"""
An abstract processor and some helping code.

Currently, I assume a plain text interface for those.  It might be
a good idea to use the event mechanism here.
"""

#c Copyright 2008-2025, the GAVO project <gavo@ari.uni-heidelberg.de>
#c
#c This program is free software, covered by the GNU GPL.  See the
#c COPYING file in the source distribution.


import io
import os
import sys
import textwrap
import threading
import traceback
from contextlib import contextmanager

from PIL import Image

from gavo import base
from gavo import rsc
from gavo import utils
from gavo.helpers import anet
from gavo.helpers import fitstricks
from gavo.utils import fitstools
from gavo.utils import pyfits


# matplotlib is an expensive import.  Only do that if we're sure
# we need it.
matplotlib = utils.DeferredImport("matplotlib", "import matplotlib")
figure = utils.DeferredImport("figure", "from matplotlib import figure")

_MPL_LOCK = threading.RLock()
@contextmanager
def matplotlibLock():
	_MPL_LOCK.acquire()
	matplotlib.use("Agg")
	try:
		yield
	finally:
		_MPL_LOCK.release()


class CannotComputeHeader(Exception):
	"""is raised when no FITS header was generated by a HeaderProcessor.
	
	Specifically, this is what gets raised when ``_getHeader`` returns ``None``.
	"""


class FileProcessor(object):
	"""An abstract base for a source file processor.

	In concrete classes, you need to define a ``process(accref)`` method
	receiving a source as returned by the dd (i.e., usually an inputsDir-relative
	file name).

	You can override the method ``_createAuxiliaries(dataDesc)`` to compute
	things like source catalogues, etc.  Thus, you should not need to
	override the constructor.

	These objects are usually constructed thorough ``api.procmain`` as
	discussed in :dachsdoc:`processing.html`.
	"""
	inputsDir = base.getConfig("inputsDir")

	def __init__(self, opts, dd):
		self.opts, self.dd = opts, dd
		self._createAuxiliaries(dd)

	def _createAuxiliaries(self, dd):
		# There's been a typo here in previous DaCHS versions; try
		# to call old methods if they are still there
		if hasattr(self, "_createAuxillaries"):
			self._createAuxillaries(dd)

	def classify(self, srcName):
		return "unknown"

	def process(self, accref):
		pass
	
	def addClassification(self, srcName):
		label = self.classify(srcName)
		self.reportDict.setdefault(label, []).append(os.path.basename(srcName))

	def printTableSize(self):
		try:
			tableName = self.dd.makes[0].table.getQName()
			with base.AdhocQuerier(base.getAdminConn) as q:
				itemsInDB = list(q.query("SELECT count(*) from %s"%tableName))[0][0]
			print("Items currently in assumed database table: %d\n"%itemsInDB)
		except (base.DBError, IndexError):
			pass

	def printReport(self, processed, ignored):
		print("\n\nProcessor Report\n================\n")
		if ignored:
			print("Warning: There were %d errors during classification"%ignored)
		repData = sorted(zip([len(l) for l in list(self.reportDict.values())],
                                     list(self.reportDict.keys())))
		print(utils.formatSimpleTable(repData))
		print("\n")
		self.printTableSize()

	def printVerboseReport(self, processed, ignored):
		print("\n\nProcessor Report\n================\n")
		if ignored:
			print("Warning: There were %d errors during classification"%ignored)
		repData = sorted(zip(list(self.reportDict.values()),
                                     list(self.reportDict.keys())),
                                 key=lambda v: -len(v[0]))
		print("\n%s\n%s\n"%(repData[0][1], "-"*len(repData[0][1])))
		print("%d items\n"%(len(repData[0][0])))
		for items, label in repData[1:]:
			print("\n%s\n%s\n"%(label, "-"*len(label)))
			items.sort()
			print("%d items:\n"%(len(items)))
			print("\n".join(textwrap.wrap(", ".join(items))))
		print("\n")
		self.printTableSize()

