stoxkart

Stoxkart ticks.

bin/stoxkart/instruments/websocket_quotes streams Stoxkart's broadcast websocket, wss://broadcasting-v2.stoxkart.com/, and names each instrument EXCHANGE:TOKEN in Stoxkart's own exchange vocabulary: NSE, BSE, NFO and MCX. The bare token collides across exchanges, so the exchange narrows the search. NSECD, BSECD, BFO and NCDEX are accepted here too, though the quote script does not yet subscribe to them.

What Stoxkart's values mean, as measured against Zerodha's ticks received in the same second during the session of 2026-09-15:

• close is the previous session's close, from Stoxkart's previous close packet: TCS read 2200.80, HDFCBANK 708.25 and CRUDEOIL SEP 9717, all Zerodha's figures. What it holds after the session has not been seen, so it is trusted only before the session closes.
• On MCX every quantity is in lots, as at Zerodha: CRUDEOIL SEP read volume 8997 and open interest 15634 at both. On NSE price, volume, average price, total bid and offered quantity and the first depth level matched Zerodha's.
• Both times are true instants on NSE: Stoxkart counts seconds from 1980, bin/stoxkart/instruments/websocket_quotes converts them, and TCS and RELIANCE matched Zerodha's last trade and exchange times to the second, while HDFCBANK's exchange time read one second earlier in a snapshot taken a second before Zerodha's. Stoxkart sends no exchange time on MCX.

Typical usage example:

normalizer = StoxkartTickNormalizer() key = normalizer.feed_key("NSE:760946")

Classes:

Name	Description
StoxkartTickNormalizer	Normalizes the ticks bin/stoxkart/instruments/websocket_quotes writes from Stoxkart's broadcast websocket.

StoxkartTickNormalizer

StoxkartTickNormalizer()

Bases: TickNormalizer

Normalizes the ticks bin/stoxkart/instruments/websocket_quotes writes from Stoxkart's broadcast websocket.

Builds the canonical segments each Stoxkart exchange's tokens may name.

Example programs

Placing feed tokensMcx quantities in lots

examples/stock_brokers/instruments/ticks/stoxkart/StoxkartTickNormalizer/example_1_placing_feed_tokens.py

"""Places Stoxkart feed tokens, spelled `EXCHANGE:TOKEN`, on the canonical segments they can be in.

A Stoxkart token names its exchange before a colon: NSE and BSE hold shares and indices, NFO, NSECD, BFO and BSECD hold NSE and BSE derivatives, and MCX and NCDEX hold commodity derivatives. A token with no colon, or an exchange Stoxkart does not serve, prints `None`.

The normalizer only works on the text of each token, so the program needs no Redis, database, network or stand-in of any kind. Each output line shows a token as the feed spells it, then the broker token that `unified.broker_mappings` is searched with, the order symbol when the broker names instruments by symbol, and how many canonical segments the search is limited to, with the first of them. A token the normalizer cannot place prints `None`.

Run it from the project root:

    python examples/stock_brokers/instruments/ticks/stoxkart/StoxkartTickNormalizer/example_1_placing_feed_tokens.py
"""

from stock_brokers.instruments.ticks.stoxkart import (
    StoxkartTickNormalizer,
)


class PlacingFeedTokensExample:
    """Asks the Stoxkart normalizer where each of a few feed tokens belongs.

    Attributes:
        normalizer (StoxkartTickNormalizer): The normalizer being shown.
        tokens (list): The tokens to place, spelled as the feed spells them.
    """

    def __init__(self):
        """Builds the normalizer and the tokens to place.

        Returns:
            None: This method returns nothing.
        """
        self.normalizer = StoxkartTickNormalizer()
        self.tokens = [
            'NSE:2885',
            'NFO:35003',
            'MCX:440001',
            'NCDEX:12345',
            'NSE',
            'LSE:1',
        ]

    def describe(self, feed_key):
        """Describes a feed key in one line.

        Args:
            feed_key (FeedKey | None): The key the normalizer returned.

