Fix 'create_classifications' helper

arkindex_worker/worker/classification.py

@@ -2,8 +2,6 @@
 ElementsWorker methods for classifications and ML classes.
 """
 
-from uuid import UUID
-
 from apistar.exceptions import ErrorResponse
 from peewee import IntegrityError
 
@@ -178,10 +176,14 @@ class ClassificationMixin:
         Create multiple classifications at once on the given element through the API.
 
         :param element: The element to create classifications on.
-        :param classifications: The classifications to create, a list of dicts. Each of them contains
-            a **ml_class_id** (str), the ID of the MLClass for this classification;
-            a **confidence** (float), the confidence score, between 0 and 1;
-            a **high_confidence** (bool), the high confidence state of the classification.
+        :param classifications: A list of dicts representing a classification each, with the following keys:
+
+            ml_class (str)
+                Required. Name of the MLClass to use.
+            confidence (float)
+                Required. Confidence score for the classification. Must be between 0 and 1.
+            high_confidence (bool)
+                Optional. Whether or not the classification is of high confidence.
 
         :returns: List of created classifications, as returned in the ``classifications`` field by
            the ``CreateClassifications`` API endpoint.
@@ -194,18 +196,10 @@ class ClassificationMixin:
         ), "classifications shouldn't be null and should be of type list"
 
         for index, classification in enumerate(classifications):
-            ml_class_id = classification.get("ml_class_id")
+            ml_class = classification.get("ml_class")
             assert (
-                ml_class_id and isinstance(ml_class_id, str)
-            ), f"Classification at index {index} in classifications: ml_class_id shouldn't be null and should be of type str"
-
-            # Make sure it's a valid UUID
-            try:
-                UUID(ml_class_id)
-            except ValueError as e:
-                raise ValueError(
-                    f"Classification at index {index} in classifications: ml_class_id is not a valid uuid."
-                ) from e
+                ml_class and isinstance(ml_class, str)
+            ), f"Classification at index {index} in classifications: ml_class shouldn't be null and should be of type str"
 
             confidence = classification.get("confidence")
             assert (
@@ -231,7 +225,13 @@ class ClassificationMixin:
             body={
                 "parent": str(element.id),
                 "worker_run_id": self.worker_run_id,
-                "classifications": classifications,
+                "classifications": [
+                    {
+                        **classification,
+                        "ml_class": self.get_ml_class_id(classification["ml_class"]),
+                    }
+                    for classification in classifications
+                ],
             },
         )["classifications"]
 

tests/test_elements_worker/test_classifications.py

 import json
 import re
-from uuid import UUID, uuid4
+from uuid import UUID
 
 import pytest
 from apistar.exceptions import ErrorResponse
@@ -325,9 +325,6 @@ def test_create_classification_create_ml_class(mock_elements_worker, responses):
     )
 
     # Check a class & classification has been created
-    for call in responses.calls:
-        print(call.request.url, call.request.body)
-
     assert [
         (call.request.url, json.loads(call.request.body))
         for call in responses.calls[-2:]
@@ -506,12 +503,12 @@ def test_create_classifications_wrong_data(
                 "element": Element({"id": "12341234-1234-1234-1234-123412341234"}),
                 "classifications": [
                     {
-                        "ml_class_id": "uuid1",
+                        "ml_class": "cat",
                         "confidence": 0.75,
                         "high_confidence": False,
                     },
                     {
-                        "ml_class_id": "uuid2",
+                        "ml_class": "dog",
                         "confidence": 0.25,
                         "high_confidence": False,
                     },
@@ -523,86 +520,71 @@ def test_create_classifications_wrong_data(
 
