trying a fixture-based approach

Author: timmarkhuff

test/conftest.py

@@ -6,11 +6,17 @@
 from model import Detector, ImageQuery, ImageQueryTypeEnum, ResultTypeEnum
 
 
-def generate_test_detector_name(prefix: str = "Test") -> str:
-    """Generates a unique detector name with a timestamp and random suffix to avoid collisions in parallel CI."""
+def _generate_test_detector_name(prefix: str = "Test") -> str:
+    """Generates a detector name with a timestamp and random suffix to ensure uniqueness."""
     return f"{prefix} {datetime.utcnow().strftime('%Y-%m-%d %H:%M:%S')}_{uuid4().hex[:8]}"
 
 
+@pytest.fixture(name="generate_test_detector_name")
+def fixture_test_detector_name():
+    """Fixture that provides a callable to generate unique detector names."""
+    return _generate_test_detector_name
+
+
 def pytest_configure(config):  # pylint: disable=unused-argument
     # Run environment check before tests
     gl = Groundlight()
@@ -33,7 +39,7 @@ def fixture_detector(gl: Groundlight) -> Detector:
     """Creates a new Test detector."""
     query = "Is there a dog?"
     pipeline_config = "never-review"
-    return gl.create_detector(name=generate_test_detector_name(), query=query, pipeline_config=pipeline_config)
+    return gl.create_detector(name=_generate_test_detector_name(), query=query, pipeline_config=pipeline_config)
 
 
 @pytest.fixture(name="count_detector")
@@ -42,7 +48,7 @@ def fixture_count_detector(gl_experimental: ExperimentalApi) -> Detector:
     query = "How many dogs?"
     pipeline_config = "never-review-multi"  # always predicts 0
     return gl_experimental.create_counting_detector(
-        name=generate_test_detector_name(), query=query, class_name="dog", pipeline_config=pipeline_config
+        name=_generate_test_detector_name(), query=query, class_name="dog", pipeline_config=pipeline_config
     )
 
 

test/integration/test_groundlight.py

@@ -5,10 +5,9 @@
 import random
 import string
 import time
-from typing import Any, Dict, Optional, Union
+from typing import Any, Callable, Dict, Optional, Union
 
 import pytest
-from conftest import generate_test_detector_name
 from groundlight import Groundlight
 from groundlight.binary_labels import VALID_DISPLAY_LABELS, Label, convert_internal_label_to_display
 from groundlight.internalapi import ApiException, InternalApiError, NotFoundError
@@ -96,7 +95,7 @@ def test_create_groundlight_with_retries():
     assert gl.api_client.configuration.retries.total == retries.total
 
 
-def test_create_detector(gl: Groundlight):
+def test_create_detector(gl: Groundlight, generate_test_detector_name: Callable):
     name = generate_test_detector_name()
     query = "Is there a dog?"
     _detector = gl.create_detector(name=name, query=query)
@@ -117,7 +116,7 @@ def test_create_detector(gl: Groundlight):
     assert str(multiclass_detector)
 
 
-def test_create_detector_with_pipeline_config(gl: Groundlight):
+def test_create_detector_with_pipeline_config(gl: Groundlight, generate_test_detector_name: Callable):
     # "never-review" is a special model that always returns the same result with 100% confidence.
     # It's useful for testing.
     name = generate_test_detector_name("Test never-review")
@@ -128,7 +127,7 @@ def test_create_detector_with_pipeline_config(gl: Groundlight):
     assert isinstance(_detector, Detector)
 
 
-def test_create_detector_with_edge_pipeline_config(gl: Groundlight):
+def test_create_detector_with_edge_pipeline_config(gl: Groundlight, generate_test_detector_name: Callable):
     name = generate_test_detector_name("Test edge-pipeline-config")
     query = "Is there a dog (edge-config)?"
     _detector = gl.create_detector(
@@ -141,7 +140,7 @@ def test_create_detector_with_edge_pipeline_config(gl: Groundlight):
     assert isinstance(_detector, Detector)
 
