anchor.diff:      prefix_re = re.compile(r'''[\[\(&quot;']''')
       suffix_re = re.compile(r'''[\]\)&quot;']''')
       infix_re = re.compile(r'''[-~]''')
  +    simple_url_re = re.compile(r'''^https?://''')
       def create_tokenizer(nlp):
  -        return Tokenizer(nlp.vocab, rules={},
  +        return Tokenizer(nlp.vocab,
  +                rules={},
                   prefix_search=prefix_re.search,
                   suffix_search=suffix_re.search,
  -                infix_finditer=infix_re.finditer)
  +                infix_finditer=infix_re.finditer,
  +                token_match=simple_url_re.match
  +                )
   
       nlp = spacy.load('en', create_make_doc=create_tokenizer)
   
  
positive.code:     +item
          |  A function #[code infixes_finditer], to handle non-whitespace
          |  separators, such as hyphens etc.
  
  p
      |  You shouldn't usually need to create a #[code Tokenizer] subclass.
  
negative.code: 
  p
      |  Let's imagine you wanted to create a tokenizer for a new language. There
      |  are five things you would need to define:
  
  +list("numbers")
      +item
  