 
 @pytest.mark.parametrize(
-    ("arg_name", "data", "error_message", "error_type"),
+    ("arg_name", "data", "error_message"),
     [
-        # Wrong classifications > ml_class_id
+        # Wrong classifications > ml_class
         (
-            "ml_class_id",
+            "ml_class",
             DELETE_PARAMETER,
-            "ml_class_id shouldn't be null and should be of type str",
-            AssertionError,
-        ),  # Updated
+            "ml_class shouldn't be null and should be of type str",
+        ),
         (
-            "ml_class_id",
+            "ml_class",
             None,
-            "ml_class_id shouldn't be null and should be of type str",
-            AssertionError,
+            "ml_class shouldn't be null and should be of type str",
         ),
         (
-            "ml_class_id",
+            "ml_class",
             1234,
-            "ml_class_id shouldn't be null and should be of type str",
-            AssertionError,
-        ),
-        (
-            "ml_class_id",
-            "not_an_uuid",
-            "ml_class_id is not a valid uuid.",
-            ValueError,
+            "ml_class shouldn't be null and should be of type str",
         ),
         # Wrong classifications > confidence
         (
             "confidence",
             DELETE_PARAMETER,
             "confidence shouldn't be null and should be a float in [0..1] range",
-            AssertionError,
         ),
         (
             "confidence",
             None,
             "confidence shouldn't be null and should be a float in [0..1] range",
-            AssertionError,
         ),
         (
             "confidence",
             "wrong confidence",
             "confidence shouldn't be null and should be a float in [0..1] range",
-            AssertionError,
         ),
         (
             "confidence",
             0,
             "confidence shouldn't be null and should be a float in [0..1] range",
-            AssertionError,
         ),
         (
             "confidence",
             2.00,
             "confidence shouldn't be null and should be a float in [0..1] range",
-            AssertionError,
         ),
         # Wrong classifications > high_confidence
         (
             "high_confidence",
             "wrong high_confidence",
             "high_confidence should be of type bool",
-            AssertionError,
         ),
     ],
 )
 def test_create_classifications_wrong_classifications_data(
-    arg_name, data, error_message, error_type, mock_elements_worker
+    arg_name, data, error_message, mock_elements_worker
 ):
     all_data = {
         "element": Element({"id": "12341234-1234-1234-1234-123412341234"}),
         "classifications": [
             {
-                "ml_class_id": str(uuid4()),
+                "ml_class": "cat",
                 "confidence": 0.75,
                 "high_confidence": False,
             },
             {
-                "ml_class_id": str(uuid4()),
+                "ml_class": "dog",
                 "confidence": 0.25,
                 "high_confidence": False,
                 # Overwrite with wrong data
@@ -614,7 +596,7 @@ def test_create_classifications_wrong_classifications_data(
         del all_data["classifications"][1][arg_name]
 
     with pytest.raises(
-        error_type,
+        AssertionError,
         match=re.escape(
             f"Classification at index 1 in classifications: {error_message}"
         ),
@@ -623,6 +605,7 @@ def test_create_classifications_wrong_classifications_data(
 
 
 def test_create_classifications_api_error(responses, mock_elements_worker):
+    mock_elements_worker.classes = {"cat": "0000", "dog": "1111"}
     responses.add(
         responses.POST,
         "http://testserver/api/v1/classification/bulk/",
@@ -631,12 +614,12 @@ def test_create_classifications_api_error(responses, mock_elements_worker):
     elt = Element({"id": "12341234-1234-1234-1234-123412341234"})
     classes = [
         {
-            "ml_class_id": str(uuid4()),
+            "ml_class": "cat",
             "confidence": 0.75,
             "high_confidence": False,
         },
         {
-            "ml_class_id": str(uuid4()),
+            "ml_class": "dog",
             "confidence": 0.25,
             "high_confidence": False,
         },
@@ -660,57 +643,96 @@ def test_create_classifications_api_error(responses, mock_elements_worker):
     ]
 
 
-def test_create_classifications(responses, mock_elements_worker_with_cache):
-    # Set MLClass in cache
-    portrait_uuid = str(uuid4())
-    landscape_uuid = str(uuid4())
-    mock_elements_worker_with_cache.classes = {
-        "portrait": portrait_uuid,
-        "landscape": landscape_uuid,
-    }
-
-    elt = CachedElement.create(id="12341234-1234-1234-1234-123412341234", type="thing")
-    classes = [
-        {
-            "ml_class_id": portrait_uuid,
-            "confidence": 0.75,
-            "high_confidence": False,
-        },
-        {
-            "ml_class_id": landscape_uuid,
-            "confidence": 0.25,
-            "high_confidence": False,
-        },
-    ]
+def test_create_classifications_create_ml_class(mock_elements_worker, responses):
+    elt = Element({"id": "12341234-1234-1234-1234-123412341234"})
 
+    # Automatically create a missing class!
+    responses.add(
+        responses.POST,
+        "http://testserver/api/v1/corpus/11111111-1111-1111-1111-111111111111/classes/",
+        status=201,
+        json={"id": "new-ml-class-1234"},
+    )
     responses.add(
         responses.POST,
         "http://testserver/api/v1/classification/bulk/",
-        status=200,
+        status=201,
         json={
             "parent": str(elt.id),
             "worker_run_id": "56785678-5678-5678-5678-567856785678",
             "classifications": [
                 {
                     "id": "00000000-0000-0000-0000-000000000000",
-                    "ml_class": portrait_uuid,
+                    "ml_class": "new-ml-class-1234",
                     "confidence": 0.75,
                     "high_confidence": False,
                     "state": "pending",
                 },
-                {
-                    "id": "11111111-1111-1111-1111-111111111111",
-                    "ml_class": landscape_uuid,
-                    "confidence": 0.25,
-                    "high_confidence": False,
-                    "state": "pending",
-                },
             ],
         },
     )
+    mock_elements_worker.classes = {"another_class": "0000"}
+    mock_elements_worker.create_classifications(
+        element=elt,
+        classifications=[
+            {
+                "ml_class": "a_class",
+                "confidence": 0.75,
+                "high_confidence": False,
+            }
+        ],
+    )
 
-    mock_elements_worker_with_cache.create_classifications(
-        element=elt, classifications=classes
+    # Check a class & classification has been created
+    assert len(responses.calls) == len(BASE_API_CALLS) + 2
+    assert [
+        (call.request.method, call.request.url) for call in responses.calls
+    ] == BASE_API_CALLS + [
+        (
+            "POST",
+            "http://testserver/api/v1/corpus/11111111-1111-1111-1111-111111111111/classes/",
+        ),
+        ("POST", "http://testserver/api/v1/classification/bulk/"),
+    ]
+
+    assert json.loads(responses.calls[-2].request.body) == {"name": "a_class"}
+    assert json.loads(responses.calls[-1].request.body) == {
+        "parent": "12341234-1234-1234-1234-123412341234",
+        "worker_run_id": "56785678-5678-5678-5678-567856785678",
+        "classifications": [
+            {
+                "ml_class": "new-ml-class-1234",
+                "confidence": 0.75,
+                "high_confidence": False,
+            }
+        ],
+    }
+
+
+def test_create_classifications(responses, mock_elements_worker):
+    mock_elements_worker.classes = {"portrait": "0000", "landscape": "1111"}
+    elt = Element({"id": "12341234-1234-1234-1234-123412341234"})
+    responses.add(
+        responses.POST,
+        "http://testserver/api/v1/classification/bulk/",
+        status=200,
+        json={"classifications": []},
+    )
+
+    mock_elements_worker.create_classifications(
+        element=elt,
+        classifications=[
+            {
+                "ml_class": "portrait",
+                "confidence": 0.75,
+                "high_confidence": False,
+            },
+            {
+                "ml_class": "landscape",
+                "confidence": 0.25,
+                "high_confidence": False,
+            },
+        ],
     )
 
     assert len(responses.calls) == len(BASE_API_CALLS) + 1
@@ -723,52 +745,24 @@ def test_create_classifications(responses, mock_elements_worker_with_cache):
     assert json.loads(responses.calls[-1].request.body) == {
         "parent": str(elt.id),
         "worker_run_id": "56785678-5678-5678-5678-567856785678",
-        "classifications": classes,
+        "classifications": [
+            {
+                "confidence": 0.75,
+                "high_confidence": False,
+                "ml_class": "0000",
+            },
+            {
+                "confidence": 0.25,
+                "high_confidence": False,
+                "ml_class": "1111",
+            },
+        ],
     }
 
