Update app/daily.py

app/daily.py

@@ -2,16 +2,13 @@
 import yfinance as yf
 import pandas as pd
 from datetime import datetime as dt
-from plotly import graph_objs as go
-from plotly.subplots import make_subplots
 import traceback
 
 from . import persist
-from . import backblaze as b2
-from .common import wrap_html, format_large_number
+from .common import wrap_html
 
 # ===========================================================
-# RAW DAILY FETCHER (from your stock.py)
+# RAW DAILY FETCHER
 # ===========================================================
 def daily(symbol, date_end, date_start):
     """Fetch daily OHLCV from Yahoo Finance."""
@@ -20,7 +17,7 @@ def daily(symbol, date_end, date_start):
     start = dt.strptime(date_start, "%d-%m-%Y").strftime("%Y-%m-%d")
     end = dt.strptime(date_end, "%d-%m-%Y").strftime("%Y-%m-%d")
     
-    df = yf.download(symbol + ".NS", start=start, end=end).round(2)
+    df = yf.download(symbol + ".NS", start=start, end=end)
     
     # Flatten MultiIndex columns if present
     if isinstance(df.columns, pd.MultiIndex):
@@ -29,9 +26,9 @@ def daily(symbol, date_end, date_start):
     return df
 
 # ===========================================================
-# DASHBOARD BUILDER
+# FETCH DAILY HTML TABLE
 # ===========================================================
-def fetch_daily(symbol, date_end, date_start, b2_save=False):
+def fetch_daily(symbol, date_end, date_start):
     key = f"daily_{symbol}"
     if persist.exists(key, "html"):
         cached = persist.load(key, "html")
@@ -48,7 +45,7 @@ def fetch_daily(symbol, date_end, date_start, b2_save=False):
         if not isinstance(df.index, pd.RangeIndex):
             df.reset_index(inplace=True)
 
-        # Convert OHLCV to numeric safely
+        # Convert numeric columns safely
         numeric_cols = ["Open","High","Low","Close","Adj Close","Volume"]
         for col in numeric_cols:
             if col in df.columns:
@@ -62,72 +59,12 @@ def fetch_daily(symbol, date_end, date_start, b2_save=False):
         df = df.dropna(subset=["Date"]).reset_index(drop=True)
         df["Date"] = df["Date"].dt.strftime("%d-%b-%Y")
 
-        if b2_save:
-            b2.upload_file("eshanhf", f"daily/{symbol}.csv", df)
+        # Build HTML table
+        html_table = f'<div id="daily_table"><h2>{symbol} Daily Data</h2>{df.to_html(index=False, escape=False)}</div>'
 
-        # Indicators
-        df["Daily Return %"] = df["Close"].pct_change()*100
-        df["SMA20"] = df["Close"].rolling(20).mean()
-        df["SMA50"] = df["Close"].rolling(50).mean()
-        df["EMA20"] = df["Close"].ewm(span=20, adjust=False).mean()
-        df["EMA50"] = df["Close"].ewm(span=50, adjust=False).mean()
-        df["UpperBB"] = df["Close"].rolling(20).mean() + 2*df["Close"].rolling(20).std()
-        df["LowerBB"] = df["Close"].rolling(20).mean() - 2*df["Close"].rolling(20).std()
-        df["ATR"] = df["High"].combine(df["Low"], lambda h,l: h-l).rolling(14).mean()
-
-        # Summary stats
-        summary = pd.DataFrame({
-            "Metric": ["Start Date","End Date","Min Price","Max Price","Mean Price","Total Volume","Avg Daily Return %","Volatility ATR"],
-            "Value": [
-                df["Date"].iloc[0],
-                df["Date"].iloc[-1],
-                format_large_number(df["Close"].min()),
-                format_large_number(df["Close"].max()),
-                format_large_number(df["Close"].mean()),
-                format_large_number(df["Volume"].sum()),
-                f"{df['Daily Return %'].mean():.2f}%",
-                f"{df['ATR'].mean():.2f}"
-            ]
-        })
-
-        # Plotly dashboard
-        fig = make_subplots(rows=4, cols=1, shared_xaxes=True,
-                            vertical_spacing=0.05,
-                            row_heights=[0.4,0.2,0.2,0.2],
-                            specs=[[{}],[{}],[{}],[{}]])
-
-        # Candlestick + moving averages + Bollinger
-        fig.add_trace(go.Candlestick(x=df["Date"], open=df["Open"], high=df["High"], low=df["Low"], close=df["Close"], name="OHLC"), row=1, col=1)
-        fig.add_trace(go.Scatter(x=df["Date"], y=df["SMA20"], mode="lines", name="SMA20"), row=1, col=1)
-        fig.add_trace(go.Scatter(x=df["Date"], y=df["SMA50"], mode="lines", name="SMA50"), row=1, col=1)
-        fig.add_trace(go.Scatter(x=df["Date"], y=df["EMA20"], mode="lines", name="EMA20"), row=1, col=1)
-        fig.add_trace(go.Scatter(x=df["Date"], y=df["EMA50"], mode="lines", name="EMA50"), row=1, col=1)
-        fig.add_trace(go.Scatter(x=df["Date"], y=df["UpperBB"], mode="lines", name="UpperBB", line=dict(dash="dot")), row=1, col=1)
-        fig.add_trace(go.Scatter(x=df["Date"], y=df["LowerBB"], mode="lines", name="LowerBB", line=dict(dash="dot")), row=1, col=1)
-
-        # Volume
-        fig.add_trace(go.Bar(x=df["Date"], y=df["Volume"], name="Volume"), row=2, col=1)
-        # Daily Return %
-        fig.add_trace(go.Scatter(x=df["Date"], y=df["Daily Return %"], mode="lines+markers", name="Daily Return %"), row=3, col=1)
-        # ATR
-        fig.add_trace(go.Scatter(x=df["Date"], y=df["ATR"], mode="lines", name="ATR"), row=4, col=1)
-
-        fig.update_layout(height=1000, width=1200, title=f"{symbol} Daily Analysis Dashboard", xaxis_rangeslider_visible=False)
-
-        chart_html = ""
-        try:
-            chart_html = f'<div id="chart_dashboard">{fig.to_html(full_html=False, include_plotlyjs="cdn")}</div>'
-        except Exception as e:
-            chart_html = f'<div id="chart_dashboard"><h2>Chart generation failed: {e}</h2></div>'
-
-        # Tables wrapped in divs
-        table_html = f'<div id="summary_stats"><h2>Summary Stats</h2>{summary.to_html(index=False, escape=False)}</div>'
-        data_table_html = f'<div id="ohlc_table"><h2>OHLC Table</h2>{df.to_html(index=False, escape=False)}</div>'
-
-        full_html = chart_html + table_html + data_table_html
-
-        persist.save(key, full_html, "html")
-        return full_html
+        # Save to cache
+        persist.save(key, html_table, "html")
+        return html_table
 
     except Exception as e:
         return wrap_html(f'<div id="daily_wrapper"><h1>Error fetch_daily: {e}</h1><pre>{traceback.format_exc()}</pre></div>')