import os
import sys
# Required to load modules from vendored subfolder (for clean development env)
sys.path.append(os.path.join(os.path.dirname(os.path.realpath(__file__)), "./vendored"))
import boto3
import datetime
import logging
import pandas as pd
#For date
from dateutil.relativedelta import relativedelta
#For email
from email.mime.application import MIMEApplication
from email.mime.multipart import MIMEMultipart
from email.mime.text import MIMEText
from email.utils import COMMASPACE, formatdate
SES_REGION="ap-south-1"
CURRENT_MONTH = True
#Default exclude support, as for Enterprise Support
#as support billing is finalised later in month so skews trends
INC_SUPPORT = os.environ.get('INC_SUPPORT')
if INC_SUPPORT == "true":
    INC_SUPPORT = True
else:
    INC_SUPPORT = False
TAG_VALUE_FILTER = os.environ.get('TAG_VALUE_FILTER') or '*'
TAG_KEY = os.environ.get('TAG_KEY')
class CostExplorer:
    """Retrieves BillingInfo checks from CostExplorer API
    >>> costexplorer = CostExplorer()
    >>> costexplorer.addReport(GroupBy=[{"Type": "DIMENSION","Key": "SERVICE"}])
    >>> costexplorer.generateExcel()
    """
    def __init__(self, CurrentMonth=False):
        #Array of reports ready to be output to Excel.
        self.reports = []
        self.client = boto3.client('ce', region_name='us-east-1')
        # self.end = datetime.date.today().replace(day=1)
        self.riend = datetime.date.today()
        self.end = self.riend
        # Default is last 12 months
        self.start = (datetime.date.today() - relativedelta(months=+12)).replace(day=1) #1st day of month 12 months ago
        self.ristart = (datetime.date.today() - relativedelta(months=+11)).replace(day=1) #1st day of month 11 months ago
        self.sixmonth = (datetime.date.today() - relativedelta(months=+6)).replace(day=1) #1st day of month 6 months ago, so RI util has savings values
        self.accounts = {}
    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})
    def addReport(self, Name="Default",GroupBy=[{"Type": "DIMENSION","Key": "SERVICE"},],
    Style='Total', NoCredits=True, CreditsOnly=False, RefundOnly=False, UpfrontOnly=False, IncSupport=False):
        type = 'chart' #other option table
        results = []
        if not NoCredits:
            response = self.client.get_cost_and_usage(
                TimePeriod={
                    'Start': self.start.isoformat(),
                    'End': self.end.isoformat()
                },
                Granularity='MONTHLY',
                Metrics=[
                    'UnblendedCost',
                ],
                GroupBy=GroupBy
            )
        else:
            Filter = {"And": []}
            Dimensions={"Not": {"Dimensions": {"Key": "RECORD_TYPE","Values": ["Credit", "Refund", "Upfront", "Support"]}}}
            if INC_SUPPORT or IncSupport: #If global set for including support, we dont exclude it
                Dimensions={"Not": {"Dimensions": {"Key": "RECORD_TYPE","Values": ["Credit", "Refund", "Upfront"]}}}
            if CreditsOnly:
                Dimensions={"Dimensions": {"Key": "RECORD_TYPE","Values": ["Credit",]}}
            if RefundOnly:
                Dimensions={"Dimensions": {"Key": "RECORD_TYPE","Values": ["Refund",]}}
            if UpfrontOnly:
                Dimensions={"Dimensions": {"Key": "RECORD_TYPE","Values": ["Upfront",]}}
            tagValues = None
            if TAG_KEY:
                tagValues = self.client.get_tags(
                    SearchString=TAG_VALUE_FILTER,
                    TimePeriod = {
                        'Start': self.start.isoformat(),
                        'End': datetime.date.today().isoformat()
                    },
                    TagKey=TAG_KEY
                )
            if tagValues:
                Filter["And"].append(Dimensions)
                if len(tagValues["Tags"]) > 0:
                    Tags = {"Tags": {"Key": TAG_KEY, "Values": tagValues["Tags"]}}
                    Filter["And"].append(Tags)
            else:
                Filter = Dimensions.copy()
            response = self.client.get_cost_and_usage(
                TimePeriod={
                    'Start': self.start.isoformat(),
                    'End': self.end.isoformat()
                },
                Granularity='MONTHLY',
                Metrics=[
                    'UnblendedCost',
                ],
                GroupBy=GroupBy,
                Filter=Filter
            )
        if response:
            results.extend(response['ResultsByTime'])
            while 'nextToken' in response:
                nextToken = response['nextToken']
                response = self.client.get_cost_and_usage(
                    TimePeriod={
                        'Start': self.start.isoformat(),
                        'End': self.end.isoformat()
                    },
                    Granularity='MONTHLY',
                    Metrics=[
                        'UnblendedCost',
                    ],
                    GroupBy=GroupBy,
                    NextPageToken=nextToken
                )
                results.extend(response['ResultsByTime'])
                if 'nextToken' in response:
                    nextToken = response['nextToken']
                else:
                    nextToken = False
        rows = []
        sort = ''
        for v in results:
            row = {'date':v['TimePeriod']['Start']}
            sort = v['TimePeriod']['Start']
            for i in v['Groups']:
                key = i['Keys'][0]
                if key in self.accounts:
                    key = self.accounts[key][ACCOUNT_LABEL]
                row.update({key:float(i['Metrics']['UnblendedCost']['Amount'])})
            if not v['Groups']:
                row.update({'Total':float(v['Total']['UnblendedCost']['Amount'])})
            rows.append(row)
        df = pd.DataFrame(rows)
        df.set_index("date", inplace= True)
        df = df.fillna(0.0)
        if Style == 'Change':
            dfc = df.copy()
            lastindex = None
            for index, row in df.iterrows():
                if lastindex:
                    for i in row.index:
                        try:
                            df.at[index,i] = dfc.at[index,i] - dfc.at[lastindex,i]
                        except:
                            logging.exception("Error")
                            df.at[index,i] = 0
                lastindex = index
        df = df.T
        df = df.sort_values(sort, ascending=False)
        self.reports.append({'Name':Name,'Data':df, 'Type':type})
    def generateExcel(self):
        # Create a Pandas Excel writer using XlsxWriter as the engine.\
        os.chdir('/tmp')
        writer = pd.ExcelWriter('cost_explorer_report.xlsx', engine='xlsxwriter')
        workbook = writer.book
        for report in self.reports:
            print(report['Name'],report['Type'])
            report['Data'].to_excel(writer, sheet_name=report['Name'])
            worksheet = writer.sheets[report['Name']]
            if report['Type'] == 'chart':
                # Create a chart object.
                chart = workbook.add_chart({'type': 'column', 'subtype': 'stacked'})
                chartend=13
                for row_num in range(1, len(report['Data']) + 1):
                    chart.add_series({
                        'name':       [report['Name'], row_num, 0],
                        'categories': [report['Name'], 0, 1, 0, chartend],
                        'values':     [report['Name'], row_num, 1, row_num, chartend],
                    })
                chart.set_y_axis({'label_position': 'low'})
                chart.set_x_axis({'label_position': 'low'})
                worksheet.insert_chart('O2', chart, {'x_scale': 2.0, 'y_scale': 2.0})
        writer.save()
        #Time to deliver the file to S3
        if os.environ.get('S3_BUCKET'):
            s3 = boto3.client('s3')
            s3.upload_file("cost_explorer_report.xlsx", os.environ.get('S3_BUCKET'), "cost_explorer_report.xlsx")
        if os.environ.get('SES_SEND'):
            #Email logic
            msg = MIMEMultipart()
            msg['From'] = os.environ.get('SES_FROM')
            msg['To'] = COMMASPACE.join(os.environ.get('SES_SEND').split(","))
            msg['Date'] = formatdate(localtime=True)
            msg['Subject'] = "Cost Explorer Report"
            text = "Find your Cost Explorer report attached\n\n"
