Example #1
0
    def __init__(self, configuration, model=None, dataStream=None, rethrowExceptions=None):
        self.model = model
        self.dataStream = dataStream
        self.rethrowExceptions = rethrowExceptions
        self.fileNameOnException = None

        # get the configuration, in whatever form you find it
        if isinstance(configuration, config.AugustusConfiguration):
            pass
        elif isinstance(configuration, basestring):
            try:
                configuration = xmlbase.loadfile(configuration, config.Config, lineNumbers=True)
            except IOError:
                configuration = xmlbase.load(configuration, config.Config, lineNumbers=True)
        else:
            raise ConfigurationError("Configuration must be a pre-validated XML object, a fileName, or a literal configuration string.")
    
        # set up logging
        setupLogging(configuration.matches(lambda x: isinstance(x, (config.Logging, config.Metadata))))
        self.logger = logging.getLogger()
        self.metadata = logging.getLogger("metadata")

        # begin "initialization" phase
        for l in self.logger, self.metadata:
            if "initialization" in l.differentLevel:
                l.setLevel(l.differentLevel["initialization"])
            else:
                l.setLevel(l.naturalLevel)

        # get the model, in whatever form you find it
        self.logger.info("Loading PMML model.")
        self.metadata.startTiming("Time to load PMML model")
        modelFileName = "(none)"
        maturityThreshold = 0
        if self.model is None:
            modelInput = configuration.child(config.ModelInput, exception=None)
            if modelInput is None:
                raise ConfigurationError("If a model is not provided to MainLoop explicitly, it must be present in the configuration file.")

            fileLocation = modelInput["fileLocation"]
            if not fileLocation.startswith("http://") and not fileLocation.startswith("https://"):
                fileList = glob.glob(fileLocation)
                if len(fileList) > 1:
                    fileList = [f for f in fileList if self._modelExceptionIdentifier not in f]
                if len(fileList) == 0:
                    raise IOError("No files matched the ModelInput fileLocation \"%s\"." % fileLocation)

                selectmode = modelInput.attrib.get("selectmode", "lastAlphabetic")
                if selectmode == "mostRecent":
                    fileLocation = max(fileList, key=lambda x: os.stat(x).st_mtime)
                elif selectmode == "lastAlphabetic":
                    fileList.sort()
                    fileLocation = fileList[-1]
                else:
                    assert False

                if self._modelExceptionIdentifier in fileLocation:
                    self.logger.warning("Using a PMML model that was written on exception (fileName \"%s\")" % fileLocation)

            self.model = xmlbase.loadfile(fileLocation, pmml.X_ODG_PMML, lineNumbers=True)

            if "maturityThreshold" in modelInput.attrib: maturityThreshold = modelInput["maturityThreshold"]

        elif isinstance(self.model, pmml.PMML):
            pass
        elif isinstance(self.model, basestring):
            try:
                self.model, modelFileName = xmlbase.loadfile(self.model, pmml.X_ODG_PMML, lineNumbers=True), self.model
            except IOError:
                self.model = xmlbase.load(self.model, pmml.X_ODG_PMML, lineNumbers=True)
        else:
            raise ConfigurationError("Model must be a pre-validated XML object, a fileName, or a literal PMML string.")
        self.metadata.stopTiming("Time to load PMML model")
        self.metadata.data["PMML model file"] = modelFileName

        # globally set random number seeds
        if "randomSeed" in configuration.attrib:
            augustusRandomSeed = configuration["randomSeed"]
            random.seed(augustusRandomSeed)
            numpy.random.seed(augustusRandomSeed + 1)
        else:
            augustusRandomSeed = "unspecified"

        # globally set numpy error handling
        numpy.seterr(divide="raise", over="raise", under="ignore", invalid="raise")

        # update schemes (producerUpdateScheme may be redefined below)
        consumerUpdateScheme = self._getUpdateScheme(configuration.child(config.ConsumerBlending, exception=False))
        producerUpdateScheme = self._getUpdateScheme(None)

