Update index_live_html.py

index_live_html.py

@@ -2,19 +2,25 @@ from nsepython import *
 import pandas as pd
 from datetime import datetime as dt
 
-# persist helpers (already exist)
+# persist helpers (HF only)
 from persist import exists, load, save
 
 
 def build_index_live_html():
-    # ================= CACHE =================
-    cache_key = "index_live_NIFTY50"
-    today = dt.now().strftime("%Y-%m-%d")
+    """
+    Live HTML for NIFTY 50
+    - Intraday TTL (15 minutes)
+    - HTML only cache
+    - persist.py controls validity
+    """
 
-    if exists(cache_key):
-        cached = load(cache_key)
-        if isinstance(cached, dict) and cached.get("date") == today:
-            return cached.get("html")
+    # ================= CACHE (TTL via persist) =================
+    cache_name = "INTRADAY_INDEX_LIVE_NIFTY50"
+
+    if exists(cache_name, "html"):
+        cached_html = load(cache_name, "html")
+        if isinstance(cached_html, str):
+            return cached_html
 
     # ================= LIVE FETCH =================
     index_name = "NIFTY 50"
@@ -33,7 +39,7 @@ def build_index_live_html():
         if not const_df.empty:
             const_df = const_df.iloc[:, 1:]
 
-            move_to_info = [c for c in ['segment','equityTime','preOpenTime'] if c in const_df.columns]
+            move_to_info = [c for c in ["segment", "equityTime", "preOpenTime"] if c in const_df.columns]
             if move_to_info:
                 rem_df = pd.concat([rem_df, const_df[move_to_info].iloc[[0]]], axis=1)
                 const_df = const_df.drop(columns=move_to_info)
@@ -65,33 +71,38 @@ def build_index_live_html():
     # ================= HTML HELPERS =================
     def df_to_html_color(df, metric_col=None):
         df_html = df.copy()
-        top3_up, top3_down = [], []
+        top_up, top_down = [], []
 
         if metric_col and metric_col in df_html.columns:
-            col_numeric = pd.to_numeric(df_html[metric_col], errors="coerce").dropna()
-            top3_up = col_numeric.nlargest(3).index.tolist()
-            top3_down = col_numeric.nsmallest(3).index.tolist()
+            col_num = pd.to_numeric(df_html[metric_col], errors="coerce").dropna()
+            top_up = col_num.nlargest(3).index.tolist()
+            top_down = col_num.nsmallest(3).index.tolist()
 
         for idx, row in df_html.iterrows():
             for col in df_html.columns:
                 val = row[col]
-                style = ""
+                cls = ""
                 if isinstance(val, (int, float)):
                     val_fmt = f"{val:.2f}"
-                    if val > 0: style = "numeric-positive"
-                    elif val < 0: style = "numeric-negative"
+                    if val > 0:
+                        cls = "numeric-positive"
+                    elif val < 0:
+                        cls = "numeric-negative"
                     if metric_col and col == metric_col:
-                        if idx in top3_up: style += " top-up"
-                        elif idx in top3_down: style += " top-down"
-                    df_html.at[idx, col] = f'<span class="{style.strip()}">{val_fmt}</span>'
+                        if idx in top_up:
+                            cls += " top-up"
+                        elif idx in top_down:
+                            cls += " top-down"
+                    df_html.at[idx, col] = f'<span class="{cls.strip()}">{val_fmt}</span>'
                 else:
                     df_html.at[idx, col] = str(val)
 
         return df_html.to_html(index=False, escape=False, classes="compact-table")
 
-    def merge_info_main_cards(rem_df, main_df):
+    def build_info_cards(rem_df, main_df):
         combined = pd.concat([rem_df, main_df], axis=1)
         combined = combined.loc[:, ~combined.columns.duplicated()]
+
         html = '<div class="mini-card-container">'
         for col in combined.columns:
             val = combined.at[0, col] if not combined.empty else ""
@@ -104,27 +115,31 @@ def build_index_live_html():
         html += "</div>"
         return html
 
-    info_cards_html = merge_info_main_cards(rem_df, main_df)
+    info_cards_html = build_info_cards(rem_df, main_df)
     cons_html = df_to_html_color(const_df)
 
-    metric_cols = ["pChange","totalTradedValue","nearWKH","nearWKL","perChange365d","perChange30d"]
-    metric_tables = ""
+    metric_cols = [
+        "pChange","totalTradedValue","nearWKH",
+        "nearWKL","perChange365d","perChange30d"
+    ]
 
+    metric_tables = ""
     for col in metric_cols:
         if col not in const_df.columns:
             continue
-        df_const = const_df[['symbol', col]].copy()
-        df_const[col] = pd.to_numeric(df_const[col], errors="coerce")
-        df_const = df_const.sort_values(col, ascending=False)
+        df_m = const_df[["symbol", col]].copy()
+        df_m[col] = pd.to_numeric(df_m[col], errors="coerce")
+        df_m = df_m.sort_values(col, ascending=False)
+
         metric_tables += f"""
         <div class="small-table">
             <div class="st-title">{col}</div>
-            <div class="st-body">{df_to_html_color(df_const, col)}</div>
+            <div class="st-body">{df_to_html_color(df_m, col)}</div>
         </div>
         """
 
     # ================= FINAL HTML =================
-    html = f"""
+    html_out = f"""
 <!DOCTYPE html>
 <html>
 <head>
@@ -149,7 +164,7 @@ th, td {{ border: 1px solid #bbb; padding: 5px 8px; }}
 
 <h2>Live Index Data: NIFTY 50</h2>
 
-<h3>Index Info + Main Data</h3>
+<h3>Index Info</h3>
 {info_cards_html}
 
 <h3>Constituents</h3>
@@ -164,10 +179,7 @@ th, td {{ border: 1px solid #bbb; padding: 5px 8px; }}
 </html>
 """
 
-    # ================= SAVE CACHE =================
-    save(cache_key, {
-        "date": today,
-        "html": html
-    })
+    # ================= SAVE (HTML ONLY) =================
+    save(cache_name, html_out, "html")
 
-    return html
+    return html_out