Skip to content

zerodha

Zerodha historical candle download.

Kite serves candles at /instruments/historical/{token}/{interval}, three requests a second, and goes back to 2005 for daily bars on long listed equities. oi=1 is always sent: for cash it changes nothing, and for derivatives it adds open interest as a seventh element, so the response is read by length rather than by fixed index.

Two behaviours are worth knowing. Kite caps how far one request may reach, and the cap differs by interval - sixty days for minute bars, two thousand for daily - which is what makes a deep backfill a walk rather than a single call. And an instrument that has left the current instrument dump is refused with invalid token rather than an empty response, so an expired contract's history is unreachable the moment it expires; the series is retired instead of retried.

Classes:

Name Description
ZerodhaCandles

Downloads Zerodha's historical candles.

ZerodhaCandles 

ZerodhaCandles(api=None)

Bases: BrokerCandles

Downloads Zerodha's historical candles.

Zerodha candle downloader.

  • api is an authenticated ZerodhaAPI. One is constructed when not supplied, which establishes a session if the stored one has expired.

Example programs

examples/stock_brokers/instruments/historical/zerodha/ZerodhaCandles/example_1_fetching_five_minute_bars.py
"""Fetches one window of five minute RELIANCE futures bars from Kite and reads them into stored bars.

A `ZerodhaCandles` downloader is normally built with no arguments, and its constructor then opens a PostgreSQL connection for the progress table and logs in to Kite if the stored session has expired. Neither is wanted here, so the program builds the object without running its constructor, exactly as the offline suite `test_runs/candle_parse.py` does, and gives it a stand-in for the `ZerodhaAPI` object it would otherwise hold. `fetch_candles` and `parse_response` need nothing else.

The stand-in records the URL and query parameters it is asked for and answers with a response shaped like the one Kite returned on 2026-09-11, wrapped in the `status_code` and `data` envelope the real API class returns. Notice three things in the output: the stored interval name `5minute` is sent to Kite as `5minute` while `1minute` would have been sent as `minute`, `oi=1` is always asked for, and the seventh element of each candle becomes the bar's open interest.

Run it from the project root:

    python examples/stock_brokers/instruments/historical/zerodha/ZerodhaCandles/example_1_fetching_five_minute_bars.py
"""

import datetime

from stock_brokers.instruments.historical.zerodha import (
    ZerodhaCandles,
)


class RecordedKiteAPI:
    """A stand-in for `ZerodhaAPI` that answers every request with one recorded candle response.

    Attributes:
        requests (list): The (url, parameters) pairs it was asked for.
    """

    def __init__(self):
        """Builds the stand-in with no requests recorded.

        Returns:
            None: This method returns nothing.
        """
        self.requests = []

    def get(self, url, params=None):
        """Records a GET request and answers it with recorded candles.

        Args:
            url (str): The URL the downloader asked for.
            params (dict): The query parameters it sent.

        Returns:
            dict: The response envelope, with the candles under `data`.
        """
        self.requests.append((url, params))
        return {
            'status_code': 200,
            'data': {
                'candles': [
                    [
                        '2026-09-11T09:15:00+0530',
                        1285.0,
                        1291.0,
                        1283.6,
                        1290.5,
                        225000,
                        128846500,
                    ],
                    [
                        '2026-09-11T09:20:00+0530',
                        1290.5,
                        1292.2,
                        1288.1,
                        1289.0,
                        98500,
                        128901000,
                    ],
                ],
            },
        }


class FetchingFiveMinuteBarsExample:
    """Asks for one window of five minute bars and prints the request and the bars.

    Attributes:
        api (RecordedKiteAPI): The stand-in Kite API.
        candles (ZerodhaCandles): The downloader being shown.
    """

    def __init__(self):
        """Builds the downloader around the stand-in API without opening a database connection.

        Returns:
            None: This method returns nothing.
        """
        self.api = RecordedKiteAPI()
        self.candles = object.__new__(ZerodhaCandles)
        self.candles._api = self.api

    def run(self):
        """Fetches the window, parses it and prints what was sent and what came back.

        Returns:
            None: This method returns nothing.
        """
        payload = self.candles.fetch_candles(
            '13368834',
            '5minute',
            datetime.date(2026, 9, 11),
            datetime.date(2026, 9, 11),
        )
        url, parameters = self.api.requests[0]
        print(f'Requested: {url}')
        print(f'Parameters: {parameters}')
        print(f'Candles in the payload: {len(payload["candles"])}')
        bars = self.candles.parse_response(payload, '5minute')
        for bar in bars:
            bar_time, open_price, high, low, close, volume, open_interest = bar
            print(f'{bar_time.isoformat()} open {open_price} high {high} low {low} close {close} volume {volume} oi {open_interest}')
        print(f'Kite name for 1minute: {ZerodhaCandles.INTERVALS["1minute"]}')


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

It prints:

Requested: https://api.kite.trade/instruments/historical/13368834/5minute
Parameters: {'from': '2026-09-11', 'to': '2026-09-11', 'oi': 1}
Candles in the payload: 2
2026-09-11T09:15:00+05:30 open 1285.0 high 1291.0 low 1283.6 close 1290.5 volume 225000 oi 128846500
2026-09-11T09:20:00+05:30 open 1290.5 high 1292.2 low 1288.1 close 1289.0 volume 98500 oi 128901000
Kite name for 1minute: minute
examples/stock_brokers/instruments/historical/zerodha/ZerodhaCandles/example_2_tokens_day_bars_and_refusals.py
"""Reads what a Kite instrument token says about its instrument, collapses a day bar onto its trading date, and shows an expired contract being refused.

Kite packs the exchange segment into the low byte of every instrument token and the exchange's own token into the bits above it, so RELIANCE on NSE is 738561, which is 2885 shifted left by eight bits with segment 1 in the low byte. `series_context` and `exchange_token` read that without any session, because they are a classmethod and a staticmethod. The program reads three tokens: NSE cash RELIANCE, the NIFTY 50 index (segment 9, which holds both exchanges' indices, so no exchange is named) and a token whose segment code Kite does not use.

It then parses a day bar stamped midnight India time, which `daily_bar_time` leaves on the same date, and skips a candle that is too short to read. Finally it fetches from a stand-in for `ZerodhaAPI` that raises the `ZerodhaAPIException` Kite's `invalid token` answer produces, which is what an instrument that has left the instrument dump gets. `fetch_candles` turns that into `CandleInstrumentUnknown`, the signal that retires the series rather than retrying it. The downloader is built without its constructor, as in `test_runs/candle_parse.py`, so no database connection is opened and no login happens.