        # set up scoring output
        outputConfig = configuration.child(config.Output, exception=False)
        if outputConfig is None:
            self.outputWriter = None
        else:
            outputParams = {"pmmlFileName": modelFileName, "mode": outputConfig.destination.attrib.get("type", "XML").lower()}

            if isinstance(outputConfig.destination, config.ToFile):
                if outputConfig.destination.attrib.get("overwrite", False):
                    outputStream = codecs.open(outputConfig.destination["name"], "w", encoding="utf-8")
                else:
                    outputStream = codecs.open(outputConfig.destination["name"], "a", encoding="utf-8")
            elif isinstance(outputConfig.destination, config.ToStandardError):
                outputStream = sys.stderr
            elif isinstance(outputConfig.destination, config.ToStandardOut):
                outputStream = sys.stdout
            else:
                assert False

            reportTag = outputConfig.child("ReportTag", exception=False)
            if reportTag:
                outputParams["reportName"] = reportTag.attrib.get("name", "Report")

            eventTag = outputConfig.child("EventTag", exception=False)
            if eventTag:
                outputParams["eventName"] = eventTag.attrib.get("name", "Event")
                outputParams["pseudoEventName"] = eventTag.attrib.get("pseudoName", "pseudoEvent")

            self.outputWriter = OutputWriter(outputStream, **outputParams)

        # initialize for the case of no output model
        engineSettings = {"maturityThreshold": maturityThreshold, "augustusRandomSeed": augustusRandomSeed}
        self.modelWriter = None
        segmentationScheme = SegmentationScheme(None, self.model)
        self.updateFlag = False
        self.aggregateUpdateFlag = False

        producerAlgorithm = dict(config.producerAlgorithmDefaults)
        for pa in producerAlgorithm.values():
            validationResult = pa.validate()
            assert validationResult is None

        # set up output model, if present in the configuration
        modelSetup = configuration.child(config.ModelSetup, exception=False)
        engineSettings["hasProducer"] = modelSetup is not None
        if engineSettings["hasProducer"]:
            self.logger.info("Setting up model updating/producing.")

            producerBlending = modelSetup.child(config.ProducerBlending, exception=False)
            producerUpdateScheme = self._getUpdateScheme(producerBlending)
            if producerBlending is not None and producerBlending.contains(config.MaturityThreshold):
                maturityConfig = producerBlending.child(config.MaturityThreshold)
                engineSettings["maturityThreshold"] = int(maturityConfig.attrib.get("threshold", 1))
                try:
                    engineSettings["lockingThreshold"] = int(maturityConfig.attrib["lockingThreshold"])
                except KeyError:
                    engineSettings["lockingThreshold"] = None

            engineSettings["lockAllSegments"] = modelSetup.attrib.get("mode", None) == "lockExisting"
            if engineSettings["lockAllSegments"] and segmentationScheme is not None and not segmentationScheme._generic and not segmentationScheme._whiteList:
                self.logger.warning("The model is locked and no new segments are specified...new model files will be unchanged.")

            self.modelWriter = getModelWriter(modelSetup)
            if self.modelWriter is not None:
                if self.modelWriter.baseName is None:
                    self.fileNameOnException = self._modelExceptionIdentifier + ".pmml"
                else:
                    self.fileNameOnException = "".join([self.modelWriter.baseName, self._modelExceptionIdentifier, ".pmml"])
            else:
                self.logger.warning("There is no outputFile attribute in the ModelSetup; no new model file will be created.")

            segmentationScheme = SegmentationScheme(modelSetup.child(config.SegmentationSchema, exception=False), self.model)
            self.updateFlag = modelSetup.attrib.get("updateEvery", "event") in ("event", "both")
            self.aggregateUpdateFlag = modelSetup.attrib.get("updateEvery", "event") in ("aggregate", "both")

            for pa in modelSetup.matches(config.ProducerAlgorithm):
                producerAlgorithm[pa["model"]] = pa
            if modelSetup.attrib.get("mode", None) == "updateExisting":
                for pa in producerAlgorithm.values():
                    pa.parameters["updateExisting"] = True
            if modelSetup.attrib.get("mode", None) == "replaceExisting":
                for pa in producerAlgorithm.values():
                    pa.parameters["updateExisting"] = False

