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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) -> str:
212 """Write a Dataset.
214 Parameters
215 ----------
216 inMemoryDataset : `object`
217 The Dataset to store.
219 Returns
220 -------
221 path : `str`
222 The path to where the Dataset was stored within the datastore.
223 """
224 raise NotImplementedError("Type does not support writing")
226 @classmethod
227 def can_read_bytes(cls) -> bool:
228 """Indicate if this formatter can format from bytes.
230 Returns
231 -------
232 can : `bool`
233 `True` if the `fromBytes` method is implemented.
234 """
235 # We have no property to read so instead try to format from a byte
236 # and see what happens
237 try:
238 # We know the arguments are incompatible
239 cls.fromBytes(cls, b"") # type: ignore
240 except NotImplementedError:
241 return False
242 except Exception:
243 # There will be problems with the bytes we are supplying so ignore
244 pass
245 return True
247 def fromBytes(self, serializedDataset: bytes,
248 component: Optional[str] = None) -> object:
249 """Reads serialized data into a Dataset or its component.
251 Parameters
252 ----------
253 serializedDataset : `bytes`
254 Bytes object to unserialize.
255 component : `str`, optional
256 Component to read from the Dataset. Only used if the `StorageClass`
257 for reading differed from the `StorageClass` used to write the
258 file.
260 Returns
261 -------
262 inMemoryDataset : `object`
263 The requested data as a Python object. The type of object
264 is controlled by the specific formatter.
265 """
266 raise NotImplementedError("Type does not support reading from bytes.")
268 def toBytes(self, inMemoryDataset: Any) -> bytes:
269 """Serialize the Dataset to bytes based on formatter.
271 Parameters
272 ----------
273 inMemoryDataset : `object`
274 The Python object to serialize.
276 Returns
277 -------
278 serializedDataset : `bytes`
279 Bytes representing the serialized dataset.
280 """
281 raise NotImplementedError("Type does not support writing to bytes.")
283 @contextlib.contextmanager
284 def _updateLocation(self, location: Optional[Location]) -> Iterator[Location]:
285 """Temporarily replace the location associated with this formatter.
287 Parameters
288 ----------
289 location : `Location`
290 New location to use for this formatter. If `None` the
291 formatter will not change but it will still return
292 the old location. This allows it to be used in a code
293 path where the location may not need to be updated
294 but the with block is still convenient.
296 Yields
297 ------
298 old : `Location`
299 The old location that will be restored.
301 Notes
302 -----
303 This is an internal method that should be used with care.
304 It may change in the future. Should be used as a context
305 manager to restore the location when the temporary is no
306 longer required.
307 """
308 old = self._fileDescriptor.location
309 try:
310 if location is not None:
311 self._fileDescriptor.location = location
312 yield old
313 finally:
314 if location is not None:
315 self._fileDescriptor.location = old
317 def makeUpdatedLocation(self, location: Location) -> Location:
318 """Return a new `Location` instance updated with this formatter's
319 extension.
321 Parameters
322 ----------
323 location : `Location`
324 The location to update.
326 Returns
327 -------
328 updated : `Location`
329 A new `Location` with a new file extension applied.
331 Raises
332 ------
333 NotImplementedError
334 Raised if there is no ``extension`` attribute associated with
335 this formatter.
337 Notes
338 -----
339 This method is available to all Formatters but might not be
340 implemented by all formatters. It requires that a formatter set
341 an ``extension`` attribute containing the file extension used when
342 writing files. If ``extension`` is `None` the supplied file will
343 not be updated. Not all formatters write files so this is not
344 defined in the base class.
345 """
346 location = copy.deepcopy(location)
347 try:
348 # We are deliberately allowing extension to be undefined by
349 # default in the base class and mypy complains.
350 location.updateExtension(self.extension) # type:ignore
351 except AttributeError:
352 raise NotImplementedError("No file extension registered with this formatter") from None
353 return location
355 @classmethod
356 def validateExtension(cls, location: Location) -> None:
357 """Check that the provided location refers to a file extension that is
358 understood by this formatter.
360 Parameters
361 ----------
362 location : `Location`
363 Location from which to extract a file extension.
365 Raises
366 ------
367 NotImplementedError
368 Raised if file extensions are a concept not understood by this
369 formatter.
370 ValueError
371 Raised if the formatter does not understand this extension.
373 Notes
374 -----
375 This method is available to all Formatters but might not be
376 implemented by all formatters. It requires that a formatter set
377 an ``extension`` attribute containing the file extension used when
378 writing files. If ``extension`` is `None` only the set of supported
379 extensions will be examined.
380 """
381 supported = set(cls.supportedExtensions)
383 try:
384 # We are deliberately allowing extension to be undefined by
385 # default in the base class and mypy complains.
