fix rebase errors

microsoft · May 19, 2020 · 8de3d09 · 8de3d09
1 parent ab5553b
commit 8de3d09
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Showing 2 changed files with 18 additions and 112 deletions.
diff --git a/presidio-analyzer/presidio_analyzer/recognizer_registry/recognizers_store_api.py b/presidio-analyzer/presidio_analyzer/recognizer_registry/recognizers_store_api.py
@@ -3,7 +3,10 @@
 import grpc
 from presidio_analyzer.protobuf_models import recognizers_store_pb2, recognizers_store_pb2_grpc
 
-from presidio_analyzer import PatternRecognizer, Pattern
+from presidio_analyzer import PatternRecognizer, Pattern, PresidioLogger
+
+
+logger = PresidioLogger("presidio")
 
 
 class RecognizerStoreApi:

diff --git a/presidio-analyzer/tests/test_analyzer_engine.py b/presidio-analyzer/tests/test_analyzer_engine.py
@@ -131,7 +131,7 @@ def test_analyze_with_predefined_recognizers_return_results(
     language = "en"
     entities = ["CREDIT_CARD"]
     results = loaded_analyzer_engine.analyze(
-        unit_test_guid, text, entities, language, all_fields=False
+        correlation_id=unit_test_guid, text=text, entities=entities, language=language, all_fields=False
     )
 
     assert len(results) == 1
@@ -149,7 +149,7 @@ def test_analyze_with_multiple_predefined_recognizers(
         registry=loaded_registry, nlp_engine=nlp_engine
     )
     results = analyzer_engine_with_spacy.analyze(
-        unit_test_guid, text, entities, language, all_fields=False
+        correlation_id=unit_test_guid, text=text, entities=entities, language=language, all_fields=False
     )
 
     assert len(results) == 2
@@ -160,110 +160,13 @@ def test_analyze_with_multiple_predefined_recognizers(
     assert_result(results[1], "PHONE_NUMBER", 48, 59, expected_score)
 
