mirror of
https://github.com/freqtrade/freqtrade.git
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385 lines
15 KiB
Python
385 lines
15 KiB
Python
# pragma pylint: disable=missing-docstring, protected-access, invalid-name
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from datetime import datetime, timedelta, timezone
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import pytest
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from ccxt import (
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DECIMAL_PLACES,
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ROUND,
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ROUND_DOWN,
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ROUND_UP,
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SIGNIFICANT_DIGITS,
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TICK_SIZE,
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TRUNCATE,
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)
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from freqtrade.enums import RunMode
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from freqtrade.exceptions import OperationalException
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from freqtrade.exchange import (
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amount_to_contract_precision,
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amount_to_precision,
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date_minus_candles,
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price_to_precision,
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timeframe_to_minutes,
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timeframe_to_msecs,
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timeframe_to_next_date,
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timeframe_to_prev_date,
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timeframe_to_resample_freq,
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timeframe_to_seconds,
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)
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from freqtrade.exchange.check_exchange import check_exchange
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from tests.conftest import log_has_re
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def test_check_exchange(default_conf, caplog) -> None:
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# Test an officially supported by Freqtrade team exchange
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default_conf["runmode"] = RunMode.DRY_RUN
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default_conf.get("exchange").update({"name": "BINANCE"})
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assert check_exchange(default_conf)
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assert log_has_re(
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r"Exchange .* is officially supported by the Freqtrade development team\.", caplog
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)
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caplog.clear()
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# Test an officially supported by Freqtrade team exchange
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default_conf.get("exchange").update({"name": "binance"})
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assert check_exchange(default_conf)
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assert log_has_re(
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r"Exchange \"binance\" is officially supported by the Freqtrade development team\.", caplog
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)
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caplog.clear()
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# Test an officially supported by Freqtrade team exchange
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default_conf.get("exchange").update({"name": "binanceus"})
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assert check_exchange(default_conf)
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assert log_has_re(
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r"Exchange \"binanceus\" is officially supported by the Freqtrade development team\.",
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caplog,
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)
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caplog.clear()
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# Test an officially supported by Freqtrade team exchange - with remapping
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default_conf.get("exchange").update({"name": "okx"})
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assert check_exchange(default_conf)
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assert log_has_re(
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r"Exchange \"okx\" is officially supported by the Freqtrade development team\.", caplog
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)
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caplog.clear()
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# Test an available exchange, supported by ccxt
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default_conf.get("exchange").update({"name": "huobijp"})
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assert check_exchange(default_conf)
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assert log_has_re(
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r"Exchange .* is known to the ccxt library, available for the bot, "
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r"but not officially supported "
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r"by the Freqtrade development team\. .*",
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caplog,
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)
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caplog.clear()
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# Test a 'bad' exchange, which known to have serious problems
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default_conf.get("exchange").update({"name": "bitmex"})
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with pytest.raises(OperationalException, match=r"Exchange .* will not work with Freqtrade\..*"):
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check_exchange(default_conf)
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caplog.clear()
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# Test a 'bad' exchange with check_for_bad=False
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default_conf.get("exchange").update({"name": "bitmex"})
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assert check_exchange(default_conf, False)
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assert log_has_re(
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r"Exchange .* is known to the ccxt library, available for the bot, "
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r"but not officially supported "
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r"by the Freqtrade development team\. .*",
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caplog,
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)
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caplog.clear()
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# Test an invalid exchange
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default_conf.get("exchange").update({"name": "unknown_exchange"})
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with pytest.raises(
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OperationalException,
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match=r'Exchange "unknown_exchange" is not known to the ccxt library '
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r"and therefore not available for the bot.*",
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):
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check_exchange(default_conf)
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# Test no exchange...
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default_conf.get("exchange").update({"name": ""})
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default_conf["runmode"] = RunMode.PLOT
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assert check_exchange(default_conf)
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# Test no exchange...
