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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__ = ("Formatter", "FormatterFactory", "FormatterParameter")
26from abc import ABCMeta, abstractmethod
27from collections.abc import Mapping
28import contextlib
29import logging
30import copy
31from typing import (
32 AbstractSet,
33 Any,
34 ClassVar,
35 Dict,
36 Iterator,
37 Optional,
38 Set,
39 Tuple,
40 Type,
41 TYPE_CHECKING,
42 Union,
43)
45from .configSupport import processLookupConfigs, LookupKey
46from .mappingFactory import MappingFactory
47from .utils import getFullTypeName
48from .fileDescriptor import FileDescriptor
49from .location import Location
50from .config import Config
51from .dimensions import DimensionUniverse
52from .storageClass import StorageClass
53from .datasets import DatasetType, DatasetRef
55log = logging.getLogger(__name__)
57# Define a new special type for functions that take "entity"
58Entity = Union[DatasetType, DatasetRef, StorageClass, str]
61if TYPE_CHECKING: 61 ↛ 62line 61 didn't jump to line 62, because the condition on line 61 was never true
62 from .dimensions import DataCoordinate
65class Formatter(metaclass=ABCMeta):
66 """Interface for reading and writing Datasets with a particular
67 `StorageClass`.
69 Parameters
70 ----------
71 fileDescriptor : `FileDescriptor`, optional
72 Identifies the file to read or write, and the associated storage
73 classes and parameter information. Its value can be `None` if the
74 caller will never call `Formatter.read` or `Formatter.write`.
75 dataId : `DataCoordinate`, optional
76 Data ID associated with this formatter.
77 writeParameters : `dict`, optional
78 Any parameters to be hard-coded into this instance to control how
79 the dataset is serialized.
80 """
82 unsupportedParameters: ClassVar[Optional[AbstractSet[str]]] = frozenset()
83 """Set of read parameters not understood by this `Formatter`. An empty set
84 means all parameters are supported. `None` indicates that no parameters
85 are supported. These param (`frozenset`).
86 """
88 supportedWriteParameters: ClassVar[Optional[AbstractSet[str]]] = None
89 """Parameters understood by this formatter that can be used to control
90 how a dataset is serialized. `None` indicates that no parameters are
91 supported."""
93 supportedExtensions: ClassVar[AbstractSet[str]] = frozenset()
94 """Set of all extensions supported by this formatter.
96 Only expected to be populated by Formatters that write files. Any extension
97 assigned to the ``extension`` property will be automatically included in
98 the list of supported extensions."""
100 def __init__(self, fileDescriptor: FileDescriptor, dataId: Optional[DataCoordinate] = None,
101 writeParameters: Optional[Dict[str, Any]] = None,
102 writeRecipes: Optional[Dict[str, Any]] = None):
103 if not isinstance(fileDescriptor, FileDescriptor):
104 raise TypeError("File descriptor must be a FileDescriptor")
105 self._fileDescriptor = fileDescriptor
106 self._dataId = dataId
108 # Check that the write parameters are allowed
109 if writeParameters:
110 if self.supportedWriteParameters is None:
111 raise ValueError("This formatter does not accept any write parameters. "
112 f"Got: {', '.join(writeParameters)}")
113 else:
114 given = set(writeParameters)
115 unknown = given - self.supportedWriteParameters
116 if unknown:
117 s = "s" if len(unknown) != 1 else ""
118 unknownStr = ", ".join(f"'{u}'" for u in unknown)
119 raise ValueError(f"This formatter does not accept parameter{s} {unknownStr}")
121 self._writeParameters = writeParameters
122 self._writeRecipes = self.validateWriteRecipes(writeRecipes)
124 def __str__(self) -> str:
125 return f"{self.name()}@{self.fileDescriptor.location.path}"
127 def __repr__(self) -> str:
128 return f"{self.name()}({self.fileDescriptor!r})"
130 @property
131 def fileDescriptor(self) -> FileDescriptor:
132 """FileDescriptor associated with this formatter
133 (`FileDescriptor`, read-only)"""
134 return self._fileDescriptor
136 @property
137 def dataId(self) -> Optional[DataCoordinate]:
138 """DataId associated with this formatter (`DataCoordinate`)"""
139 return self._dataId
141 @property
142 def writeParameters(self) -> Mapping[str, Any]:
143 """Parameters to use when writing out datasets."""
144 if self._writeParameters is not None:
145 return self._writeParameters
146 return {}
148 @property
149 def writeRecipes(self) -> Mapping[str, Any]:
150 """Detailed write Recipes indexed by recipe name."""
151 if self._writeRecipes is not None:
152 return self._writeRecipes
153 return {}
155 @classmethod
156 def validateWriteRecipes(cls, recipes: Optional[Mapping[str, Any]]) -> Optional[Mapping[str, Any]]:
157 """Validate supplied recipes for this formatter.
159 The recipes are supplemented with default values where appropriate.
161 Parameters
162 ----------
163 recipes : `dict`
164 Recipes to validate.
166 Returns
167 -------
168 validated : `dict`
169 Validated recipes.
171 Raises
172 ------
173 RuntimeError
174 Raised if validation fails. The default implementation raises
175 if any recipes are given.
176 """
177 if recipes:
178 raise RuntimeError(f"This formatter does not understand these writeRecipes: {recipes}")
179 return recipes
181 @classmethod
182 def name(cls) -> str:
183 """Returns the fully qualified name of the formatter.
185 Returns
186 -------
187 name : `str`
188 Fully-qualified name of formatter class.
189 """
190 return getFullTypeName(cls)
192 @abstractmethod
193 def read(self, component: Optional[str] = None) -> Any:
194 """Read a Dataset.
196 Parameters
197 ----------
198 component : `str`, optional
199 Component to read from the file. Only used if the `StorageClass`
200 for reading differed from the `StorageClass` used to write the
201 file.
203 Returns
204 -------
205 inMemoryDataset : `object`
206 The requested Dataset.
207 """
208 raise NotImplementedError("Type does not support reading")
210 @abstractmethod
211 def write(self, inMemoryDataset: Any) -> None:
212 """Write a Dataset.
214 Parameters
215 ----------
216 inMemoryDataset : `object`
217 The Dataset to store.
218 """
219 raise NotImplementedError("Type does not support writing")
221 @classmethod
222 def can_read_bytes(cls) -> bool:
223 """Indicate if this formatter can format from bytes.
225 Returns
226 -------
227 can : `bool`
228 `True` if the `fromBytes` method is implemented.
229 """
230 # We have no property to read so instead try to format from a byte
231 # and see what happens
232 try:
233 # We know the arguments are incompatible
234 cls.fromBytes(cls, b"") # type: ignore
235 except NotImplementedError:
236 return False
237 except Exception:
238 # There will be problems with the bytes we are supplying so ignore
239 pass
240 return True
242 def fromBytes(self, serializedDataset: bytes,
243 component: Optional[str] = None) -> object:
244 """Reads serialized data into a Dataset or its component.
246 Parameters
247 ----------
248 serializedDataset : `bytes`
249 Bytes object to unserialize.
250 component : `str`, optional
251 Component to read from the Dataset. Only used if the `StorageClass`
252 for reading differed from the `StorageClass` used to write the
253 file.
255 Returns
256 -------
257 inMemoryDataset : `object`
258 The requested data as a Python object. The type of object
259 is controlled by the specific formatter.
260 """
261 raise NotImplementedError("Type does not support reading from bytes.")
263 def toBytes(self, inMemoryDataset: Any) -> bytes:
264 """Serialize the Dataset to bytes based on formatter.
266 Parameters
267 ----------
268 inMemoryDataset : `object`
269 The Python object to serialize.
271 Returns
272 -------
273 serializedDataset : `bytes`
274 Bytes representing the serialized dataset.
275 """
276 raise NotImplementedError("Type does not support writing to bytes.")
278 @contextlib.contextmanager
279 def _updateLocation(self, location: Optional[Location]) -> Iterator[Location]:
280 """Temporarily replace the location associated with this formatter.
282 Parameters
283 ----------
284 location : `Location`
285 New location to use for this formatter. If `None` the
286 formatter will not change but it will still return
287 the old location. This allows it to be used in a code
288 path where the location may not need to be updated
289 but the with block is still convenient.
