Merge pull request #734 from Labelbox/ms/al-3814

data row content under row_data

Author: msokoloff1

labelbox/schema/data_row.py

@@ -1,5 +1,6 @@
 import logging
 from typing import TYPE_CHECKING
+import json
 
 from labelbox.orm import query
 from labelbox.orm.db_object import DbObject, Updateable, BulkDeletable
@@ -64,6 +65,14 @@ def __init__(self, *args, **kwargs):
         self.attachments.supports_filtering = False
         self.attachments.supports_sorting = False
 
+    def update(self, **kwargs):
+        # Convert row data to string if it is an object
+        # All other updates pass through
+        row_data = kwargs.get("row_data")
+        if isinstance(row_data, dict):
+            kwargs['row_data'] = json.dumps(kwargs['row_data'])
+        super().update(**kwargs)
+
     @staticmethod
     def bulk_delete(data_rows) -> None:
         """ Deletes all the given DataRows.

labelbox/schema/dataset.py

@@ -15,6 +15,7 @@
 from labelbox.exceptions import InvalidQueryError, LabelboxError, ResourceNotFoundError, InvalidAttributeError
 from labelbox.orm.db_object import DbObject, Updateable, Deletable
 from labelbox.orm.model import Entity, Field, Relationship
+from labelbox.orm import query
 from labelbox.exceptions import MalformedQueryException
 
 if TYPE_CHECKING:
@@ -95,18 +96,46 @@ def convert_field_keys(items):
             raise InvalidQueryError(
                 "DataRow.row_data missing when creating DataRow.")
 
-        # If row data is a local file path, upload it to server.
         row_data = args[DataRow.row_data.name]
-        if os.path.exists(row_data):
+        if not isinstance(row_data, str):
+            # If the row data is an object, upload as a string
+            args[DataRow.row_data.name] = json.dumps(row_data)
+        elif os.path.exists(row_data):
+            # If row data is a local file path, upload it to server.
             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.metadata_fields.name in args:
             mdo = self.client.get_data_row_metadata_ontology()
             args[DataRow.metadata_fields.name] = mdo.parse_upsert_metadata(
                 args[DataRow.metadata_fields.name])
-        return self.client._create(DataRow, args)
+
+        query_str = """mutation CreateDataRowPyApi(
+            $row_data: String!,
+            $metadata_fields: [DataRowCustomMetadataUpsertInput!],
+            $attachments: [DataRowAttachmentInput!],
+            $media_type : MediaType,
+            $external_id : String,
+            $global_key : String,
+            $dataset: ID!
+            ){
+                createDataRow(
+                    data:
+                      {
+                        rowData: $row_data
+                        mediaType: $media_type
+                        metadataFields: $metadata_fields
+                        externalId: $external_id
+                        globalKey: $global_key
+                        attachments: $attachments
+                        dataset: {connect: {id: $dataset}}
+                    }
+                   )
+                {%s}
+            }
+        """ % query.results_query_part(Entity.DataRow)
+        res = self.client.execute(query_str, {**args, 'dataset': self.uid})
+        return DataRow(self.client, res['createDataRow'])
 
     def create_data_rows_sync(self, items) -> None:
         """ Synchronously bulk upload data rows.
@@ -229,8 +258,8 @@ def _create_descriptor_file(self, items, max_attachments_per_data_row=None):
         >>>     {DataRow.row_data:"http://my_site.com/photos/img_01.jpg"},
         >>>     {DataRow.row_data:"/path/to/file1.jpg"},
         >>>     "path/to/file2.jpg",
-        >>>     {"tileLayerUrl" : "http://", ...}
-        >>>     {"conversationalData" : [...], ...}
+        >>>     {DataRow.row_data: {"tileLayerUrl" : "http://", ...}}
+        >>>     {DataRow.row_data: {"type" : ..., 'version' : ..., 'messages' : [...]}}
         >>>     ])
 
         For an example showing how to upload tiled data_rows see the following notebook:
@@ -258,7 +287,7 @@ def _create_descriptor_file(self, items, max_attachments_per_data_row=None):
 
         def upload_if_necessary(item):
             row_data = item['row_data']
-            if os.path.exists(row_data):
+            if isinstance(row_data, str) and os.path.exists(row_data):
                 item_url = self.client.upload_file(row_data)
                 item['row_data'] = item_url
                 if 'external_id' not in item:
@@ -341,40 +370,39 @@ def validate_keys(item):
                     "`row_data` missing when creating DataRow.")
 
             invalid_keys = set(item) - {
-                *{f.name for f in DataRow.fields()}, 'attachments'
+                *{f.name for f in DataRow.fields()}, 'attachments', 'media_type'
             }
             if invalid_keys:
                 raise InvalidAttributeError(DataRow, invalid_keys)
             return item
 
+        def formatLegacyConversationalData(item):
+            messages = item.pop("conversationalData")
+            version = item.pop("version", 1)
+            type = item.pop("type", "application/vnd.labelbox.conversational")
+            if "externalId" in item:
+                external_id = item.pop("externalId")
+                item["external_id"] = external_id
+            if "globalKey" in item:
+                global_key = item.pop("globalKey")
+                item["globalKey"] = global_key
+            validate_conversational_data(messages)
+            one_conversation = \
+                {
+                    "type": type,
+                    "version": version,
+                    "messages": messages
+                }
+            item["row_data"] = one_conversation
+            return item
+
         def convert_item(item):
-            # Don't make any changes to tms data
             if "tileLayerUrl" in item:
                 validate_attachments(item)
                 return item
 
             if "conversationalData" in item:
-                messages = item.pop("conversationalData")
-                version = item.pop("version")
-                type = item.pop("type")
-                if "externalId" in item:
-                    external_id = item.pop("externalId")
-                    item["external_id"] = external_id
-                if "globalKey" in item:
-                    global_key = item.pop("globalKey")
-                    item["globalKey"] = global_key
-                validate_conversational_data(messages)
-                one_conversation = \
-                    {
-                        "type": type,
-                        "version": version,
-                        "messages": messages
-                    }
-                conversationUrl = self.client.upload_data(
-                    json.dumps(one_conversation),
-                    content_type="application/json",
-                    filename="conversational_data.json")
-                item["row_data"] = conversationUrl
+                formatLegacyConversationalData(item)
 
             # Convert all payload variations into the same dict format
             item = format_row(item)
@@ -386,11 +414,7 @@ def convert_item(item):
             parse_metadata_fields(item)
             # Upload any local file paths
             item = upload_if_necessary(item)
-
-            return {
-                "data" if key == "row_data" else utils.camel_case(key): value
-                for key, value in item.items()
-            }
+            return item
 
         if not isinstance(items, Iterable):
             raise ValueError(

labelbox/schema/media_type.py

@@ -21,9 +21,9 @@ class MediaType(Enum):
 
     @classmethod
     def _missing_(cls, name):
-        """Handle missing null data types for projects 
+        """Handle missing null data types for projects
             created without setting allowedMediaType
-            Handle upper case names for compatibility with 
+            Handle upper case names for compatibility with
             the GraphQL"""
 
         if name is None:

tests/integration/test_data_row_media_attributes.py

@@ -7,4 +7,4 @@ def test_export_empty_media_attributes(configured_project_with_label):
     sleep(10)
     labels = project.label_generator()
     label = next(labels)
-    assert label.data.media_attributes == {}
+    assert label.data.media_attributes == {}

tests/integration/test_data_rows.py

@@ -1,6 +1,7 @@
 from tempfile import NamedTemporaryFile
 import uuid
 from datetime import datetime
+import json
 
 import pytest
 import requests
@@ -28,6 +29,56 @@ def mdo(client):
     yield mdo
 
 
+@pytest.fixture
+def conversational_content():
+    return {
+        'row_data': {
+            "messages": [{
+                "messageId": "message-0",
+                "timestampUsec": 1530718491,
+                "content": "I love iphone! i just bought new iphone! 🥰 📲",
+                "user": {
+                    "userId": "Bot 002",
+                    "name": "Bot"
+                },
+                "align": "left",
+                "canLabel": False
+            }],
+            "version": 1,
+            "type": "application/vnd.labelbox.conversational"
+        }
+    }
+
+
+@pytest.fixture
+def tile_content():
+    return {
+        "row_data": {
+            "tileLayerUrl":
+                "https://s3-us-west-1.amazonaws.com/lb-tiler-layers/mexico_city/{z}/{x}/{y}.png",
+            "bounds": [[19.405662413477728, -99.21052827588443],
+                       [19.400498983095076, -99.20534818927473]],
+            "minZoom":
+                12,
+            "maxZoom":
+                20,
+            "epsg":
+                "EPSG4326",
+            "alternativeLayers": [{
+                "tileLayerUrl":
+                    "https://api.mapbox.com/styles/v1/mapbox/satellite-streets-v11/tiles/{z}/{x}/{y}?access_token=pk.eyJ1IjoibWFwYm94IiwiYSI6ImNpejY4NXVycTA2emYycXBndHRqcmZ3N3gifQ.rJcFIG214AriISLbB6B5aw",
+                "name":
+                    "Satellite"
+            }, {
+                "tileLayerUrl":
+                    "https://api.mapbox.com/styles/v1/mapbox/navigation-guidance-night-v4/tiles/{z}/{x}/{y}?access_token=pk.eyJ1IjoibWFwYm94IiwiYSI6ImNpejY4NXVycTA2emYycXBndHRqcmZ3N3gifQ.rJcFIG214AriISLbB6B5aw",
+                "name":
+                    "Guidance"
+            }]
+        }
+    }
+
+
 def make_metadata_fields():
     embeddings = [0.0] * 128
     msg = "A message"
@@ -408,6 +459,18 @@ def test_data_row_update(dataset, rand_gen, image_url):
     data_row.update(external_id=external_id_2)
     assert data_row.external_id == external_id_2
 
