Vowpal Wabbit Python Wrapper

Vowpal Wabbit is a fast machine learning library for online learning.

Installation

From PyPI:

$ pip install vowpalwabbit

From remote repo:

$ pip install -e git+https://github.com/JohnLangford/vowpal_wabbit/python

From local repo:

$ cd python
$ python setup.py install

or

$ cd python
$ pip install -e .

Usage

You can use the python wrapper directly like this:

>>> from vowpalwabbit import 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:

>>> 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:

$ 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.