#!/usr/bin/env python # coding: utf-8 """This example contains several snippets of methods that can be set via custom Doc, Token or Span attributes in spaCy v2.0. Attribute methods act like they're "bound" to the object and are partially applied – i.e. the object they're called on is passed in as the first argument. * Custom pipeline components: https://alpha.spacy.io//usage/processing-pipelines#custom-components Compatible with: spaCy 2.0.0a17+ """ from __future__ import unicode_literals, print_function import plac from spacy.lang.en import English from spacy.tokens import Doc, Span from spacy import displacy from pathlib import Path @plac.annotations( output_dir=("Output directory for saved HTML", "positional", None, Path)) def main(output_dir=None): nlp = English() # start off with blank English class Doc.set_extension('overlap', method=overlap_tokens) doc1 = nlp(u"Peach emoji is where it has always been.") doc2 = nlp(u"Peach is the superior emoji.") print("Text 1:", doc1.text) print("Text 2:", doc2.text) print("Overlapping tokens:", doc1._.overlap(doc2)) Doc.set_extension('to_html', method=to_html) doc = nlp(u"This is a sentence about Apple.") # add entity manually for demo purposes, to make it work without a model doc.ents = [Span(doc, 5, 6, label=nlp.vocab.strings['ORG'])] print("Text:", doc.text) doc._.to_html(output=output_dir, style='ent') def to_html(doc, output='/tmp', style='dep'): """Doc method extension for saving the current state as a displaCy visualization. """ # generate filename from first six non-punct tokens file_name = '-'.join([w.text for w in doc[:6] if not w.is_punct]) + '.html' html = displacy.render(doc, style=style, page=True) # render markup if output is not None: output_path = Path(output) if not output_path.exists(): output_path.mkdir() output_file = Path(output) / file_name output_file.open('w', encoding='utf-8').write(html) # save to file print('Saved HTML to {}'.format(output_file)) else: print(html) def overlap_tokens(doc, other_doc): """Get the tokens from the original Doc that are also in the comparison Doc. """ overlap = [] other_tokens = [token.text for token in other_doc] for token in doc: if token.text in other_tokens: overlap.append(token) return overlap if __name__ == '__main__': plac.call(main) # Expected output: # Text 1: Peach emoji is where it has always been. # Text 2: Peach is the superior emoji. # Overlapping tokens: [Peach, emoji, is, .]