import pandas as pd

import numpy as np

from datetime import date

import boto3

import io

from io import StringIO

s3_res=boto3.client('s3')

s3_res1=boto3.resource('s3')

s3_res2=boto3.resource('s3')

stg_bucket=StringIO()

rmv_bucket=StringIO()

pos_error_bucket=StringIO()

posBucket=s3_res1.Bucket('positions-incoming-mohamw')

secBucket=s3_res2.Bucket('securities-incoming-mohamw')

count=0

for posFile in posBucket.objects.all():

#Print('Inside file processing')

#position_file=pd.read_csv(r's3://positions-incoming-na/PMT_Positions_POC.csv')

position_file=pd.read_csv(r's3://positions-incoming-mohamw/'+posFile.key)

#security_file=pd.read_csv(r's3://securities-incoming-na/PMT_Securities_POC.csv')

zero_position=position_file[position_file['Position|Market_Value_Local']==0]

good_position=position_file[~position_file['Account|Account_Number'].insin(zero_position['Account|Account_Number'])]

ref=0

i=0

for i in zero_position['Account|Account_Number']:

s3_res1.Object(pos_error_bucket,i+'_error_'+str(date.today())+'.txt').put(Body=i)

good_position.to_csv(stg_bucket)

s3_res1.Object(bucket_name,posFile.key).put(Bocy=stg_bucket.getValue())

for secFile in secBucket.Objects.all():

strTemp3=""

#3s3_res1.Object(bucket_name,'PMT_Positions_POC.csv').put(Body=stg_bucket.getvalue())

#good_position.to_csv(r'\\D:\poc\PMT_Positions_POC.csv',index=False)

security_file=pd.read_csv(r's3://securities-incoming-mohamw/'+secFile.key)

good_position['flag1']=security_file['Instrument_Issue|Cadis_ID']

good_position['flag2']=np.where(good_position['Position_Sec_ID|Cadis_ID']==good_position['flag1'],1,0)

error_position_file2=good_position[good_position['flag2']==0]

error_position_file2=pd.DataFrame(error_position_file2)

for x in error_position_file2['Account|Account)Number'].unique():

s3_res1.Object(pos_error_bucket,x+'_error2_'+str(date.today())+'.txt').put(Body=x)

position_file1=good_position[good_position['flag2']==0]

position_file1=pd.DataFrame(position_file1)

rmv_position_file=good_position[good_position['flag2']==1]

lstoutput=[]

#print(good_position)

if not emv_psoition_file.empty:

rmv_position_file=pd.DataFrame(rmv_position_file)

#print(rmv_position_file)

rmv_position_file['RMV']=rmv_position_file['Position|Market_Value_Local']*rmv_position_file['Position_Market+Price_Per_Unit']

rmv_position_file1=rmv_position_file[['Account|Account_Number','RMV']]

rmv_position_file1.rename(columns={'Account|Account_Number':'account_number'},inplace=True)

#rmv_position_file1.drop_duplicates(keep=False,inplace=True)

#rmv_position_file1.groupby(['account_number']).agg('sum').to_csv(rmv_bucket)

rmv_position_file1.groupby(['account_number']).agg('sum').to_csv(rmv_bucket)

context=rmv_bucket.getvalue()

strTemp=""

strTemp2=""

charVal2=""

for charVal in context:

charval2=charVal

strTemp=strTemp+charval2

stringToAdd="account_number,rmv"

strTemp2=(strTemp.replace("account_number,RMV",""))

#print("printing whole string:",strTemp2)

for temp in strTemp2.split("\n"):

if not temp.isspace():

strTemp3=strTemp3+temp+"\r\n"

finalString=stringToAdd+"\r\n"+strTemp3

print(finalString)

for i in rmv_position_file1['account_number']:

s3_res1.Object(rmv_bucket_name,i+'_rmv_.txt').put(Body=finalString)