Run it from the project root:

    python examples/stock_brokers/instruments/historical/zerodha/ZerodhaCandles/example_2_tokens_day_bars_and_refusals.py
"""

import datetime

from stock_brokers.api.zerodha import (
    ZerodhaAPIException,
)
from stock_brokers.instruments.historical.base import (
    CandleInstrumentUnknown,
)
from stock_brokers.instruments.historical.zerodha import (
    ZerodhaCandles,
)


class RefusingKiteAPI:
    """A stand-in for `ZerodhaAPI` that refuses every request the way Kite refuses an expired contract."""

    def get(self, url, params=None):
        """Refuses a GET request with Kite's invalid token error.

        Args:
            url (str): The URL the downloader asked for.
            params (dict): The query parameters it sent.

        Returns:
            dict: Never returns.

        Raises:
            ZerodhaAPIException: Always, with Kite's `InputException` code.
        """
        raise ZerodhaAPIException(code='InputException', message='invalid token')


class TokensDayBarsAndRefusalsExample:
    """Reads tokens, parses a day bar and handles a refused window.

    Attributes:
        candles (ZerodhaCandles): The downloader being shown.
    """

    def __init__(self):
        """Builds the downloader around the refusing stand-in without opening a database connection.

        Returns:
            None: This method returns nothing.
        """
        self.candles = object.__new__(ZerodhaCandles)
        self.candles._api = RefusingKiteAPI()

    def show_tokens(self):
        """Prints what each of three tokens says about its instrument.

        Returns:
            None: This method returns nothing.
        """
        tokens = [
            '738561',
            '256265',
            '738560',
        ]
        for token in tokens:
            context = ZerodhaCandles.series_context(token)
            if context.segments:
                segments = f'{len(context.segments)} segments starting {context.segments[0]}'
            else:
                segments = 'any segment'
            print(f'{token}: exchange {context.exchange}, {segments}, exchange token {context.exchange_token}')
        print(f'Exchange token inside 738561: {ZerodhaCandles.exchange_token("738561")}')

    def show_day_bars(self):
        """Parses a day bar and a candle too short to read.

        Returns:
            None: This method returns nothing.
        """
        payload = {
            'candles': [
                [
                    '2026-09-11T00:00:00+0530',
                    1267.0,
                    1267.4,
                    1253.0,
                    1257.5,
                    8777736,
                ],
                [
                    '2026-09-12T00:00:00+0530',
                    1257.5,
                ],
            ],
        }
        bars = self.candles.parse_response(payload, 'day')
        print(f'Day bars read: {len(bars)} of {len(payload["candles"])}')
        print(f'Day bar time: {bars[0][0].isoformat()}, close {bars[0][4]}, open interest {bars[0][6]}')

    def show_refusal(self):
        """Fetches a window of an expired contract and prints how the refusal is classified.

        Returns:
            None: This method returns nothing.
        """
        try:
            self.candles.fetch_candles(
                '13368834',
                'day',
                datetime.date(2026, 1, 1),
                datetime.date(2026, 9, 11),
            )
        except CandleInstrumentUnknown as error:
            print(f'Refused as {type(error).__name__}: {error}')

    def run(self):
        """Runs the three parts in turn.

        Returns:
            None: This method returns nothing.
        """
        self.show_tokens()
        self.show_day_bars()
        self.show_refusal()


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

It prints:

738561: exchange nse, 6 segments starting nse_equities, exchange token 2885
256265: exchange None, 8 segments starting nse_equity_indices, exchange token None
738560: exchange None, any segment, exchange token None
Exchange token inside 738561: 2885
Day bars read: 1 of 2
Day bar time: 2026-09-11T00:00:00+05:30, close 1257.5, open interest None
Refused as CandleInstrumentUnknown: ('InputException', 'invalid token')

Methods:

Name Description
series_context

Read the exchange and segment out of a Kite instrument token.
exchange_token

The exchange's own token inside a Kite instrument token.
fetch_candles

Fetch one window of Kite candles.
parse_response

Turn Kite's candle list into bars.
instruments

Every instrument this broker has ever published, with the fields priority needs.
priority_for

Where a series sits in the queue. Lower is worked first.
seed

Make sure every instrument and interval this broker serves has a progress row.
claim

The next series due for a window, or None when there is nothing to do.
next_window

The date range to ask for next, as a (start, end, direction) triple.
relogin

Establish a fresh session and rebuild everything built on the old one.
after_relogin

Re-establish anything a downloader keeps on top of the broker session. Nothing by default.
visit

Fetch one window for one series and store it, advancing the watermark.
run

Work the queue until stopped, out of work, or out of time.
summary

How far the download has got, for a status display.
close

Close the database connection.
Source code in stock_brokers/instruments/historical/zerodha.py 
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
def __init__(self, api=None):
    """
    Zerodha candle downloader.

    - `api` is an authenticated `ZerodhaAPI`. One is constructed when not supplied, which
      establishes a session if the stored one has expired.
    """
    super().__init__()
    if api is None:
        from stock_brokers.api.utilities.session import ensure_session
        from stock_brokers.api.zerodha import ZerodhaAPI

        # Through ensure_session rather than straight to ZerodhaAPI, so this shares the Redis
        # lock and the rate limiter with any other process using ensure_session. Kite issues one
        # access token per session and a second login invalidates the first, and this process
        # runs for weeks - it will be alive across the overnight expiry, when another process may
        # be logging in too. Without the lock one of the two ends up holding a replaced token.
        ensure_session(self.BROKER_NAME, logger=self._logger)
        api = ZerodhaAPI()
    self._api = api

series_context classmethod 

series_context(identifier)

Read the exchange and segment out of a Kite instrument token.

Parameters:

Name Type Description Default
identifier str

A Kite instrument token, for example "738561".

 required

Returns:

Type Description
SeriesContext

The token itself, with the exchange and segments its low byte names.

Example usage

From example_2_tokens_day_bars_and_refusals.py
context = ZerodhaCandles.series_context(token)
Source code in stock_brokers/instruments/historical/zerodha.py 
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
@classmethod
def series_context(cls, identifier):
    """
    Read the exchange and segment out of a Kite instrument token.

    Args:
        identifier (str): A Kite instrument token, for example "738561".

    Returns:
        SeriesContext: The token itself, with the exchange and segments its low byte names.
    """
    token = str(identifier)
    exchange, family = cls.SEGMENT_CODES.get(int(token) & 255, (None, None))
    if family is None:
        return SeriesContext(token)
    if exchange is None:
        return SeriesContext(token, None, segments_of(["nse", "bse"], family))
    return SeriesContext(token, exchange, segments_of([exchange], family),
                         exchange_token=cls.exchange_token(token))

exchange_token staticmethod 

exchange_token(identifier)

The exchange's own token inside a Kite instrument token.

Parameters:

Name Type Description Default
identifier str

A Kite instrument token.

 required

Returns:

Type Description
str

The exchange token, for example "2885" for 738561.

