Update app/daily.py

app/daily.py

@@ -2,45 +2,35 @@
 
 import yfinance as yf
 import pandas as pd
-from datetime import datetime as dt
 import matplotlib.pyplot as plt
-import os
+from datetime import datetime as dt
 import traceback
-from . import persist
+import io
 
-# ============================================================
-# Static path (HF serves this automatically)
-# ============================================================
-BASE_STATIC = "/app/app/static/charts/daily"
+from . import persist
+from . import backblaze as b2   # your existing B2 helper
 
 
+# ============================================================
+# MAIN
 # ============================================================
 def fetch_daily(symbol, date_end, date_start):
-    """
-    Fetch daily OHLCV data from Yahoo Finance,
-    generate PNG charts using matplotlib,
-    and return FULL HTML to frontend.
-    """
-
-    cache_key = f"daily_{symbol}"
-
-    # --------------------------------------------------------
-    # Cache
-    # --------------------------------------------------------
-    if persist.exists(cache_key, "html"):
-        cached = persist.load(cache_key, "html")
+    key = f"daily_{symbol}"
+
+    if persist.exists(key, "html"):
+        cached = persist.load(key, "html")
         if cached:
             return cached
 
     try:
         # ----------------------------------------------------
-        # Date handling
+        # Date conversion (YOUR FORMAT)
         # ----------------------------------------------------
         start = dt.strptime(date_start, "%d-%m-%Y").strftime("%Y-%m-%d")
         end   = dt.strptime(date_end, "%d-%m-%Y").strftime("%Y-%m-%d")
 
         # ----------------------------------------------------
-        # Fetch data
+        # Fetch data (EXACT METHOD)
         # ----------------------------------------------------
         df = yf.download(symbol + ".NS", start=start, end=end)
 
@@ -48,17 +38,17 @@ def fetch_daily(symbol, date_end, date_start):
             df.columns = df.columns.get_level_values(0)
 
         if df.empty:
-            return "<h2>No data available</h2>"
+            return "<h3>No daily data found</h3>"
 
         # ----------------------------------------------------
-        # Clean & prepare
+        # Clean data
         # ----------------------------------------------------
         df = df.reset_index()
         df["Date"] = pd.to_datetime(df["Date"], errors="coerce")
         df = df.dropna(subset=["Date"])
 
-        for col in ["Open", "High", "Low", "Close", "Volume"]:
-            df[col] = pd.to_numeric(df[col], errors="coerce")
+        for c in ["Open", "High", "Low", "Close", "Volume"]:
+            df[c] = pd.to_numeric(df[c], errors="coerce")
 
         df = df.dropna()
         df["DateStr"] = df["Date"].dt.strftime("%d-%b-%Y")
@@ -69,57 +59,52 @@ def fetch_daily(symbol, date_end, date_start):
         df["MA20"] = df["Close"].rolling(20).mean()
         df["MA50"] = df["Close"].rolling(50).mean()
 
-        # ----------------------------------------------------
-        # Output paths
-        # ----------------------------------------------------
-        out_dir = f"{BASE_STATIC}/{symbol}"
-        os.makedirs(out_dir, exist_ok=True)
-
-        price_png = f"{out_dir}/price_volume.png"
-        ma_png    = f"{out_dir}/moving_avg.png"
-
-        price_url = f"/static/charts/daily/{symbol}/price_volume.png"
-        ma_url    = f"/static/charts/daily/{symbol}/moving_avg.png"
+        # ====================================================
+        # PRICE + VOLUME CHART → B2
+        # ====================================================
+        buf = io.BytesIO()
 
-        # ----------------------------------------------------
-        # PRICE + VOLUME CHART
-        # ----------------------------------------------------
         plt.figure(figsize=(14, 6))
         plt.plot(df["Date"], df["Close"], label="Close", linewidth=2)
 
-        # Scale volume visually
         vol_scaled = df["Volume"] / df["Volume"].max() * df["Close"].max()
-        plt.bar(df["Date"], vol_scaled, alpha=0.2, label="Volume")
+        plt.bar(df["Date"], vol_scaled, alpha=0.25, label="Volume")
 
         plt.title(f"{symbol} Price & Volume")
-        plt.xlabel("Date")
-        plt.ylabel("Price")
         plt.legend()
         plt.grid(True)
         plt.tight_layout()
-        plt.savefig(price_png)
+        plt.savefig(buf, format="png")
         plt.close()
 
-        # ----------------------------------------------------
-        # MOVING AVERAGE CHART
-        # ----------------------------------------------------
+        buf.seek(0)
+        price_key = f"daily/{symbol}_price_volume.png"
+        price_url = b2.upload_bytes("eshanhf", price_key, buf.getvalue())
+
+        # ====================================================
+        # MOVING AVERAGE CHART → B2
+        # ====================================================
+        buf = io.BytesIO()
+
         plt.figure(figsize=(14, 6))
         plt.plot(df["Date"], df["Close"], label="Close", linewidth=2)
         plt.plot(df["Date"], df["MA20"], label="MA20")
         plt.plot(df["Date"], df["MA50"], label="MA50")
 
         plt.title(f"{symbol} Moving Averages")
-        plt.xlabel("Date")
-        plt.ylabel("Price")
         plt.legend()
         plt.grid(True)
         plt.tight_layout()
-        plt.savefig(ma_png)
+        plt.savefig(buf, format="png")
         plt.close()
 
-        # ----------------------------------------------------
-        # TABLE (last 100 rows)
-        # ----------------------------------------------------
+        buf.seek(0)
+        ma_key = f"daily/{symbol}_ma.png"
+        ma_url = b2.upload_bytes("eshanhf", ma_key, buf.getvalue())
+
+        # ====================================================
+        # TABLE
+        # ====================================================
         rows = ""
         for r in df.tail(100).itertuples():
             rows += f"""
@@ -133,15 +118,17 @@ def fetch_daily(symbol, date_end, date_start):
             </tr>
             """
 
-        # ----------------------------------------------------
-        # FINAL HTML (FULL DOCUMENT FRAGMENT)
-        # ----------------------------------------------------
+        # ====================================================
+        # FINAL HTML
+        # ====================================================
         html = f"""
-<h2>{symbol} – Daily Dashboard</h2>
+<div id="daily_dashboard">
+
+<h2>{symbol} – Daily Analysis</h2>
 
 <h3>Price Table (Last 100 Days)</h3>
-<table border="1" cellpadding="6" cellspacing="0" style="border-collapse:collapse;">
-<tr style="background:#eee;font-weight:bold;">
+<table style="border-collapse:collapse;width:100%;" border="1" cellpadding="6">
+<tr style="background:#f0f0f0;font-weight:bold;">
     <th>Date</th>
     <th>Open</th>
     <th>High</th>
@@ -157,9 +144,11 @@ def fetch_daily(symbol, date_end, date_start):
 
 <h3>Moving Averages</h3>
 <img src="{ma_url}" style="width:100%;max-width:1200px;">
+
+</div>
 """
 
-        persist.save(cache_key, html, "html")
+        persist.save(key, html, "html")
         return html
 
     except Exception: