analysis/webservice/algorithms_spark/TimeAvgMapSpark.py [38:99]:
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    params = {
        "ds": {
            "name": "Dataset",
            "type": "String",
            "description": "The dataset used to generate the map. Required"
        },
        "startTime": {
            "name": "Start Time",
            "type": "string",
            "description": "Starting time in format YYYY-MM-DDTHH:mm:ssZ or seconds since EPOCH. Required"
        },
        "endTime": {
            "name": "End Time",
            "type": "string",
            "description": "Ending time in format YYYY-MM-DDTHH:mm:ssZ or seconds since EPOCH. Required"
        },
        "b": {
            "name": "Bounding box",
            "type": "comma-delimited float",
            "description": "Minimum (Western) Longitude, Minimum (Southern) Latitude, "
                           "Maximum (Eastern) Longitude, Maximum (Northern) Latitude. Required"
        },
        "spark": {
            "name": "Spark Configuration",
            "type": "comma-delimited value",
            "description": "Configuration used to launch in the Spark cluster. Value should be 3 elements separated by "
                           "commas. 1) Spark Master 2) Number of Spark Executors 3) Number of Spark Partitions. Only "
                           "Number of Spark Partitions is used by this function. Optional (Default: local,1,1)"
        }
    }
    singleton = True

    # @classmethod
    # def instance(cls, algorithm_config=None, sc=None):
    #     with cls.__singleton_lock:
    #         if not cls.__singleton_instance:
    #             try:
    #                 singleton_instance = cls()
    #                 singleton_instance.set_config(algorithm_config)
    #                 singleton_instance.set_spark_context(sc)
    #                 cls.__singleton_instance = singleton_instance
    #             except AttributeError:
    #                 pass
    #     return cls.__singleton_instance

    def parse_arguments(self, request):
        # Parse input arguments
        self.log.debug("Parsing arguments")

        try:
            ds = request.get_dataset()
            if type(ds) == list or type(ds) == tuple:
                ds = next(iter(ds))
        except:
            raise NexusProcessingException(
                reason="'ds' argument is required. Must be a string",
                code=400)

        # Do not allow time series on Climatology
        if next(iter([clim for clim in ds if 'CLIM' in clim]), False):
            raise NexusProcessingException(
                reason="Cannot compute Latitude/Longitude Time Average plot on a climatology", code=400)
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analysis/webservice/algorithms_spark/VarianceSpark.py [37:86]:
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    params = {
        "ds": {
            "name": "Dataset",
            "type": "String",
            "description": "The dataset used to generate the map. Required"
        },
        "startTime": {
            "name": "Start Time",
            "type": "string",
            "description": "Starting time in format YYYY-MM-DDTHH:mm:ssZ or seconds since EPOCH. Required"
        },
        "endTime": {
            "name": "End Time",
            "type": "string",
            "description": "Ending time in format YYYY-MM-DDTHH:mm:ssZ or seconds since EPOCH. Required"
        },
        "b": {
            "name": "Bounding box",
            "type": "comma-delimited float",
            "description": "Minimum (Western) Longitude, Minimum (Southern) Latitude, "
                           "Maximum (Eastern) Longitude, Maximum (Northern) Latitude. Required"
        },
        "spark": {
            "name": "Spark Configuration",
            "type": "comma-delimited value",
            "description": "Configuration used to launch in the Spark cluster. Value should be 3 elements separated by "
                           "commas. 1) Spark Master 2) Number of Spark Executors 3) Number of Spark Partitions. Only "
                           "Number of Spark Partitions is used by this function. Optional (Default: local,1,1)"
        }
    }
    singleton = True


    def parse_arguments(self, request):
        # Parse input arguments
        self.log.debug("Parsing arguments")

        try:
            ds = request.get_dataset()
            if type(ds) == list or type(ds) == tuple:
                ds = next(iter(ds))
        except:
            raise NexusProcessingException(
                reason="'ds' argument is required. Must be a string",
                code=400)

        # Do not allow time series on Climatology
        if next(iter([clim for clim in ds if 'CLIM' in clim]), False):
            raise NexusProcessingException(
                reason="Cannot compute Latitude/Longitude Time Average plot on a climatology", code=400)
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