        Returns:
            str: The description.
        """
        if feed_key is None:
            return 'None'
        segment_count = len(feed_key.segments)
        first_segment = feed_key.segments[0]
        return f'broker_token={feed_key.broker_token!r} order_symbol={feed_key.order_symbol!r} segments={segment_count} starting with {first_segment}'

    def run(self):
        """Prints where each token belongs.

        Returns:
            None: This method returns nothing.
        """
        print(f'Broker: {StoxkartTickNormalizer.BROKER_NAME}')
        for token in self.tokens:
            feed_key = self.normalizer.feed_key(token)
            print(f'{token!r} -> {self.describe(feed_key)}')


if __name__ == '__main__':
    PlacingFeedTokensExample().run()

It prints:

Broker: stoxkart
'NSE:2885' -> broker_token='2885' order_symbol=None segments=10 starting with nse_equities
'NFO:35003' -> broker_token='35003' order_symbol=None segments=16 starting with nse_fixed_income_futures
'MCX:440001' -> broker_token='440001' order_symbol=None segments=16 starting with mcx_fixed_income_futures
'NCDEX:12345' -> broker_token='12345' order_symbol=None segments=16 starting with ncdex_fixed_income_futures
'NSE' -> None
'LSE:1' -> None

examples/stock_brokers/instruments/ticks/stoxkart/StoxkartTickNormalizer/example_2_mcx_quantities_in_lots.py

"""Normalizes one Stoxkart tick for an MCX crude oil future, whose quantities arrive in lots.

Stoxkart reports MCX quantities in lots, so the plan multiplies each by the 100-barrel lot. Its `close` is the previous close only while the session runs, so `reported_close` is kept before the close and dropped after it.

The plan that `normalize` applies is normally compiled by `TickResolver` from the mapping cache. This program builds it by hand with the same rules, asking the normalizer how it reports each quantity field and when its close may be trusted, so it needs no database. The tick is shaped like the ones the broker's market feed publishes, with fixed times, so the output is the same on every run. The program normalizes the tick twice, once as received before the session's close and once as received after it, which only changes whether `reported_close` is kept. Order book levels are printed as (price, quantity, orders).

Run it from the project root:

    python examples/stock_brokers/instruments/ticks/stoxkart/StoxkartTickNormalizer/example_2_mcx_quantities_in_lots.py
"""

import datetime
import zoneinfo

from stock_brokers.instruments.ticks import base
from stock_brokers.instruments.ticks.base import (
    InstrumentPlan,
)
from stock_brokers.instruments.ticks.stoxkart import (
    StoxkartTickNormalizer,
)
from stock_brokers.instruments.ticks.utilities import sessions

INDIA = zoneinfo.ZoneInfo('Asia/Kolkata')


class CrudeOilTickExample:
    """Normalizes one Stoxkart tick through a hand-built plan and prints the result.

    Attributes:
        normalizer (StoxkartTickNormalizer): The normalizer being shown.
        received_at (float): When the tick was received, in epoch seconds.
        tick (dict): The tick as the market feed published it.
        plan (InstrumentPlan): The plan for the tick's instrument.
    """

    def __init__(self):
        """Builds the normalizer, the tick and its plan.

        Returns:
            None: This method returns nothing.
        """
        self.normalizer = StoxkartTickNormalizer()
        received = datetime.datetime(2026, 9, 15, 22, 46, tzinfo=INDIA)
        self.received_at = received.timestamp()
        self.tick = {
            'instrument_token': 'MCX:440001',
            'last_price': 9731.0,
            'last_quantity': 2,
            'average_price': 9718.45,
            'volume': 67958,
            'buy_quantity': 4210,
            'sell_quantity': 3987,
            'ohlc': {
                'open': 9702.0,
                'high': 9745.0,
                'low': 9688.0,
                'close': 9722.0,
            },
            'oi': 18095,
            'oi_day_high': 18410,
            'oi_day_low': 17602,
            'last_trade_time': self.received_at - 2.0,
            'exchange_timestamp': self.received_at - 1.0,
            'received_at': self.received_at,
            'depth': {
                'buy': [
                    {
                        'price': 9730.0,
                        'quantity': 3,
                        'orders': 2,
                    },
                    {
                        'price': 9729.0,
                        'quantity': 11,
                        'orders': 4,
                    },
                ],
                'sell': [
                    {
                        'price': 9731.0,
                        'quantity': 5,
                        'orders': 2,
                    },
                    {
                        'price': 9732.0,
                        'quantity': 8,
                        'orders': 3,
                    },
                ],
            },
        }
        self.plan = self.build_plan()

