init

README.md

+# FT Quant Rebalance API #
+
+   Version 1.3
+
+## Quick Start for Developing
+
+### Developing
+1. 為你的再平衡模型取一個簡稱(vender)，Ex: `sample` ( mpt, tv 已使用)
+2. 複製 vender/sample_quant_api.py  到  vender/`sample`_quant_api.py
+3. 打開 vender/`sample`_quant_api.py 實作 _rebalance(), 與 _dividend() (如果有需要)
+
+_rebalance(), 與 _dividend() 開發請參考 vender/sample_quant_api.py
+測試方式分述如下:
+#### _Rebalance() 測試說明
+1. Testing:
+   ```
+   python reb_test.py vender mode portfiolio_file [recommand_file [ class_file  [record_recomm_file [YYYYMMDD]]]]
+
+   ex:
+   python reb_test.py sample test test_data\reb.json test_data\portfolio.json  test_data\class.json test_data\record_portfolio.json 20180401
+
+   ```
+
+2. 參數格式說明
+   1. vender = 再平衡模型取一個簡稱 (sample 會執行 sample code )
+   2. mode = test or pord.   **`計量團隊`請固定用test**, prod 會取實際資料，且不需後續參數
+   3. portfiolio_file = 客戶持股比例檔(請參考quant_api.pdf: Q00003)， Prod mode: 資料由中台系統傳入 
+   4. recommand_file = 從推薦系統取得資料之格式，Prod mode: 資料由本RecommSystem提供
+   5. class_file = 資產分類檔。 **需由`計量團隊`提供**
+   6. record_recomm_file = 歷史推薦檔 ( for testing: default: "")
+   7. YYYYMMDD 模擬測試日期(default: Today)
+           
+
+##### About Test Case
+
+為了測試各種情況，請參考 src\test_case_gen\Sample 下建立相關用測試用例所需 json檔
+```
+cd src\test_case_gen\sample
+python gentestcase.py testcase_example.xlsx
+```
+
+步驟:
+1. 建立目錄 src/test_case_gen/`vendor`
+2. copy gentestcase.py, testcase_example.xlsx 到 src/test_case_gen/`vendor`
+3. 編輯 test_case.xlsx (與相關人員確認test case正確性)
+4. 執行 gentestcase.py (可自行調整程式，確保正確 parse test_case.xlsx)
+
+
+系統UAT時，會根據測試用例，做產出所有測試結果，提供`計量團隊`與相關專案人員審視，是否與白皮書相符。
+通過所有測試，方可上線
+
+
+##### Troubleshooting
+1. 為了測試Prod mode(RecommSystem 與 prod_api_agent.py )
+
+    ```
+    SET PYTHONPATH=.
+    python lib\prod_api_agent.py
+    ```
+
+#### _Dividend() 測試說明 
+1. Testing:
+   ```
+   python div_test.py vender portfiolio_file [YYYYMMDD]
+
+   ex:
+        python div_test.py sample test_data\test_case_01.json
+        or
+        python div_test.py sample test_data_div\test_case_01.json  20230301
+   ```
+
+2. 參數格式說明
+   1. vender = 再平衡模型取一個簡稱 (sample 會執行 sample code )
+   2. portfiolio_file = 客戶持股詳細資料 (請參考quant_api.pdf: Q00003)
+   3. YYYYMMDD 模擬測試日期(default: Today)
+           
+
+##### About Test Case
+    TBD 
\ No newline at end of file

div_test.py

+#from quant_api import Quant_api
+import sys
+import json
+import importlib as im
+
+def is_request_validated(data, ptype):
+    para = { "dividend" : ["vendor_id", "pts"]}
+    for parameter in para[ptype]:
+        if not parameter in data.keys():
+            return False
+    return True
+
+
+def dividend(data):
+    default_return_msg = {}
+    if not is_request_validated(data, "dividend"):
+        default_return_msg.update({"errorCode":"2002", "errorMsg":"json format is incorrect."})
+        return json.dumps(default_return_msg)
+
+    result = quant_api.dividend(data["pts"])
+    result.update(default_return_msg)
+    #quant_api.show_debug_info()
+    return json.dumps(result,indent=2, sort_keys=True, ensure_ascii=False)
+
+def usage():
+    print( '\n\tUsage: %s vender portfiolio_file [YYYYMMDD]' % sys.argv[0] )
+    print( 
+    '''
+        vender = sample (for testing)
+        portfiolio_file = 客戶持股詳情檔
+        YYYYMMDD = 假設今日日期 Default: Today
+    ''' )
+    sys.exit()
+
+_NOW__ = ''
+if __name__ == '__main__':
+    if len(sys.argv) >= 3 and len(sys.argv) <= 4:
+        vender = sys.argv[1]
+        data = json.load(open(sys.argv[2], encoding='utf-8'))
+        if len(sys.argv) == 4:
+            _NOW__=sys.argv[3]
+    else:
+        usage()
+    
+    mod = im.import_module('vender.'+ vender + "_quant_api")
+    Quant_api = getattr(mod, "Quant_api")
+    
+    quant_api = Quant_api("test", "", "", now=_NOW__)
+    print(dividend(data))