        # to score or not to score
        eventSettings = configuration.child(config.EventSettings, exception=False)
        if eventSettings is not None:
            self.logger.info("Setting up output.")
            self.scoreFlag = eventSettings["score"]
            self.outputFlag = eventSettings["output"]
        else:
            self.scoreFlag = False
            self.outputFlag = False

        aggregationConfig = configuration.child(config.AggregationSettings, exception=False)
        if aggregationConfig is not None:
            self.aggregateScoreFlag = aggregationConfig["score"]
            self.aggregateOutputFlag = aggregationConfig["output"]
            self.aggregationSettings = dict(aggregationConfig.attrib)
        else:
            self.aggregateScoreFlag = False
            self.aggregateOutputFlag = False
            self.aggregationSettings = None

        self.metadata.data["Update model"] = "true" if self.updateFlag or self.aggregateUpdateFlag else "false"

        # build a scoring engine once without a dataStream (to evaluate any verification blocks)
        self.engine = Engine(self.model, None, producerUpdateScheme, consumerUpdateScheme, segmentationScheme, producerAlgorithm, **engineSettings)
        self.engine.initialize()
        if self.outputWriter is not None: self.outputWriter.open()

        # begin "verification" phase
        for l in self.logger, self.metadata:
            if "verification" in l.differentLevel:
                l.eventLogLevel = l.differentLevel["verification"]
                l.setLevel(l.differentLevel["verification"])
            else:
                l.eventLogLevel = l.naturalLevel
                l.setLevel(l.naturalLevel)

        # evaluate verification blocks
        modelVerificationConfig = configuration.child(config.ModelVerification, exception=False)
        if modelVerificationConfig is not None:
            verify(modelVerificationConfig, self.engine, self.logger, self.outputWriter)

        # verification can increment aggregate variables, but
        # aggregates should all start at zero at the start of real
        # processing, whether verification happened or not
        self.engine.flushAggregates()

        # get the dataStream, in whatever form you find it
        self.logger.info("Setting up data input.")
        if self.dataStream is None:
            configDataInput = configuration.child(config.DataInput, exception=None)
            if configDataInput is None:
                raise ConfigurationError("If a dataStream is not provided to MainLoop explicitly, it must be present in the configuration file.")
            if configDataInput.contains(config.FromFile):
                self.dataStream = DataStreamer(configDataInput.child(config.FromFile), self.engine.pmmlModel)
            elif configDataInput.contains(config.FromStandardIn):
                self.dataStream = DataStreamer(configDataInput.child(config.FromStandardIn), self.engine.pmmlModel)
            elif configDataInput.contains(config.FromHTTP):
                self.dataStream = AugustusHTTPDataStream(configDataInput.child(config.FromHTTP))
                if self.outputWriter is None:
                    self.dataStream.respond = False
                if self.dataStream.respond:
                    self.dataStream.setupOutput(self.outputWriter)
            else:
                assert False

        # begin "eventLoop" phase
        for l in self.logger, self.metadata:
            if "eventloop" in l.differentLevel:
                l.eventLogLevel = l.differentLevel["eventloop"]
                l.setLevel(l.differentLevel["eventloop"])
            else:
                l.eventLogLevel = l.naturalLevel
                l.setLevel(l.naturalLevel)

        # possibly set up custom processing
        self.customProcessing = configuration.child(config.CustomProcessing, exception=False)
        if self.customProcessing is not None:
            constants = self.engine.pmmlModel.child(pmml.Extension, exception=False)
            if constants is None:
                constants = NameSpaceReadOnly()
            else:
                constants = constants.child(pmml.X_ODG_CustomProcessingConstants, exception=False)
                if constants is None:
                    constants = NameSpaceReadOnly()
                else:
                    constants = constants.nameSpace

            atoms = {"INVALID": INVALID, "MISSING": MISSING, "IMMATURE": IMMATURE, "MATURE": MATURE, "LOCKED": LOCKED, "UNINITIALIZED": UNINITIALIZED}
            for thing in pmml.OutputField.__dict__.values() + pmml.X_ODG_OutputField.__dict__.values():
                if isinstance(thing, Atom):
                    atoms[repr(thing)] = thing

