Coverage for python/lsst/obs/base/gen2to3/convertRepo.py : 32%

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1# This file is part of obs_base.
2#
3# Developed for the LSST Data Management System.
4# This product includes software developed by the LSST Project
5# (https://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/>.
21from __future__ import annotations
23__all__ = ["ConvertRepoConfig", "ConvertRepoTask", "ConvertRepoSkyMapConfig"]
25import os
26import fnmatch
27from dataclasses import dataclass
28from typing import Iterable, Optional, List, Dict
30from lsst.utils import doImport
31from lsst.daf.butler import (
32 Butler as Butler3,
33 SkyPixDimension
34)
35from lsst.pex.config import Config, ConfigurableField, ConfigDictField, DictField, ListField, Field
36from lsst.pipe.base import Task
37from lsst.skymap import skyMapRegistry, BaseSkyMap
39from ..ingest import RawIngestTask
40from .repoConverter import ConversionSubset
41from .rootRepoConverter import RootRepoConverter
42from .calibRepoConverter import CalibRepoConverter
43from .standardRepoConverter import StandardRepoConverter
46@dataclass
47class ConfiguredSkyMap:
48 """Struct containing information about a skymap that may appear in a Gen2
49 repository.
50 """
52 name: str
53 """Name of the skymap used in Gen3 data IDs.
54 """
56 sha1: bytes
57 """Hash computed by `BaseSkyMap.getSha1`.
58 """
60 instance: BaseSkyMap
61 """Name of the skymap used in Gen3 data IDs.
62 """
64 used: bool = False
65 """Whether this skymap has been found in at least one repository being
66 converted.
67 """
70class ConvertRepoSkyMapConfig(Config):
71 """Sub-config used to hold the parameters of a SkyMap.
73 Notes
74 -----
75 This config only needs to exist because we can't put a
76 `~lsst.pex.config.RegistryField` directly inside a
77 `~lsst.pex.config.ConfigDictField`.
79 It needs to have its only field named "skyMap" for compatibility with the
80 configuration of `lsst.pipe.tasks.MakeSkyMapTask`, which we want so we can
81 use one config file in an obs package to configure both.
83 This name leads to unfortunate repetition with the field named
84 "skymap" that holds it - "skyMap[name].skyMap" - but that seems
85 unavoidable.
86 """
87 skyMap = skyMapRegistry.makeField(
88 doc="Type and parameters for the SkyMap itself.",
89 default="dodeca",
90 )
93class ConvertRepoConfig(Config):
94 raws = ConfigurableField(
95 "Configuration for subtask responsible for ingesting raws and adding "
96 "visit and exposure dimension entries.",
97 target=RawIngestTask,
98 )
99 skyMaps = ConfigDictField(
100 "Mapping from Gen3 skymap name to the parameters used to construct a "
101 "BaseSkyMap instance. This will be used to associate names with "
102 "existing skymaps found in the Gen2 repo.",
103 keytype=str,
104 itemtype=ConvertRepoSkyMapConfig,
105 default={}
106 )
107 rootSkyMapName = Field(
108 "Name of a Gen3 skymap (an entry in ``self.skyMaps``) to assume for "
109 "datasets in the root repository when no SkyMap is found there. ",
110 dtype=str,
111 optional=True,
112 default=None,
113 )
114 collections = DictField(
115 "Special collections (values) for certain dataset types (keys). "
116 "These are used in addition to rerun collections for datasets in "
117 "reruns. The 'raw' dataset must have an entry here if it is to be "
118 "converted.",
119 keytype=str,
120 itemtype=str,
121 default={
122 "deepCoadd_skyMap": "skymaps",
123 "brightObjectMask": "masks",
124 }
125 )
126 storageClasses = DictField(
127 "Mapping from dataset type name or Gen2 policy entry (e.g. 'python' "
128 "or 'persistable') to the Gen3 StorageClass name.",
129 keytype=str,
130 itemtype=str,
131 default={
132 "BaseSkyMap": "SkyMap",
133 "BaseCatalog": "Catalog",
134 "BackgroundList": "Background",
135 "raw": "Exposure",
136 "MultilevelParquetTable": "DataFrame",
137 "ParquetTable": "DataFrame",
138 "SkyWcs": "Wcs",
139 }
140 )
141 doRegisterInstrument = Field(
142 "If True (default), add dimension records for the Instrument and its "
143 "filters and detectors to the registry instead of assuming they are "
144 "already present.",
145 dtype=bool,
146 default=True,
147 )
