Update main.py

main.py

@@ -2,253 +2,8 @@ from fastapi.responses import HTMLResponse
 from fastapi.templating import Jinja2Templates
 from fastapi import FastAPI, Request, HTTPException
 from fastapi.middleware.cors import CORSMiddleware
+from pycatchs import eqt
 import warnings
-import yfinance as yf
-import pandas as pd
-import requests
-
-warnings.simplefilter(action='ignore', category=FutureWarning)
-warnings.filterwarnings('ignore')
-
-df_logo = pd.read_csv("https://raw.githubusercontent.com/jarvisx17/nifty500/main/Nifty500.csv")
-
-async def calculate_profit(ltp, share, entry):
-  tgt1 = entry + (0.02 * entry)
-  tgt2 = entry + (0.04 * entry)
-  if ltp > tgt2:
-      profit = round((share / 3 * (tgt1-entry)) + (share / 3 * (tgt2-entry)) + (share / 3 * (ltp-entry)), 2)
-  elif ltp > tgt1 and ltp < tgt2:
-      profit = round((share / 3 * (tgt1-entry)) + ((share / 3) * 2 * (ltp-entry)), 2)
-  elif ltp > tgt1:
-      profit = round(share * (ltp-entry), 2)   
-  else:
-      profit = round(share * (ltp-entry), 2)
-  return profit
-
-async def info(ticker):
-    data = df_logo[df_logo['Symbol'] == ticker]
-    logo = data.logo.values[0]
-    Industry = data.Industry.values[0]
-    return logo, Industry
-
-async def calculate_percentage_loss(buying_price, ltp):
-    percentage_loss = ((ltp - buying_price) / buying_price) * 100
-    return f"{percentage_loss:.2f}%"
-
-async def latestprice(ticker):
-    ticker = ticker.split(".")[0]
-    url = f"https://stock-market-lo24myw5sq-el.a.run.app/currentprice?ticker={ticker}"
-    response = requests.get(url)
-    if response.status_code == 200:
-        data = response.json()
-        return data['ltp']
-    else:
-        return "N/A"
-
-async def process_dataframe(df):
-
-    def get_rsi(close, lookback):
-        ret = close.diff()
-        up = []
-        down = []
-        for i in range(len(ret)):
-            if ret[i] < 0:
-                up.append(0)
-                down.append(ret[i])
-            else:
-                up.append(ret[i])
-                down.append(0)
-        up_series = pd.Series(up)
-        down_series = pd.Series(down).abs()
-        up_ewm = up_series.ewm(com=lookback - 1, adjust=False).mean()
-        down_ewm = down_series.ewm(com=lookback - 1, adjust=False).mean()
-        rs = up_ewm / down_ewm
-        rsi = 100 - (100 / (1 + rs))
-        rsi_df = pd.DataFrame(rsi).rename(columns={0: 'RSI'}).set_index(close.index)
-        rsi_df = rsi_df.dropna()
-        return rsi_df[3:]
-
-    df['RSI'] = get_rsi(df['Close'], 14)
-    df['SMA20'] = df['Close'].rolling(window=20).mean()
-    df.drop(['Adj Close'], axis=1, inplace=True)
-    df = df.dropna()
-
-    return df
-
-async def fin_data(ticker, startdate):
-
-  ltp = await latestprice(ticker)
-  df=yf.download(ticker, period="36mo", progress=False)
-  df = await process_dataframe(df)
-  df.reset_index(inplace=True)
-  df['Prev_RSI'] = df['RSI'].shift(1).round(2)
-  df = df.dropna()
-  df.reset_index(drop=True, inplace=True)
-  df[['Open', 'High', 'Low', 'Close',"RSI","SMA20"]] = df[['Open', 'High', 'Low', 'Close',"RSI", "SMA20"]].round(2)
-  df = df[200:]
-  df['Target1'] = df['High'] + (df['High'] * 0.02)
-  df['Target1'] = df['Target1'].round(2)
-  df['Target2'] = df['High'] + (df['High'] * 0.04)
-  df['Target2'] = df['Target2'].round(2)
-  df['Target3'] = "will announced"
-  df['SL'] = df['Low']
-  df['LTP'] = ltp
-  date_index = df.loc[df['Date'] == startdate].index[0]
-  df = df.loc[date_index-1:]
-  df['Date'] = pd.to_datetime(df['Date'])
-  df.reset_index(drop=True,inplace=True)
-
-  return df
-
-async def eqt(ticker, startdate, share_qty = 90):
-
-  df = await fin_data(ticker, startdate)
-  logo, Industry = await info(ticker)
-  entry = False
-  trading = False
-  shares_held = 0
-  buy_price = 0
-  target1 = False
-  target2 = False
-  target3 = False
-  tgt1 = 0
-  tgt2 = 0
-  tgt3 = 0
-  total_profit = 0
-  profits = []
-  stop_loss = 0
-  capital_list = []
-  data = {}
-  totalshares = share_qty
-  ltp = await latestprice(ticker)
