Merge pull request #930 from Labelbox/VB/remove-labellist-sdk_AL-4965

Vb/remove labellist sdk al 4965

Author: vbrodsky

labelbox/data/annotation_types/__init__.py

@@ -24,7 +24,6 @@
 from .data import VideoData
 
 from .label import Label
-
 from .collection import LabelList
 from .collection import LabelGenerator
 

labelbox/data/annotation_types/collection.py

@@ -22,10 +22,10 @@ class LabelList:
     Use on smaller datasets.
     """
 
-    warnings.warn("LabelList is deprecated and will be "
-                  "removed in a future release.")
-
     def __init__(self, data: Optional[Iterable[Label]] = None):
+        warnings.warn("LabelList is deprecated and will be "
+                      "removed in a future release.")
+
         if data is None:
             self._data = []
         elif isinstance(data, Label):
@@ -179,10 +179,8 @@ def _apply_threaded(self, fns, max_concurrency, *args):
 
 class LabelGenerator(PrefetchGenerator):
     """
-    A container for interacting with a collection of labels.
-
-    Use this class if you have larger data. It is slightly harder to work with
-    than the LabelList but will be much more memory efficient.
+    A container for interacting with a large collection of labels. 
+    For a small number of labels, just use a list of Label objects.
     """
 
     def __init__(self, data: Generator[Label, None, None], *args, **kwargs):
@@ -191,7 +189,7 @@ def __init__(self, data: Generator[Label, None, None], *args, **kwargs):
 
     def as_list(self) -> "LabelList":
         warnings.warn("This method is deprecated and will be "
-                      "removed in a future release. LabeList"
+                      "removed in a future release. LabelList"
                       " class will be deprecated.")
         return LabelList(data=list(self))
 
@@ -304,4 +302,4 @@ def __next__(self):
         return self._process(value)
 
 
-LabelCollection = Union[LabelList, LabelGenerator, Iterable[Label]]
+LabelCollection = Union[LabelGenerator, Iterable[Label]]

labelbox/data/metrics/group.py

@@ -12,7 +12,7 @@
     from typing_extensions import Literal
 
 from ..annotation_types.feature import FeatureSchema
-from ..annotation_types import ObjectAnnotation, ClassificationAnnotation, Label, LabelList
+from ..annotation_types import ObjectAnnotation, ClassificationAnnotation, Label
 
 
 def get_identifying_key(
@@ -79,8 +79,8 @@ def all_have_key(features: List[FeatureSchema]) -> Tuple[bool, bool]:
     return all_schemas, all_names
 
 
-def get_label_pairs(labels_a: LabelList,
-                    labels_b: LabelList,
+def get_label_pairs(labels_a: list,
+                    labels_b: list,
                     match_on="uid",
                     filter_mismatch=False) -> Dict[str, Tuple[Label, Label]]:
     """
@@ -91,8 +91,8 @@ def get_label_pairs(labels_a: LabelList,
     If this assumption fails, then the user has to determine their own matching strategy.
 
     Args:
-        labels_a (LabelList): A collection of labels to match with labels_b
-        labels_b (LabelList): A collection of labels to match with labels_a
+        labels_a (list): A collection of labels to match with labels_b
+        labels_b (list): A collection of labels to match with labels_a
         match_on ('uid' or 'external_id'): The data row key to match labels by. Can either be uid or external id.
         filter_mismatch (bool): Whether or not to ignore mismatches
 

labelbox/data/serialization/labelbox_v1/converter.py

@@ -69,7 +69,7 @@ def serialize(
         Note that any metric annotations will not be written since they are not defined in the LBV1 format.
 
         Args:
-            labels: Either a LabelList or a LabelGenerator (LabelCollection)
+            labels: Either a list of Label objects or a LabelGenerator (LabelCollection)
         Returns:
             A generator for accessing the labelbox json export representation of the data
         """

labelbox/data/serialization/labelbox_v1/objects.py

@@ -219,7 +219,7 @@ def from_common(cls, mask: Mask,
                     extra: Dict[str, Any]) -> "LBV1Mask":
         if mask.mask.url is None:
             raise ValueError(
-                "Mask does not have a url. Use `LabelGenerator.add_url_to_masks`, `LabelList.add_url_to_masks`, or `Label.add_url_to_masks`."
+                "Mask does not have a url. Use `LabelGenerator.add_url_to_masks`, or `Label.add_url_to_masks`."
             )
         return cls(instanceURI=mask.mask.url,
                    classifications=classifications,

labelbox/data/serialization/ndjson/base.py

@@ -13,7 +13,7 @@ class DataRow(BaseModel):
     def validate_id(cls, v):
         if v is None:
             raise ValueError(
-                "Data row ids are not set. Use `LabelGenerator.add_to_dataset`, `LabelList.add_to_dataset`, or `Label.create_data_row`. "
+                "Data row ids are not set. Use `LabelGenerator.add_to_dataset`,or `Label.create_data_row`. "
                 "You can also manually assign the id for each `BaseData` object"
             )
         return v

labelbox/data/serialization/ndjson/converter.py

@@ -36,7 +36,7 @@ def serialize(
         We will continue to improve the error messages and add helper functions to deal with this.
 
