Merge branch 'develop' into bot-start

This commit is contained in:
Sam Germain 2022-04-29 22:23:42 -06:00
commit 4a6f1e90c3
25 changed files with 187 additions and 116 deletions

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@ -309,6 +309,9 @@ jobs:
webhookUrl: ${{ secrets.DISCORD_WEBHOOK }}
cleanup-prior-runs:
permissions:
actions: write # for rokroskar/workflow-run-cleanup-action to obtain workflow name & cancel it
contents: read # for rokroskar/workflow-run-cleanup-action to obtain branch
runs-on: ubuntu-20.04
steps:
- name: Cleanup previous runs on this branch
@ -321,6 +324,10 @@ jobs:
notify-complete:
needs: [ build_linux, build_macos, build_windows, docs_check, mypy_version_check ]
runs-on: ubuntu-20.04
# Discord notification can't handle schedule events
if: (github.event_name != 'schedule')
permissions:
repository-projects: read
steps:
- name: Check user permission

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@ -39,6 +39,14 @@ Please read the [exchange specific notes](docs/exchanges.md) to learn about even
- [X] [OKX](https://okx.com/) (Former OKEX)
- [ ] [potentially many others](https://github.com/ccxt/ccxt/). _(We cannot guarantee they will work)_
### Experimentally, freqtrade also supports futures on the following exchanges
- [X] [Binance](https://www.binance.com/)
- [X] [Gate.io](https://www.gate.io/ref/6266643)
- [X] [OKX](https://okx.com/).
Please make sure to read the [exchange specific notes](docs/exchanges.md), as well as the [trading with leverage](docs/leverage.md) documentation before diving in.
### Community tested
Exchanges confirmed working by the community:

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@ -90,7 +90,7 @@
},
"bot_name": "freqtrade",
"initial_state": "running",
"force_enter_enable": false,
"force_entry_enable": false,
"internals": {
"process_throttle_secs": 5
}

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@ -51,6 +51,14 @@ Please read the [exchange specific notes](exchanges.md) to learn about eventual,
- [X] [OKX](https://okx.com/) (Former OKEX)
- [ ] [potentially many others through <img alt="ccxt" width="30px" src="assets/ccxt-logo.svg" />](https://github.com/ccxt/ccxt/). _(We cannot guarantee they will work)_
### Experimentally, freqtrade also supports futures on the following exchanges:
- [X] [Binance](https://www.binance.com/)
- [X] [Gate.io](https://www.gate.io/ref/6266643)
- [X] [OKX](https://okx.com/).
Please make sure to read the [exchange specific notes](exchanges.md), as well as the [trading with leverage](leverage.md) documentation before diving in.
### Community tested
Exchanges confirmed working by the community:

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@ -146,11 +146,11 @@ See [Dataframe access](strategy-advanced.md#dataframe-access) for more informati
## Custom stoploss
Called for open trade every throttling iteration (roughly every 5 seconds) until a trade is closed.
Called for open trade every iteration (roughly every 5 seconds) until a trade is closed.
The usage of the custom stoploss method must be enabled by setting `use_custom_stoploss=True` on the strategy object.
The stoploss price can only ever move upwards - if the stoploss value returned from `custom_stoploss` would result in a lower stoploss price than was previously set, it will be ignored. The traditional `stoploss` value serves as an absolute lower level and will be instated as the initial stoploss (before this method is called for the first time for a trade).
The stoploss price can only ever move upwards - if the stoploss value returned from `custom_stoploss` would result in a lower stoploss price than was previously set, it will be ignored. The traditional `stoploss` value serves as an absolute lower level and will be instated as the initial stoploss (before this method is called for the first time for a trade), and is still mandatory.
The method must return a stoploss value (float / number) as a percentage of the current price.
E.g. If the `current_rate` is 200 USD, then returning `0.02` will set the stoploss price 2% lower, at 196 USD.
