diff --git a/tests/test_elements_worker/test_classifications.py b/tests/test_elements_worker/test_classifications.py
index 31ec96b63200a321a29c8628f200ef68e72ab98e..738de363046afc4582a2fd1cd448912fb306f387 100644
--- a/tests/test_elements_worker/test_classifications.py
+++ b/tests/test_elements_worker/test_classifications.py
@@ -10,6 +10,8 @@ from arkindex_worker.models import Element
from . import BASE_API_CALLS
+DELETE_PARAMETER = "DELETE_PARAMETER"
+
def test_get_ml_class_id_load_classes(responses, mock_elements_worker):
corpus_id = "11111111-1111-1111-1111-111111111111"
@@ -191,108 +193,79 @@ def test_retrieve_ml_class_not_in_cache(responses, mock_elements_worker):
@pytest.mark.parametrize(
- ("data", "error_message"),
+ ("arg_name", "data", "error_message"),
[
# Wrong element
(
- {
- "element": None,
- "ml_class": "a_class",
- "confidence": 0.42,
- "high_confidence": True,
- },
+ "element",
+ None,
"element shouldn't be null and should be an Element or CachedElement",
),
(
- {
- "element": "not element type",
- "ml_class": "a_class",
- "confidence": 0.42,
- "high_confidence": True,
- },
+ "element",
+ "not element type",
"element shouldn't be null and should be an Element or CachedElement",
),
# Wrong ml_class
(
- {
- "element": Element({"id": "12341234-1234-1234-1234-123412341234"}),
- "ml_class": None,
- "confidence": 0.42,
- "high_confidence": True,
- },
+ "ml_class",
+ None,
"ml_class shouldn't be null and should be of type str",
),
(
- {
- "element": Element({"id": "12341234-1234-1234-1234-123412341234"}),
- "ml_class": 1234,
- "confidence": 0.42,
- "high_confidence": True,
- },
+ "ml_class",
+ 1234,
"ml_class shouldn't be null and should be of type str",
),
# Wrong confidence
(
- {
- "element": Element({"id": "12341234-1234-1234-1234-123412341234"}),
- "ml_class": "a_class",
- "confidence": None,
- "high_confidence": True,
- },
+ "confidence",
+ None,
"confidence shouldn't be null and should be a float in [0..1] range",
),
(
- {
- "element": Element({"id": "12341234-1234-1234-1234-123412341234"}),
- "ml_class": "a_class",
- "confidence": "wrong confidence",
- "high_confidence": True,
- },
+ "confidence",
+ "wrong confidence",
"confidence shouldn't be null and should be a float in [0..1] range",
),
(
- {
- "element": Element({"id": "12341234-1234-1234-1234-123412341234"}),
- "ml_class": "a_class",
- "confidence": 0,
- "high_confidence": True,
- },
+ "confidence",
+ 0,
"confidence shouldn't be null and should be a float in [0..1] range",
),
(
- {
- "element": Element({"id": "12341234-1234-1234-1234-123412341234"}),
- "ml_class": "a_class",
- "confidence": 2.00,
- "high_confidence": True,
- },
+ "confidence",
+ 2.00,
"confidence shouldn't be null and should be a float in [0..1] range",
),
# Wrong high_confidence
(
- {
- "element": Element({"id": "12341234-1234-1234-1234-123412341234"}),
- "ml_class": "a_class",
- "confidence": 0.42,
- "high_confidence": None,
- },
+ "high_confidence",
+ None,
"high_confidence shouldn't be null and should be of type bool",
),
(
- {
- "element": Element({"id": "12341234-1234-1234-1234-123412341234"}),
- "ml_class": "a_class",
- "confidence": 0.42,
- "high_confidence": "wrong high_confidence",
- },
+ "high_confidence",
+ "wrong high_confidence",
"high_confidence shouldn't be null and should be of type bool",
),
],
)
-def test_create_classification_wrong_data(data, error_message, mock_elements_worker):
+def test_create_classification_wrong_data(
+ arg_name, data, error_message, mock_elements_worker
+):
mock_elements_worker.classes = {"a_class": "0000"}
with pytest.raises(AssertionError, match=re.escape(error_message)):
- mock_elements_worker.create_classification(**data)
+ mock_elements_worker.create_classification(
+ **{
+ "element": Element({"id": "12341234-1234-1234-1234-123412341234"}),
+ "ml_class": "a_class",
+ "confidence": 0.42,
+ "high_confidence": True,
+ # Overwrite with wrong data
+ arg_name: data,
+ }
+ )
def test_create_classification_api_error(responses, mock_elements_worker):