-    # Check that created classifications were properly stored in SQLite cache
-    assert list(CachedClassification.select()) == [
-        CachedClassification(
-            id=UUID("00000000-0000-0000-0000-000000000000"),
-            element_id=UUID(elt.id),
-            class_name="portrait",
-            confidence=0.75,
-            state="pending",
-            worker_run_id=UUID("56785678-5678-5678-5678-567856785678"),
-        ),
-        CachedClassification(
-            id=UUID("11111111-1111-1111-1111-111111111111"),
-            element_id=UUID(elt.id),
-            class_name="landscape",
-            confidence=0.25,
-            state="pending",
-            worker_run_id=UUID("56785678-5678-5678-5678-567856785678"),
-        ),
-    ]
-
 
-def test_create_classifications_not_in_cache(
-    responses, mock_elements_worker_with_cache
-):
-    """
-    CreateClassifications using ID that are not in `.classes` attribute.
-    Will load corpus MLClass to insert the corresponding name in Cache.
-    """
-    portrait_uuid = str(uuid4())
-    landscape_uuid = str(uuid4())
+def test_create_classifications_with_cache(responses, mock_elements_worker_with_cache):
+    mock_elements_worker_with_cache.classes = {"portrait": "0000", "landscape": "1111"}
     elt = CachedElement.create(id="12341234-1234-1234-1234-123412341234", type="thing")
-    classes = [
-        {
-            "ml_class_id": portrait_uuid,
-            "confidence": 0.75,
-            "high_confidence": False,
-        },
-        {
-            "ml_class_id": landscape_uuid,
-            "confidence": 0.25,
-            "high_confidence": False,
-        },
-    ]
 
     responses.add(
         responses.POST,
@@ -780,14 +774,14 @@ def test_create_classifications_not_in_cache(
             "classifications": [
                 {
                     "id": "00000000-0000-0000-0000-000000000000",
-                    "ml_class": portrait_uuid,
+                    "ml_class": "0000",
                     "confidence": 0.75,
                     "high_confidence": False,
                     "state": "pending",
                 },
                 {
                     "id": "11111111-1111-1111-1111-111111111111",
-                    "ml_class": landscape_uuid,
+                    "ml_class": "1111",
                     "confidence": 0.25,
                     "high_confidence": False,
                     "state": "pending",
@@ -795,42 +789,45 @@ def test_create_classifications_not_in_cache(
             ],
         },
     )
-    responses.add(
-        responses.GET,
-        f"http://testserver/api/v1/corpus/{mock_elements_worker_with_cache.corpus_id}/classes/",
-        status=200,
-        json={
-            "count": 2,
-            "next": None,
-            "results": [
-                {
-                    "id": portrait_uuid,
-                    "name": "portrait",
-                },
-                {"id": landscape_uuid, "name": "landscape"},
-            ],
-        },
-    )
 
     mock_elements_worker_with_cache.create_classifications(
-        element=elt, classifications=classes
+        element=elt,
+        classifications=[
+            {
+                "ml_class": "portrait",
+                "confidence": 0.75,
+                "high_confidence": False,
+            },
+            {
+                "ml_class": "landscape",
+                "confidence": 0.25,
+                "high_confidence": False,
+            },
+        ],
     )
 
-    assert len(responses.calls) == len(BASE_API_CALLS) + 2
+    assert len(responses.calls) == len(BASE_API_CALLS) + 1
     assert [
         (call.request.method, call.request.url) for call in responses.calls
     ] == BASE_API_CALLS + [
         ("POST", "http://testserver/api/v1/classification/bulk/"),
-        (
-            "GET",
-            f"http://testserver/api/v1/corpus/{mock_elements_worker_with_cache.corpus_id}/classes/",
-        ),
     ]
 
-    assert json.loads(responses.calls[-2].request.body) == {
+    assert json.loads(responses.calls[-1].request.body) == {
         "parent": str(elt.id),
         "worker_run_id": "56785678-5678-5678-5678-567856785678",
-        "classifications": classes,
+        "classifications": [
+            {
+                "confidence": 0.75,
+                "high_confidence": False,
+                "ml_class": "0000",
+            },
+            {
+                "confidence": 0.25,
+                "high_confidence": False,
+                "ml_class": "1111",
+            },
+        ],
     }
 
     # Check that created classifications were properly stored in SQLite cache