pr comments

Author: Grant Eaton

labelbox/schema/annotation_import.py

@@ -266,7 +266,7 @@ def from_name(cls,
 
     @classmethod
     def _get_url_mutation(cls) -> str:
-        return """mutation createMEAPredictionImportPyApi($modelRunId : ID!, $name: String!, $fileUrl: String!) {
+        return """mutation createMEAPredictionImportByUrlPyApi($modelRunId : ID!, $name: String!, $fileUrl: String!) {
             createModelErrorAnalysisPredictionImport(data: {
                 modelRunId: $modelRunId
                 name: $name
@@ -276,7 +276,7 @@ def _get_url_mutation(cls) -> str:
 
     @classmethod
     def _get_file_mutation(cls) -> str:
-        return """mutation createMEAPredictionImportPyApi($modelRunId : ID!, $name: String!, $file: Upload!, $contentLength: Int!) {
+        return """mutation createMEAPredictionImportByFilePyApi($modelRunId : ID!, $name: String!, $file: Upload!, $contentLength: Int!) {
             createModelErrorAnalysisPredictionImport(data: {
                 modelRunId: $modelRunId name: $name filePayload: { file: $file, contentLength: $contentLength}
         }) {%s}
@@ -423,7 +423,7 @@ def from_name(cls,
 
     @classmethod
     def _get_url_mutation(cls) -> str:
-        return """mutation createMALPredictionImportPyApi($projectId : ID!, $name: String!, $fileUrl: String!) {
+        return """mutation createMALPredictionImportByUrlPyApi($projectId : ID!, $name: String!, $fileUrl: String!) {
             createModelAssistedLabelingPredictionImport(data: {
                 projectId: $projectId
                 name: $name
@@ -433,7 +433,7 @@ def _get_url_mutation(cls) -> str:
 
     @classmethod
     def _get_file_mutation(cls) -> str:
-        return """mutation createMALPredictionImportPyApi($projectId : ID!, $name: String!, $file: Upload!, $contentLength: Int!) {
+        return """mutation createMALPredictionImportByFilePyApi($projectId : ID!, $name: String!, $file: Upload!, $contentLength: Int!) {
             createModelAssistedLabelingPredictionImport(data: {
                 projectId: $projectId name: $name filePayload: { file: $file, contentLength: $contentLength}
         }) {%s}
@@ -493,7 +493,7 @@ def create_from_objects(cls, client: "labelbox.Client", project_id: str,
                             name: str,
                             labels: List[Dict[str, Any]]) -> "LabelImport":
         """
-        Create an label import job from an in memory dictionary
+        Create a label import job from an in memory dictionary
 
         Args:
             client: Labelbox Client for executing queries
@@ -514,7 +514,7 @@ def create_from_objects(cls, client: "labelbox.Client", project_id: str,
     def create_from_url(cls, client: "labelbox.Client", project_id: str,
                         name: str, url: str) -> "LabelImport":
         """
-        Create an label annotation import job from a url
+        Create a label annotation import job from a url
         The url must point to a file containing label annotations.
 
         Args:
@@ -573,7 +573,7 @@ def from_name(cls,
 
     @classmethod
     def _get_url_mutation(cls) -> str:
-        return """mutation createLabelImportPyApi($projectId : ID!, $name: String!, $fileUrl: String!) {
+        return """mutation createLabelImportByUrlPyApi($projectId : ID!, $name: String!, $fileUrl: String!) {
             createLabelImport(data: {
                 projectId: $projectId
                 name: $name
@@ -583,7 +583,7 @@ def _get_url_mutation(cls) -> str:
 
     @classmethod
     def _get_file_mutation(cls) -> str:
-        return """mutation createLabelImportPyApi($projectId : ID!, $name: String!, $file: Upload!, $contentLength: Int!) {
+        return """mutation createLabelImportByFilePyApi($projectId : ID!, $name: String!, $file: Upload!, $contentLength: Int!) {
             createLabelImport(data: {
                 projectId: $projectId name: $name filePayload: { file: $file, contentLength: $contentLength}
         }) {%s}

test.py

@@ -0,0 +1,10 @@
+from labelbox import Client
+import os
+from labelbox.schema.annotation_import import MEAPredictionImport
+from labelbox.schema.annotation_import import MALPredictionImport
+from labelbox.schema.annotation_import import LabelImport
+client = Client(api_key="eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJ1c2VySWQiOiJja3RxcTdmMjcwMDAxZ3dzYjh1b28yanduIiwib3JnYW5pemF0aW9uSWQiOiJja3RxcTdmMDkwMDAwZ3dzYmh0c2RmZmlsIiwiaWF0IjoxNjMyMDI2MTA4LCJleHAiOjE2MzI2MzA5MDh9.F4yQsuq1L-XFX4WiN9duf0s9xxpHZUn3YkMSJd4ZG1Y", endpoint="http://localhost:8080/_gql")
+b = LabelImport.create_from_url(client, "ckhmkoa24001e0789rf41gm3p", "test-label-import-1",
+                                 "https://storage.labelbox.com/ckk4q1vgapsau07324awnsjq2%2F388e1da0-5a2e-56b0-227f-18e452e6ac1f-1?Expires=1622247070155&KeyName=labelbox-assets-key-3&Signature=UdKsAaYAMYg0WSGZqApHoyR87Us")
+# b = LabelImport.from_name(client, "ckhmkoa24001e0789rf41gm3p", "test-label-import-1")
+print(b)

tests/integration/annotation_import/test_label_import.py

@@ -55,25 +55,25 @@ def test_get(client, project, annotation_import_test_helpers):
 
 
 @pytest.mark.slow
-def test_wait_till_done(client, project, model_run_predictions):
+def test_wait_till_done(client, project, predictions):
     name = str(uuid.uuid4())
-    label_import = LabelImport.create_from_objects(client=client, project_id=project.uid, name=name, labels=model_run_predictions)
+    label_import = LabelImport.create_from_objects(client=client, project_id=project.uid, name=name, labels=predictions)
 
-    assert len(label_import.inputs) == len(model_run_predictions)
+    assert len(label_import.inputs) == len(predictions)
     label_import.wait_until_done()
     # TODO(grant): some of this is commented out
     # TODO(grant): since the pipeline is not complete, you will get a failed status
 
     # assert label_import.state == AnnotationImportState.FINISHED
     # # Check that the status files are being returned as expected
     # assert len(label_import.errors) == 0
-    assert len(label_import.inputs) == len(model_run_predictions)
+    assert len(label_import.inputs) == len(predictions)
     input_uuids = [
         input_annot['uuid'] for input_annot in label_import.inputs
     ]
-    inference_uuids = [pred['uuid'] for pred in model_run_predictions]
+    inference_uuids = [pred['uuid'] for pred in predictions]
     assert set(input_uuids) == set(inference_uuids)
-    assert len(label_import.statuses) == len(model_run_predictions)
+    assert len(label_import.statuses) == len(predictions)
     # for status in label_import.statuses:
     #     assert status['status'] == 'SUCCESS'
     status_uuids = [