291 Yields
292 ------
293 old : `Location`
294 The old location that will be restored.
296 Notes
297 -----
298 This is an internal method that should be used with care.
299 It may change in the future. Should be used as a context
300 manager to restore the location when the temporary is no
301 longer required.
302 """
303 old = self._fileDescriptor.location
304 try:
305 if location is not None:
306 self._fileDescriptor.location = location
307 yield old
308 finally:
309 if location is not None:
310 self._fileDescriptor.location = old
312 def makeUpdatedLocation(self, location: Location) -> Location:
313 """Return a new `Location` instance updated with this formatter's
314 extension.
316 Parameters
317 ----------
318 location : `Location`
319 The location to update.
321 Returns
322 -------
323 updated : `Location`
324 A new `Location` with a new file extension applied.
326 Raises
327 ------
328 NotImplementedError
329 Raised if there is no ``extension`` attribute associated with
330 this formatter.
332 Notes
333 -----
334 This method is available to all Formatters but might not be
335 implemented by all formatters. It requires that a formatter set
336 an ``extension`` attribute containing the file extension used when
337 writing files. If ``extension`` is `None` the supplied file will
338 not be updated. Not all formatters write files so this is not
339 defined in the base class.
340 """
341 location = copy.deepcopy(location)
342 try:
343 # We are deliberately allowing extension to be undefined by
344 # default in the base class and mypy complains.
345 location.updateExtension(self.extension) # type:ignore
346 except AttributeError:
347 raise NotImplementedError("No file extension registered with this formatter") from None
348 return location
350 @classmethod
351 def validateExtension(cls, location: Location) -> None:
352 """Check that the provided location refers to a file extension that is
353 understood by this formatter.
355 Parameters
356 ----------
357 location : `Location`
358 Location from which to extract a file extension.
360 Raises
361 ------
362 NotImplementedError
363 Raised if file extensions are a concept not understood by this
364 formatter.
365 ValueError
366 Raised if the formatter does not understand this extension.
368 Notes
369 -----
370 This method is available to all Formatters but might not be
371 implemented by all formatters. It requires that a formatter set
372 an ``extension`` attribute containing the file extension used when
373 writing files. If ``extension`` is `None` only the set of supported
374 extensions will be examined.
375 """
376 supported = set(cls.supportedExtensions)
378 try:
379 # We are deliberately allowing extension to be undefined by
380 # default in the base class and mypy complains.
381 default = cls.extension # type: ignore
382 except AttributeError:
383 raise NotImplementedError("No file extension registered with this formatter") from None
385 # If extension is implemented as an instance property it won't return
386 # a string when called as a class propertt. Assume that
387 # the supported extensions class property is complete.
388 if default is not None and isinstance(default, str):
389 supported.add(default)
391 # Get the file name from the uri
392 file = location.uri.basename()
394 # Check that this file name ends with one of the supported extensions.
395 # This is less prone to confusion than asking the location for
396 # its extension and then doing a set comparison
397 for ext in supported:
398 if file.endswith(ext):
399 return
401 raise ValueError(f"Extension '{location.getExtension()}' on '{location}' "
402 f"is not supported by Formatter '{cls.__name__}' (supports: {supported})")
404 def predictPath(self) -> str:
405 """Return the path that would be returned by write, without actually
406 writing.
408 Uses the `FileDescriptor` associated with the instance.
410 Returns
411 -------
412 path : `str`
413 Path within datastore that would be associated with the location
414 stored in this `Formatter`.
415 """
416 updated = self.makeUpdatedLocation(self.fileDescriptor.location)
417 return updated.pathInStore.path
419 def segregateParameters(self, parameters: Optional[Dict[str, Any]] = None) -> Tuple[Dict, Dict]:
420 """Segregate the supplied parameters into those understood by the
421 formatter and those not understood by the formatter.
423 Any unsupported parameters are assumed to be usable by associated
424 assemblers.
426 Parameters
427 ----------
428 parameters : `dict`, optional
429 Parameters with values that have been supplied by the caller
430 and which might be relevant for the formatter. If `None`
431 parameters will be read from the registered `FileDescriptor`.
