Merge pull request #578 from Labelbox/kkim/AL-2496

[AL-2496] [AL-2498] Rename custom_metadata to metadata_fields for DataRow

Author: kkim-labelbox

labelbox/schema/batch.py

@@ -104,9 +104,9 @@ def export_data_rows(self, timeout_seconds=120) -> Generator:
                 response = requests.get(download_url)
                 response.raise_for_status()
                 reader = ndjson.reader(StringIO(response.text))
-                # TODO: Update result to parse customMetadata when resolver returns
+                # TODO: Update result to parse metadataFields when resolver returns
                 return (Entity.DataRow(self.client, {
-                    **result, 'customMetadata': []
+                    **result, 'metadataFields': []
                 }) for result in reader)
             elif res["status"] == "FAILED":
                 raise LabelboxError("Data row export failed.")

labelbox/schema/data_row.py

@@ -22,7 +22,7 @@ class DataRow(DbObject, Updateable, BulkDeletable):
         updated_at (datetime)
         created_at (datetime)
         media_attributes (dict): generated media attributes for the datarow
-        custom_metadata (list): metadata associated with the datarow
+        metadata_fields (list): metadata associated with the datarow
 
         dataset (Relationship): `ToOne` relationship to Dataset
         created_by (Relationship): `ToOne` relationship to User
@@ -35,11 +35,11 @@ class DataRow(DbObject, Updateable, BulkDeletable):
     updated_at = Field.DateTime("updated_at")
     created_at = Field.DateTime("created_at")
     media_attributes = Field.Json("media_attributes")
-    custom_metadata = Field.List(
+    metadata_fields = Field.List(
         DataRowMetadataField,
         graphql_type="DataRowCustomMetadataUpsertInput!",
-        name="custom_metadata",
-        result_subquery="customMetadata { value schemaId }")
+        name="metadata_fields",
+        result_subquery="metadataFields { schemaId name value kind }")
 
     # Relationships
     dataset = Relationship.ToOne("Dataset")

labelbox/schema/dataset.py

@@ -52,40 +52,57 @@ class Dataset(DbObject, Updateable, Deletable):
     iam_integration = Relationship.ToOne("IAMIntegration", False,
                                          "iam_integration", "signer")
 
-    def create_data_row(self, **kwargs) -> "DataRow":
+    def create_data_row(self, items=None, **kwargs) -> "DataRow":
         """ Creates a single DataRow belonging to this dataset.
 
         >>> dataset.create_data_row(row_data="http://my_site.com/photos/img_01.jpg")
 
         Args:
+            items: Dictionary containing new `DataRow` data. At a minimum,
+                must contain `row_data` or `DataRow.row_data`.
             **kwargs: Key-value arguments containing new `DataRow` data. At a minimum,
                 must contain `row_data`.
 
         Raises:
+            InvalidQueryError: If both dictionary and `kwargs` are provided as inputs
             InvalidQueryError: If `DataRow.row_data` field value is not provided
                 in `kwargs`.
             InvalidAttributeError: in case the DB object type does not contain
                 any of the field names given in `kwargs`.
 
         """
+        invalid_argument_error = "Argument to create_data_row() must be either a dictionary, or kwargs containing `row_data` at minimum"
+
+        def convert_field_keys(items):
+            if not isinstance(items, dict):
+                raise InvalidQueryError(invalid_argument_error)
+            return {
+                key.name if isinstance(key, Field) else key: value
+                for key, value in items.items()
+            }
+
+        if items is not None and len(kwargs) > 0:
+            raise InvalidQueryError(invalid_argument_error)
+
         DataRow = Entity.DataRow
-        if DataRow.row_data.name not in kwargs:
+        args = convert_field_keys(items) if items is not None else kwargs
+
+        if DataRow.row_data.name not in args:
             raise InvalidQueryError(
                 "DataRow.row_data missing when creating DataRow.")
 
         # If row data is a local file path, upload it to server.
-        row_data = kwargs[DataRow.row_data.name]
+        row_data = args[DataRow.row_data.name]
         if os.path.exists(row_data):
-            kwargs[DataRow.row_data.name] = self.client.upload_file(row_data)
-        kwargs[DataRow.dataset.name] = self
+            args[DataRow.row_data.name] = self.client.upload_file(row_data)
+        args[DataRow.dataset.name] = self
 
