Merge branch 'develop' into feat/cancel_order
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commit
c1a34396d0
@ -9,7 +9,7 @@ from collections import deque
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from datetime import datetime, timezone
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from typing import Any, Dict, List, Optional, Tuple
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from pandas import DataFrame, to_timedelta
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from pandas import DataFrame, Timedelta, Timestamp, to_timedelta
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from freqtrade.configuration import TimeRange
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from freqtrade.constants import (FULL_DATAFRAME_THRESHOLD, Config, ListPairsWithTimeframes,
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@ -206,9 +206,11 @@ class DataProvider:
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existing_df, _ = self.__producer_pairs_df[producer_name][pair_key]
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# CHECK FOR MISSING CANDLES
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timeframe_delta = to_timedelta(timeframe) # Convert the timeframe to a timedelta for pandas
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local_last = existing_df.iloc[-1]['date'] # We want the last date from our copy
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incoming_first = dataframe.iloc[0]['date'] # We want the first date from the incoming
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# Convert the timeframe to a timedelta for pandas
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timeframe_delta: Timedelta = to_timedelta(timeframe)
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local_last: Timestamp = existing_df.iloc[-1]['date'] # We want the last date from our copy
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# We want the first date from the incoming
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incoming_first: Timestamp = dataframe.iloc[0]['date']
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# Remove existing candles that are newer than the incoming first candle
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existing_df1 = existing_df[existing_df['date'] < incoming_first]
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@ -221,7 +223,7 @@ class DataProvider:
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# we missed some candles between our data and the incoming
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# so return False and candle_difference.
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if candle_difference > 1:
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return (False, candle_difference)
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return (False, int(candle_difference))
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if existing_df1.empty:
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appended_df = dataframe
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else:
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@ -308,7 +308,7 @@ class IDataHandler(ABC):
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timerange=timerange_startup,
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candle_type=candle_type
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)
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if self._check_empty_df(pairdf, pair, timeframe, candle_type, warn_no_data, True):
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if self._check_empty_df(pairdf, pair, timeframe, candle_type, warn_no_data):
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return pairdf
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else:
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enddate = pairdf.iloc[-1]['date']
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@ -316,7 +316,7 @@ class IDataHandler(ABC):
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if timerange_startup:
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self._validate_pairdata(pair, pairdf, timeframe, candle_type, timerange_startup)
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pairdf = trim_dataframe(pairdf, timerange_startup)
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if self._check_empty_df(pairdf, pair, timeframe, candle_type, warn_no_data):
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if self._check_empty_df(pairdf, pair, timeframe, candle_type, warn_no_data, True):
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return pairdf
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# incomplete candles should only be dropped if we didn't trim the end beforehand.
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@ -34,6 +34,7 @@ class Bybit(Exchange):
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"ohlcv_candle_limit": 200,
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"ohlcv_has_history": True,
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"mark_ohlcv_timeframe": "4h",
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"funding_fee_timeframe": "8h",
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"stoploss_on_exchange": True,
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"stoploss_order_types": {"limit": "limit", "market": "market"},
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}
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@ -36,3 +36,34 @@ class Kucoin(Exchange):
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'stop': 'loss'
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})
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return params
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def create_order(
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self,
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*,
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pair: str,
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ordertype: str,
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side: BuySell,
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amount: float,
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rate: float,
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leverage: float,
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reduceOnly: bool = False,
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time_in_force: str = 'GTC',
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) -> Dict:
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res = super().create_order(
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pair=pair,
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ordertype=ordertype,
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side=side,
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amount=amount,
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rate=rate,
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leverage=leverage,
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reduceOnly=reduceOnly,
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time_in_force=time_in_force,
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)
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# Kucoin returns only the order-id.
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# ccxt returns status = 'closed' at the moment - which is information ccxt invented.
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# Since we rely on status heavily, we must set it to 'open' here.