         Args:
-            labels: Either a LabelList or a LabelGenerator
+            labels: Either a list of Label objects or a LabelGenerator
         Returns:
             A generator for accessing the ndjson representation of the data
         """

tests/data/annotation_types/test_collection.py

@@ -4,9 +4,9 @@
 import numpy as np
 import pytest
 
-from labelbox.data.annotation_types import (LabelList, LabelGenerator,
-                                            ObjectAnnotation, ImageData,
-                                            MaskData, Line, Mask, Point, Label)
+from labelbox.data.annotation_types import (LabelGenerator, ObjectAnnotation,
+                                            ImageData, MaskData, Line, Mask,
+                                            Point, Label)
 from labelbox import OntologyBuilder, Tool
 
 
@@ -61,7 +61,7 @@ def test_generator(list_of_labels):
 
 def test_conversion(list_of_labels):
     generator = LabelGenerator(list_of_labels)
-    label_collection = generator.as_list()
+    label_collection = list(generator)
     assert len(label_collection) == len(list_of_labels)
     assert [x for x in label_collection] == list_of_labels
 
@@ -83,9 +83,6 @@ def test_adding_schema_ids():
     ])
     generator = LabelGenerator([label]).assign_feature_schema_ids(ontology)
     assert next(generator).annotations[0].feature_schema_id == feature_schema_id
-    labels = LabelList([label]).assign_feature_schema_ids(ontology)
-    assert next(labels).annotations[0].feature_schema_id == feature_schema_id
-    assert labels[0].annotations[0].feature_schema_id == feature_schema_id
 
 
 def test_adding_urls(signer):
@@ -98,15 +95,6 @@ def test_adding_urls(signer):
     assert next(generator).data.url == uuid
     assert label.data.url == uuid
 
-    label = Label(data=ImageData(arr=np.random.random((32, 32,
-                                                       3)).astype(np.uint8)),
-                  annotations=[])
-    assert label.data.url != uuid
-    labels = LabelList([label]).add_url_to_data(signer(uuid))
-    assert label.data.url == uuid
-    assert next(labels).data.url == uuid
-    assert labels[0].data.url == uuid
-
 
 def test_adding_to_dataset(signer):
     dataset = FakeDataset()
@@ -122,22 +110,6 @@ def test_adding_to_dataset(signer):
     assert generated_label.data.uid == dataset.uid
     assert label.data.url == uuid
 
-    dataset = FakeDataset()
-    label = Label(data=ImageData(arr=np.random.random((32, 32,
-                                                       3)).astype(np.uint8)),
-                  annotations=[])
-    assert label.data.url != uuid
-    assert label.data.external_id == None
-    assert label.data.uid != dataset.uid
-    labels = LabelList([label]).add_to_dataset(dataset, signer(uuid))
-    assert label.data.url == uuid
-    assert label.data.external_id != None
-    assert label.data.uid == dataset.uid
-    generated_label = next(labels)
-    assert generated_label.data.url == uuid
-    assert generated_label.data.external_id != None
-    assert generated_label.data.uid == dataset.uid
-
 
 def test_adding_to_masks(signer):
     label = Label(
@@ -154,17 +126,3 @@ def test_adding_to_masks(signer):
     assert label.annotations[0].value.mask.url != uuid
     assert next(generator).annotations[0].value.mask.url == uuid
     assert label.annotations[0].value.mask.url == uuid
-
-    label = Label(
-        data=ImageData(arr=np.random.random((32, 32, 3)).astype(np.uint8)),
-        annotations=[
-            ObjectAnnotation(name="1234",
-                             value=Mask(mask=MaskData(
-                                 arr=np.random.random((32, 32,
-                                                       3)).astype(np.uint8)),
-                                        color=[255, 255, 255]))
-        ])
-    assert label.annotations[0].value.mask.url != uuid
-    labels = LabelList([label]).add_url_to_masks(signer(uuid))
-    assert next(labels).annotations[0].value.mask.url == uuid
-    assert labels[0].annotations[0].value.mask.url == uuid

tests/data/annotation_types/test_metrics.py

@@ -3,7 +3,6 @@
 
 from labelbox.data.annotation_types.metrics import ConfusionMatrixAggregation, ScalarMetricAggregation
 from labelbox.data.annotation_types.metrics import ConfusionMatrixMetric, ScalarMetric
-from labelbox.data.annotation_types.collection import LabelList
 from labelbox.data.annotation_types import ScalarMetric, Label, ImageData
 from labelbox.data.annotation_types.metrics.scalar import RESERVED_METRIC_NAMES
 
@@ -34,7 +33,6 @@ def test_legacy_scalar_metric():
         'uid': None
     }
     assert label.dict() == expected
-    assert next(LabelList([label])).dict() == expected
 
 
 # TODO: Test with confidence
@@ -96,7 +94,6 @@ def test_custom_scalar_metric(feature_name, subclass_name, aggregation, value):
     }
 
     assert label.dict() == expected
-    assert next(LabelList([label])).dict() == expected
 
 
 @pytest.mark.parametrize('feature_name,subclass_name,aggregation,value', [
@@ -152,7 +149,6 @@ def test_custom_confusison_matrix_metric(feature_name, subclass_name,
         'uid': None
     }
     assert label.dict() == expected
-    assert next(LabelList([label])).dict() == expected
 
 
 def test_name_exists():

tests/data/serialization/labelbox_v1/test_tiled_image.py

@@ -20,7 +20,7 @@ def test_image(file_path):
         payload = json.load(f)
 
         collection = LBV1Converter.deserialize(payload)
-        collection_as_list = collection.as_list()
+        collection_as_list = list(collection)
 
         assert len(collection_as_list) == 2