@ -389,30 +389,30 @@ class AwesomeStrategy(IStrategy):
# ... populate_* methods
def custom_entry_price(self, pair: str, current_time: datetime, proposed_rate: float,
def custom_entry_price(self, pair: str, current_time: datetime, proposed_rate: float,
entry_tag: Optional[str], side: str, **kwargs) -> float:
dataframe, last_updated = self.dp.get_analyzed_dataframe(pair=pair,
timeframe=self.timeframe)
new_entryprice = dataframe['bollinger_10_lowerband'].iat[-1]
return new_entryprice
def custom_exit_price(self, pair: str, trade: Trade,
current_time: datetime, proposed_rate: float,
current_profit: float, **kwargs) -> float:
current_profit: float, exit_tag: Optional[str], **kwargs) -> float:
dataframe, last_updated = self.dp.get_analyzed_dataframe(pair=pair,
timeframe=self.timeframe)
new_exitprice = dataframe['bollinger_10_upperband'].iat[-1]
return new_exitprice
```
!!! Warning
Modifying entry and exit prices will only work for limit orders. Depending on the price chosen, this can result in a lot of unfilled orders. By default the maximum allowed distance between the current price and the custom price is 2%, this value can be changed in config with the `custom_price_max_distance_ratio` parameter.
**Example**:
Modifying entry and exit prices will only work for limit orders. Depending on the price chosen, this can result in a lot of unfilled orders. By default the maximum allowed distance between the current price and the custom price is 2%, this value can be changed in config with the `custom_price_max_distance_ratio` parameter.
**Example**:
If the new_entryprice is 97, the proposed_rate is 100 and the `custom_price_max_distance_ratio` is set to 2%, The retained valid custom entry price will be 98, which is 2% below the current (proposed) rate.
!!! Warning "Backtesting"
@ -454,7 +454,7 @@ class AwesomeStrategy(IStrategy):
'exit': 60 * 25
}
def check_entry_timeout(self, pair: str, trade: 'Trade', order: 'Order',
def check_entry_timeout(self, pair: str, trade: 'Trade', order: 'Order',
current_time: datetime, **kwargs) -> bool:
if trade.open_rate > 100 and trade.open_date_utc < current_time - timedelta(minutes=5):
return True
@ -532,7 +532,7 @@ class AwesomeStrategy(IStrategy):
# ... populate_* methods
def confirm_trade_entry(self, pair: str, order_type: str, amount: float, rate: float,
time_in_force: str, current_time: datetime, entry_tag: Optional[str],
time_in_force: str, current_time: datetime, entry_tag: Optional[str],
side: str, **kwargs) -> bool:
"""
Called right before placing a entry order.
@ -640,35 +640,35 @@ from freqtrade.persistence import Trade
class DigDeeperStrategy(IStrategy):
position_adjustment_enable = True
# Attempts to handle large drops with DCA. High stoploss is required.
stoploss = -0.30
# ... populate_* methods
# Example specific variables
max_entry_position_adjustment = 3
# This number is explained a bit further down
max_dca_multiplier = 5.5
# This is called when placing the initial order (opening trade)
def custom_stake_amount(self, pair: str, current_time: datetime, current_rate: float,
proposed_stake: float, min_stake: float, max_stake: float,
entry_tag: Optional[str], side: str, **kwargs) -> float:
# We need to leave most of the funds for possible further DCA orders
# This also applies to fixed stakes
return proposed_stake / self.max_dca_multiplier
def adjust_trade_position(self, trade: Trade, current_time: datetime,
current_rate: float, current_profit: float, min_stake: float,
max_stake: float, **kwargs):
"""
Custom trade adjustment logic, returning the stake amount that a trade should be increased.
This means extra buy orders with additional fees.
:param trade: trade object.
:param current_time: datetime object, containing the current datetime
:param current_rate: Current buy rate.
@ -678,7 +678,7 @@ class DigDeeperStrategy(IStrategy):
:param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
:return float: Stake amount to adjust your trade
"""
if current_profit > -0.05:
return None

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@ -12,7 +12,8 @@ import pandas as pd
from freqtrade.constants import LAST_BT_RESULT_FN
from freqtrade.exceptions import OperationalException
from freqtrade.misc import get_backtest_metadata_filename, json_load
from freqtrade.misc import json_load
from freqtrade.optimize.backtest_caching import get_backtest_metadata_filename
from freqtrade.persistence import LocalTrade, Trade, init_db

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@ -9,6 +9,7 @@ import logging
from copy import deepcopy
from datetime import datetime, timedelta, timezone
from math import ceil
from threading import Lock
from typing import Any, Coroutine, Dict, List, Literal, Optional, Tuple, Union
import arrow
@ -96,6 +97,9 @@ class Exchange:
self._markets: Dict = {}
self._trading_fees: Dict[str, Any] = {}
self._leverage_tiers: Dict[str, List[Dict]] = {}
# Lock event loop. This is necessary to avoid race-conditions when using force* commands
# Due to funding fee fetching.
self._loop_lock = Lock()
self.loop = asyncio.new_event_loop()
asyncio.set_event_loop(self.loop)
self._config: Dict = {}
@ -167,7 +171,7 @@ class Exchange:
self._api_async = self._init_ccxt(
exchange_config, ccxt_async, ccxt_kwargs=ccxt_async_config)
logger.info('Using Exchange "%s"', self.name)
logger.info(f'Using Exchange "{self.name}"')
if validate:
# Check if timeframe is available
@ -555,7 +559,7 @@ class Exchange:
# Therefore we also show that.
raise OperationalException(
f"The ccxt library does not provide the list of timeframes "
f"for the exchange \"{self.name}\" and this exchange "
f"for the exchange {self.name} and this exchange "
f"is therefore not supported. ccxt fetchOHLCV: {self.exchange_has('fetchOHLCV')}")
if timeframe and (timeframe not in self.timeframes):
@ -785,7 +789,9 @@ class Exchange:
rate: float, leverage: float, params: Dict = {},
stop_loss: bool = False) -> Dict[str, Any]:
order_id = f'dry_run_{side}_{datetime.now().timestamp()}'
_amount = self.amount_to_precision(pair, amount)
# Rounding here must respect to contract sizes
_amount = self._contracts_to_amount(
pair, self.amount_to_precision(pair, self._amount_to_contracts(pair, amount)))
dry_order: Dict[str, Any] = {
'id': order_id,
'symbol': pair,
@ -1775,7 +1781,8 @@ class Exchange:
async def gather_stuff():
return await asyncio.gather(*input_coro, return_exceptions=True)
results = self.loop.run_until_complete(gather_stuff())
with self._loop_lock:
results = self.loop.run_until_complete(gather_stuff())
for res in results:
if isinstance(res, Exception):
@ -2032,9 +2039,10 @@ class Exchange:
if not self.exchange_has("fetchTrades"):
raise OperationalException("This exchange does not support downloading Trades.")
return self.loop.run_until_complete(
self._async_get_trade_history(pair=pair, since=since,
until=until, from_id=from_id))
with self._loop_lock:
return self.loop.run_until_complete(
self._async_get_trade_history(pair=pair, since=since,
until=until, from_id=from_id))
@retrier
def _get_funding_fees_from_exchange(self, pair: str, since: Union[datetime, int]) -> float:

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@ -587,7 +587,6 @@ class FreqtradeBot(LoggingMixin):
Executes a limit buy for the given pair
:param pair: pair for which we want to create a LIMIT_BUY
:param stake_amount: amount of stake-currency for the pair
:param leverage: amount of leverage applied to this trade
:return: True if a buy order is created, false if it fails.
"""
time_in_force = self.strategy.order_time_in_force['entry']
@ -666,16 +665,6 @@ class FreqtradeBot(LoggingMixin):
amount = safe_value_fallback(order, 'filled', 'amount')
enter_limit_filled_price = safe_value_fallback(order, 'average', 'price')
