[PLT-1487] Remaining sdk deprecated items removed (#1853)

Author: Gabefire

libs/labelbox/src/labelbox/__init__.py

@@ -59,7 +59,6 @@
 from labelbox.schema.project_resource_tag import ProjectResourceTag
 from labelbox.schema.media_type import MediaType
 from labelbox.schema.slice import Slice, CatalogSlice, ModelSlice
-from labelbox.schema.queue_mode import QueueMode
 from labelbox.schema.task_queue import TaskQueue
 from labelbox.schema.label_score import LabelScore
 from labelbox.schema.identifiables import UniqueIds, GlobalKeys, DataRowIds

libs/labelbox/src/labelbox/client.py

@@ -72,7 +72,6 @@
     CONSENSUS_AUTO_AUDIT_PERCENTAGE,
     QualityMode,
 )
-from labelbox.schema.queue_mode import QueueMode
 from labelbox.schema.role import Role
 from labelbox.schema.search_filters import SearchFilter
 from labelbox.schema.send_to_annotate_params import (
@@ -468,13 +467,11 @@ def _create(self, db_object_type, data, extra_params={}):
         res = self.execute(
             query_string, params, raise_return_resource_not_found=True
         )
-
         if not res:
             raise LabelboxError(
                 "Failed to create %s" % db_object_type.type_name()
             )
         res = res["create%s" % db_object_type.type_name()]
-
         return db_object_type(self, res)
 
     def create_model_config(
@@ -621,7 +618,6 @@ def create_project(
             name (str): A name for the project
             description (str): A short summary for the project
             media_type (MediaType): The type of assets that this project will accept
-            queue_mode (Optional[QueueMode]): The queue mode to use
             quality_modes (Optional[List[QualityMode]]): The quality modes to use (e.g. Benchmark, Consensus). Defaults to
                 Benchmark.
             is_benchmark_enabled (Optional[bool]): Whether the project supports benchmark. Defaults to None.
@@ -853,11 +849,7 @@ def create_response_creation_project(
         return self._create_project(_CoreProjectInput(**input))
 
     def _create_project(self, input: _CoreProjectInput) -> Project:
-        media_type_value = input.media_type.value
-
         params = input.model_dump(exclude_none=True)
-        if media_type_value:
-            params["media_type"] = media_type_value
 
         extra_params = {
             Field.String("dataset_name_or_id"): params.pop(
@@ -1644,10 +1636,6 @@ def get_data_row_ids_for_global_keys(
         """
         Gets data row ids for a list of global keys.
 
-        Deprecation Notice: This function will soon no longer return 'Deleted Data Rows'
-        as part of the 'results'. Global keys for deleted data rows will soon be placed
-        under 'Data Row not found' portion.
-
         Args:
             A list of global keys
         Returns:

libs/labelbox/src/labelbox/data/annotation_types/collection.py

@@ -25,21 +25,6 @@ def __init__(self, data: Generator[Label, None, None], *args, **kwargs):
         self._fns = {}
         super().__init__(data, *args, **kwargs)
 
-    def assign_feature_schema_ids(
-        self, ontology_builder: "ontology.OntologyBuilder"
-    ) -> "LabelGenerator":
-        def _assign_ids(label: Label):
-            label.assign_feature_schema_ids(ontology_builder)
-            return label
-
-        warnings.warn(
-            "This method is deprecated and will be "
-            "removed in a future release. Feature schema ids"
-            " are no longer required for importing."
-        )
-        self._fns["assign_feature_schema_ids"] = _assign_ids
-        return self
-
     def add_url_to_masks(
         self, signer: Callable[[bytes], str]
     ) -> "LabelGenerator":

libs/labelbox/src/labelbox/data/annotation_types/label.py

@@ -136,42 +136,6 @@ def create_data_row(
             self.data.external_id = data_row.external_id
         return self
 