148 doWriteCuratedCalibrations = Field(
149 "If True (default), ingest human-curated calibrations directly via "
150 "the Instrument interface. Note that these calibrations are never "
151 "converted from Gen2 repositories.",
152 dtype=bool,
153 default=True,
154 )
155 refCats = ListField(
156 "The names of reference catalogs (subdirectories under ref_cats) to "
157 "be converted",
158 dtype=str,
159 default=[]
160 )
161 fileIgnorePatterns = ListField(
162 "Filename globs that should be ignored instead of being treated as "
163 "datasets.",
164 dtype=str,
165 default=["README.txt", "*~?", "butler.yaml", "gen3.sqlite3",
166 "registry.sqlite3", "calibRegistry.sqlite3", "_mapper",
167 "_parent", "repositoryCfg.yaml"]
168 )
169 datasetIncludePatterns = ListField(
170 "Glob-style patterns for dataset type names that should be converted.",
171 dtype=str,
172 default=["*"]
173 )
174 datasetIgnorePatterns = ListField(
175 "Glob-style patterns for dataset type names that should not be "
176 "converted despite matching a pattern in datasetIncludePatterns.",
177 dtype=str,
178 default=[]
179 )
180 ccdKey = Field(
181 "Key used for the Gen2 equivalent of 'detector' in data IDs.",
182 dtype=str,
183 default="ccd",
184 )
185 relatedOnly = Field(
186 "If True (default), only convert datasets that are related to the "
187 "ingested visits. Ignored unless a list of visits is passed to "
188 "run().",
189 dtype=bool,
190 default=False,
191 )
193 @property
194 def transfer(self):
195 return self.raws.transfer
197 @transfer.setter
198 def transfer(self, value):
199 self.raws.transfer = value
201 @property
202 def instrument(self):
203 return self.raws.instrument
205 @instrument.setter
206 def instrument(self, value):
207 self.raws.instrument = value
209 def setDefaults(self):
210 self.transfer = None
212 # TODO: check that there are no collection overrides for curated
213 # calibrations, since we don't have a good way to utilize them.
216class ConvertRepoTask(Task):
217 """A task that converts one or more related Gen2 data repositories to a
218 single Gen3 data repository (with multiple collections).
220 Parameters
221 ----------
222 config: `ConvertRepoConfig`
223 Configuration for this task.
224 butler3: `lsst.daf.butler.Butler`
225 Gen3 Butler instance that represents the data repository datasets will
226 be ingested into. The collection and/or run associated with this
227 Butler will be ignored in favor of collections/runs passed via config
228 or to `run`.
229 kwds
230 Other keyword arguments are forwarded to the `Task` constructor.
232 Notes
233 -----
234 Most of the work of converting repositories is delegated to instances of
235 the `RepoConverter` hierarchy. The `ConvertRepoTask` instance itself holds
236 only state that is relevant for all Gen2 repositories being ingested, while
237 each `RepoConverter` instance holds only state relevant for the conversion
238 of a single Gen2 repository. Both the task and the `RepoConverter`
239 instances are single use; `ConvertRepoTask.run` and most `RepoConverter`
240 methods may only be called once on a particular instance.
241 """
243 ConfigClass = ConvertRepoConfig
245 _DefaultName = "convertRepo"
247 def __init__(self, config=None, *, butler3: Butler3, **kwds):
248 super().__init__(config, **kwds)
249 self.butler3 = butler3
250 self.registry = self.butler3.registry
251 self.universe = self.registry.dimensions
252 if self.isDatasetTypeIncluded("raw"):
253 self.makeSubtask("raws", butler=butler3)
254 self.instrument = self.raws.instrument
255 else:
256 self.raws = None
257 self.instrument = doImport(self.config.instrument)()
258 self._configuredSkyMapsBySha1 = {}
259 self._configuredSkyMapsByName = {}
260 for name, config in self.config.skyMaps.items():
261 instance = config.skyMap.apply()
262 struct = ConfiguredSkyMap(name=name, sha1=instance.getSha1(), instance=instance)
263 self._configuredSkyMapsBySha1[struct.sha1] = struct
264 self._configuredSkyMapsByName[struct.name] = struct
265 self._usedSkyPix = set()
267 def isDatasetTypeIncluded(self, datasetTypeName: str):
268 """Return `True` if configuration indicates that the given dataset type
269 should be converted.