            self.customProcessing.initialize(self.model, self.engine.pmmlModel, constants, [s.userFriendly for s in self.engine.segmentRecords], atoms, self.logger, self.metadata, consumerUpdateScheme, producerUpdateScheme)
            self.engine.customProcessing = self.customProcessing
            self.engine.reinitialize()

        else:
            # only turn off circular garbage collection if there is no CustomProcessing or AugustusInterface
            gc.disable()
Example #2
0
class MainLoop(object):
    """Read the configuration file, set up an Augustus job, and run it.

    Arguments:

        configuration (string or XML object):
            Literal configuration string, path to a configuration
            file, or configuration XML tree structure (must be
            validated).  Must be provided.

        model (optional string or XML object):
            Literal PMML string, path to a PMML file, or a validated
            XML tree structure.  If provided, this overrides what is
            in the configuration.

        dataStream (optional class with 'initialize', 'next', and 'get'):
            Explicit data stream, overriding that which is in the
            configuration file.

        rethrowExceptions (optional bool, default is False):
            If an exception is caught by MainLoop, re-throw it to the
            containing loop.  Use this if you're running Augustus in
            a larger program and want to handle exceptions on your
            own.

    Notes:

        If the configuration contains a "randomSeed" directive,
        MainLoop's __init__ will globally change the random seed of
        Python's random library and numpy.random.

        MainLoop's __init__ will globally change the numpy error
        handling.

        Unless the configuration has a <CustomProcessing> block (which
        is always the case within an AugustusInterface), MainLoop's
        __init__ will globally disable circular garbage collection.

    """

    _modelExceptionIdentifier = "EXCEPTION"

    def __init__(self, configuration, model=None, dataStream=None, rethrowExceptions=None):
        self.model = model
        self.dataStream = dataStream
        self.rethrowExceptions = rethrowExceptions
        self.fileNameOnException = None

        # get the configuration, in whatever form you find it
        if isinstance(configuration, config.AugustusConfiguration):
            pass
        elif isinstance(configuration, basestring):
            try:
                configuration = xmlbase.loadfile(configuration, config.Config, lineNumbers=True)
            except IOError:
                configuration = xmlbase.load(configuration, config.Config, lineNumbers=True)
        else:
            raise ConfigurationError("Configuration must be a pre-validated XML object, a fileName, or a literal configuration string.")
    
        # set up logging
        setupLogging(configuration.matches(lambda x: isinstance(x, (config.Logging, config.Metadata))))
        self.logger = logging.getLogger()
        self.metadata = logging.getLogger("metadata")

        # begin "initialization" phase
        for l in self.logger, self.metadata:
            if "initialization" in l.differentLevel:
                l.setLevel(l.differentLevel["initialization"])
            else:
                l.setLevel(l.naturalLevel)

        # get the model, in whatever form you find it
        self.logger.info("Loading PMML model.")
        self.metadata.startTiming("Time to load PMML model")
        modelFileName = "(none)"
        maturityThreshold = 0
        if self.model is None:
            modelInput = configuration.child(config.ModelInput, exception=None)
            if modelInput is None:
                raise ConfigurationError("If a model is not provided to MainLoop explicitly, it must be present in the configuration file.")

            fileLocation = modelInput["fileLocation"]
            if not fileLocation.startswith("http://") and not fileLocation.startswith("https://"):
                fileList = glob.glob(fileLocation)
                if len(fileList) > 1:
                    fileList = [f for f in fileList if self._modelExceptionIdentifier not in f]
                if len(fileList) == 0:
                    raise IOError("No files matched the ModelInput fileLocation \"%s\"." % fileLocation)

                selectmode = modelInput.attrib.get("selectmode", "lastAlphabetic")
                if selectmode == "mostRecent":
                    fileLocation = max(fileList, key=lambda x: os.stat(x).st_mtime)
                elif selectmode == "lastAlphabetic":
                    fileList.sort()
                    fileLocation = fileList[-1]
                else:
                    assert False