	@staticmethod
	def addOptions(parser):
		parser.add_option("--filter", dest="requireFrag", metavar="STR",
			help="Only process files with names containing STR", default=None)
		parser.add_option("--bail", help="Bail out on a processor error,"
			" dumping a traceback", action="store_true", dest="bailOnError",
			default=False)
		parser.add_option("--report", help="Output a report only",
			action="store_true", dest="doReport", default=False)
		parser.add_option("--verbose", help="Be more talkative",
			action="store_true", dest="beVerbose", default=False)
		parser.add_option("--n-procs", "-j", help="Run NUM processes in"
			" parallel", action="store", dest="nParallel", default=1,
			metavar="NUM", type=int)

	_doneSentinel = ("MAGIC: QUEUE DONE",)

	def iterJobs(self, nParallel):
		"""executes process() in parallel for all sources and iterates
		over the results.

		We use this rather than multiprocessing's Pool, as that cannot
		call methods.  I'm working around this here.
		"""
		import multiprocessing

		taskQueue = multiprocessing.Queue(nParallel*4)
		doneQueue = multiprocessing.Queue()

		def worker(inQueue, outQueue):
			if hasattr(self, "conn"):
				self.conn = base.getDBConnection("trustedquery")
			for srcId in iter(inQueue.get, None):
				if (self.opts.requireFrag is not None
						and not self.opts.requireFrag in srcId):
					continue

				try:
					outQueue.put(self.process(srcId))
				except base.SkipThis:
					continue
				except Exception as ex:
					ex.source = srcId
					if self.opts.bailOnError:
						sys.stderr.write("*** %s\n"%srcId)
						traceback.print_exc()
					outQueue.put(ex)
			outQueue.put(self._doneSentinel)

		# create nParallel workers
		activeWorkers = 0
		# close my connection; it'll be nothing but trouble once
		# the workers see (and close) it, too
		if hasattr(self, "conn"):
			self.conn.close()
		for i in range(nParallel):
			multiprocessing.Process(target=worker,
				args=(taskQueue, doneQueue)).start()
			activeWorkers += 1
		if hasattr(self, "conn"):
			self.conn = base.getDBConnection("trustedquery")

		# feed them their tasks
		toDo = self.iterIdentifiers()
		while True:
			try:
				taskQueue.put(next(toDo))
			except StopIteration:
				break

			while not doneQueue.empty():
				yield doneQueue.get()

		# ask them to quit and wait until all have said they're quitting
		for i in range(nParallel):
			taskQueue.put(None)
		taskQueue.close()
		while activeWorkers:
			item = doneQueue.get()
			if item==self._doneSentinel:
				activeWorkers -= 1
			else:
				yield item

	def _runProcessor(self, procFunc, nParallel=1):
		"""calls procFunc for all sources in self.dd.

		This is the default, single-tasking implementation.
		"""
		processed, ignored = 0, 0

		if nParallel==1:
			def iterProcResults():
				for source in self.iterIdentifiers():
					if (self.opts.requireFrag is not None
							and not self.opts.requireFrag in source):
						continue

					try:
						yield procFunc(source)
					except base.SkipThis:
						continue
					except Exception as ex:
						ex.source = source
						if self.opts.bailOnError:
							sys.stderr.write("*** %s\n"%source)
							traceback.print_exc()
						yield ex
			resIter = iterProcResults()
		else:
			resIter = self.iterJobs(nParallel)

		while True:
			try:
				res = next(resIter)
				if isinstance(res, Exception):
					raise res
			except StopIteration:
				break
			except KeyboardInterrupt:
				sys.exit(2)
			except Exception as msg:
				if self.opts.bailOnError:
					sys.exit(1)
				sys.stderr.write("Skipping source %s: (%s, %s)\n"%(
					getattr(msg, "source", "(unknown)"), msg.__class__.__name__,
						repr(msg)))
				ignored += 1
			processed += 1
			sys.stdout.write("%6d (-%5d)\r"%(processed, ignored))
			sys.stdout.flush()
		return processed, ignored

	def iterIdentifiers(self):
		"""iterates over all identifiers that should be processed.