lib/test_api_agent.py

+import urllib3
+import json
+from datetime import datetime
+
+try:
+    from __main__ import _NOW__
+except:
+    _NOW__ = ''
+
+
+class Api_agent():
+
+    def __init__(self, portfolioDataPath="", assetClassPath=''):
+        if portfolioDataPath == "":
+            portfolioDataPath = 'test_data/portfolio.json'
+        if assetClassPath == "":
+            assetClassPath = 'test_data/class.json'
+        self.__DEBUG_INFO = ""
+        self.__classdata = json.load(open(assetClassPath, encoding='utf8'))
+        if type(portfolioDataPath) == str:
+            self.__portfolioData  = json.load(open(portfolioDataPath, encoding='utf8'))
+        else: 
+            self.__portfolioData  = json.load(open(portfolioDataPath[0], encoding='utf8'))
+            if portfolioDataPath[1] != "":
+                self.__portfolioData_record  = json.load(open(portfolioDataPath[1], encoding='utf8'))
+            
+        self.__portfolios = {}
+        self.__rp_idPortfolios = {}
+        self.today = datetime.now().strftime("%Y%m%d")
+        if _NOW__ != '':
+            self.today = _NOW__
+            print(f"日期非採用系統時間 ，採用傳入時間{self.today}")
+    '''    
+    def __get_request(self, query_string):
+        try:
+            rel = self.__TV_API.request("GET", query_string, headers = self.__HEADER_VALUES)
+            if rel == None:
+                pe
+                return None
+            data = ""
+            data = json.loads(rel.data.decode('utf-8'))
+            if len(data['data']) == 0:
+                return None
+            return data
+        except Exception as e:
+            self.__DEBUG_INFO = str(e)
+            return None
+    '''
+    def get_debug_info(self):
+        return self.__DEBUG_INFO
+
+    def get_latest_portfolio(self, portfolio_id, query_date):
+        query_date = query_date.replace('-','')
+        if query_date != '' and query_date != self.today:
+            self.__DEBUG_INFO = ('目前不提供指定日期取得推薦功能，除非是本日(%s)，實際輸入日期為(%s)' %(self.today,query_date ))
+            #print("測試時忽略推薦日期檢查")
+            print("***  測試時間不同，可能是 {vender}_quant_api.py 未加入 replace datetime.now()的程式碼")
+            return None
+        if portfolio_id in self.__portfolios.keys():
+            return self.__portfolios[portfolio_id]
+
+        try:
+            data = self.__portfolioData
+            if len(data['rps']) == 0:
+                return None
+
+            for d in data['rps'] :
+                if d['recomm_guid'] == portfolio_id:
+                    if not 'data_Date' in d:
+                        print(" Warning: `data_Date` is None, 但是不影響測試，只影響生產環境")
+                    elif  d['data_Date'] == self.today :
+                        pass
+                    else: 
+                        print(" Warning: `data_Date` is invalidated, 但是不影響測試，只影響生產環境")
+                        
+                    self.__portfolios[portfolio_id] = d
+                    return self.__portfolios[portfolio_id]
+                    
+
+            return None
+        except Exception as e:
+            self.__DEBUG_INFO = str(e)
+            return None
+        pass
+
+        api_query = "%s/franklin/prediction_data/%s/%s" % (self.__TV_API_URL, portfolio_id, query_date)
+        return self.__get_request(api_query)
+
+    def get_portfolio_by_rpid(self, rp_id):
+        rp_id = str(rp_id)
+        if rp_id in self.__rp_idPortfolios.keys():
+            return self.__rp_idPortfolios[rp_id]
+
+        try:
+            data = self.__portfolioData_record
+            if len(data['rps']) == 0:
+                return None
+
+            for d in data['rps'] :
+                d['rp_id'] = str(d['rp_id'])
+                if d['rp_id'] == rp_id:
+                    self.__rp_idPortfolios[rp_id] = d
+                    return self.__rp_idPortfolios[rp_id]
+
+            return None
+        except Exception as e:
+            self.__DEBUG_INFO = str(e)
+            return None
+        pass
+
+        api_query = "%s/franklin/prediction_data/%s/%s" % (self.__TV_API_URL, portfolio_id, query_date)
+        return self.__get_request(api_query)
+
+    def get_fund_metadata(self, fund_id):
+        return self.__classdata[fund_id]
+        pass
+
+        api_query = "%s/franklin/fundpool/%s" % (self.__TV_API_URL, fund_code)
+        data = self.__get_request(api_query)
+        if not data == None:
+            return data['data'][0]
+        return None

