testing spacy

Author: isabelizimm

vetiver/tests/test_spacy.py

@@ -11,6 +11,7 @@
 
 @pytest.fixture
 def spacy_model():
+<<<<<<< HEAD
     @spacy.language.Language.component("animals")
     def animal_component_function(doc):
         matches = matcher(doc)  # noqa
@@ -33,21 +34,39 @@ def animal_component_function(doc):
 @pytest.fixture
 def vetiver_client(spacy_model):  # With check_prototype=True
     app = vetiver.VetiverAPI(spacy_model, check_prototype=True)
+=======
+
+    nlp = spacy.blank("en")
+    sentencizer = nlp.add_pipe("sentencizer")
+
+    return vetiver.VetiverModel(sentencizer, "sentencizer")
+
+
+@pytest.fixture
+def vetiver_client(spacy_model):  # With check_ptype=True
+    app = vetiver.VetiverAPI(spacy_model, check_ptype=True)
+>>>>>>> b600e38 (testing spacy)
     app.app.root_path = "/predict"
     client = TestClient(app.app)
 
     return client
 
 
 @pytest.fixture
+<<<<<<< HEAD
 def vetiver_client_check_ptype_false(spacy_model):  # With check_prototype=False
     app = vetiver.VetiverAPI(spacy_model, check_prototype=True)
+=======
+def vetiver_client_check_ptype_false(spacy_model):  # With check_ptype=True
+    app = vetiver.VetiverAPI(spacy_model, check_ptype=False)
+>>>>>>> b600e38 (testing spacy)
     app.app.root_path = "/predict"
     client = TestClient(app.app)
 
     return client
 
 
+<<<<<<< HEAD
 def test_vetiver_post(vetiver_client):
     df = pd.DataFrame({"text": ["one", "my turtle is smarter than my dog"]})
 
@@ -92,3 +111,51 @@ def test_vetiver_post(vetiver_client):
 #         spacy.Language,
 #     )
 #     board.pin_delete("animals")
+=======
+def test_vetiver_build(vetiver_client):
+    nlp = spacy.blank("en")
+    words = ["This", "is", "a", "new", "Sentence", "."]
+    doc = spacy.tokens.Doc(nlp.vocab, words=words)
+
+    response = vetiver.predict(endpoint=vetiver_client, data=doc.to_json())
+
+    assert response == [[True, False, False, False, False, False]]
+
+
+def test_batch(vetiver_client):
+    nlp = spacy.blank("en")
+    words1 = ["This", "is", "a", "new", "Sentence", "."]
+    doc1 = spacy.tokens.Doc(nlp.vocab, words=words1)
+    words2 = ["Another", "one", "."]
+    doc2 = spacy.tokens.Doc(nlp.vocab, words=words2)
+
+    response = vetiver.predict(endpoint=vetiver_client, data=[doc1, doc2])
+
+    assert response == [[True, False, False, False, False, False], [True, False, False]]
+
+
+def test_no_ptype(vetiver_client_check_ptype_false):
+    nlp = spacy.blank("en")
+    words1 = ["This", "is", "a", "new", "Sentence", "."]
+    doc1 = spacy.tokens.Doc(nlp.vocab, words=words1)
+    words2 = ["Another", "one", "."]
+    doc2 = spacy.tokens.Doc(nlp.vocab, words=words2)
+
+    response = vetiver.predict(
+        endpoint=vetiver_client_check_ptype_false, data=[doc1, doc2]
+    )
+
+    assert response == [[True, False, False, False, False, False], [True, False, False]]
+
+
+def test_serialize(spacy_model):
+    import pins
+
+    board = pins.board_temp(allow_pickle_read=True)
+    vetiver.vetiver_pin_write(board=board, model=spacy_model)
+    assert isinstance(
+        board.pin_read("sentencizer"),
+        spacy.pipeline.sentencizer.Sentencizer,
+    )
+    board.pin_delete("sentencizer")
+>>>>>>> b600e38 (testing spacy)