Function fuzzy_merge has 6 arguments (exceeds 4 allowed). Consider refactoring.

Open

    def fuzzy_merge(self, df_1, df_2, key1, key2, threshold=90, limit=1):

Function risk_evolution has 6 arguments (exceeds 4 allowed). Consider refactoring.

Open

    def risk_evolution(self, impact_cc, impact_urb, impact_pop, impact_gdp, prot, prot_idx):

Function find_impact has 6 arguments (exceeds 4 allowed). Consider refactoring.

Open

    def find_impact(self, impact_cc, impact_soc, impact_sub, impact_cc_soc, impact_urb, model):

Function select_projection_data has 5 arguments (exceeds 4 allowed). Consider refactoring.

Open

    def select_projection_data(self, dataframe, climate, model, socioecon, year):

Function compute_rp_change has 5 arguments (exceeds 4 allowed). Consider refactoring.

Open

    def compute_rp_change(self, ref_impact, target_impact, rp, min_rp=2, max_rp=1000):

Function user_selections has a Cognitive Complexity of 7 (exceeds 5 allowed). Consider refactoring.

Open

    def user_selections(self):
        """
        Purpose: Gather all neccesary inputs to run any analysis

        Output:

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Avoid too many return statements within this function.

Open

        return error(status=500, detail=str(e))

Avoid too many return statements within this function.

Open

            return error(

Avoid too many return statements within this function.

Open

        return jsonify(payload), 500, {}

Avoid too many return statements within this function.

Open

        return error(status=500, detail=str(e))

Avoid too many return statements within this function.

Open

        return error(status=500, detail="Generic Error")

Avoid too many return statements within this function.

Open

            return jsonify(analyzer.results()), 200, {}

Avoid too many return statements within this function.

Open

        return error(status=500, detail=str(e))

Function clean_buffer has a Cognitive Complexity of 6 (exceeds 5 allowed). Consider refactoring.

Open

    def clean_buffer(self, row):
        """
        :param row: individual row (1 coordinate + material type)
        :return: buffer radius in decimal degrees
        """

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Function user_selections has a Cognitive Complexity of 6 (exceeds 5 allowed). Consider refactoring.

Open

    def user_selections(self):
        """
        Purpose: Gather all necessary inputs to run any analysis
        Input:
            flood: Riverine of Coastal (User must select)

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Function worker_int has a Cognitive Complexity of 6 (exceeds 5 allowed). Consider refactoring.

Open

def worker_int(worker):
    worker.log.info("worker received INT or QUIT signal")

    ## get traceback info
    import threading, sys, traceback

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Function execute has a Cognitive Complexity of 6 (exceeds 5 allowed). Consider refactoring.

Open

    def execute(self):
        try:
            inspector = sqlalchemy.inspect(self.engine)
            logging.info('[CBADCache]: Getting cba default...')
            if 'cache_d_cba' in inspector.get_table_names():

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Function execute has a Cognitive Complexity of 6 (exceeds 5 allowed). Consider refactoring.

Open

    def execute(uri, api_key):
        try:
            response = request_to_microservice(uri=uri, api_key=api_key, method="GET")
            if not response or response.get("errors"):
                raise GeostoreNotFound

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Function execute has a Cognitive Complexity of 6 (exceeds 5 allowed). Consider refactoring.

Open

    def execute(self):
        try:
            inspector = sqlalchemy.inspect(self.engine)
            logging.info('[CBAICache]: Getting cba default...')
            if 'cache_cba' in inspector.get_table_names():

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Function bench has a Cognitive Complexity of 6 (exceeds 5 allowed). Consider refactoring.

Open

    def bench(self):
        defaultfn = "precalc_agg_{0}_{1}_{2}".format(self.flood, self.geogunit_type, self.sub_abb)
        print(defaultfn)

        # cols = ['{0} as {1}'.format(col, col.replace(self.exposure, 'bench').replace('urban_damage_v2', 'bench').replace("_"+ self.scen_abb, '')) for col in sqlalchemy.Table(defaultfn, self.metadata).columns.keys() if ((self.exposure in col) or ('urban_damage_v2' in col)) and (self.scen_abb in col) and ("cc" not in col) and ("soc" not in col) and ("sub" not in col) and ("avg" in col)]

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