Coverage for python / lsst / daf / butler / datastore / generic_base.py: 35%

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27 

28"""Generic datastore code useful for most datastores.""" 

29 

30from __future__ import annotations 

31 

32__all__ = ("GenericBaseDatastore", "post_process_get") 

33 

34import logging 

35from collections.abc import Mapping 

36from typing import TYPE_CHECKING, Any, Generic, TypeVar 

37 

38from ..datastore._datastore import Datastore 

39from .stored_file_info import StoredDatastoreItemInfo 

40 

41if TYPE_CHECKING: 

42 from .._dataset_ref import DatasetRef 

43 from .._storage_class import StorageClass 

44 

45log = logging.getLogger(__name__) 

46 

47_InfoType = TypeVar("_InfoType", bound=StoredDatastoreItemInfo) 

48 

49 

50class GenericBaseDatastore(Datastore, Generic[_InfoType]): 

51 """Methods useful for most implementations of a `Datastore`. 

52 

53 Should always be sub-classed since key abstract methods are missing. 

54 """ 

55 

56 def remove(self, ref: DatasetRef) -> None: 

57 """Indicate to the Datastore that a dataset can be removed. 

58 

59 .. warning:: 

60 

61 This method deletes the artifact associated with this 

62 dataset and can not be reversed. 

63 

64 Parameters 

65 ---------- 

66 ref : `DatasetRef` 

67 Reference to the required Dataset. 

68 

69 Raises 

70 ------ 

71 FileNotFoundError 

72 Attempt to remove a dataset that does not exist. 

73 

74 Notes 

75 ----- 

76 This method is used for immediate removal of a dataset and is 

77 generally reserved for internal testing of datastore APIs. 

78 It is implemented by calling `trash()` and then immediately calling 

79 `emptyTrash()`. This call is meant to be immediate so errors 

80 encountered during removal are not ignored. 

81 """ 

82 self.trash(ref, ignore_errors=False) 

83 self.emptyTrash(ignore_errors=False, refs=[ref]) 

84 

85 def transfer(self, inputDatastore: Datastore, ref: DatasetRef) -> None: 

86 """Retrieve a dataset from an input `Datastore`, 

87 and store the result in this `Datastore`. 

88 

89 Parameters 

90 ---------- 

91 inputDatastore : `Datastore` 

92 The external `Datastore` from which to retrieve the Dataset. 

93 ref : `DatasetRef` 

94 Reference to the required dataset in the input data store. 

95 """ 

96 assert inputDatastore is not self # unless we want it for renames? 

97 inMemoryDataset = inputDatastore.get(ref) 

98 return self.put(inMemoryDataset, ref) 

99 

100 

101def post_process_get( 

102 inMemoryDataset: object, 

103 readStorageClass: StorageClass, 

104 assemblerParams: Mapping[str, Any] | None = None, 

105 isComponent: bool = False, 

106) -> object: 

107 """Given the Python object read from the datastore, manipulate 

108 it based on the supplied parameters and ensure the Python 

109 type is correct. 

110 

111 Parameters 

112 ---------- 

113 inMemoryDataset : `object` 

114 Dataset to check. 

115 readStorageClass : `StorageClass` 

116 The `StorageClass` used to obtain the assembler and to 

117 check the python type. 

118 assemblerParams : `dict`, optional 

119 Parameters to pass to the assembler. Can be `None`. 

120 isComponent : `bool`, optional 

121 If this is a component, allow the inMemoryDataset to be `None`. 

122 

123 Returns 

124 ------- 

125 dataset : `object` 

126 In-memory dataset, potentially converted to expected type. 

127 """ 

128 # Process any left over parameters 

129 if assemblerParams: 

130 inMemoryDataset = readStorageClass.delegate().handleParameters(inMemoryDataset, assemblerParams) 

131 

132 # Validate the returned data type matches the expected data type 

133 pytype = readStorageClass.pytype 

134 

135 allowedTypes = [] 

136 if pytype: 

137 allowedTypes.append(pytype) 

138 

139 # Special case components to allow them to be None 

140 if isComponent: 

141 allowedTypes.append(type(None)) 

142 

143 if allowedTypes and not isinstance(inMemoryDataset, tuple(allowedTypes)): 

144 inMemoryDataset = readStorageClass.coerce_type(inMemoryDataset) 

145 

146 return inMemoryDataset