 
-def test_analyze_without_entities(loaded_analyzer_engine, unit_test_guid):
-    with pytest.raises(ValueError):
-        language = "en"
-<<<<<<< HEAD
-        entities = ["CREDIT_CARD", "PHONE_NUMBER"]
-
-        # This analyzer engine is different from the global one, as this one
-        # also loads SpaCy so it can use the context words
-
-        analyzer_engine_with_spacy = AnalyzerEngine(
-            registry=self.loaded_registry, nlp_engine=loaded_spacy_nlp_engine)
-        results = analyzer_engine_with_spacy.analyze(self.unit_test_guid, text,
-                                                     entities, language,
-                                                     all_fields=False)
-
-        assert len(results) == 2
-        medium_regex_score = 0.5  # UsPhoneRecognizer.PATTERN_GROUPS[1][2]
-        context_similarity_factor = 0.35  # PatternRecognizer.CONTEXT_SIMILARITY_FACTOR
-        assert_result(results[0], "CREDIT_CARD", 14,
-                      33, EntityRecognizer.MAX_SCORE)
-        expected_score = medium_regex_score + context_similarity_factor
-        assert_result(results[1], "PHONE_NUMBER", 48, 59, expected_score)
-
-    def test_analyze_without_entities(self):
-        with pytest.raises(ValueError):
-            language = "en"
-            text = " Credit card: 4095-2609-9393-4932,  my name is  John Oliver, DateTime: September 18 Domain: microsoft.com"
-            entities = []
-            self.loaded_analyzer_engine.analyze(self.unit_test_guid,
-                                                text, entities, language,
-                                                all_fields=False)
-
-    def test_analyze_with_empty_text(self):
-=======
-@pytest.fixture(scope="module")
-def loaded_registry():
-    return MockRecognizerRegistry(RecognizerStoreApiMock())
-
-@pytest.fixture(scope="module")
-def app_tracer():
-    return AppTracerMock(enable_interpretability=True)
-
-@pytest.fixture(scope="module")
-def loaded_analyzer_engine(loaded_registry, app_tracer):
-    mock_nlp_artifacts = NlpArtifacts([], [], [], [], None, "en")
-    analyzer_engine = AnalyzerEngine(
-        loaded_registry,
-        MockNlpEngine(
-            stopwords=[],
-            punct_words=[],
-            nlp_artifacts=mock_nlp_artifacts
-        ),
-        app_tracer=app_tracer,
-        enable_trace_pii=True
-    )
-    return analyzer_engine
-
-@pytest.fixture(scope="module")
-def unit_test_guid():
-    return "00000000-0000-0000-0000-000000000000"
-
-def test_analyze_with_predefined_recognizers_return_results(loaded_analyzer_engine, unit_test_guid):
-    text = " Credit card: 4095-2609-9393-4932,  my phone is 425 8829090"
-    language = "en"
-    entities = ["CREDIT_CARD"]
-    results = loaded_analyzer_engine.analyze(
-        unit_test_guid,
-        text, entities, language, all_fields=False)
-
-    assert len(results) == 1
-    assert_result(results[0], "CREDIT_CARD", 14,
-                  33, EntityRecognizer.MAX_SCORE)
-
-def test_analyze_with_multiple_predefined_recognizers(loaded_registry, unit_test_guid, nlp_engines):
-    text = " Credit card: 4095-2609-9393-4932,  my phone is 425 8829090"
-    language = "en"
-    entities = ["CREDIT_CARD", "PHONE_NUMBER"]
-
-    # This analyzer engine is different from the global one, as this one
-    # also loads SpaCy so it can use the context words
-
-    nlp_engine = nlp_engines["spacy_en"]
-
-    analyzer_engine_with_spacy = AnalyzerEngine(
-        registry=loaded_registry, nlp_engine=nlp_engine)
-    results = analyzer_engine_with_spacy.analyze(unit_test_guid, text,
-                                                 entities, language,
-                                                 all_fields=False)
-
-    assert len(results) == 2
-    medium_regex_score = 0.5  # UsPhoneRecognizer.PATTERN_GROUPS[1][2]
-    context_similarity_factor = 0.35  # PatternRecognizer.CONTEXT_SIMILARITY_FACTOR
-    assert_result(results[0], "CREDIT_CARD", 14,
-                  33, EntityRecognizer.MAX_SCORE)
-    expected_score = medium_regex_score + context_similarity_factor
-    assert_result(results[1], "PHONE_NUMBER", 48, 59, expected_score)
-
 def test_analyze_without_entities(loaded_analyzer_engine, unit_test_guid):
     with pytest.raises(ValueError):
         language = "en"
         text = " Credit card: 4095-2609-9393-4932,  my name is  John Oliver, DateTime: September 18 Domain: microsoft.com"  # noqa E501
         entities = []
         loaded_analyzer_engine.analyze(
-            unit_test_guid, text, entities, language, all_fields=False
+            correlation_id=unit_test_guid, text=text, entities=entities, language=language, all_fields=False
         )
 
 
@@ -272,7 +175,7 @@ def test_analyze_with_empty_text(loaded_analyzer_engine, unit_test_guid):
     text = ""
     entities = ["CREDIT_CARD", "PHONE_NUMBER"]
     results = loaded_analyzer_engine.analyze(
-        unit_test_guid, text, entities, language, all_fields=False
+        correlation_id=unit_test_guid, text=text, entities=entities, language=language, all_fields=False
     )
 
     assert len(results) == 0
@@ -284,7 +187,7 @@ def test_analyze_with_unsupported_language(loaded_analyzer_engine, unit_test_gui
         text = ""
         entities = ["CREDIT_CARD", "PHONE_NUMBER"]
         loaded_analyzer_engine.analyze(
-            unit_test_guid, text, entities, language, all_fields=False
+            correlation_id=unit_test_guid, text=text, entities=entities, language=language, all_fields=False
         )
 