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default_conf.get("exchange").update({"name": ""})
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default_conf["runmode"] = RunMode.UTIL_EXCHANGE
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with pytest.raises(
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OperationalException, match=r"This command requires a configured exchange.*"
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):
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check_exchange(default_conf)
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def test_date_minus_candles():
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date = datetime(2019, 8, 12, 13, 25, 0, tzinfo=timezone.utc)
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assert date_minus_candles("5m", 3, date) == date - timedelta(minutes=15)
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assert date_minus_candles("5m", 5, date) == date - timedelta(minutes=25)
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assert date_minus_candles("1m", 6, date) == date - timedelta(minutes=6)
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assert date_minus_candles("1h", 3, date) == date - timedelta(hours=3, minutes=25)
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assert date_minus_candles("1h", 3) == timeframe_to_prev_date("1h") - timedelta(hours=3)
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def test_timeframe_to_minutes():
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assert timeframe_to_minutes("5m") == 5
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assert timeframe_to_minutes("10m") == 10
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assert timeframe_to_minutes("1h") == 60
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assert timeframe_to_minutes("1d") == 1440
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def test_timeframe_to_seconds():
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assert timeframe_to_seconds("5m") == 300
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assert timeframe_to_seconds("10m") == 600
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assert timeframe_to_seconds("1h") == 3600
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assert timeframe_to_seconds("1d") == 86400
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def test_timeframe_to_msecs():
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assert timeframe_to_msecs("5m") == 300000
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assert timeframe_to_msecs("10m") == 600000
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assert timeframe_to_msecs("1h") == 3600000
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assert timeframe_to_msecs("1d") == 86400000
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@pytest.mark.parametrize(
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"timeframe,expected",
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[
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("1s", "1s"),
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("15s", "15s"),
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("5m", "300s"),
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("10m", "600s"),
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("1h", "3600s"),
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("1d", "86400s"),
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("1w", "1W-MON"),
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("1M", "1MS"),
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("1y", "1YS"),
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],
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)
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def test_timeframe_to_resample_freq(timeframe, expected):
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assert timeframe_to_resample_freq(timeframe) == expected
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def test_timeframe_to_prev_date():
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# 2019-08-12 13:22:08
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date = datetime.fromtimestamp(1565616128, tz=timezone.utc)
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tf_list = [
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# 5m -> 2019-08-12 13:20:00
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("5m", datetime(2019, 8, 12, 13, 20, 0, tzinfo=timezone.utc)),
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# 10m -> 2019-08-12 13:20:00
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("10m", datetime(2019, 8, 12, 13, 20, 0, tzinfo=timezone.utc)),
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# 1h -> 2019-08-12 13:00:00
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("1h", datetime(2019, 8, 12, 13, 00, 0, tzinfo=timezone.utc)),
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# 2h -> 2019-08-12 12:00:00
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("2h", datetime(2019, 8, 12, 12, 00, 0, tzinfo=timezone.utc)),
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# 4h -> 2019-08-12 12:00:00
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("4h", datetime(2019, 8, 12, 12, 00, 0, tzinfo=timezone.utc)),
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# 1d -> 2019-08-12 00:00:00
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("1d", datetime(2019, 8, 12, 00, 00, 0, tzinfo=timezone.utc)),
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]
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for interval, result in tf_list:
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assert timeframe_to_prev_date(interval, date) == result
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date = datetime.now(tz=timezone.utc)
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assert timeframe_to_prev_date("5m") < date
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# Does not round
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time = datetime(2019, 8, 12, 13, 20, 0, tzinfo=timezone.utc)
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assert timeframe_to_prev_date("5m", time) == time
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time = datetime(2019, 8, 12, 13, 0, 0, tzinfo=timezone.utc)
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assert timeframe_to_prev_date("1h", time) == time
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def test_timeframe_to_next_date():
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# 2019-08-12 13:22:08
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date = datetime.fromtimestamp(1565616128, tz=timezone.utc)
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tf_list = [
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# 5m -> 2019-08-12 13:25:00
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("5m", datetime(2019, 8, 12, 13, 25, 0, tzinfo=timezone.utc)),
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# 10m -> 2019-08-12 13:30:00
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("10m", datetime(2019, 8, 12, 13, 30, 0, tzinfo=timezone.utc)),
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# 1h -> 2019-08-12 14:00:00
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("1h", datetime(2019, 8, 12, 14, 00, 0, tzinfo=timezone.utc)),
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# 2h -> 2019-08-12 14:00:00
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("2h", datetime(2019, 8, 12, 14, 00, 0, tzinfo=timezone.utc)),
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# 4h -> 2019-08-12 14:00:00
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("4h", datetime(2019, 8, 12, 16, 00, 0, tzinfo=timezone.utc)),
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# 1d -> 2019-08-13 00:00:00
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("1d", datetime(2019, 8, 13, 0, 0, 0, tzinfo=timezone.utc)),
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]
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for interval, result in tf_list:
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assert timeframe_to_next_date(interval, date) == result
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date = datetime.now(tz=timezone.utc)
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assert timeframe_to_next_date("5m") > date
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date = datetime(2019, 8, 12, 13, 30, 0, tzinfo=timezone.utc)
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assert timeframe_to_next_date("5m", date) == date + timedelta(minutes=5)
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@pytest.mark.parametrize(
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"amount,precision_mode,precision,expected",
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[
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(2.34559, DECIMAL_PLACES, 4, 2.3455),
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(2.34559, DECIMAL_PLACES, 5, 2.34559),
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(2.34559, DECIMAL_PLACES, 3, 2.345),
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(2.9999, DECIMAL_PLACES, 3, 2.999),
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(2.9909, DECIMAL_PLACES, 3, 2.990),
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(2.9909, DECIMAL_PLACES, 0, 2),
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(29991.5555, DECIMAL_PLACES, 0, 29991),
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(29991.5555, DECIMAL_PLACES, -1, 29990),
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(29991.5555, DECIMAL_PLACES, -2, 29900),
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# Tests for
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(2.34559, SIGNIFICANT_DIGITS, 4, 2.345),
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(2.34559, SIGNIFICANT_DIGITS, 5, 2.3455),
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(2.34559, SIGNIFICANT_DIGITS, 3, 2.34),
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(2.9999, SIGNIFICANT_DIGITS, 3, 2.99),
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(2.9909, SIGNIFICANT_DIGITS, 3, 2.99),
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(0.0000077723, SIGNIFICANT_DIGITS, 5, 0.0000077723),
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(0.0000077723, SIGNIFICANT_DIGITS, 3, 0.00000777),
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(0.0000077723, SIGNIFICANT_DIGITS, 1, 0.000007),
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# Tests for Tick-size
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(2.34559, TICK_SIZE, 0.0001, 2.3455),
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(2.34559, TICK_SIZE, 0.00001, 2.34559),
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(2.34559, TICK_SIZE, 0.001, 2.345),
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(2.9999, TICK_SIZE, 0.001, 2.999),
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(2.9909, TICK_SIZE, 0.001, 2.990),
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(2.9909, TICK_SIZE, 0.005, 2.99),
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(2.9999, TICK_SIZE, 0.005, 2.995),
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],
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)
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def test_amount_to_precision(
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amount,
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precision_mode,
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precision,
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expected,
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):
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"""
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Test rounds down
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"""
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# digits counting mode
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# DECIMAL_PLACES = 2
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# SIGNIFICANT_DIGITS = 3
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# TICK_SIZE = 4
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assert amount_to_precision(amount, precision, precision_mode) == expected
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@pytest.mark.parametrize(
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"price,precision_mode,precision,expected,rounding_mode",
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[
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# Tests for DECIMAL_PLACES, ROUND_UP
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(2.34559, DECIMAL_PLACES, 4, 2.3456, ROUND_UP),
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(2.34559, DECIMAL_PLACES, 5, 2.34559, ROUND_UP),
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(2.34559, DECIMAL_PLACES, 3, 2.346, ROUND_UP),
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(2.9999, DECIMAL_PLACES, 3, 3.000, ROUND_UP),
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(2.9909, DECIMAL_PLACES, 3, 2.991, ROUND_UP),
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(2.9901, DECIMAL_PLACES, 3, 2.991, ROUND_UP),
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(2.34559, DECIMAL_PLACES, 5, 2.34559, ROUND_DOWN),
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(2.34559, DECIMAL_PLACES, 4, 2.3455, ROUND_DOWN),
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(2.9901, DECIMAL_PLACES, 3, 2.990, ROUND_DOWN),
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(0.00299, DECIMAL_PLACES, 3, 0.002, ROUND_DOWN),
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# Tests for DECIMAL_PLACES, ROUND
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(2.345600000000001, DECIMAL_PLACES, 4, 2.3456, ROUND),
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(2.345551, DECIMAL_PLACES, 4, 2.3456, ROUND),
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(2.49, DECIMAL_PLACES, 0, 2.0, ROUND),
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(2.51, DECIMAL_PLACES, 0, 3.0, ROUND),
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(5.1, DECIMAL_PLACES, -1, 10.0, ROUND),
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(4.9, DECIMAL_PLACES, -1, 0.0, ROUND),
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(0.000007222, SIGNIFICANT_DIGITS, 1, 0.000007, ROUND),
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(0.000007222, SIGNIFICANT_DIGITS, 2, 0.0000072, ROUND),
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(0.000007777, SIGNIFICANT_DIGITS, 2, 0.0000078, ROUND),
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# Tests for TICK_SIZE, ROUND_UP
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(2.34559, TICK_SIZE, 0.0001, 2.3456, ROUND_UP),
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(2.34559, TICK_SIZE, 0.00001, 2.34559, ROUND_UP),
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(2.34559, TICK_SIZE, 0.001, 2.346, ROUND_UP),
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(2.9999, TICK_SIZE, 0.001, 3.000, ROUND_UP),
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(2.9909, TICK_SIZE, 0.001, 2.991, ROUND_UP),
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(2.9909, TICK_SIZE, 0.001, 2.990, ROUND_DOWN),
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(2.9909, TICK_SIZE, 0.005, 2.995, ROUND_UP),
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(2.9973, TICK_SIZE, 0.005, 3.0, ROUND_UP),
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(2.9977, TICK_SIZE, 0.005, 3.0, ROUND_UP),
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(234.43, TICK_SIZE, 0.5, 234.5, ROUND_UP),
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(234.43, TICK_SIZE, 0.5, 234.0, ROUND_DOWN),
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(234.53, TICK_SIZE, 0.5, 235.0, ROUND_UP),
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(234.53, TICK_SIZE, 0.5, 234.5, ROUND_DOWN),
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(0.891534, TICK_SIZE, 0.0001, 0.8916, ROUND_UP),
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(64968.89, TICK_SIZE, 0.01, 64968.89, ROUND_UP),
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(0.000000003483, TICK_SIZE, 1e-12, 0.000000003483, ROUND_UP),
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# Tests for TICK_SIZE, ROUND
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(2.49, TICK_SIZE, 1.0, 2.0, ROUND),
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(2.51, TICK_SIZE, 1.0, 3.0, ROUND),
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(2.000000051, TICK_SIZE, 0.0000001, 2.0000001, ROUND),
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(2.000000049, TICK_SIZE, 0.0000001, 2.0, ROUND),
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(2.9909, TICK_SIZE, 0.005, 2.990, ROUND),
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(2.9973, TICK_SIZE, 0.005, 2.995, ROUND),
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(2.9977, TICK_SIZE, 0.005, 3.0, ROUND),
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(234.24, TICK_SIZE, 0.5, 234.0, ROUND),
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(234.26, TICK_SIZE, 0.5, 234.5, ROUND),
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# Tests for TRUNCATTE
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(2.34559, DECIMAL_PLACES, 4, 2.3455, TRUNCATE),
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(2.34559, DECIMAL_PLACES, 5, 2.34559, TRUNCATE),
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(2.34559, DECIMAL_PLACES, 3, 2.345, TRUNCATE),
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(2.9999, DECIMAL_PLACES, 3, 2.999, TRUNCATE),
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(2.9909, DECIMAL_PLACES, 3, 2.990, TRUNCATE),
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(2.9909, TICK_SIZE, 0.001, 2.990, TRUNCATE),
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(2.9909, TICK_SIZE, 0.01, 2.99, TRUNCATE),
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(2.9909, TICK_SIZE, 0.1, 2.9, TRUNCATE),
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# Tests for Significant
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(2.34559, SIGNIFICANT_DIGITS, 4, 2.345, TRUNCATE),
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(2.34559, SIGNIFICANT_DIGITS, 5, 2.3455, TRUNCATE),
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(2.34559, SIGNIFICANT_DIGITS, 3, 2.34, TRUNCATE),
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(2.9999, SIGNIFICANT_DIGITS, 3, 2.99, TRUNCATE),
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(2.9909, SIGNIFICANT_DIGITS, 2, 2.9, TRUNCATE),
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(0.00000777, SIGNIFICANT_DIGITS, 2, 0.0000077, TRUNCATE),
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(0.00000729, SIGNIFICANT_DIGITS, 2, 0.0000072, TRUNCATE),
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# ROUND
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(722.2, SIGNIFICANT_DIGITS, 1, 700.0, ROUND),
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(790.2, SIGNIFICANT_DIGITS, 1, 800.0, ROUND),
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(722.2, SIGNIFICANT_DIGITS, 2, 720.0, ROUND),
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(722.2, SIGNIFICANT_DIGITS, 1, 800.0, ROUND_UP),
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(722.2, SIGNIFICANT_DIGITS, 2, 730.0, ROUND_UP),
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(777.7, SIGNIFICANT_DIGITS, 2, 780.0, ROUND_UP),
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(777.7, SIGNIFICANT_DIGITS, 3, 778.0, ROUND_UP),
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(722.2, SIGNIFICANT_DIGITS, 1, 700.0, ROUND_DOWN),
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(722.2, SIGNIFICANT_DIGITS, 2, 720.0, ROUND_DOWN),
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(777.7, SIGNIFICANT_DIGITS, 2, 770.0, ROUND_DOWN),
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(777.7, SIGNIFICANT_DIGITS, 3, 777.0, ROUND_DOWN),
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(0.000007222, SIGNIFICANT_DIGITS, 1, 0.000008, ROUND_UP),
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(0.000007222, SIGNIFICANT_DIGITS, 2, 0.0000073, ROUND_UP),
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(0.000007777, SIGNIFICANT_DIGITS, 2, 0.0000078, ROUND_UP),
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(0.000007222, SIGNIFICANT_DIGITS, 1, 0.000007, ROUND_DOWN),
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(0.000007222, SIGNIFICANT_DIGITS, 2, 0.0000072, ROUND_DOWN),
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(0.000007777, SIGNIFICANT_DIGITS, 2, 0.0000077, ROUND_DOWN),
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],
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)
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def test_price_to_precision(price, precision_mode, precision, expected, rounding_mode):
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assert (
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price_to_precision(price, precision, precision_mode, rounding_mode=rounding_mode)
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== expected
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)
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@pytest.mark.parametrize(
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"amount,precision,precision_mode,contract_size,expected",
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[
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(1.17, 1.0, 4, 0.01, 1.17), # Tick size
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(1.17, 1.0, 2, 0.01, 1.17), #
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(1.16, 1.0, 4, 0.01, 1.16), #
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(1.16, 1.0, 2, 0.01, 1.16), #
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(1.13, 1.0, 2, 0.01, 1.13), #
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(10.988, 1.0, 2, 10, 10),
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(10.988, 1.0, 4, 10, 10),
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],
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)
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def test_amount_to_contract_precision_standalone(
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amount, precision, precision_mode, contract_size, expected
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):
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res = amount_to_contract_precision(amount, precision, precision_mode, contract_size)
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assert pytest.approx(res) == expected
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