386 default = cls.extension # type: ignore
387 except AttributeError:
388 raise NotImplementedError("No file extension registered with this formatter") from None
390 # If extension is implemented as an instance property it won't return
391 # a string when called as a class propertt. Assume that
392 # the supported extensions class property is complete.
393 if default is not None and isinstance(default, str):
394 supported.add(default)
396 # Get the file name from the uri
397 file = location.uri.basename()
399 # Check that this file name ends with one of the supported extensions.
400 # This is less prone to confusion than asking the location for
401 # its extension and then doing a set comparison
402 for ext in supported:
403 if file.endswith(ext):
404 return
406 raise ValueError(f"Extension '{location.getExtension()}' on '{location}' "
407 f"is not supported by Formatter '{cls.__name__}' (supports: {supported})")
409 def predictPath(self) -> str:
410 """Return the path that would be returned by write, without actually
411 writing.
413 Uses the `FileDescriptor` associated with the instance.
415 Returns
416 -------
417 path : `str`
418 Path within datastore that would be associated with the location
419 stored in this `Formatter`.
420 """
421 updated = self.makeUpdatedLocation(self.fileDescriptor.location)
422 return updated.pathInStore
424 def segregateParameters(self, parameters: Optional[Dict[str, Any]] = None) -> Tuple[Dict, Dict]:
425 """Segregate the supplied parameters into those understood by the
426 formatter and those not understood by the formatter.
428 Any unsupported parameters are assumed to be usable by associated
429 assemblers.
431 Parameters
432 ----------
433 parameters : `dict`, optional
434 Parameters with values that have been supplied by the caller
435 and which might be relevant for the formatter. If `None`
436 parameters will be read from the registered `FileDescriptor`.
438 Returns
439 -------
440 supported : `dict`
441 Those parameters supported by this formatter.
442 unsupported : `dict`
443 Those parameters not supported by this formatter.
444 """
446 if parameters is None:
447 parameters = self.fileDescriptor.parameters
449 if parameters is None:
450 return {}, {}
452 if self.unsupportedParameters is None:
453 # Support none of the parameters
454 return {}, parameters.copy()
456 # Start by assuming all are supported
457 supported = parameters.copy()
458 unsupported = {}
460 # And remove any we know are not supported
461 for p in set(supported):
462 if p in self.unsupportedParameters:
463 unsupported[p] = supported.pop(p)
465 return supported, unsupported
468class FormatterFactory:
469 """Factory for `Formatter` instances.
470 """
472 defaultKey = LookupKey("default")
473 """Configuration key associated with default write parameter settings."""
475 writeRecipesKey = LookupKey("write_recipes")
476 """Configuration key associated with write recipes."""
478 def __init__(self) -> None:
479 self._mappingFactory = MappingFactory(Formatter)
481 def __contains__(self, key: Union[LookupKey, str]) -> bool:
482 """Indicates whether the supplied key is present in the factory.
484 Parameters
485 ----------
486 key : `LookupKey`, `str` or objects with ``name`` attribute
487 Key to use to lookup in the factory whether a corresponding
488 formatter is present.
490 Returns
491 -------
492 in : `bool`
493 `True` if the supplied key is present in the factory.
494 """
495 return key in self._mappingFactory
497 def registerFormatters(self, config: Config, *, universe: DimensionUniverse) -> None:
498 """Bulk register formatters from a config.
500 Parameters
501 ----------
502 config : `Config`
503 ``formatters`` section of a configuration.
504 universe : `DimensionUniverse`, optional
505 Set of all known dimensions, used to expand and validate any used
506 in lookup keys.
508 Notes
509 -----
510 The configuration can include one level of hierarchy where an
511 instrument-specific section can be defined to override more general
512 template specifications. This is represented in YAML using a
513 key of form ``instrument<name>`` which can then define templates
514 that will be returned if a `DatasetRef` contains a matching instrument
515 name in the data ID.
517 The config is parsed using the function
518 `~lsst.daf.butler.configSubset.processLookupConfigs`.
520 The values for formatter entries can be either a simple string
521 referring to a python type or a dict representing the formatter and
522 parameters to be hard-coded into the formatter constructor. For
523 the dict case the following keys are supported:
525 - formatter: The python type to be used as the formatter class.
526 - parameters: A further dict to be passed directly to the
527 ``writeParameters`` Formatter constructor to seed it.
528 These parameters are validated at instance creation and not at
529 configuration.
531 Additionally, a special ``default`` section can be defined that
532 uses the formatter type (class) name as the keys and specifies
533 default write parameters that should be used whenever an instance
534 of that class is constructed.
536 .. code-block:: yaml
538 formatters:
539 default:
540 lsst.daf.butler.formatters.example.ExampleFormatter:
541 max: 10
542 min: 2
543 comment: Default comment
544 calexp: lsst.daf.butler.formatters.example.ExampleFormatter
545 coadd:
546 formatter: lsst.daf.butler.formatters.example.ExampleFormatter
547 parameters:
548 max: 5
550 Any time an ``ExampleFormatter`` is constructed it will use those
551 parameters. If an explicit entry later in the configuration specifies
552 a different set of parameters, the two will be merged with the later
553 entry taking priority. In the example above ``calexp`` will use
554 the default parameters but ``coadd`` will override the value for
555 ``max``.
557 Formatter configuration can also include a special section describing
558 collections of write parameters that can be accessed through a
559 simple label. This allows common collections of options to be
560 specified in one place in the configuration and reused later.
561 The ``write_recipes`` section is indexed by Formatter class name
562 and each key is the label to associate with the parameters.
564 .. code-block:: yaml
566 formatters:
567 write_recipes:
568 lsst.obs.base.formatters.fitsExposure.FixExposureFormatter:
569 lossless:
570 ...
571 noCompression:
572 ...
574 By convention a formatter that uses write recipes will support a
575 ``recipe`` write parameter that will refer to a recipe name in
576 the ``write_recipes`` component. The `Formatter` will be constructed
577 in the `FormatterFactory` with all the relevant recipes and
578 will not attempt to filter by looking at ``writeParameters`` in
579 advance. See the specific formatter documentation for details on
580 acceptable recipe options.
581 """
582 allowed_keys = {"formatter", "parameters"}
584 contents = processLookupConfigs(config, allow_hierarchy=True, universe=universe)
586 # Extract any default parameter settings
587 defaultParameters = contents.get(self.defaultKey, {})
588 if not isinstance(defaultParameters, Mapping):
589 raise RuntimeError("Default formatter parameters in config can not be a single string"
590 f" (got: {type(defaultParameters)})")
592 # Extract any global write recipes -- these are indexed by
593 # Formatter class name.
594 writeRecipes = contents.get(self.writeRecipesKey, {})
595 if isinstance(writeRecipes, str):
596 raise RuntimeError(f"The formatters.{self.writeRecipesKey} section must refer to a dict"
597 f" not '{writeRecipes}'")
599 for key, f in contents.items():
600 # default is handled in a special way
601 if key == self.defaultKey:
602 continue
603 if key == self.writeRecipesKey:
604 continue
606 # Can be a str or a dict.
607 specificWriteParameters = {}
608 if isinstance(f, str):
609 formatter = f
610 elif isinstance(f, Mapping):
611 all_keys = set(f)
612 unexpected_keys = all_keys - allowed_keys
613 if unexpected_keys:
614 raise ValueError(f"Formatter {key} uses unexpected keys {unexpected_keys} in config")
615 if "formatter" not in f:
616 raise ValueError(f"Mandatory 'formatter' key missing for formatter key {key}")
617 formatter = f["formatter"]
618 if "parameters" in f:
619 specificWriteParameters = f["parameters"]
620 else:
621 raise ValueError(f"Formatter for key {key} has unexpected value: '{f}'")
623 # Apply any default parameters for this formatter
624 writeParameters = copy.deepcopy(defaultParameters.get(formatter, {}))
625 writeParameters.update(specificWriteParameters)
627 kwargs: Dict[str, Any] = {}
628 if writeParameters:
629 kwargs["writeParameters"] = writeParameters
631 if formatter in writeRecipes:
632 kwargs["writeRecipes"] = writeRecipes[formatter]
634 self.registerFormatter(key, formatter, **kwargs)
636 def getLookupKeys(self) -> Set[LookupKey]:
637 """Retrieve the look up keys for all the registry entries.
639 Returns
640 -------
641 keys : `set` of `LookupKey`
642 The keys available for matching in the registry.
643 """
644 return self._mappingFactory.getLookupKeys()
646 def getFormatterClassWithMatch(self, entity: Entity) -> Tuple[LookupKey, Type[Formatter],
647 Dict[str, Any]]:
648 """Get the matching formatter class along with the matching registry
649 key.
651 Parameters
652 ----------
653 entity : `DatasetRef`, `DatasetType`, `StorageClass`, or `str`
654 Entity to use to determine the formatter to return.
655 `StorageClass` will be used as a last resort if `DatasetRef`
656 or `DatasetType` instance is provided. Supports instrument
657 override if a `DatasetRef` is provided configured with an
658 ``instrument`` value for the data ID.
