Remove February 2026 deprecated parameters

CHANGELOG.md

@@ -1,6 +1,9 @@
 # v0.9.4 (Upcoming)
 
 ## Removals, Deprecations and Changes
+* Removed the deprecated `staging` parameter from `automatic_dandi_upload`. Use `sandbox` instead. [PR #1678](https://github.com/catalystneuro/neuroconv/pull/1678)
+* Removed the deprecated `container_name` parameter from `ImageInterface.add_to_nwbfile` and `DeepLabCutInterface.add_to_nwbfile`. Use `metadata_key` in `__init__` instead. [PR #1678](https://github.com/catalystneuro/neuroconv/pull/1678)
+* Removed the deprecated `time_series_name` parameter from `add_recording_as_time_series_to_nwbfile`. Use `metadata_key` instead. [PR #1678](https://github.com/catalystneuro/neuroconv/pull/1678)
 
 ## Bug Fixes
 * Fixed `get_json_schema_from_method_signature` to resolve PEP 563 string annotations (from `from __future__ import annotations`) before passing them to pydantic. This affected any interface defined in a module with deferred annotations (e.g. `MiniscopeConverter`, or external subclasses from SpikeInterface). [PR #1670](https://github.com/catalystneuro/neuroconv/pull/1670)

src/neuroconv/datainterfaces/behavior/deeplabcut/deeplabcutdatainterface.py

@@ -559,8 +559,6 @@ def add_to_nwbfile(
         self,
         nwbfile: NWBFile,
         metadata: dict | None = None,
-        *args,  # TODO: change to * (keyword only) on or after August 2026
-        container_name: str | None = None,
     ):
         """
         Conversion from DLC output files to nwb. Derived from dlc2nwb library.
@@ -571,53 +569,13 @@ def add_to_nwbfile(
             nwb file to which the recording information is to be added
         metadata: dict
             metadata info for constructing the nwb file (optional).
-        container_name: str, default: None
-            name of the PoseEstimation container in the nwb. If None, uses the container_name from the interface.
-            This parameter is deprecated and will be removed on or after October 2025.
-            Use the pose_estimation_metadata_key parameter when initializing the interface instead to specify
-            the content of the metadata.
-
         """
-        # Handle deprecated positional arguments
-        if args:
-            parameter_names = [
-                "container_name",
-            ]
-            num_positional_args_before_args = 2  # nwbfile, metadata
-            if len(args) > len(parameter_names):
-                raise TypeError(
-                    f"add_to_nwbfile() takes at most {len(parameter_names) + num_positional_args_before_args} positional arguments but "
-                    f"{len(args) + num_positional_args_before_args} were given. "
-                    "Note: Positional arguments are deprecated and will be removed on or after August 2026. "
-                    "Please use keyword arguments."
-                )
-            positional_values = dict(zip(parameter_names, args))
-            passed_as_positional = list(positional_values.keys())
-            warnings.warn(
-                f"Passing arguments positionally to DeepLabCutInterface.add_to_nwbfile() is deprecated "
-                f"and will be removed on or after August 2026. "
-                f"The following arguments were passed positionally: {passed_as_positional}. "
-                "Please use keyword arguments instead.",
-                FutureWarning,
-                stacklevel=2,
-            )
-            container_name = positional_values.get("container_name", container_name)
         from ._dlc_utils import (
             _add_pose_estimation_to_nwbfile,
             _ensure_individuals_in_header,
         )
 
-        # Use the pose_estimation_metadata_key from the instance if container_name not provided
-        if container_name is not None:
-            warnings.warn(
-                "The container_name parameter in add_to_nwbfile is deprecated and will be removed on or after October 2025. "
-                "Use the pose_estimation_metadata_key parameter when initializing the interface instead.",
-                DeprecationWarning,
-                stacklevel=2,
-            )
-            pose_estimation_metadata_key = container_name
-        else:
-            pose_estimation_metadata_key = self.pose_estimation_metadata_key
+        pose_estimation_metadata_key = self.pose_estimation_metadata_key
 
         # Get default metadata
         default_metadata = DeepDict(self.get_metadata())
@@ -626,22 +584,6 @@ def add_to_nwbfile(
         if metadata is not None:
             default_metadata.deep_update(metadata)
 
-        # Set the container name in the metadata, remove this once container_name is deprecated
-        if container_name is not None:
-            if (
-                "PoseEstimation" in default_metadata
-                and "PoseEstimationContainers" in default_metadata["PoseEstimation"]
-            ):
-                if container_name in default_metadata["PoseEstimation"]["PoseEstimationContainers"]:
-                    default_metadata["PoseEstimation"]["PoseEstimationContainers"][container_name][
-                        "name"
-                    ] = container_name
-                else:
-                    # If the container doesn't exist in the metadata, create it with the name
-                    default_metadata["PoseEstimation"]["PoseEstimationContainers"][container_name] = {
-                        "name": container_name
-                    }
-
         file_path = Path(self.source_data["file_path"])
 
         # Read the data

src/neuroconv/datainterfaces/image/imageinterface.py

@@ -332,8 +332,6 @@ def add_to_nwbfile(
         self,
         nwbfile: NWBFile,
         metadata: DeepDict | None = None,
-        *args,  # TODO: change to * (keyword only) on or after August 2026
-        container_name: str | None = None,
     ) -> None:
         """
         Add the image data to an NWB file.
@@ -344,43 +342,7 @@ def add_to_nwbfile(
             The NWB file to add the images to
         metadata : dict, optional
             Metadata for the images
-        container_name : str, optional, deprecated
-            Name of the Images container. This parameter is deprecated and will be removed
-            on or after February 2026. Use metadata_key in __init__ instead.
-            If provided, it overrides the name from metadata.
         """
-        # Handle deprecated positional arguments
-        if args:
-            parameter_names = [
-                "container_name",
-            ]
-            num_positional_args_before_args = 2  # nwbfile, metadata
-            if len(args) > len(parameter_names):
-                raise TypeError(
-                    f"add_to_nwbfile() takes at most {len(parameter_names) + num_positional_args_before_args} positional arguments but "
-                    f"{len(args) + num_positional_args_before_args} were given. "
-                    "Note: Positional arguments are deprecated and will be removed on or after August 2026. "
-                    "Please use keyword arguments."
-                )
-            positional_values = dict(zip(parameter_names, args))
-            passed_as_positional = list(positional_values.keys())
-            warnings.warn(
-                f"Passing arguments positionally to ImageInterface.add_to_nwbfile() is deprecated "
-                f"and will be removed on or after August 2026. "
-                f"The following arguments were passed positionally: {passed_as_positional}. "
-                "Please use keyword arguments instead.",
-                FutureWarning,
-                stacklevel=2,
-            )
-            container_name = positional_values.get("container_name", container_name)
-
-        if container_name is not None:
-            warnings.warn(
-                "The 'container_name' parameter is deprecated and will be removed on or after February 2026. "
-                "Use 'metadata_key' in the __init__ method instead.",
-                FutureWarning,
-                stacklevel=2,
-            )
 
         if metadata is None:
             metadata = self.get_metadata()
@@ -389,11 +351,7 @@ def add_to_nwbfile(
         images_metadata = metadata.get("Images", {})
         container_metadata = images_metadata.get(self.metadata_key, {})
 
-        # Use container_name only if explicitly provided (deprecated), otherwise use metadata
-        if container_name is not None:
-            name = container_name
-        else:
-            name = container_metadata.get("name", self.metadata_key)
+        name = container_metadata.get("name", self.metadata_key)
 
         description = container_metadata.get("description", "Images loaded through ImageInterface")
 

src/neuroconv/tools/data_transfers/_dandi.py

@@ -16,8 +16,7 @@ def automatic_dandi_upload(
     nwb_folder_path: DirectoryPath,
     dandiset_folder_path: DirectoryPath | None = None,
     version: str = "draft",
-    sandbox: bool | None = None,
-    staging: bool | None = None,
+    sandbox: bool = False,
     cleanup: bool = False,
     number_of_jobs: int | None = None,
     number_of_threads: int | None = None,
@@ -52,13 +51,8 @@ def automatic_dandi_upload(
     version : str, default="draft"
         The version of the Dandiset to download. Even if no data has been uploaded yes, this step downloads an essential
         Dandiset metadata yaml file. Default is "draft", which is the latest state.
-    sandbox : bool, optional
+    sandbox : bool, default: False
         Is the Dandiset hosted on the sandbox server? This is mostly for testing purposes.
-        Defaults to False.
-    staging : bool, optional
-        .. deprecated:: 0.6.0
-            The 'staging' parameter is deprecated and will be removed in February 2026.
-            Use 'sandbox' instead.
     cleanup : bool, default: False
         Whether to remove the Dandiset folder path and nwb_folder_path.
     number_of_jobs : int, optional
@@ -77,21 +71,6 @@ def automatic_dandi_upload(
         message = "The 'instance' parameter must be either 'dandi', 'ember', or a full URL starting with 'https://'."
         raise ValueError(message)
 
-    # Handle deprecated 'staging' parameter and set defaults
-    if staging is not None and sandbox is not None:
-        raise ValueError("Cannot specify both 'staging' and 'sandbox' parameters. Use 'sandbox' only.")
-
-    if staging is not None:
-        warn(
-            "The 'staging' parameter is deprecated and will be removed in February 2026. " "Use 'sandbox' instead.",
-            DeprecationWarning,
-            stacklevel=2,
-        )
-        sandbox = staging
-
-    if sandbox is None:
-        sandbox = False
-
     # Determine the actual dandi_instance name and URL based on instance and sandbox parameters
     if instance == "dandi" and sandbox:
         url_base = "https://sandbox.dandiarchive.org"

src/neuroconv/tools/spikeinterface/spikeinterface.py

@@ -1,6 +1,6 @@
 import warnings
 from collections import defaultdict
-from typing import Any, Literal, Optional
+from typing import Any, Literal
 
 import numpy as np
 import psutil
@@ -1235,7 +1235,6 @@ def add_recording_as_time_series_to_nwbfile(
     iterator_options: dict | None = None,
     iterator_opts: dict | None = None,
     always_write_timestamps: bool = False,
-    time_series_name: Optional[str] = None,
     metadata_key: str = "TimeSeries",
 ):
     """
@@ -1294,16 +1293,6 @@ def add_recording_as_time_series_to_nwbfile(
             raise ValueError("Cannot specify both 'iterator_opts' and 'iterator_options'. Use 'iterator_options'.")
         iterator_options = iterator_opts
 
-    # Handle backward compatibility for time_series_name
-    if time_series_name is not None:
-        warnings.warn(
-            "The 'time_series_name' parameter is deprecated and will be removed in or after February 2026. "
-            "Use 'metadata_key' to specify the metadata entry instead.",
-            DeprecationWarning,
-            stacklevel=2,
-        )
-        metadata_key = time_series_name
-
     num_segments = recording.get_num_segments()
     for segment_index in range(num_segments):
         _add_time_series_segment_to_nwbfile(
@@ -1363,7 +1352,7 @@ def _add_time_series_segment_to_nwbfile(
                 "The recording extractor has heterogeneous units or is lacking scaling factors. "
                 "The time series will be saved with unit 'n.a.' and the conversion factors will not be set. "
                 "To fix this issue, either: "
-                "1) Set the unit in the metadata['TimeSeries'][time_series_name]['unit'] field, or "
+                "1) Set the unit in the metadata['TimeSeries'][metadata_key]['unit'] field, or "
                 "2) Set the `physical_unit`, `gain_to_physical_unit`, and `offset_to_physical_unit` properties "
                 "on the recording object with consistent units across all channels. "
                 f"Channel units: {units if units is not None else 'None'}, "