@@ -498,262 +471,153 @@ def test_create_classification_duplicate_worker_run(responses, mock_elements_wor
@pytest.mark.parametrize(
- ("data", "error_message", "error_type"),
+ ("arg_name", "data", "error_message"),
[
- # Wrong element
(
- {
- "element": None,
- "classifications": [
- {
- "ml_class_id": "uuid1",
- "confidence": 0.75,
- "high_confidence": False,
- },
- {
- "ml_class_id": "uuid2",
- "confidence": 0.25,
- "high_confidence": False,
- },
- ],
- },
+ "element",
+ None,
"element shouldn't be null and should be an Element or CachedElement",
- AssertionError,
),
(
- {
- "element": "not element type",
- "classifications": [
- {
- "ml_class_id": "uuid1",
- "confidence": 0.75,
- "high_confidence": False,
- },
- {
- "ml_class_id": "uuid2",
- "confidence": 0.25,
- "high_confidence": False,
- },
- ],
- },
+ "element",
+ "not element type",
"element shouldn't be null and should be an Element or CachedElement",
- AssertionError,
),
- # Wrong classifications
(
- {
- "element": Element({"id": "12341234-1234-1234-1234-123412341234"}),
- "classifications": None,
- },
+ "classifications",
+ None,
"classifications shouldn't be null and should be of type list",
- AssertionError,
),
(
- {
- "element": Element({"id": "12341234-1234-1234-1234-123412341234"}),
- "classifications": 1234,
- },
+ "classifications",
+ 1234,
"classifications shouldn't be null and should be of type list",
- AssertionError,
),
- # Wrong classifications > ml_class_id
- (
- {
+ ],
+)
+def test_create_classifications_wrong_data(
+ arg_name, data, error_message, mock_elements_worker
+):
+ with pytest.raises(AssertionError, match=error_message):
+ mock_elements_worker.create_classifications(
+ **{
"element": Element({"id": "12341234-1234-1234-1234-123412341234"}),
"classifications": [
{
- "ml_class_id": str(uuid4()),
+ "ml_class_id": "uuid1",
"confidence": 0.75,
"high_confidence": False,
},
{
- "ml_class_id": 0.25,
+ "ml_class_id": "uuid2",
+ "confidence": 0.25,
"high_confidence": False,
},
],
+ # Overwrite with wrong data
+ arg_name: data,
},
- "Classification at index 1 in classifications: ml_class_id shouldn't be null and should be of type str",
+ )
+
+
+@pytest.mark.parametrize(
+ ("arg_name", "data", "error_message", "error_type"),
+ [
+ # Wrong classifications > ml_class_id
+ (
+ "ml_class_id",
+ DELETE_PARAMETER,
+ "ml_class_id shouldn't be null and should be of type str",
AssertionError,
- ),
+ ), # Updated
(
- {
- "element": Element({"id": "12341234-1234-1234-1234-123412341234"}),
- "classifications": [
- {
- "ml_class_id": str(uuid4()),
- "confidence": 0.75,
- "high_confidence": False,
- },
- {
- "ml_class_id": None,
- "confidence": 0.25,
- "high_confidence": False,
- },
- ],
- },
- "Classification at index 1 in classifications: ml_class_id shouldn't be null and should be of type str",
+ "ml_class_id",
+ None,
+ "ml_class_id shouldn't be null and should be of type str",
AssertionError,
),
(
- {
- "element": Element({"id": "12341234-1234-1234-1234-123412341234"}),
- "classifications": [
- {
- "ml_class_id": str(uuid4()),
- "confidence": 0.75,
- "high_confidence": False,
- },
- {
- "ml_class_id": 1234,
- "confidence": 0.25,
- "high_confidence": False,
- },
- ],
- },
- "Classification at index 1 in classifications: ml_class_id shouldn't be null and should be of type str",
+ "ml_class_id",
+ 1234,
+ "ml_class_id shouldn't be null and should be of type str",
AssertionError,
),
(
- {
- "element": Element({"id": "12341234-1234-1234-1234-123412341234"}),
- "classifications": [
- {
- "ml_class_id": str(uuid4()),
- "confidence": 0.75,
- "high_confidence": False,
- },
- {
- "ml_class_id": "not_an_uuid",
- "confidence": 0.25,
- "high_confidence": False,
- },
- ],
- },
- "Classification at index 1 in classifications: ml_class_id is not a valid uuid.",
+ "ml_class_id",
+ "not_an_uuid",
+ "ml_class_id is not a valid uuid.",
ValueError,
),
# Wrong classifications > confidence
(
- {
- "element": Element({"id": "12341234-1234-1234-1234-123412341234"}),
- "classifications": [
- {
- "ml_class_id": str(uuid4()),
- "confidence": 0.75,
- "high_confidence": False,