 
-def test_create_detector_with_confidence_threshold(gl: Groundlight):
+def test_create_detector_with_confidence_threshold(gl: Groundlight, generate_test_detector_name: Callable):
     # "never-review" is a special model that always returns the same result with 100% confidence.
     # It's useful for testing.
     name = generate_test_detector_name("Test with confidence")
@@ -197,7 +196,7 @@ def test_create_detector_with_confidence_threshold(gl: Groundlight):
 
 
 @pytest.mark.skip_for_edge_endpoint(reason="The edge-endpoint does not support passing detector metadata.")
-def test_create_detector_with_everything(gl: Groundlight):
+def test_create_detector_with_everything(gl: Groundlight, generate_test_detector_name: Callable):
     name = generate_test_detector_name()
     query = "Is there a dog?"
     group_name = "Test group"
@@ -232,7 +231,7 @@ def test_list_detectors(gl: Groundlight):
     assert isinstance(detectors, PaginatedDetectorList)
 
 
-def test_get_or_create_detector(gl: Groundlight):
+def test_get_or_create_detector(gl: Groundlight, generate_test_detector_name: Callable):
     # With a unique name, we should be creating a new detector.
     unique_name = generate_test_detector_name()
     query = "Is there a dog?"
@@ -410,7 +409,7 @@ def test_submit_image_query_with_low_request_timeout(gl: Groundlight, detector:
 
 
 @pytest.mark.skip_for_edge_endpoint(reason="The edge-endpoint does not support passing detector metadata.")
-def test_create_detector_with_metadata(gl: Groundlight):
+def test_create_detector_with_metadata(gl: Groundlight, generate_test_detector_name: Callable):
     name = generate_test_detector_name()
     query = "Is there a dog?"
     metadata = generate_random_dict(target_size_bytes=200)
@@ -422,7 +421,7 @@ def test_create_detector_with_metadata(gl: Groundlight):
 
 
 @pytest.mark.skip_for_edge_endpoint(reason="The edge-endpoint does not support passing detector metadata.")
-def test_get_or_create_detector_with_metadata(gl: Groundlight):
+def test_get_or_create_detector_with_metadata(gl: Groundlight, generate_test_detector_name: Callable):
     unique_name = generate_test_detector_name()
     query = "Is there a dog?"
     metadata = generate_random_dict(target_size_bytes=200)
@@ -443,7 +442,7 @@ def test_get_or_create_detector_with_metadata(gl: Groundlight):
         [""],
     ],
 )
-def test_create_detector_with_invalid_metadata(gl: Groundlight, metadata_list: Any):
+def test_create_detector_with_invalid_metadata(gl: Groundlight, metadata_list: Any, generate_test_detector_name: Callable):
     name = generate_test_detector_name()
     query = "Is there a dog?"
 
@@ -627,7 +626,7 @@ def test_list_image_queries(gl: Groundlight):
             assert is_valid_display_result(image_query.result)
 
 
-def test_list_image_queries_with_filter(gl: Groundlight):
+def test_list_image_queries_with_filter(gl: Groundlight, generate_test_detector_name: Callable):
     # We want a fresh detector so we know exactly what image queries are associated with it
     detector = gl.create_detector(name=generate_test_detector_name(), query="Is there a dog?")
     image_query_yes = gl.ask_async(detector=detector.id, image="test/assets/dog.jpeg", human_review="NEVER")
@@ -855,7 +854,7 @@ def test_submit_image_query_with_empty_inspection_id(gl: Groundlight, detector:
     )
 
 
-def test_binary_detector(gl: Groundlight):
+def test_binary_detector(gl: Groundlight, generate_test_detector_name: Callable):
     """
     verify that we can create and submit to a binary detector
     """
@@ -866,7 +865,7 @@ def test_binary_detector(gl: Groundlight):
     assert binary_iq.result.label is not None
 
 
-def test_counting_detector(gl: Groundlight):
+def test_counting_detector(gl: Groundlight, generate_test_detector_name: Callable):
     """
     verify that we can create and submit to a counting detector
     """
@@ -877,7 +876,7 @@ def test_counting_detector(gl: Groundlight):
     assert count_iq.result.count is not None
 
 
-def test_counting_detector_async(gl: Groundlight):
+def test_counting_detector_async(gl: Groundlight, generate_test_detector_name: Callable):
     """
     verify that we can create and submit to a counting detector
     """
@@ -896,7 +895,7 @@ def test_counting_detector_async(gl: Groundlight):
     assert _image_query.result is not None
 
 
-def test_multiclass_detector(gl: Groundlight):
+def test_multiclass_detector(gl: Groundlight, generate_test_detector_name: Callable):
     """
     verify that we can create and submit to a multi-class detector
     """
@@ -911,7 +910,7 @@ def test_multiclass_detector(gl: Groundlight):
     assert mc_iq.result.label in class_names
 
 
-def test_delete_detector(gl: Groundlight):
+def test_delete_detector(gl: Groundlight, generate_test_detector_name: Callable):
     """
     Test deleting a detector by both ID and object, and verify proper error handling.
     """
@@ -952,7 +951,7 @@ def test_delete_detector(gl: Groundlight):
         gl.delete_detector(fake_detector_id)  # type: ignore
 
 
-def test_create_detector_with_invalid_priming_group_id(gl: Groundlight):
+def test_create_detector_with_invalid_priming_group_id(gl: Groundlight, generate_test_detector_name: Callable):
     """
     Test that creating a detector with a non-existent priming_group_id returns an appropriate error.
 

test/integration/test_groundlight_expensive.py

@@ -7,9 +7,9 @@
 # pylint: disable=wildcard-import,unused-wildcard-import,redefined-outer-name,import-outside-toplevel
 import random
 import time
+from typing import Callable
 
 import pytest
-from conftest import generate_test_detector_name
 from groundlight import Groundlight
 from groundlight.internalapi import iq_is_answered, iq_is_confident
 from groundlight.optional_imports import *
@@ -30,7 +30,7 @@ def fixture_gl() -> Groundlight:
 
 
 @pytest.mark.skip(reason="This test requires a human labeler who does not need to be in the testing loop")
-def test_human_label(gl: Groundlight):
+def test_human_label(gl: Groundlight, generate_test_detector_name: Callable):
     detector = gl.create_detector(name=generate_test_detector_name(), query="Is there a dog?")
     img_query = gl.submit_image_query(
         detector=detector.id, image="test/assets/dog.jpeg", wait=60, human_review="ALWAYS"
@@ -52,7 +52,7 @@ def test_human_label(gl: Groundlight):
 
 @pytest.mark.skip(reason="This test can block development depending on the state of the service")
 @pytest.mark.skipif(MISSING_PIL, reason="Needs pillow")  # type: ignore
-def test_detector_improvement(gl: Groundlight):
+def test_detector_improvement(gl: Groundlight, generate_test_detector_name: Callable):
     # test that we get confidence improvement after sending images in
     # Pass two of each type of image in
     import time
@@ -122,7 +122,7 @@ def submit_noisy_image(image, label=None):
 @pytest.mark.skip(
     reason="We don't yet have an SLA level to test ask_confident against, and the test is flakey as a result"
 )
-def test_ask_method_quality(gl: Groundlight, detector: Detector):
+def test_ask_method_quality(gl: Groundlight, detector: Detector, generate_test_detector_name: Callable):
     # asks for some level of quality on how fast ask_ml is and that we will get a confident result from ask_confident
     fast_always_yes_iq = gl.ask_ml(detector=detector.id, image="test/assets/dog.jpeg", wait=0)
     assert iq_is_answered(fast_always_yes_iq)

test/unit/test_cli.py

@@ -1,10 +1,9 @@
 import os
 import re
 import subprocess
+from typing import Callable
 from unittest.mock import patch
 
-from conftest import generate_test_detector_name
-
 
 def test_whoami():
     completed_process = subprocess.run(
@@ -24,7 +23,7 @@ def test_list_detector():
     assert completed_process.returncode == 0
 
 
-def test_detector_and_image_queries():
+def test_detector_and_image_queries(generate_test_detector_name: Callable):
     # test creating a detector
     test_detector_name = generate_test_detector_name("testdetector")
     completed_process = subprocess.run(

test/unit/test_detector_reset.py

@@ -1,13 +1,13 @@
 import time
+from typing import Callable
 
 import pytest
-from conftest import generate_test_detector_name
 from groundlight import ExperimentalApi
 from groundlight_openapi_client.exceptions import NotFoundException
 
