Merge branch 'develop' into feat/cancel_order

This commit is contained in:
Matthias 2023-02-01 07:06:17 +00:00
commit c1a34396d0
11 changed files with 93 additions and 29 deletions

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@ -9,7 +9,7 @@ from collections import deque
from datetime import datetime, timezone
from typing import Any, Dict, List, Optional, Tuple
from pandas import DataFrame, to_timedelta
from pandas import DataFrame, Timedelta, Timestamp, to_timedelta
from freqtrade.configuration import TimeRange
from freqtrade.constants import (FULL_DATAFRAME_THRESHOLD, Config, ListPairsWithTimeframes,
@ -206,9 +206,11 @@ class DataProvider:
existing_df, _ = self.__producer_pairs_df[producer_name][pair_key]
# CHECK FOR MISSING CANDLES
timeframe_delta = to_timedelta(timeframe) # Convert the timeframe to a timedelta for pandas
local_last = existing_df.iloc[-1]['date'] # We want the last date from our copy
incoming_first = dataframe.iloc[0]['date'] # We want the first date from the incoming
# Convert the timeframe to a timedelta for pandas
timeframe_delta: Timedelta = to_timedelta(timeframe)
local_last: Timestamp = existing_df.iloc[-1]['date'] # We want the last date from our copy
# We want the first date from the incoming
incoming_first: Timestamp = dataframe.iloc[0]['date']
# Remove existing candles that are newer than the incoming first candle
existing_df1 = existing_df[existing_df['date'] < incoming_first]
@ -221,7 +223,7 @@ class DataProvider:
# we missed some candles between our data and the incoming
# so return False and candle_difference.
if candle_difference > 1:
return (False, candle_difference)
return (False, int(candle_difference))
if existing_df1.empty:
appended_df = dataframe
else:

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@ -308,7 +308,7 @@ class IDataHandler(ABC):
timerange=timerange_startup,
candle_type=candle_type
)
if self._check_empty_df(pairdf, pair, timeframe, candle_type, warn_no_data, True):
if self._check_empty_df(pairdf, pair, timeframe, candle_type, warn_no_data):
return pairdf
else:
enddate = pairdf.iloc[-1]['date']
@ -316,7 +316,7 @@ class IDataHandler(ABC):
if timerange_startup:
self._validate_pairdata(pair, pairdf, timeframe, candle_type, timerange_startup)
pairdf = trim_dataframe(pairdf, timerange_startup)
if self._check_empty_df(pairdf, pair, timeframe, candle_type, warn_no_data):
if self._check_empty_df(pairdf, pair, timeframe, candle_type, warn_no_data, True):
return pairdf
# 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):
"ohlcv_candle_limit": 200,
"ohlcv_has_history": True,
"mark_ohlcv_timeframe": "4h",
"funding_fee_timeframe": "8h",
"stoploss_on_exchange": True,
"stoploss_order_types": {"limit": "limit", "market": "market"},
}

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@ -36,3 +36,34 @@ class Kucoin(Exchange):
'stop': 'loss'
})
return params
def create_order(
self,
*,
pair: str,
ordertype: str,
side: BuySell,
amount: float,
rate: float,
leverage: float,
reduceOnly: bool = False,
time_in_force: str = 'GTC',
) -> Dict:
res = super().create_order(
pair=pair,
ordertype=ordertype,
side=side,
amount=amount,
rate=rate,
leverage=leverage,
reduceOnly=reduceOnly,
time_in_force=time_in_force,
)
# Kucoin returns only the order-id.
# ccxt returns status = 'closed' at the moment - which is information ccxt invented.
# Since we rely on status heavily, we must set it to 'open' here.
# ref: https://github.com/ccxt/ccxt/pull/16674, (https://github.com/ccxt/ccxt/pull/16553)
res['type'] = ordertype
res['status'] = 'open'
return res

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@ -750,13 +750,15 @@ class FreqtradeBot(LoggingMixin):
self.exchange.name, order['filled'], order['amount'],
order['remaining']
)
amount = safe_value_fallback(order, 'filled', 'amount')
enter_limit_filled_price = safe_value_fallback(order, 'average', 'price')
amount = safe_value_fallback(order, 'filled', 'amount', amount)
enter_limit_filled_price = safe_value_fallback(
order, 'average', 'price', enter_limit_filled_price)
# in case of FOK the order may be filled immediately and fully
elif order_status == 'closed':
amount = safe_value_fallback(order, 'filled', 'amount')
enter_limit_filled_price = safe_value_fallback(order, 'average', 'price')
amount = safe_value_fallback(order, 'filled', 'amount', amount)
enter_limit_filled_price = safe_value_fallback(
order, 'average', 'price', enter_limit_requested)
# Fee is applied twice because we make a LIMIT_BUY and LIMIT_SELL
fee = self.exchange.get_fee(symbol=pair, taker_or_maker='maker')

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@ -44,7 +44,7 @@ class SharpeHyperOptLossDaily(IHyperOptLoss):
sum_daily = (
results.resample(resample_freq, on='close_date').agg(
{"profit_ratio_after_slippage": sum}).reindex(t_index).fillna(0)
{"profit_ratio_after_slippage": 'sum'}).reindex(t_index).fillna(0)
)
total_profit = sum_daily["profit_ratio_after_slippage"] - risk_free_rate

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@ -46,7 +46,7 @@ class SortinoHyperOptLossDaily(IHyperOptLoss):
sum_daily = (
results.resample(resample_freq, on='close_date').agg(
{"profit_ratio_after_slippage": sum}).reindex(t_index).fillna(0)
{"profit_ratio_after_slippage": 'sum'}).reindex(t_index).fillna(0)
)
total_profit = sum_daily["profit_ratio_after_slippage"] - minimum_acceptable_return

