Installing sklearn-pmml-model

The easiest way to install sklearn-pmml-model is with pip. Alternatively, you can install it from source.

pip

Pre-built binary packages (wheels) are provided for Linux, MacOS, and Windows through PyPI. To install using pip, simply run:

$ pip install sklearn-pmml-model

More details on using pip can be found here.

From source

If you want to build sklearn-pmml-model from source, you will need a C/C++ compiler to compile extensions.

Linux

On Linux, you need to install gcc, which in most cases is available via your distribution’s packaging system. Please follow your distribution’s instructions on how to install packages.

MacOS

On MacOS, you need to install clang, which is available from the Command Line Tools package. Open a terminal and execute:

$ xcode-select --install

Alternatively, you can download it from the Apple Developers page. Log in with your Apple ID, then search and download the Command Line Tools for Xcode package.

Windows

On Windows, the compiler you need depends on the Python version you are using. See this guide to determine which Microsoft Visual C++ compiler to use with a specific Python version.

Installing

Grab a local copy of the source:

$ git clone http://github.com/iamDecode/sklearn-pmml-model
$ cd sklearn-pmml-model

create a virtual environment and activate it:

$ python3 -m venv venv
$ source venv/bin/activate

and install the dependencies:

$ pip install -r requirements.txt

The final step is to build the Cython extensions (this part requires the C/C++ compiler):

$ python setup.py build_ext --inplace

Dependencies

The current minimum dependencies to run sklearn-pmml-model are:

• numpy 1.16 or later

• pandas

• scikit-learn

• scipy

• cached-property