A small test on spaCy Natural Language handling

spaCy-demo.py

import spacy
from spacy import displacy
from pathlib import Path

# spaCy API Documentation : https://spacy.io/api

nlp = spacy.load("en_core_web_sm")
doc = nlp(u"Next friday at 1 PM, I will have lunch in Paris with my friend Chris, the one who has a red hair cat.")
options={"collapse_punct": True, "word_spacing":10, "distance":100}

# SVG output for token relations
svg = displacy.render(doc, style="dep", options=options)
output_path = Path("sentence.svg")
output_path.open("w", encoding="utf-8").write(svg)

# HTML output for token entities (cf page option)
html = displacy.render(doc, style="ent", options=options, page=True)
output_path = Path("sentence.html")
output_path.open("w", encoding="utf-8").write(html)

print("Tokens:")
for token in doc:
    print("\t", token.pos_, token.text)

print("Entities", [(ent.text, ent.label_) for ent in doc.ents])