Revert "feat: add special datatype for timestamp (#730)"

docs/reference/experimental/index.md

@@ -24,6 +24,3 @@
     options:
         members: ["download_results_by_tag"]
         show_root_heading: true
-::: kolena._experimental.special_data_type
-    options:
-        show_root_heading: true

examples/dataset/classification/classification/multiclass/upload_results.py

@@ -22,9 +22,9 @@
 from classification.multiclass.constants import DATASET
 from classification.multiclass.constants import ID_FIELDS
 
-from kolena.annotation import ScoredClassificationLabel
 from kolena.dataset import download_dataset
 from kolena.dataset import upload_results
+from kolena.workflow.annotation import ScoredClassificationLabel
 
 
 MODELS = ["resnet50v2", "inceptionv3"]

kolena/_utils/datatypes.py

@@ -85,7 +85,6 @@ class DataCategory(str, Enum):
     METRICS = "METRICS"
     ASSET = "ASSET"
     ANNOTATION = "ANNOTATION"
-    SPECIAL = "SPECIAL"
 
     def data_category_to_module_name(self) -> str:
         if self == DataCategory.TEST_SAMPLE:
@@ -98,8 +97,6 @@ def data_category_to_module_name(self) -> str:
             return "kolena.asset"
         if self == DataCategory.ANNOTATION:
             return "kolena.annotation"
-        if self == DataCategory.SPECIAL:
-            return "kolena._experimental.data_type.special"
         raise ValueError(f"Must specify module name for data category: {self}")
 
 

kolena/annotation.py

@@ -62,7 +62,6 @@ class _AnnotationType(DataType):
     TIME_SEGMENT = "TIME_SEGMENT"
     TEXT_SEGMENT = "TEXT_SEGMENT"
     CUSTOM = "CUSTOM"
-    TIMESTAMP = "TIMESTAMP"
 
     @staticmethod
     def _data_category() -> DataCategory:

tests/integration/dataset/test_dataset.py

@@ -21,16 +21,15 @@
 import pytest
 
 from kolena._api.v2.dataset import CommitData
-from kolena._experimental.special_data_type import Timestamp
-from kolena.annotation import BoundingBox
-from kolena.annotation import LabeledBoundingBox
 from kolena.dataset import download_dataset
 from kolena.dataset import list_datasets
 from kolena.dataset import upload_dataset
 from kolena.dataset.dataset import _fetch_dataset_history
 from kolena.dataset.dataset import _load_dataset_metadata
 from kolena.errors import InputValidationError
 from kolena.errors import NotFoundError
+from kolena.workflow.annotation import BoundingBox
+from kolena.workflow.annotation import LabeledBoundingBox
 from tests.integration.helper import assert_frame_equal
 from tests.integration.helper import fake_locator
 from tests.integration.helper import upload_extracted_properties
@@ -84,8 +83,6 @@ def test__upload_dataset() -> None:
                 LabeledBoundingBox(label="cat", top_left=[i, i], bottom_right=[i + 10, i + 10]),
                 LabeledBoundingBox(label="dog", top_left=[i + 5, i + 5], bottom_right=[i + 20, i + 20]),
             ],
-            time_str=Timestamp(value=f"12/31/2024, 00:00:{'{:02d}'.format(i)}", format="%m/%d/%Y, %H:%M:%S"),
-            time_num=Timestamp(epoch_time=1735689600 + i),
         )
         for i in range(20)
     ]
@@ -99,12 +96,10 @@ def test__upload_dataset() -> None:
                 BoundingBox(label=bbox.label, top_left=bbox.top_left, bottom_right=bbox.bottom_right)
                 for bbox in dp["bboxes"]
             ],
-            time_str=dp["time_str"],
-            time_num=dp["time_num"],
         )
         for dp in datapoints
     ]
-    columns = ["locator", "width", "height", "city", "bboxes", "time_str", "time_num"]
+    columns = ["locator", "width", "height", "city", "bboxes"]
 
     upload_dataset(name, pd.DataFrame(datapoints[:10], columns=columns), id_fields=["locator"])