Example usage

From example_2_tokens_day_bars_and_refusals.py
print(f'Exchange token inside 738561: {ZerodhaCandles.exchange_token("738561")}')
Source code in stock_brokers/instruments/historical/zerodha.py 
128
129
130
131
132
133
134
135
136
137
138
139
@staticmethod
def exchange_token(identifier):
    """
    The exchange's own token inside a Kite instrument token.

    Args:
        identifier (str): A Kite instrument token.

    Returns:
        str: The exchange token, for example "2885" for 738561.
    """
    return str(int(identifier) >> 8)

fetch_candles 

fetch_candles(token, interval, start_date, end_date)

Fetch one window of Kite candles.

  • token is the Kite instrument token.
  • interval is the stored interval name.
  • start_date and end_date bound the window, inclusive.

Example usage

From example_1_fetching_five_minute_bars.py
payload = self.candles.fetch_candles(
    '13368834',
    '5minute',
    datetime.date(2026, 9, 11),
    datetime.date(2026, 9, 11),
)
From example_2_tokens_day_bars_and_refusals.py
self.candles.fetch_candles(
    '13368834',
    'day',
    datetime.date(2026, 1, 1),
    datetime.date(2026, 9, 11),
)
Source code in stock_brokers/instruments/historical/zerodha.py 
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
def fetch_candles(self, token, interval, start_date, end_date):
    """
    Fetch one window of Kite candles.

    - `token` is the Kite instrument token.
    - `interval` is the stored interval name.
    - `start_date` and `end_date` bound the window, inclusive.
    """
    url = f"{HISTORICAL_URL}/{token}/{self.INTERVALS[interval]}"
    parameters = {"from": start_date.isoformat(), "to": end_date.isoformat(), "oi": 1}

    try:
        response = self._api.get(url=url, params=parameters)
    except Exception as exception:
        raise self._classify(exception) from exception

    return (response or {}).get("data") or {}

_classify staticmethod 

_classify(exception)

Decide what a Kite error means for the series being downloaded.

The distinction that matters is between "this instrument will never work", which retires the series, and everything else, which is retried with backoff. Kite reports the first as an InputException naming an invalid token.

  • exception is what the API call raised.
Source code in stock_brokers/instruments/historical/zerodha.py 
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
@staticmethod
def _classify(exception):
    """
    Decide what a Kite error means for the series being downloaded.

    The distinction that matters is between "this instrument will never work", which retires
    the series, and everything else, which is retried with backoff. Kite reports the first as
    an InputException naming an invalid token.

    - `exception` is what the API call raised.
    """
    text = str(exception).lower()

    if "invalid token" in text or "invalid instrument" in text:
        return CandleInstrumentUnknown(str(exception)[:200])
    if "too many requests" in text or "429" in text:
        return CandleThrottled(str(exception)[:200])
    if ("tokenexception" in text or "invalid api" in text
            or "incorrect `api_key`" in text or "access_token" in text):
        return CandleAuthenticationError(str(exception)[:200])
    return exception

parse_response 

parse_response(payload, interval)

Turn Kite's candle list into bars.

Kite returns [timestamp, open, high, low, close, volume], and a seventh element for open interest when oi=1 applies. Read by length: a cash instrument simply has six.

  • payload is the data object from the response.
  • interval is the stored interval name, which decides whether the bar time is left alone or collapsed onto its trading date.

Example usage

From example_1_fetching_five_minute_bars.py
bars = self.candles.parse_response(payload, '5minute')
From example_2_tokens_day_bars_and_refusals.py
bars = self.candles.parse_response(payload, 'day')
Source code in stock_brokers/instruments/historical/zerodha.py 
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
def parse_response(self, payload, interval):
    """
    Turn Kite's candle list into bars.

    Kite returns `[timestamp, open, high, low, close, volume]`, and a seventh element for
    open interest when `oi=1` applies. Read by length: a cash instrument simply has six.

    - `payload` is the `data` object from the response.
    - `interval` is the stored interval name, which decides whether the bar time is left
      alone or collapsed onto its trading date.
    """
    bars = []
    for candle in (payload or {}).get("candles") or []:
        if len(candle) < 6:
            continue
        # Kite sends ISO-8601 with an offset, "2026-09-01T00:00:00+0530". Parsed here rather
        # than left as text so the stored bar time and the watermark read back from Postgres
        # are the same kind of thing and can be compared.
        try:
            bar_time = datetime.datetime.fromisoformat(candle[0])
        except (TypeError, ValueError):
            continue
        if not is_intraday(interval):
            # Kite already stamps midnight India time, so this changes nothing for Zerodha.
            # It is applied anyway so that every broker's day bar is normalised in the same
            # place, and a reader does not have to know Kite's convention to trust the row.
            bar_time = daily_bar_time(bar_time)
        open_interest = candle[6] if len(candle) > 6 else None
        bars.append((bar_time, candle[1], candle[2], candle[3], candle[4],
                     candle[5], open_interest))
    return bars

instruments 

instruments()

Every instrument this broker has ever published, with the fields priority needs.

The most recent snapshot each token appeared in, not merely today's: a contract that expired last month is still worth asking about, and the answer decides whether it is retired. Today's snapshot alone would silently narrow the universe to whatever is live.

Example usage

From example_1_one_window_of_daily_bars.py
self.downloader.instruments()
Source code in stock_brokers/instruments/historical/base.py 
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
def instruments(self):
    """
    Every instrument this broker has ever published, with the fields priority needs.

    The most recent snapshot each token appeared in, not merely today's: a contract that
    expired last month is still worth asking about, and the answer decides whether it is
    retired. Today's snapshot alone would silently narrow the universe to whatever is live.
    """
    query = f"""
        select distinct on (i."{self.TOKEN_COLUMN}")
               i."{self.TOKEN_COLUMN}", i."{self.TYPE_COLUMN}", i."{self.EXPIRY_COLUMN}"
        from {self.BROKER_NAME}.instruments i
        where i."{self.TOKEN_COLUMN}" is not null and i."{self.TOKEN_COLUMN}" <> ''
        order by i."{self.TOKEN_COLUMN}", i.download_date desc
    """
    with self._connection.cursor() as cursor:
        cursor.execute(query)
        return cursor.fetchall()

priority_for 

priority_for(instrument_type, expiry, interval)

Where a series sits in the queue. Lower is worked first.

The ordering is the difference between useful data in days and useful data in months. Cash instruments come first because they have the deepest history and are wanted most; expired options come last because there are tens of thousands of them, each holding a few weeks of data, and most will be refused outright. Coarse intervals beat fine ones within each tier, since a day bar covers a year in one request and a minute bar covers two months.

  • instrument_type is the broker's own type string.
  • expiry is the contract expiry, or None for cash.
  • interval is the stored interval name.

Example usage

From example_1_one_window_of_daily_bars.py
priority = self.downloader.priority_for(instrument_type, expiry, interval)
Source code in stock_brokers/instruments/historical/base.py 
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
def priority_for(self, instrument_type, expiry, interval):
    """
    Where a series sits in the queue. Lower is worked first.

    The ordering is the difference between useful data in days and useful data in months.
    Cash instruments come first because they have the deepest history and are wanted most;
    expired options come last because there are tens of thousands of them, each holding a few
    weeks of data, and most will be refused outright. Coarse intervals beat fine ones within
    each tier, since a day bar covers a year in one request and a minute bar covers two
    months.

    - `instrument_type` is the broker's own type string.
    - `expiry` is the contract expiry, or None for cash.
    - `interval` is the stored interval name.
    """
    kind = (instrument_type or "").upper()
    expired = False
    if expiry:
        try:
            expired = datetime.date.fromisoformat(str(expiry)[:10]) < datetime.date.today()
        except ValueError:
            expired = False

    if not expiry:
        base = 10                                   # cash: equities, indices
    elif kind in ("FUT", "FUTSTK", "FUTIDX", "FUTCOM", "FUTCUR"):
        base = 80 if expired else 30
    else:
        base = 90 if expired else 60                # options, live or dead

    if interval in ("day", "week", "month"):
        return base
    minutes = self._interval_minutes(interval)
    return base + (5 if minutes >= 15 else 15)

_interval_minutes staticmethod 

_interval_minutes(interval)

Minutes in an interval name like 15minute, or 0 when it is not a minute interval.

  • interval is the stored interval name.
Source code in stock_brokers/instruments/historical/base.py 
389
390
391
392
393
394
395
396
397
398
399
400
401
@staticmethod
def _interval_minutes(interval):
    """
    Minutes in an interval name like `15minute`, or 0 when it is not a minute interval.

    - `interval` is the stored interval name.
    """
    if not interval.endswith("minute"):
        return 0
    try:
        return int(interval[:-len("minute")])
    except ValueError:
        return 0

seed 

seed()

Make sure every instrument and interval this broker serves has a progress row.

Safe to run again: existing rows are left exactly as they are, so re-seeding after a new instrument master picks up what is new without disturbing what is already downloaded. Returns how many rows were added.

Example usage

From example_1_one_window_of_daily_bars.py
print(f'Series added by the first seed: {self.downloader.seed()}')
From example_1_one_window_of_daily_bars.py
print(f'Series added by a second seed: {self.downloader.seed()}')
Source code in stock_brokers/instruments/historical/base.py 
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
def seed(self):
    """
    Make sure every instrument and interval this broker serves has a progress row.

    Safe to run again: existing rows are left exactly as they are, so re-seeding after a new
    instrument master picks up what is new without disturbing what is already downloaded.
    Returns how many rows were added.
    """
    instruments = self.instruments()
    if not instruments:
        self._logger.warning(f"No instruments for {self.BROKER_NAME}; nothing to seed. "
                             f"Has the instrument master been downloaded?")
        return 0

    today = datetime.date.today()
    considered = 0
    batch = []

    with self._connection.cursor() as cursor:
        # Counted by measuring the table, not by summing cursor.rowcount: execute_values
        # splits a batch into pages of its own, and rowcount then reports only the last page,
        # which made a complete seed of 1,149,064 rows announce itself as 22,964.
        cursor.execute(f"select count(*) from {self._progress_table}")
        before = cursor.fetchone()[0]

        # Written a batch at a time as the instruments are walked rather than assembled in
        # full first. Wisdom Capital alone is 372,545 instruments across thirteen intervals,
        # and holding all 4.8 million rows in memory to write them costs a gigabyte for
        # nothing.
        for token, instrument_type, expiry in instruments:
            for interval in self.INTERVALS:
                batch.append((str(token), interval,
                              self.priority_for(instrument_type, expiry, interval), today))
            considered += len(self.INTERVALS)
            if len(batch) >= WRITE_BATCH_ROWS:
                self._insert_series(cursor, batch)
                batch = []
        if batch:
            self._insert_series(cursor, batch)

        cursor.execute(f"select count(*) from {self._progress_table}")
        added = cursor.fetchone()[0] - before
    self._connection.commit()
    self._logger.info(f"Seeded {added} new series ({considered} considered).")
    return added

_insert_series 

_insert_series(cursor, batch)

Register one batch of series, leaving any that already exist exactly as they are.

  • cursor is an open cursor on this broker's connection.
  • batch is a list of (token, interval, priority, seeded_date) tuples.
Source code in stock_brokers/instruments/historical/base.py 
449
450
451
452
453
454
455
456
457
458
459
460
461
def _insert_series(self, cursor, batch):
    """
    Register one batch of series, leaving any that already exist exactly as they are.

    - `cursor` is an open cursor on this broker's connection.
    - `batch` is a list of `(token, interval, priority, seeded_date)` tuples.
    """
    execute_values(cursor, f"""
        insert into {self._progress_table}
            (instrument_token, "interval", priority, seeded_date)
        values %s
        on conflict (instrument_token, "interval") do nothing
    """, batch, page_size=WRITE_BATCH_ROWS)

claim 

claim()

The next series due for a window, or None when there is nothing to do.

Ordered by priority and then by how long a series has been waiting. Series that have reached the broker's limit, or that are backing off after failures, are skipped.

Example usage

From example_1_one_window_of_daily_bars.py
series = self.downloader.claim()
Source code in stock_brokers/instruments/historical/base.py 
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
def claim(self):
    """
    The next series due for a window, or None when there is nothing to do.

    Ordered by priority and then by how long a series has been waiting. Series that have
    reached the broker's limit, or that are backing off after failures, are skipped.
    """
    with self._connection.cursor() as cursor:
        cursor.execute(f"""
            select instrument_token, "interval", earliest_bar_time, latest_bar_time,
                   oldest_requested_time, empty_window_streak, consecutive_failures
            from {self._progress_table}
            where reached_broker_limit = false
              and consecutive_failures < %s
              and (next_attempt_after is null or next_attempt_after <= now())
            order by priority, last_attempt_at nulls first
            limit 1
        """, (MAXIMUM_CONSECUTIVE_FAILURES,))
        row = cursor.fetchone()
    self._connection.commit()
    return row

next_window 

next_window(series)

The date range to ask for next, as a (start, end, direction) triple.

The backward walk comes first and runs to completion. A series starts at today and steps back a window at a time until it reaches the broker's earliest date or the broker stops returning anything, and only then does it start filling forward with whatever has happened since.

Doing it the other way round - preferring forward whenever the last stored bar is older than today - looks reasonable and does not work: outside market hours the last bar is always older than today, so the series asks for the same empty recent window forever and never walks back at all.

  • series is a row from claim.

