def addRiReport()

in src/lambda.py [0:0]
118 lines of code
18 McCabe index (conditional complexity)

    def addRiReport(self, Name='RICoverage', Savings=False, PaymentOption='PARTIAL_UPFRONT', Service='Amazon Elastic Compute Cloud - Compute'): #Call with Savings True to get Utilization report in dollar savings
        type = 'chart' #other option table
        if Name == "RICoverage":
            results = []
            response = self.client.get_reservation_coverage(
                TimePeriod={
                    'Start': self.ristart.isoformat(),
                    'End': self.riend.isoformat()
                },
                Granularity='MONTHLY'
            )
            results.extend(response['CoveragesByTime'])
            while 'nextToken' in response:
                nextToken = response['nextToken']
                response = self.client.get_reservation_coverage(
                    TimePeriod={
                        'Start': self.ristart.isoformat(),
                        'End': self.riend.isoformat()
                    },
                    Granularity='MONTHLY',
                    NextPageToken=nextToken
                )
                results.extend(response['CoveragesByTime'])
                if 'nextToken' in response:
                    nextToken = response['nextToken']
                else:
                    nextToken = False
            
            rows = []
            for v in results:
                row = {'date':v['TimePeriod']['Start']}
                row.update({'Coverage%':float(v['Total']['CoverageHours']['CoverageHoursPercentage'])})
                rows.append(row)  
                    
            df = pd.DataFrame(rows)
            df.set_index("date", inplace= True)
            df = df.fillna(0.0)
            df = df.T
        elif Name in ['RIUtilization','RIUtilizationSavings']:
            #Only Six month to support savings
            results = []
            response = self.client.get_reservation_utilization(
                TimePeriod={
                    'Start': self.sixmonth.isoformat(),
                    'End': self.riend.isoformat()
                },
                Granularity='MONTHLY'
            )
            results.extend(response['UtilizationsByTime'])
            while 'nextToken' in response:
                nextToken = response['nextToken']
                response = self.client.get_reservation_utilization(
                    TimePeriod={
                        'Start': self.sixmonth.isoformat(),
                        'End': self.riend.isoformat()
                    },
                    Granularity='MONTHLY',
                    NextPageToken=nextToken
                )
                results.extend(response['UtilizationsByTime'])
                if 'nextToken' in response:
                    nextToken = response['nextToken']
                else:
                    nextToken = False
            
            rows = []
            if results:
                for v in results:
                    row = {'date':v['TimePeriod']['Start']}
                    if Savings:
                        row.update({'Savings$':float(v['Total']['NetRISavings'])})
                    else:
                        row.update({'Utilization%':float(v['Total']['UtilizationPercentage'])})
                    rows.append(row)  
                        
                df = pd.DataFrame(rows)
                df.set_index("date", inplace= True)
                df = df.fillna(0.0)
                df = df.T
                type = 'chart'
            else:
                df = pd.DataFrame(rows)
                type = 'table' #Dont try chart empty result
        elif Name == 'RIRecommendation':
            results = []
            response = self.client.get_reservation_purchase_recommendation(
                #AccountId='string', May use for Linked view
                LookbackPeriodInDays='SIXTY_DAYS',
                TermInYears='ONE_YEAR',
                PaymentOption=PaymentOption,
                Service=Service
            )
            results.extend(response['Recommendations'])
            while 'nextToken' in response:
                nextToken = response['nextToken']
                response = self.client.get_reservation_purchase_recommendation(
                    #AccountId='string', May use for Linked view
                    LookbackPeriodInDays='SIXTY_DAYS',
                    TermInYears='ONE_YEAR',
                    PaymentOption=PaymentOption,
                    Service=Service,
                    NextPageToken=nextToken
                )
                results.extend(response['Recommendations'])
                if 'nextToken' in response:
                    nextToken = response['nextToken']
                else:
                    nextToken = False
                
            rows = []
            for i in results:
                for v in i['RecommendationDetails']:
                    row = v['InstanceDetails'][list(v['InstanceDetails'].keys())[0]]
                    row['Recommended']=v['RecommendedNumberOfInstancesToPurchase']
                    row['Minimum']=v['MinimumNumberOfInstancesUsedPerHour']
                    row['Maximum']=v['MaximumNumberOfInstancesUsedPerHour']
                    row['Savings']=v['EstimatedMonthlySavingsAmount']
                    row['OnDemand']=v['EstimatedMonthlyOnDemandCost']
                    row['BreakEvenIn']=v['EstimatedBreakEvenInMonths']
                    row['UpfrontCost']=v['UpfrontCost']
                    row['MonthlyCost']=v['RecurringStandardMonthlyCost']
                    rows.append(row)  
                
                    
            df = pd.DataFrame(rows)
            df = df.fillna(0.0)
            type = 'table' #Dont try chart this
        self.reports.append({'Name':Name,'Data':df, 'Type':type})