# coding: utf8 from __future__ import unicode_literals import spacy.language from spacy.language import Language, component from spacy.analysis import print_summary, validate_attrs from spacy.analysis import get_assigns_for_attr, get_requires_for_attr from spacy.compat import is_python2 from mock import Mock, ANY import pytest def test_component_decorator_function(): @component(name="test") def test_component(doc): """docstring""" return doc assert test_component.name == "test" if not is_python2: assert test_component.__doc__ == "docstring" assert test_component("foo") == "foo" def test_component_decorator_class(): @component(name="test") class TestComponent(object): """docstring1""" foo = "bar" def __call__(self, doc): """docstring2""" return doc def custom(self, x): """docstring3""" return x assert TestComponent.name == "test" assert TestComponent.foo == "bar" assert hasattr(TestComponent, "custom") test_component = TestComponent() assert test_component.foo == "bar" assert test_component("foo") == "foo" assert hasattr(test_component, "custom") assert test_component.custom("bar") == "bar" if not is_python2: assert TestComponent.__doc__ == "docstring1" assert TestComponent.__call__.__doc__ == "docstring2" assert TestComponent.custom.__doc__ == "docstring3" assert test_component.__doc__ == "docstring1" assert test_component.__call__.__doc__ == "docstring2" assert test_component.custom.__doc__ == "docstring3" def test_component_decorator_assigns(): spacy.language.ENABLE_PIPELINE_ANALYSIS = True @component("c1", assigns=["token.tag", "doc.tensor"]) def test_component1(doc): return doc @component( "c2", requires=["token.tag", "token.pos"], assigns=["token.lemma", "doc.tensor"] ) def test_component2(doc): return doc @component("c3", requires=["token.lemma"], assigns=["token._.custom_lemma"]) def test_component3(doc): return doc assert "c1" in Language.factories assert "c2" in Language.factories assert "c3" in Language.factories nlp = Language() nlp.add_pipe(test_component1) with pytest.warns(UserWarning): nlp.add_pipe(test_component2) nlp.add_pipe(test_component3) assigns_tensor = get_assigns_for_attr(nlp.pipeline, "doc.tensor") assert [name for name, _ in assigns_tensor] == ["c1", "c2"] test_component4 = nlp.create_pipe("c1") assert test_component4.name == "c1" assert test_component4.factory == "c1" nlp.add_pipe(test_component4, name="c4") assert nlp.pipe_names == ["c1", "c2", "c3", "c4"] assert "c4" not in Language.factories assert nlp.pipe_factories["c1"] == "c1" assert nlp.pipe_factories["c4"] == "c1" assigns_tensor = get_assigns_for_attr(nlp.pipeline, "doc.tensor") assert [name for name, _ in assigns_tensor] == ["c1", "c2", "c4"] requires_pos = get_requires_for_attr(nlp.pipeline, "token.pos") assert [name for name, _ in requires_pos] == ["c2"] assert print_summary(nlp, no_print=True) assert nlp("hello world") def test_component_factories_from_nlp(): """Test that class components can implement a from_nlp classmethod that gives them access to the nlp object and config via the factory.""" class TestComponent5(object): def __call__(self, doc): return doc mock = Mock() mock.return_value = TestComponent5() TestComponent5.from_nlp = classmethod(mock) TestComponent5 = component("c5")(TestComponent5) assert "c5" in Language.factories nlp = Language() pipe = nlp.create_pipe("c5", config={"foo": "bar"}) nlp.add_pipe(pipe) assert nlp("hello world") # The first argument here is the class itself, so we're accepting any here mock.assert_called_once_with(ANY, nlp, foo="bar") def test_analysis_validate_attrs_valid(): attrs = ["doc.sents", "doc.ents", "token.tag", "token._.xyz", "span._.xyz"] assert validate_attrs(attrs) for attr in attrs: assert validate_attrs([attr]) with pytest.raises(ValueError): validate_attrs(["doc.sents", "doc.xyz"]) @pytest.mark.parametrize( "attr", [ "doc", "doc_ents", "doc.xyz", "token.xyz", "token.tag_", "token.tag.xyz", "token._.xyz.abc", "span.label", ], ) def test_analysis_validate_attrs_invalid(attr): with pytest.raises(ValueError): validate_attrs([attr])