reb_test.py

+#from quant_api import Quant_api
+import sys
+import json
+import importlib as im
+
+def is_request_validated(data, ptype):
+    para = { "rebalance" : ["vendor_id", "pts"]}
+    for parameter in para[ptype]:
+        if not parameter in data.keys():
+            return False
+    return True
+
+
+def rebalance(data):
+    default_return_msg = {}
+    if not is_request_validated(data, "rebalance"):
+        default_return_msg.update({"errorCode":"2002", "errorMsg":"json format is incorrect."})
+        return json.dumps(default_return_msg)
+
+    result = quant_api.rebalance(data["pts"])
+    result.update(default_return_msg)
+    #quant_api.show_debug_info()
+    return json.dumps(result,indent=2, sort_keys=True, ensure_ascii=False)
+
+def usage():
+    print( '\n\tUsage: %s vender mode portfiolio_file [recommand_file [ class_file [recordportfolio [now]] ]]' % sys.argv[0] )
+    print( 
+    '''
+        vender = sample (for testing)
+        mode = test / pord
+        portfiolio_file = 客戶持股比例檔
+        recommandile = 推薦檔 ( for testing: default: test_data/portfolio.json)
+        class_file = 大類資產檔 ( for testing: default: test_data/class.json)
+        recordportfolio = 歷史推薦檔 ( for testing: default: "")
+        now  =  測試用系統時間 (預設為當日,format: yyyymmdd))
+    ''' )
+    sys.exit()
+
+_NOW__ = ''
+if __name__ == '__main__':
+    portfolioDataPath = ""
+    assetClassPath = ""
+    recordportfolio_DataPath = ""
+    now = ""
+
+    if len(sys.argv) >= 4:
+        vender = sys.argv[1]
+        mode = sys.argv[2]
+        
+        if mode == 'test' : 
+            data = json.load(open(sys.argv[3], encoding='utf-8'))
+            if len(sys.argv) == 5 :
+                portfolioDataPath = sys.argv[4]
+            if len(sys.argv) == 6 :
+                portfolioDataPath = sys.argv[4]
+                assetClassPath = sys.argv[5]
+            if len(sys.argv) == 7:
+                portfolioDataPath = sys.argv[4]
+                assetClassPath = sys.argv[5]
+                recordportfolio_DataPath = sys.argv[6]
+            if len(sys.argv) == 8:
+                portfolioDataPath = sys.argv[4]
+                assetClassPath = sys.argv[5]
+                recordportfolio_DataPath = '' if sys.argv[6] == 'None' else sys.argv[6]
+                _NOW__=sys.argv[7]
+            
+                
+        elif mode == 'prod':
+            data = json.load(open(sys.argv[3], encoding='utf-8'))
+        
+        else:
+            usage()
+    else:
+        usage()
+    
+    '''
+    else:
+        vender = sys.argv[1]
+        mode = 'release'
+        data = json.load(open(sys.argv[2]))
+    '''
+
+    mod = im.import_module('vender.'+ vender + "_quant_api")
+    Quant_api = getattr(mod, "Quant_api")
+    if assetClassPath == "":
+        def print2(*args):
+            #print(*args)
+            return
+        from flask import Flask, current_app
+        app = Flask(__name__)
+        app.logger.error = print2
+        app.logger.warning = print2
+        app.logger.info = print2
+        app.logger.debug = print2
+        with app.app_context():
+            quant_api = Quant_api(mode, portfolioDataPath)
+            print(rebalance(data))
+
+    else:
+        #if recordportfolio_DataPath == "":
+        #    quant_api = Quant_api(mode, portfolioDataPath, assetClassPath)
+        #else:
+        quant_api = Quant_api(mode, [portfolioDataPath, recordportfolio_DataPath], assetClassPath, now=_NOW__)
+        #quant_api = Quant_api(mode, [portfolioDataPath, recordportfolio_DataPath], assetClassPath)
+        print(rebalance(data))

requirements.txt

+click==6.7
+DateTime==4.3
+Flask==1.0.2
+Flask-Cors==3.0.6
+itsdangerous==0.24
+Jinja2==2.10
+joblib==0.14.0
+MarkupSafe
+numpy==1.17.2
+pandas==0.25.1
+python-dateutil==2.8.0
+pytz==2018.7
+scikit-learn==0.21.3
+scipy==1.3.1
+six==1.11.0
+urllib3==1.23
+Werkzeug==0.14.1
+wfastcgi==3.0.0
+xlrd==1.2.0
+zope.interface==4.6.0

test_case_gen/Sample/gentestcase.py

+#!/usr/bin/env python3
+# -*- coding: UTF-8 -*-
+import json
+import sys
+import pandas as pd
+
+
+def main(xls_path):
+	xls = pd.ExcelFile(xls_path)
+	if len(xls.sheet_names) <2:
+		return
+	
+	
+	for sheet_name in xls.sheet_names[1:]:
+		df = xls.parse(sheet_name)
+		tc = sheet_name.replace(' ', '_')
+
+
+		portfolio = {}
+		portfolio["vendor_id"] = "test"
+		portfolio["sync"] = 1
+		obj = {}
+		portfolio["pts"]= [obj]
+
+		obj['recomm_id'] = str(df.loc[0][2])
+		obj['rp_id'] = df.loc[1][2]
+		obj['pt_id'] = df.loc[2][2]
+		obj['last_tx_date'] = df.loc[3][2]
+		obj['last_recomm_date'] = df.loc[4][2]
+		obj['create_date'] = df.loc[5][2]
+		if str(df.loc[6][2]) != 'nan': obj['last_check_date'] = df.loc[6][2]   
+		if str(df.loc[7][2]) != 'nan': obj['last_reb_date'] = df.loc[7][2] 
+		obj['note'] = str(df.loc[8][2])
+		fas = []
+		obj['fas'] = fas
+		
+		#for i in range(10, len(df.loc[1:])):
+		for i in range(10, 20):
+			try:
+				#print(str(df.loc[i][2]))
+				if str(df.loc[i][2]) == 'nan':
+					print('len(portfolios) = ' + str(i))
+					break
+
+				fas.append( { 
+						'fund_id': str(df.loc[i][2]),
+						'weight': str(df.loc[i][3])
+				})
+			except:
+				print('len(portfolios) = ' + str(i))
+				break
+	
+		#print(json.dumps(portfolio))
+		outf = tc+'_portfolio.json'
+		print ( "create file: " + outf)
+		with open(outf, 'w') as outfile:
+			json.dump(portfolio, outfile)
+
+
+		recomm  = {}
+		rp = {}
+		recomm['rps']  = [rp]
+		rp['recomm_guid'] = str(df.loc[0][9])
+		rp['rp_id'] = df.loc[1][9]
+		rp['note'] = str(df.loc[8][2])
+		fws = []
+		rp['fws'] = fws
+		#for i in range(10, len(df.loc[1:])):
+		for i in range(10, 20):
+			try:
+				#print(df.loc[i][8])
+				if str(df.loc[i][8]) == 'nan':
+					print('len(recomm) = ' + str(i))
+					break
+				fws.append( { 
+						'fund_id': str(df.loc[i][8]),
+						'weight': str(df.loc[i][9])
+				})
+			except:
+				print('len(recomm) = ' + str(i))
+				break
+
+		outf = tc+'_recomm.json'
+		print ( "create file: " + outf)
+		with open(outf, 'w') as outfile:
+			json.dump(recomm, outfile)
+
+def usage():
+	print("USAGE:\n\t", sys.argv[0], " XLS_PATH"  )
+	
+if __name__ == "__main__":
+	if len(sys.argv) == 2 :
+		xls_path = sys.argv[1]
+		main(xls_path)
+	else:
+		usage()
+	

test_data/class.json

+{
+    "0352": "Equity"
+   , "0358": "Equity"
+   , "0361": "Equity"
+   , "0375": "Equity"
+   , "0419": "Equity"
+   , "0433": "Equity"
+   , "0533": "Equity"
+   , "0575": "Equity"
+   , "0587": "Equity"
+   , "0592": "Equity"
+   , "0776": "Equity"
+   , "0777": "Equity"
+   , "0778": "Equity"
+   , "0779": "Equity"
+   , "0781": "Equity"
+   , "0782": "Equity"
+   , "0785": "Equity"
+   , "0786": "Equity"
+   , "0790": "Equity"
+   , "0794": "Equity"
+   , "0796": "Equity"
+   , "0797": "Equity"
+   , "0799": "Equity"
+   , "0805": "Equity"
+   , "0822": "Equity"
+   , "0824": "Equity"
+   , "0828": "Equity"
+   , "0830": "Equity"
+   , "0836": "Equity"
+   , "1000": "Equity"
+   , "1009": "Equity"
+   , "101": "Equity"
+   , "1019": "Equity"
+   , "102": "Equity"
+   , "103": "Equity"
+   , "104": "Equity"
+   , "106": "Equity"
+   , "107": "Equity"
+   , "108": "Equity"
+   , "150": "Equity"
+   , "158": "Equity"
+   , "0152": "Equity"
+   , "0384": "Bond"
+   , "0426": "Bond"
+   , "0549": "Bond"
+   , "0651": "Bond"
+   , "0750": "Bond"
+   , "0751": "Bond"
+   , "1105": "Bond"
+   , "1174": "Bond"
+   , "1715": "Bond"
+   , "132": "AntiInflation"
+   , "0788": "Cash"
+   , "1641": "Cash"
+}

test_data/portfolio.json

+{
+    "errorMSG": true,
+    "rps": [
+       {
+        "recomm_guid": "12345678-1234-ABCD-ABCD-123456789012",
+        "rp_id": 888,
+        "fws": [
+            {
+                "fund_id": "0575",
+                "weight": "35"
+            },
+            {
+                "fund_id": "0352",
+                "weight": "6"
+            },
+            {
+                "fund_id": "0384",
+                "weight": "19"
+            },
+            {
+                "fund_id": "1105",
+                "weight": "5"
+            },
+            {
+                "fund_id": "103",
+                "weight": "35"
+            }
+         ]
+         ,"note" : "{\"last_reg_reb\":\"20190801\",\"last_irreg_reb\":\"20190825\",\"risk_control\": [[0, 1, 2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19],[0, 1, 2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19]]}"
+       },
+       {
+        "recomm_guid": "87654321-4321-DCBA-DCBA-210987654321",
+        "rp_id": "999",
+        "fws": [
+            {
+                "fund_id": "0575",
+                "weight": "35"
+            },
+            {
+                "fund_id": "0352",
+                "weight": "6"
+            },
+            {
+                "fund_id": "0384",
+                "weight": "19"
+            },
+            {
+                "fund_id": "1105",
+                "weight": "5"
+            },
+            {
+                "fund_id": "103",
+                "weight": "35"
+            }
+         ]
+         ,"note" : "{\"last_reg_reb\":\"20190801\",\"last_irreg_reb\":\"20190825\",\"risk_control\": [[0, 1, 2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19],[0, 1, 2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19]]}"
+      },
+      {
+       "recomm_guid": "87654321-4321-DCBA-DCBA-210987654321",
+       "rp_id": "310",
+       "fws": [
+           {
+               "fund_id": "0575",
+               "weight": "30"
+           },
+           {
+               "fund_id": "0352",
+               "weight": "11"
+           },
+           {
+               "fund_id": "0384",
+               "weight": "19"
+           },
+           {
+               "fund_id": "1105",
+               "weight": "5"
+           },
+           {
+               "fund_id": "103",
+               "weight": "35"
+           }
+        ]
+        ,"note" : "{\"last_reg_reb\":\"20190801\",\"last_irreg_reb\":\"20190825\",\"risk_control\": [[0, 1, 2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19],[0, 1, 2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19]]}"
+     }
+    ]
+}

test_data/reb.json

+{
+	"pts": [{
+			"create_date": "2018-02-20",
+			"fas": [{
+					"fund_id": "0352",
+					"weight": "45"
+				}, {
+					"fund_id": "0788",
+					"weight": "0"
+				}, {
+					"fund_id": "0384",
+					"weight": "6"
+				}, {
+					"fund_id": "1105",
+					"weight": "5"
+				}, {
+					"fund_id": "1715",
+					"weight": "9"
+				}
+			],
+			"last_recomm_date": "2018-03-20",
+			"last_tx_date": "2018-03-27",
+			"last_check_date": "2018-03-27",
+			"pt_id": "0",
+			"recomm_id": "87654321-4321-DCBA-DCBA-210987654321",
+			"rp_id": 310
+		}, {
+			"create_date": "2018-02-20",
+			"fas": [{
+					"fund_id": "0352",
+					"weight": "45"
+				}, {
+					"fund_id": "0788",
+					"weight": "0"
+				}, {
+					"fund_id": "0384",
+					"weight": "6"
+				}, {
+					"fund_id": "1105",
+					"weight": "5"
+				}, {
+					"fund_id": "1715",
+					"weight": "9"
+				}
+			],
+			"last_recomm_date": "2018-03-20",
+			"last_tx_date": "2018-03-27",
+			"last_check_date": "2018-03-27",
+			"pt_id": "1",
+			"recomm_id": "87654321-4321-DCBA-DCBA-210987654321",
+			"rp_id": 310
+		}, {
+			"create_date": "2018-02-20",
+			"fas": [{
+					"fund_id": "0352",
+					"weight": "5"
+				}, {
+					"fund_id": "0788",
+					"weight": "35"
+				}, {
+					"fund_id": "0384",
+					"weight": "16"
+				}, {
+					"fund_id": "1105",
+					"weight": "25"
+				}, {
+					"fund_id": "1715",
+					"weight": "19"
+				}
+			],
+			"last_recomm_date": "2018-03-20",
+			"last_tx_date": "2018-03-27",
+			"last_check_date": "2018-03-27",
+			"pt_id": "9999999",
+			"recomm_id": "87654321-4321-DCBA-DCBA-210987654321",
+			"rp_id": 310
+		}
+	],
+	"vendor_id": "TV",
+	"sync": 1
+}