		This is usually the paths of the files to be processed.
		You can, however, override it to do something else if that
		fits your problem (example: Previews in SSA use the accref).
		"""
		return iter(self.dd.sources)

	def processAll(self):
		"""calls the process method of processor for all sources of the data
		descriptor dd.
		"""
		if self.opts.doReport:
			self.reportDict = {}
			procFunc = self.addClassification
		else:
			procFunc = self.process
		processed, ignored = self._runProcessor(procFunc,
			nParallel=self.opts.nParallel)
		if self.opts.doReport:
			if self.opts.beVerbose:
				self.printVerboseReport(processed, ignored)
			else:
				self.printReport(processed, ignored)
		return processed, ignored

	######### Utility methods

	def getProductKey(self, srcName):
		return utils.getRelativePath(str(srcName), self.inputsDir)


class ImmediateHeaderProcessor(FileProcessor):
	"""An base for processors doing simple FITS manipulations to the primary
	FITS header.

	To define these, override ``_isProcessed(self, srcName, hdr)`` and
	``_changeHeader(self, hdr)``.

	``_changeHeader`` can change the pyfits header ``hdr`` in place.  It
	will then be replaced on the actual file.

	For complex operations, it is probably advisable to use ``HeaderProcessor``
	which gives you a two-step process of first having the detached headers
	that you can check before applying them.
	"""
	def _isProcessed(self, srcName, hdr):
		return False

	def process(self, accref):
		srcName = str(self.inputsDir / accref)
		with open(srcName, "rb") as f:
			hdr = fitstools.readPrimaryHeaderQuick(f)
		if not self.opts.reProcess:
			if self._isProcessed(srcName, hdr):
				return

		self._changeHeader(srcName, hdr)
		fitstools.replacePrimaryHeaderInPlace(srcName, hdr)

	@staticmethod
	def addOptions(optParser):
		FileProcessor.addOptions(optParser)
		optParser.add_option("--reprocess", help="Recompute all headers",
			action="store_true", dest="reProcess", default=False)


class HeaderProcessor(FileProcessor):
	"""A base for processors doing FITS header manipulations.

	The processor builds naked FITS headers alongside the actual files, with an
	added extension .hdr (or whatever is in the headerExt attribute).  The
	presence of a FITS header indicates that a file has been processed.  The
	headers on the actual FITS files are only replaced if necessary.

	The basic flow is: Check if there is a header.  If not, call
	_getNewHeader(srcFile) -> hdr.  Store hdr to cache.  Insert cached
	header in the new FITS if it's not there yet.

	You have to implement the _getHeader(srcName) -> pyfits header object
	function.  It must raise an exception if it cannot come up with a
	header.  You also have to implement _isProcessed(srcName) -> boolean
	returning True if you think srcName already has a processed header.

	This basic flow is influenced by the following opts attributes:

	* reProcess -- even if a cache is present, recompute header values
	* applyHeaders -- actually replace old headers with new headers
	* reHeader -- even if _isProcessed returns True, write a new header
	* compute -- perform computations

	The idea is that you can:

	* generate headers without touching the original files: proc
	* write all cached headers to files that don't have them:
	  ``proc --apply --nocompute``
	* after a bugfix force all headers to be regenerated:
	  ``proc --reprocess --apply --reheader``
	
	All this leads to the messy logic.  Sorry about this.
	"""
	headerExt = ".hdr"
	maxHeaderBlocks = 40
	cardSequence = None

	def _makeCacheName(self, srcName):
		return srcName+self.headerExt

	def _writeCache(self, srcName, hdr):
		dest = self._makeCacheName(srcName)