- },
- {
- "ml_class_id": str(uuid4()),
- "high_confidence": False,
- },
- ],
- },
- "Classification at index 1 in classifications: confidence shouldn't be null and should be a float in [0..1] range",
+ "confidence",
+ DELETE_PARAMETER,
+ "confidence shouldn't be null and should be a float in [0..1] range",
AssertionError,
),
(
- {
- "element": Element({"id": "12341234-1234-1234-1234-123412341234"}),
- "classifications": [
- {
- "ml_class_id": str(uuid4()),
- "confidence": 0.75,
- "high_confidence": False,
- },
- {
- "ml_class_id": str(uuid4()),
- "confidence": None,
- "high_confidence": False,
- },
- ],
- },
- "Classification at index 1 in classifications: confidence shouldn't be null and should be a float in [0..1] range",
+ "confidence",
+ None,
+ "confidence shouldn't be null and should be a float in [0..1] range",
AssertionError,
),
(
- {
- "element": Element({"id": "12341234-1234-1234-1234-123412341234"}),
- "classifications": [
- {
- "ml_class_id": str(uuid4()),
- "confidence": 0.75,
- "high_confidence": False,
- },
- {
- "ml_class_id": str(uuid4()),
- "confidence": "wrong confidence",
- "high_confidence": False,
- },
- ],
- },
- "Classification at index 1 in classifications: confidence shouldn't be null and should be a float in [0..1] range",
+ "confidence",
+ "wrong confidence",
+ "confidence shouldn't be null and should be a float in [0..1] range",
AssertionError,
),
(
- {
- "element": Element({"id": "12341234-1234-1234-1234-123412341234"}),
- "classifications": [
- {
- "ml_class_id": str(uuid4()),
- "confidence": 0.75,
- "high_confidence": False,
- },
- {
- "ml_class_id": str(uuid4()),
- "confidence": 0,
- "high_confidence": False,
- },
- ],
- },
- "Classification at index 1 in classifications: confidence shouldn't be null and should be a float in [0..1] range",
+ "confidence",
+ 0,
+ "confidence shouldn't be null and should be a float in [0..1] range",
AssertionError,
),
(
- {
- "element": Element({"id": "12341234-1234-1234-1234-123412341234"}),
- "classifications": [
- {
- "ml_class_id": str(uuid4()),
- "confidence": 0.75,
- "high_confidence": False,
- },
- {
- "ml_class_id": str(uuid4()),
- "confidence": 2.00,
- "high_confidence": False,
- },
- ],
- },
- "Classification at index 1 in classifications: confidence shouldn't be null and should be a float in [0..1] range",
+ "confidence",
+ 2.00,
+ "confidence shouldn't be null and should be a float in [0..1] range",
AssertionError,
),
# Wrong classifications > high_confidence
(
- {
- "element": Element({"id": "12341234-1234-1234-1234-123412341234"}),
- "classifications": [
- {
- "ml_class_id": str(uuid4()),
- "confidence": 0.75,
- "high_confidence": False,
- },
- {
- "ml_class_id": str(uuid4()),
- "confidence": 0.25,
- "high_confidence": "wrong high_confidence",
- },
- ],
- },
- "Classification at index 1 in classifications: high_confidence should be of type bool",
+ "high_confidence",
+ "wrong high_confidence",
+ "high_confidence should be of type bool",
AssertionError,
),
],
)
-def test_create_classifications_wrong_data(
- data, error_message, error_type, mock_elements_worker
+def test_create_classifications_wrong_classifications_data(
+ arg_name, data, error_message, error_type, mock_elements_worker
):
- with pytest.raises(error_type, match=re.escape(error_message)):
- mock_elements_worker.create_classifications(**data)
+ all_data = {
+ "element": Element({"id": "12341234-1234-1234-1234-123412341234"}),
+ "classifications": [
+ {
+ "ml_class_id": str(uuid4()),
+ "confidence": 0.75,
+ "high_confidence": False,
+ },
+ {
+ "ml_class_id": str(uuid4()),
+ "confidence": 0.25,
+ "high_confidence": False,
+ # Overwrite with wrong data
+ arg_name: data,
+ },
+ ],
+ }
+ if data == DELETE_PARAMETER:
+ del all_data["classifications"][1][arg_name]
+
+ with pytest.raises(
+ error_type,
+ match=re.escape(
+ f"Classification at index 1 in classifications: {error_message}"
+ ),
+ ):
+ mock_elements_worker.create_classifications(**all_data)
def test_create_classifications_api_error(responses, mock_elements_worker):