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Merge branch 'develop' into pr/GluTbl/5756

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This commit is contained in:
Matthias
2021-12-03 17:37:44 +01:00
parent 00406ea7d5 d09a30cc67
commit d1209fe415
124 changed files with 3853 additions and 1534 deletions
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3
freqtrade/commands/__init__.py
View File

@@ -16,7 +16,8 @@ from freqtrade.commands.hyperopt_commands import start_hyperopt_list, start_hype
from freqtrade.commands.list_commands import (start_list_exchanges, start_list_markets,
start_list_strategies, start_list_timeframes,
start_show_trades)
from freqtrade.commands.optimize_commands import start_backtesting, start_edge, start_hyperopt
from freqtrade.commands.optimize_commands import (start_backtesting, start_backtesting_show,
start_edge, start_hyperopt)
from freqtrade.commands.pairlist_commands import start_test_pairlist
from freqtrade.commands.plot_commands import start_plot_dataframe, start_plot_profit
from freqtrade.commands.trade_commands import start_trading

21
freqtrade/commands/arguments.py
View File

@@ -23,7 +23,8 @@ ARGS_COMMON_OPTIMIZE = ["timeframe", "timerange", "dataformat_ohlcv",
ARGS_BACKTEST = ARGS_COMMON_OPTIMIZE + ["position_stacking", "use_max_market_positions",
"enable_protections", "dry_run_wallet", "timeframe_detail",
"strategy_list", "export", "exportfilename"]
"strategy_list", "export", "exportfilename",
"backtest_breakdown"]
ARGS_HYPEROPT = ARGS_COMMON_OPTIMIZE + ["hyperopt", "hyperopt_path",
"position_stacking", "use_max_market_positions",
@@ -40,6 +41,8 @@ ARGS_LIST_STRATEGIES = ["strategy_path", "print_one_column", "print_colorized"]
ARGS_LIST_HYPEROPTS = ["hyperopt_path", "print_one_column", "print_colorized"]
ARGS_BACKTEST_SHOW = ["exportfilename", "backtest_show_pair_list"]
ARGS_LIST_EXCHANGES = ["print_one_column", "list_exchanges_all"]
ARGS_LIST_TIMEFRAMES = ["exchange", "print_one_column"]
@@ -89,11 +92,11 @@ ARGS_HYPEROPT_LIST = ["hyperopt_list_best", "hyperopt_list_profitable",
ARGS_HYPEROPT_SHOW = ["hyperopt_list_best", "hyperopt_list_profitable", "hyperopt_show_index",
"print_json", "hyperoptexportfilename", "hyperopt_show_no_header",
"disableparamexport"]
"disableparamexport", "backtest_breakdown"]
NO_CONF_REQURIED = ["convert-data", "convert-trade-data", "download-data", "list-timeframes",
"list-markets", "list-pairs", "list-strategies", "list-data",
"hyperopt-list", "hyperopt-show",
"hyperopt-list", "hyperopt-show", "backtest-filter",
"plot-dataframe", "plot-profit", "show-trades", "trades-to-ohlcv"]
NO_CONF_ALLOWED = ["create-userdir", "list-exchanges", "new-strategy"]
@@ -172,7 +175,8 @@ class Arguments:
self.parser = argparse.ArgumentParser(description='Free, open source crypto trading bot')
self._build_args(optionlist=['version'], parser=self.parser)
from freqtrade.commands import (start_backtesting, start_convert_data, start_convert_trades,
from freqtrade.commands import (start_backtesting, start_backtesting_show,
start_convert_data, start_convert_trades,
start_create_userdir, start_download_data, start_edge,
start_hyperopt, start_hyperopt_list, start_hyperopt_show,
start_install_ui, start_list_data, start_list_exchanges,
@@ -263,6 +267,15 @@ class Arguments:
backtesting_cmd.set_defaults(func=start_backtesting)
self._build_args(optionlist=ARGS_BACKTEST, parser=backtesting_cmd)
# Add backtesting-show subcommand
backtesting_show_cmd = subparsers.add_parser(
'backtesting-show',
help='Show past Backtest results',
parents=[_common_parser],
)
backtesting_show_cmd.set_defaults(func=start_backtesting_show)
self._build_args(optionlist=ARGS_BACKTEST_SHOW, parser=backtesting_show_cmd)
# Add edge subcommand
edge_cmd = subparsers.add_parser('edge', help='Edge module.',
parents=[_common_parser, _strategy_parser])

11
freqtrade/commands/build_config_commands.py
View File

@@ -83,11 +83,19 @@ def ask_user_config() -> Dict[str, Any]:
if val == UNLIMITED_STAKE_AMOUNT
else val
},
{
"type": "select",
"name": "timeframe_in_config",
"message": "Tim",
"choices": ["Have the strategy define timeframe.", "Override in configuration."]
},
{
"type": "text",
"name": "timeframe",
"message": "Please insert your desired timeframe (e.g. 5m):",
"default": "5m",
"when": lambda x: x["timeframe_in_config"] == 'Override in configuration.'
},
{
"type": "text",
@@ -107,6 +115,7 @@ def ask_user_config() -> Dict[str, Any]:
"ftx",
"kucoin",
"gateio",
"okex",
Separator(),
"other",
],
@@ -134,7 +143,7 @@ def ask_user_config() -> Dict[str, Any]:
"type": "password",
"name": "exchange_key_password",
"message": "Insert Exchange API Key password",
"when": lambda x: not x['dry_run'] and x['exchange_name'] == 'kucoin'
"when": lambda x: not x['dry_run'] and x['exchange_name'] in ('kucoin', 'okex')
},
{
"type": "confirm",

12
freqtrade/commands/cli_options.py
View File

@@ -152,6 +152,12 @@ AVAILABLE_CLI_OPTIONS = {
action='store_false',
default=True,
),
"backtest_show_pair_list": Arg(
'--show-pair-list',
help='Show backtesting pairlist sorted by profit.',
action='store_true',
default=False,
),
"enable_protections": Arg(
'--enable-protections', '--enableprotections',
help='Enable protections for backtesting.'
@@ -193,6 +199,12 @@ AVAILABLE_CLI_OPTIONS = {
type=float,
metavar='FLOAT',
),
"backtest_breakdown": Arg(
'--breakdown',
help='Show backtesting breakdown per [day, week, month].',
nargs='+',
choices=constants.BACKTEST_BREAKDOWNS
),
# Edge
"stoploss_range": Arg(
'--stoplosses',

2
freqtrade/commands/hyperopt_commands.py
View File

@@ -96,7 +96,7 @@ def start_hyperopt_show(args: Dict[str, Any]) -> None:
if 'strategy_name' in metrics:
strategy_name = metrics['strategy_name']
show_backtest_result(strategy_name, metrics,
metrics['stake_currency'])
metrics['stake_currency'], config.get('backtest_breakdown', []))
HyperoptTools.try_export_params(config, strategy_name, val)

