Metadata-Version: 1.1
Name: vowpalwabbit
Version: 8.2.0
Summary: Vowpal Wabbit Python package
Home-page: https://github.com/JohnLangford/vowpal_wabbit
Author: Scott Graham
Author-email: scott.d.graham@gmail.com
License: BSD 3-Clause License
Description: Vowpal Wabbit Python Wrapper
        ============================
        
        Vowpal Wabbit is a fast machine learning library for online learning.
        
        Installation
        ------------
        
        From PyPI:
        
        .. code-block:: bash
        
            $ pip install vowpalwabbit
        
        From remote repo:
        
        .. code-block:: bash
        
            $ pip install -e git+https://github.com/JohnLangford/vowpal_wabbit/python
        
        From local repo:
        
        .. code-block:: bash
        
            $ cd python
            $ python setup.py install
        
        or
        
        .. code-block::
        
            $ cd python
            $ pip install -e .
        
        Usage
        -----
        
        You can use the python wrapper directly like this:
        
        .. code-block:: python
        
            >>> from vowpalwabbit impor pyvw
            >>> vw = pyvw.vw(quiet=True)
            >>> ex = vw.example('1 | a b c')
            >>> vw.learn(ex)
            >>> vw.predict(ex)
        
        Or you can use the scikit-learn interface like this:
        
        .. code-block:: python
        
            >>> import numpy as np
            >>> from sklearn import datasets
            >>> from sklearn.cross_validation import train_test_split
            >>> from vowpalwabbit.sklearn_vw import VWClassifier
            >>>
            >>> # generate some data
            >>> X, y = datasets.make_hastie_10_2(n_samples=10000, random_state=1)
            >>> X = X.astype(np.float32)
            >>>
            >>> # split train and test set
            >>> X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=256)
            >>>
            >>> # build model
            >>> model = VWClassifier()
            >>> model.fit(X_train, y_train)
            >>>
            >>> # evaluate model
            >>> model.score(X_train, y_train)
            >>> model.score(X_test, y_test))
        
        Development
        -----------
        
        Contributions are welcome for improving the python wrapper to Vowpal Wabbit.
        
        1. Check for open issues_ or create one to discuss a feature idea or bug.
        2. Fork the repo_ on Github and make changes to the master branch (or a new branch off of master).
        3. Write a test in the python/tests folder showing the bug was fixed or feature works (recommend using pytest_).
        4. Make sure package installs and tests pass under all supported environments (this calls tox_ automatically).
        5. Send the pull request.
        
        Tests can be run using setup.py:
        
        .. code-block:: bash
        
            $ python setup.py test
        
        
        Directory Structure:
        
        * python : this is where the c++ extension lives
        * python/vowpalwabbit : this is then main directory for python wrapper code and utilities
        * python/examples : example python code and jupyter notebooks to demonstrate functionality
        * python/tests : contains all tests for python code
        
        **Note:** neither examples nor tests directories are included in the distributed package, they are only for development purposes.
        
        .. _issues: https://github.com/JohnLangford/vowpal_wabbit/issues
        .. _repo: https://github.com/JohnLangford/vowpal_wabbit
        .. _pytest: http://pytest.org/latest/getting-started.html
        .. _tox: https://tox.readthedocs.io/en/latest/index.html
        
        
        
Keywords: fast machine learning online classification regression
Platform: any
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Classifier: License :: OSI Approved :: BSD License
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.7