		# nuke info on sizes that may still lurk; we don't want that in the
		# cache
		hdr = hdr.copy()
		hdr.set("BITPIX", 8)
		hdr.set("NAXIS", 0)
		if "NAXIS1" in hdr:
			del hdr["NAXIS1"]
		if "NAXIS2" in hdr:
			del hdr["NAXIS2"]

		hdr = fitstools.sortHeaders(hdr,
			commentFilter=self.commentFilter,
			historyFilter=self.historyFilter,
			cardSequence=self.cardSequence)

		serialized = fitstools.serializeHeader(hdr)
		with open(dest, "wb") as f:
			f.write(serialized)
		hdus = pyfits.open(dest)
		hdus.verify()
		hdus.close()

	def _readCache(self, srcName):
		"""returns a pyfits header object for the cached result in srcName.

		If there is no cache, None is returned.
		"""
		src = self._makeCacheName(srcName)
		if os.path.exists(src):
			with open(src, "rb") as f:
				hdr = fitstools.readPrimaryHeaderQuick(f, self.maxHeaderBlocks)
			return hdr

	def _makeCache(self, srcName):
		if self.opts.compute:
			if self.opts.beVerbose:
				print("Now computing for", srcName)
			hdr = self._getHeader(srcName)
			if hdr is None:
				raise CannotComputeHeader("_getHeader returned None")
			self._writeCache(srcName, hdr)

	# headers copied from original file rather than the cached header
	keepKeys = set(["SIMPLE", "BITPIX", "NAXIS", "NAXIS1", "NAXIS2",
			"EXTEND", "BZERO", "BSCALE"])

	def _fixHeaderDataKeys(self, srcName, header):
		oldHeader = self.getPrimaryHeader(srcName)
		for key in self.keepKeys:
			if key in oldHeader:
				header.set(key, oldHeader[key])

	def commentFilter(self, value):
		"""returns true if the comment value should be preserved.

		You may want to override this.
		"""
		return True
	
	def historyFilter(self, value):
		"""returns true if the history item value should be preserved.
		"""
		return True

	def _writeHeader(self, srcName, header):
		self._fixHeaderDataKeys(srcName, header)
		header = fitstools.sortHeaders(header, commentFilter=self.commentFilter,
			historyFilter=self.historyFilter)
		fitstools.replacePrimaryHeaderInPlace(srcName, header)

	def _isProcessed(self, srcName):
		"""override.
		"""
		return False

	def _mungeHeader(self, srcName, header):
		"""override this or _getHeader.
		"""
		return header

	def _getHeader(self, srcName):
		"""override this or _mungeHeader.
		"""
		return self._mungeHeader(srcName, self.getPrimaryHeader(srcName))

	@staticmethod
	def getPrimaryHeader(srcName):
		"""returns the primary header of srcName.

		This is a convenience function for user derived classes.
		"""
		f = open(srcName, "rb")
		hdr = utils.readPrimaryHeaderQuick(f)
		f.close()
		return hdr

	def process(self, accref):
		srcName = str(self.inputsDir / accref)
		if (not (self.opts.reProcess or self.opts.reHeader)
				and self._isProcessed(srcName)):
			return
		cache = self._readCache(srcName)
		if cache is None or self.opts.reProcess:
			self._makeCache(srcName)
			cache = self._readCache(srcName)
		if cache is None:
			return
		if not self.opts.applyHeaders:
			return
		if self.opts.reHeader or not self._isProcessed(srcName):
			self._writeHeader(srcName, cache)

	@staticmethod
	def addOptions(optParser):
		FileProcessor.addOptions(optParser)
		optParser.add_option("--reprocess", help="Recompute all headers",
			action="store_true", dest="reProcess", default=False)
		optParser.add_option("--no-compute", help="Only use cached headers",
			action="store_false", dest="compute", default=True)
		optParser.add_option("--apply", help="Write cached headers to"
			" source files", action="store_true", dest="applyHeaders",
			default=False)
		optParser.add_option("--reheader", help="Write cached headers"
			" to source files even if it looks like they already have"
			" been written", action="store_true", dest="reHeader",
			default=False)


class AnetHeaderProcessor(HeaderProcessor):
	"""A file processor for calibrating FITS frames using astrometry.net.