16
freqtrade/commands/optimize_commands.py
View File

@@ -54,6 +54,22 @@ def start_backtesting(args: Dict[str, Any]) -> None:
backtesting.start()
def start_backtesting_show(args: Dict[str, Any]) -> None:
"""
Show previous backtest result
"""
config = setup_utils_configuration(args, RunMode.UTIL_NO_EXCHANGE)
from freqtrade.data.btanalysis import load_backtest_stats
from freqtrade.optimize.optimize_reports import show_backtest_results, show_sorted_pairlist
results = load_backtest_stats(config['exportfilename'])
show_backtest_results(config, results)
show_sorted_pairlist(config, results)
def start_hyperopt(args: Dict[str, Any]) -> None:
"""
Start hyperopt script

8
freqtrade/configuration/configuration.py
View File

@@ -245,6 +245,10 @@ class Configuration:
self._args_to_config(config, argname='timeframe_detail',
logstring='Parameter --timeframe-detail detected, '
'using {} for intra-candle backtesting ...')
self._args_to_config(config, argname='backtest_show_pair_list',
logstring='Parameter --show-pair-list detected.')
self._args_to_config(config, argname='stake_amount',
logstring='Parameter --stake-amount detected, '
'overriding stake_amount to: {} ...')
@@ -269,8 +273,12 @@ class Configuration:
self._args_to_config(config, argname='export',
logstring='Parameter --export detected: {} ...')
self._args_to_config(config, argname='backtest_breakdown',
logstring='Parameter --breakdown detected ...')
self._args_to_config(config, argname='disableparamexport',
logstring='Parameter --disableparamexport detected: {} ...')
# Edge section:
if 'stoploss_range' in self.args and self.args["stoploss_range"]:
txt_range = eval(self.args["stoploss_range"])

5
freqtrade/configuration/environment_vars.py
View File

@@ -32,6 +32,7 @@ def flat_vars_to_nested_dict(env_dict: Dict[str, Any], prefix: str) -> Dict[str,
:param prefix: Prefix to consider (usually FREQTRADE__)
:return: Nested dict based on available and relevant variables.
"""
no_convert = ['CHAT_ID']
relevant_vars: Dict[str, Any] = {}
for env_var, val in sorted(env_dict.items()):
@@ -39,9 +40,9 @@ def flat_vars_to_nested_dict(env_dict: Dict[str, Any], prefix: str) -> Dict[str,
logger.info(f"Loading variable '{env_var}'")
key = env_var.replace(prefix, '')
for k in reversed(key.split('__')):
val = {k.lower(): get_var_typed(val) if type(val) != dict else val}
val = {k.lower(): get_var_typed(val)
if type(val) != dict and k not in no_convert else val}
relevant_vars = deep_merge_dicts(val, relevant_vars)
return relevant_vars

32
freqtrade/constants.py
View File

@@ -25,6 +25,7 @@ ORDERTIF_POSSIBILITIES = ['gtc', 'fok', 'ioc']
HYPEROPT_LOSS_BUILTIN = ['ShortTradeDurHyperOptLoss', 'OnlyProfitHyperOptLoss',
'SharpeHyperOptLoss', 'SharpeHyperOptLossDaily',
'SortinoHyperOptLoss', 'SortinoHyperOptLossDaily',
'CalmarHyperOptLoss',
'MaxDrawDownHyperOptLoss']
AVAILABLE_PAIRLISTS = ['StaticPairList', 'VolumePairList',
'AgeFilter', 'OffsetFilter', 'PerformanceFilter',
@@ -32,6 +33,7 @@ AVAILABLE_PAIRLISTS = ['StaticPairList', 'VolumePairList',
'ShuffleFilter', 'SpreadFilter', 'VolatilityFilter']
AVAILABLE_PROTECTIONS = ['CooldownPeriod', 'LowProfitPairs', 'MaxDrawdown', 'StoplossGuard']
AVAILABLE_DATAHANDLERS = ['json', 'jsongz', 'hdf5']
BACKTEST_BREAKDOWNS = ['day', 'week', 'month']
DRY_RUN_WALLET = 1000
DATETIME_PRINT_FORMAT = '%Y-%m-%d %H:%M:%S'
MATH_CLOSE_PREC = 1e-14 # Precision used for float comparisons
@@ -48,11 +50,12 @@ USERPATH_STRATEGIES = 'strategies'
USERPATH_NOTEBOOKS = 'notebooks'
TELEGRAM_SETTING_OPTIONS = ['on', 'off', 'silent']
WEBHOOK_FORMAT_OPTIONS = ['form', 'json', 'raw']
ENV_VAR_PREFIX = 'FREQTRADE__'
NON_OPEN_EXCHANGE_STATES = ('cancelled', 'canceled', 'closed', 'expired')
# Define decimals per coin for outputs
# Only used for outputs.
DECIMAL_PER_COIN_FALLBACK = 3 # Should be low to avoid listing all possible FIAT's
@@ -66,7 +69,6 @@ DUST_PER_COIN = {
'ETH': 0.01
}
# Source files with destination directories within user-directory
USER_DATA_FILES = {
'sample_strategy.py': USERPATH_STRATEGIES,
@@ -146,12 +148,17 @@ CONF_SCHEMA = {
'sell_profit_offset': {'type': 'number'},
'ignore_roi_if_buy_signal': {'type': 'boolean'},
'ignore_buying_expired_candle_after': {'type': 'number'},
'backtest_breakdown': {
'type': 'array',
'items': {'type': 'string', 'enum': BACKTEST_BREAKDOWNS}
},
'bot_name': {'type': 'string'},
'unfilledtimeout': {
'type': 'object',
'properties': {
'buy': {'type': 'number', 'minimum': 1},
'sell': {'type': 'number', 'minimum': 1},
'exit_timeout_count': {'type': 'number', 'minimum': 0, 'default': 0},
'unit': {'type': 'string', 'enum': TIMEOUT_UNITS, 'default': 'minutes'}
}
},
@@ -193,7 +200,7 @@ CONF_SCHEMA = {
'required': ['price_side']
},
'custom_price_max_distance_ratio': {
'type': 'number', 'minimum': 0.0
'type': 'number', 'minimum': 0.0
},
'order_types': {
'type': 'object',
@@ -202,7 +209,10 @@ CONF_SCHEMA = {
'sell': {'type': 'string', 'enum': ORDERTYPE_POSSIBILITIES},
'forcesell': {'type': 'string', 'enum': ORDERTYPE_POSSIBILITIES},
'forcebuy': {'type': 'string', 'enum': ORDERTYPE_POSSIBILITIES},
'emergencysell': {'type': 'string', 'enum': ORDERTYPE_POSSIBILITIES},
'emergencysell': {
'type': 'string',
'enum': ORDERTYPE_POSSIBILITIES,
'default': 'market'},
'stoploss': {'type': 'string', 'enum': ORDERTYPE_POSSIBILITIES},
'stoploss_on_exchange': {'type': 'boolean'},
'stoploss_on_exchange_interval': {'type': 'number'},
@@ -304,10 +314,16 @@ CONF_SCHEMA = {
'type': 'object',
'properties': {
'enabled': {'type': 'boolean'},
'url': {'type': 'string'},
'format': {'type': 'string', 'enum': WEBHOOK_FORMAT_OPTIONS, 'default': 'form'},
'retries': {'type': 'integer', 'minimum': 0},
'retry_delay': {'type': 'number', 'minimum': 0},
'webhookbuy': {'type': 'object'},
'webhookbuycancel': {'type': 'object'},
'webhookbuyfill': {'type': 'object'},
'webhooksell': {'type': 'object'},
'webhooksellcancel': {'type': 'object'},
'webhooksellfill': {'type': 'object'},
'webhookstatus': {'type': 'object'},
},
},
@@ -346,13 +362,13 @@ CONF_SCHEMA = {
},
'dataformat_ohlcv': {
'type': 'string',
'enum': AVAILABLE_DATAHANDLERS,
'default': 'json'
'enum': AVAILABLE_DATAHANDLERS,
'default': 'json'
},
'dataformat_trades': {
'type': 'string',
'enum': AVAILABLE_DATAHANDLERS,
'default': 'jsongz'
'enum': AVAILABLE_DATAHANDLERS,
'default': 'jsongz'
}
},
'definitions': {