    def build_plan(self):
        """Compiles the plan for the tick's instrument the way the resolver would.

        Returns:
            InstrumentPlan: The plan.
        """
        exchange = 'mcx'
        segment = 'mcx_commodity_futures'
        lot_size = 100
        broker_lot_size = 1
        multipliers = {}
        for field in base.QUANTITY_FIELDS:
            basis = self.normalizer.quantity_basis(exchange, field)
            if basis == base.BASIS_LOTS:
                multipliers[field] = lot_size
            elif basis == base.BASIS_BROKER_LOTS:
                multipliers[field] = lot_size // broker_lot_size
            else:
                multipliers[field] = 1
        identity = {
            'exchange': 'mcx',
            'segment': 'mcx_commodity_futures',
            'shape': 'future',
            'symbol': 'CRUDEOIL26OCTFUT',
            'underlying_symbol': 'CRUDEOIL',
            'expiry_date': '2026-10-19',
            'strike_price': None,
            'option_type': None,
        }
        instrument_id = '11111111-1111-5111-8111-000000000101'
        broker_token = '440001'
        return InstrumentPlan(
            instrument_id=instrument_id,
            broker=StoxkartTickNormalizer.BROKER_NAME,
            broker_token=broker_token,
            exchange=exchange,
            segment=segment,
            shape=identity['shape'],
            session=sessions.session_for(segment),
            lot_size=lot_size,
            multipliers=multipliers,
            price_decimals=2,
            negative_prices=True,
            close_policy=self.normalizer.close_policy(exchange),
            has_open_interest=identity['shape'] != 'security',
            trusts_last_trade_time=StoxkartTickNormalizer.TRUSTS_LAST_TRADE_TIME,
            trusts_exchange_time=StoxkartTickNormalizer.TRUSTS_EXCHANGE_TIME,
            identity_json=base.identity_json(
                instrument_id,
                StoxkartTickNormalizer.BROKER_NAME,
                broker_token,
                identity,
                lot_size,
            ),
        )

    def run(self):
        """Prints the feed key, the plan's rules and the normalized values.

        Returns:
            None: This method returns nothing.
        """
        token = self.tick['instrument_token']
        feed_key = self.normalizer.feed_key(token)
        print(f'Token {token!r}: broker_token={feed_key.broker_token!r} order_symbol={feed_key.order_symbol!r}')
        volume_basis = self.normalizer.quantity_basis(self.plan.exchange, 'volume')
        print(f'Volume on {self.plan.exchange} is reported in {volume_basis}, multiplier {self.plan.multipliers["volume"]}')
        print(f'Close policy on {self.plan.exchange}: {self.normalizer.close_policy(self.plan.exchange)}')
        before_close = self.normalizer.normalize(self.tick, self.plan, True)
        print('Normalized, received before the close:')
        for name, value in before_close.items():
            print(f'  {name}: {value}')
        after_close = self.normalizer.normalize(self.tick, self.plan, False)
        print(f'reported_close when received after the close: {after_close["reported_close"]}')


if __name__ == '__main__':
    CrudeOilTickExample().run()

It prints:

Token 'MCX:440001': broker_token='440001' order_symbol=None
Volume on mcx is reported in lots, multiplier 100
Close policy on mcx: before
Normalized, received before the close:
  last_price: 9731.0
  last_quantity: 200
  average_price: 9718.45
  volume: 6795800
  buy_quantity: 421000
  sell_quantity: 398700
  open: 9702.0
  high: 9745.0
  low: 9688.0
  reported_close: 9722.0
  oi: 1809500
  oi_day_high: 1841000
  oi_day_low: 1760200
  last_trade_time: 1789492558.0
  exchange_time: 1789492559.0
  bids: [(9730.0, 300, 2), (9729.0, 1100, 4)]
  asks: [(9731.0, 500, 2), (9732.0, 800, 3)]
reported_close when received after the close: None

Methods:

Name	Description
feed_key	Reads the broker token and segments out of a Stoxkart EXCHANGE:TOKEN.
tick_spelling	A subscription-set token spelled the way the feed spells it on ticks.
quantity_basis	Whether the broker reports a quantity field in lots or units on an exchange.
close_policy	When the broker's close is the previous session's close on an exchange.
normalize	Apply a plan to one tick.

Source code in stock_brokers/instruments/ticks/stoxkart.py

def __init__(self):
    """Builds the canonical segments each Stoxkart exchange's tokens may name."""
    self._segments = {}
    for name, (exchanges, family) in self.EXCHANGES.items():
        self._segments[name] = family_segments(exchanges, family)

feed_key

feed_key(instrument_token)

Reads the broker token and segments out of a Stoxkart EXCHANGE:TOKEN.

Parameters:

Name	Type	Description	Default
instrument_token	str	The tick's instrument_token, such as NSE:760946.	required

Returns:

Type	Description
FeedKey | None	The key, or None for a malformed token or an unknown exchange.

Example usage

From example_1_placing_feed_tokens.py

feed_key = self.normalizer.feed_key(token)

From example_2_mcx_quantities_in_lots.py

feed_key = self.normalizer.feed_key(token)

Source code in stock_brokers/instruments/ticks/stoxkart.py

def feed_key(self, instrument_token):
    """Reads the broker token and segments out of a Stoxkart `EXCHANGE:TOKEN`.

    Args:
        instrument_token (str): The tick's `instrument_token`, such as `NSE:760946`.

    Returns:
        FeedKey | None: The key, or None for a malformed token or an unknown exchange.
    """
    exchange, _, token = str(instrument_token).partition(":")
    segments = self._segments.get(exchange.strip().upper())
    if segments is None or not token.strip():
        return None
    return FeedKey(token.strip(), segments)

tick_spelling

tick_spelling(subscription_token)

A subscription-set token spelled the way the feed spells it on ticks.

Plans are filed under the tick's spelling, because that is what the per-tick path looks up. A subscription set holds strings in the spelling the broker's quote feed subscribes with, which is not always the tick's: Kite ticks carry an integer, Dhan ticks a numeric segment code.

Parameters:

Name	Type	Description	Default
subscription_token	str	A member of subscriptions_<broker>.	required

Returns:

Type	Description
int | str | None	The tick's spelling, or None for a token this normalizer cannot place.

Example usage

From example_1_a_new_broker_subclass.py

print(f"Tick spelling of 'NSE-2885': {self.normalizer.tick_spelling('NSE-2885')!r}")

Source code in stock_brokers/instruments/ticks/base.py

def tick_spelling(self, subscription_token):
    """
    A subscription-set token spelled the way the feed spells it on ticks.

    Plans are filed under the tick's spelling, because that is what the per-tick path looks up.
    A subscription set holds strings in the spelling the broker's quote feed subscribes with, which is
    not always the tick's: Kite ticks carry an integer, Dhan ticks a numeric segment code.

    Args:
        subscription_token (str): A member of `subscriptions_<broker>`.

    Returns:
        int | str | None: The tick's spelling, or None for a token this normalizer cannot place.
    """
    return subscription_token

quantity_basis

quantity_basis(exchange, field)

Whether the broker reports a quantity field in lots or units on an exchange.

Parameters:

Name	Type	Description	Default
exchange	str	Canonical exchange.	required
field	str	One of QUANTITY_FIELDS.	required

Returns:

Type	Description
str	BASIS_UNITS, BASIS_LOTS or BASIS_BROKER_LOTS.