433 Returns
434 -------
435 supported : `dict`
436 Those parameters supported by this formatter.
437 unsupported : `dict`
438 Those parameters not supported by this formatter.
439 """
441 if parameters is None:
442 parameters = self.fileDescriptor.parameters
444 if parameters is None:
445 return {}, {}
447 if self.unsupportedParameters is None:
448 # Support none of the parameters
449 return {}, parameters.copy()
451 # Start by assuming all are supported
452 supported = parameters.copy()
453 unsupported = {}
455 # And remove any we know are not supported
456 for p in set(supported):
457 if p in self.unsupportedParameters:
458 unsupported[p] = supported.pop(p)
460 return supported, unsupported
463class FormatterFactory:
464 """Factory for `Formatter` instances.
465 """
467 defaultKey = LookupKey("default")
468 """Configuration key associated with default write parameter settings."""
470 writeRecipesKey = LookupKey("write_recipes")
471 """Configuration key associated with write recipes."""
473 def __init__(self) -> None:
474 self._mappingFactory = MappingFactory(Formatter)
476 def __contains__(self, key: Union[LookupKey, str]) -> bool:
477 """Indicates whether the supplied key is present in the factory.
479 Parameters
480 ----------
481 key : `LookupKey`, `str` or objects with ``name`` attribute
482 Key to use to lookup in the factory whether a corresponding
483 formatter is present.
485 Returns
486 -------
487 in : `bool`
488 `True` if the supplied key is present in the factory.
489 """
490 return key in self._mappingFactory
492 def registerFormatters(self, config: Config, *, universe: DimensionUniverse) -> None:
493 """Bulk register formatters from a config.
495 Parameters
496 ----------
497 config : `Config`
498 ``formatters`` section of a configuration.
499 universe : `DimensionUniverse`, optional
500 Set of all known dimensions, used to expand and validate any used
501 in lookup keys.
503 Notes
504 -----
505 The configuration can include one level of hierarchy where an
506 instrument-specific section can be defined to override more general
507 template specifications. This is represented in YAML using a
508 key of form ``instrument<name>`` which can then define templates
509 that will be returned if a `DatasetRef` contains a matching instrument
510 name in the data ID.
512 The config is parsed using the function
513 `~lsst.daf.butler.configSubset.processLookupConfigs`.
515 The values for formatter entries can be either a simple string
516 referring to a python type or a dict representing the formatter and
517 parameters to be hard-coded into the formatter constructor. For
518 the dict case the following keys are supported:
520 - formatter: The python type to be used as the formatter class.
521 - parameters: A further dict to be passed directly to the
522 ``writeParameters`` Formatter constructor to seed it.
523 These parameters are validated at instance creation and not at
524 configuration.
526 Additionally, a special ``default`` section can be defined that
527 uses the formatter type (class) name as the keys and specifies
528 default write parameters that should be used whenever an instance
529 of that class is constructed.
531 .. code-block:: yaml
533 formatters:
534 default:
535 lsst.daf.butler.formatters.example.ExampleFormatter:
536 max: 10
537 min: 2
538 comment: Default comment
539 calexp: lsst.daf.butler.formatters.example.ExampleFormatter
540 coadd:
541 formatter: lsst.daf.butler.formatters.example.ExampleFormatter
542 parameters:
543 max: 5
545 Any time an ``ExampleFormatter`` is constructed it will use those
546 parameters. If an explicit entry later in the configuration specifies
547 a different set of parameters, the two will be merged with the later
548 entry taking priority. In the example above ``calexp`` will use
549 the default parameters but ``coadd`` will override the value for
550 ``max``.
552 Formatter configuration can also include a special section describing
553 collections of write parameters that can be accessed through a
554 simple label. This allows common collections of options to be
555 specified in one place in the configuration and reused later.
556 The ``write_recipes`` section is indexed by Formatter class name
557 and each key is the label to associate with the parameters.
559 .. code-block:: yaml
561 formatters:
562 write_recipes:
563 lsst.obs.base.formatters.fitsExposure.FixExposureFormatter:
564 lossless:
565 ...