-
-  for i in range(1, len(df)-1):
-      try:
-          if df.at[i, 'RSI'] > 60 and df.at[i - 1, 'RSI'] < 60 and df.at[i, 'High'] < df.at[i + 1, 'High'] and not entry and not trading:
-              buy_price = df.at[i, 'High']
-              stop_loss = df.at[i, 'Low']
-              capital = buy_price * share_qty
-              capital_list.append(capital)
-              shares_held = share_qty
-              entdate = df.at[i+1, 'Date']
-              entry_info = {"Date": pd.to_datetime(df.at[i+1, 'Date']).strftime('%d-%m-%Y'), "Note": "Entry Successful", "SL": stop_loss}
-              entryStock_info = df.iloc[i: i+1].reset_index(drop=True).to_dict(orient='records')[0] # Entry info
-              entryStock_info['Date'] = str(pd.to_datetime(df.at[i, 'Date']).strftime('%d-%m-%Y'))
-              data['StockInfo'] = {}
-              data['StockInfo']['Stock'] = {}
-              data['StockInfo']['Stock']['Name'] = ticker
-              data['StockInfo']['Stock']['Industry'] = Industry
-              data['StockInfo']['Stock']['Logo'] = logo
-              data['StockInfo']['Stock']['Status'] = "Active"
-              data['StockInfo']['Stock']['Levels'] = "Entry"
-              data['StockInfo']['Stock']['Values'] = entryStock_info
-              buying_price = entryStock_info['High']
-              ltp = entryStock_info['LTP']
-              data['StockInfo']['Stock']['Values']['Share QTY'] = share_qty
-              data['StockInfo']['Stock']['Values']['Invested Amount'] = (share_qty * buy_price).round(2)
-              data['StockInfo']['Stock']['Values']['Percentage'] = await calculate_percentage_loss(buying_price, ltp)
-              data['StockInfo']['Stock']['Values']['Total P/L'] = await calculate_profit(ltp, totalshares, buy_price)
-              data['StockInfo']['Entry'] = entry_info
-              entry = True
-              trading = True
-
-          if trading and not target1:
-              if (df.at[i + 1, 'High'] - buy_price) >= 0.02 * buy_price:
-                  stop_loss = buy_price
-                  target1 = True
-                  tgt1 = 0.02 * buy_price * (share_qty / 3)
-                  shares_held -= (share_qty / 3)
-                  total_profit = round(tgt1,2)
-                  target1_info = {"Date" : pd.to_datetime(df.at[i+1, 'Date']).strftime('%d-%m-%Y'), "Profit" : round(tgt1,2), "Remaining Shares": shares_held,"Note" : "TGT1 Achieved Successfully", "SL" : stop_loss}
-                  data['StockInfo']['TGT1'] = target1_info
-                  data['StockInfo']['Stock']['Values']['SL'] = stop_loss
-                  data['StockInfo']['Stock']['Levels'] = data['StockInfo']['Stock']['Levels'] + " TGT1"
-                  data['StockInfo']['Stock']['Values']['Total P/L'] = await calculate_profit(ltp, totalshares, buy_price)
-                  data['StockInfo']['Entry']['Trade Status'] = "Trading is ongoing...."
-
-          if trading and target1 and not target2:
-              if (df.at[i + 1, 'High'] - buy_price) >= 0.04 * buy_price:
-                  target2 = True
-                  tgt2 = 0.04 * buy_price * (share_qty / 3)
-                  total_profit += round(tgt2,2)
-                  shares_held -= (share_qty / 3)
-                  data['StockInfo']['Stock']['Levels'] = data['StockInfo']['Stock']['Levels'] + " TGT2"
-                  data['StockInfo']['Stock']['Values']['Total P/L'] = await calculate_profit(ltp, totalshares, buy_price)
-                  target2_info = {"Date" : pd.to_datetime(df.at[i+1, 'Date']).strftime('%d-%m-%Y'), "Profit" : round(tgt2,2), "Remaining Shares": shares_held,"Note" : "TGT2 Achieved Successfully", "SL" : stop_loss}
-                  data['StockInfo']['TGT2'] = target2_info
-                  data['StockInfo']['Entry']['Trade Status']  = "Trading is ongoing...."
-
-          if trading and target2 and not target3:
-              if (df.at[i + 1, 'Open'] < df.at[i + 1, 'SMA20'] < df.at[i + 1, 'Close']) or (df.at[i + 1, 'Open'] > df.at[i + 1, 'SMA20'] > df.at[i + 1, 'Close']):
