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Factor out ref utilities from RemoteButler
Pull out some standalone functions from RemoteButler to a new file to cut down clutter.
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| # This file is part of daf_butler. | ||
| # | ||
| # Developed for the LSST Data Management System. | ||
| # This product includes software developed by the LSST Project | ||
| # (http://www.lsst.org). | ||
| # See the COPYRIGHT file at the top-level directory of this distribution | ||
| # for details of code ownership. | ||
| # | ||
| # This software is dual licensed under the GNU General Public License and also | ||
| # under a 3-clause BSD license. Recipients may choose which of these licenses | ||
| # to use; please see the files gpl-3.0.txt and/or bsd_license.txt, | ||
| # respectively. If you choose the GPL option then the following text applies | ||
| # (but note that there is still no warranty even if you opt for BSD instead): | ||
| # | ||
| # This program is free software: you can redistribute it and/or modify | ||
| # it under the terms of the GNU General Public License as published by | ||
| # the Free Software Foundation, either version 3 of the License, or | ||
| # (at your option) any later version. | ||
| # | ||
| # This program is distributed in the hope that it will be useful, | ||
| # but WITHOUT ANY WARRANTY; without even the implied warranty of | ||
| # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the | ||
| # GNU General Public License for more details. | ||
| # | ||
| # You should have received a copy of the GNU General Public License | ||
| # along with this program. If not, see <http://www.gnu.org/licenses/>. | ||
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| from __future__ import annotations | ||
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| __all__ = ( | ||
| "apply_storage_class_override", | ||
| "normalize_dataset_type_name", | ||
| "simplify_dataId", | ||
| ) | ||
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| from pydantic import TypeAdapter | ||
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| from .._dataset_ref import DatasetRef | ||
| from .._dataset_type import DatasetType | ||
| from .._storage_class import StorageClass | ||
| from ..dimensions import DataCoordinate, DataId, DataIdValue, SerializedDataId | ||
| from .server_models import DatasetTypeName | ||
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| _SERIALIZED_DATA_ID_TYPE_ADAPTER = TypeAdapter(SerializedDataId) | ||
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| def apply_storage_class_override( | ||
| ref: DatasetRef, | ||
| original_dataset_ref_or_type: DatasetRef | DatasetType | str, | ||
| explicit_storage_class: StorageClass | str | None, | ||
| ) -> DatasetRef: | ||
| """Return a DatasetRef with its storage class overridden to match the | ||
| StorageClass supplied by the user as input to one of the search functions. | ||
| Parameters | ||
| ---------- | ||
| ref : `DatasetRef` | ||
| The ref to which we will apply the StorageClass override. | ||
| original_dataset_ref_or_type : `DatasetRef` | `DatasetType` | `str` | ||
| The ref or type that was input to the search, which may contain a | ||
| storage class override. | ||
| explicit_storage_class : `StorageClass` | `str` | `None` | ||
| A storage class that the user explicitly requested as an override. | ||
| """ | ||
| if explicit_storage_class is not None: | ||
| return ref.overrideStorageClass(explicit_storage_class) | ||
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| # If the caller provided a DatasetRef or DatasetType, they may have | ||
| # overridden the storage class on it, and we need to propagate that to the | ||
| # output. | ||
| dataset_type = _extract_dataset_type(original_dataset_ref_or_type) | ||
| if dataset_type is not None: | ||
| return ref.overrideStorageClass(dataset_type.storageClass) | ||
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| return ref | ||
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| def normalize_dataset_type_name(datasetTypeOrName: DatasetType | str) -> DatasetTypeName: | ||
| """Convert DatasetType parameters in the format used by Butler methods | ||
| to a standardized string name for the REST API. | ||
| Parameters | ||
| ---------- | ||
| datasetTypeOrName : `DatasetType` | `str` | ||
| A DatasetType, or the name of a DatasetType. This union is a common | ||
| parameter in many `Butler` methods. | ||
| """ | ||
| if isinstance(datasetTypeOrName, DatasetType): | ||
| return DatasetTypeName(datasetTypeOrName.name) | ||
| elif isinstance(datasetTypeOrName, str): | ||
| return DatasetTypeName(datasetTypeOrName) | ||
| else: | ||
| raise TypeError(f"Got unexpected object for DatasetType: {datasetTypeOrName}") | ||
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| def simplify_dataId(dataId: DataId | None, kwargs: dict[str, DataIdValue]) -> SerializedDataId: | ||
| """Take a generic Data ID and convert it to a serializable form. | ||
| Parameters | ||
| ---------- | ||
| dataId : `dict`, `None`, `DataCoordinate` | ||
| The data ID to serialize. | ||
| kwargs : `dict` | ||
| Additional entries to augment or replace the values in ``dataId``. | ||
| Returns | ||
| ------- | ||
| data_id : `SerializedDataId` | ||
| A serializable form. | ||
| """ | ||
| if dataId is None: | ||
| dataId = {} | ||
| elif isinstance(dataId, DataCoordinate): | ||
| dataId = dataId.to_simple(minimal=True).dataId | ||
| else: | ||
| dataId = dict(dataId) | ||
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| return _SERIALIZED_DATA_ID_TYPE_ADAPTER.validate_python(dataId | kwargs) | ||
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| def _extract_dataset_type(datasetRefOrType: DatasetRef | DatasetType | str) -> DatasetType | None: | ||
| """Return the DatasetType associated with the argument, or None if the | ||
| argument is not an object that contains a DatasetType object. | ||
| Parameters | ||
| ---------- | ||
| datasetRefOrType : `DatasetRef` | `DatasetType` | `str` | ||
| A DatasetRef, DatasetType, or name of a DatasetType. This union is a | ||
| common parameter in many `Butler` methods. | ||
| """ | ||
| if isinstance(datasetRefOrType, DatasetType): | ||
| return datasetRefOrType | ||
| elif isinstance(datasetRefOrType, DatasetRef): | ||
| return datasetRefOrType.datasetType | ||
| else: | ||
| return None | ||
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