2
freqtrade/data/converter.py
View File

@@ -113,7 +113,7 @@ def ohlcv_fill_up_missing_data(dataframe: DataFrame, timeframe: str, pair: str)
pct_missing = (len_after - len_before) / len_before if len_before > 0 else 0
if len_before != len_after:
message = (f"Missing data fillup for {pair}: before: {len_before} - after: {len_after}"
f" - {round(pct_missing * 100, 2)}%")
f" - {pct_missing:.2%}")
if pct_missing > 0.01:
logger.info(message)
else:

58
freqtrade/data/history/hdf5datahandler.py
View File

@@ -6,7 +6,6 @@ from typing import List, Optional
import numpy as np
import pandas as pd
from freqtrade import misc
from freqtrade.configuration import TimeRange
from freqtrade.constants import (DEFAULT_DATAFRAME_COLUMNS, DEFAULT_TRADES_COLUMNS,
ListPairsWithTimeframes, TradeList)
@@ -61,10 +60,10 @@ class HDF5DataHandler(IDataHandler):
filename = self._pair_data_filename(self._datadir, pair, timeframe)
ds = pd.HDFStore(filename, mode='a', complevel=9, complib='blosc')
ds.put(key, _data.loc[:, self._columns], format='table', data_columns=['date'])
ds.close()
_data.loc[:, self._columns].to_hdf(
filename, key, mode='a', complevel=9, complib='blosc',
format='table', data_columns=['date']
)
def _ohlcv_load(self, pair: str, timeframe: str,
timerange: Optional[TimeRange] = None) -> pd.DataFrame:
@@ -99,19 +98,6 @@ class HDF5DataHandler(IDataHandler):
'low': 'float', 'close': 'float', 'volume': 'float'})
return pairdata
def ohlcv_purge(self, pair: str, timeframe: str) -> bool:
"""
Remove data for this pair
:param pair: Delete data for this pair.
:param timeframe: Timeframe (e.g. "5m")
:return: True when deleted, false if file did not exist.
"""
filename = self._pair_data_filename(self._datadir, pair, timeframe)
if filename.exists():
filename.unlink()
return True
return False
def ohlcv_append(self, pair: str, timeframe: str, data: pd.DataFrame) -> None:
"""
Append data to existing data structures
@@ -142,11 +128,11 @@ class HDF5DataHandler(IDataHandler):
"""
key = self._pair_trades_key(pair)
ds = pd.HDFStore(self._pair_trades_filename(self._datadir, pair),
mode='a', complevel=9, complib='blosc')
ds.put(key, pd.DataFrame(data, columns=DEFAULT_TRADES_COLUMNS),
format='table', data_columns=['timestamp'])
ds.close()
pd.DataFrame(data, columns=DEFAULT_TRADES_COLUMNS).to_hdf(
self._pair_trades_filename(self._datadir, pair), key,
mode='a', complevel=9, complib='blosc',
format='table', data_columns=['timestamp']
)
def trades_append(self, pair: str, data: TradeList):
"""
@@ -180,17 +166,9 @@ class HDF5DataHandler(IDataHandler):
trades[['id', 'type']] = trades[['id', 'type']].replace({np.nan: None})
return trades.values.tolist()
def trades_purge(self, pair: str) -> bool:
"""
Remove data for this pair
:param pair: Delete data for this pair.
:return: True when deleted, false if file did not exist.
"""
filename = self._pair_trades_filename(self._datadir, pair)
if filename.exists():
filename.unlink()
return True
return False
@classmethod
def _get_file_extension(cls):
return "h5"
@classmethod
def _pair_ohlcv_key(cls, pair: str, timeframe: str) -> str:
@@ -199,15 +177,3 @@ class HDF5DataHandler(IDataHandler):
@classmethod
def _pair_trades_key(cls, pair: str) -> str:
return f"{pair}/trades"
@classmethod
def _pair_data_filename(cls, datadir: Path, pair: str, timeframe: str) -> Path:
pair_s = misc.pair_to_filename(pair)
filename = datadir.joinpath(f'{pair_s}-{timeframe}.h5')
return filename
@classmethod
def _pair_trades_filename(cls, datadir: Path, pair: str) -> Path:
pair_s = misc.pair_to_filename(pair)
filename = datadir.joinpath(f'{pair_s}-trades.h5')
return filename

32
freqtrade/data/history/idatahandler.py
View File

@@ -12,6 +12,7 @@ from typing import List, Optional, Type
from pandas import DataFrame
from freqtrade import misc
from freqtrade.configuration import TimeRange
from freqtrade.constants import ListPairsWithTimeframes, TradeList
from freqtrade.data.converter import clean_ohlcv_dataframe, trades_remove_duplicates, trim_dataframe
@@ -26,6 +27,13 @@ class IDataHandler(ABC):
def __init__(self, datadir: Path) -> None:
self._datadir = datadir
@classmethod
def _get_file_extension(cls) -> str:
"""
Get file extension for this particular datahandler
"""
raise NotImplementedError()
@abstractclassmethod
def ohlcv_get_available_data(cls, datadir: Path) -> ListPairsWithTimeframes:
"""
@@ -70,7 +78,6 @@ class IDataHandler(ABC):
:return: DataFrame with ohlcv data, or empty DataFrame
"""
@abstractmethod
def ohlcv_purge(self, pair: str, timeframe: str) -> bool:
"""
Remove data for this pair
@@ -78,6 +85,11 @@ class IDataHandler(ABC):
:param timeframe: Timeframe (e.g. "5m")
:return: True when deleted, false if file did not exist.
"""
filename = self._pair_data_filename(self._datadir, pair, timeframe)
if filename.exists():
filename.unlink()
return True
return False
@abstractmethod
def ohlcv_append(self, pair: str, timeframe: str, data: DataFrame) -> None:
@@ -123,13 +135,17 @@ class IDataHandler(ABC):
:return: List of trades
"""
@abstractmethod
def trades_purge(self, pair: str) -> bool:
"""
Remove data for this pair
:param pair: Delete data for this pair.
:return: True when deleted, false if file did not exist.
"""
filename = self._pair_trades_filename(self._datadir, pair)
if filename.exists():
filename.unlink()
return True
return False
def trades_load(self, pair: str, timerange: Optional[TimeRange] = None) -> TradeList:
"""
@@ -141,6 +157,18 @@ class IDataHandler(ABC):
"""
return trades_remove_duplicates(self._trades_load(pair, timerange=timerange))
@classmethod
def _pair_data_filename(cls, datadir: Path, pair: str, timeframe: str) -> Path:
pair_s = misc.pair_to_filename(pair)
filename = datadir.joinpath(f'{pair_s}-{timeframe}.{cls._get_file_extension()}')
return filename
@classmethod
def _pair_trades_filename(cls, datadir: Path, pair: str) -> Path:
pair_s = misc.pair_to_filename(pair)
filename = datadir.joinpath(f'{pair_s}-trades.{cls._get_file_extension()}')
return filename
def ohlcv_load(self, pair, timeframe: str,
timerange: Optional[TimeRange] = None,
fill_missing: bool = True,

