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kotak_neo.py

@@ -5,6 +5,7 @@ import threading
 from csv import DictReader
 from concurrent.futures import ThreadPoolExecutor, as_completed
 from datetime import date, datetime, time, timezone
+from functools import lru_cache
 from pathlib import Path
 from time import monotonic
 from typing import Any
@@ -16,6 +17,11 @@ import json
 import pandas as pd
 import requests
 
+try:
+    import pandas_market_calendars as mcal
+except Exception:  # pragma: no cover - deployed environments may fall back to weekdays
+    mcal = None
+
 
 SESSION_BASE_URL = "https://mis.kotaksecurities.com"
 QUOTE_PATH_TEMPLATE = "script-details/1.0/quotes/neosymbol/{neo_symbols}/{quote_type}"
@@ -28,6 +34,8 @@ KOTAK_ACTIVITY_LOG_PATH = DATA_DIR / "kotak_activity_log.txt"
 NIFTY_1M_PATH = DATA_DIR / "nifty50_1m.parquet"
 NIFTY_1D_PATH = DATA_DIR / "nifty50_1d.parquet"
 IST = ZoneInfo("Asia/Kolkata")
+MARKET_OPEN_TIME = time(9, 15)
+MARKET_CLOSE_TIME = time(15, 30)
 
 
 class KotakNeoError(Exception):
@@ -85,6 +93,50 @@ def _normalize_frame_dates(frame: pd.DataFrame) -> pd.Series:
     return values
 
 
+@lru_cache(maxsize=1)
+def _nse_calendar():
+    if mcal is None:
+        return None
+    for name in ("XNSE", "NSE", "BSE"):
+        try:
+            return mcal.get_calendar(name)
+        except Exception:
+            continue
+    return None
+
+
+@lru_cache(maxsize=64)
+def _is_nse_trading_day(day: date) -> bool:
+    calendar = _nse_calendar()
+    if calendar is None:
+        return day.weekday() < 5
+    return not calendar.schedule(start_date=day, end_date=day).empty
+
+
+def _file_version(path: Path) -> tuple[str, int | None, int | None]:
+    try:
+        stat = path.stat()
+        return (str(path), stat.st_mtime_ns, stat.st_size)
+    except OSError:
+        return (str(path), None, None)
+
+
+@lru_cache(maxsize=4)
+def _load_nifty_daily_frame(file_version: tuple[str, int | None, int | None]) -> pd.DataFrame:
+    path = Path(file_version[0])
+    daily = pd.read_parquet(path, columns=["date", "open", "high", "low", "close"]).copy()
+    daily["date"] = pd.to_datetime(daily["date"], errors="coerce").dt.date
+    return daily.dropna(subset=["date"]).sort_values("date")
+
+
+@lru_cache(maxsize=4)
+def _load_nifty_minute_frame(file_version: tuple[str, int | None, int | None]) -> pd.DataFrame:
+    path = Path(file_version[0])
+    minute = pd.read_parquet(path, columns=["date", "open", "high", "low", "close"]).copy()
+    minute["date"] = _normalize_frame_dates(minute)
+    return minute.dropna(subset=["date"]).sort_values("date")
+
+
 def _first_text(*values: Any) -> str | None:
     for value in values:
         if isinstance(value, dict):
@@ -432,7 +484,10 @@ class KotakNeoManager:
         item = items[0]
         now_ist = datetime.now(IST)
         last_traded_price = _first_market_number(item.get("last_traded_price"), item.get("ltp"), item.get("iv"))
-        live_stats = self._load_nifty50_reference_stats(now_ist, last_traded_price)
+        quote_open = _first_market_number(item.get("openingPrice"), item.get("open"), item.get("o"))
+        quote_high = _first_market_number(item.get("high"), item.get("highPrice"), item.get("h"))
+        quote_low = _first_market_number(item.get("low"), item.get("lowPrice"), item.get("l"))
+        live_stats = self._load_nifty50_reference_stats(now_ist, last_traded_price, quote_open, quote_high, quote_low)
         close = live_stats["previous_close"]
         change_base = live_stats["return_base"]
         change = None
@@ -442,7 +497,7 @@ class KotakNeoManager:
             change_pct = (change / change_base) * 100.0
         high = live_stats["range_high"]
         low = live_stats["range_low"]
-        open_price = _first_market_number(item.get("openingPrice"), item.get("open"), item.get("o"))
+        open_price = quote_open
 
         payload = {
             "symbol": "NIFTY 50",
@@ -464,6 +519,7 @@ class KotakNeoManager:
             "low": low,
             "return_basis": live_stats["return_basis"],
             "market_open": live_stats["market_open"],
+            "is_trading_session": live_stats["is_trading_session"],
             "exchange_feed_time": _first_text(item.get("tvalue"), item.get("updRecvTm"), item.get("hsUpTm")),
             "as_of": _utc_now_iso(),
             "source": {
@@ -483,46 +539,62 @@ class KotakNeoManager:
             }
         return payload
 