                if self._modelExceptionIdentifier in fileLocation:
                    self.logger.warning("Using a PMML model that was written on exception (fileName \"%s\")" % fileLocation)

            self.model = xmlbase.loadfile(fileLocation, pmml.X_ODG_PMML, lineNumbers=True)

            if "maturityThreshold" in modelInput.attrib: maturityThreshold = modelInput["maturityThreshold"]

        elif isinstance(self.model, pmml.PMML):
            pass
        elif isinstance(self.model, basestring):
            try:
                self.model, modelFileName = xmlbase.loadfile(self.model, pmml.X_ODG_PMML, lineNumbers=True), self.model
            except IOError:
                self.model = xmlbase.load(self.model, pmml.X_ODG_PMML, lineNumbers=True)
        else:
            raise ConfigurationError("Model must be a pre-validated XML object, a fileName, or a literal PMML string.")
        self.metadata.stopTiming("Time to load PMML model")
        self.metadata.data["PMML model file"] = modelFileName

        # globally set random number seeds
        if "randomSeed" in configuration.attrib:
            augustusRandomSeed = configuration["randomSeed"]
            random.seed(augustusRandomSeed)
            numpy.random.seed(augustusRandomSeed + 1)
        else:
            augustusRandomSeed = "unspecified"

        # globally set numpy error handling
        numpy.seterr(divide="raise", over="raise", under="ignore", invalid="raise")

        # update schemes (producerUpdateScheme may be redefined below)
        consumerUpdateScheme = self._getUpdateScheme(configuration.child(config.ConsumerBlending, exception=False))
        producerUpdateScheme = self._getUpdateScheme(None)

        # set up scoring output
        outputConfig = configuration.child(config.Output, exception=False)
        if outputConfig is None:
            self.outputWriter = None
        else:
            outputParams = {"pmmlFileName": modelFileName, "mode": outputConfig.destination.attrib.get("type", "XML").lower()}

            if isinstance(outputConfig.destination, config.ToFile):
                if outputConfig.destination.attrib.get("overwrite", False):
                    outputStream = codecs.open(outputConfig.destination["name"], "w", encoding="utf-8")
                else:
                    outputStream = codecs.open(outputConfig.destination["name"], "a", encoding="utf-8")
            elif isinstance(outputConfig.destination, config.ToStandardError):
                outputStream = sys.stderr
            elif isinstance(outputConfig.destination, config.ToStandardOut):
                outputStream = sys.stdout
            else:
                assert False

            reportTag = outputConfig.child("ReportTag", exception=False)
            if reportTag:
                outputParams["reportName"] = reportTag.attrib.get("name", "Report")

            eventTag = outputConfig.child("EventTag", exception=False)
            if eventTag:
                outputParams["eventName"] = eventTag.attrib.get("name", "Event")
                outputParams["pseudoEventName"] = eventTag.attrib.get("pseudoName", "pseudoEvent")

            self.outputWriter = OutputWriter(outputStream, **outputParams)

        # initialize for the case of no output model
        engineSettings = {"maturityThreshold": maturityThreshold, "augustusRandomSeed": augustusRandomSeed}
        self.modelWriter = None
        segmentationScheme = SegmentationScheme(None, self.model)
        self.updateFlag = False
        self.aggregateUpdateFlag = False

        producerAlgorithm = dict(config.producerAlgorithmDefaults)
        for pa in producerAlgorithm.values():
            validationResult = pa.validate()
            assert validationResult is None

        # set up output model, if present in the configuration
        modelSetup = configuration.child(config.ModelSetup, exception=False)
        engineSettings["hasProducer"] = modelSetup is not None
        if engineSettings["hasProducer"]:
            self.logger.info("Setting up model updating/producing.")