24
freqtrade/data/history/jsondatahandler.py
View File

@@ -174,34 +174,10 @@ class JsonDataHandler(IDataHandler):
pass
return tradesdata
def trades_purge(self, pair: str) -> bool:
"""
Remove data for this pair
:param pair: Delete data for this pair.
:return: True when deleted, false if file did not exist.
"""
filename = self._pair_trades_filename(self._datadir, pair)
if filename.exists():
filename.unlink()
return True
return False
@classmethod
def _pair_data_filename(cls, datadir: Path, pair: str, timeframe: str) -> Path:
pair_s = misc.pair_to_filename(pair)
filename = datadir.joinpath(f'{pair_s}-{timeframe}.{cls._get_file_extension()}')
return filename
@classmethod
def _get_file_extension(cls):
return "json.gz" if cls._use_zip else "json"
@classmethod
def _pair_trades_filename(cls, datadir: Path, pair: str) -> Path:
pair_s = misc.pair_to_filename(pair)
filename = datadir.joinpath(f'{pair_s}-trades.{cls._get_file_extension()}')
return filename
class JsonGzDataHandler(JsonDataHandler):

1
freqtrade/enums/__init__.py
View File

@@ -1,5 +1,6 @@
# flake8: noqa: F401
from freqtrade.enums.backteststate import BacktestState
from freqtrade.enums.ordertypevalue import OrderTypeValues
from freqtrade.enums.rpcmessagetype import RPCMessageType
from freqtrade.enums.runmode import NON_UTIL_MODES, OPTIMIZE_MODES, TRADING_MODES, RunMode
from freqtrade.enums.selltype import SellType

6
freqtrade/enums/ordertypevalue.py Normal file
View File

@@ -0,0 +1,6 @@
from enum import Enum
class OrderTypeValues(str, Enum):
limit = 'limit'
market = 'market'

1
freqtrade/enums/signaltype.py
View File

@@ -14,3 +14,4 @@ class SignalTagType(Enum):
Enum for signal columns
"""
BUY_TAG = "buy_tag"
EXIT_TAG = "exit_tag"

2
freqtrade/exceptions.py
View File

@@ -1,5 +1,3 @@
class FreqtradeException(Exception):
"""
Freqtrade base exception. Handled at the outermost level.

1
freqtrade/exchange/__init__.py
View File

@@ -19,3 +19,4 @@ from freqtrade.exchange.gateio import Gateio
from freqtrade.exchange.hitbtc import Hitbtc
from freqtrade.exchange.kraken import Kraken
from freqtrade.exchange.kucoin import Kucoin
from freqtrade.exchange.okex import Okex

10
freqtrade/exchange/binance.py
View File

@@ -1,6 +1,6 @@
""" Binance exchange subclass """
import logging
from typing import Dict, List
from typing import Dict, List, Tuple
import arrow
import ccxt
@@ -93,8 +93,9 @@ class Binance(Exchange):
raise OperationalException(e) from e
async def _async_get_historic_ohlcv(self, pair: str, timeframe: str,
since_ms: int, is_new_pair: bool
) -> List:
since_ms: int, is_new_pair: bool = False,
raise_: bool = False
) -> Tuple[str, str, List]:
"""
Overwrite to introduce "fast new pair" functionality by detecting the pair's listing date
Does not work for other exchanges, which don't return the earliest data when called with "0"
@@ -107,4 +108,5 @@ class Binance(Exchange):
logger.info(f"Candle-data for {pair} available starting with "
f"{arrow.get(since_ms // 1000).isoformat()}.")
return await super()._async_get_historic_ohlcv(
pair=pair, timeframe=timeframe, since_ms=since_ms, is_new_pair=is_new_pair)
pair=pair, timeframe=timeframe, since_ms=since_ms, is_new_pair=is_new_pair,
raise_=raise_)

15
freqtrade/exchange/common.py
View File

@@ -16,8 +16,6 @@ API_FETCH_ORDER_RETRY_COUNT = 5
BAD_EXCHANGES = {
"bitmex": "Various reasons.",
"bitstamp": "Does not provide history. "
"Details in https://github.com/freqtrade/freqtrade/issues/1983",
"phemex": "Does not provide history. ",
"poloniex": "Does not provide fetch_order endpoint to fetch both open and closed orders.",
}
@@ -83,9 +81,16 @@ def retrier_async(f):
count -= 1
kwargs.update({'count': count})
if isinstance(ex, DDosProtection):
backoff_delay = calculate_backoff(count + 1, API_RETRY_COUNT)
logger.info(f"Applying DDosProtection backoff delay: {backoff_delay}")
await asyncio.sleep(backoff_delay)
if "kucoin" in str(ex) and "429000" in str(ex):
# Temporary fix for 429000 error on kucoin
# see https://github.com/freqtrade/freqtrade/issues/5700 for details.
logger.warning(
f"Kucoin 429 error, avoid triggering DDosProtection backoff delay. "
f"{count} tries left before giving up")
else:
backoff_delay = calculate_backoff(count + 1, API_RETRY_COUNT)
logger.info(f"Applying DDosProtection backoff delay: {backoff_delay}")
await asyncio.sleep(backoff_delay)
return await wrapper(*args, **kwargs)
else:
logger.warning('Giving up retrying: %s()', f.__name__)