# TODO: this might be unnecessary, as we're calling it in update_trade_state.
isolated_liq = self.exchange.get_liquidation_price(
leverage=leverage,
pair=pair,
amount=amount,
open_rate=enter_limit_filled_price,
is_short=is_short
)
interest_rate = self.exchange.get_interest_rate()
# Fee is applied twice because we make a LIMIT_BUY and LIMIT_SELL
fee = self.exchange.get_fee(symbol=pair, taker_or_maker='maker')
base_currency = self.exchange.get_pair_base_currency(pair)
@ -704,8 +693,6 @@ class FreqtradeBot(LoggingMixin):
timeframe=timeframe_to_minutes(self.config['timeframe']),
leverage=leverage,
is_short=is_short,
interest_rate=interest_rate,
liquidation_price=isolated_liq,
trading_mode=self.trading_mode,
funding_fees=funding_fees
)
@ -1375,7 +1362,8 @@ class FreqtradeBot(LoggingMixin):
default_retval=proposed_limit_rate)(
pair=trade.pair, trade=trade,
current_time=datetime.now(timezone.utc),
proposed_rate=proposed_limit_rate, current_profit=current_profit)
proposed_rate=proposed_limit_rate, current_profit=current_profit,
exit_tag=exit_check.exit_reason)
limit = self.get_valid_price(custom_exit_price, proposed_limit_rate)

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@ -2,13 +2,11 @@
Various tool function for Freqtrade and scripts
"""
import gzip
import hashlib
import logging
import re
from copy import deepcopy
from datetime import datetime
from pathlib import Path
from typing import Any, Iterator, List, Union
from typing import Any, Iterator, List
from typing.io import IO
from urllib.parse import urlparse
@ -251,34 +249,3 @@ def parse_db_uri_for_logging(uri: str):
return uri
pwd = parsed_db_uri.netloc.split(':')[1].split('@')[0]
return parsed_db_uri.geturl().replace(f':{pwd}@', ':*****@')
def get_strategy_run_id(strategy) -> str:
"""
Generate unique identification hash for a backtest run. Identical config and strategy file will
always return an identical hash.
:param strategy: strategy object.
:return: hex string id.
"""
digest = hashlib.sha1()
config = deepcopy(strategy.config)
# Options that have no impact on results of individual backtest.
not_important_keys = ('strategy_list', 'original_config', 'telegram', 'api_server')
for k in not_important_keys:
if k in config:
del config[k]
# Explicitly allow NaN values (e.g. max_open_trades).
# as it does not matter for getting the hash.
digest.update(rapidjson.dumps(config, default=str,
number_mode=rapidjson.NM_NAN).encode('utf-8'))
with open(strategy.__file__, 'rb') as fp:
digest.update(fp.read())
return digest.hexdigest().lower()
def get_backtest_metadata_filename(filename: Union[Path, str]) -> Path:
"""Return metadata filename for specified backtest results file."""
filename = Path(filename)
return filename.parent / Path(f'{filename.stem}.meta{filename.suffix}')

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@ -0,0 +1,40 @@
import hashlib
from copy import deepcopy
from pathlib import Path
from typing import Union
import rapidjson
def get_strategy_run_id(strategy) -> str:
"""
Generate unique identification hash for a backtest run. Identical config and strategy file will
always return an identical hash.
:param strategy: strategy object.
:return: hex string id.
"""
digest = hashlib.sha1()
config = deepcopy(strategy.config)
# Options that have no impact on results of individual backtest.
not_important_keys = ('strategy_list', 'original_config', 'telegram', 'api_server')
for k in not_important_keys:
if k in config:
del config[k]
# Explicitly allow NaN values (e.g. max_open_trades).
# as it does not matter for getting the hash.
digest.update(rapidjson.dumps(config, default=str,
number_mode=rapidjson.NM_NAN).encode('utf-8'))
# Include _ft_params_from_file - so changing parameter files cause cache eviction
digest.update(rapidjson.dumps(
strategy._ft_params_from_file, default=str, number_mode=rapidjson.NM_NAN).encode('utf-8'))
with open(strategy.__file__, 'rb') as fp:
digest.update(fp.read())
return digest.hexdigest().lower()
def get_backtest_metadata_filename(filename: Union[Path, str]) -> Path:
"""Return metadata filename for specified backtest results file."""
filename = Path(filename)
return filename.parent / Path(f'{filename.stem}.meta{filename.suffix}')

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@ -24,8 +24,8 @@ from freqtrade.enums import (BacktestState, CandleType, ExitCheckTuple, ExitType
TradingMode)
from freqtrade.exceptions import DependencyException, OperationalException
from freqtrade.exchange import timeframe_to_minutes, timeframe_to_seconds
from freqtrade.misc import get_strategy_run_id
from freqtrade.mixins import LoggingMixin
from freqtrade.optimize.backtest_caching import get_strategy_run_id
from freqtrade.optimize.bt_progress import BTProgress
from freqtrade.optimize.optimize_reports import (generate_backtest_stats, show_backtest_results,
store_backtest_signal_candles,
@ -54,6 +54,11 @@ ESHORT_IDX = 8 # Exit short
ENTER_TAG_IDX = 9
EXIT_TAG_IDX = 10
# Every change to this headers list must evaluate further usages of the resulting tuple
# and eventually change the constants for indexes at the top
HEADERS = ['date', 'open', 'high', 'low', 'close', 'enter_long', 'exit_long',
'enter_short', 'exit_short', 'enter_tag', 'exit_tag']
class Backtesting:
"""
@ -265,10 +270,18 @@ class Backtesting:
candle_type=CandleType.from_string(self.exchange._ft_has["mark_ohlcv_price"])
)