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# ref: https://github.com/ccxt/ccxt/pull/16674, (https://github.com/ccxt/ccxt/pull/16553)
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res['type'] = ordertype
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res['status'] = 'open'
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return res
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@ -750,13 +750,15 @@ class FreqtradeBot(LoggingMixin):
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self.exchange.name, order['filled'], order['amount'],
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order['remaining']
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)
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amount = safe_value_fallback(order, 'filled', 'amount')
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enter_limit_filled_price = safe_value_fallback(order, 'average', 'price')
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amount = safe_value_fallback(order, 'filled', 'amount', amount)
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enter_limit_filled_price = safe_value_fallback(
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order, 'average', 'price', enter_limit_filled_price)
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# in case of FOK the order may be filled immediately and fully
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elif order_status == 'closed':
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amount = safe_value_fallback(order, 'filled', 'amount')
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enter_limit_filled_price = safe_value_fallback(order, 'average', 'price')
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amount = safe_value_fallback(order, 'filled', 'amount', amount)
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enter_limit_filled_price = safe_value_fallback(
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order, 'average', 'price', enter_limit_requested)
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# Fee is applied twice because we make a LIMIT_BUY and LIMIT_SELL
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fee = self.exchange.get_fee(symbol=pair, taker_or_maker='maker')
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@ -44,7 +44,7 @@ class SharpeHyperOptLossDaily(IHyperOptLoss):
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sum_daily = (
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results.resample(resample_freq, on='close_date').agg(
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{"profit_ratio_after_slippage": sum}).reindex(t_index).fillna(0)
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{"profit_ratio_after_slippage": 'sum'}).reindex(t_index).fillna(0)
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)
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total_profit = sum_daily["profit_ratio_after_slippage"] - risk_free_rate
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@ -46,7 +46,7 @@ class SortinoHyperOptLossDaily(IHyperOptLoss):
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sum_daily = (
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results.resample(resample_freq, on='close_date').agg(
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{"profit_ratio_after_slippage": sum}).reindex(t_index).fillna(0)
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{"profit_ratio_after_slippage": 'sum'}).reindex(t_index).fillna(0)
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)
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total_profit = sum_daily["profit_ratio_after_slippage"] - minimum_acceptable_return
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@ -172,7 +172,7 @@ class Order(_DECL_BASE):
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def to_json(self, entry_side: str, minified: bool = False) -> Dict[str, Any]:
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resp = {
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'amount': self.amount,
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'amount': self.safe_amount,
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'safe_price': self.safe_price,
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'ft_order_side': self.ft_order_side,
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'order_filled_timestamp': int(self.order_filled_date.replace(
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@ -90,7 +90,7 @@ async def _process_consumer_request(
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elif type == RPCRequestType.ANALYZED_DF:
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# Limit the amount of candles per dataframe to 'limit' or 1500
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limit = min(data.get('limit', 1500), 1500) if data else None
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limit = int(min(data.get('limit', 1500), 1500)) if data else None
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pair = data.get('pair', None) if data else None
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# For every pair in the generator, send a separate message
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@ -437,6 +437,7 @@ def test_dp__add_external_df(default_conf_usdt):
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# Add the same dataframe again - dataframe size shall not change.
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res = dp._add_external_df('ETH/USDT', df, last_analyzed, timeframe, CandleType.SPOT)
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assert res[0] is True
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assert isinstance(res[1], int)
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assert res[1] == 0
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df, _ = dp.get_producer_df('ETH/USDT', timeframe, CandleType.SPOT)
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assert len(df) == 24
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@ -446,6 +447,7 @@ def test_dp__add_external_df(default_conf_usdt):
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res = dp._add_external_df('ETH/USDT', df2, last_analyzed, timeframe, CandleType.SPOT)
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assert res[0] is True
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assert isinstance(res[1], int)
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assert res[1] == 0
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df, _ = dp.get_producer_df('ETH/USDT', timeframe, CandleType.SPOT)
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assert len(df) == 48
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@ -455,6 +457,7 @@ def test_dp__add_external_df(default_conf_usdt):
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res = dp._add_external_df('ETH/USDT', df3, last_analyzed, timeframe, CandleType.SPOT)
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assert res[0] is True
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assert isinstance(res[1], int)
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assert res[1] == 0
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df, _ = dp.get_producer_df('ETH/USDT', timeframe, CandleType.SPOT)
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# New length = 48 + 12 (since we have a 12 hour offset).
