spaCy/spacy/displacy/__init__.py
Ole Henrik Skogstrøm d16cb6bee6 Accept Span to displacy render (#2478) (closes #2477)
* Add Span to displacy render

* Fix span support, errors and add tests
2018-06-25 14:55:16 +02:00

138 lines
5.3 KiB
Python

# coding: utf8
from __future__ import unicode_literals
from .render import DependencyRenderer, EntityRenderer
from ..tokens import Doc, Span
from ..compat import b_to_str
from ..errors import Errors, Warnings, user_warning
from ..util import prints, is_in_jupyter
_html = {}
IS_JUPYTER = is_in_jupyter()
def render(docs, style='dep', page=False, minify=False, jupyter=IS_JUPYTER,
options={}, manual=False):
"""Render displaCy visualisation.
docs (list or Doc): Document(s) to visualise.
style (unicode): Visualisation style, 'dep' or 'ent'.
page (bool): Render markup as full HTML page.
minify (bool): Minify HTML markup.
jupyter (bool): Experimental, use Jupyter's `display()` to output markup.
options (dict): Visualiser-specific options, e.g. colors.
manual (bool): Don't parse `Doc` and instead expect a dict/list of dicts.
RETURNS (unicode): Rendered HTML markup.
"""
factories = {'dep': (DependencyRenderer, parse_deps),
'ent': (EntityRenderer, parse_ents)}
if style not in factories:
raise ValueError(Errors.E087.format(style=style))
if isinstance(docs, (Doc, Span, dict)):
docs = [docs]
docs = [obj if not isinstance(obj, Span) else obj.as_doc() for obj in docs]
if not all(isinstance(obj, (Doc, Span, dict)) for obj in docs):
raise ValueError(Errors.E096)
renderer, converter = factories[style]
renderer = renderer(options=options)
parsed = [converter(doc, options) for doc in docs] if not manual else docs
_html['parsed'] = renderer.render(parsed, page=page, minify=minify).strip()
html = _html['parsed']
if jupyter: # return HTML rendered by IPython display()
from IPython.core.display import display, HTML
return display(HTML(html))
return html
def serve(docs, style='dep', page=True, minify=False, options={}, manual=False,
port=5000):
"""Serve displaCy visualisation.
docs (list or Doc): Document(s) to visualise.
style (unicode): Visualisation style, 'dep' or 'ent'.
page (bool): Render markup as full HTML page.
minify (bool): Minify HTML markup.
options (dict): Visualiser-specific options, e.g. colors.
manual (bool): Don't parse `Doc` and instead expect a dict/list of dicts.
port (int): Port to serve visualisation.
"""
from wsgiref import simple_server
render(docs, style=style, page=page, minify=minify, options=options,
manual=manual)
httpd = simple_server.make_server('0.0.0.0', port, app)
prints("Using the '{}' visualizer".format(style),
title="Serving on port {}...".format(port))
try:
httpd.serve_forever()
except KeyboardInterrupt:
prints("Shutting down server on port {}.".format(port))
finally:
httpd.server_close()
def app(environ, start_response):
# headers and status need to be bytes in Python 2, see #1227
headers = [(b_to_str(b'Content-type'),
b_to_str(b'text/html; charset=utf-8'))]
start_response(b_to_str(b'200 OK'), headers)
res = _html['parsed'].encode(encoding='utf-8')
return [res]
def parse_deps(orig_doc, options={}):
"""Generate dependency parse in {'words': [], 'arcs': []} format.
doc (Doc): Document do parse.
RETURNS (dict): Generated dependency parse keyed by words and arcs.
"""
doc = Doc(orig_doc.vocab).from_bytes(orig_doc.to_bytes())
if not doc.is_parsed:
user_warning(Warnings.W005)
if options.get('collapse_phrases', False):
for np in list(doc.noun_chunks):
np.merge(tag=np.root.tag_, lemma=np.root.lemma_,
ent_type=np.root.ent_type_)
if options.get('collapse_punct', True):
spans = []
for word in doc[:-1]:
if word.is_punct or not word.nbor(1).is_punct:
continue
start = word.i
end = word.i + 1
while end < len(doc) and doc[end].is_punct:
end += 1
span = doc[start:end]
spans.append((span.start_char, span.end_char, word.tag_,
word.lemma_, word.ent_type_))
for start, end, tag, lemma, ent_type in spans:
doc.merge(start, end, tag=tag, lemma=lemma, ent_type=ent_type)
if options.get('fine_grained'):
words = [{'text': w.text, 'tag': w.tag_} for w in doc]
else:
words = [{'text': w.text, 'tag': w.pos_} for w in doc]
arcs = []
for word in doc:
if word.i < word.head.i:
arcs.append({'start': word.i, 'end': word.head.i,
'label': word.dep_, 'dir': 'left'})
elif word.i > word.head.i:
arcs.append({'start': word.head.i, 'end': word.i,
'label': word.dep_, 'dir': 'right'})
return {'words': words, 'arcs': arcs}
def parse_ents(doc, options={}):
"""Generate named entities in [{start: i, end: i, label: 'label'}] format.
doc (Doc): Document do parse.
RETURNS (dict): Generated entities keyed by text (original text) and ents.
"""
ents = [{'start': ent.start_char, 'end': ent.end_char, 'label': ent.label_}
for ent in doc.ents]
if not ents:
user_warning(Warnings.W006)
title = (doc.user_data.get('title', None)
if hasattr(doc, 'user_data') else None)
return {'text': doc.text, 'ents': ents, 'title': title}