Deprecate specialist gen3 raw ingest task

python/lsst/obs/cfht/ingest.py

@@ -24,10 +24,9 @@
 
 import re
 
-from lsst.daf.butler import ButlerURI, Formatter
+from deprecated.sphinx import deprecated
+
 import lsst.obs.base
-from lsst.obs.base.ingest import RawFileData
-from astro_metadata_translator import fix_header
 
 from lsst.pipe.tasks.ingest import ParseTask
 import lsst.pex.exceptions
@@ -46,47 +45,13 @@
            }
 
 
+@deprecated(reason="MegaPrime no longer requires a specialist gen3 ingest task. Please use the default."
+            " Will be removed after v23.",
+            category=FutureWarning,
+            version="22.0")
 class MegaPrimeRawIngestTask(lsst.obs.base.RawIngestTask):
     """Task for ingesting raw MegaPrime multi-extension FITS data into Gen3.
     """
-    def extractMetadata(self, filename: ButlerURI) -> RawFileData:
-        datasets = []
-
-        try:
-            with filename.as_local() as local_file:
-                fitsData = lsst.afw.fits.Fits(local_file.ospath, "r")
-
-                # NOTE: The primary header (HDU=0) does not contain detector
-                # data.
-                for i in range(1, fitsData.countHdus()):
-                    fitsData.setHdu(i)
-                    header = fitsData.readMetadata()
-                    if not header["EXTNAME"].startswith("ccd"):
-                        continue
-                    fix_header(header)
-                    datasets.append(self._calculate_dataset_info(header, filename))
-        except Exception as e:
-            self.log.debug("Problem extracting metadata from %s: %s", filename, e)
-            # Indicate to the caller that we failed to read.
-            # Do not try to ingest partial contents of file.
-            datasets = []
-            formatterClass = Formatter
-            instrument = None
-            self._on_metadata_failure(filename, e)
-            if self.config.failFast:
-                raise RuntimeError(f"Problem extracting metadata for file {filename}") from e
-        else:
-            # The data model currently assumes that whilst multiple datasets
-            # can be associated with a single file, they must all share the
-            # same formatter.
-            instrument, formatterClass = self._determine_instrument_formatter(datasets[0].dataId, filename)
-            if instrument is None:
-                datasets = []
-
-        self.log.info(f"Found images for {len(datasets)} detectors in {filename}")
-        return RawFileData(datasets=datasets, filename=filename,
-                           FormatterClass=formatterClass,
-                           instrumentClass=type(instrument))
 
 
 class MegacamParseTask(ParseTask):

tests/test_ingest.py

@@ -42,7 +42,6 @@ class MegaPrimeIngestTestCase(IngestTestBase, lsst.utils.tests.TestCase):
     curatedCalibrationDatasetTypes = ()
     ingestDir = os.path.dirname(__file__)
     instrumentClassName = "lsst.obs.cfht.MegaPrime"
-    rawIngestTask = "lsst.obs.cfht.MegaPrimeRawIngestTask"
     filterLabel = lsst.afw.image.FilterLabel(physical="i.MP9702", band="i")
 
     @property