 
@@ -376,7 +279,7 @@ def test_added_pattern_recognizer_works(unit_test_guid):
     entities = ["CREDIT_CARD", "ROCKET"]
 
     results = analyze_engine.analyze(
-        unit_test_guid, text=text, entities=entities, language="en", all_fields=False
+        correlation_id=unit_test_guid, text=text, entities=entities, language="en", all_fields=False
     )
 
     assert len(results) == 0
@@ -386,7 +289,7 @@ def test_added_pattern_recognizer_works(unit_test_guid):
 
     # Check that the entity is recognized:
     results = analyze_engine.analyze(
-        unit_test_guid, text=text, entities=entities, language="en", all_fields=False
+        correlation_id=unit_test_guid, text=text, entities=entities, language="en", all_fields=False
     )
 
     assert len(results) == 1
@@ -409,7 +312,7 @@ def test_removed_pattern_recognizer_doesnt_work(unit_test_guid):
     entities = ["CREDIT_CARD", "SPACESHIP"]
 
     results = analyze_engine.analyze(
-        unit_test_guid, text=text, entities=entities, language="en", all_fields=False
+        correlation_id=unit_test_guid, text=text, entities=entities, language="en", all_fields=False
     )
 
     assert len(results) == 0
@@ -418,7 +321,7 @@ def test_removed_pattern_recognizer_doesnt_work(unit_test_guid):
     recognizers_store_api_mock.add_custom_pattern_recognizer(pattern_recognizer)
     # Check that the entity is recognized:
     results = analyze_engine.analyze(
-        unit_test_guid, text=text, entities=entities, language="en", all_fields=False
+        correlation_id=unit_test_guid, text=text, entities=entities, language="en", all_fields=False
     )
     assert len(results) == 1
     assert_result(results[0], "SPACESHIP", 0, 10, 0.8)
@@ -427,7 +330,7 @@ def test_removed_pattern_recognizer_doesnt_work(unit_test_guid):
     recognizers_store_api_mock.remove_recognizer("Spaceship recognizer")
     # Test again to see we didn't get any results
     results = analyze_engine.analyze(
-        unit_test_guid, text=text, entities=entities, language="en", all_fields=False
+        correlation_id=unit_test_guid, text=text, entities=entities, language="en", all_fields=False
     )
 
     assert len(results) == 0
@@ -547,7 +450,7 @@ def test_when_threshold_is_zero_all_results_pass(loaded_registry, unit_test_guid
         registry=loaded_registry, nlp_engine=NlpEngineMock()
     )
     results = analyzer_engine.analyze(
-        unit_test_guid, text, entities, language, all_fields=False, score_threshold=0
+        correlation_id=unit_test_guid, text=text, entities=entities, language=language, all_fields=False, score_threshold=0
     )
 
     assert len(results) == 2
@@ -567,7 +470,7 @@ def test_when_threshold_is_more_than_half_only_credit_card_passes(
         registry=loaded_registry, nlp_engine=NlpEngineMock()
     )
     results = analyzer_engine.analyze(
-        unit_test_guid, text, entities, language, all_fields=False, score_threshold=0.51
+        correlation_id=unit_test_guid, text=text, entities=entities, language=language, score_threshold=0.51, all_fields=False
     )
 
     assert len(results) == 1
@@ -589,7 +492,7 @@ def test_when_default_threshold_is_more_than_half_only_one_passes(
         default_score_threshold=0.7,
     )
     results = analyzer_engine.analyze(
-        unit_test_guid, text, entities, language, all_fields=False
+        correlation_id=unit_test_guid, text=text, entities=entities, language=language, all_fields=False
     )
 
     assert len(results) == 1
@@ -609,7 +512,7 @@ def test_when_default_threshold_is_zero_all_results_pass(
         registry=loaded_registry, nlp_engine=NlpEngineMock()
     )
     results = analyzer_engine.analyze(
-        unit_test_guid, text, entities, language, all_fields=False
+        correlation_id=unit_test_guid, text=text, entities=entities, language=language, all_fields=False
     )
 
     assert len(results) == 2