+    in_line_content = "123"
+    data_row.update(row_data=in_line_content)
+    assert requests.get(data_row.row_data).text == in_line_content
+
+    data_row.update(row_data=image_url)
+    assert data_row.row_data == image_url
+
+    # tileLayer becomes a media attribute
+    pdf_url = "http://somepdfurl"
+    data_row.update(row_data={'pdfUrl': pdf_url, "tileLayerUrl": "123"})
+    assert data_row.row_data == pdf_url
+
 
 def test_data_row_filtering_sorting(dataset, image_url):
     task = dataset.create_data_rows([
@@ -696,3 +759,74 @@ def test_data_row_rulk_creation_sync_with_same_global_keys(
 
     assert len(list(dataset.data_rows())) == 1
     assert list(dataset.data_rows())[0].global_key == global_key_1
+
+
+def test_create_conversational_text(dataset, conversational_content):
+    examples = [
+        {
+            **conversational_content, 'media_type': 'CONVERSATIONAL'
+        },
+        conversational_content,
+        {
+            "conversationalData": conversational_content['row_data']['messages']
+        }  # Old way to check for backwards compatibility
+    ]
+    dataset.create_data_rows_sync(examples)
+    data_rows = list(dataset.data_rows())
+    assert len(data_rows) == len(examples)
+    for data_row in data_rows:
+        assert requests.get(
+            data_row.row_data).json() == conversational_content['row_data']
+
+
+def test_invalid_media_type(dataset, conversational_content):
+    for error_message, invalid_media_type in [[
+            "Found invalid contents for media type: 'IMAGE'", 'IMAGE'
+    ], ["Found invalid media type: 'totallyinvalid'", 'totallyinvalid']]:
+        # TODO: What error kind should this be? It looks like for global key we are
+        # using malformed query. But for invalid contents in FileUploads we use InvalidQueryError
+        with pytest.raises(labelbox.exceptions.InvalidQueryError):
+            dataset.create_data_rows_sync([{
+                **conversational_content, 'media_type': invalid_media_type
+            }])
+
+        task = dataset.create_data_rows([{
+            **conversational_content, 'media_type': invalid_media_type
+        }])
+        task.wait_till_done()
+        assert task.errors == {'message': error_message}
+
+
+def test_create_tiled_layer(dataset, tile_content):
+    examples = [
+        {
+            **tile_content, 'media_type': 'TMS_SIMPLE'
+        },
+        tile_content,
+        tile_content['row_data']  # Old way to check for backwards compatibility
+    ]
+    dataset.create_data_rows_sync(examples)
+    data_rows = list(dataset.data_rows())
+    assert len(data_rows) == len(examples)
+    for data_row in data_rows:
+        assert json.loads(data_row.row_data) == tile_content['row_data']
+
+
+def test_create_data_row_with_attachments(dataset):
+    attachment_value = 'attachment value'
+    dr = dataset.create_data_row(row_data="123",
+                                 attachments=[{
+                                     'type': 'TEXT',
+                                     'value': attachment_value
+                                 }])
+    attachments = list(dr.attachments())
+    assert len(attachments) == 1
+
+
+def test_create_data_row_with_media_type(dataset, image_url):
+    with pytest.raises(labelbox.exceptions.InvalidQueryError) as exc:
+        dr = dataset.create_data_row(
+            row_data={'invalid_object': 'invalid_value'}, media_type="IMAGE")
+    assert "Found invalid contents for media type: \'IMAGE\'" in str(exc.value)
+
+    dataset.create_data_row(row_data=image_url, media_type="IMAGE")