#!/usr/bin/env python
# coding: utf-8

# In[3]:


import pandas as pd

query = """
    select  final.CUSTOMER_NUMBER_main as Focal_id,
        CAST(final.Cash_deposit_total AS DECIMAL(18, 2)) AS Cash_deposit_total,
        final.Cash_deposit_count,
        final.SEGMENT,
        final.RISK,
        final.SAR_FLAG
from 
(
    (
        select subquery.CUSTOMER_NUMBER_1 as CUSTOMER_NUMBER_main,
               subquery.Cash_deposit_total,
               subquery.Cash_deposit_count
        from 
        (
            select customer_number as CUSTOMER_NUMBER_1, 
                   sum(transaction_amount) as Cash_deposit_total, 
                   count(*) as Cash_deposit_count
            from 
            (
                select * 
                from {trans_data} trans_table 
                left join {acc_data} acc_table
                on trans_table.benef_account_number = acc_table.account_number
            ) trans
            where account_number not in ('None')
            and transaction_desc = 'CASH RELATED TRANSACTION'
            group by customer_number
        ) subquery
    ) main 
    left join 
   (
        select cd.CUSTOMER_NUMBER_3 as CUSTOMER_NUMBER_cust,
               cd.SEGMENT,
               cd.RISK,
               case
                    when ad.SAR_FLAG is NULL then 'N'
                    else ad.SAR_FLAG
               end as SAR_FLAG    
        from
        (
            select customer_number as CUSTOMER_NUMBER_3, 
                   business_segment as SEGMENT,
                   case
                       when RISK_CLASSIFICATION = 1 then 'Low Risk'
                       when RISK_CLASSIFICATION = 2 then 'Medium Risk'
                       when RISK_CLASSIFICATION = 3 then 'High Risk'
                       else 'Unknown Risk'
                   end AS RISK
            from {cust_data}
        ) cd 
        left join
        (
            select customer_number as CUSTOMER_NUMBER_4, 
                   sar_flag as SAR_FLAG
            from {alert_data}
        ) ad 
        on cd.CUSTOMER_NUMBER_3 = ad.CUSTOMER_NUMBER_4
    ) as cust_alert
    on cust_alert.CUSTOMER_NUMBER_cust = main.CUSTOMER_NUMBER_main
) as final
"""

from tms_data_interface import SQLQueryInterface

class Scenario:
    seq = SQLQueryInterface(schema="transactionschema")

    def logic(self, **kwargs):
        row_list = self.seq.execute_raw(query.format(trans_data="transaction10m",
                                                    cust_data="customer_data_v1",
                                                    acc_data="account_data_v1",
                                                    alert_data="alert_data_v1")
                                       )
        cols = ["Focal_id", "Cash_deposit_total", "Cash_deposit_count",
                "Segment", "Risk", "SAR_FLAG"]
        df = pd.DataFrame(row_list, columns = cols)
        df["Cash_deposit_total"] = df["Cash_deposit_total"].astype(float)
        return df


# In[6]:


# import pandas as pd

# query = """
#         SELECT 
#         t.transaction_id,
#         t.transaction_date,
#         t.transaction_amount,
#         t.transaction_desc,
#         t.benef_account_number,

#         -- Account data
#         a.account_number,
#         a.customer_number AS acc_customer_number,
#         a.account_type,
#         a.branch_code,

#         -- Party data
#         p.customer_number AS party_customer_number,
#         p.customer_name,
#         p.date_of_birth,
#         p.nationality,
#         p.business_segment,
#         CASE
#             WHEN p.risk_classification = 1 THEN 'Low Risk'
#             WHEN p.risk_classification = 2 THEN 'Medium Risk'
#             WHEN p.risk_classification = 3 THEN 'High Risk'
#             ELSE 'Unknown Risk'
#         END AS risk_level,

#         -- Alert data
#         COALESCE(al.sar_flag, 'N') AS sar_flag

#     FROM {trans_data} t

#     -- Join with account data on beneficiary account
#     LEFT JOIN {acc_data} a
#         ON t.benef_account_number = a.account_number

#     -- Join with party/customer data using account's customer number
#     LEFT JOIN {cust_data} p
#         ON a.customer_number = p.customer_number

#     -- Join with alert data using party's customer number
#     LEFT JOIN {alert_data} al
#         ON p.customer_number = al.customer_number

#     WHERE a.account_number IS NOT NULL
#     limit 100
# """

# from tms_data_interface import SQLQueryInterface

# class Scenario:
#     seq = SQLQueryInterface(schema="transactionschema")

#     def logic(self, **kwargs):
#         row_list = self.seq.execute_raw(query.format(trans_data="transaction10m",
#                                                     cust_data="customer_data_v1",
#                                                     acc_data="account_data_v1",
#                                                     alert_data="alert_data_v1")
#                                        )
#         cols = [
#                 "transaction_id",
#                 "transaction_date",
#                 "transaction_amount",
#                 "transaction_desc",
#                 "benef_account_number",
#                 "account_number",
#                 "acc_customer_number",
#                 "account_type",
#                 "branch_code",
#                 "party_customer_number",
#                 "customer_name",
#                 "date_of_birth",
#                 "nationality",
#                 "business_segment",
#                 "risk_level",
#                 "sar_flag"
#             ]
#         df = pd.DataFrame(row_list, columns = cols)
#         return df


# In[5]:


# sen = Scenario()
# sen.logic()


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