-    def assign_feature_schema_ids(
-        self, ontology_builder: ontology.OntologyBuilder
-    ) -> "Label":
-        """
-        Adds schema ids to all FeatureSchema objects in the Labels.
-
-        Args:
-            ontology_builder: The ontology that matches the feature names assigned to objects in this dataset
-        Returns:
-            Label. useful for chaining these modifying functions
-
-        Note: You can now import annotations using names directly without having to lookup schema_ids
-        """
-        warnings.warn(
-            "This method is deprecated and will be "
-            "removed in a future release. Feature schema ids"
-            " are no longer required for importing."
-        )
-        tool_lookup, classification_lookup = get_feature_schema_lookup(
-            ontology_builder
-        )
-        for annotation in self.annotations:
-            if isinstance(annotation, ClassificationAnnotation):
-                self._assign_or_raise(annotation, classification_lookup)
-                self._assign_option(annotation, classification_lookup)
-            elif isinstance(annotation, ObjectAnnotation):
-                self._assign_or_raise(annotation, tool_lookup)
-                for classification in annotation.classifications:
-                    self._assign_or_raise(classification, classification_lookup)
-                    self._assign_option(classification, classification_lookup)
-            else:
-                raise TypeError(
-                    f"Unexpected type found for annotation. {type(annotation)}"
-                )
-        return self
-
     def _assign_or_raise(self, annotation, lookup: Dict[str, str]) -> None:
         if annotation.feature_schema_id is not None:
             return

libs/labelbox/src/labelbox/project_validation.py

@@ -11,7 +11,6 @@
     CONSENSUS_AUTO_AUDIT_PERCENTAGE,
     QualityMode,
 )
-from labelbox.schema.queue_mode import QueueMode
 
 PositiveInt = Annotated[int, Field(gt=0)]
 
@@ -20,7 +19,6 @@ class _CoreProjectInput(BaseModel):
     name: str
     description: Optional[str] = None
     media_type: MediaType
-    queue_mode: QueueMode = Field(default=QueueMode.Batch, frozen=True)
     auto_audit_percentage: Optional[float] = None
     auto_audit_number_of_labels: Optional[int] = None
     quality_modes: Optional[Set[QualityMode]] = Field(
@@ -33,7 +31,7 @@ class _CoreProjectInput(BaseModel):
     data_row_count: Optional[PositiveInt] = None
     editor_task_type: Optional[EditorTaskType] = None
 
-    model_config = ConfigDict(extra="forbid")
+    model_config = ConfigDict(extra="forbid", use_enum_values=True)
 
     @model_validator(mode="after")
     def validate_fields(self):

libs/labelbox/src/labelbox/schema/asset_attachment.py

@@ -7,15 +7,6 @@
 
 
 class AttachmentType(str, Enum):
-    @classmethod
-    def __missing__(cls, value: object):
-        if str(value) == "TEXT":
-            warnings.warn(
-                "The TEXT attachment type is deprecated. Use RAW_TEXT instead."
-            )
-            return cls.RAW_TEXT
-        return value
-
     VIDEO = "VIDEO"
     IMAGE = "IMAGE"
     IMAGE_OVERLAY = "IMAGE_OVERLAY"
@@ -30,7 +21,7 @@ class AssetAttachment(DbObject):
     """Asset attachment provides extra context about an asset while labeling.
 
     Attributes:
-        attachment_type (str): IMAGE, VIDEO, IMAGE_OVERLAY, HTML, RAW_TEXT, TEXT_URL, or PDF_URL. TEXT attachment type is deprecated.
+        attachment_type (str): IMAGE, VIDEO, IMAGE_OVERLAY, HTML, RAW_TEXT, TEXT_URL, or PDF_URL.
         attachment_value (str): URL to an external file or a string of text
         attachment_name (str): The name of the attachment
     """

libs/labelbox/src/labelbox/schema/data_row_metadata.py

@@ -673,10 +673,8 @@ def bulk_delete(
         if not len(deletes):
             raise ValueError("The 'deletes' list cannot be empty.")
 
-        passed_strings = False
         for i, delete in enumerate(deletes):
             if isinstance(delete.data_row_id, str):
-                passed_strings = True
                 deletes[i] = DeleteDataRowMetadata(
                     data_row_id=UniqueId(delete.data_row_id),
                     fields=delete.fields,
@@ -690,12 +688,6 @@ def bulk_delete(
                     f"Invalid data row identifier type '{type(delete.data_row_id)}' for '{delete.data_row_id}'"
                 )
 
-            if passed_strings:
-                warnings.warn(
-                    "Using string for data row id will be deprecated. Please use "
-                    "UniqueId instead."
-                )
-
         def _batch_delete(
             deletes: List[_DeleteBatchDataRowMetadata],
         ) -> List[DataRowMetadataBatchResponse]:

libs/labelbox/src/labelbox/schema/dataset.py

@@ -166,49 +166,9 @@ def create_data_row(self, items=None, **kwargs) -> "DataRow":
 
         return self.client.get_data_row(res[0]["id"])
 
