From 0b1ac5b974d690e90bff6027db19f380d240772b Mon Sep 17 00:00:00 2001 From: qatest Date: Mon, 7 Oct 2024 06:06:54 +0000 Subject: [PATCH] System save at 07/10/2024 11:36 by qatest --- .ipynb_checkpoints/main-checkpoint.ipynb | 173 +++++++++++++++++++ main.ipynb | 206 +++++++++++++++++++---- main.py | 130 ++++++++++++++ 3 files changed, 476 insertions(+), 33 deletions(-) create mode 100644 .ipynb_checkpoints/main-checkpoint.ipynb create mode 100644 main.py diff --git a/.ipynb_checkpoints/main-checkpoint.ipynb b/.ipynb_checkpoints/main-checkpoint.ipynb new file mode 100644 index 0000000..81840d1 --- /dev/null +++ b/.ipynb_checkpoints/main-checkpoint.ipynb @@ -0,0 +1,173 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": null, + "id": "e706cfb0-2234-4c4c-95d8-d1968f656aa0", + "metadata": {}, + "outputs": [], + "source": [ + "from tms_data_interface import SQLQueryInterface\n", + "seq = SQLQueryInterface()\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "399856f9-dd38-4239-a35e-9a878c5391a6", + "metadata": {}, + "outputs": [], + "source": [ + "seq.execute_raw(\"show tables\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "ea68418d-e898-451b-8c9a-2f379b91dd6b", + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "a4d51f70-feaa-4565-8894-7fc5893f258e", + "metadata": {}, + "outputs": [], + "source": [ + "query = \"\"\"\n", + " select final.CUSTOMER_NUMBER_main as Focal_id,\n", + " final.Credit_transaction_amount,\n", + " final.Total_no_of_credit_transactions,\n", + " final.Debit_transaction_amount,\n", + " final.Total_no_of_debit_transactions,\n", + " final.SEGMENT,\n", + " final.RISK,\n", + " final.SAR_FLAG\n", + " from \n", + " (\n", + " (\n", + " select subquery.CUSTOMER_NUMBER_1 as CUSTOMER_NUMBER_main,\n", + " subquery.Credit_transaction_amount,\n", + " subquery.Total_no_of_credit_transactions,\n", + " case\n", + " when subquery.Debit_transaction_amount is NULL then 0\n", + " else Debit_transaction_amount\n", + " end as Debit_transaction_amount,\n", + " case\n", + " when subquery.Total_no_of_debit_transactions is NULL then 0\n", + " else Total_no_of_debit_transactions\n", + " end as Total_no_of_debit_transactions\n", + " from \n", + " (\n", + " (\n", + " select customer_number as CUSTOMER_NUMBER_1, \n", + " sum(transaction_amount) as Credit_transaction_amount, \n", + " count(*) as Total_no_of_credit_transactions\n", + " from \n", + " (\n", + " select * \n", + " from {trans_data} trans_table left join {acc_data} acc_table\n", + " on trans_table.benef_account_number = acc_table.account_number\n", + " )\n", + " where account_number not in ('None')\n", + " group by 1\n", + " ) credit left join\n", + " (\n", + " select customer_number as CUSTOMER_NUMBER_2, \n", + " sum(transaction_amount) as Debit_transaction_amount, \n", + " count(*) as Total_no_of_debit_transactions\n", + " from \n", + " (\n", + " select * \n", + " from {trans_data} trans_table left join {acc_data} acc_table\n", + " on trans_table.orig_account_number = acc_table.account_number\n", + " )\n", + " where account_number not in ('None')\n", + " group by 1\n", + " ) debit on credit.CUSTOMER_NUMBER_1 = debit.CUSTOMER_NUMBER_2 \n", + " ) subquery\n", + " ) main left join \n", + " (\n", + " select subquery.CUSTOMER_NUMBER_3 as CUSTOMER_NUMBER_cust,\n", + " subquery.SEGMENT,\n", + " subquery.RISK,\n", + " case\n", + " when subquery.SAR_FLAG is NULL then 'N'\n", + " else subquery.SAR_FLAG\n", + " end as SAR_FLAG \n", + " from\n", + " (\n", + " (\n", + " select customer_number as CUSTOMER_NUMBER_3, \n", + " business_segment as SEGMENT,\n", + " case\n", + " when RISK_CLASSIFICATION = 1 then 'Low Risk'\n", + " when RISK_CLASSIFICATION = 2 then 'Medium Risk'\n", + " when RISK_CLASSIFICATION = 3 then 'High Risk'\n", + " else 'Unknown Risk'\n", + " end AS RISK\n", + " from {cust_data}\n", + " ) cd left join\n", + " (\n", + " select customer_number as CUSTOMER_NUMBER_4, \n", + " sar_flag as SAR_FLAG\n", + " from {alert_data}\n", + " ) ad on cd.CUSTOMER_NUMBER_3 = ad.CUSTOMER_NUMBER_4\n", + " ) subquery\n", + " ) cust_alert on cust_alert.CUSTOMER_NUMBER_cust = main.CUSTOMER_NUMBER_main\n", + " ) final\n", + "\"\"\" " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "ea234072-0b05-4cde-8f12-7ac5c27e08ce", + "metadata": {}, + "outputs": [], + "source": [ + "from tms_data_interface import SQLQueryInterface\n", + " \n", + "class Scenario:\n", + " seq = SQLQueryInterface()\n", + " \n", + " def logic(self, **kwargs):\n", + " row_list = self.seq.execute_raw(query.format(trans_data=\"trans_60m_data\",\n", + " cust_data=\"final_customer_data_v1\",\n", + " acc_data=\"final_account_data_v1\",\n", + " alert_data=\"final_alert_data_v1\")\n", + " )\n", + " cols = [\"Focal_id\", \"Credit_transaction_amount\", \"Total_no_of_credit_transactions\",\n", + " \"Debit_transaction_amount\", \"Total_no_of_debit_transactions\",\n", + " \"Segment\", \"Risk\", \"SAR_FLAG\"]\n", + " df = pd.DataFrame(row_list, columns = cols)\n", + " return df" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.8" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/main.ipynb b/main.ipynb index 3277afb..81840d1 100644 --- a/main.ipynb +++ b/main.ipynb @@ -1,33 +1,173 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": null, - "id": "e706cfb0-2234-4c4c-95d8-d1968f656aa0", - "metadata": {}, - "outputs": [], - "source": "from tms_data_interface import SQLQueryInterface\n\nclass Scenario:\n\tseq = SQLQueryInterface()\n\n\tdef logic(self, **kwargs):\n\t\t# Write your code here\n" - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.8.13" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} \ No newline at end of file +{ + "cells": [ + { + "cell_type": "code", + "execution_count": null, + "id": "e706cfb0-2234-4c4c-95d8-d1968f656aa0", + "metadata": {}, + "outputs": [], + "source": [ + "from tms_data_interface import SQLQueryInterface\n", + "seq = SQLQueryInterface()\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "399856f9-dd38-4239-a35e-9a878c5391a6", + "metadata": {}, + "outputs": [], + "source": [ + "seq.execute_raw(\"show tables\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "ea68418d-e898-451b-8c9a-2f379b91dd6b", + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "a4d51f70-feaa-4565-8894-7fc5893f258e", + "metadata": {}, + "outputs": [], + "source": [ + "query = \"\"\"\n", + " select final.CUSTOMER_NUMBER_main as Focal_id,\n", + " final.Credit_transaction_amount,\n", + " final.Total_no_of_credit_transactions,\n", + " final.Debit_transaction_amount,\n", + " final.Total_no_of_debit_transactions,\n", + " final.SEGMENT,\n", + " final.RISK,\n", + " final.SAR_FLAG\n", + " from \n", + " (\n", + " (\n", + " select subquery.CUSTOMER_NUMBER_1 as CUSTOMER_NUMBER_main,\n", + " subquery.Credit_transaction_amount,\n", + " subquery.Total_no_of_credit_transactions,\n", + " case\n", + " when subquery.Debit_transaction_amount is NULL then 0\n", + " else Debit_transaction_amount\n", + " end as Debit_transaction_amount,\n", + " case\n", + " when subquery.Total_no_of_debit_transactions is NULL then 0\n", + " else Total_no_of_debit_transactions\n", + " end as Total_no_of_debit_transactions\n", + " from \n", + " (\n", + " (\n", + " select customer_number as CUSTOMER_NUMBER_1, \n", + " sum(transaction_amount) as Credit_transaction_amount, \n", + " count(*) as Total_no_of_credit_transactions\n", + " from \n", + " (\n", + " select * \n", + " from {trans_data} trans_table left join {acc_data} acc_table\n", + " on trans_table.benef_account_number = acc_table.account_number\n", + " )\n", + " where account_number not in ('None')\n", + " group by 1\n", + " ) credit left join\n", + " (\n", + " select customer_number as CUSTOMER_NUMBER_2, \n", + " sum(transaction_amount) as Debit_transaction_amount, \n", + " count(*) as Total_no_of_debit_transactions\n", + " from \n", + " (\n", + " select * \n", + " from {trans_data} trans_table left join {acc_data} acc_table\n", + " on trans_table.orig_account_number = acc_table.account_number\n", + " )\n", + " where account_number not in ('None')\n", + " group by 1\n", + " ) debit on credit.CUSTOMER_NUMBER_1 = debit.CUSTOMER_NUMBER_2 \n", + " ) subquery\n", + " ) main left join \n", + " (\n", + " select subquery.CUSTOMER_NUMBER_3 as CUSTOMER_NUMBER_cust,\n", + " subquery.SEGMENT,\n", + " subquery.RISK,\n", + " case\n", + " when subquery.SAR_FLAG is NULL then 'N'\n", + " else subquery.SAR_FLAG\n", + " end as SAR_FLAG \n", + " from\n", + " (\n", + " (\n", + " select customer_number as CUSTOMER_NUMBER_3, \n", + " business_segment as SEGMENT,\n", + " case\n", + " when