missing fixture

libs/labelbox/tests/conftest.py

@@ -6,6 +6,7 @@
 import os
 import re
 import uuid
+import time
 import requests
 from types import SimpleNamespace
 from enum import Enum
@@ -22,6 +23,20 @@
 from labelbox.schema.queue_mode import QueueMode
 from labelbox import Client
 
+from labelbox import Dataset, DataRow
+from labelbox import LabelingFrontend
+from labelbox import OntologyBuilder, Tool, Option, Classification, MediaType
+from labelbox.orm import query
+from labelbox.pagination import PaginatedCollection
+from labelbox.schema.annotation_import import LabelImport
+from labelbox.schema.catalog import Catalog
+from labelbox.schema.enums import AnnotationImportState
+from labelbox.schema.invite import Invite
+from labelbox.schema.quality_mode import QualityMode
+from labelbox.schema.queue_mode import QueueMode
+from labelbox.schema.user import User
+from labelbox import Client
+
 IMG_URL = "https://picsum.photos/200/300.jpg"
 MASKABLE_IMG_URL = "https://storage.googleapis.com/labelbox-datasets/image_sample_data/2560px-Kitano_Street_Kobe01s5s4110.jpeg"
 SMALL_DATASET_URL = "https://storage.googleapis.com/lb-artifacts-testing-public/sdk_integration_test/potato.jpeg"
@@ -576,3 +591,77 @@ def organization(client):
     for invite in get_invites(client):
         if "@labelbox.com" in invite.email:
             cancel_invite(client, invite.uid)
+
+
+@pytest.fixture
+def configured_project_with_label(client, rand_gen, image_url, project, dataset,
+                                  data_row, wait_for_label_processing):
+    """Project with a connected dataset, having one datarow
+    Project contains an ontology with 1 bbox tool
+    Additionally includes a create_label method for any needed extra labels
+    One label is already created and yielded when using fixture
+    """
+    project._wait_until_data_rows_are_processed(
+        data_row_ids=[data_row.uid],
+        wait_processing_max_seconds=DATA_ROW_PROCESSING_WAIT_TIMEOUT_SECONDS,
+        sleep_interval=DATA_ROW_PROCESSING_WAIT_SLEEP_INTERNAL_SECONDS)
+
+    project.create_batch(
+        rand_gen(str),
+        [data_row.uid],  # sample of data row objects
+        5  # priority between 1(Highest) - 5(lowest)
+    )
+    ontology = _setup_ontology(project)
+    label = _create_label(project, data_row, ontology,
+                          wait_for_label_processing)
+    yield [project, dataset, data_row, label]
+
+    for label in project.labels():
+        label.delete()
+
+
+def _create_label(project, data_row, ontology, wait_for_label_processing):
+    predictions = [{
+        "uuid": str(uuid.uuid4()),
+        "schemaId": ontology.tools[0].feature_schema_id,
+        "dataRow": {
+            "id": data_row.uid
+        },
+        "bbox": {
+            "top": 20,
+            "left": 20,
+            "height": 50,
+            "width": 50
+        }
+    }]
+
+    def create_label():
+        """ Ad-hoc function to create a LabelImport
+        Creates a LabelImport task which will create a label
+        """
+        upload_task = LabelImport.create_from_objects(
+            project.client, project.uid, f'label-import-{uuid.uuid4()}',
+            predictions)
+        upload_task.wait_until_done(sleep_time_seconds=5)
+        assert upload_task.state == AnnotationImportState.FINISHED, "Label Import did not finish"
+        assert len(
+            upload_task.errors
+        ) == 0, f"Label Import {upload_task.name} failed with errors {upload_task.errors}"
+
+    project.create_label = create_label
+    project.create_label()
+    label = wait_for_label_processing(project)[0]
+    return label
+
+
+def _setup_ontology(project):
+    editor = list(
+        project.client.get_labeling_frontends(
+            where=LabelingFrontend.name == "editor"))[0]
+    ontology_builder = OntologyBuilder(tools=[
+        Tool(tool=Tool.Type.BBOX, name="test-bbox-class"),
+    ])
+    project.setup(editor, ontology_builder.asdict())
+    # TODO: ontology may not be synchronous after setup. remove sleep when api is more consistent
+    time.sleep(2)
+    return OntologyBuilder.from_project(project)