660 Returns
661 -------
662 matchKey : `LookupKey`
663 The key that resulted in the successful match.
664 formatter : `type`
665 The class of the registered formatter.
666 formatter_kwargs : `dict`
667 Keyword arguments that are associated with this formatter entry.
668 """
669 names = (LookupKey(name=entity),) if isinstance(entity, str) else entity._lookupNames()
670 matchKey, formatter, formatter_kwargs = self._mappingFactory.getClassFromRegistryWithMatch(names)
671 log.debug("Retrieved formatter %s from key '%s' for entity '%s'", getFullTypeName(formatter),
672 matchKey, entity)
674 return matchKey, formatter, formatter_kwargs
676 def getFormatterClass(self, entity: Entity) -> Type:
677 """Get the matching formatter class.
679 Parameters
680 ----------
681 entity : `DatasetRef`, `DatasetType`, `StorageClass`, or `str`
682 Entity to use to determine the formatter to return.
683 `StorageClass` will be used as a last resort if `DatasetRef`
684 or `DatasetType` instance is provided. Supports instrument
685 override if a `DatasetRef` is provided configured with an
686 ``instrument`` value for the data ID.
688 Returns
689 -------
690 formatter : `type`
691 The class of the registered formatter.
692 """
693 _, formatter, _ = self.getFormatterClassWithMatch(entity)
694 return formatter
696 def getFormatterWithMatch(self, entity: Entity, *args: Any, **kwargs: Any) -> Tuple[LookupKey, Formatter]:
697 """Get a new formatter instance along with the matching registry
698 key.
700 Parameters
701 ----------
702 entity : `DatasetRef`, `DatasetType`, `StorageClass`, or `str`
703 Entity to use to determine the formatter to return.
704 `StorageClass` will be used as a last resort if `DatasetRef`
705 or `DatasetType` instance is provided. Supports instrument
706 override if a `DatasetRef` is provided configured with an
707 ``instrument`` value for the data ID.
708 args : `tuple`
709 Positional arguments to use pass to the object constructor.
710 kwargs : `dict`
711 Keyword arguments to pass to object constructor.
713 Returns
714 -------
715 matchKey : `LookupKey`
716 The key that resulted in the successful match.
717 formatter : `Formatter`
718 An instance of the registered formatter.
719 """
720 names = (LookupKey(name=entity),) if isinstance(entity, str) else entity._lookupNames()
721 matchKey, formatter = self._mappingFactory.getFromRegistryWithMatch(names, *args, **kwargs)
722 log.debug("Retrieved formatter %s from key '%s' for entity '%s'", getFullTypeName(formatter),
723 matchKey, entity)
725 return matchKey, formatter
727 def getFormatter(self, entity: Entity, *args: Any, **kwargs: Any) -> Formatter:
728 """Get a new formatter instance.
730 Parameters
731 ----------
732 entity : `DatasetRef`, `DatasetType`, `StorageClass`, or `str`
733 Entity to use to determine the formatter to return.
734 `StorageClass` will be used as a last resort if `DatasetRef`
735 or `DatasetType` instance is provided. Supports instrument
736 override if a `DatasetRef` is provided configured with an
737 ``instrument`` value for the data ID.
738 args : `tuple`
739 Positional arguments to use pass to the object constructor.
740 kwargs : `dict`
741 Keyword arguments to pass to object constructor.
743 Returns
744 -------
745 formatter : `Formatter`
746 An instance of the registered formatter.
747 """
748 _, formatter = self.getFormatterWithMatch(entity, *args, **kwargs)
749 return formatter
751 def registerFormatter(self, type_: Union[LookupKey, str, StorageClass, DatasetType],
752 formatter: str, *, overwrite: bool = False,
753 **kwargs: Any) -> None:
754 """Register a `Formatter`.
756 Parameters
757 ----------
758 type_ : `LookupKey`, `str`, `StorageClass` or `DatasetType`
759 Type for which this formatter is to be used. If a `LookupKey`
760 is not provided, one will be constructed from the supplied string
761 or by using the ``name`` property of the supplied entity.
762 formatter : `str` or class of type `Formatter`
763 Identifies a `Formatter` subclass to use for reading and writing
764 Datasets of this type. Can be a `Formatter` class.
765 overwrite : `bool`, optional
766 If `True` an existing entry will be replaced by the new value.
767 Default is `False`.
768 kwargs : `dict`
769 Keyword arguments to always pass to object constructor when
770 retrieved.
772 Raises
773 ------
774 ValueError
775 Raised if the formatter does not name a valid formatter type and
776 ``overwrite`` is `False`.
777 """
778 self._mappingFactory.placeInRegistry(type_, formatter, overwrite=overwrite, **kwargs)
781# Type to use when allowing a Formatter or its class name
782FormatterParameter = Union[str, Type[Formatter], Formatter]