RISK_CLASSIFICATION = 1 then 'Low Risk'\n", + " when RISK_CLASSIFICATION = 2 then 'Medium Risk'\n", + " when RISK_CLASSIFICATION = 3 then 'High Risk'\n", + " else 'Unknown Risk'\n", + " end AS RISK\n", + " from {cust_data}\n", + " ) cd left join\n", + " (\n", + " select customer_number as CUSTOMER_NUMBER_4, \n", + " sar_flag as SAR_FLAG\n", + " from {alert_data}\n", + " ) ad on cd.CUSTOMER_NUMBER_3 = ad.CUSTOMER_NUMBER_4\n", + " ) subquery\n", + " ) cust_alert on cust_alert.CUSTOMER_NUMBER_cust = main.CUSTOMER_NUMBER_main\n", + " ) final\n", + "\"\"\" " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "ea234072-0b05-4cde-8f12-7ac5c27e08ce", + "metadata": {}, + "outputs": [], + "source": [ + "from tms_data_interface import SQLQueryInterface\n", + " \n", + "class Scenario:\n", + " seq = SQLQueryInterface()\n", + " \n", + " def logic(self, **kwargs):\n", + " row_list = self.seq.execute_raw(query.format(trans_data=\"trans_60m_data\",\n", + " cust_data=\"final_customer_data_v1\",\n", + " acc_data=\"final_account_data_v1\",\n", + " alert_data=\"final_alert_data_v1\")\n", + " )\n", + " cols = [\"Focal_id\", \"Credit_transaction_amount\", \"Total_no_of_credit_transactions\",\n", + " \"Debit_transaction_amount\", \"Total_no_of_debit_transactions\",\n", + " \"Segment\", \"Risk\", \"SAR_FLAG\"]\n", + " df = pd.DataFrame(row_list, columns = cols)\n", + " return df" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.8" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/main.py b/main.py new file mode 100644 index 0000000..47a6ddd --- /dev/null +++ b/main.py @@ -0,0 +1,130 @@ +#!/usr/bin/env python +# coding: utf-8 + +# In[ ]: + + +from tms_data_interface import SQLQueryInterface +seq = SQLQueryInterface() + + +# In[ ]: + + +seq.execute_raw("show tables") + + +# In[ ]: + + +import pandas as pd + + +# In[ ]: + + +query = """ + select final.CUSTOMER_NUMBER_main as Focal_id, + final.Credit_transaction_amount, + final.Total_no_of_credit_transactions, + final.Debit_transaction_amount, + final.Total_no_of_debit_transactions, + final.SEGMENT, + final.RISK, + final.SAR_FLAG + from + ( + ( + select subquery.CUSTOMER_NUMBER_1 as CUSTOMER_NUMBER_main, + subquery.Credit_transaction_amount, + subquery.Total_no_of_credit_transactions, + case + when subquery.Debit_transaction_amount is NULL then 0 + else Debit_transaction_amount + end as Debit_transaction_amount, + case + when subquery.Total_no_of_debit_transactions is NULL then 0 + else Total_no_of_debit_transactions + end as Total_no_of_debit_transactions + from + ( + ( + select customer_number as CUSTOMER_NUMBER_1, + sum(transaction_amount) as Credit_transaction_amount, + count(*) as Total_no_of_credit_transactions + from + ( + select * + from {trans_data} trans_table left join {acc_data} acc_table + on trans_table.benef_account_number = acc_table.account_number + ) + where account_number not in ('None') + group by 1 + ) credit left join + ( + select customer_number as CUSTOMER_NUMBER_2, + sum(transaction_amount) as Debit_transaction_amount, + count(*) as Total_no_of_debit_transactions + from + ( + select * + from {trans_data} trans_table left join {acc_data} acc_table + on trans_table.orig_account_number = acc_table.account_number + ) + where account_number not in ('None') + group by 1 + ) debit on credit.CUSTOMER_NUMBER_1 = debit.CUSTOMER_NUMBER_2 + ) subquery + ) main left join + ( + select subquery.CUSTOMER_NUMBER_3 as CUSTOMER_NUMBER_cust, + subquery.SEGMENT, + subquery.RISK, + case + when subquery.SAR_FLAG is NULL then 'N' + else subquery.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 + ) subquery + ) cust_alert on cust_alert.CUSTOMER_NUMBER_cust = main.CUSTOMER_NUMBER_main + ) final +""" + + +# In[ ]: + + +from tms_data_interface import SQLQueryInterface + +class Scenario: + seq = SQLQueryInterface() + + def logic(self, **kwargs): + row_list = self.seq.execute_raw(query.format(trans_data="trans_60m_data", + cust_data="final_customer_data_v1", + acc_data="final_account_data_v1", + alert_data="final_alert_data_v1") + ) + cols = ["Focal_id", "Credit_transaction_amount", "Total_no_of_credit_transactions", + "Debit_transaction_amount", "Total_no_of_debit_transactions", + "Segment", "Risk", "SAR_FLAG"] + df = pd.DataFrame(row_list, columns = cols) + return df +