groww

Groww ticks.

Groww names an instrument as EXCHANGE|SEGMENT|EXCHANGE_TOKEN - NSE|CASH|2885, NSE|FNO|35001 - and stores the bare exchange token, which collides across segments, so the exchange and segment narrow the search. Its feed publishes NSE and BSE cash and derivatives only; Groww is still the authority on MCX lot sizes, from its instrument file, whether or not its feed streams MCX.

Nothing Groww streams is stored yet - its raw tick table is empty - so the broker stays unverified until a live session, and two things are read conservatively:

• close is not taken as the previous close. The protobuf field is named only close, and at two of the brokers measured a field of that name turns into the day's own close after the session. The previous close comes from an earlier owner's tick the same day instead.
• Quantities are taken to be units, which is what NSE and BSE report and what every broker measured on those exchanges sends.

The book carries no order counts, and the feed sends no last trade time or last quantity; those fields are null rather than guessed.

Classes:

Name	Description
GrowwTickNormalizer	Normalizes Groww ticks.

GrowwTickNormalizer

GrowwTickNormalizer()

Bases: TickNormalizer

Normalizes Groww ticks.

Build the lookup from each Groww exchange prefix and segment to the canonical segments it can hold.

Every exchange in EXCHANGES is paired with every segment in SEGMENTS, so feed_key only has to look a tick's exchange and segment up rather than recompute its segments on every call.

Example programs

Placing feed tokensUntrusted time and close

examples/stock_brokers/instruments/ticks/groww/GrowwTickNormalizer/example_1_placing_feed_tokens.py

"""Places Groww feed tokens, spelled `EXCHANGE|SEGMENT|TOKEN`, on the canonical segments they can be in.

A Groww token has three parts: the exchange, Groww's own segment and the exchange token. Indices arrive on the CASH segment, so a CASH token is searched among both share and index segments. FNO and COMMODITY are derivatives. A token without all three parts, or with an exchange Groww 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/groww/GrowwTickNormalizer/example_1_placing_feed_tokens.py
"""

from stock_brokers.instruments.ticks.groww import (
    GrowwTickNormalizer,
)


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

    Attributes:
        normalizer (GrowwTickNormalizer): 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 = GrowwTickNormalizer()
        self.tokens = [
            'NSE|CASH|2885',
            'BSE|CASH|500325',
            'NSE|FNO|35003',
            'MCX|COMMODITY|440001',
            'NSE|2885',
            'NYSE|CASH|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: {GrowwTickNormalizer.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: groww
'NSE|CASH|2885' -> broker_token='2885' order_symbol=None segments=10 starting with nse_equities
'BSE|CASH|500325' -> broker_token='500325' order_symbol=None segments=10 starting with bse_equities
'NSE|FNO|35003' -> broker_token='35003' order_symbol=None segments=16 starting with nse_fixed_income_futures
'MCX|COMMODITY|440001' -> broker_token='440001' order_symbol=None segments=16 starting with mcx_fixed_income_futures
'NSE|2885' -> None
'NYSE|CASH|1' -> None

examples/stock_brokers/instruments/ticks/groww/GrowwTickNormalizer/example_2_untrusted_time_and_close.py

"""Normalizes one Groww tick for RELIANCE on NSE, whose last trade time and close are not trusted.

Groww's last trade time is not a true instant, so the normalizer leaves `last_trade_time` as None and keeps only the exchange time. Its `close` is never the previous session's close, so `reported_close` is None both before and after the session ends; the unified pipeline takes the previous close from elsewhere.

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/groww/GrowwTickNormalizer/example_2_untrusted_time_and_close.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.groww import (
    GrowwTickNormalizer,
)
from stock_brokers.instruments.ticks.utilities import sessions