tests/remote_transfer_services/dandi_transfer_tools.py

@@ -84,47 +84,3 @@ def test_automatic_dandi_upload_non_parallel_non_threaded(tmp_path):
         number_of_jobs=1,
         number_of_threads=1,
     )
-
-
-@pytest.mark.skipif(
-    not HAVE_DANDI_KEY,
-    reason="You must set your DANDI_SANDBOX_API_KEY to run this test!",
-)
-def test_staging_sandbox_conflict(tmp_path):
-    """Test that providing both 'staging' and 'sandbox' parameters raises ValueError."""
-
-    nwb_folder_path = tmp_path / "test_nwb"
-    nwb_folder_path.mkdir()
-
-    with pytest.raises(ValueError, match="Cannot specify both 'staging' and 'sandbox' parameters"):
-        automatic_dandi_upload(dandiset_id="200000", nwb_folder_path=nwb_folder_path, sandbox=True, staging=True)
-
-
-@pytest.mark.skipif(
-    not HAVE_DANDI_KEY,
-    reason="You must set your DANDI_SANDBOX_API_KEY to run this test!",
-)
-def test_staging_backward_compatibility(tmp_path):
-    """Test that staging=True works the same as sandbox=True with deprecation warning."""
-    import warnings
-
-    nwb_folder_path = tmp_path / "test_nwb"
-    nwb_folder_path.mkdir()
-    metadata = get_default_nwbfile_metadata()
-    metadata["NWBFile"].update(
-        session_start_time=datetime.now().astimezone(),
-        session_id=f"test-staging-compat-{sys.platform}-{get_python_version().replace('.', '-')}",
-    )
-    metadata.update(Subject=dict(subject_id="foo", species="Mus musculus", age="P1D", sex="U"))
-    with NWBHDF5IO(path=nwb_folder_path / "test_nwb_staging.nwb", mode="w") as io:
-        io.write(make_nwbfile_from_metadata(metadata=metadata))
-
-    with warnings.catch_warnings(record=True) as w:
-        warnings.simplefilter("always")
-
-        # This should work with deprecation warning
-        automatic_dandi_upload(dandiset_id="200560", nwb_folder_path=nwb_folder_path, staging=True)
-
-        # Check that deprecation warning was issued
-        deprecation_warnings = [warning for warning in w if issubclass(warning.category, DeprecationWarning)]
-        assert len(deprecation_warnings) == 1, f"Expected 1 deprecation warning, got {len(deprecation_warnings)}"

tests/test_modalities/test_ecephys/test_tools_spikeinterface.py

@@ -1158,8 +1158,8 @@ def test_default_values(self):
         expected_data = recording.get_traces(segment_index=0)
         np.testing.assert_array_almost_equal(expected_data, extracted_data)
 
-    def test_time_series_name(self):
-        """Test that time_series_name is used to look up metadata."""
+    def test_metadata_key(self):
+        """Test that metadata_key is used to look up metadata."""
         # Create a recording object for testing
         num_channels = 3
         sampling_frequency = 1.0
@@ -1185,7 +1185,7 @@ def test_time_series_name(self):
             recording=recording,
             nwbfile=nwbfile,
             metadata=metadata,
-            time_series_name="CustomTimeSeries",
+            metadata_key="CustomTimeSeries",
             iterator_type=None,
         )
 
@@ -1194,8 +1194,8 @@ def test_time_series_name(self):
         assert time_series.unit == "custom_unit"
         assert time_series.description == "Custom description"
 
-    def test_custom_metadata_with_time_series_name(self):
-        """Test that custom metadata is applied when time_series_name is provided."""
+    def test_custom_metadata_with_metadata_key(self):
+        """Test that custom metadata is applied when metadata_key is provided."""
         # Create a recording object for testing
         num_channels = 3
         sampling_frequency = 1.0
@@ -1223,7 +1223,7 @@ def test_custom_metadata_with_time_series_name(self):
             recording=recording,
             nwbfile=nwbfile,
             metadata=metadata,
-            time_series_name="MyCustomSeries",
+            metadata_key="MyCustomSeries",
             iterator_type=None,
         )
 
@@ -1342,7 +1342,7 @@ def test_metadata_priority(self):
             recording=recording,
             nwbfile=nwbfile,
             metadata=metadata,
-            time_series_name="TimeSeriesRaw",
+            metadata_key="TimeSeriesRaw",
         )
 
         time_series = nwbfile.acquisition["TimeSeriesRaw"]