	It might provide calibration for "simple" cases out of the box.  You
	will usually want to override some solver parameters.  To do that,
	define class attributes sp_<parameter name>, where the parameters
	available are discussed in helpers.anet's docstring.  sp_indices is
	one thing you will typically need to override.
	
	To use SExtractor rather than anet's source extractor, override
	sexControl, to use an object filter (see anet.getWCSFieldsFor), override
	the objectFilter attribute.

	To add additional fields, override _getHeader and call the parent
	class' _getHeader method.  To change the way astrometry.net is
	called, override the _solveAnet method (it needs to return some
	result anet.of getWCSFieldsFor) and call _runAnet with your
	custom arguments for getWCSFieldsFor.

	See :dachsdoc:`processors#astrometry-net` for details.
	"""
	sourceExtractorControl = None
	objectFilter = None
	indexPath = base.getConfig("rootDir") / "astrometry-indexes"

	noCopyHeaders = set(["simple", "bitpix", "naxis", "imageh", "imagew",
		"naxis1", "naxis2", "datamin", "datamax", "date"])

	@staticmethod
	def addOptions(optParser):
		def storeDestPath(opt, opt_str, value, parser):
			parser.values.copyTo = os.path.join(
				os.getcwd(),
				os.path.expanduser(value))

		HeaderProcessor.addOptions(optParser)
		optParser.add_option("--no-anet", help="Do not run anet, fail if"
			" no cache is present to take anet headers from", action="store_false",
			dest="runAnet", default=True)
		optParser.add_option("--copy-to", help="Copy astrometry.net sandbox to"
			" this directory (WARNING: it will be deleted if it exists!)."
			"  Probably most useful with --bail", type="str",
			action="callback", callback=storeDestPath)
		optParser.set_defaults(copyTo=None)

	def _isProcessed(self, srcName):
		return "CD1_1" in self.getPrimaryHeader(srcName)

	def _runAnet(self, srcName):
		return anet.getWCSFieldsFor(
			srcName, self.solverParameters,
			self.sourceExtractorControl,
			self.objectFilter,
			getattr(self.opts, "copyTo", None),
			self.indexPath,
			self.opts.beVerbose)

	@property
	def solverParameters(self):
		return dict(
			(n[3:], getattr(self, n))
			for n in dir(self) if n.startswith("sp_"))

	def _solveAnet(self, srcName):
		if self.opts.runAnet:
			return self._runAnet(srcName)
		else:
			oldCards = self._readCache(srcName)
			if oldCards is None:
				raise CannotComputeHeader("No cached headers and you asked"
					" not to run astrometry.net")
			return oldCards.cards

	def _shouldRunAnet(self, srcName, hdr):
		return True

	def _getHeader(self, srcName):
		hdr = self.getPrimaryHeader(srcName)
		if self._shouldRunAnet(srcName, hdr):
			wcsCards = self._solveAnet(srcName)
			if not wcsCards:
				raise CannotComputeHeader("astrometry.net did not"
					" find a solution")
			fitstricks.copyFields(hdr, wcsCards, self.noCopyHeaders)
		return self._mungeHeader(srcName, hdr)

	def commentFilter(self, value):
		return ( "Index name" in value or
			"Cxdx margin" in value or
			"Field scale lower" in value or
			"Field scale upper" in value or
			"Start obj" in value or
			"End obj" in value or
			"Tweak" in value or
			"code error" in value)

	def historyFilter(self, value):
		return ("suite" in value or
			"blind" in value)


class PreviewMaker(FileProcessor):
	"""A file processor for generating previews.