-    def _load_nifty50_reference_stats(self, now_ist: datetime, last_traded_price: float | None) -> dict[str, Any]:
+    def _load_nifty50_reference_stats(
+        self,
+        now_ist: datetime,
+        last_traded_price: float | None,
+        live_open: float | None = None,
+        live_high: float | None = None,
+        live_low: float | None = None,
+    ) -> dict[str, Any]:
         today = now_ist.date()
-        market_open = time(9, 15) <= now_ist.time() < time(15, 30)
+        is_trading_session = _is_nse_trading_day(today)
+        market_open = is_trading_session and MARKET_OPEN_TIME <= now_ist.time() < MARKET_CLOSE_TIME
 
-        daily = pd.read_parquet(NIFTY_1D_PATH, columns=["date", "open", "high", "low", "close"]).copy()
-        daily["date"] = pd.to_datetime(daily["date"], errors="coerce").dt.date
-        daily = daily.dropna(subset=["date"]).sort_values("date")
+        daily = _load_nifty_daily_frame(_file_version(NIFTY_1D_PATH))
 
         previous_close = None
+        previous_high = None
+        previous_low = None
         today_daily = daily[daily["date"] == today]
         previous_daily = daily[daily["date"] < today]
         if not previous_daily.empty:
-            previous_close = _to_float(previous_daily.iloc[-1]["close"])
+            previous_row = previous_daily.iloc[-1]
+            previous_close = _to_float(previous_row["close"])
+            previous_high = _to_float(previous_row["high"])
+            previous_low = _to_float(previous_row["low"])
 
         today_open = _to_float(today_daily.iloc[-1]["open"]) if not today_daily.empty else None
         today_high = _to_float(today_daily.iloc[-1]["high"]) if not today_daily.empty else None
         today_low = _to_float(today_daily.iloc[-1]["low"]) if not today_daily.empty else None
         today_close = _to_float(today_daily.iloc[-1]["close"]) if not today_daily.empty else None
 
-        minute = pd.read_parquet(NIFTY_1M_PATH, columns=["date", "open", "high", "low", "close"]).copy()
-        minute["date"] = _normalize_frame_dates(minute)
-        minute = minute.dropna(subset=["date"]).sort_values("date")
-        today_minute = minute[minute["date"].dt.date == today]
-
-        if not today_minute.empty:
-            today_open = _to_float(today_minute.iloc[0]["open"]) or today_open
-            minute_high = pd.to_numeric(today_minute["high"], errors="coerce").max()
-            minute_low = pd.to_numeric(today_minute["low"], errors="coerce").min()
-            today_high = _to_float(minute_high) or today_high
-            today_low = _to_float(minute_low) or today_low
-            today_close = _to_float(today_minute.iloc[-1]["close"]) or today_close
-
-        if market_open:
+        session_started = is_trading_session and now_ist.time() >= MARKET_OPEN_TIME
+
+        if session_started:
+            today_open = live_open or today_open
+            today_high = live_high or today_high
+            today_low = live_low or today_low
+
+            if today_open is None or today_high is None or today_low is None:
+                minute = _load_nifty_minute_frame(_file_version(NIFTY_1M_PATH))
+                today_minute = minute[minute["date"].dt.date == today]
+                if not today_minute.empty:
+                    today_open = _to_float(today_minute.iloc[0]["open"]) or today_open
+                    minute_high = pd.to_numeric(today_minute["high"], errors="coerce").max()
+                    minute_low = pd.to_numeric(today_minute["low"], errors="coerce").min()
+                    today_high = _to_float(minute_high) or today_high
+                    today_low = _to_float(minute_low) or today_low
+                    today_close = _to_float(today_minute.iloc[-1]["close"]) or today_close
+
+        if session_started:
             range_high = max([value for value in [today_high, last_traded_price] if value is not None], default=None)
             range_low = min([value for value in [today_low, last_traded_price] if value is not None], default=None)
             return_base = today_open
             return_basis = "open"
         else:
-            range_high = today_high
-            range_low = today_low
+            range_high = previous_high
+            range_low = previous_low
             return_base = previous_close
             return_basis = "previous_close"
             if last_traded_price is None:
@@ -535,6 +607,7 @@ class KotakNeoManager:
             "range_high": range_high,
             "range_low": range_low,
             "market_open": market_open,
+            "is_trading_session": is_trading_session,
         }
 
     def _ensure_authenticated_locked(self) -> None: