mixin example(name)
  details
    summary
      h4= name
    block


+example("Load resources and process text")
  pre.language-python: code
    | from __future__ import unicode_literals, print_function
    | from spacy.en import English
    | nlp = English()
    | doc = nlp('Hello, world. Here are two sentences.')

+example("Get tokens and sentences")
  pre.language-python: code
    | token = doc[0]
    | sentence = doc.sents[0]
    | assert token[0] is sentence[0]

+example("Use integer IDs for any string")
  pre.language-python: code
    | hello_id = nlp.vocab.strings['Hello']
    | hello_str = nlp.vocab.strings[hello_id]
    | 
    | assert token.orth == hello_id == 52
    | assert token.orth_ == hello_str == 'Hello'

+example("Get and set string views and flags")
  pre.language-python: code
    | assert token.shape_ == 'Xxxx'
    | for lexeme in nlp.vocab:
    |     if lexeme.is_alpha:
    |         lexeme.shape_ = 'W'
    |     elif lexeme.is_digit:
    |         lexeme.shape_ = 'D'
    |     elif lexeme.is_punct:
    |         lexeme.shape_ = 'P'
    |     else:
    |         lexeme.shape_ = 'M'
    | assert token.shape_ == 'W'

+example("Export to numpy arrays")
  pre.language-python: code
    | from spacy.en.attrs import ORTH, LIKE_URL, IS_OOV
    | 
    | attr_ids = [ORTH, LIKE_URL, IS_OOV]
    | doc_array = doc.to_array(attr_ids)
    | assert doc_array.shape == (len(doc), len(attrs)
    | assert doc[0].orth == doc_array[0, 0]
    | assert doc[1].orth == doc_array[1, 0]
    | assert doc[0].like_url == doc_array[0, 1]
    | assert doc_array[, 1] == [t.like_url for t in doc]

+example("Word vectors")
  pre.language-python: code
    | doc = nlp("Apples and oranges are similar. Boots and hippos aren't.")
    | 
    | apples = doc[0]
    | oranges = doc[1]
    | boots = doc[6]
    | hippos = doc[8]
    | 
    | assert apples.similarity(oranges) > boots.similarity(hippos)


+example("Part-of-speech tags")
  pre.language-python: code
    | doc[0].pos
    | doc[0].tag

+example("Syntactic dependencies")
  pre.language-python: code
    | for head in tokens:
    |     for child in head.lefts:
    |         assert child.head is head
    |     for child in head.rights:
    |         assert child.head is head
    | sent = nlp('The four wheels on the bus turned quickly.')
    | wheels = sent[2]
    | bus = sent[5]
    | assert len(list(wheels.lefts)) == 2
    | assert len(list(wheels.rights)) == 1
    | assert len(list(wheels.children)) == 3
    | assert len(list(bus.lefts)) == 1
    | assert len(list(bus.rights)) == 0
    | assert len(list(bus.children)) == 1
    | 
    | assert len(list(wheels.subtree)) == 6 

+example("Named entities")
  pre.language-python: code
    | doc.ents
    | token.ent_type
    | token.ent_iob

+example("Define custom NER rules")
  pre.language-python: code
    | nlp.matcher

+example("Calculate inline mark-up on original string")
  pre.language-python: code
    | token.string
    | token.spacy
    | token.whitespace_

+example("Efficient binary serialization")
  pre.language-python: code
    |