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# Configurable PySpark Pipeline
_A configurable PySpark pipeline library._

## Getting Started
* Requirements:
* Python 3.5
* install the package using pip:

``` bash
$ pip install sparkml-pipe
```

## Project Organization
```
├── README.md <- The top-level README for developers using this project.
├── data <- Data for testing the library.
│
├── docs <- A default Sphinx project; see sphinx-doc.org for details
│
├── requirements.txt <- The requirements file for reproducing the analysis environment, e.g.
│ generated with `pip freeze > requirements.txt`
│
├── sparkmlpip <- Source code for use in this project.
│ ├── conf <- YAML config files for pyspark pipeline.
│ │
│ ├── pipeline <- pyspark model pipelines.
│ │
│ ├── stat <- pyspark stat pipelines.
│ │
│ ├── test <- test code.
│ │
│ └── utils <- util functions.
│
└── setup.py <- Metadata about your project for easy distribution.
```



## Contributing
### checkout the codebase
``` bash
$ git checkout develop
```
### Update the PyPI version
* Update sparkmlpipe/\_\_version\_\_.py if needed
* Upload to PyPI
``` bash
$ python setup.py sdist
$ pip install twine
// upload to Test PyPI
$ twine upload --repository-url https://test.pypi.org/legacy/ dist/*
// upload to PyPI
$ twine upload dist/*
```
### Installing development requirements
``` bash
$ pip install -r requirements.txt
```

Metadata

Release files for sparkml-pipe 0.2.5

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