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@ -478,6 +481,7 @@ def test_dp__add_external_df(default_conf_usdt):
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res = dp._add_external_df('ETH/USDT', df4, last_analyzed, timeframe, CandleType.SPOT)
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assert res[0] is False
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# 36 hours - from 2022-01-03 12:00:00+00:00 to 2022-01-05 00:00:00+00:00
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assert isinstance(res[1], int)
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assert res[1] == 36
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df, _ = dp.get_producer_df('ETH/USDT', timeframe, CandleType.SPOT)
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# New length = 61 + 1
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@ -488,4 +492,5 @@ def test_dp__add_external_df(default_conf_usdt):
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res = dp._add_external_df('ETH/USDT', df4, last_analyzed, timeframe, CandleType.SPOT)
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assert res[0] is False
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# 36 hours - from 2022-01-03 12:00:00+00:00 to 2022-01-05 00:00:00+00:00
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assert isinstance(res[1], int)
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assert res[1] == 0
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@ -49,8 +49,8 @@ EXCHANGES = {
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"orderListId": -1,
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"clientOrderId": "x-R4DD3S8297c73a11ccb9dc8f2811ba",
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"transactTime": 1674493798550,
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"price": "15.00000000",
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"origQty": "1.00000000",
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"price": "15.50000000",
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"origQty": "1.10000000",
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"executedQty": "0.00000000",
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"cummulativeQuoteQty": "0.00000000",
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"status": "NEW",
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@ -74,8 +74,8 @@ EXCHANGES = {
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"orderListId": -1,
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"clientOrderId": "x-R4DD3S8297c73a11ccb9dc8f2811ba",
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"transactTime": 1674493798550,
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"price": "15.00000000",
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"origQty": "1.00000000",
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"price": "15.50000000",
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"origQty": "1.10000000",
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"executedQty": "0.00000000",
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"cummulativeQuoteQty": "0.00000000",
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"status": "NEW",
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@ -106,12 +106,12 @@ EXCHANGES = {
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{'id': '63d6742d0adc5570001d2bbf7'}, # create order
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{
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'id': '63d6742d0adc5570001d2bbf7',
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'symbol': 'NAKA-USDT',
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'symbol': 'SOL-USDT',
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'opType': 'DEAL',
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'type': 'limit',
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'side': 'buy',
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'price': '30',
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'size': '0.1',
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'price': '15.5',
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'size': '1.1',
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'funds': '0',
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'dealFunds': '0.032626',
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'dealSize': '0.1',
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@ -168,6 +168,23 @@ EXCHANGES = {
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'futures': True,
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'leverage_tiers_public': True,
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'leverage_in_spot_market': True,
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'sample_order': [
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{
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"orderId": "1274754916287346280",
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"orderLinkId": "1666798627015730",
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"symbol": "SOLUSDT",
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"createTime": "1674493798550",
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"orderPrice": "15.5",
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"orderQty": "1.1",
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"orderType": "LIMIT",
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"side": "BUY",
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"status": "NEW",
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"timeInForce": "GTC",
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"accountId": "5555555",
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"execQty": "0",
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"orderCategory": "0"
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}
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]
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},
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'huobi': {
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'pair': 'ETH/BTC',
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@ -306,13 +323,19 @@ class TestCCXTExchange():
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po = exch._api.parse_order(order)
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assert isinstance(po['id'], str)
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assert po['id'] is not None
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if len(order.keys()) > 1:
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assert po['timestamp'] == 1674493798550
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assert isinstance(po['datetime'], str)
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assert isinstance(po['timestamp'], int)
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assert isinstance(po['price'], float)
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assert isinstance(po['amount'], float)
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assert isinstance(po['status'], str)
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if len(order.keys()) < 5:
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# Kucoin case
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assert po['status'] == 'closed'
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continue
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assert po['timestamp'] == 1674493798550
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assert isinstance(po['datetime'], str)
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assert isinstance(po['timestamp'], int)
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assert isinstance(po['price'], float)
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assert po['price'] == 15.5
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assert po['symbol'] == 'SOL/USDT'
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assert isinstance(po['amount'], float)
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assert po['amount'] == 1.1
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assert isinstance(po['status'], str)
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else:
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pytest.skip(f"No sample order available for exchange {exchange_name}")
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