mirror of
https://github.com/explosion/spaCy.git
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d307e9ca58
* restore load_nlp.VECTORS in the child process * add unit test * fix test * remove unnecessary import * add utf8 encoding * import unicode_literals
44 lines
1.2 KiB
Python
44 lines
1.2 KiB
Python
# coding: utf8
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from __future__ import unicode_literals
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from spacy.lang.en import English
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from spacy.tokens import Span, Doc
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class CustomPipe:
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name = "my_pipe"
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def __init__(self):
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Span.set_extension("my_ext", getter=self._get_my_ext)
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Doc.set_extension("my_ext", default=None)
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def __call__(self, doc):
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gathered_ext = []
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for sent in doc.sents:
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sent_ext = self._get_my_ext(sent)
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sent._.set("my_ext", sent_ext)
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gathered_ext.append(sent_ext)
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doc._.set("my_ext", "\n".join(gathered_ext))
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return doc
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@staticmethod
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def _get_my_ext(span):
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return str(span.end)
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def test_issue4903():
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# ensures that this runs correctly and doesn't hang or crash on Windows / macOS
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nlp = English()
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custom_component = CustomPipe()
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nlp.add_pipe(nlp.create_pipe("sentencizer"))
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nlp.add_pipe(custom_component, after="sentencizer")
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text = ["I like bananas.", "Do you like them?", "No, I prefer wasabi."]
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docs = list(nlp.pipe(text, n_process=2))
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assert docs[0].text == "I like bananas."
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assert docs[1].text == "Do you like them?"
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assert docs[2].text == "No, I prefer wasabi."
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