	For these, define a method getPreviewData(accref) -> string returning
	the raw preview data.
	"""
	@staticmethod
	def addOptions(optParser):
		FileProcessor.addOptions(optParser)
		optParser.add_option("--force", help="Generate previews even"
			" where they already exist", action="store_true",
			dest="force", default=False)

	def iterIdentifiers(self):
		"""iterates over the accrefs in the first table of dd.
		"""
		tableId = self.dd.makes[0].table.getQName()
		for r in self.conn.queryToDicts("select accref from %s"%tableId):
			yield r["accref"]

	def _createAuxiliaries(self, dd):
		self.previewDir = dd.rd.getAbsPath(
			dd.getProperty("previewDir"))
		if not os.path.isdir(self.previewDir):
			os.makedirs(self.previewDir)
		self.conn = base.getDBConnection("trustedquery")
		FileProcessor._createAuxiliaries(self, dd)

	def getPreviewPath(self, accref):
		res = list(self.conn.query("select preview from dc.products where"
			" accref=%(accref)s", {"accref": accref}))
		if not res:
			raise IOError("%s is not in the products table.  Update/import"
				" the resource?"%accref)
		if res[0][0]=="AUTO":
			raise base.ReportableError("Preview path in the product table is AUTO."
				"  Will not write preview there.  Make sure you have properly"
				" bound the preview parameter in //products#define and re-import.")
		return str(self.inputsDir / res[0][0])

	def classify(self, srcName, previewPath):
		if self.opts.force:
			return "without"
		if os.path.exists(previewPath):
			return "with"
		else:
			return "without"
	
	def process(self, accref):
		srcName = str(self.inputsDir / accref)
		previewPath = self.getPreviewPath(accref)
		if self.classify(srcName, previewPath)=="with":
			return

		dirPart = os.path.dirname(previewPath)
		if not os.path.exists(dirPart):
			os.makedirs(dirPart)
			os.chmod(dirPart, 0o775)

		with utils.safeReplaced(previewPath) as f:
			f.write(self.getPreviewData(str(srcName)))
		os.chmod(previewPath, 0o664)


class OneDPreviewMaker(PreviewMaker):
	"""A preview maker for 1D data.

	This is for when you produce your data sets from datalink using
	an embedded grammar using a datalink descriptor as the source token.
	That's what we recommend for time series (and probably for
	spectra too, soon).

	To make this work, derive from it and define the following class
	attributes:

	* abscName -- abscisssa, the name of the x axis column (preconfigured
	  for timeseries#phot-0, override otherwise)
	* ordName -- ordinate, the name of the y axis column
	* builderId -- the ID of the data item building the data collection
	  (must define a previews property)
	* logOrd=False -- logarithmic ordinate
	* connectPoints=True -- or do a scatter plot

	Then define a method getSource(srcName) –> something that
	returns something that the builder's grammar can use.  See
	SpectralPreviewMaker and DLPreviewMaker for examples.

	For context, see :dachsref:`processors.html#precomputing-previews`.
	"""
	logOrd = False
	abscName = "obs_time"
	ordName = "phot"
	connectPoints = True
	builderId = None

	def _createAuxiliaries(self, dd):
		if self.builderId is None:
			raise base.ReportableError("Concrete OneDPreviewMakers"
				" need a non-None builderId.")

		PreviewMaker._createAuxiliaries(self, dd)
		self.builderDD = self.dd.rd.getById(self.builderId)

