feat: update macd data

models/macd.py

@@ -0,0 +1,5 @@
+from pydantic import BaseModel
+
+
+class MACDPayload(BaseModel):
+    symbol: str

routes/data.py

@@ -2,6 +2,7 @@ from services.indicator import Indicator
 from models.ichimoku import IchimokuPayload
 from models.rsi import RSIPayload
 from models.price import PricePayload
+from models.macd import MACDPayload
 from fastapi import status, APIRouter
 from typing import Sequence
 import json
@@ -45,6 +46,15 @@ async def update_entire_rsi():
     Indicator.update_entire_rsi()
 
 
+@router.get(
+    "/update_entire_macd",
+    name="Update entire macd data",
+    status_code=status.HTTP_200_OK
+)
+async def update_entire_macd():
+    Indicator.update_entire_macd()
+
+
 @router.post(
     "/get_price",
     name="Get price",
@@ -74,6 +84,20 @@ async def get_rsi_data(payload: RSIPayload) -> Sequence[dict]:
     return json.loads(rsi_df.to_json(orient="records"))
 
 
+@router.post(
+    "/get_macd",
+    name="Get data of MACD",
+    status_code=status.HTTP_200_OK
+)
+async def get_macd_data(payload: MACDPayload) -> Sequence[dict]:
+    macd_df = Indicator.get_macd(
+        payload.symbol
+    )
+    if macd_df is None:
+        return [{"message": "Error"}]
+    return json.loads(macd_df.to_json(orient="records"))
+
+
 @router.post(
     "/get_ichimoku",
     name="Get data of Ichimoku cloud",

services/indicator.py

@@ -105,6 +105,7 @@ class Indicator:
             for value in data:
                 lst_symbols.append(value["cell"][2].strip())
             if weekday < 5 and hour < 12:
+                updating_price = False
                 return
             end_date = datetime_now.date()
             delta = timedelta(days=300)
@@ -114,6 +115,7 @@ class Indicator:
             lst_time = []
             lst_values = []
             if len(lst_symbols) != 100:
+                updating_price = False
                 return
             for symbol in lst_symbols:
                 df = longterm_ohlc_data(symbol,
@@ -201,6 +203,7 @@ class Indicator:
                                             "D",
                                             "stock").reset_index(drop=True)
                 if tmp_df.shape[0] == 0:
+                    updating_rsi = False
                     return
                 last_date = str(tmp_df["time"])
                 newest_record = \
@@ -237,10 +240,12 @@ class Indicator:
             for value in data:
                 lst_symbols.append(value["cell"][2].strip())
             if weekday < 5 and hour < 12:
+                updating_rsi = False
                 return
             get_time = True
             lst_values = {}
             if len(lst_symbols) != 100:
+                updating_rsi = False
                 return
             cnt = 0
             for symbol in lst_symbols:
@@ -317,6 +322,79 @@ class Indicator:
     def stoch_rsi_smooth_d(stoch_rsi_k: pd.Series, d: int) -> pd.Series:
         return stoch_rsi_k.rolling(window=d).mean()
 
+    @staticmethod
+    def update_entire_macd() -> None:
+        global updating_macd
+        if updating_macd:
+            return
+        updating_macd = True
+        datetime_now = datetime.utcnow()
+        hour = datetime_now.hour
+        weekday = datetime_now.weekday()
+        try:
+            data = requests.get(VN100_URL).json()
+            data = data["rows"]
+            lst_symbols = []
+            for value in data:
+                lst_symbols.append(value["cell"][2].strip())
+            if weekday < 5 and hour < 12:
+                updating_macd = False
+                return
+            get_time = True
+            lst_values = {}
+            if len(lst_symbols) != 100:
+                updating_macd = False
+                return
+            cnt = 0
+            for symbol in lst_symbols:
+                cnt += 1
+                url = PREFIX + INDICATORS["MACD"] \
+                    + f"?stockSymbol={symbol}&rangeSelector=3&fastPeriod=12&slowPeriod=26&signalPeriod=9"
+                data = requests.get(url).json()
+                rsi_df = pd.DataFrame(
+                    data["SeriesColection"][0]["Points"]).tail(5)
+                if get_time:
+                    lst_values["time"] = \
+                        rsi_df["Time"].apply(lambda x:
+                                             Utility.ts_to_date(x/1000))
+                    get_time = False
+                lst_values[symbol] = rsi_df["Value"].apply(lambda x: int(x[0]))
+            df = pd.DataFrame(lst_values)
+            records = df.to_dict(orient="records")
+            uri = os.environ.get("MONGODB_URI")
+            client = MongoClient(uri)
+            database = client.get_database("data")
+            collection = database.get_collection("macd")
+            if "macd" in database.list_collection_names():
+                collection.drop()
+            collection.insert_many(records)
+            print("Updated entire MACD")
+            updating_macd = False
+        except Exception as e:
+            print(f"Error: {e}")
+            updating_macd = False
+
+    @staticmethod
+    def get_macd(
+        symbol: str,
+    ) -> pd.DataFrame:
+        try:
+            symbol = symbol.upper()
+            uri = os.environ.get("MONGODB_URI")
+            client = MongoClient(uri)
+            database = client.get_database("data")
+            collection = database.get_collection("macd")
+            try:
+                records = list(collection.find())
+            except Exception as e:
+                print(f"Error: {e}")
+            record_df = pd.DataFrame(records).drop(columns=["_id"])
+            record_df = \
+                record_df[["time", symbol]].rename(columns={symbol: "macd"})
+            return record_df
+        except Exception:
+            return None
+
     @staticmethod
     def get_ichimoku_cloud(
         df: pd.DataFrame,