Example usage

From example_1_one_window_of_daily_bars.py
start_date, end_date, direction = self.downloader.next_window(series)
Source code in stock_brokers/instruments/historical/base.py 
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
def next_window(self, series):
    """
    The date range to ask for next, as a `(start, end, direction)` triple.

    The backward walk comes first and runs to completion. A series starts at today and steps
    back a window at a time until it reaches the broker's earliest date or the broker stops
    returning anything, and only then does it start filling forward with whatever has
    happened since.

    Doing it the other way round - preferring forward whenever the last stored bar is older
    than today - looks reasonable and does not work: outside market hours the last bar is
    always older than today, so the series asks for the same empty recent window forever and
    never walks back at all.

    - `series` is a row from `claim`.
    """
    _, interval, earliest, latest, oldest_requested, _, _ = series
    span = datetime.timedelta(days=self.MAXIMUM_WINDOW_DAYS.get(interval, 60) - 1)
    today = datetime.date.today()

    backward_done = (oldest_requested is not None
                     and oldest_requested.date() <= self.EARLIEST_AVAILABLE_DATE)

    if not backward_done:
        end = today if oldest_requested is None else (oldest_requested.date()
                                                      - datetime.timedelta(days=1))
        start = max(end - span, self.EARLIEST_AVAILABLE_DATE)
        if start > end:
            return None, None, "exhausted"
        return start, end, "backward"

    if latest is None:
        return None, None, "exhausted"
    start = latest.date()
    if start >= today:
        return None, None, "current"
    return start, min(start + span, today), "forward"

_fetch_bars 

_fetch_bars(token, interval, start_date, end_date)

Fetch and parse one window, logging in once first if the broker refuses the session.

A token expiring does not mean the download is over, and it does not mean this series is at fault. The rule is to log in first and then carry on: one login, then the same window again. Only if that login fails, or the fresh session is refused as well, does the error go back up - where visit and run stop the broker rather than carry on with a dead token.

Both alternatives are worse. Stopping outright leaves the download waiting for systemd to restart it into a login, and recording the refusal against whichever series it was on and moving to the next sends thousands of refused requests an hour - enough for Cloudflare to ban the machine from Fyers.

The login is re-armed by any window that comes back without a session error, so a backfill that runs for weeks gets its one login at each daily expiry.

  • token, interval, start_date and end_date are as for fetch_candles.
Source code in stock_brokers/instruments/historical/base.py 
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
def _fetch_bars(self, token, interval, start_date, end_date):
    """
    Fetch and parse one window, logging in once first if the broker refuses the session.

    A token expiring does not mean the download is over, and it does not mean this series is at
    fault. The rule is to log in first and then carry on: one login, then the same window
    again. Only if that login fails, or the fresh session is refused as well, does the error go
    back up - where `visit` and `run` stop the broker rather than carry on with a dead token.

    Both alternatives are worse. Stopping outright leaves the download waiting for systemd to
    restart it into a login, and recording the refusal against whichever series it was on and
    moving to the next sends thousands of refused requests an hour - enough for Cloudflare to
    ban the machine from Fyers.

    The login is re-armed by any window that comes back without a session error, so a
    backfill that runs for weeks gets its one login at each daily expiry.

    - `token`, `interval`, `start_date` and `end_date` are as for `fetch_candles`.
    """
    try:
        bars = self.parse_response(self.fetch_candles(token, interval, start_date, end_date),
                                   interval)
    except CandleAuthenticationError as failure:
        if self._relogin_used:
            raise
        self._relogin_used = True
        self._logger.warning(f"{self.BROKER_NAME} refused the session ({failure}). Logging in "
                             f"once before continuing.")
        self.relogin()
        self._limiter.take()
        bars = self.parse_response(self.fetch_candles(token, interval, start_date, end_date),
                                   interval)
    self._relogin_used = False
    return bars

relogin 

relogin()

Establish a fresh session and rebuild everything built on the old one.

Through ensure_session, so it takes the same Redis lock and obeys the same floor on login attempts as any other process using it - which means it may wait, and may find another process has already logged in, in which case that session is simply used.

Raises:

Type Description
CandleAuthenticationError

If no working session could be established.

Example usage

From example_3_logging_in_again_after_a_refused_session.py
downloader.relogin()
Source code in stock_brokers/instruments/historical/base.py 
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
def relogin(self):
    """
    Establish a fresh session and rebuild everything built on the old one.

    Through `ensure_session`, so it takes the same Redis lock and obeys the same floor on login
    attempts as any other process using it - which means it may wait, and may find another
    process has already logged in, in which case that session is simply used.

    Raises:
        CandleAuthenticationError: If no working session could be established.
    """
    from stock_brokers.api.utilities.session import ensure_session

    try:
        ensure_session(self.BROKER_NAME, logger=self._logger)
        self._api = self._build_api()
        self.after_relogin()
    except CandleAuthenticationError:
        raise
    except Exception as exception:
        raise CandleAuthenticationError(
            f"logging in again did not produce a working session: "
            f"{type(exception).__name__}: {str(exception)[:200]}") from exception
    self._logger.info(f"{self.BROKER_NAME} logged in again. Continuing.")

_build_api 

_build_api()

Construct this broker's authenticated API class, around whatever session is now stored.

The broker's own class from api_class_for, which is what every downloader builds. A downloader that builds its API differently overrides this.

Source code in stock_brokers/instruments/historical/base.py 
589
590
591
592
593
594
595
596
597
598
def _build_api(self):
    """
    Construct this broker's authenticated API class, around whatever session is now stored.

    The broker's own class from `api_class_for`, which is what every downloader builds. A
    downloader that builds its API differently overrides this.
    """
    from stock_brokers.api.utilities.session import api_class_for

    return api_class_for(self.BROKER_NAME)()

after_relogin 

after_relogin()

Re-establish anything a downloader keeps on top of the broker session. Nothing by default.

For a broker whose historical endpoint takes a second credential minted from the session, such as a separate market data token, this is where that credential is renewed.

Example usage

From example_3_logging_in_again_after_a_refused_session.py
downloader.after_relogin()
Source code in stock_brokers/instruments/historical/base.py 
600
601
602
603
604
605
606
def after_relogin(self):
    """
    Re-establish anything a downloader keeps on top of the broker session. Nothing by default.

    For a broker whose historical endpoint takes a second credential minted from the session,
    such as a separate market data token, this is where that credential is renewed.
    """

visit 

visit(series)

Fetch one window for one series and store it, advancing the watermark.

Returns the number of bars stored. The bars and the watermark are written in the same transaction, so an interruption costs at most the window in flight - and repeating that window is harmless, because bars upsert on their key.

  • series is a row from claim.

