init

hts/OrderChecker.py

@@ -6,107 +6,42 @@ from hts.OrderType import OrderType
 
 class OrderChecker:
 
-    saveFileName = None
+    RESOURCE_PATH = None
+    order_df = None
 
-    def __init__(self, RESOURCE_PATH, stock_code):
-        self.saveFileName = os.path.join(RESOURCE_PATH, "order", stock_code + "_" + datetime.today().strftime("%Y%m%d") + ".csv")
+    def __init__(self, RESOURCE_PATH):
+        self.RESOURCE_PATH = RESOURCE_PATH
+        self.order_df = None
         return
 
-    def read(self):
-        if os.path.isfile(self.saveFileName):
-            order_df = pd.read_csv(self.saveFileName)
+    def read(self, ymd):
+        saveFileName = os.path.join(self.RESOURCE_PATH, "order", ymd + ".csv")
+
+        if os.path.isfile(saveFileName):
+            self.order_df = pd.read_csv(saveFileName)
         else:
-            order_df = pd.DataFrame(columns=["stock_code", "type", "orderNum", "count", "price", "datetime"])
+            self.order_df = pd.DataFrame(columns=["datetime", "stock_code", "type", "orderNum", "count", "price"])
 
-        if 'Unnamed: 0' in order_df.columns:
-            order_df.drop(['Unnamed: 0'], axis=1, inplace=True)
-        order_df = order_df.fillna(0)
-        order_df = order_df.astype({"stock_code": str, "type": str, "orderNum": int, "count": int, "price": int})
-        order_df['datetime'] = pd.to_datetime(order_df['datetime'])
-        return order_df
+        if 'Unnamed: 0' in self.order_df.columns:
+            self.order_df.drop(['Unnamed: 0'], axis=1, inplace=True)
+        self.order_df = self.order_df.fillna(0)
+        self.order_df = self.order_df.astype({"stock_code": str, "type": str, "orderNum": int, "count": int, "price": int})
+        self.order_df['datetime'] = pd.to_datetime(self.order_df['datetime'])
+        return
 
-    def add(self, stock_code, type, orderNum, count, price, orderList):
-        orderListToCancel = []
-        # 매수 요청인 경우만 두 시간 전 주문을 찾아서 제외한다.
+    def exist(self, stock_code):
+        if self.order_df.loc[self.order_df["stock_code"] == stock_code] is None:
+            return False
+        return True
 
-        order_df = self.read()
+    def add(self, ymd, stock_code, type, orderNum, count, price):
+        if self.exist(stock_code):
+            return False
+        # 새로운 주문을 추가한다.
+        self.order_df = self.order_df.append({"stock_code": stock_code, "type": type, "orderNum": orderNum, "count": count, "price": price, "datetime": datetime.now()}, ignore_index=True)
 
-        # 두 시간 전 주문을 찾는다.
-        if orderList is not None and len(orderList) > 0:
-            # 1) 종목 코드를 찾는다.
-            stock_df = order_df.loc[order_df["stock_code"] == stock_code]
+        # 파일로 기록한다.
+        saveFileName = os.path.join(self.RESOURCE_PATH, "order", ymd + ".csv")
+        self.order_df.to_csv(saveFileName)
 
-            # 2) 5분 전 계산
-            before_two_hour = datetime.now() - timedelta(minutes=5)
-
-            # 3) 만약 5분 전 주문을 찾는다.
-            stock_twohour_df = stock_df.loc[stock_df["datetime"] <= before_two_hour]
-
-            # 4) 5분 전 주문 중에서 매수 데이터만 찾는다.
-            orderNum_df = stock_twohour_df.loc[stock_twohour_df["type"] == OrderType.buy.value]
-
-            # 5) 5분 전 매수 항목을 별도로 추출한다.
-            orderNumSet = set(list(orderNum_df["orderNum"]))
-            for item in orderList:
-                if item.orderNum in orderNumSet:
-                    orderListToCancel.append(item)
-
-                    # 6) 추출된 항목을 제외시킨다.
-                    order_df = order_df.loc[order_df["orderNum"] != item.orderNum]
-
-        # 7) 새로운 주문을 추가한다.
-        order_df = order_df.append({"stock_code": stock_code, "type": type.value, "orderNum": orderNum, "count": count, "price": price, "datetime": datetime.now()}, ignore_index=True)
-
-        # 8) 파일로 기록한다.
-        order_df.to_csv(self.saveFileName)
-
-        return orderListToCancel
-
-    def remove(self, stock_code, type, orderList):
-        order_df = self.read()
-        orderListToCancel = []
-
-        if orderList is not None and len(orderList) > 0:
-            # 1) 종목 코드를 찾는다.
-            stock_df = order_df.loc[order_df["stock_code"] == stock_code]
-
-            # 2) 매도 주문을 찾는다.
-            orderNum_df = stock_df.loc[stock_df["type"] == type.value]
-
-            # 3) 매도 주문 중에서 항목을 별도로 추출한다.
-            orderNumSet = set(list(orderNum_df["orderNum"]))
-            for item in orderList:
-                if item.orderNum in orderNumSet:
-                    orderListToCancel.append(item)
-
-                    # 4) 해당 orderNum 제외하기
-                    order_df = order_df.loc[order_df["orderNum"] != item.orderNum]
-            order_df.to_csv(self.saveFileName)
-
-        return orderListToCancel
-
-if __name__ == "__main__":
-    a = pd.DataFrame(columns=["type", "orderNum", "count", "price", "datetime"])
-    a = a.astype({"type": str, "orderNum": int, "count": int, "price": int})
-    a['datetime'] = pd.to_datetime(a['datetime'])
-
-    this_time = datetime.now()
-    a = a.append({"stock_code": "a", "type": "0", "orderNum": 1, "count": 3, "price": 7, "datetime": this_time}, ignore_index=True)
-    a = a.append({"stock_code": "a", "type": "1", "orderNum": 3, "count": 0, "price": 6, "datetime": this_time - timedelta(hours=2)}, ignore_index=True)
-    a = a.append({"stock_code": "a", "type": "2", "orderNum": 3, "count": 0, "price": 3, "datetime": this_time + timedelta(hours=1)}, ignore_index=True)
-    a = a.append({"stock_code": "a", "type": "1", "orderNum": 9, "count": 9, "price": 8, "datetime": this_time}, ignore_index=True)
-
-    b = a.loc[a["orderNum"] != 3]
-    print(b.tail())
-    print()
-
-    b = a.loc[a["datetime"] < this_time]
-    print(b.tail())
-
-    a.to_csv("test.csv")
-    a = pd.read_csv("test.csv")
-    a.drop(['Unnamed: 0'], axis=1, inplace=True)
-    a = a.astype({"stock_code": str, "type": str, "orderNum": int, "count": int, "price": int})
-    a['datetime'] = pd.to_datetime(a['datetime'])
-
-    print("done")
+        return True