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@ -172,7 +172,7 @@ class Order(_DECL_BASE):
def to_json(self, entry_side: str, minified: bool = False) -> Dict[str, Any]:
resp = {
'amount': self.amount,
'amount': self.safe_amount,
'safe_price': self.safe_price,
'ft_order_side': self.ft_order_side,
'order_filled_timestamp': int(self.order_filled_date.replace(

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@ -90,7 +90,7 @@ async def _process_consumer_request(
elif type == RPCRequestType.ANALYZED_DF:
# Limit the amount of candles per dataframe to 'limit' or 1500
limit = min(data.get('limit', 1500), 1500) if data else None
limit = int(min(data.get('limit', 1500), 1500)) if data else None
pair = data.get('pair', None) if data else None
# 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):
# Add the same dataframe again - dataframe size shall not change.
res = dp._add_external_df('ETH/USDT', df, last_analyzed, timeframe, CandleType.SPOT)
assert res[0] is True
assert isinstance(res[1], int)
assert res[1] == 0
df, _ = dp.get_producer_df('ETH/USDT', timeframe, CandleType.SPOT)
assert len(df) == 24
@ -446,6 +447,7 @@ def test_dp__add_external_df(default_conf_usdt):
res = dp._add_external_df('ETH/USDT', df2, last_analyzed, timeframe, CandleType.SPOT)
assert res[0] is True
assert isinstance(res[1], int)
assert res[1] == 0
df, _ = dp.get_producer_df('ETH/USDT', timeframe, CandleType.SPOT)
assert len(df) == 48
@ -455,6 +457,7 @@ def test_dp__add_external_df(default_conf_usdt):
res = dp._add_external_df('ETH/USDT', df3, last_analyzed, timeframe, CandleType.SPOT)
assert res[0] is True
assert isinstance(res[1], int)
assert res[1] == 0
df, _ = dp.get_producer_df('ETH/USDT', timeframe, CandleType.SPOT)
# New length = 48 + 12 (since we have a 12 hour offset).
@ -478,6 +481,7 @@ def test_dp__add_external_df(default_conf_usdt):
res = dp._add_external_df('ETH/USDT', df4, last_analyzed, timeframe, CandleType.SPOT)
assert res[0] is False
# 36 hours - from 2022-01-03 12:00:00+00:00 to 2022-01-05 00:00:00+00:00
assert isinstance(res[1], int)
assert res[1] == 36
df, _ = dp.get_producer_df('ETH/USDT', timeframe, CandleType.SPOT)
# New length = 61 + 1
@ -488,4 +492,5 @@ def test_dp__add_external_df(default_conf_usdt):
res = dp._add_external_df('ETH/USDT', df4, last_analyzed, timeframe, CandleType.SPOT)
assert res[0] is False
# 36 hours - from 2022-01-03 12:00:00+00:00 to 2022-01-05 00:00:00+00:00
assert isinstance(res[1], int)
assert res[1] == 0

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@ -49,8 +49,8 @@ EXCHANGES = {
"orderListId": -1,
"clientOrderId": "x-R4DD3S8297c73a11ccb9dc8f2811ba",
"transactTime": 1674493798550,
"price": "15.00000000",
"origQty": "1.00000000",
"price": "15.50000000",
"origQty": "1.10000000",
"executedQty": "0.00000000",
"cummulativeQuoteQty": "0.00000000",
"status": "NEW",
@ -74,8 +74,8 @@ EXCHANGES = {
"orderListId": -1,
"clientOrderId": "x-R4DD3S8297c73a11ccb9dc8f2811ba",
"transactTime": 1674493798550,
"price": "15.00000000",
"origQty": "1.00000000",
"price": "15.50000000",
"origQty": "1.10000000",
"executedQty": "0.00000000",
"cummulativeQuoteQty": "0.00000000",
"status": "NEW",
@ -106,12 +106,12 @@ EXCHANGES = {
{'id': '63d6742d0adc5570001d2bbf7'}, # create order
{
'id': '63d6742d0adc5570001d2bbf7',
'symbol': 'NAKA-USDT',
'symbol': 'SOL-USDT',
'opType': 'DEAL',
'type': 'limit',
'side': 'buy',
'price': '30',
'size': '0.1',
'price': '15.5',
'size': '1.1',
'funds': '0',
'dealFunds': '0.032626',
'dealSize': '0.1',
@ -168,6 +168,23 @@ EXCHANGES = {
'futures': True,
'leverage_tiers_public': True,
'leverage_in_spot_market': True,
'sample_order': [
{
"orderId": "1274754916287346280",
"orderLinkId": "1666798627015730",
"symbol": "SOLUSDT",
"createTime": "1674493798550",
"orderPrice": "15.5",
"orderQty": "1.1",
"orderType": "LIMIT",
"side": "BUY",
"status": "NEW",
"timeInForce": "GTC",
"accountId": "5555555",
"execQty": "0",
"orderCategory": "0"
}
]
},
'huobi': {
'pair': 'ETH/BTC',
@ -306,12 +323,18 @@ class TestCCXTExchange():
po = exch._api.parse_order(order)
assert isinstance(po['id'], str)
assert po['id'] is not None
if len(order.keys()) > 1:
if len(order.keys()) < 5:
# Kucoin case
assert po['status'] == 'closed'
continue
assert po['timestamp'] == 1674493798550
assert isinstance(po['datetime'], str)
assert isinstance(po['timestamp'], int)
assert isinstance(po['price'], float)
assert po['price'] == 15.5
assert po['symbol'] == 'SOL/USDT'
assert isinstance(po['amount'], float)
assert po['amount'] == 1.1
assert isinstance(po['status'], str)
else:
pytest.skip(f"No sample order available for exchange {exchange_name}")