# Legacy approach when manually downloading CSVs from cost explorer
import pandas as pd
import time
import argparse
from datetime import date

import core
from accounts import accountListLegacy

def parse_arguments():
    parser = argparse.ArgumentParser()
    parser.add_argument('--path', default='', help='Path to external CSVs (only works if from-external-csv has been set)')


# Create dataframe from CSV file with report based on Services for untagged resources
def createDfFromUntaggedCsv(filename: str) -> pd.DataFrame:
    df = pd.read_csv(filename ,index_col='Service')
    df = df.fillna(0)
    df = df.drop(index='Service Total')
    df = df.drop(columns=['Total cost ($)'])
    return df

# Create dataframe from CSV file with report based on plat_env_project_service tag
# Ignores summary and untagged costs
def createDfFromTaggedCsv(filename: str) -> pd.DataFrame:
    df = pd.read_csv(filename ,index_col='plat_env_project_service')
    df = df.fillna(0)
    df = df.drop(index='plat_env_project_service Total')
    df = df.drop(columns=['No Tagkey: plat_env_project_service($)','Total cost ($)'])
    return df

# Generate reports from CSV files downloaded from
# CloudOps CostExplorer. You should have these files:
# amortized_costs.csv from "CF- Data Strategy Costs - Amortized Costs" report
# <account_number>.csv from "CF - 1 – 475275892927" report
def createReportFromCsvFiles(path: str) -> pd.DataFrame:
    resultDf = core.createEmptyDf()
    for acc, id in accountListLegacy().items():
        file = path + id + '.csv'
        input = createDfFromUntaggedCsv(file)
        accountDf = core.generateAccountCost(input, acc.split('-')[0], acc.split('-')[1])
        resultDf = pd.concat([resultDf, accountDf], ignore_index=True)
    print(resultDf)
    amortizedDf = core.generateAmortizedCosts(createDfFromTaggedCsv(path + 'amortized_costs.csv'))
    print(amortizedDf)

    concatDf = pd.concat([resultDf, amortizedDf], ignore_index=True)
    concatDf = core.sortBillingDf(concatDf)

    summarizedDf = core.generateSummaries(concatDf)
    print(summarizedDf)
    reportName = path + 'amortized_fully_tagged_costs_' + date.today().strftime("%Y-%m-%d") + '.csv'
    summarizedDf.to_csv(reportName, index=False)
    return summarizedDf

if __name__ == '__main__':
    args = parse_arguments()
    start = time.time()

    createReportFromCsvFiles(args.path)

    end = time.time()
    print(end - start)