	@staticmethod
	def get2DPlot(tuples, linear=False, connectPoints=True):
		"""returns a png-compressed pixel image for a 2D plot of (x,y)
		tuples.
		"""
		with matplotlibLock():
			fig = figure.Figure(figsize=(4,2))
			ax = fig.add_axes([0,0,1,1], frameon=False)

			if linear:
				plotter = ax.plot
			else:
				plotter = ax.semilogy

			if connectPoints:
				linestyle = "-"
			else:
				linestyle = "o"

			plotter(
				[r[0] for r in tuples],
				[r[1] for r in tuples],
				linestyle,
				color="black")
			ax.xaxis.set_major_locator(matplotlib.ticker.NullLocator())
			ax.yaxis.set_major_locator(matplotlib.ticker.NullLocator())
			ax.yaxis.set_minor_locator(matplotlib.ticker.NullLocator())

			rendered = io.BytesIO()
			fig.savefig(rendered, format="png", dpi=50)

			rendered = io.BytesIO(rendered.getvalue())
			im = Image.open(rendered)
			im = im.convert("L")
			im = im.convert("P", palette=Image.ADAPTIVE, colors=8)
			compressed = io.BytesIO()
			im.save(compressed, format="png", bits=3)
			return compressed.getvalue()

	def getSource(self, srcName):
		raise NotImplementedError("Concrete preview makers need to"
			" define a getSource method.")

	def getPreviewData(self, srcName):
		table = rsc.makeData(self.builderDD, forceSource=self.getSource(srcName)
			).getPrimaryTable()
		data = [(r[self.abscName], r[self.ordName]) for r in table.rows]
		data.sort()

		return self.get2DPlot(data, not self.logOrd, self.connectPoints)


class SpectralPreviewMaker(OneDPreviewMaker):
	"""a preview maker for DaCHS' sdm spectra generators.

	You typically only need to fill out sdmId; class attribute you might
	want to change are linearFluxes, connectPoints and porbably not
	spectralColumn and fluxColumn.
	"""
	linearFluxes = False
	spectralColumn = "spectral"
	fluxColumn = "flux"
	connectPoints = True
	sdmId = None

	def __init__(self, opts, dd):
		# translate legacy attribute names to the OneDPreviewMaker ones.
		self.abscName = self.spectralColumn
		self.ordName = self.fluxColumn
		self.logOrd = not self.linearFluxes
		self.builderId = self.sdmId
		OneDPreviewMaker.__init__(self, opts, dd)

	def getSource(self, srcName):
		return {"accref": self.getProductKey(srcName)}


class DLPreviewMaker(OneDPreviewMaker):
	"""A preview maker for building from embedded grammars that take
	datalink descriptors as source tokens.

	In DaCHS, we typically use these for time series.

	In addition to what OneDPreviewMaker wants, this needs a dlId, the
	Id of the datalink service producing the data.
	"""
	dlId = None

	def _createAuxiliaries(self, dd):
		if self.dlId is None:
			raise base.ReportableError("Concrete DLPreviewMakers"
				" need a non-None dlId.")
		self.descriptorGenerator = self.dd.rd.getById(self.dlId
			).core.descriptorGenerator.compile()

		OneDPreviewMaker._createAuxiliaries(self, dd)

	def getSource(self, srcName):
		"""returns a descriptor generator for a source name.

		This assumes the accref is just the inputsDir-relative file name.
		If this assumption is wrong, you need to re-implement this.
		"""
		accref = self.getProductKey(srcName)
		return self.descriptorGenerator(accref, {})


def procmain(processorClass, rdId, ddId):
	"""The "standard" main function for processor scripts.

	The function returns the instantiated processor so you can communicate
	from your processor back to your own main.

	See :dachsdoc:`processors.html` for details.
	"""
	import optparse
	from gavo import rscdesc  #noflake: for registration
	rd = base.caches.getRD(rdId)
	dd = rd.getById(ddId)

	parser = optparse.OptionParser()
	processorClass.addOptions(parser)
	opts, args = parser.parse_args()
	if args:
		parser.print_help(file=sys.stderr)
		sys.exit(1)
	if opts.beVerbose:
		from gavo.user import logui
		logui.LoggingUI(base.ui)
		base.DEBUG = True

	proc = processorClass(opts, dd)
	processed, ignored = proc.processAll()
	print("%s files processed, %s files with errors"%(processed, ignored))
	return proc