            msg.attach(MIMEText(text))
            with open("cost_explorer_report.xlsx", "rb") as fil:
                part = MIMEApplication(
                    fil.read(),
                    Name="cost_explorer_report.xlsx"
                )
            part['Content-Disposition'] = 'attachment; filename="%s"' % "cost_explorer_report.xlsx"
            msg.attach(part)
            #SES Sending
            ses = boto3.client('ses', region_name=SES_REGION)
            result = ses.send_raw_email(
                Source=msg['From'],
                Destinations=os.environ.get('SES_SEND').split(","),
                RawMessage={'Data': msg.as_string()}
            )
def lambda_handler(event, context):
    costexplorer = CostExplorer(CurrentMonth=False)
    #Default addReport has filter to remove Support / Credits / Refunds / UpfrontRI
    #Overall Billing Reports
    costexplorer.addReport(Name="Total", GroupBy=[],Style='Total',IncSupport=True)
    costexplorer.addReport(Name="TotalChange", GroupBy=[],Style='Change')
    costexplorer.addReport(Name="TotalInclCredits", GroupBy=[],Style='Total',NoCredits=False,IncSupport=True)
    costexplorer.addReport(Name="TotalInclCreditsChange", GroupBy=[],Style='Change',NoCredits=False)
    costexplorer.addReport(Name="Credits", GroupBy=[],Style='Total',CreditsOnly=True)
    costexplorer.addReport(Name="Refunds", GroupBy=[],Style='Total',RefundOnly=True)
    costexplorer.addReport(Name="RIUpfront", GroupBy=[],Style='Total',UpfrontOnly=True)
    #GroupBy Reports
    costexplorer.addReport(Name="Services", GroupBy=[{"Type": "DIMENSION","Key": "SERVICE"}],Style='Total',IncSupport=True)
    costexplorer.addReport(Name="ServicesChange", GroupBy=[{"Type": "DIMENSION","Key": "SERVICE"}],Style='Change')
    costexplorer.addReport(Name="Accounts", GroupBy=[{"Type": "DIMENSION","Key": "LINKED_ACCOUNT"}],Style='Total')
    costexplorer.addReport(Name="AccountsChange", GroupBy=[{"Type": "DIMENSION","Key": "LINKED_ACCOUNT"}],Style='Change')
    costexplorer.addReport(Name="Regions", GroupBy=[{"Type": "DIMENSION","Key": "REGION"}],Style='Total')
    costexplorer.addReport(Name="RegionsChange", GroupBy=[{"Type": "DIMENSION","Key": "REGION"}],Style='Change')
    if os.environ.get('COST_TAGS'): #Support for multiple/different Cost Allocation tags
        for tagkey in os.environ.get('COST_TAGS').split(','):
            tabname = tagkey.replace(":",".") #Remove special chars from Excel tabname
            costexplorer.addReport(Name="{}".format(tabname)[:31], GroupBy=[{"Type": "TAG","Key": tagkey}],Style='Total')
            costexplorer.addReport(Name="Change-{}".format(tabname)[:31], GroupBy=[{"Type": "TAG","Key": tagkey}],Style='Change')
    #RI Reports
    costexplorer.addRiReport(Name="RICoverage")
    costexplorer.addRiReport(Name="RIUtilization")
    costexplorer.addRiReport(Name="RIUtilizationSavings", Savings=True)
    costexplorer.addRiReport(Name="RIRecommendation") #Service supported value(s): Amazon Elastic Compute Cloud - Compute, Amazon Relational Database Service
    costexplorer.generateExcel()
    return "Report Generated"

{
    "Version": "2012-10-17",
    "Statement": [
        {
            "Effect": "Allow",
            "Action": [
                "logs:CreateLogGroup",
                "logs:CreateLogStream",
                "logs:PutLogEvents"
            ],
            "Resource": "*"
        }
    ]
}

{
    "Version": "2012-10-17",
    "Statement": [
        {
            "Sid": "VisualEditor0",
            "Effect": "Allow",
            "Action": [
                "s3:PutObject",
                "s3:GetObject"
            ],
            "Resource": "arn:aws:s3:::account.admin/*"
        }
    ]
}

{
    "Version": "2012-10-17",
    "Statement": [
        {
            "Sid": "VisualEditor0",
            "Effect": "Allow",
            "Action": [
                "ses:SendEmail",
                "ses:SendRawEmail"
            ],
            "Resource": "*"
        }
    ]
}

{
    "Version": "2012-10-17",
    "Statement": [
        {
            "Sid": "VisualEditor0",
            "Effect": "Allow",
            "Action": "ce:*",
            "Resource": "*"
        }
    ]
}