 
 @pytest.mark.skip(reason="This is an expensive test, reset may take some time")
-def test_reset_retry(gl_experimental: ExperimentalApi):
+def test_reset_retry(gl_experimental: ExperimentalApi, generate_test_detector_name: Callable):
     # Reset the detector, retrying in case the reset is still ongoing
     det = gl_experimental.create_detector(generate_test_detector_name(), "test_query")
     iq = gl_experimental.submit_image_query(det, "test/assets/cat.jpeg")
@@ -27,7 +27,7 @@ def test_reset_retry(gl_experimental: ExperimentalApi):
 
 
 @pytest.mark.skip(reason="This test does not work with strong 0 shot models, enabled by default based on your account")
-def test_reset_training(gl_experimental: ExperimentalApi):
+def test_reset_training(gl_experimental: ExperimentalApi, generate_test_detector_name: Callable):
     # If we reset a detector, we should have low confidence after the reset
     low_confidence_threshold = 0.6
     det = gl_experimental.create_detector(generate_test_detector_name(), "is this a cat")

test/unit/test_experimental.py

@@ -1,12 +1,12 @@
 import time
+from typing import Callable
 
 import pytest
-from conftest import generate_test_detector_name
 from groundlight import ExperimentalApi
 from model import Detector, ImageQuery
 
 
-def test_detector_groups(gl_experimental: ExperimentalApi):
+def test_detector_groups(gl_experimental: ExperimentalApi, generate_test_detector_name: Callable):
     """
     verify that we can create a detector group and retrieve it
     """
@@ -30,7 +30,7 @@ def test_update_detector_confidence_threshold(gl_experimental: ExperimentalApi,
     assert updated_detector.confidence_threshold == newer_confidence
 
 
-def test_update_detector_name(gl_experimental: ExperimentalApi, detector: Detector):
+def test_update_detector_name(gl_experimental: ExperimentalApi, detector: Detector, generate_test_detector_name: Callable):
     """
     verify that we can update the name of a detector
     """
@@ -40,7 +40,7 @@ def test_update_detector_name(gl_experimental: ExperimentalApi, detector: Detect
     assert updated_detector.name == new_name
 
 
-def test_update_detector_status(gl_experimental: ExperimentalApi):
+def test_update_detector_status(gl_experimental: ExperimentalApi, generate_test_detector_name: Callable):
     """
     verify that we can update the status of a detector
     """
@@ -53,7 +53,7 @@ def test_update_detector_status(gl_experimental: ExperimentalApi):
     assert updated_detector.status.value == "ON"
 
 
-def test_update_detector_escalation_type(gl_experimental: ExperimentalApi):
+def test_update_detector_escalation_type(gl_experimental: ExperimentalApi, generate_test_detector_name: Callable):
     """
     verify that we can update the escalation type of a detector
     """
@@ -90,7 +90,7 @@ def test_submit_multiple_rois(gl_experimental: ExperimentalApi, image_query_one:
     gl_experimental.add_label(image_query_one, 3, [roi] * 3)
 
 
-def test_text_recognition_detector(gl_experimental: ExperimentalApi):
+def test_text_recognition_detector(gl_experimental: ExperimentalApi, generate_test_detector_name: Callable):
     """
     verify that we can create and submit to a text recognition detector
     """
@@ -103,7 +103,7 @@ def test_text_recognition_detector(gl_experimental: ExperimentalApi):
     assert mc_iq.result.text is not None
 
 
-def test_bounding_box_detector(gl_experimental: ExperimentalApi):
+def test_bounding_box_detector(gl_experimental: ExperimentalApi, generate_test_detector_name: Callable):
     """
     Verify that we can create and submit to a bounding box detector
     """
@@ -117,7 +117,7 @@ def test_bounding_box_detector(gl_experimental: ExperimentalApi):
     assert bbox_iq.rois is not None
 
 
-def test_bounding_box_detector_async(gl_experimental: ExperimentalApi):
+def test_bounding_box_detector_async(gl_experimental: ExperimentalApi, generate_test_detector_name: Callable):
     """
     Verify that we can create and submit to a bounding box detector with ask_async
     """