Update daily.py

daily.py

@@ -6,110 +6,6 @@ import requests
 from datetime import datetime, timedelta
 from ta_indi_pat import talib_df  # use the combined talib_df function
 from common import html_card, wrap_html
-
-# -----------------------------
-# Global Variables
-# -----------------------------
-nse_del_key_map = {
-    'Symbol': "Symbol", 'Series': "Series",
-    'Date': 'Date', 'Prev Close': 'Preclose',
-    'Open Price': 'Open', 'High Price': 'High',
-    'Low Price': 'Low', 'Last Price': 'Last',
-    'Close Price': 'Close', 'Average Price': 'AvgPrice',
-    'Total Traded Quantity': 'Volume',
-    'Turnover ₹': 'Turnover', 'No. of Trades': "Trades",
-    'Deliverable Qty': "Delivery", '% Dly Qt to Traded Qty': "Del%"
-}
-
-# -----------------------------
-# Data Fetching Functions (NSE)
-# -----------------------------
-def url_nse_del(symbol, start_date, end_date):
-    base_url = "https://www.nseindia.com/api/historicalOR/generateSecurityWiseHistoricalData"
-    start_date_str = start_date.strftime("%d-%m-%Y")
-    end_date_str = end_date.strftime("%d-%m-%Y")
-    url = f"{base_url}?from={start_date_str}&to={end_date_str}&symbol={symbol.split('.')[0]}&type=priceVolumeDeliverable&series=ALL&csv=true"
-    return url
-
-def to_numeric_safe(series):
-    series = series.replace('-', 0)
-    series = series.fillna(0)
-    series = series.astype(str).str.replace(',', '')
-    return pd.to_numeric(series, errors='coerce').fillna(0)
-
-
-def nse_del(symbol, start_date_str=None, end_date_str=None):
-    # Default end date is today
-    end_date = datetime.now()
-    if end_date_str:
-        try:
-            end_date = datetime.strptime(end_date_str, "%Y-%m-%d")
-        except ValueError:
-            print(f"Warning: Invalid end date format '{end_date_str}'. Using today's date.")
-            end_date = datetime.now()
-
-    # Default start date is one year prior to end_date
-    start_date = end_date - timedelta(days=365)
-    if start_date_str:
-        try:
-            start_date = datetime.strptime(start_date_str, "%Y-%m-%d")
-        except ValueError:
-            print(f"Warning: Invalid start date format '{start_date_str}'. Using default start date.")
-            start_date = end_date - timedelta(days=365)
-
-    # Ensure start_date is not after end_date
-    if start_date > end_date:
-        print("Warning: Start date is after end date. Swapping dates.")
-        start_date, end_date = end_date, start_date
-
-    url = url_nse_del(symbol, start_date, end_date)
-    headers = {
-        'User-Agent': 'Mozilla/5.0'
-    }
-    try:
-        response = requests.get(url, headers=headers)
-        response.raise_for_status()
-        if response.content:
-            df = pd.read_csv(io.StringIO(response.content.decode('utf-8'))).round(2)
-            df.columns = df.columns.str.strip()
-            df.rename(columns=nse_del_key_map, inplace=True)
-
-            # Capitalize the first letter of ALL column names after renaming
-            df.columns = [col.capitalize() for col in df.columns]
-
-            # Remove 'Symbol', 'Series', 'Avgprice', and 'Last' columns (now capitalized)
-            df.drop(columns=['Symbol','Series','Avgprice','Last'], errors='ignore', inplace=True)
-
-            # Convert 'Date' column to datetime objects
-            df['Date'] = pd.to_datetime(df['Date'], format='%d-%b-%Y').dt.strftime('%Y-%m-%d')
-
-            numeric_cols = ['Close', 'Preclose', 'Open', 'High', 'Low', 'Volume', 'Delivery', 'Turnover', 'Trades']
-            # Ensure numeric_cols are capitalized before checking and conversion
-            numeric_cols_capitalized = [col.capitalize() for col in numeric_cols]
-            for col in numeric_cols_capitalized:
-                if col in df.columns:
-                    df[col] = to_numeric_safe(df[col])
-                else:
-                    df[col] = 0
-            return df
-    except Exception as e:
-        print(f"Error fetching data from NSE for {symbol}: {e}")
-    return None
-
-def daily(symbol,source="yfinace"):
-    if source=="yfinance":
-        df = yf.download(symbol + ".NS", period="1y", interval="1d").round(2)
-        if df.empty:
-            return html_card("Error", f"No daily data found for {symbol}")
-
-        # --- Standardize columns ---
-        df.columns = ["Close", "High", "Low", "Open", "Volume"]
-        df.reset_index(inplace=True)  # make Date a column
-    
-    if source=="NSE":
-        df=nse_del(symbol)
-        print("df from nse data")
-    return df
 def fetch_daily(symbol, source,max_rows=200):
     """
     Fetch daily OHLCV data, calculate TA-Lib indicators + patterns,