Get full quote (OHLC + depth summary)

quote() returns much more than ltp() — today's OHLC, volume, open interest (for F&O), and a snapshot of top-of-book depth.

quotes = kite.quote(["NSE:INFY"])
print(quotes["NSE:INFY"])

{
  "instrument_token": 408065,
  "last_price": 1478.9,
  "volume": 3821450,
  "buy_quantity": 12500,
  "sell_quantity": 9800,
  "ohlc": {"open": 1465.0, "high": 1482.0, "low": 1460.5, "close": 1470.2},
  "net_change": 8.7,
  "oi": 0,                       # open interest, non-zero for F&O
  "oi_day_high": 0,
  "oi_day_low": 0,
  "depth": {
    "buy": [{"price": 1478.8, "quantity": 75, "orders": 3}, ...],   # 5 levels
    "sell": [{"price": 1479.0, "quantity": 60, "orders": 2}, ...],  # 5 levels
  },
}

close in ohlc is *yesterday's* close, not today's

A common misread: ohlc.close is the previous trading day's closing price (used to compute net_change), not today's current close (the market is still open). Today's running high/low/open are the other three fields.

def percent_change_from_prev_close(quote: dict) -> float:
    prev_close = quote["ohlc"]["close"]
    return (quote["last_price"] - prev_close) / prev_close * 100

When to use quote() vs ltp() vs ohlc()

• ltp() — cheapest, just price. Use for frequent polling of many symbols where you only need price.
• ohlc() — price + today's OHLC, no depth. Middle ground.
• quote() — everything, including depth and OI. Use when you actually need depth (e.g. estimating slippage before a market order, chapter 86) or OI (F&O strategies) — it's the most expensive call of the three, use sparingly in tight loops.

Next: 026 — Get market depth (5-level book)