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


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

    Attributes:
        normalizer (GrowwTickNormalizer): 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 = GrowwTickNormalizer()
        received = datetime.datetime(2026, 9, 15, 11, 5, tzinfo=INDIA)
        self.received_at = received.timestamp()
        self.tick = {
            'instrument_token': 'NSE|CASH|2885',
            'last_price': 1262.7,
            'last_quantity': 15,
            'average_price': 1263.84,
            'volume': 1885670,
            'buy_quantity': 402113,
            'sell_quantity': 388921,
            'ohlc': {
                'open': 1266.4,
                'high': 1267.4,
                'low': 1261.5,
                'close': 1262.7,
            },
            'oi': None,
            'oi_day_high': None,
            'oi_day_low': None,
            'last_trade_time': self.received_at - 2.0,
            'exchange_timestamp': self.received_at - 1.0,
            'received_at': self.received_at,
            'depth': {
                'buy': [
                    {
                        'price': 1262.6,
                        'quantity': 120,
                        'orders': 4,
                    },
                    {
                        'price': 1262.5,
                        'quantity': 340,
                        'orders': 9,
                    },
                ],
                'sell': [
                    {
                        'price': 1262.7,
                        'quantity': 95,
                        'orders': 3,
                    },
                    {
                        'price': 1262.8,
                        'quantity': 210,
                        'orders': 6,
                    },
                ],
            },
        }
        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 = 'nse'
        segment = 'nse_equities'
        lot_size = 1
        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': 'nse',
            'segment': 'nse_equities',
            'shape': 'security',
            'symbol': 'RELIANCE',
            'underlying_symbol': None,
            'expiry_date': None,
            'strike_price': None,
            'option_type': None,
        }
        instrument_id = '11111111-1111-5111-8111-000000000102'
        broker_token = '2885'
        return InstrumentPlan(
            instrument_id=instrument_id,
            broker=GrowwTickNormalizer.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=False,
            close_policy=self.normalizer.close_policy(exchange),
            has_open_interest=identity['shape'] != 'security',
            trusts_last_trade_time=GrowwTickNormalizer.TRUSTS_LAST_TRADE_TIME,
            trusts_exchange_time=GrowwTickNormalizer.TRUSTS_EXCHANGE_TIME,
            identity_json=base.identity_json(
                instrument_id,
                GrowwTickNormalizer.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__':
    RelianceTickExample().run()

It prints:

Token 'NSE|CASH|2885': broker_token='2885' order_symbol=None
Volume on nse is reported in units, multiplier 1
Close policy on nse: never
Normalized, received before the close:
  last_price: 1262.7
  last_quantity: 15
  average_price: 1263.84
  volume: 1885670
  buy_quantity: 402113
  sell_quantity: 388921
  open: 1266.4
  high: 1267.4
  low: 1261.5
  reported_close: None
  oi: None
  oi_day_high: None
  oi_day_low: None
  last_trade_time: None
  exchange_time: 1789450499.0
  bids: [(1262.6, 120, 4), (1262.5, 340, 9)]
  asks: [(1262.7, 95, 3), (1262.8, 210, 6)]
reported_close when received after the close: None

Methods:

Name	Description
feed_key	The broker token and segments for a Groww EXCHANGE|SEGMENT|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/groww.py

def __init__(self):
    """
    Build the lookup from each Groww exchange prefix and segment to the canonical segments it can hold.

    Every exchange in `EXCHANGES` is paired with every segment in `SEGMENTS`, so `feed_key` only has to look a tick's exchange and segment up rather than recompute its segments on every call.
    """
    self._segments = {(prefix, segment): family_segments([exchange], family)
                      for prefix, exchange in self.EXCHANGES.items()
                      for segment, family in self.SEGMENTS.items()}

feed_key

feed_key(instrument_token)

The broker token and segments for a Groww EXCHANGE|SEGMENT|EXCHANGE_TOKEN.

Parameters:

Name	Type	Description	Default
instrument_token	str	The tick's instrument_token, such as "NSE|CASH|2885".	required

Returns:

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

Example usage

From example_1_placing_feed_tokens.py

feed_key = self.normalizer.feed_key(token)

From example_2_untrusted_time_and_close.py

feed_key = self.normalizer.feed_key(token)

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

def feed_key(self, instrument_token):
    """
    The broker token and segments for a Groww `EXCHANGE|SEGMENT|EXCHANGE_TOKEN`.

    Args:
        instrument_token (str): The tick's `instrument_token`, such as "NSE|CASH|2885".

    Returns:
        FeedKey | None: The key, or None for a malformed token or an unknown exchange or segment.
    """
    parts = [part.strip() for part in str(instrument_token).split("|")]
    if len(parts) != 3 or not parts[2]:
        return None
    segments = self._segments.get((parts[0].upper(), parts[1].upper()))
    if segments is None:
        return None
    return FeedKey(parts[2], 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