Coverage for python/lsst/daf/butler/formatters/yaml.py : 30%

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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/>.
22from __future__ import annotations
24__all__ = ("YamlFormatter", )
26import builtins
27import yaml
29from typing import (
30 TYPE_CHECKING,
31 Any,
32 Optional,
33 Type,
34)
36from .file import FileFormatter
38if TYPE_CHECKING: 38 ↛ 39line 38 didn't jump to line 39, because the condition on line 38 was never true
39 from lsst.daf.butler import StorageClass
42class YamlFormatter(FileFormatter):
43 """Interface for reading and writing Python objects to and from YAML files.
44 """
45 extension = ".yaml"
47 unsupportedParameters = None
48 """This formatter does not support any parameters"""
50 supportedWriteParameters = frozenset({"unsafe_dump"})
51 """Allow the normal yaml.dump to be used to write the YAML. Use this
52 if you know that your class has registered representers."""
54 def _readFile(self, path: str, pytype: Type[Any] = None) -> Any:
55 """Read a file from the path in YAML format.
57 Parameters
58 ----------
59 path : `str`
60 Path to use to open YAML format file.
61 pytype : `class`, optional
62 Not used by this implementation.
64 Returns
65 -------
66 data : `object`
67 Either data as Python object read from YAML file, or None
68 if the file could not be opened.
70 Notes
71 -----
72 The `~yaml.SafeLoader` is used when parsing the YAML file.
73 """
74 try:
75 with open(path, "rb") as fd:
76 data = self._fromBytes(fd.read(), pytype)
77 except FileNotFoundError:
78 data = None
80 return data
82 def _fromBytes(self, serializedDataset: bytes, pytype: Optional[Type[Any]] = None) -> Any:
83 """Read the bytes object as a python object.
85 Parameters
86 ----------
87 serializedDataset : `bytes`
88 Bytes object to unserialize.
89 pytype : `class`, optional
90 Not used by this implementation.
92 Returns
93 -------
94 inMemoryDataset : `object`
95 The requested data as an object, or None if the string could
96 not be read.
98 Notes
99 -----
100 The `~yaml.SafeLoader` is used when parsing the YAML.
101 """
102 data = yaml.safe_load(serializedDataset)
104 try:
105 data = data.exportAsDict()
106 except AttributeError:
107 pass
108 return data
110 def _writeFile(self, inMemoryDataset: Any) -> None:
111 """Write the in memory dataset to file on disk.
113 Will look for `_asdict()` method to aid YAML serialization, following
114 the approach of the simplejson module. The `dict` will be passed
115 to the relevant constructor on read.
117 Parameters
118 ----------
119 inMemoryDataset : `object`
120 Object to serialize.
122 Raises
123 ------
124 Exception
125 The file could not be written.
127 Notes
128 -----
129 The `~yaml.SafeDumper` is used when generating the YAML serialization.
130 This will fail for data structures that have complex python classes
131 without a registered YAML representer.
132 """
133 with open(self.fileDescriptor.location.path, "wb") as fd:
134 fd.write(self._toBytes(inMemoryDataset))
136 def _toBytes(self, inMemoryDataset: Any) -> bytes:
137 """Write the in memory dataset to a bytestring.
139 Will look for `_asdict()` method to aid YAML serialization, following
140 the approach of the simplejson module. The `dict` will be passed
141 to the relevant constructor on read.
143 Parameters
144 ----------
145 inMemoryDataset : `object`
146 Object to serialize
148 Returns
149 -------
150 serializedDataset : `bytes`
151 YAML string encoded to bytes.
153 Raises
154 ------
155 Exception
156 The object could not be serialized.
158 Notes
159 -----
160 The `~yaml.SafeDumper` is used when generating the YAML serialization.
161 This will fail for data structures that have complex python classes
162 without a registered YAML representer.
163 """
164 if hasattr(inMemoryDataset, "_asdict"):
165 inMemoryDataset = inMemoryDataset._asdict()
166 unsafe_dump = self.writeParameters.get("unsafe_dump", False)
167 if unsafe_dump:
168 serialized = yaml.dump(inMemoryDataset)
169 else:
170 serialized = yaml.safe_dump(inMemoryDataset)
171 return serialized.encode()
173 def _coerceType(self, inMemoryDataset: Any, storageClass: StorageClass,
174 pytype: Optional[Type[Any]] = None) -> Any:
175 """Coerce the supplied inMemoryDataset to type `pytype`.
177 Parameters
178 ----------
179 inMemoryDataset : `object`
180 Object to coerce to expected type.
181 storageClass : `StorageClass`
182 StorageClass associated with `inMemoryDataset`.
183 pytype : `type`, optional
184 Override type to use for conversion.
186 Returns
187 -------
188 inMemoryDataset : `object`
189 Object of expected type `pytype`.
190 """
191 if inMemoryDataset is not None and pytype is not None and not hasattr(builtins, pytype.__name__):
192 if storageClass.isComposite():
193 inMemoryDataset = storageClass.delegate().assemble(inMemoryDataset, pytype=pytype)
194 elif not isinstance(inMemoryDataset, pytype):
195 # Hope that we can pass the arguments in directly
196 inMemoryDataset = pytype(inMemoryDataset)
197 return inMemoryDataset