            producerBlending = modelSetup.child(config.ProducerBlending, exception=False)
            producerUpdateScheme = self._getUpdateScheme(producerBlending)
            if producerBlending is not None and producerBlending.contains(config.MaturityThreshold):
                maturityConfig = producerBlending.child(config.MaturityThreshold)
                engineSettings["maturityThreshold"] = int(maturityConfig.attrib.get("threshold", 1))
                try:
                    engineSettings["lockingThreshold"] = int(maturityConfig.attrib["lockingThreshold"])
                except KeyError:
                    engineSettings["lockingThreshold"] = None

            engineSettings["lockAllSegments"] = modelSetup.attrib.get("mode", None) == "lockExisting"
            if engineSettings["lockAllSegments"] and segmentationScheme is not None and not segmentationScheme._generic and not segmentationScheme._whiteList:
                self.logger.warning("The model is locked and no new segments are specified...new model files will be unchanged.")

            self.modelWriter = getModelWriter(modelSetup)
            if self.modelWriter is not None:
                if self.modelWriter.baseName is None:
                    self.fileNameOnException = self._modelExceptionIdentifier + ".pmml"
                else:
                    self.fileNameOnException = "".join([self.modelWriter.baseName, self._modelExceptionIdentifier, ".pmml"])
            else:
                self.logger.warning("There is no outputFile attribute in the ModelSetup; no new model file will be created.")

            segmentationScheme = SegmentationScheme(modelSetup.child(config.SegmentationSchema, exception=False), self.model)
            self.updateFlag = modelSetup.attrib.get("updateEvery", "event") in ("event", "both")
            self.aggregateUpdateFlag = modelSetup.attrib.get("updateEvery", "event") in ("aggregate", "both")

            for pa in modelSetup.matches(config.ProducerAlgorithm):
                producerAlgorithm[pa["model"]] = pa
            if modelSetup.attrib.get("mode", None) == "updateExisting":
                for pa in producerAlgorithm.values():
                    pa.parameters["updateExisting"] = True
            if modelSetup.attrib.get("mode", None) == "replaceExisting":
                for pa in producerAlgorithm.values():
                    pa.parameters["updateExisting"] = False

        # to score or not to score
        eventSettings = configuration.child(config.EventSettings, exception=False)
        if eventSettings is not None:
            self.logger.info("Setting up output.")
            self.scoreFlag = eventSettings["score"]
            self.outputFlag = eventSettings["output"]
        else:
            self.scoreFlag = False
            self.outputFlag = False

        aggregationConfig = configuration.child(config.AggregationSettings, exception=False)
        if aggregationConfig is not None:
            self.aggregateScoreFlag = aggregationConfig["score"]
            self.aggregateOutputFlag = aggregationConfig["output"]
            self.aggregationSettings = dict(aggregationConfig.attrib)
        else:
            self.aggregateScoreFlag = False
            self.aggregateOutputFlag = False
            self.aggregationSettings = None

        self.metadata.data["Update model"] = "true" if self.updateFlag or self.aggregateUpdateFlag else "false"

        # build a scoring engine once without a dataStream (to evaluate any verification blocks)
        self.engine = Engine(self.model, None, producerUpdateScheme, consumerUpdateScheme, segmentationScheme, producerAlgorithm, **engineSettings)
        self.engine.initialize()
        if self.outputWriter is not None: self.outputWriter.open()

        # begin "verification" phase
        for l in self.logger, self.metadata:
            if "verification" in l.differentLevel:
                l.eventLogLevel = l.differentLevel["verification"]
                l.setLevel(l.differentLevel["verification"])
            else:
                l.eventLogLevel = l.naturalLevel
                l.setLevel(l.naturalLevel)

        # evaluate verification blocks
        modelVerificationConfig = configuration.child(config.ModelVerification, exception=False)
        if modelVerificationConfig is not None:
            verify(modelVerificationConfig, self.engine, self.logger, self.outputWriter)

        # verification can increment aggregate variables, but
        # aggregates should all start at zero at the start of real
        # processing, whether verification happened or not
        self.engine.flushAggregates()

        # get the dataStream, in whatever form you find it
        self.logger.info("Setting up data input.")
        if self.dataStream is None:
            configDataInput = configuration.child(config.DataInput, exception=None)
            if configDataInput is None:
                raise ConfigurationError("If a dataStream is not provided to MainLoop explicitly, it must be present in the configuration file.")
            if configDataInput.contains(config.FromFile):
                self.dataStream = DataStreamer(configDataInput.child(config.FromFile), self.engine.pmmlModel)
            elif configDataInput.contains(config.FromStandardIn):
                self.dataStream = DataStreamer(configDataInput.child(config.FromStandardIn), self.engine.pmmlModel)
            elif configDataInput.contains(config.FromHTTP):
                self.dataStream = AugustusHTTPDataStream(configDataInput.child(config.FromHTTP))
                if self.outputWriter is None:
                    self.dataStream.respond = False
                if self.dataStream.respond:
                    self.dataStream.setupOutput(self.outputWriter)
            else:
                assert False

        # begin "eventLoop" phase
        for l in self.logger, self.metadata:
            if "eventloop" in l.differentLevel:
                l.eventLogLevel = l.differentLevel["eventloop"]
                l.setLevel(l.differentLevel["eventloop"])
            else:
                l.eventLogLevel = l.naturalLevel
                l.setLevel(l.naturalLevel)

        # possibly set up custom processing
        self.customProcessing = configuration.child(config.CustomProcessing, exception=False)
        if self.customProcessing is not None:
            constants = self.engine.pmmlModel.child(pmml.Extension, exception=False)
            if constants is None:
                constants = NameSpaceReadOnly()
            else:
                constants = constants.child(pmml.X_ODG_CustomProcessingConstants, exception=False)
                if constants is None:
                    constants = NameSpaceReadOnly()
                else:
                    constants = constants.nameSpace

            atoms = {"INVALID": INVALID, "MISSING": MISSING, "IMMATURE": IMMATURE, "MATURE": MATURE, "LOCKED": LOCKED, "UNINITIALIZED": UNINITIALIZED}
            for thing in pmml.OutputField.__dict__.values() + pmml.X_ODG_OutputField.__dict__.values():
                if isinstance(thing, Atom):
                    atoms[repr(thing)] = thing

            self.customProcessing.initialize(self.model, self.engine.pmmlModel, constants, [s.userFriendly for s in self.engine.segmentRecords], atoms, self.logger, self.metadata, consumerUpdateScheme, producerUpdateScheme)
            self.engine.customProcessing = self.customProcessing
            self.engine.reinitialize()

        else:
            # only turn off circular garbage collection if there is no CustomProcessing or AugustusInterface
            gc.disable()

    def _getUpdateScheme(self, configuration):
        """Return an UpdateScheme as specified by the user configuration.

        Arguments:

            configuration (XML object, defined in xmlbase):
                An XML element of type "Blending"; either
                <ConsumerBlending/> or <ProducerBlending/>; containing the
                weightings and default settings for the model update schemes.
        """

        if configuration is None: return UpdateScheme("unweighted")

        params = dict(configuration.attrib)
        scheme = "unweighted"

        if "method" in params:
            scheme = params["method"]
            if scheme == "eventTimeWindow": scheme = "synchronized"
            del params["method"]

        if scheme in ("window", "synchronized") and "windowLag" not in params:
            params["windowLag"] = 0

        return UpdateScheme(scheme, **params)

    def doBegin(self):
        """Executes code before the event stream; necessary for setting up metadata."""

        # start of real data
        self.logger.info("Setting up Augustus's main engine.")
        self.engine.resetDataStream(self.dataStream)
        self.dataStream.initialize()

        if self.customProcessing is not None:
            out = self.customProcessing.doBegin()
            if out is not None and self.outputWriter and self.outputFlag:
                self.outputWriter.write(out)

        self.metadata.data["Events"] = 0
        self.logger.info("Calculating.")
        self.metadata.startTiming("Run time")

    def doEvent(self):
        """Executes one event, returning False if there was an error that should stop the loop."""

