This package contains a library for extracting contact information from HTML pages.
- American contact information extraction
- Netherlands open hours extraction
- Ireland open hours extraction
- Ireland contact address extraction
Clone the repository, then install package requirements (package requires lxml, scikit-learn and python-wapiti):
$ pip install -r requirements.txtthen install package itself:
$ python setup.py install>>> import wapiti
>>> from webstruct.wapiti import WapitiChunker
>>> from sklearn.externals import joblibLoad trained model ('wfe.joblib' and 'model.wapiti' files must exists):
>>> feature_encoder = joblib.load('wfe.joblib')
>>> wapiti_model = wapiti.Model(model='model.wapiti')
>>> ner = WapitiChunker(wapiti_model, feature_encoder)Get a HTML page somewhere:
>>> import requests
>>> page = requests.get(some_url)and extract information:
>>> for text, label in ner.transform(page.text, page.encoding):
... if label != 'O':
... print("%6s %s" % (label, text))
TEL 800-4-Altman ( 425-8626 )
EMAIL sales@altmanlighting.com
ORG Altman Lighting Co. Inc.
STREET 57 Alexander Street
CITY Yonkers
STATE NY
ZIPCODE 10701
TEL 1-800-4-ALTMAN ( 425-8626 )Model should be trained before usage. See '../notebooks/train-token-model.ipynb' IPython notebook for an example.
Make sure nose is installed, then run runtests.sh script.