contractions · PyPI
pypi.org › project › contractionsNov 15, 2021 · Download the file for your platform. If you're not sure which to choose, learn more about installing packages. Files for contractions, version 0.0.58. Filename, size. File type. Python version. Upload date. Hashes. Filename, size contractions-0.0.58.tar.gz (7.0 kB)
contractions · PyPI
https://pypi.org/project/contractions15.11.2021 · Dec 25, 2016. Download files. Download the file for your platform. If you're not sure which to choose, learn more about installing packages. Files for contractions, version 0.0.58. Filename, size. File type. Python version. Upload date.
nlp - Expanding English language contractions in Python ...
stackoverflow.com › questions › 19790188Aug 23, 2018 · def expand_contractions(text, contraction_mapping=CONTRACTION_MAP): # contraction_mapping is a dictionary of words having the compact form contractions_pattern = re.compile('({})'.format('|'.join(contraction_mapping.keys())),flags=re.IGNORECASE|re.DOTALL) def expand_match(contraction): match = contraction.group(0) first_char = match[0] expanded_contraction = contraction_mapping.get(match) \ if contraction_mapping.get(match) \ else contraction_mapping.get(match.lower()) expanded_contraction ...
pycontractions · PyPI
https://pypi.org/project/pycontractionsA Python library for expanding and creating common English contractions in text. This is very useful for dimensionality reduction by normalizing the text before generating word or character vectors. It performs contraction by simple replacement rules of the commonly used English contractions. Expansion, on the other hand, is not as simple as it ...
pycontractions · PyPI
pypi.org › project › pycontractions>>> from pycontractions import Contractions # Load your favorite semantic vector model in gensim keyedvectors format from disk >>> cont = Contractions ('GoogleNews-vectors-negative300.bin') # or specify any model from the gensim.downloader api >>> cont = Contractions (api_key = "glove-twitter-100") # or train or load your own keyedvectors model and pass it in >>> cont = Contractions (kv_model = mykvmodel) # optional, prevents loading on first expand_texts call >>> cont. load_models ()