-                  stop_loss = df.at[i + 1, 'Low']
-                  data['StockInfo']['Stock']['Values']['SL'] = stop_loss
-                  if df.at[i + 2, 'Low'] < stop_loss:
-                      target3 = True
-                      tgt3 = stop_loss * (share_qty / 3)
-                      shares_held -= (share_qty / 3)
-                      total_profit += round(tgt3,2)
-                      target3_info = {"Date" : pd.to_datetime(df.at[i+1, 'Date']).strftime('%d-%m-%Y'), "Profit" : round(tgt3,2), "Remaining Shares": shares_held,"Note" : "TGT3 Achieved Successfully", "SL" : stop_loss}
-                      data['StockInfo']['Stock']['Values']['Target3'] = tgt3
-                      data['StockInfo']['TGT3'] = target3_info
-                      data['StockInfo']['Stock']['Levels'] = data['StockInfo']['Stock']['Levels'] +" TGT3"
-                      data['StockInfo']['Stock']['Values']['Total P/L'] = await calculate_profit(ltp, totalshares, buy_price)
-                      data['StockInfo']['TotalProfit'] = {}
-                      data['StockInfo']['TotalProfit']['Profit'] = total_profit
-                      data['StockInfo']['Entry']['Trade Status']  = "Trade closed successfully...."
-                      data['StockInfo']['TotalProfit']['Trade Status']  = "Trade closed successfully...."
-                      break
-
-          if (df.at[i + 1, 'Low'] < stop_loss and trading and entdate != df.at[i + 1, 'Date']) or stop_loss > ltp:
-              profit_loss = (shares_held * stop_loss) - (shares_held * buy_price)
-              total_profit += profit_loss
-              profits.append(total_profit)
-              shares_held = 0
-              if data['StockInfo']['Stock']['Values']['Target3'] == "will announced" :
-                data['StockInfo']['Stock']['Values']['Target3'] = "-"
-              data['StockInfo']['Stock']['Status'] = "Closed"
-              data['StockInfo']['Stock']['Levels'] = data['StockInfo']['Stock']['Levels'] +" SL"
-              stoploss_info = {"Date" : pd.to_datetime(df.at[i+1, 'Date']).strftime('%d-%m-%Y'), "Profit" : total_profit, "SL" : stop_loss, "Remaining Shares": shares_held,"Note" : "SL Hit Successfully"}
-              data['StockInfo']['SL'] = stoploss_info
-              data['StockInfo']['TotalProfit'] = {}
-              data['StockInfo']['TotalProfit']['Profit'] = round(total_profit, 2)
-              data['StockInfo']['Stock']['Values']['Total P/L'] = round(total_profit, 2)
-              data['StockInfo']['Entry']['Trade Status']  = "Trade closed successfully...."
-              data['StockInfo']['TotalProfit']['Trade Status']  = "Trade closed successfully...."
-              buy_price = 0
-              entry = False
-              trading = False
-              target1 = target2 = target3 = False
-              tgt1 = tgt2 = tgt3 = 0
-              total_profit = 0
-              break
-
-      except IndexError:
-          continue
-
-  if capital_list and profits:
-
-    return data
-
-  else:
-    if data:
-
-      return data
-
-    else:
-      data['StockInfo'] = {}
-      data['StockInfo']['Stock'] = {}
-      data['StockInfo']['Stock']['Name']  = ticker
-      data['StockInfo']['Stock']['Industry'] = Industry
-      data['StockInfo']['Stock']['Logo'] = logo
-      data['StockInfo']['Stock']['Status'] = "Waiting for entry"
-      entryStock_info = df.iloc[1: 2].reset_index(drop=True).to_dict(orient='records')[0] # Entry info
-      entryStock_info['Date'] = str(pd.to_datetime(df.at[1, 'Date']).strftime('%d-%m-%Y'))
-      data['StockInfo']['Stock']['Values'] = entryStock_info
-      data['StockInfo']['Stock']['Values']['Target3'] = "-"
-      data['StockInfo']['Info'] = "Don't buy stock right now...."
-
-      return data
-
 
 app = FastAPI()
 
@@ -262,10 +17,6 @@ app.add_middleware(
     allow_headers=["*"],
 )
 
-# @app.get('/')
-# def index():
-#     return {"message": "welcome to Investify"}
-
 templates = Jinja2Templates(directory="templates")
 
 @app.get("/", response_class=HTMLResponse)