Example usage

From example_1_one_window_of_daily_bars.py
stored = self.downloader.visit(series)
From example_3_logging_in_again_after_a_refused_session.py
stored = downloader.visit(self.series('738561'))
Source code in stock_brokers/instruments/historical/base.py 
608
609
610
611
612
613
614
615
616
617
618
619
620
621
622
623
624
625
626
627
628
629
630
631
632
633
634
635
636
637
638
639
640
641
642
643
644
645
646
647
648
649
650
651
652
653
654
655
656
657
658
659
660
661
662
663
664
665
666
667
668
669
670
671
672
673
674
675
676
def visit(self, series):
    """
    Fetch one window for one series and store it, advancing the watermark.

    Returns the number of bars stored. The bars and the watermark are written in the same
    transaction, so an interruption costs at most the window in flight - and repeating that
    window is harmless, because bars upsert on their key.

    - `series` is a row from `claim`.
    """
    token, interval, _, previous_latest, _, empty_streak, _ = series
    start_date, end_date, direction = self.next_window(series)

    if direction == "exhausted":
        if previous_latest is None:
            # Walked the whole range the broker serves and never saw a bar. A contract that
            # listed and never traded is the usual case, and there are tens of thousands of
            # them. Without this they would be claimed again the moment they were put down -
            # `next_window` answers "exhausted" every time, so nothing would move - and the
            # queue would spin through them at database speed making no requests at all.
            self._retire(token, interval,
                         "the broker served no bars anywhere in the range it offers")
            return 0
        # The backward walk is finished. Not retired: the series still gets new bars each
        # day, it simply has no more past to collect.
        self._finish_backfill(token, interval, "reached the broker's earliest date")
        return 0
    if direction == "current":
        self._defer_until_tomorrow(token, interval, "up to date")
        return 0

    self._limiter.take()
    try:
        bars = self._fetch_bars(token, interval, start_date, end_date)
    except CandleInstrumentUnknown as exception:
        self._retire(token, interval, str(exception))
        return 0
    except CandleThrottled as exception:
        # A throttle says something about the pace, not about this series, so it costs the
        # limiter five seconds and leaves the series claimable. Counting it as a failure
        # instead would push a perfectly good series an hour into the future - and a broker
        # that throttles does it to a run of series, not to one.
        self._limiter.back_off(5.0)
        self._record_throttle(token, interval, str(exception))
        return 0
    except (CandleAuthenticationError, CandleBlocked):
        # Neither says anything about this series, so neither is recorded against it. Before a
        # dead token was re-raised here, every refused request landed on whichever series was
        # claimed, and after five of those a good series stopped being claimed at all.
        raise
    except Exception as exception:
        self._record_failure(token, interval,
                             f"{type(exception).__name__}: {str(exception)[:200]}")
        return 0

    if not bars:
        streak = (empty_streak or 0) + 1
        if direction == "backward" and streak >= MAXIMUM_EMPTY_WINDOWS:
            # The broker has nothing older. Stop walking back, keep collecting forward.
            self._finish_backfill(token, interval,
                                  f"{streak} empty windows walking back from {end_date}")
        elif direction == "forward":
            self._defer_until_tomorrow(token, interval, "no new bars yet")
        else:
            self._record_empty(token, interval, streak, start_date, direction)
        return 0

    self._store(token, interval, bars, start_date, direction, previous_latest)
    return len(bars)

_store 

_store(token, interval, bars, requested_from, direction, previous_latest=None)

Write a window's bars and move the watermark, in one transaction.

  • token is the broker's instrument identifier.
  • interval is the stored interval name.
  • bars are the parsed (time, open, high, low, close, volume, oi) tuples.
  • requested_from is the start of the window that was asked for.
  • direction is whether the walk was forward or backward.
  • previous_latest is the newest bar already stored, used to tell a forward window that gained ground from one that returned only what was already known.
Source code in stock_brokers/instruments/historical/base.py 
678
679
680
681
682
683
684
685
686
687
688
689
690
691
692
693
694
695
696
697
698
699
700
701
702
703
704
705
706
707
708
709
710
711
712
713
714
715
716
717
718
719
720
721
722
723
724
725
726
727
728
729
730
731
732
733
734
735
736
737
738
739
740
741
742
743
744
def _store(self, token, interval, bars, requested_from, direction, previous_latest=None):
    """
    Write a window's bars and move the watermark, in one transaction.

    - `token` is the broker's instrument identifier.
    - `interval` is the stored interval name.
    - `bars` are the parsed `(time, open, high, low, close, volume, oi)` tuples.
    - `requested_from` is the start of the window that was asked for.
    - `direction` is whether the walk was forward or backward.
    - `previous_latest` is the newest bar already stored, used to tell a forward window that
      gained ground from one that returned only what was already known.
    """
    # Collapsed on bar time before the write, last one winning. A broker can answer with the
    # same timestamp twice in one window - Dhan does - and Postgres refuses a batch that
    # touches the same row twice with "ON CONFLICT DO UPDATE command cannot affect row a
    # second time", which killed the whole process rather than the window.
    by_time = {}
    for bar in bars:
        volume = self._value_within_bigint(token, interval, bar[0], "volume", bar[5])
        open_interest = self._value_within_bigint(token, interval, bar[0], "oi", bar[6])
        by_time[bar[0]] = (bar[0], str(token), interval,
                           bar[1], bar[2], bar[3], bar[4], volume, open_interest)
    rows = list(by_time.values())
    times = list(by_time)

    try:
        with self._connection.cursor() as cursor:
            for start in range(0, len(rows), WRITE_BATCH_ROWS):
                execute_values(cursor, f"""
                    insert into {self._table}
                        ("time", instrument_token, "interval", open, high, low, close,
                         volume, oi)
                    values %s
                    on conflict (instrument_token, "interval", "time") do update set
                        open = excluded.open, high = excluded.high, low = excluded.low,
                        close = excluded.close, volume = excluded.volume, oi = excluded.oi,
                        downloaded_at = now()
                """, rows[start:start + WRITE_BATCH_ROWS])

            cursor.execute(f"""
                update {self._progress_table} set
                    earliest_bar_time = least(coalesce(earliest_bar_time, %s), %s),
                    latest_bar_time = greatest(coalesce(latest_bar_time, %s), %s),
                    oldest_requested_time = case when %s = 'backward'
                        then least(coalesce(oldest_requested_time, %s), %s)
                        else oldest_requested_time end,
                    bar_count = bar_count + %s,
                    empty_window_streak = 0,
                    consecutive_failures = 0,
                    next_attempt_after = null,
                    last_attempt_at = now(),
                    last_outcome = 'stored',
                    last_failure_reason = null
                where instrument_token = %s and "interval" = %s
            """, (min(times), min(times), max(times), max(times),
                  direction, requested_from, requested_from,
                  len(rows), str(token), interval))
        self._connection.commit()
    except Exception:
        self._connection.rollback()
        raise

    # A forward window that returned nothing newer than what was already stored means the
    # market has not produced more yet. Without this the series would be claimed again
    # immediately and spend the rate limit re-fetching the same bars all weekend.
    if direction == "forward" and previous_latest is not None and max(times) <= previous_latest:
        self._defer_until_tomorrow(token, interval, "forward window gained no new bars")

_value_within_bigint 

_value_within_bigint(token, interval, bar_time, column, value)

Returns a bar's count, or None when the count cannot fit in a BIGINT column.