566 noCompression:
567 ...
569 By convention a formatter that uses write recipes will support a
570 ``recipe`` write parameter that will refer to a recipe name in
571 the ``write_recipes`` component. The `Formatter` will be constructed
572 in the `FormatterFactory` with all the relevant recipes and
573 will not attempt to filter by looking at ``writeParameters`` in
574 advance. See the specific formatter documentation for details on
575 acceptable recipe options.
576 """
577 allowed_keys = {"formatter", "parameters"}
579 contents = processLookupConfigs(config, allow_hierarchy=True, universe=universe)
581 # Extract any default parameter settings
582 defaultParameters = contents.get(self.defaultKey, {})
583 if not isinstance(defaultParameters, Mapping):
584 raise RuntimeError("Default formatter parameters in config can not be a single string"
585 f" (got: {type(defaultParameters)})")
587 # Extract any global write recipes -- these are indexed by
588 # Formatter class name.
589 writeRecipes = contents.get(self.writeRecipesKey, {})
590 if isinstance(writeRecipes, str):
591 raise RuntimeError(f"The formatters.{self.writeRecipesKey} section must refer to a dict"
592 f" not '{writeRecipes}'")
594 for key, f in contents.items():
595 # default is handled in a special way
596 if key == self.defaultKey:
597 continue
598 if key == self.writeRecipesKey:
599 continue
601 # Can be a str or a dict.
602 specificWriteParameters = {}
603 if isinstance(f, str):
604 formatter = f
605 elif isinstance(f, Mapping):
606 all_keys = set(f)
607 unexpected_keys = all_keys - allowed_keys
608 if unexpected_keys:
609 raise ValueError(f"Formatter {key} uses unexpected keys {unexpected_keys} in config")
610 if "formatter" not in f:
611 raise ValueError(f"Mandatory 'formatter' key missing for formatter key {key}")
612 formatter = f["formatter"]
613 if "parameters" in f:
614 specificWriteParameters = f["parameters"]
615 else:
616 raise ValueError(f"Formatter for key {key} has unexpected value: '{f}'")
618 # Apply any default parameters for this formatter
619 writeParameters = copy.deepcopy(defaultParameters.get(formatter, {}))
620 writeParameters.update(specificWriteParameters)
622 kwargs: Dict[str, Any] = {}
623 if writeParameters:
624 kwargs["writeParameters"] = writeParameters
626 if formatter in writeRecipes:
627 kwargs["writeRecipes"] = writeRecipes[formatter]
629 self.registerFormatter(key, formatter, **kwargs)
631 def getLookupKeys(self) -> Set[LookupKey]:
632 """Retrieve the look up keys for all the registry entries.
634 Returns
635 -------
636 keys : `set` of `LookupKey`
637 The keys available for matching in the registry.
638 """
639 return self._mappingFactory.getLookupKeys()
641 def getFormatterClassWithMatch(self, entity: Entity) -> Tuple[LookupKey, Type[Formatter],
642 Dict[str, Any]]:
643 """Get the matching formatter class along with the matching registry
644 key.
646 Parameters
647 ----------
648 entity : `DatasetRef`, `DatasetType`, `StorageClass`, or `str`
649 Entity to use to determine the formatter to return.
650 `StorageClass` will be used as a last resort if `DatasetRef`
651 or `DatasetType` instance is provided. Supports instrument
652 override if a `DatasetRef` is provided configured with an
653 ``instrument`` value for the data ID.
655 Returns
656 -------
657 matchKey : `LookupKey`
658 The key that resulted in the successful match.
659 formatter : `type`
660 The class of the registered formatter.
661 formatter_kwargs : `dict`
662 Keyword arguments that are associated with this formatter entry.
663 """
664 names = (LookupKey(name=entity),) if isinstance(entity, str) else entity._lookupNames()
665 matchKey, formatter, formatter_kwargs = self._mappingFactory.getClassFromRegistryWithMatch(names)
666 log.debug("Retrieved formatter %s from key '%s' for entity '%s'", getFullTypeName(formatter),
667 matchKey, entity)
669 return matchKey, formatter, formatter_kwargs
671 def getFormatterClass(self, entity: Entity) -> Type:
672 """Get the matching formatter class.