139
freqtrade/exchange/exchange.py
View File

@@ -7,7 +7,7 @@ import http
import inspect
import logging
from copy import deepcopy
from datetime import datetime, timezone
from datetime import datetime, timedelta, timezone
from math import ceil
from typing import Any, Dict, List, Optional, Tuple
@@ -155,8 +155,8 @@ class Exchange:
self.validate_pairs(config['exchange']['pair_whitelist'])
self.validate_ordertypes(config.get('order_types', {}))
self.validate_order_time_in_force(config.get('order_time_in_force', {}))
self.validate_required_startup_candles(config.get('startup_candle_count', 0),
config.get('timeframe', ''))
self.required_candle_call_count = self.validate_required_startup_candles(
config.get('startup_candle_count', 0), config.get('timeframe', ''))
# Converts the interval provided in minutes in config to seconds
self.markets_refresh_interval: int = exchange_config.get(
@@ -471,16 +471,29 @@ class Exchange:
raise OperationalException(
f'Time in force policies are not supported for {self.name} yet.')
def validate_required_startup_candles(self, startup_candles: int, timeframe: str) -> None:
def validate_required_startup_candles(self, startup_candles: int, timeframe: str) -> int:
"""
Checks if required startup_candles is more than ohlcv_candle_limit().
Requires a grace-period of 5 candles - so a startup-period up to 494 is allowed by default.
"""
candle_limit = self.ohlcv_candle_limit(timeframe)
if startup_candles + 5 > candle_limit:
# Require one more candle - to account for the still open candle.
candle_count = startup_candles + 1
# Allow 5 calls to the exchange per pair
required_candle_call_count = int(
(candle_count / candle_limit) + (0 if candle_count % candle_limit == 0 else 1))
if required_candle_call_count > 5:
# Only allow 5 calls per pair to somewhat limit the impact
raise OperationalException(
f"This strategy requires {startup_candles} candles to start. "
f"{self.name} only provides {candle_limit - 5} for {timeframe}.")
f"This strategy requires {startup_candles} candles to start, which is more than 5x "
f"the amount of candles {self.name} provides for {timeframe}.")
if required_candle_call_count > 1:
logger.warning(f"Using {required_candle_call_count} calls to get OHLCV. "
f"This can result in slower operations for the bot. Please check "
f"if you really need {startup_candles} candles for your strategy")
return required_candle_call_count
def exchange_has(self, endpoint: str) -> bool:
"""
@@ -672,16 +685,20 @@ class Exchange:
if not self.exchange_has('fetchL2OrderBook'):
return True
ob = self.fetch_l2_order_book(pair, 1)
if side == 'buy':
price = ob['asks'][0][0]
logger.debug(f"{pair} checking dry buy-order: price={price}, limit={limit}")
if limit >= price:
return True
else:
price = ob['bids'][0][0]
logger.debug(f"{pair} checking dry sell-order: price={price}, limit={limit}")
if limit <= price:
return True
try:
if side == 'buy':
price = ob['asks'][0][0]
logger.debug(f"{pair} checking dry buy-order: price={price}, limit={limit}")
if limit >= price:
return True
else:
price = ob['bids'][0][0]
logger.debug(f"{pair} checking dry sell-order: price={price}, limit={limit}")
if limit <= price:
return True
except IndexError:
# Ignore empty orderbooks when filling - can be filled with the next iteration.
pass
return False
def check_dry_limit_order_filled(self, order: Dict[str, Any]) -> Dict[str, Any]:
@@ -1205,9 +1222,11 @@ class Exchange:
:param since_ms: Timestamp in milliseconds to get history from
:return: List with candle (OHLCV) data
"""
return asyncio.get_event_loop().run_until_complete(
pair, timeframe, data = asyncio.get_event_loop().run_until_complete(
self._async_get_historic_ohlcv(pair=pair, timeframe=timeframe,
since_ms=since_ms, is_new_pair=is_new_pair))
logger.info(f"Downloaded data for {pair} with length {len(data)}.")
return data
def get_historic_ohlcv_as_df(self, pair: str, timeframe: str,
since_ms: int) -> DataFrame:
@@ -1223,8 +1242,9 @@ class Exchange:
drop_incomplete=self._ohlcv_partial_candle)
async def _async_get_historic_ohlcv(self, pair: str, timeframe: str,
since_ms: int, is_new_pair: bool
) -> List:
since_ms: int, is_new_pair: bool = False,
raise_: bool = False
) -> Tuple[str, str, List]:
"""
Download historic ohlcv
:param is_new_pair: used by binance subclass to allow "fast" new pair downloading
@@ -1247,16 +1267,18 @@ class Exchange:
results = await asyncio.gather(*input_coro, return_exceptions=True)
for res in results:
if isinstance(res, Exception):
logger.warning("Async code raised an exception: %s", res.__class__.__name__)
logger.warning(f"Async code raised an exception: {repr(res)}")
if raise_:
raise
continue
# Deconstruct tuple if it's not an exception
p, _, new_data = res
if p == pair:
data.extend(new_data)
else:
# Deconstruct tuple if it's not an exception
p, _, new_data = res
if p == pair:
data.extend(new_data)
# Sort data again after extending the result - above calls return in "async order"
data = sorted(data, key=lambda x: x[0])
logger.info(f"Downloaded data for {pair} with length {len(data)}.")
return data
return pair, timeframe, data
def refresh_latest_ohlcv(self, pair_list: ListPairsWithTimeframes, *,
since_ms: Optional[int] = None, cache: bool = True
@@ -1276,10 +1298,22 @@ class Exchange:
cached_pairs = []
# Gather coroutines to run
for pair, timeframe in set(pair_list):
if (((pair, timeframe) not in self._klines)
if ((pair, timeframe) not in self._klines or not cache
or self._now_is_time_to_refresh(pair, timeframe)):
input_coroutines.append(self._async_get_candle_history(pair, timeframe,
since_ms=since_ms))
if not since_ms and self.required_candle_call_count > 1:
# Multiple calls for one pair - to get more history
one_call = timeframe_to_msecs(timeframe) * self.ohlcv_candle_limit(timeframe)
move_to = one_call * self.required_candle_call_count
now = timeframe_to_next_date(timeframe)
since_ms = int((now - timedelta(seconds=move_to // 1000)).timestamp() * 1000)
if since_ms:
input_coroutines.append(self._async_get_historic_ohlcv(
pair, timeframe, since_ms=since_ms, raise_=True))
else:
# One call ... "regular" refresh
input_coroutines.append(self._async_get_candle_history(
pair, timeframe, since_ms=since_ms))
else:
logger.debug(
"Using cached candle (OHLCV) data for pair %s, timeframe %s ...",
@@ -1287,27 +1321,30 @@ class Exchange:
)
cached_pairs.append((pair, timeframe))
results = asyncio.get_event_loop().run_until_complete(
asyncio.gather(*input_coroutines, return_exceptions=True))
results_df = {}
# handle caching
for res in results:
if isinstance(res, Exception):
logger.warning("Async code raised an exception: %s", res.__class__.__name__)
continue
# Deconstruct tuple (has 3 elements)
pair, timeframe, ticks = res
# keeping last candle time as last refreshed time of the pair
if ticks:
self._pairs_last_refresh_time[(pair, timeframe)] = ticks[-1][0] // 1000
# keeping parsed dataframe in cache
ohlcv_df = ohlcv_to_dataframe(
ticks, timeframe, pair=pair, fill_missing=True,
drop_incomplete=self._ohlcv_partial_candle)
results_df[(pair, timeframe)] = ohlcv_df
if cache:
self._klines[(pair, timeframe)] = ohlcv_df
# Chunk requests into batches of 100 to avoid overwelming ccxt Throttling
for input_coro in chunks(input_coroutines, 100):
results = asyncio.get_event_loop().run_until_complete(
asyncio.gather(*input_coro, return_exceptions=True))
# handle caching
for res in results:
if isinstance(res, Exception):
logger.warning(f"Async code raised an exception: {repr(res)}")
continue
# Deconstruct tuple (has 3 elements)
pair, timeframe, ticks = res
# keeping last candle time as last refreshed time of the pair
if ticks:
self._pairs_last_refresh_time[(pair, timeframe)] = ticks[-1][0] // 1000
# keeping parsed dataframe in cache
ohlcv_df = ohlcv_to_dataframe(
ticks, timeframe, pair=pair, fill_missing=True,
drop_incomplete=self._ohlcv_partial_candle)
results_df[(pair, timeframe)] = ohlcv_df
if cache:
self._klines[(pair, timeframe)] = ohlcv_df
# Return cached klines
for pair, timeframe in cached_pairs:
results_df[(pair, timeframe)] = self.klines((pair, timeframe), copy=False)
@@ -1534,7 +1571,7 @@ def is_exchange_known_ccxt(exchange_name: str, ccxt_module: CcxtModuleType = Non
def is_exchange_officially_supported(exchange_name: str) -> bool:
return exchange_name in ['bittrex', 'binance', 'kraken']
return exchange_name in ['bittrex', 'binance', 'kraken', 'ftx', 'gateio', 'okex']
def ccxt_exchanges(ccxt_module: CcxtModuleType = None) -> List[str]:

8
freqtrade/exchange/kucoin.py
View File

@@ -1,4 +1,4 @@
""" Kucoin exchange subclass """
"""Kucoin exchange subclass."""
import logging
from typing import Dict
@@ -9,9 +9,9 @@ logger = logging.getLogger(__name__)
class Kucoin(Exchange):
"""
Kucoin exchange class. Contains adjustments needed for Freqtrade to work
with this exchange.
"""Kucoin exchange class.
Contains adjustments needed for Freqtrade to work with this exchange.
Please note that this exchange is not included in the list of exchanges
officially supported by the Freqtrade development team. So some features

18
freqtrade/exchange/okex.py Normal file
View File

@@ -0,0 +1,18 @@
import logging
from typing import Dict
from freqtrade.exchange import Exchange
logger = logging.getLogger(__name__)
class Okex(Exchange):
"""Okex exchange class.
Contains adjustments needed for Freqtrade to work with this exchange.
"""
_ft_has: Dict = {
"ohlcv_candle_limit": 100,
}

149
freqtrade/freqtradebot.py
View File

@@ -193,19 +193,20 @@ class FreqtradeBot(LoggingMixin):
def check_for_open_trades(self):
"""
Notify the user when the bot is stopped
Notify the user when the bot is stopped (not reloaded)
and there are still open trades active.
"""
open_trades = Trade.get_trades([Trade.is_open.is_(True)]).all()
if len(open_trades) != 0:
if len(open_trades) != 0 and self.state != State.RELOAD_CONFIG:
msg = {
'type': RPCMessageType.WARNING,
'status': f"{len(open_trades)} open trades active.\n\n"
f"Handle these trades manually on {self.exchange.name}, "
f"or '/start' the bot again and use '/stopbuy' "
f"to handle open trades gracefully. \n"
f"{'Trades are simulated.' if self.config['dry_run'] else ''}",
'status':
f"{len(open_trades)} open trades active.\n\n"
f"Handle these trades manually on {self.exchange.name}, "
f"or '/start' the bot again and use '/stopbuy' "
f"to handle open trades gracefully. \n"
f"{'Note: Trades are simulated (dry run).' if self.config['dry_run'] else ''}",
}
self.rpc.send_msg(msg)
@@ -277,7 +278,8 @@ class FreqtradeBot(LoggingMixin):
if order:
logger.info(f"Updating sell-fee on trade {trade} for order {order.order_id}.")
self.update_trade_state(trade, order.order_id,
stoploss_order=order.ft_order_side == 'stoploss')
stoploss_order=order.ft_order_side == 'stoploss',
send_msg=False)
trades: List[Trade] = Trade.get_open_trades_without_assigned_fees()
for trade in trades:
@@ -285,7 +287,7 @@ class FreqtradeBot(LoggingMixin):
order = trade.select_order('buy', False)
if order:
logger.info(f"Updating buy-fee on trade {trade} for order {order.order_id}.")
self.update_trade_state(trade, order.order_id)
self.update_trade_state(trade, order.order_id, send_msg=False)
def handle_insufficient_funds(self, trade: Trade):
"""
@@ -307,7 +309,7 @@ class FreqtradeBot(LoggingMixin):
order = trade.select_order('buy', False)
if order:
logger.info(f"Updating buy-fee on trade {trade} for order {order.order_id}.")
self.update_trade_state(trade, order.order_id)
self.update_trade_state(trade, order.order_id, send_msg=False)
def refind_lost_order(self, trade):
"""
@@ -420,7 +422,7 @@ class FreqtradeBot(LoggingMixin):
return False
# running get_signal on historical data fetched
(buy, sell, buy_tag) = self.strategy.get_signal(
(buy, sell, buy_tag, _) = self.strategy.get_signal(
pair,
self.strategy.timeframe,
analyzed_df
@@ -465,8 +467,8 @@ class FreqtradeBot(LoggingMixin):
logger.info(f"Bids to asks delta for {pair} does not satisfy condition.")
return False
def execute_entry(self, pair: str, stake_amount: float, price: Optional[float] = None,
forcebuy: bool = False, buy_tag: Optional[str] = None) -> bool:
def execute_entry(self, pair: str, stake_amount: float, price: Optional[float] = None, *,
ordertype: Optional[str] = None, buy_tag: Optional[str] = None) -> bool:
"""
Executes a limit buy for the given pair
:param pair: pair for which we want to create a LIMIT_BUY
@@ -500,7 +502,7 @@ class FreqtradeBot(LoggingMixin):
pair=pair, current_time=datetime.now(timezone.utc),
current_rate=enter_limit_requested, proposed_stake=stake_amount,
min_stake=min_stake_amount, max_stake=max_stake_amount)
stake_amount = self.wallets._validate_stake_amount(pair, stake_amount, min_stake_amount)
stake_amount = self.wallets.validate_stake_amount(pair, stake_amount, min_stake_amount)
if not stake_amount:
return False
@@ -509,10 +511,7 @@ class FreqtradeBot(LoggingMixin):
f"{stake_amount} ...")
amount = stake_amount / enter_limit_requested
order_type = self.strategy.order_types['buy']
if forcebuy:
# Forcebuy can define a different ordertype
order_type = self.strategy.order_types.get('forcebuy', order_type)
order_type = ordertype or self.strategy.order_types['buy']
if not strategy_safe_wrapper(self.strategy.confirm_trade_entry, default_retval=True)(
pair=pair, order_type=order_type, amount=amount, rate=enter_limit_requested,
@@ -580,10 +579,6 @@ class FreqtradeBot(LoggingMixin):
)
trade.orders.append(order_obj)
# Update fees if order is closed
if order_status == 'closed':
self.update_trade_state(trade, order_id, order)
Trade.query.session.add(trade)
Trade.commit()
@@ -592,19 +587,25 @@ class FreqtradeBot(LoggingMixin):
self._notify_enter(trade, order_type)
# Update fees if order is closed
if order_status == 'closed':
self.update_trade_state(trade, order_id, order)
return True
def _notify_enter(self, trade: Trade, order_type: str) -> None:
def _notify_enter(self, trade: Trade, order_type: Optional[str] = None,
fill: bool = False) -> None:
"""
Sends rpc notification when a buy occurred.
"""
msg = {
'trade_id': trade.id,
'type': RPCMessageType.BUY,
'type': RPCMessageType.BUY_FILL if fill else RPCMessageType.BUY,
'buy_tag': trade.buy_tag,
'exchange': self.exchange.name.capitalize(),
'pair': trade.pair,
'limit': trade.open_rate,
'limit': trade.open_rate, # Deprecated (?)
'open_rate': trade.open_rate,
'order_type': order_type,
'stake_amount': trade.stake_amount,
'stake_currency': self.config['stake_currency'],
@@ -643,22 +644,6 @@ class FreqtradeBot(LoggingMixin):
# Send the message
self.rpc.send_msg(msg)
def _notify_enter_fill(self, trade: Trade) -> None:
msg = {
'trade_id': trade.id,
'type': RPCMessageType.BUY_FILL,
'buy_tag': trade.buy_tag,
'exchange': self.exchange.name.capitalize(),
'pair': trade.pair,
'open_rate': trade.open_rate,
'stake_amount': trade.stake_amount,
'stake_currency': self.config['stake_currency'],
'fiat_currency': self.config.get('fiat_display_currency', None),
'amount': trade.amount,
'open_date': trade.open_date,
}
self.rpc.send_msg(msg)
#
# SELL / exit positions / close trades logic and methods
#
@@ -700,21 +685,22 @@ class FreqtradeBot(LoggingMixin):
logger.debug('Handling %s ...', trade)
(buy, sell) = (False, False)
exit_tag = None
if (self.config.get('use_sell_signal', True) or
self.config.get('ignore_roi_if_buy_signal', False)):
analyzed_df, _ = self.dataprovider.get_analyzed_dataframe(trade.pair,
self.strategy.timeframe)
(buy, sell, _) = self.strategy.get_signal(
(buy, sell, _, exit_tag) = self.strategy.get_signal(
trade.pair,
self.strategy.timeframe,
analyzed_df
)
logger.debug('checking sell')
exit_rate = self.exchange.get_rate(trade.pair, refresh=True, side="sell")
if self._check_and_execute_exit(trade, exit_rate, buy, sell):
sell_rate = self.exchange.get_rate(trade.pair, refresh=True, side="sell")
if self._check_and_execute_exit(trade, sell_rate, buy, sell, exit_tag):
return True
logger.debug('Found no sell signal for %s.', trade)
@@ -852,18 +838,21 @@ class FreqtradeBot(LoggingMixin):
f"for pair {trade.pair}.")
def _check_and_execute_exit(self, trade: Trade, exit_rate: float,
buy: bool, sell: bool) -> bool:
buy: bool, sell: bool, exit_tag: Optional[str]) -> bool:
"""
Check and execute exit
"""
should_sell = self.strategy.should_sell(
trade, exit_rate, datetime.now(timezone.utc), buy, sell,
force_stoploss=self.edge.stoploss(trade.pair) if self.edge else 0
)
if should_sell.sell_flag:
logger.info(f'Executing Sell for {trade.pair}. Reason: {should_sell.sell_type}')
self.execute_trade_exit(trade, exit_rate, should_sell)
logger.info(
f'Executing Sell for {trade.pair}. Reason: {should_sell.sell_type}. '
f'Tag: {exit_tag if exit_tag is not None else "None"}')
self.execute_trade_exit(trade, exit_rate, should_sell, exit_tag=exit_tag)
return True
return False
@@ -916,6 +905,13 @@ class FreqtradeBot(LoggingMixin):
trade=trade,
order=order))):
self.handle_cancel_exit(trade, order, constants.CANCEL_REASON['TIMEOUT'])
canceled_count = trade.get_exit_order_count()
max_timeouts = self.config.get('unfilledtimeout', {}).get('exit_timeout_count', 0)
if max_timeouts > 0 and canceled_count >= max_timeouts:
logger.warning(f'Emergencyselling trade {trade}, as the sell order '
f'timed out {max_timeouts} times.')
self.execute_trade_exit(trade, order.get('price'), sell_reason=SellCheckTuple(
sell_type=SellType.EMERGENCY_SELL))
def cancel_all_open_orders(self) -> None:
"""
@@ -1064,7 +1060,15 @@ class FreqtradeBot(LoggingMixin):
raise DependencyException(
f"Not enough amount to sell. Trade-amount: {amount}, Wallet: {wallet_amount}")
def execute_trade_exit(self, trade: Trade, limit: float, sell_reason: SellCheckTuple) -> bool:
def execute_trade_exit(
self,
trade: Trade,
limit: float,
sell_reason: SellCheckTuple,
*,
exit_tag: Optional[str] = None,
ordertype: Optional[str] = None,
) -> bool:
"""
Executes a trade exit for the given trade and limit
:param trade: Trade instance
@@ -1102,14 +1106,10 @@ class FreqtradeBot(LoggingMixin):
except InvalidOrderException:
logger.exception(f"Could not cancel stoploss order {trade.stoploss_order_id}")
order_type = self.strategy.order_types[sell_type]
order_type = ordertype or self.strategy.order_types[sell_type]
if sell_reason.sell_type == SellType.EMERGENCY_SELL:
# Emergency sells (default to market!)
order_type = self.strategy.order_types.get("emergencysell", "market")
if sell_reason.sell_type == SellType.FORCE_SELL:
# Force sells (default to the sell_type defined in the strategy,
# but we allow this value to be changed)
order_type = self.strategy.order_types.get("forcesell", order_type)
amount = self._safe_exit_amount(trade.pair, trade.amount)
time_in_force = self.strategy.order_time_in_force['sell']
@@ -1140,17 +1140,17 @@ class FreqtradeBot(LoggingMixin):
trade.open_order_id = order['id']
trade.sell_order_status = ''
trade.close_rate_requested = limit
trade.sell_reason = sell_reason.sell_reason
# In case of market sell orders the order can be closed immediately
if order.get('status', 'unknown') in ('closed', 'expired'):
self.update_trade_state(trade, trade.open_order_id, order)
Trade.commit()
trade.sell_reason = exit_tag or sell_reason.sell_reason
# Lock pair for one candle to prevent immediate re-buys
self.strategy.lock_pair(trade.pair, datetime.now(timezone.utc),
reason='Auto lock')
self._notify_exit(trade, order_type)
# In case of market sell orders the order can be closed immediately
if order.get('status', 'unknown') in ('closed', 'expired'):
self.update_trade_state(trade, trade.open_order_id, order)
Trade.commit()
return True
@@ -1181,6 +1181,7 @@ class FreqtradeBot(LoggingMixin):
'current_rate': current_rate,
'profit_amount': profit_trade,
'profit_ratio': profit_ratio,
'buy_tag': trade.buy_tag,
'sell_reason': trade.sell_reason,
'open_date': trade.open_date,
'close_date': trade.close_date or datetime.utcnow(),
@@ -1224,6 +1225,7 @@ class FreqtradeBot(LoggingMixin):
'current_rate': current_rate,
'profit_amount': profit_trade,
'profit_ratio': profit_ratio,
'buy_tag': trade.buy_tag,
'sell_reason': trade.sell_reason,
'open_date': trade.open_date,
'close_date': trade.close_date or datetime.now(timezone.utc),
@@ -1245,13 +1247,14 @@ class FreqtradeBot(LoggingMixin):
#
def update_trade_state(self, trade: Trade, order_id: str, action_order: Dict[str, Any] = None,
stoploss_order: bool = False) -> bool:
stoploss_order: bool = False, send_msg: bool = True) -> bool:
"""
Checks trades with open orders and updates the amount if necessary
Handles closing both buy and sell orders.
:param trade: Trade object of the trade we're analyzing
:param order_id: Order-id of the order we're analyzing
:param action_order: Already acquired order object
:param send_msg: Send notification - should always be True except in "recovery" methods
:return: True if order has been cancelled without being filled partially, False otherwise
"""
if not order_id:
@@ -1270,6 +1273,11 @@ class FreqtradeBot(LoggingMixin):
trade.update_order(order)
if self.exchange.check_order_canceled_empty(order):
# Trade has been cancelled on exchange
# Handling of this will happen in check_handle_timedout.
return True
# Try update amount (binance-fix)
try:
new_amount = self.get_real_amount(trade, order)
@@ -1281,22 +1289,18 @@ class FreqtradeBot(LoggingMixin):
except DependencyException as exception:
logger.warning("Could not update trade amount: %s", exception)
if self.exchange.check_order_canceled_empty(order):
# Trade has been cancelled on exchange
# Handling of this will happen in check_handle_timeout.
return True
trade.update(order)
Trade.commit()
# Updating wallets when order is closed
if not trade.is_open:
if not stoploss_order and not trade.open_order_id:
if send_msg and not stoploss_order and not trade.open_order_id:
self._notify_exit(trade, '', True)
self.handle_protections(trade.pair)
self.wallets.update()
elif not trade.open_order_id:
elif send_msg and not trade.open_order_id:
# Buy fill
self._notify_enter_fill(trade)
self._notify_enter(trade, fill=True)
return False
@@ -1361,14 +1365,17 @@ class FreqtradeBot(LoggingMixin):
return self.apply_fee_conditional(trade, trade_base_currency,
amount=order_amount, fee_abs=fee_cost)
return order_amount
return self.fee_detection_from_trades(trade, order, order_amount)
return self.fee_detection_from_trades(trade, order, order_amount, order.get('trades', []))
def fee_detection_from_trades(self, trade: Trade, order: Dict, order_amount: float) -> float:
def fee_detection_from_trades(self, trade: Trade, order: Dict, order_amount: float,
trades: List) -> float:
"""
fee-detection fallback to Trades. Parses result of fetch_my_trades to get correct fee.
fee-detection fallback to Trades.
Either uses provided trades list or the result of fetch_my_trades to get correct fee.
"""
trades = self.exchange.get_trades_for_order(self.exchange.get_order_id_conditional(order),
trade.pair, trade.open_date)
if not trades:
trades = self.exchange.get_trades_for_order(
self.exchange.get_order_id_conditional(order), trade.pair, trade.open_date)
if len(trades) == 0:
logger.info("Applying fee on amount for %s failed: myTrade-Dict empty found", trade)