-    def create_data_rows_sync(
-        self, items, file_upload_thread_count=FILE_UPLOAD_THREAD_COUNT
-    ) -> None:
-        """Synchronously bulk upload data rows.
-
-        Use this instead of `Dataset.create_data_rows` for smaller batches of data rows that need to be uploaded quickly.
-        Cannot use this for uploads containing more than 1000 data rows.
-        Each data row is also limited to 5 attachments.
-
-        Args:
-            items (iterable of (dict or str)):
-                See the docstring for `Dataset._create_descriptor_file` for more information.
-        Returns:
-            None. If the function doesn't raise an exception then the import was successful.
-
-        Raises:
-            ResourceCreationError: If the `items` parameter does not conform to
-                the specification in Dataset._create_descriptor_file or if the server did not accept the
-                DataRow creation request (unknown reason).
-            InvalidAttributeError: If there are fields in `items` not valid for
-                a DataRow.
-            ValueError: When the upload parameters are invalid
-        """
-        warnings.warn(
-            "This method is deprecated and will be "
-            "removed in a future release. Please use create_data_rows instead."
-        )
-
-        self._create_data_rows_sync(
-            items, file_upload_thread_count=file_upload_thread_count
-        )
-
-        return None  # Return None if no exception is raised
-
     def _create_data_rows_sync(
         self, items, file_upload_thread_count=FILE_UPLOAD_THREAD_COUNT
     ) -> "DataUpsertTask":
-        max_data_rows_supported = 1000
-        if len(items) > max_data_rows_supported:
-            raise ValueError(
-                f"Dataset.create_data_rows_sync() supports a max of {max_data_rows_supported} data rows."
-                " For larger imports use the async function Dataset.create_data_rows()"
-            )
         if file_upload_thread_count < 1:
             raise ValueError(
                 "file_upload_thread_count must be a positive integer"
@@ -235,8 +195,6 @@ def create_data_rows(
     ) -> "DataUpsertTask":
         """Asynchronously bulk upload data rows
 
-        Use this instead of `Dataset.create_data_rows_sync` uploads for batches that contain more than 1000 data rows.
-
         Args:
             items (iterable of (dict or str))
 

libs/labelbox/src/labelbox/schema/project.py

@@ -61,7 +61,6 @@
     ProjectOverview,
     ProjectOverviewDetailed,
 )
-from labelbox.schema.queue_mode import QueueMode
 from labelbox.schema.resource_tag import ResourceTag
 from labelbox.schema.task import Task
 from labelbox.schema.task_queue import TaskQueue
@@ -109,7 +108,6 @@ class Project(DbObject, Updateable, Deletable):
         created_at (datetime)
         setup_complete (datetime)
         last_activity_time (datetime)
-        queue_mode (string)
         auto_audit_number_of_labels (int)
         auto_audit_percentage (float)
         is_benchmark_enabled (bool)
@@ -132,7 +130,6 @@ class Project(DbObject, Updateable, Deletable):
     created_at = Field.DateTime("created_at")
     setup_complete = Field.DateTime("setup_complete")
     last_activity_time = Field.DateTime("last_activity_time")
-    queue_mode = Field.Enum(QueueMode, "queue_mode")
     auto_audit_number_of_labels = Field.Int("auto_audit_number_of_labels")
     auto_audit_percentage = Field.Float("auto_audit_percentage")
     # Bind data_type and allowedMediaTYpe using the GraphQL type MediaType
@@ -734,9 +731,6 @@ def create_batch(
         Raises:
             lbox.exceptions.ValueError if a project is not batch mode, if the project is auto data generation, if the batch exceeds 100k data rows
         """
-        # @TODO: make this automatic?
-        if self.queue_mode != QueueMode.Batch:
-            raise ValueError("Project must be in batch mode")
 
         if self.is_auto_data_generation():
             raise ValueError(
@@ -816,9 +810,6 @@ def create_batches(
         Returns: a task for the created batches
         """
 
-        if self.queue_mode != QueueMode.Batch:
-            raise ValueError("Project must be in batch mode")
-
         dr_ids = []
         if data_rows is not None:
             for dr in data_rows:
@@ -901,9 +892,6 @@ def create_batches_from_dataset(
         Returns: a task for the created batches
         """
 
-        if self.queue_mode != QueueMode.Batch:
-            raise ValueError("Project must be in batch mode")
-
         if consensus_settings:
             consensus_settings = ConsensusSettings(
                 **consensus_settings