I was going though the existing enhancement issues again and though it'd be nice to collect ideas for spaCy plugins and related projects. There are always people in the community who are looking for new things to build, so here's some inspiration ✨ For existing plugins and projects, check out the spaCy universe.

If you have questions about the projects I suggested,

I propose this topic as feature request, but it's also a documentation issue, as lack of details in user guide paragraph: https://rasa.com/docs/rasa/core/actions/#custom-actions.

What specified in paragraph Execute Actions in Other Code is obscure to me, and details at the API documentation link [Action Server](]https://rasa.com/docs/rasa/api/acti

The procedure for downloading the "en_vectors_web_lg" in spacy. by downloading and unzipping the file, and shifting it to the appropriate directory, as illustrated here is l

I'm trying to find verbs in a sentence with python for a NLP problem but the new function returns any match and not only the longest match (which pos_regex_matches does).

pattern = r'<VERB>*<ADV>*<VERB>+<PART>*'
verb_pattern = [{"POS": "VERB", "OP": "*"},{"POS": "ADV", "OP": "*"},{"POS": "VERB", "OP": "+"},{"POS": "PART", "OP": "*"}]

t_list_1 = textacy.extract.pos_regex_matches(text, pat

I wanted to use pytextrank together with spacy_udpipe to get keywords from texts in other languages (see https://stackoverflow.com/questions/59824405/spacy-udpipe-with-pytextrank-to-extract-keywords-from-non-english-text) but I realized, that udpipe-spacy somehow "overrides" the original spacy's pipeline so the noun_chunks are not generated (btw: the noun_chunks are created in lang/en/syntax_itera

Add the ability to answer weather forecast questions. DO NOT USE any API key because Dragonfire is an application that runs on the client's machine.

This is also on page 356.

from nltk.corpus import sentiwordnet as swn

good = swn.senti_synsets('good', 'n')[0]
Traceback (most recent call last):
File "", line 1, in
TypeError: 'filter' object is not subscriptable

Hi,
When we try to tokenize the following sentence:

If we use spacy

a = spacy.load('en_core_web_lg')

doc = a("I like the link http://www.idph.iowa.gov/ohds/oral-health-center/coordinator")

list(doc)

We got

[I, like, the, link, http://www.idph.iowa.gov, /, ohds, /, oral, -, health, -, center, /, coordinator]

But if we use the Spacy transformer tokenizer:

spaCy version: 2.1.9
spaCy-stanza version: 0.2.1

import stanza
from spacy_stanza import StanzaLanguage

stanza.download('ru')
snlp = stanza.Pipeline(lang="ru")
nlp = StanzaLanguage(snlp)
text = "Мама мыла раму"

Using stanza, i get this:

for sentence in snlp(text).senteces:
	for word in sentence.words:
		print(word.feats)

# Animacy=Anim|Case=Nom|Gender=