         # Parse metadata fields, if they are provided
-        if DataRow.custom_metadata.name in kwargs:
+        if DataRow.metadata_fields.name in args:
             mdo = self.client.get_data_row_metadata_ontology()
-            kwargs[DataRow.custom_metadata.name] = mdo.parse_upsert_metadata(
-                kwargs[DataRow.custom_metadata.name])
-
-        return self.client._create(DataRow, kwargs)
+            args[DataRow.metadata_fields.name] = mdo.parse_upsert_metadata(
+                args[DataRow.metadata_fields.name])
+        return self.client._create(DataRow, args)
 
     def create_data_rows_sync(self, items) -> None:
         """ Synchronously bulk upload data rows.
@@ -264,10 +281,10 @@ def validate_attachments(item):
             return attachments
 
         def parse_metadata_fields(item):
-            metadata_fields = item.get('custom_metadata')
+            metadata_fields = item.get('metadata_fields')
             if metadata_fields:
                 mdo = self.client.get_data_row_metadata_ontology()
-                item['custom_metadata'] = mdo.parse_upsert_metadata(
+                item['metadata_fields'] = mdo.parse_upsert_metadata(
                     metadata_fields)
 
         def format_row(item):
@@ -413,9 +430,9 @@ def export_data_rows(self, timeout_seconds=120) -> Generator:
                 response = requests.get(download_url)
                 response.raise_for_status()
                 reader = ndjson.reader(StringIO(response.text))
-                # TODO: Update result to parse customMetadata when resolver returns
+                # TODO: Update result to parse metadataFields when resolver returns
                 return (Entity.DataRow(self.client, {
-                    **result, 'customMetadata': []
+                    **result, 'metadataFields': []
                 }) for result in reader)
             elif res["status"] == "FAILED":
                 raise LabelboxError("Data row export failed.")

tests/integration/test_data_rows.py

@@ -1,3 +1,4 @@
+import imghdr
 from tempfile import NamedTemporaryFile
 import uuid
 import time
@@ -177,12 +178,63 @@ def test_data_row_single_creation(dataset, rand_gen, image_url):
         assert requests.get(data_row_2.row_data).content == data
 
 
+def test_create_data_row_with_dict(dataset, image_url):
+    client = dataset.client
+    assert len(list(dataset.data_rows())) == 0
+    dr = {"row_data": image_url}
+    data_row = dataset.create_data_row(dr)
+    assert len(list(dataset.data_rows())) == 1
+    assert data_row.dataset() == dataset
+    assert data_row.created_by() == client.get_user()
+    assert data_row.organization() == client.get_organization()
+    assert requests.get(image_url).content == \
+        requests.get(data_row.row_data).content
+    assert data_row.media_attributes is not None
+
+
+def test_create_data_row_with_dict_containing_field(dataset, image_url):
+    client = dataset.client
+    assert len(list(dataset.data_rows())) == 0
+    dr = {DataRow.row_data: image_url}
+    data_row = dataset.create_data_row(dr)
+    assert len(list(dataset.data_rows())) == 1
+    assert data_row.dataset() == dataset
+    assert data_row.created_by() == client.get_user()
+    assert data_row.organization() == client.get_organization()
+    assert requests.get(image_url).content == \
+        requests.get(data_row.row_data).content
+    assert data_row.media_attributes is not None
+
+
+def test_create_data_row_with_dict_unpacked(dataset, image_url):
+    client = dataset.client
+    assert len(list(dataset.data_rows())) == 0
+    dr = {"row_data": image_url}
+    data_row = dataset.create_data_row(**dr)
+    assert len(list(dataset.data_rows())) == 1
+    assert data_row.dataset() == dataset
+    assert data_row.created_by() == client.get_user()
+    assert data_row.organization() == client.get_organization()
+    assert requests.get(image_url).content == \
+        requests.get(data_row.row_data).content
+    assert data_row.media_attributes is not None
+
+
+def test_create_data_row_with_invalid_input(dataset, image_url):
+    with pytest.raises(labelbox.exceptions.InvalidQueryError) as exc:
+        dataset.create_data_row("asdf")
+
+    dr = {"row_data": image_url}
+    with pytest.raises(labelbox.exceptions.InvalidQueryError) as exc:
+        dataset.create_data_row(dr, row_data=image_url)
+
+
 def test_create_data_row_with_metadata(dataset, image_url):
     client = dataset.client
     assert len(list(dataset.data_rows())) == 0
 
     data_row = dataset.create_data_row(row_data=image_url,
-                                       custom_metadata=make_metadata_fields())
+                                       metadata_fields=make_metadata_fields())
 
     assert len(list(dataset.data_rows())) == 1
     assert data_row.dataset() == dataset
@@ -191,8 +243,8 @@ def test_create_data_row_with_metadata(dataset, image_url):
     assert requests.get(image_url).content == \
         requests.get(data_row.row_data).content
     assert data_row.media_attributes is not None
-    assert len(data_row.custom_metadata) == 5
-    assert [m["schemaId"] for m in data_row.custom_metadata
+    assert len(data_row.metadata_fields) == 4
+    assert [m["schemaId"] for m in data_row.metadata_fields
            ].sort() == EXPECTED_METADATA_SCHEMA_IDS
 
 
@@ -201,7 +253,7 @@ def test_create_data_row_with_metadata_dict(dataset, image_url):
     assert len(list(dataset.data_rows())) == 0
 
     data_row = dataset.create_data_row(
-        row_data=image_url, custom_metadata=make_metadata_fields_dict())
+        row_data=image_url, metadata_fields=make_metadata_fields_dict())
 
     assert len(list(dataset.data_rows())) == 1
     assert data_row.dataset() == dataset
@@ -210,8 +262,8 @@ def test_create_data_row_with_metadata_dict(dataset, image_url):
     assert requests.get(image_url).content == \
         requests.get(data_row.row_data).content
     assert data_row.media_attributes is not None
-    assert len(data_row.custom_metadata) == 5
-    assert [m["schemaId"] for m in data_row.custom_metadata
+    assert len(data_row.metadata_fields) == 4
+    assert [m["schemaId"] for m in data_row.metadata_fields
            ].sort() == EXPECTED_METADATA_SCHEMA_IDS
 
 
@@ -221,7 +273,7 @@ def test_create_data_row_with_invalid_metadata(dataset, image_url):
         DataRowMetadataField(schema_id=EMBEDDING_SCHEMA_ID, value=[0.0] * 128))
 
     with pytest.raises(labelbox.exceptions.MalformedQueryException) as excinfo:
-        dataset.create_data_row(row_data=image_url, custom_metadata=fields)
+        dataset.create_data_row(row_data=image_url, metadata_fields=fields)
 
 
 def test_create_data_rows_with_metadata(dataset, image_url):
@@ -232,22 +284,22 @@ def test_create_data_rows_with_metadata(dataset, image_url):
         {
             DataRow.row_data: image_url,
             DataRow.external_id: "row1",
-            DataRow.custom_metadata: make_metadata_fields()
+            DataRow.metadata_fields: make_metadata_fields()
         },
         {
             DataRow.row_data: image_url,
             DataRow.external_id: "row2",
-            "custom_metadata": make_metadata_fields()
+            "metadata_fields": make_metadata_fields()
         },
         {
             DataRow.row_data: image_url,
             DataRow.external_id: "row3",
-            DataRow.custom_metadata: make_metadata_fields_dict()
+            DataRow.metadata_fields: make_metadata_fields_dict()
         },
         {
             DataRow.row_data: image_url,
             DataRow.external_id: "row4",
-            "custom_metadata": make_metadata_fields_dict()
+            "metadata_fields": make_metadata_fields_dict()
         },
     ])
     task.wait_till_done()
@@ -261,8 +313,8 @@ def test_create_data_rows_with_metadata(dataset, image_url):
         assert requests.get(image_url).content == \
             requests.get(row.row_data).content
         assert row.media_attributes is not None
-        assert len(row.custom_metadata) == 5
-        assert [m["schemaId"] for m in row.custom_metadata
+        assert len(row.metadata_fields) == 4
+        assert [m["schemaId"] for m in row.metadata_fields
                ].sort() == EXPECTED_METADATA_SCHEMA_IDS
 
 
@@ -273,7 +325,7 @@ def test_create_data_rows_with_invalid_metadata(dataset, image_url):
 
     task = dataset.create_data_rows([{
         DataRow.row_data: image_url,
-        DataRow.custom_metadata: fields
+        DataRow.metadata_fields: fields
     }])
     task.wait_till_done()
     assert task.status == "FAILED"
@@ -288,7 +340,7 @@ def test_create_data_rows_with_metadata_missing_value(dataset, image_url):
             {
                 DataRow.row_data: image_url,
                 DataRow.external_id: "row1",
-                DataRow.custom_metadata: fields
+                DataRow.metadata_fields: fields
             },
         ])
 
@@ -302,7 +354,7 @@ def test_create_data_rows_with_metadata_missing_schema_id(dataset, image_url):
             {
                 DataRow.row_data: image_url,
                 DataRow.external_id: "row1",
-                DataRow.custom_metadata: fields
+                DataRow.metadata_fields: fields
             },
         ])
 
@@ -316,7 +368,7 @@ def test_create_data_rows_with_metadata_wrong_type(dataset, image_url):
             {
                 DataRow.row_data: image_url,
                 DataRow.external_id: "row1",
-                DataRow.custom_metadata: fields
+                DataRow.metadata_fields: fields
             },
         ])