manage framework

1. load_data: load data
2. feature definition: metadata, input data, transform
3. assemble: construct


## pada command line generates the project directory

```
project
|---definition
|  |-feats_def.py
|---load_data.py
|---main.py
|---url.py    
```

## base introduce

### load_data.py
define a function named *data()*, return your data which is a pd.DataFrame

### definition
you should define your feature in this directory

### url.py
find your feature definition by *url()* function

### main.py
run your feature engeering by *run()* function



# History

## 0.1.0 (2022-03-01)

* First release on PyPI