test_data/record_portfolio.json

+{
+  "errorMSG": true,
+  "rps": [
+    {
+      "recomm_guid": "D02C7E12-0A50-46BA-840F-F7C47BD8FCD5",
+      "rp_id": "310",
+      "fws": [
+        {
+          "fund_id": "0779",
+          "weight": "30"
+        },
+        {
+          "fund_id": "1049",
+          "weight": "15"
+        },
+        {
+          "fund_id": "0810",
+          "weight": "20"
+        },
+        {
+          "fund_id": "1435",
+          "weight": "5"
+        },
+        {
+          "fund_id": "1174",
+          "weight": "30"
+        }
+      ],
+      "note": "{'last_reg_reb': '20190501', 'last_irreg_reb': '20190420', 'risk_control': [{'2019-06-27': {('成熟亚洲股票', 'ACDPAC Index'): 7.1, ('大宗商品', 'BCOM Index'): 3.9, ('全球股票', 'BWORLD Index'): 5.5, ('中国债券', 'CSIH1001 Index'): 3.6, ('中国利率债', 'CSIH1006 Index'): 4.1, ('中国信用债', 'CSIH1073 Index'): 3.7, ('新兴市场债券', 'EMUSTRUU Index'): 6.6, ('成熟亚洲债券', 'H05411US Index'): 4.0, ('北美投资级及以上债券', 'I17660US Index'): 7.9, ('大中华债券', 'I29380US Index'): 4.7, ('新兴亚洲债券', 'LAPCTRUU Index'): 5.3, ('全球债券', 'LEGATRUU Index'): 4.3, ('北美高收益债券', 'LF98TRUU Index'): 4.0, ('货币市场', 'LIBMB01M Index'): 2.8, ('欧洲高收益债券', 'LP01TREU Index'): 5.1, ('新兴拉美股票', 'MSEUEGFL Index'): 5.3, ('欧非中东股票', 'MXEE Index'): 4.8, ('新兴市场股票', 'MXEF Index'): 4.3, ('欧洲股票', 'MXEU Index'): 3.7, ('大中华股票', 'MXGD Index'): 5.2, ('新兴亚洲股票', 'MXMS Index'): 4.1, ('房地产', 'MXWO0RE Index'): 5.3, ('欧洲投资级及以上债券', 'QW1A Index'): 4.0, ('A股小盘', 'SH000905 Index'): 4.2, ('A股被动型', 'SHSZ300 Index'): 3.1, ('能源', 'SPGSCITR Index'): 4.0, ('北美股票', 'SPX Index'): 4.9, ('A股大盘', 'SSE50 Index'): 4.6, ('全球另类策略', 'USGG3YR Index'): 5.6, ('黄金', 'XAU Curncy'): 4.4}}, {'2019-06-26': {('成熟亚洲股票', 'ACDPAC Index'): 7.2, ('大宗商品', 'BCOM Index'): 3.9, ('全球股票', 'BWORLD Index'): 5.5, ('中国债券', 'CSIH1001 Index'): 3.3, ('中国利率债', 'CSIH1006 Index'): 4.2, ('中国信用债', 'CSIH1073 Index'): 3.5, ('新兴市场债券', 'EMUSTRUU Index'): 6.6, ('成熟亚洲债券', 'H05411US Index'): 3.6, ('北美投资级及以上债券', 'I17660US Index'): 7.9, ('大中华债券', 'I29380US Index'): 5.0, ('新兴亚洲债券', 'LAPCTRUU Index'): 5.3, ('全球债券', 'LEGATRUU Index'): 4.3, ('北美高收益债券', 'LF98TRUU Index'): 3.7, ('货币市场', 'LIBMB01M Index'): 2.8, ('欧洲高收益债券', 'LP01TREU Index'): 5.3, ('新兴拉美股票', 'MSEUEGFL Index'): 5.4, ('欧非中东股票', 'MXEE Index'): 4.7, ('新兴市场股票', 'MXEF Index'): 4.4, ('欧洲股票', 'MXEU Index'): 3.7, ('大中华股票', 'MXGD Index'): 5.3, ('新兴亚洲股票', 'MXMS Index'): 4.2, ('房地产', 'MXWO0RE Index'): 5.1, ('欧洲投资级及以上债券', 'QW1A Index'): 4.0, ('A股小盘', 'SH000905 Index'): 4.2, ('A股被动型', 'SHSZ300 Index'): 3.0, ('能源', 'SPGSCITR Index'): 4.3, ('北美股票', 'SPX Index'): 4.9, ('A股大盘', 'SSE50 Index'): 4.6, ('全球另类策略', 'USGG3YR Index'): 5.5, ('黄金', 'XAU Curncy'): 4.3}}]}"
+    }
+  ]
+}
\ No newline at end of file

