Coverage for python/lsst/daf/butler/datastores/genericDatastore.py : 87%

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1# This file is part of daf_butler.
2#
3# Developed for the LSST Data Management System.
4# This product includes software developed by the LSST Project
5# (http://www.lsst.org).
6# See the COPYRIGHT file at the top-level directory of this distribution
7# for details of code ownership.
8#
9# This program is free software: you can redistribute it and/or modify
10# it under the terms of the GNU General Public License as published by
11# the Free Software Foundation, either version 3 of the License, or
12# (at your option) any later version.
13#
14# This program is distributed in the hope that it will be useful,
15# but WITHOUT ANY WARRANTY; without even the implied warranty of
16# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
17# GNU General Public License for more details.
18#
19# You should have received a copy of the GNU General Public License
20# along with this program. If not, see <http://www.gnu.org/licenses/>.
22"""Generic datastore code useful for most datastores."""
24__all__ = ("GenericBaseDatastore", )
26import logging
27from abc import abstractmethod
29from lsst.daf.butler import Datastore, DatasetTypeNotSupportedError
31log = logging.getLogger(__name__)
34class GenericBaseDatastore(Datastore):
35 """Methods useful for most implementations of a `Datastore`.
37 Should always be sub-classed since key abstract methods are missing.
38 """
40 @abstractmethod
41 def addStoredItemInfo(self, refs, infos):
42 """Record internal storage information associated with one or more
43 datasets.
45 Parameters
46 ----------
47 refs : sequence of `DatasetRef`
48 The datasets that have been stored.
49 infos : sequence of `StoredDatastoreItemInfo`
50 Metadata associated with the stored datasets.
51 """
52 raise NotImplementedError()
54 @abstractmethod
55 def getStoredItemInfo(self, ref):
56 """Retrieve information associated with file stored in this
57 `Datastore`.
59 Parameters
60 ----------
61 ref : `DatasetRef`
62 The dataset that is to be queried.
64 Returns
65 -------
66 info : `StoredFilenfo`
67 Stored information about this file and its formatter.
69 Raises
70 ------
71 KeyError
72 Dataset with that id can not be found.
73 """
74 raise NotImplementedError()
76 @abstractmethod
77 def removeStoredItemInfo(self, ref):
78 """Remove information about the file associated with this dataset.
80 Parameters
81 ----------
82 ref : `DatasetRef`
83 The dataset that has been removed.
84 """
85 raise NotImplementedError()
87 def _register_datasets(self, refsAndInfos):
88 """Update registry to indicate that one or more datasets have been
89 stored.
91 Parameters
92 ----------
93 refsAndInfos : sequence `tuple` [`DatasetRef`, `StoredDatasetItemInfo`]
94 Datasets to register and the internal datastore metadata associated
95 with them.
96 """
97 expandedRefs = []
98 expandedItemInfos = []
100 for ref, itemInfo in refsAndInfos:
101 # Need the main dataset and the components
102 expandedRefs.extend(ref.flatten([ref]))
104 # Need one for the main ref and then one for each component
105 expandedItemInfos.extend([itemInfo] * (len(ref.components) + 1))
107 self.registry.insertDatasetLocations(self.name, expandedRefs)
108 self.addStoredItemInfo(expandedRefs, expandedItemInfos)
110 def _move_to_trash_in_registry(self, ref):
111 """Tell registry that this dataset and associated components
112 are to be trashed.
114 Parameters
115 ----------
116 ref : `DatasetRef`
117 Dataset to mark for removal from registry.
119 Notes
120 -----
121 Dataset is not removed from internal stored item info table.
122 """
124 # Note that a ref can point to component dataset refs that
125 # have been deleted already from registry but are still in
126 # the python object. moveDatasetLocationToTrash will deal with that.
127 self.registry.moveDatasetLocationToTrash(self.name, list(ref.flatten([ref])))
129 def _post_process_get(self, inMemoryDataset, readStorageClass, assemblerParams=None):
130 """Given the Python object read from the datastore, manipulate
131 it based on the supplied parameters and ensure the Python
132 type is correct.
134 Parameters
135 ----------
136 inMemoryDataset : `object`
137 Dataset to check.
138 readStorageClass: `StorageClass`
139 The `StorageClass` used to obtain the assembler and to
140 check the python type.
141 assemblerParams : `dict`
142 Parameters to pass to the assembler. Can be `None`.
143 """
144 # Process any left over parameters
145 if assemblerParams:
146 inMemoryDataset = readStorageClass.assembler().handleParameters(inMemoryDataset, assemblerParams)
148 # Validate the returned data type matches the expected data type
149 pytype = readStorageClass.pytype
150 if pytype and not isinstance(inMemoryDataset, pytype): 150 ↛ 151line 150 didn't jump to line 151, because the condition on line 150 was never true
151 raise TypeError("Got Python type {} from datastore but expected {}".format(type(inMemoryDataset),
152 pytype))
154 return inMemoryDataset
156 def _validate_put_parameters(self, inMemoryDataset, ref):
157 """Validate the supplied arguments for put.
159 Parameters
160 ----------
161 inMemoryDataset : `object`
162 The dataset to store.
163 ref : `DatasetRef`
164 Reference to the associated Dataset.
165 """
166 storageClass = ref.datasetType.storageClass
168 # Sanity check
169 if not isinstance(inMemoryDataset, storageClass.pytype): 169 ↛ 170line 169 didn't jump to line 170, because the condition on line 169 was never true
170 raise TypeError("Inconsistency between supplied object ({}) "
171 "and storage class type ({})".format(type(inMemoryDataset),
172 storageClass.pytype))
174 # Confirm that we can accept this dataset
175 if not self.constraints.isAcceptable(ref):
176 # Raise rather than use boolean return value.
177 raise DatasetTypeNotSupportedError(f"Dataset {ref} has been rejected by this datastore via"
178 " configuration.")
180 return
182 def remove(self, ref):
183 """Indicate to the Datastore that a dataset can be removed.
185 .. warning::
187 This method deletes the artifact associated with this
188 dataset and can not be reversed.
190 Parameters
191 ----------
192 ref : `DatasetRef`
193 Reference to the required Dataset.
195 Raises
196 ------
197 FileNotFoundError
198 Attempt to remove a dataset that does not exist.
200 Notes
201 -----
202 This method is used for immediate removal of a dataset and is
203 generally reserved for internal testing of datastore APIs.
204 It is implemented by calling `trash()` and then immediately calling
205 `emptyTrash()`. This call is meant to be immediate so errors
206 encountered during removal are not ignored.
207 """
208 self.trash(ref, ignore_errors=False)
209 self.emptyTrash(ignore_errors=False)
211 def transfer(self, inputDatastore, ref):
212 """Retrieve a dataset from an input `Datastore`,
213 and store the result in this `Datastore`.
215 Parameters
216 ----------
217 inputDatastore : `Datastore`
218 The external `Datastore` from which to retreive the Dataset.
219 ref : `DatasetRef`
220 Reference to the required dataset in the input data store.
222 """
223 assert inputDatastore is not self # unless we want it for renames?
224 inMemoryDataset = inputDatastore.get(ref)
225 return self.put(inMemoryDataset, ref)