# Combine data to avoid combining the data per trade.
unavailable_pairs = []
for pair in self.pairlists.whitelist:
if pair not in self.exchange._leverage_tiers:
unavailable_pairs.append(pair)
continue
self.futures_data[pair] = funding_rates_dict[pair].merge(
mark_rates_dict[pair], on='date', how="inner", suffixes=["_fund", "_mark"])
if unavailable_pairs:
raise OperationalException(
f"Pairs {', '.join(unavailable_pairs)} got no leverage tiers available. "
"It is therefore impossible to backtest with this pair at the moment.")
else:
self.futures_data = {}
@ -306,10 +319,7 @@ class Backtesting:
:param processed: a processed dictionary with format {pair, data}, which gets cleared to
optimize memory usage!
"""
# Every change to this headers list must evaluate further usages of the resulting tuple
# and eventually change the constants for indexes at the top
headers = ['date', 'open', 'high', 'low', 'close', 'enter_long', 'exit_long',
'enter_short', 'exit_short', 'enter_tag', 'exit_tag']
data: Dict = {}
self.progress.init_step(BacktestState.CONVERT, len(processed))
@ -321,7 +331,7 @@ class Backtesting:
if not pair_data.empty:
# Cleanup from prior runs
pair_data.drop(headers[5:] + ['buy', 'sell'], axis=1, errors='ignore')
pair_data.drop(HEADERS[5:] + ['buy', 'sell'], axis=1, errors='ignore')
df_analyzed = self.strategy.advise_exit(
self.strategy.advise_entry(pair_data, {'pair': pair}),
@ -340,7 +350,7 @@ class Backtesting:
# To avoid using data from future, we use entry/exit signals shifted
# from the previous candle
for col in headers[5:]:
for col in HEADERS[5:]:
tag_col = col in ('enter_tag', 'exit_tag')
if col in df_analyzed.columns:
df_analyzed.loc[:, col] = df_analyzed.loc[:, col].replace(
@ -352,7 +362,7 @@ class Backtesting:
# Convert from Pandas to list for performance reasons
# (Looping Pandas is slow.)
data[pair] = df_analyzed[headers].values.tolist() if not df_analyzed.empty else []
data[pair] = df_analyzed[HEADERS].values.tolist() if not df_analyzed.empty else []
return data
def _get_close_rate(self, row: Tuple, trade: LocalTrade, exit: ExitCheckTuple,
@ -516,10 +526,10 @@ class Backtesting:
exit_candle_time: datetime = row[DATE_IDX].to_pydatetime()
enter = row[SHORT_IDX] if trade.is_short else row[LONG_IDX]
exit_ = row[ESHORT_IDX] if trade.is_short else row[ELONG_IDX]
exit_sig = row[ESHORT_IDX] if trade.is_short else row[ELONG_IDX]
exit_ = self.strategy.should_exit(
trade, row[OPEN_IDX], exit_candle_time, # type: ignore
enter=enter, exit_=exit_,
enter=enter, exit_=exit_sig,
low=row[LOW_IDX], high=row[HIGH_IDX]
)
@ -541,7 +551,8 @@ class Backtesting:
default_retval=closerate)(
pair=trade.pair, trade=trade,
current_time=exit_candle_time,
proposed_rate=closerate, current_profit=current_profit)
proposed_rate=closerate, current_profit=current_profit,
exit_tag=exit_.exit_reason)