Example usage

From example_1_a_new_broker_subclass.py

basis = self.normalizer.quantity_basis(exchange, field)

From example_2_what_normalize_refuses.py

self.normalizer.quantity_basis(exchange, field)

Source code in stock_brokers/instruments/ticks/base.py

def quantity_basis(self, exchange, field):
    """
    Whether the broker reports a quantity field in lots or units on an exchange.

    Args:
        exchange (str): Canonical exchange.
        field (str): One of QUANTITY_FIELDS.

    Returns:
        str: BASIS_UNITS, BASIS_LOTS or BASIS_BROKER_LOTS.
    """
    if field in self.BROKER_LOT_FIELDS.get(exchange, ()):
        return BASIS_BROKER_LOTS
    if field in self.LOT_FIELDS.get(exchange, ()):
        return BASIS_LOTS
    return BASIS_UNITS

close_policy

close_policy(exchange)

When the broker's close is the previous session's close on an exchange.

Parameters:

Name	Type	Description	Default
exchange	str	Canonical exchange.	required

Returns:

Type	Description
str	One of the CLOSE_* policies.

Example usage

From example_1_a_new_broker_subclass.py

print(f'{exchange} close policy: {self.normalizer.close_policy(exchange)}')

From example_2_what_normalize_refuses.py

return InstrumentPlan(
    instrument_id='11111111-1111-5111-8111-000000000102',
    broker='imaginary',
    broker_token='2885',
    exchange=exchange,
    segment=segment,
    shape=shape,
    session=sessions.session_for(segment),
    lot_size=lot_size,
    multipliers=multipliers,
    price_decimals=2,
    negative_prices=shape != 'security' and exchange == 'mcx',
    close_policy=self.normalizer.close_policy(exchange),
    has_open_interest=shape != 'security',
    trusts_last_trade_time=True,
    trusts_exchange_time=True,
    identity_json='"instrument_id":"11111111-1111-5111-8111-000000000102"',
)

Source code in stock_brokers/instruments/ticks/base.py

def close_policy(self, exchange):
    """
    When the broker's `close` is the previous session's close on an exchange.

    Args:
        exchange (str): Canonical exchange.

    Returns:
        str: One of the CLOSE_* policies.
    """
    return self.CLOSE_POLICY.get(exchange, CLOSE_NEVER)

normalize

normalize(tick, plan, before_trading_close)

Apply a plan to one tick.

Parameters:

Name	Type	Description	Default
tick	dict	A tick as the broker's market feed published it.	required
plan	InstrumentPlan	The compiled plan for the tick's token.	required
before_trading_close	bool	Whether the tick was received before its session's close, for the close policy.	required

Returns:

Type	Description
dict | None	The normalized values, or None when the tick carries no usable last price. Keys are last_price, last_quantity, average_price, volume, buy_quantity, sell_quantity, open, high, low, reported_close, oi, oi_day_high, oi_day_low, last_trade_time, exchange_time, bids and asks, where bids and asks are lists of (price, quantity, orders) best first.

Example usage

From example_2_what_normalize_refuses.py

values = self.normalizer.normalize(tick, share, True)

From example_2_what_normalize_refuses.py

values = self.normalizer.normalize(
    {
        'last_price': -12.5,
        'volume': 400,
        'oi': 900,
        'received_at': self.received_at,
    },
    future,
    True,
)

From example_2_what_normalize_refuses.py

outcome = self.normalizer.normalize(
    {
        'last_price': last_price,
        'received_at': self.received_at,
    },
    share,
    True,
)

Source code in stock_brokers/instruments/ticks/base.py

def normalize(self, tick, plan, before_trading_close):
    """
    Apply a plan to one tick.

    Args:
        tick (dict): A tick as the broker's market feed published it.
        plan (InstrumentPlan): The compiled plan for the tick's token.
        before_trading_close (bool): Whether the tick was received before its session's close, for the close policy.

    Returns:
        dict | None: The normalized values, or None when the tick carries no usable last price. Keys are last_price, last_quantity, average_price, volume, buy_quantity, sell_quantity, open, high, low, reported_close, oi, oi_day_high, oi_day_low, last_trade_time, exchange_time, bids and asks, where bids and asks are lists of (price, quantity, orders) best first.
    """
    decimals = plan.price_decimals
    negative = plan.negative_prices

    last_price = tick.get("last_price")
    if last_price is None or last_price == 0 or (last_price < 0 and not negative):
        return None
    last_price = round(last_price, decimals)

    multipliers = plan.multipliers
    received_at = tick.get("received_at") or 0.0
    ohlc = tick.get("ohlc") or {}

    close = None
    policy = plan.close_policy
    if policy == CLOSE_ALWAYS or (policy == CLOSE_BEFORE_SESSION_END and before_trading_close):
        close = _price(ohlc.get("close"), decimals, negative)

    if plan.has_open_interest:
        oi = _quantity(tick.get("oi"), multipliers["oi"])
        oi_day_high = _quantity(tick.get("oi_day_high") or None, multipliers["oi_day_high"])
        oi_day_low = _quantity(tick.get("oi_day_low") or None, multipliers["oi_day_low"])
    else:
        oi = oi_day_high = oi_day_low = None

    depth = tick.get("depth") or {}
    depth_multiplier = multipliers["depth_quantity"]

    return {
        "last_price": last_price,
        "last_quantity": _quantity(tick.get("last_quantity"), multipliers["last_quantity"]),
        "average_price": _price(tick.get("average_price"), decimals, negative),
        "volume": _quantity(tick.get("volume"), multipliers["volume"]),
        "buy_quantity": _quantity(tick.get("buy_quantity"), multipliers["buy_quantity"]),
        "sell_quantity": _quantity(tick.get("sell_quantity"), multipliers["sell_quantity"]),
        "open": _price(ohlc.get("open"), decimals, negative),
        "high": _price(ohlc.get("high"), decimals, negative),
        "low": _price(ohlc.get("low"), decimals, negative),
        "reported_close": close,
        "oi": oi,
        "oi_day_high": oi_day_high,
        "oi_day_low": oi_day_low,
        "last_trade_time": self._instant(tick.get("last_trade_time"), received_at) if plan.trusts_last_trade_time else None,
        "exchange_time": self._instant(tick.get("exchange_timestamp"), received_at) if plan.trusts_exchange_time else None,
        "bids": _levels(depth.get("buy"), decimals, negative, depth_multiplier),
        "asks": _levels(depth.get("sell"), decimals, negative, depth_multiplier),
    }

_instant

_instant(value, received_at)

A broker timestamp as a true epoch, or None when it is missing or implausible.

Brokers that stamp times on a shifted clock have that corrected in their market feed; what is left to catch here is a clock nobody has corrected yet, which shows as an instant days away from when the tick arrived.

Parameters:

Name	Type	Description	Default
value	float | int | None	Epoch seconds as the feed published them.	required
received_at	float	When the feed decoded the tick.	required

Returns:

Type	Description
float | None	The instant, or None.

Source code in stock_brokers/instruments/ticks/base.py

def _instant(self, value, received_at):
    """
    A broker timestamp as a true epoch, or None when it is missing or implausible.

    Brokers that stamp times on a shifted clock have that corrected in their market feed; what is
    left to catch here is a clock nobody has corrected yet, which shows as an instant days away
    from when the tick arrived.

    Args:
        value (float | int | None): Epoch seconds as the feed published them.
        received_at (float): When the feed decoded the tick.

    Returns:
        float | None: The instant, or None.
    """
    if not value:
        return None
    try:
        instant = float(value)
    except (TypeError, ValueError):
        return None
    if received_at and not (received_at - self.MAXIMUM_TIMESTAMP_AGE_SECONDS
                            <= instant <= received_at + self.MAXIMUM_TIMESTAMP_LEAD_SECONDS):
        return None
    return instant