test_data_div/test_case_01.json

+{	"vendor_id": "Dividen_TEST", 
+    "pts": [{
+            "pt_id": 123,
+            "last_pd_date": "2023-07-15",
+            "last_check_date": "2023-07-15",
+            "create_date": "2017-11-23",
+            "total_in": 30000.0,
+            "div_rate": 0.12,
+            "div_month": [3, 6, 9, 12],
+            "asset": [{
+                    "fund_id": "1234",
+                    "nav": 1.11,
+                    "rate": 30.11,
+                    "rr": 4,
+                    "share": "1.111"
+                }, {
+                    "fund_id": "5678",
+                    "nav": 2.22,
+                    "rate": 30.22,
+                    "rr": 4,
+                    "share": "2.222"
+                }
+            ]
+        }, {
+            "pt_id": 1,
+            "create_date": "2017-11-23",
+            "total_in": 30000.0,
+            "asset": [{
+                    "fund_id": "4321",
+                    "nav": 3.33,
+                    "rate": 30.33,
+                    "rr": 4,
+                    "share": "3.333"
+                }, {
+                    "fund_id": "8765",
+                    "nav": 4.44,
+                    "rate": 30.44,
+                    "rr": 4,
+                    "share": "11.444"
+                }
+            ]
+        }
+    ]
+}

vender/quant_api_base.py

+import hashlib
+import json
+import importlib as im
+from datetime import datetime, timedelta
+
+
+class base_Quant_api():
+
+    def __init__(self, type, portfolioDataPath="", assetClassPath="", now=""):
+        mod = im.import_module('lib.' + type + "_api_agent")
+        api_agent = getattr(mod, "Api_agent")
+
+        self.__default_msg = {'errorCode': '0', 'errorMsg': ''}
+        self.__pt_keys = ["pt_id", "recomm_id", "rp_id", "last_tx_date", "last_recomm_date", "create_date", "fas", "last_check_date"]
+        self.__fas_keys = ["fund_id", "weight"]
+        self.__api = api_agent(portfolioDataPath, assetClassPath)
+        self.__portfolios = {}
+        self.__fund_metadata = {}
+        self.__debug_info = {}
+        self.nowstr  = now
+
+    def now(self):
+        if self.nowstr == "":
+            return datetime.now()
+        else:
+            return datetime(int(self.nowstr[:4]), int(self.nowstr[4:6]), int(self.nowstr[6:8]))
+
+    def __debug(self, msg):
+        self.__debug_info[datetime.now()] = msg
+        return True
+
+    def __gen_rcv_no(self, recomm_id, numbers):
+        return "%s-%s-%s" % (datetime.now().strftime("%Y%m%d%H%M%S"), recomm_id, numbers)
+
+    def __verify_pt_data(self, data):
+        para = ["fas", "last_recomm_date", "last_tx_date", "pt_id", "recomm_id", "rp_id"]
+        for parameter in para:
+            if not parameter in data.keys():
+                return False
+        if len(data["fas"]) == 0:
+            return False
+        return True
+
+    def __verify_pt_data_dividend(self, data):
+        para = ["pt_id", "total_in", "asset"]
+        for parameter in para:
+            if not parameter in data.keys():
+                return False
+        if len(data["asset"]) == 0:
+            return False            
+        return True
+
+    def get_latest_portfolio(self, recomm_id, query_date = ''):
+        #self.__debug("Getting portfolio data: %s" % query_key)
+        portfolio_data = self.__api.get_latest_portfolio(recomm_id, query_date)
+        #self.__debug("%s: %s" % (portfolio_id, json.dumps(portfolio_data)))
+        if portfolio_data != None:
+            return portfolio_data
+        return None
+        
+
+    def get_portfolio_by_rpid(self, rp_id):
+        #self.__debug("Getting portfolio data: %s" % query_key)
+        portfolio_data = self.__api.get_portfolio_by_rpid(rp_id)
+        #self.__debug("%s: %s" % (portfolio_id, json.dumps(portfolio_data)))
+        if portfolio_data != None:
+            return portfolio_data
+        return None
+
+    def get_fund_asset_class(self, fund_id):
+        self.__debug("Getting fund asset class: %s" % fund_id)
+        data = self.__api.get_fund_metadata(fund_id)
+        if data != None:
+            return data
+        return None
+
+    def _rebalance(self, pt):
+        pass
+
+    def _dividend(self, pt):
+        pass
+        
+
+    def show_debug_info(self):
+        if not bool(self.__debug_info):
+            return True 
+        for exec_time in sorted(self.__debug_info):
+            print("[%s] %s" % (exec_time.strftime("%Y-%m-%d %H:%M:%S.%f"), self.__debug_info[exec_time]))
+        self.__debug_info = {}
+        return True
+        
+
+    def rebalance(self, pts):
+        self.__default_msg = {'errorCode': '0', 'errorMsg': 'Success', 'rebs':[]}
+        pt_len = len(pts)
+        if pt_len == 0:
+            return self.__default_msg
+        self.__default_msg['rcv_no'] = self.__gen_rcv_no(pts[0]["recomm_id"], pt_len) # it need to be confirmed.
+        for pt in pts:
+            if not self.__verify_pt_data(pt):
+                self.__debug("Failed to verify pt data")
+                self.__default_msg['errorCode'] ="1001"
+                self.__default_msg['errorMsg'] = "Failed to verify pts data."
+                self.__default_msg['rebs']= []
+                break
+
+            else :
+                #self._rebalance(pt)
+                res = self._rebalance(pt)
+                #(rp_id, reason) = self._rebalance(pt)
+                
+                if res == 0:
+                    rp_id = '0'
+                    reason = '符合所有條件，無需REB'
+                else:
+                    (rp_id, reason) = res
+
+                self.__default_msg['rebs'].append({"pt_id":pt["pt_id"], "rp_id":rp_id, "reason":reason }) 
+                #self.__default_msg['rebs'].append({"pt_id":pt["pt_id"], "rp_id": self._rebalance(pt)}) 
+
+        return self.__default_msg
+
+
+    def dividend(self, pts):
+        self.__default_msg = {'errorCode': '0', 'errorMsg': 'Success', 'dividends':[]}
+        pt_len = len(pts)
+        if pt_len == 0:
+            return self.__default_msg
+        
+        for pt in pts:
+            if not self.__verify_pt_data_dividend(pt):
+                self.__debug("Failed to verify pt data")
+                self.__default_msg['errorCode'] ="1001"
+                self.__default_msg['errorMsg'] = "Failed to verify pts data."
+                self.__default_msg['rebs']= []
+                break
+            else :
+                res = self._dividend(pt)
+
+                self.__default_msg['dividends'].append({"pt_id":pt["pt_id"],  "redeem":res }) 
+                #self.__default_msg['rebs'].append({"pt_id":pt["pt_id"], "rp_id": self._rebalance(pt)}) 
+
+        return self.__default_msg
+