# We can't place orders lower than current low.
# freqtrade does not support this in live, and the order would fill immediately
if trade.is_short:
@ -568,6 +579,7 @@ class Backtesting:
len(row) > EXIT_TAG_IDX
and row[EXIT_TAG_IDX] is not None
and len(row[EXIT_TAG_IDX]) > 0
and exit_.exit_type in (ExitType.EXIT_SIGNAL,)
):
trade.exit_reason = row[EXIT_TAG_IDX]
@ -626,9 +638,7 @@ class Backtesting:
detail_data.loc[:, 'exit_short'] = row[ESHORT_IDX]
detail_data.loc[:, 'enter_tag'] = row[ENTER_TAG_IDX]
detail_data.loc[:, 'exit_tag'] = row[EXIT_TAG_IDX]
headers = ['date', 'open', 'high', 'low', 'close', 'enter_long', 'exit_long',
'enter_short', 'exit_short', 'enter_tag', 'exit_tag']
for det_row in detail_data[headers].values.tolist():
for det_row in detail_data[HEADERS].values.tolist():
res = self._get_exit_trade_entry_for_candle(trade, det_row)
if res:
return res

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@ -468,6 +468,7 @@ class Hyperopt:
self.backtesting.exchange._api = None
self.backtesting.exchange._api_async = None
self.backtesting.exchange.loop = None # type: ignore
self.backtesting.exchange._loop_lock = None # type: ignore
# self.backtesting.exchange = None # type: ignore
self.backtesting.pairlists = None # type: ignore

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@ -11,8 +11,8 @@ from tabulate import tabulate
from freqtrade.constants import DATETIME_PRINT_FORMAT, LAST_BT_RESULT_FN, UNLIMITED_STAKE_AMOUNT
from freqtrade.data.btanalysis import (calculate_cagr, calculate_csum, calculate_market_change,
calculate_max_drawdown)
from freqtrade.misc import (decimals_per_coin, file_dump_joblib, file_dump_json,
get_backtest_metadata_filename, round_coin_value)
from freqtrade.misc import decimals_per_coin, file_dump_joblib, file_dump_json, round_coin_value
from freqtrade.optimize.backtest_caching import get_backtest_metadata_filename
logger = logging.getLogger(__name__)

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@ -429,12 +429,10 @@ class LocalTrade():
def __repr__(self):
open_since = self.open_date.strftime(DATETIME_PRINT_FORMAT) if self.is_open else 'closed'
leverage = self.leverage or 1.0
is_short = self.is_short or False
return (
f'Trade(id={self.id}, pair={self.pair}, amount={self.amount:.8f}, '
f'is_short={is_short}, leverage={leverage}, '
f'is_short={self.is_short or False}, leverage={self.leverage or 1.0}, '
f'open_rate={self.open_rate:.8f}, open_since={open_since})'
)

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@ -2,7 +2,7 @@ import logging
from ipaddress import IPv4Address
from typing import Any, Dict
import rapidjson
import orjson
import uvicorn
from fastapi import Depends, FastAPI
from fastapi.middleware.cors import CORSMiddleware
@ -24,7 +24,7 @@ class FTJSONResponse(JSONResponse):
Use rapidjson for responses
Handles NaN and Inf / -Inf in a javascript way by default.
"""
return rapidjson.dumps(content).encode("utf-8")
return orjson.dumps(content, option=orjson.OPT_SERIALIZE_NUMPY)
class ApiServer(RPCHandler):

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@ -943,7 +943,7 @@ class Telegram(RPCHandler):
else:
fiat_currency = self._config.get('fiat_display_currency', '')
try:
statlist, head, fiat_profit_sum = self._rpc._rpc_status_table(
statlist, _, _ = self._rpc._rpc_status_table(
self._config['stake_currency'], fiat_currency)
except RPCException:
self._send_msg(msg='No open trade found.')

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@ -362,7 +362,7 @@ class IStrategy(ABC, HyperStrategyMixin):
def custom_exit_price(self, pair: str, trade: Trade,
current_time: datetime, proposed_rate: float,
current_profit: float, **kwargs) -> float:
current_profit: float, exit_tag: Optional[str], **kwargs) -> float:
"""
Custom exit price logic, returning the new exit price.
@ -375,6 +375,7 @@ class IStrategy(ABC, HyperStrategyMixin):
:param current_time: datetime object, containing the current datetime
:param proposed_rate: Rate, calculated based on pricing settings in exit_pricing.
:param current_profit: Current profit (as ratio), calculated based on current_rate.
:param exit_tag: Exit reason.
:param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
:return float: New exit price value if provided
"""

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@ -32,7 +32,7 @@ def custom_entry_price(self, pair: str, current_time: 'datetime', proposed_rate:
def custom_exit_price(self, pair: str, trade: 'Trade',
current_time: 'datetime', proposed_rate: float,
current_profit: float, **kwargs) -> float:
current_profit: float, exit_tag: Optional[str], **kwargs) -> float:
"""
Custom exit price logic, returning the new exit price.