674 Parameters
675 ----------
676 entity : `DatasetRef`, `DatasetType`, `StorageClass`, or `str`
677 Entity to use to determine the formatter to return.
678 `StorageClass` will be used as a last resort if `DatasetRef`
679 or `DatasetType` instance is provided. Supports instrument
680 override if a `DatasetRef` is provided configured with an
681 ``instrument`` value for the data ID.
683 Returns
684 -------
685 formatter : `type`
686 The class of the registered formatter.
687 """
688 _, formatter, _ = self.getFormatterClassWithMatch(entity)
689 return formatter
691 def getFormatterWithMatch(self, entity: Entity, *args: Any, **kwargs: Any) -> Tuple[LookupKey, Formatter]:
692 """Get a new formatter instance along with the matching registry
693 key.
695 Parameters
696 ----------
697 entity : `DatasetRef`, `DatasetType`, `StorageClass`, or `str`
698 Entity to use to determine the formatter to return.
699 `StorageClass` will be used as a last resort if `DatasetRef`
700 or `DatasetType` instance is provided. Supports instrument
701 override if a `DatasetRef` is provided configured with an
702 ``instrument`` value for the data ID.
703 args : `tuple`
704 Positional arguments to use pass to the object constructor.
705 kwargs : `dict`
706 Keyword arguments to pass to object constructor.
708 Returns
709 -------
710 matchKey : `LookupKey`
711 The key that resulted in the successful match.
712 formatter : `Formatter`
713 An instance of the registered formatter.
714 """
715 names = (LookupKey(name=entity),) if isinstance(entity, str) else entity._lookupNames()
716 matchKey, formatter = self._mappingFactory.getFromRegistryWithMatch(names, *args, **kwargs)
717 log.debug("Retrieved formatter %s from key '%s' for entity '%s'", getFullTypeName(formatter),
718 matchKey, entity)
720 return matchKey, formatter
722 def getFormatter(self, entity: Entity, *args: Any, **kwargs: Any) -> Formatter:
723 """Get a new formatter instance.
725 Parameters
726 ----------
727 entity : `DatasetRef`, `DatasetType`, `StorageClass`, or `str`
728 Entity to use to determine the formatter to return.
729 `StorageClass` will be used as a last resort if `DatasetRef`
730 or `DatasetType` instance is provided. Supports instrument
731 override if a `DatasetRef` is provided configured with an
732 ``instrument`` value for the data ID.
733 args : `tuple`
734 Positional arguments to use pass to the object constructor.
735 kwargs : `dict`
736 Keyword arguments to pass to object constructor.
738 Returns
739 -------
740 formatter : `Formatter`
741 An instance of the registered formatter.
742 """
743 _, formatter = self.getFormatterWithMatch(entity, *args, **kwargs)
744 return formatter
746 def registerFormatter(self, type_: Union[LookupKey, str, StorageClass, DatasetType],
747 formatter: str, *, overwrite: bool = False,
748 **kwargs: Any) -> None:
749 """Register a `Formatter`.
751 Parameters
752 ----------
753 type_ : `LookupKey`, `str`, `StorageClass` or `DatasetType`
754 Type for which this formatter is to be used. If a `LookupKey`
755 is not provided, one will be constructed from the supplied string
756 or by using the ``name`` property of the supplied entity.
757 formatter : `str` or class of type `Formatter`
758 Identifies a `Formatter` subclass to use for reading and writing
759 Datasets of this type. Can be a `Formatter` class.
760 overwrite : `bool`, optional
761 If `True` an existing entry will be replaced by the new value.
762 Default is `False`.
763 kwargs : `dict`
764 Keyword arguments to always pass to object constructor when
765 retrieved.
767 Raises
768 ------
769 ValueError
770 Raised if the formatter does not name a valid formatter type and
771 ``overwrite`` is `False`.
772 """
773 self._mappingFactory.placeInRegistry(type_, formatter, overwrite=overwrite, **kwargs)
776# Type to use when allowing a Formatter or its class name
777FormatterParameter = Union[str, Type[Formatter], Formatter]