vender/sample_quant_api.py

+from vender.quant_api_base import base_Quant_api
+import json
+
+
+class Quant_api(base_Quant_api):
+
+
+    def _rebalance(self, pt):
+        # 此為範例
+
+        # print out pt data
+        print("------------ 此為 客戶portfolio ---------")
+        print(json.dumps(pt, indent=2))
+
+        print("------------ 此為 最新的投組推薦 ---------")
+        model_portfolio = self.get_latest_portfolio(pt['recomm_id'])
+        print(json.dumps(model_portfolio, indent=2))
+
+        print("------------ 利用 rp_id 舊的投組推薦 ---------")
+        print("rp_id = %s" % pt['rp_id'])
+        model_portfolio2 = self.get_portfolio_by_rpid(pt['rp_id'])
+        print(json.dumps(model_portfolio2, indent=2))
+        if model_portfolio2['note'] != "":
+            try:
+                print("note JSON Object:")
+                print(json.dumps(json.loads(model_portfolio2['note']), indent=2))
+            except:
+                None
+
+        print("------------ 此為基金的分類（非必要）-------")
+        for fund in model_portfolio['fws']:
+            fund_id = fund['fund_id']
+            fundclass = self.get_fund_asset_class(fund_id)
+            print(fund_id + ": " ,fundclass)
+        print("------------ 基金的分類（end）-------")
+
+        ## ------- 返回結果 -------
+        # 返回 model_portfolio 的 rp_id 表示需要 rebalance
+        # 若是不需要 rebalance 返回 0
+        return (model_portfolio['rp_id'], "判斷的理由")
+
+
+    def _dividend(self, pt):
+        # 此為範例
+
+        # print out pt data
+        print("****  dividend Called **** ")
+
+        print("--- 此為 客戶portfolio (input data)---")
+        print(json.dumps(pt, indent=2))
+
+        '''
+        Your core here...
+        
+        注意事項:
+        因為排程是每日執行，若是要每月只執行一次，請以last_check_date判斷。
+        為方便測試，若需取今日日期，請使用 warp function self.now()  
+        '''
+        print (f"--- 假設今日日期 :  {self.now()} " )
+
+        ## ------- 返回結果 For example-------
+        '''
+        返回一個 list 
+        每個 element 只少包含 fund_id, share,
+        允許包含有其他自訂欄位
+        '''
+        print("--- 此為 回傳結果 ---")
+        asset = pt['asset']
+        return ( 
+            {"fund_id" : f"{asset[0]['fund_id']}", "share" : f"{asset[0]['share']}" },  
+            {"fund_id" : f"{asset[1]['fund_id']}", "share" : f"{asset[1]['share']}" },  
+        )