@ -45,6 +45,7 @@ def custom_exit_price(self, pair: str, trade: 'Trade',
:param current_time: datetime object, containing the current datetime
:param proposed_rate: Rate, calculated based on pricing settings in exit_pricing.
:param current_profit: Current profit (as ratio), calculated based on current_rate.
:param exit_tag: Exit reason.
:param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
:return float: New exit price value if provided
"""

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@ -23,7 +23,7 @@ exclude = '''
line_length = 100
multi_line_output=0
lines_after_imports=2
skip_glob = ["**/.env*", "**/env/*", "**/.venv/*", "**/docs/*"]
skip_glob = ["**/.env*", "**/env/*", "**/.venv/*", "**/docs/*", "**/user_data/*"]
[tool.pytest.ini_options]
asyncio_mode = "auto"

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@ -27,6 +27,8 @@ py_find_1st==1.1.5
# Load ticker files 30% faster
python-rapidjson==1.6
# Properly format api responses
orjson==3.6.8
# Notify systemd
sdnotify==0.3.2

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@ -57,6 +57,7 @@ setup(
'pycoingecko',
'py_find_1st',
'python-rapidjson',
'orjson',
'sdnotify',
'colorama',
'jinja2',

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@ -909,7 +909,7 @@ def test_validate_timeframes_emulated_ohlcv_1(default_conf, mocker):
mocker.patch('freqtrade.exchange.Exchange.validate_stakecurrency')
with pytest.raises(OperationalException,
match=r'The ccxt library does not provide the list of timeframes '
r'for the exchange ".*" and this exchange '
r'for the exchange .* and this exchange '
r'is therefore not supported. *'):
Exchange(default_conf)
@ -930,7 +930,7 @@ def test_validate_timeframes_emulated_ohlcvi_2(default_conf, mocker):
mocker.patch('freqtrade.exchange.Exchange.validate_stakecurrency')
with pytest.raises(OperationalException,
match=r'The ccxt library does not provide the list of timeframes '
r'for the exchange ".*" and this exchange '
r'for the exchange .* and this exchange '
r'is therefore not supported. *'):
Exchange(default_conf)

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@ -22,7 +22,7 @@ from freqtrade.data.history import get_timerange
from freqtrade.enums import ExitType, RunMode
from freqtrade.exceptions import DependencyException, OperationalException
from freqtrade.exchange.exchange import timeframe_to_next_date
from freqtrade.misc import get_strategy_run_id
from freqtrade.optimize.backtest_caching import get_strategy_run_id
from freqtrade.optimize.backtesting import Backtesting
from freqtrade.persistence import LocalTrade
from freqtrade.resolvers import StrategyResolver
@ -1342,6 +1342,39 @@ def test_backtest_start_multi_strat_nomock(default_conf, mocker, caplog, testdat
assert 'STRATEGY SUMMARY' in captured.out
@pytest.mark.filterwarnings("ignore:deprecated")
def test_backtest_start_futures_noliq(default_conf_usdt, mocker,
caplog, testdatadir, capsys):
# Tests detail-data loading
default_conf_usdt.update({
"trading_mode": "futures",
"margin_mode": "isolated",
"use_exit_signal": True,
"exit_profit_only": False,
"exit_profit_offset": 0.0,
"ignore_roi_if_entry_signal": False,
"strategy": CURRENT_TEST_STRATEGY,
})
patch_exchange(mocker)
mocker.patch('freqtrade.plugins.pairlistmanager.PairListManager.whitelist',
PropertyMock(return_value=['HULUMULU/USDT', 'XRP/USDT']))
# mocker.patch('freqtrade.optimize.backtesting.Backtesting.backtest', backtestmock)
patched_configuration_load_config_file(mocker, default_conf_usdt)
args = [
'backtesting',
'--config', 'config.json',
'--datadir', str(testdatadir),
'--strategy-path', str(Path(__file__).parents[1] / 'strategy/strats'),
'--timeframe', '1h',
]
args = get_args(args)