271 This method is intended to be called primarily by the
272 `RepoConverter` instances used interally by the task.
274 Parameters
275 ----------
276 datasetTypeName: str
277 Name of the dataset type.
279 Returns
280 -------
281 included : `bool`
282 Whether the dataset should be included in the conversion.
283 """
284 return (
285 any(fnmatch.fnmatchcase(datasetTypeName, pattern)
286 for pattern in self.config.datasetIncludePatterns)
287 and not any(fnmatch.fnmatchcase(datasetTypeName, pattern)
288 for pattern in self.config.datasetIgnorePatterns)
289 )
291 def useSkyMap(self, skyMap: BaseSkyMap) -> str:
292 """Indicate that a repository uses the given SkyMap.
294 This method is intended to be called primarily by the
295 `RepoConverter` instances used interally by the task.
297 Parameters
298 ----------
299 skyMap : `lsst.skymap.BaseSkyMap`
300 SkyMap instance being used, typically retrieved from a Gen2
301 data repository.
303 Returns
304 -------
305 name : `str`
306 The name of the skymap in Gen3 data IDs.
307 """
308 sha1 = skyMap.getSha1()
309 try:
310 struct = self._configuredSkyMapsBySha1[sha1]
311 except KeyError as err:
312 raise LookupError(f"SkyMap with sha1={sha1} not included in configuration.") from err
313 struct.used = True
314 return struct.name
316 def registerUsedSkyMaps(self, subset: Optional[ConversionSubset]):
317 """Register all skymaps that have been marked as used.
319 This method is intended to be called primarily by the
320 `RepoConverter` instances used interally by the task.
322 Parameters
323 ----------
324 subset : `ConversionSubset`, optional
325 Object that will be used to filter converted datasets by data ID.
326 If given, it will be updated with the tracts of this skymap that
327 overlap the visits in the subset.
328 """
329 for struct in self._configuredSkyMapsBySha1.values():
330 if struct.used:
331 struct.instance.register(struct.name, self.registry)
332 if subset is not None and self.config.relatedOnly:
333 subset.addSkyMap(self.registry, struct.name)
335 def useSkyPix(self, dimension: SkyPixDimension):
336 """Indicate that a repository uses the given SkyPix dimension.
338 This method is intended to be called primarily by the
339 `RepoConverter` instances used interally by the task.
341 Parameters
342 ----------
343 dimension : `lsst.daf.butler.SkyPixDimension`
344 Dimension represening a pixelization of the sky.
345 """
346 self._usedSkyPix.add(dimension)
348 def registerUsedSkyPix(self, subset: Optional[ConversionSubset]):
349 """Register all skymaps that have been marked as used.
351 This method is intended to be called primarily by the
352 `RepoConverter` instances used interally by the task.
354 Parameters
355 ----------
356 subset : `ConversionSubset`, optional
357 Object that will be used to filter converted datasets by data ID.
358 If given, it will be updated with the pixelization IDs that
359 overlap the visits in the subset.
360 """
361 if subset is not None and self.config.relatedOnly:
362 for dimension in self._usedSkyPix:
363 subset.addSkyPix(self.registry, dimension)
365 def run(self, root: str, collections: List[str], *,
366 calibs: Dict[str, List[str]] = None,
367 reruns: Dict[str, List[str]] = None,
368 visits: Optional[Iterable[int]] = None):
369 """Convert a group of related data repositories.
371 Parameters
372 ----------
373 root : `str`
374 Complete path to the root Gen2 data repository. This should be
375 a data repository that includes a Gen2 registry and any raw files
376 and/or reference catalogs.