Parameters:

Name Type Description Default
token str

The broker's instrument identifier.

 required
interval str

The stored interval name.

 required
bar_time datetime

The time of the bar the value belongs to.

 required
column str

The name of the column the value is written to, either "volume" or "oi".

 required
value int | float | None

The count exactly as the broker sent it.

 required

Returns:

Type Description
int | float | None

The value unchanged when it fits in a BIGINT or is not a number, and None when it does not fit.
Source code in stock_brokers/instruments/historical/base.py 
746
747
748
749
750
751
752
753
754
755
756
757
758
759
760
761
762
763
764
765
766
767
768
769
770
771
def _value_within_bigint(self, token, interval, bar_time, column, value):
    """Returns a bar's count, or None when the count cannot fit in a BIGINT column.

    Args:
        token (str): The broker's instrument identifier.
        interval (str): The stored interval name.
        bar_time (datetime.datetime): The time of the bar the value belongs to.
        column (str): The name of the column the value is written to, either "volume" or "oi".
        value (int | float | None): The count exactly as the broker sent it.

    Returns:
        int | float | None: The value unchanged when it fits in a BIGINT or is not a number, and None when it does not fit.
    """
    if not isinstance(value, (int, float)):
        return value
    if BIGINT_MINIMUM <= value <= BIGINT_MAXIMUM:
        return value
    self._logger.warning(
        "%s %s %s: %s %s does not fit in BIGINT, storing NULL.",
        token,
        interval,
        bar_time.isoformat(),
        column,
        value,
    )
    return None

_record_empty 

_record_empty(token, interval, streak, requested_from, direction)

Note that a window came back with nothing, and step past it.

  • token, interval identify the series.
  • streak is how many empty windows in a row this makes.
  • requested_from is the start of the window that was asked for.
  • direction is whether the walk was forward or backward.
Source code in stock_brokers/instruments/historical/base.py 
773
774
775
776
777
778
779
780
781
782
783
784
785
786
787
788
789
790
791
792
793
794
795
def _record_empty(self, token, interval, streak, requested_from, direction):
    """
    Note that a window came back with nothing, and step past it.

    - `token`, `interval` identify the series.
    - `streak` is how many empty windows in a row this makes.
    - `requested_from` is the start of the window that was asked for.
    - `direction` is whether the walk was forward or backward.
    """
    with self._connection.cursor() as cursor:
        cursor.execute(f"""
            update {self._progress_table} set
                empty_window_streak = %s,
                oldest_requested_time = case when %s = 'backward'
                    then least(coalesce(oldest_requested_time, %s), %s)
                    else oldest_requested_time end,
                last_attempt_at = now(),
                last_outcome = 'empty',
                consecutive_failures = 0,
                next_attempt_after = null
            where instrument_token = %s and "interval" = %s
        """, (streak, direction, requested_from, requested_from, str(token), interval))
    self._connection.commit()

_finish_backfill 

_finish_backfill(token, interval, reason)

Mark the backward walk complete, leaving the series collecting forward.

Distinct from _retire: the broker has no more past for this series, but it will keep producing new bars. Retiring it here would quietly stop a live instrument updating.

  • token, interval identify the series.
  • reason is why the walk stopped, kept for review.
Source code in stock_brokers/instruments/historical/base.py 
797
798
799
800
801
802
803
804
805
806
807
808
809
810
811
812
813
814
815
816
817
818
819
820
def _finish_backfill(self, token, interval, reason):
    """
    Mark the backward walk complete, leaving the series collecting forward.

    Distinct from `_retire`: the broker has no more *past* for this series, but it will keep
    producing new bars. Retiring it here would quietly stop a live instrument updating.

    - `token`, `interval` identify the series.
    - `reason` is why the walk stopped, kept for review.
    """
    with self._connection.cursor() as cursor:
        cursor.execute(f"""
            update {self._progress_table} set
                oldest_requested_time = %s,
                empty_window_streak = 0,
                consecutive_failures = 0,
                next_attempt_after = null,
                last_attempt_at = now(),
                last_outcome = 'backfilled',
                limit_reason = %s
            where instrument_token = %s and "interval" = %s
        """, (self.EARLIEST_AVAILABLE_DATE, reason[:500], str(token), interval))
    self._connection.commit()
    self._logger.info(f"{token} {interval}: backfill complete ({reason}).")

_defer_until_tomorrow 

_defer_until_tomorrow(token, interval, reason)

Put a series aside until the next day.

Reached when a forward window brings nothing new, which outside market hours is every forward window. Without it the highest priority series would be re-fetched continuously and spend the whole rate limit re-reading bars already stored.

  • token, interval identify the series.
  • reason is recorded as the outcome.
Source code in stock_brokers/instruments/historical/base.py 
822
823
824
825
826
827
828
829
830
831
832
833
834
835
836
837
838
839
840
841
842
def _defer_until_tomorrow(self, token, interval, reason):
    """
    Put a series aside until the next day.

    Reached when a forward window brings nothing new, which outside market hours is every
    forward window. Without it the highest priority series would be re-fetched continuously
    and spend the whole rate limit re-reading bars already stored.

    - `token`, `interval` identify the series.
    - `reason` is recorded as the outcome.
    """
    with self._connection.cursor() as cursor:
        cursor.execute(f"""
            update {self._progress_table} set
                next_attempt_after = date_trunc('day', now()) + interval '1 day',
                last_attempt_at = now(),
                last_outcome = %s,
                consecutive_failures = 0
            where instrument_token = %s and "interval" = %s
        """, (reason[:100], str(token), interval))
    self._connection.commit()

_record_throttle 

_record_throttle(token, interval, reason)

Note that the broker asked us to slow down, without holding it against the series.

The window is left exactly as it was, so the same series is claimed again once the limiter's back off has passed and the work is simply redone.

  • token, interval identify the series.
  • reason is what the broker said.
Source code in stock_brokers/instruments/historical/base.py 
844
845
846
847
848
849
850
851
852
853
854
855
856
857
858
859
860
861
862
863
def _record_throttle(self, token, interval, reason):
    """
    Note that the broker asked us to slow down, without holding it against the series.

    The window is left exactly as it was, so the same series is claimed again once the
    limiter's back off has passed and the work is simply redone.

    - `token`, `interval` identify the series.
    - `reason` is what the broker said.
    """
    with self._connection.cursor() as cursor:
        cursor.execute(f"""
            update {self._progress_table} set
                last_attempt_at = now(),
                last_outcome = 'throttled',
                last_failure_reason = %s
            where instrument_token = %s and "interval" = %s
        """, (reason[:500], str(token), interval))
    self._connection.commit()
    self._logger.warning(f"{token} {interval}: throttled: {reason[:150]}")

_record_failure 

_record_failure(token, interval, reason)

Note a failure and push the next attempt out exponentially.

An hour, then two, four, eight and so on, so a series that is permanently broken stops crowding out the ones that are not.

  • token, interval identify the series.
  • reason is what went wrong, stored for a human to read.
Source code in stock_brokers/instruments/historical/base.py 
865
866
867
868
869
870
871
872
873
874
875
876
877
878
879
880
881
882
883
884
885
886
887
def _record_failure(self, token, interval, reason):
    """
    Note a failure and push the next attempt out exponentially.

    An hour, then two, four, eight and so on, so a series that is permanently broken stops
    crowding out the ones that are not.

    - `token`, `interval` identify the series.
    - `reason` is what went wrong, stored for a human to read.
    """
    with self._connection.cursor() as cursor:
        cursor.execute(f"""
            update {self._progress_table} set
                consecutive_failures = consecutive_failures + 1,
                next_attempt_after = now() + interval '1 hour'
                                     * power(2, least(consecutive_failures, 6)),
                last_attempt_at = now(),
                last_outcome = 'failed',
                last_failure_reason = %s
            where instrument_token = %s and "interval" = %s
        """, (reason[:500], str(token), interval))
    self._connection.commit()
    self._logger.warning(f"{token} {interval}: {reason}")

_retire 

_retire(token, interval, reason)

Stop asking for a series the broker will not serve.

  • token, interval identify the series.
  • reason is why, stored so the decision can be reviewed.
Source code in stock_brokers/instruments/historical/base.py 
889
890
891
892
893
894
895
896
897
898
899
900
901
902
903
904
905
def _retire(self, token, interval, reason):
    """
    Stop asking for a series the broker will not serve.

    - `token`, `interval` identify the series.
    - `reason` is why, stored so the decision can be reviewed.
    """
    with self._connection.cursor() as cursor:
        cursor.execute(f"""
            update {self._progress_table} set
                reached_broker_limit = true,
                limit_reason = %s,
                last_attempt_at = now(),
                last_outcome = 'retired'
            where instrument_token = %s and "interval" = %s
        """, (reason[:500], str(token), interval))
    self._connection.commit()

run 

run(stop_event=None, deadline_seconds=None)

Work the queue until stopped, out of work, or out of time.

Returns a (visits, bars) pair.

  • stop_event is a threading.Event that ends the loop when set.
  • deadline_seconds ends the loop after this long, for a job with a nightly window.

Example usage

From example_2_run_until_the_queue_is_drained.py
visits, bars = self.downloader.run()
From example_2_run_until_the_queue_is_drained.py
print(f'A run asked to stop before it starts: {self.downloader.run(stop_event=stop_event)}')
From example_3_logging_in_again_after_a_refused_session.py
visits, bars = downloader.run()
Source code in stock_brokers/instruments/historical/base.py 
909
910
911
912
913
914
915
916
917
918
919
920
921
922
923
924
925
926
927
928
929
930
931
932
933
934
935
936
937
938
939
940
941
942
943
944
945
946
947
948
949
950
951
952
953
954
955
956
957
958
959
960
961
962
def run(self, stop_event=None, deadline_seconds=None):
    """
    Work the queue until stopped, out of work, or out of time.

    Returns a `(visits, bars)` pair.

    - `stop_event` is a `threading.Event` that ends the loop when set.
    - `deadline_seconds` ends the loop after this long, for a job with a nightly window.
    """
    started = time.monotonic()
    visits = 0
    bars = 0

    while True:
        if stop_event is not None and stop_event.is_set():
            self._logger.info("Stopping: asked to.")
            break
        if deadline_seconds is not None and time.monotonic() - started > deadline_seconds:
            self._logger.info(f"Stopping: reached the {deadline_seconds}s deadline.")
            break

        series = self.claim()
        if series is None:
            self._logger.info("Nothing due. The queue is drained or backing off.")
            break

        try:
            stored = self.visit(series)
        except (CandleAuthenticationError, CandleBlocked) as exception:
            self._logger.error(f"Stopping: {type(exception).__name__}: {exception}")
            break
        except CandleThrottled as exception:
            self._logger.warning(f"Stopping: {exception}")
            break
        except Exception as exception:
            # Anything `visit` did not expect - a response shaped in a way no probe produced,
            # a write the database refuses - costs this one series and not the run. Before
            # this, a single window that failed on the way into Postgres took the process
            # down, and since the same window would be claimed again on restart it took it
            # down every ten minutes thereafter.
            self._connection.rollback()
            self._record_failure(series[0], series[1],
                                 f"{type(exception).__name__}: {str(exception)[:200]}")
            self._logger.exception(f"{series[0]} {series[1]}: unexpected failure, "
                                   f"carrying on with the next series.")
            stored = 0

        visits += 1
        bars += stored
        if visits % 200 == 0:
            self._logger.info(f"{visits} windows, {bars} bars so far.")

    self._logger.info(f"Finished: {visits} windows, {bars} bars.")
    return visits, bars

summary 

summary()

How far the download has got, for a status display.

Example usage

From example_1_one_window_of_daily_bars.py
print(f'Summary: {self.downloader.summary()}')
From example_2_run_until_the_queue_is_drained.py
print(f'Summary: {self.downloader.summary()}')
Source code in stock_brokers/instruments/historical/base.py 
964
965
966
967
968
969
970
971
972
973
974
975
976
977
978
979
980
def summary(self):
    """
    How far the download has got, for a status display.
    """
    with self._connection.cursor() as cursor:
        cursor.execute(f"""
            select count(*),
                   count(*) filter (where reached_broker_limit),
                   count(*) filter (where bar_count > 0),
                   coalesce(sum(bar_count), 0),
                   count(*) filter (where consecutive_failures >= %s)
            from {self._progress_table}
        """, (MAXIMUM_CONSECUTIVE_FAILURES,))
        total, retired, started, stored, stuck = cursor.fetchone()
    self._connection.commit()
    return {"series": total, "retired": retired, "with_bars": started,
            "bars": int(stored), "stuck": stuck}

close 

close()

Close the database connection.

Example usage

From example_1_one_window_of_daily_bars.py
self.downloader.close()
From example_2_run_until_the_queue_is_drained.py
self.downloader.close()
From example_3_logging_in_again_after_a_refused_session.py
downloader.close()
Source code in stock_brokers/instruments/historical/base.py 
982
983
984
985
986
def close(self):
    """
    Close the database connection.
    """
    self._connection.close()