with pytest.raises(OperationalException, match=r"Pairs .* got no leverage tiers available\."):
start_backtesting(args)
@pytest.mark.filterwarnings("ignore:deprecated")
def test_backtest_start_nomock_futures(default_conf_usdt, mocker,
caplog, testdatadir, capsys):

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@ -13,7 +13,6 @@ import uvicorn
from fastapi import FastAPI
from fastapi.exceptions import HTTPException
from fastapi.testclient import TestClient
from numpy import isnan
from requests.auth import _basic_auth_str
from freqtrade.__init__ import __version__
@ -985,7 +984,7 @@ def test_api_status(botclient, mocker, ticker, fee, markets, is_short,
assert_response(rc)
resp_values = rc.json()
assert len(resp_values) == 4
assert isnan(resp_values[0]['profit_abs'])
assert resp_values[0]['profit_abs'] is None
def test_api_version(botclient):

View File

@ -717,12 +717,12 @@ def test_process_informative_pairs_added(default_conf_usdt, ticker_usdt, mocker)
(True, 'spot', 'gateio', None, 0.0, None),
(False, 'spot', 'okx', None, 0.0, None),
(True, 'spot', 'okx', None, 0.0, None),
(True, 'futures', 'binance', 'isolated', 0.0, 11.89108910891089),
(False, 'futures', 'binance', 'isolated', 0.0, 8.070707070707071),
(True, 'futures', 'binance', 'isolated', 0.0, 11.88151815181518),
(False, 'futures', 'binance', 'isolated', 0.0, 8.080471380471382),
(True, 'futures', 'gateio', 'isolated', 0.0, 11.87413417771621),
(False, 'futures', 'gateio', 'isolated', 0.0, 8.085708510208207),
(True, 'futures', 'binance', 'isolated', 0.05, 11.796534653465345),
(False, 'futures', 'binance', 'isolated', 0.05, 8.167171717171717),
(True, 'futures', 'binance', 'isolated', 0.05, 11.7874422442244),
(False, 'futures', 'binance', 'isolated', 0.05, 8.17644781144781),
(True, 'futures', 'gateio', 'isolated', 0.05, 11.7804274688304),
(False, 'futures', 'gateio', 'isolated', 0.05, 8.181423084697796),
(True, 'futures', 'okx', 'isolated', 0.0, 11.87413417771621),
@ -845,6 +845,7 @@ def test_execute_entry(mocker, default_conf_usdt, fee, limit_order,
assert trade.open_order_id is None
assert trade.open_rate == 10
assert trade.stake_amount == round(order['price'] * order['filled'] / leverage, 8)
assert pytest.approx(trade.liquidation_price) == liq_price
# In case of rejected or expired order and partially filled
order['status'] = 'expired'
@ -932,8 +933,6 @@ def test_execute_entry(mocker, default_conf_usdt, fee, limit_order,
assert trade.open_rate_requested == 10
# In case of custom entry price not float type
freqtrade.exchange.get_maintenance_ratio_and_amt = MagicMock(return_value=(0.01, 0.01))
freqtrade.exchange.name = exchange_name
order['status'] = 'open'
order['id'] = '5568'
freqtrade.strategy.custom_entry_price = lambda **kwargs: "string price"
@ -946,7 +945,6 @@ def test_execute_entry(mocker, default_conf_usdt, fee, limit_order,
trade.is_short = is_short
assert trade
assert trade.open_rate_requested == 10
assert trade.liquidation_price == liq_price
# In case of too high stake amount
@ -3221,7 +3219,7 @@ def test_execute_trade_exit_custom_exit_price(
freqtrade.execute_trade_exit(
trade=trade,
limit=ticker_usdt_sell_up()['ask' if is_short else 'bid'],
exit_check=ExitCheckTuple(exit_type=ExitType.EXIT_SIGNAL)
exit_check=ExitCheckTuple(exit_type=ExitType.EXIT_SIGNAL, exit_reason='foo')
)
# Sell price must be different to default bid price
@ -3249,8 +3247,8 @@ def test_execute_trade_exit_custom_exit_price(
'profit_ratio': profit_ratio,
'stake_currency': 'USDT',
'fiat_currency': 'USD',
'sell_reason': ExitType.EXIT_SIGNAL.value,
'exit_reason': ExitType.EXIT_SIGNAL.value,
'sell_reason': 'foo',
'exit_reason': 'foo',
'open_date': ANY,
'close_date': ANY,
'close_rate': ANY,