377 collections : `list` of `str`
378 Gen3 collections that datasets from the root repository should be
379 associated with. This should include any rerun collection that
380 these datasets should also be considered to be part of; because of
381 structural difference between Gen2 parent/child relationships and
382 Gen3 collections, these cannot be reliably inferred.
383 calibs : `dict`
384 Dictionary mapping calibration repository path to the collections
385 that the repository's datasets should be associated with. The path
386 may be relative to ``root`` or absolute. Collections should
387 include child repository collections as appropriate (see
388 documentation for ``collections``).
389 reruns : `dict`
390 Dictionary mapping rerun repository path to the collections that
391 the repository's datasets should be associated with. The path may
392 be relative to ``root`` or absolute. Collections should include
393 child repository collections as appropriate (see documentation for
394 ``collections``).
395 visits : iterable of `int`, optional
396 The integer IDs of visits to convert. If not provided, all visits
397 in the Gen2 root repository will be converted.
398 """
400 if calibs is None:
401 calibs = {}
402 if reruns is None:
403 reruns = {}
404 if visits is not None:
405 subset = ConversionSubset(instrument=self.instrument.getName(), visits=frozenset(visits))
406 else:
407 if self.config.relatedOnly:
408 self.log.warn("config.relatedOnly is True but all visits are being ingested; "
409 "no filtering will be done.")
410 subset = None
412 # We can't wrap database writes sanely in transactions (yet) because we
413 # keep initializing new Butler instances just so we can write into new
414 # runs/collections, and transactions are managed at the Butler level.
415 # DM-21246 should let us fix this, assuming we actually want to keep
416 # the transaction open that long.
417 if self.config.doRegisterInstrument:
418 self.instrument.register(self.registry)
420 # Make and prep converters for all Gen2 repos. This should not modify
421 # the Registry database or filesystem at all, though it may query it.
422 # The prep() calls here will be some of the slowest ones, because
423 # that's when we walk the filesystem.
424 converters = []
425 rootConverter = RootRepoConverter(task=self, root=root, collections=collections, subset=subset)
426 rootConverter.prep()
427 converters.append(rootConverter)
429 for root, collections in calibs.items():
430 if not os.path.isabs(root):
431 root = os.path.join(rootConverter.root, root)
432 converter = CalibRepoConverter(task=self, root=root, collections=collections,
433 mapper=rootConverter.mapper,
434 subset=rootConverter.subset)
435 converter.prep()
436 converters.append(converter)
438 for root, collections in reruns.items():
439 if not os.path.isabs(root):
440 root = os.path.join(rootConverter.root, root)
441 converter = StandardRepoConverter(task=self, root=root, collections=collections,
442 subset=rootConverter.subset)
443 converter.prep()
444 converters.append(converter)
446 # Actual database writes start here. We can't wrap these sanely in
447 # transactions (yet) because we keep initializing new Butler instances
448 # just so we can write into new runs/collections, and transactions
449 # are managed at the Butler level (DM-21246 should let us fix this).
451 # Insert dimensions needed by any converters. These are only the
452 # dimensions that a converter expects to be uniquely derived from the
453 # Gen2 repository it is reponsible for - e.g. visits, exposures, and
454 # calibration_labels.
455 #
456 # Note that we do not try to filter dimensions down to just those
457 # related to the given visits, even if config.relatedOnly is True; we
458 # need them in the Gen3 repo in order to be able to know which datasets
459 # to convert, because Gen2 alone doesn't know enough about the
460 # relationships between data IDs.
461 for converter in converters:
462 converter.insertDimensionData()
464 # Insert dimensions that are potentially shared by all Gen2
465 # repositories (and are hence managed directly by the Task, rather
466 # than a converter instance).
467 # This also finishes setting up the (shared) converter.subsets object
468 # that is used to filter data IDs for config.relatedOnly.
469 self.registerUsedSkyMaps(rootConverter.subset)
470 self.registerUsedSkyPix(rootConverter.subset)
472 # Look for datasets, generally by scanning the filesystem.
473 # This requires dimensions to have already been inserted so we can use
474 # dimension information to identify related datasets.
475 for converter in converters:
476 converter.findDatasets()
478 # Expand data IDs.
479 for converter in converters:
480 converter.expandDataIds()
482 # Actually ingest datasets.
483 for converter in converters:
484 converter.ingest()