        score = self.engine.event(score=self.scoreFlag, update=self.updateFlag)

        self.metadata.data["Events"] += 1
        if self.outputWriter and self.outputFlag:
            try:
                self.outputWriter.write(score)
            except IOError:
                if self.modelWriter:
                    self.logger.info("About to write the model to PMML.")
                    self.modelWriter.write(self.model)
                    self.logger.info("Done writing PMML.")
                return False

        if self.modelWriter is not None and self.modelWriter.serialization is not None:
            self.logger.debug("Writing a copy of the current model to PMML (model serialization).")
            self.modelWriter.serialize(self.model, self.metadata.data["Events"])
            self.logger.debug("Done writing PMML.")

        if self.aggregationSettings is not None:
            if self.engine.checkPseudoeventReadiness(self.aggregationSettings):
                score = self.engine.pseudoevent(score=self.aggregateScoreFlag, update=self.aggregateUpdateFlag)
                if self.outputWriter and self.aggregateOutputFlag:
                    self.outputWriter.write(score)

        return True

    def doEnd(self):
        """Executes code after successful event processing.  For file-based producers, this is when the producer algorithm starts."""

        numEvents = self.engine.eventNumber
        self.logger.info("Processed %d events before encountering StopIteration." % numEvents)

        # begin "produce" phase
        for l in self.logger, self.metadata:
            if "produce" in l.differentLevel:
                l.setLevel(l.differentLevel["produce"])
            else:
                l.setLevel(l.naturalLevel)

        self.engine.produce()

        # begin "shutdown" phase
        for l in self.logger, self.metadata:
            if "shutdown" in l.differentLevel:
                l.setLevel(l.differentLevel["shutdown"])
            else:
                l.setLevel(l.naturalLevel)

        if self.customProcessing is not None:
            out = self.customProcessing.doEnd()
            if out is not None and self.outputWriter and self.outputFlag:
                self.outputWriter.write(out)

        if self.modelWriter is not None:
            if self.modelWriter.serialization:
                self.modelWriter.serialize(self.model, self.metadata.data["Events"])
            else:
                self.logger.info("About to write the model to PMML.")
                self.modelWriter.write(self.model)
                self.logger.info("Done writing.")

    def doShutdown(self):
        """Executes code after doEnd or an exception, if Augustus is handling exceptions (rethrowExceptions is False)."""

        self.metadata.stopTiming("Run time")

        if self.outputWriter: self.outputWriter.close()
        if self.modelWriter and self.modelWriter.thread: 
            while self.modelWriter.thread.isAlive(): time.sleep(0)
        self.metadata.flush()
        self.logger.info("Augustus is finished.")
        logging.shutdown()

    def run(self):
        """Executes all events (the doBegin, doEvent ... doEvent, doEnd, doShutdown lifecycle)."""

        self.doBegin()

        try:
            stillGoing = True
            while stillGoing:
                try:
                    stillGoing = self.doEvent()

                except StopIteration:
                    self.doEnd()
                    stillGoing = False

            # outside "while stillGoing" but inside try ... except (Exception, KeyboardInterrupt)"
            if self.aggregationSettings is not None and self.aggregationSettings["atEnd"]:
                score = self.engine.pseudoevent(score=self.aggregateScoreFlag, update=self.aggregateUpdateFlag)
                if self.outputWriter and self.aggregateOutputFlag:
                    self.outputWriter.write(score)

        except (Exception, KeyboardInterrupt), err:
            if self.rethrowExceptions: raise

            for l in self.logger, self.metadata:
                if "shutdown" in l.differentLevel:
                    l.setLevel(l.differentLevel["shutdown"])
                else:
                    l.setLevel(l.naturalLevel)

            if self.customProcessing is not None:
                self.customProcessing.doException()

            self.logger.error("Shutting down on exception after %d successful events..." % self.engine.eventNumber)
            excinfo = sys.exc_info()
            self.logger.error("...%s" % excinfo[0])
            self.logger.error("...%s" % excinfo[1])
            self.logger.error("...%s" % traceback.format_exc())
            if self.fileNameOnException is not None:
                self.logger.error("Writing last model in location %s" % self.fileNameOnException)
                self.model.write(self.fileNameOnException)

            sys.exit("Shutting down on exception; for more information check the logfile (if logging is enabled)...\n%s" % traceback.format_exc())

        self.doShutdown()