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

# In[1]:


# 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[5]:


import pandas as pd

query = """
        SELECT 
        t.transaction_key,
        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,

        -- 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
"""

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_key",
                "transaction_date",
                "transaction_amount",
                "transaction_desc",
                "benef_account_number",
                "account_number",
                "acc_customer_number",
                "Focal_id",
                "customer_name",
                "date_of_birth",
                "nationality",
                "Segment",
                "Risk", 
                "SAR_FLAG"
            ]
        df = pd.DataFrame(row_list, columns = cols)
        return df


# In[4]:


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


# In[ ]: