Update preopen_html.py

preopen_html.py

@@ -1,94 +1,134 @@
 from nsepython import *
 import pandas as pd
 import re
+from datetime import datetime as dt
+
+# persist helpers (ALREADY EXIST IN YOUR PROJECT)
+from persist import exists, load, save
+
 
 def build_preopen_html(key="NIFTY"):
-    # Fetch pre-open data
+    """
+    Build full Pre-Open HTML with daily cache.
+    If cached HTML exists for today → return it.
+    Else → fetch, rebuild, save, return.
+    """
+
+    # ================= CACHE =================
+    today = dt.now().strftime("%Y-%m-%d")
+    cache_key = f"preopen_html_{key}"
+
+    if exists(cache_key):
+        cached = load(cache_key)
+        if isinstance(cached, dict) and cached.get("date") == today:
+            return cached.get("html")
+
+    # ================= FETCH DATA =================
     p = nsefetch(f"https://www.nseindia.com/api/market-data-pre-open?key={key}")
+
     data_df = df_from_data(p.pop("data"))
     rem_df  = df_from_data([p])
-    
-    main_df = data_df.iloc[[0]] if not data_df.empty else pd.DataFrame()
+
+    main_df  = data_df.iloc[[0]] if not data_df.empty else pd.DataFrame()
     const_df = data_df.iloc[1:] if len(data_df) > 1 else pd.DataFrame()
-    
-    # ================= REMOVE *_x AND SPECIFIC PATTERNS =================
+
+    # ================= REMOVE PATTERN COLUMNS =================
     pattern_remove = re.compile(r"^(price_|buyQty_|sellQty_|iep_)\d+$")
-    
+
     def remove_pattern_cols(df):
+        if df is None or df.empty:
+            return df
         return df[[c for c in df.columns if not pattern_remove.match(c)]]
-    
-    main_df = remove_pattern_cols(main_df)
+
+    main_df  = remove_pattern_cols(main_df)
     const_df = remove_pattern_cols(const_df)
-    rem_df = remove_pattern_cols(rem_df)
+    rem_df   = remove_pattern_cols(rem_df)
 
-    # ================= HELPER FUNCTION =================
+    # ================= TABLE COLOR HELPER =================
     def df_to_html_color(df, metric_col=None):
+        if df is None or df.empty:
+            return "<i>No data</i>"
+
         df_html = df.copy()
         top3_up, top3_down = [], []
-        if metric_col and metric_col in df_html.columns and pd.api.types.is_numeric_dtype(df_html[metric_col]):
-            col_numeric = df_html[metric_col].dropna()
-            top3_up = col_numeric.nlargest(3).index.tolist()
-            top3_down = col_numeric.nsmallest(3).index.tolist()
+
+        if metric_col and metric_col in df_html.columns:
+            if pd.api.types.is_numeric_dtype(df_html[metric_col]):
+                col_numeric = df_html[metric_col].dropna()
+                top3_up = col_numeric.nlargest(3).index.tolist()
+                top3_down = col_numeric.nsmallest(3).index.tolist()
 
         for idx, row in df_html.iterrows():
             for col in df_html.columns:
                 val = row[col]
                 style = ""
+
                 if isinstance(val, (int, float)):
                     val_fmt = f"{val:.2f}"
                     if val > 0:
                         style = "numeric-positive"
                     elif val < 0:
                         style = "numeric-negative"
-                    if metric_col == col:
+
+                    if 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>'
                 else:
                     df_html.at[idx, col] = str(val)
+
         return df_html.to_html(index=False, escape=False, classes="compact-table")
 
-    # ================= MINI-CARDS =================
-    def merge_info_main_cards(rem_df, main_df):
+    # ================= MINI CARDS =================
+    def build_info_cards(rem_df, main_df):
         combined = pd.concat([rem_df, main_df], axis=1)
         combined = combined.loc[:, ~combined.columns.duplicated()]
-        # Remove pattern columns
-        combined = combined[[c for c in combined.columns if not pattern_remove.match(c)]]
-        cards_html = '<div class="mini-card-container">'
+        combined = remove_pattern_cols(combined)
+
+        cards = '<div class="mini-card-container">'
         for col in combined.columns:
             val = combined.at[0, col] if not combined.empty else ""
-            cards_html += f'''
+            cards += f"""
             <div class="mini-card">
                 <div class="card-key">{col}</div>
                 <div class="card-val">{val}</div>
             </div>
-            '''
-        cards_html += '</div>'
-        return cards_html
+            """
+        cards += '</div>'
+        return cards
 
-    info_cards_html = merge_info_main_cards(rem_df, main_df)
+    info_cards_html = build_info_cards(rem_df, main_df)
 
-    # ================= Constituents table =================
-    cons_html = df_to_html_color(const_df) if not const_df.empty else "<i>No pre-open constituents</i>"
+    # ================= CONSTITUENTS TABLE =================
+    cons_html = df_to_html_color(const_df)
 
-    # ================= Metric tables (restricted to selected columns) =================
-    metric_cols_allowed = ["pChange", "totalTurnover", "marketCap", "totalTradedVolume"]
-    metric_cols = [c for c in metric_cols_allowed if c in const_df.columns and pd.api.types.is_numeric_dtype(const_df[c])] if not const_df.empty else []
+    # ================= METRIC TABLES =================
+    metric_cols_allowed = [
+        "pChange",
+        "totalTurnover",
+        "marketCap",
+        "totalTradedVolume"
+    ]
 
     metric_tables = ""
-    for col in metric_cols:
-        df_const = const_df.copy()
-        df_const[col] = pd.to_numeric(df_const[col], errors="ignore")
-        df_const = df_const.sort_values(col, ascending=False)
-        df_html = df_to_html_color(df_const[['symbol', col]] if 'symbol' in df_const.columns else df_const[[col]], metric_col=col)
-        metric_tables += f"""
-        <div class="small-table">
-            <div class="st-title">{col}</div>
-            <div class="st-body">{df_html}</div>
-        </div>
-        """
+    for col in metric_cols_allowed:
+        if col in const_df.columns and pd.api.types.is_numeric_dtype(const_df[col]):
+            df_metric = const_df.copy()
+            df_metric[col] = pd.to_numeric(df_metric[col], errors="coerce")
+            df_metric = df_metric.sort_values(col, ascending=False)
+
+            show_cols = ["symbol", col] if "symbol" in df_metric.columns else [col]
+            metric_tables += f"""
+            <div class="small-table">
+                <div class="st-title">{col}</div>
+                <div class="st-body">
+                    {df_to_html_color(df_metric[show_cols], metric_col=col)}
+                </div>
+            </div>
+            """
 
     # ================= FINAL HTML =================
     html = f"""
@@ -97,45 +137,51 @@ def build_preopen_html(key="NIFTY"):
 <head>
 <meta charset="UTF-8">
 <style>
-body {{ font-family: Arial; margin: 12px; background: #f5f5f5; color: #222; font-size: 14px; }}
-h2, h3 {{ margin: 12px 0 6px 0; font-weight: 600; }}
-table {{ border-collapse: collapse; width: 100%; table-layout: auto; }}
-th, td {{ border: 1px solid #bbb; padding: 5px 8px; text-align: left; font-size: 13px; }}
-th {{ background: #333; color: white; font-weight: 600; }}
+body {{ font-family: Arial; margin: 12px; background: #f5f5f5; font-size: 14px; }}
+h2, h3 {{ margin: 10px 0; }}
+table {{ border-collapse: collapse; width: 100%; }}
+th, td {{ border: 1px solid #bbb; padding: 6px; font-size: 13px; }}
+th {{ background: #333; color: #fff; }}
+
 .compact-table td.numeric-positive {{ color: green; font-weight: bold; }}
 .compact-table td.numeric-negative {{ color: red; font-weight: bold; }}
-.compact-table td.top-up {{ background: #a8f0a5; }}
-.compact-table td.top-down {{ background: #f0a8a8; }}
-.small-table {{ background: white; border-radius: 6px; padding: 8px; box-shadow: 0px 1px 4px rgba(0,0,0,0.15); border: 1px solid #ddd; overflow-y: auto; }}
-.st-title {{ font-size: 14px; text-align: center; margin-bottom: 6px; font-weight: bold; background: #222; color: white; padding: 5px 0; border-radius: 4px; }}
-.st-body {{ max-height: 300px; overflow-y: auto; font-size: 12px; }}
-.grid {{ display: grid; grid-template-columns: repeat(5, 1fr); gap: 12px; margin-top: 12px; }}
+.compact-table td.top-up {{ background: #b6f2b6; }}
+.compact-table td.top-down {{ background: #f2b6b6; }}
+
+.grid {{ display: grid; grid-template-columns: repeat(5, 1fr); gap: 12px; }}
+.small-table {{ background: #fff; padding: 8px; border-radius: 6px; border: 1px solid #ddd; }}
+.st-title {{ text-align: center; font-weight: bold; background: #222; color: #fff; padding: 6px; border-radius: 4px; }}
+.st-body {{ max-height: 300px; overflow-y: auto; }}
+
 .mini-card-container {{ display: flex; flex-wrap: wrap; gap: 10px; }}
-.mini-card {{ background: #fff; padding: 8px 10px; border-radius: 6px; box-shadow: 0 1px 3px rgba(0,0,0,0.12); min-width: 120px; font-size: 13px; }}
-.card-key {{ font-weight: bold; color: #333; margin-bottom: 2px; }}
-.card-val {{ color: #222; }}
+.mini-card {{ background: #fff; padding: 8px 10px; border-radius: 6px; border: 1px solid #ddd; min-width: 120px; }}
+.card-key {{ font-weight: bold; }}
 </style>
 </head>
+
 <body>
 
-<h2>Pre-Open Data: {key}</h2>
+<h2>Pre-Open Market — {key}</h2>
 
-<div class="compact-section">
-    <h3>Info + Main Data</h3>
-    {info_cards_html}
-</div>
+<h3>Info</h3>
+{info_cards_html}
 
-<div class="compact-section">
-    <h3>Pre-Open Constituents</h3>
-    {cons_html}
-</div>
+<h3>Constituents</h3>
+{cons_html}
 
-<h3>Metric Tables (selected numeric)</h3>
+<h3>Key Metrics</h3>
 <div class="grid">
-    {metric_tables}
+{metric_tables}
 </div>
 
 </body>
 </html>
 """
+
+    # ================= SAVE CACHE =================
+    save(cache_key, {
+        "date": today,
+        "html": html
+    })
+
     return html