Code

https://github.com/mozilla/spicedham/

Issues

https://github.com/mozilla/spicedham/issues

License

Mozilla Public License Version 2.0; See LICENSE

Contributors

See AUTHORS.rst

Run:

$ pip install spicedham

Run:

# Get the code
$ git clone https://github.com/mozilla/spicedham

# Create a virtualenvironment
$ virtualenv ../venv
$ source ../venv/bin/activate
# Install dependencies
$ pip install -r requirements.txt
# Install the code
$ pip install -e .

Run:

$ nosetests

See docs/intsallation.rst.

The API for spicedham is simple. There are three steps you need to do to classify spam:

1. Instantiate a SpicedHam object:

   from spicedham import SpicedHam
   spicedham = SpicedHam()

   Optionally you can pass dictionary of configuration values like so:

   config = {
       'backend': 'SqlAlchemyWrapper', # The class name of your backend
       'engine': 'sqlite:///:memory:', # Needed by SqlAlchemyWrapper
       'tokenizer': 'SplitTokenizer',  # The class name of your tokenizer
   }
   spicedham = SpicecHam(config)

2. Train on data. The arguments are:

   • A string message which can be split up by your chosen tokenizer.
   • A boolean indicating whether classifiers should match the message

   spicedham.train('I love Firefox!', False)
   spicedham.train('SPAMMY NONSENSE AND HATE SPEECH!', True)

3. Classify some data. chance_matched is a probability that the message was what you're searching for and will be between 0 and 1 (inclusive).

   chance_matched = spicedham.classify('maybe I'm spam or maybe not')