31
freqtrade/optimize/backtesting.py
View File

@@ -44,6 +44,7 @@ SELL_IDX = 4
LOW_IDX = 5
HIGH_IDX = 6
BUY_TAG_IDX = 7
EXIT_TAG_IDX = 8
class Backtesting:
@@ -66,7 +67,7 @@ class Backtesting:
self.all_results: Dict[str, Dict] = {}
self.exchange = ExchangeResolver.load_exchange(self.config['exchange']['name'], self.config)
self.dataprovider = DataProvider(self.config, None)
self.dataprovider = DataProvider(self.config, self.exchange)
if self.config.get('strategy_list', None):
for strat in list(self.config['strategy_list']):
@@ -88,7 +89,8 @@ class Backtesting:
self.init_backtest_detail()
self.pairlists = PairListManager(self.exchange, self.config)
if 'VolumePairList' in self.pairlists.name_list:
raise OperationalException("VolumePairList not allowed for backtesting.")
raise OperationalException("VolumePairList not allowed for backtesting. "
"Please use StaticPairlist instead.")
if 'PerformanceFilter' in self.pairlists.name_list:
raise OperationalException("PerformanceFilter not allowed for backtesting.")
@@ -247,7 +249,7 @@ class Backtesting:
"""
# 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', 'buy', 'open', 'close', 'sell', 'low', 'high', 'buy_tag']
headers = ['date', 'buy', 'open', 'close', 'sell', 'low', 'high', 'buy_tag', 'exit_tag']
data: Dict = {}
self.progress.init_step(BacktestState.CONVERT, len(processed))
@@ -259,6 +261,7 @@ class Backtesting:
pair_data.loc[:, 'buy'] = 0 # cleanup if buy_signal is exist
pair_data.loc[:, 'sell'] = 0 # cleanup if sell_signal is exist
pair_data.loc[:, 'buy_tag'] = None # cleanup if buy_tag is exist
pair_data.loc[:, 'exit_tag'] = None # cleanup if exit_tag is exist
df_analyzed = self.strategy.advise_sell(
self.strategy.advise_buy(pair_data, {'pair': pair}), {'pair': pair}).copy()
@@ -270,6 +273,7 @@ class Backtesting:
df_analyzed.loc[:, 'buy'] = df_analyzed.loc[:, 'buy'].shift(1)
df_analyzed.loc[:, 'sell'] = df_analyzed.loc[:, 'sell'].shift(1)
df_analyzed.loc[:, 'buy_tag'] = df_analyzed.loc[:, 'buy_tag'].shift(1)
df_analyzed.loc[:, 'exit_tag'] = df_analyzed.loc[:, 'exit_tag'].shift(1)
# Update dataprovider cache
self.dataprovider._set_cached_df(pair, self.timeframe, df_analyzed)
@@ -312,7 +316,9 @@ class Backtesting:
# Worst case: price ticks tiny bit above open and dives down.
stop_rate = sell_row[OPEN_IDX] * (1 - abs(trade.stop_loss_pct))
assert stop_rate < sell_row[HIGH_IDX]
return stop_rate
# Limit lower-end to candle low to avoid sells below the low.
# This still remains "worst case" - but "worst realistic case".
return max(sell_row[LOW_IDX], stop_rate)
# Set close_rate to stoploss
return trade.stop_loss
@@ -357,7 +363,7 @@ class Backtesting:
if sell.sell_flag:
trade.close_date = sell_candle_time
trade.sell_reason = sell.sell_reason
trade_dur = int((trade.close_date_utc - trade.open_date_utc).total_seconds() // 60)
closerate = self._get_close_rate(sell_row, trade, sell, trade_dur)
# call the custom exit price,with default value as previous closerate
@@ -378,6 +384,17 @@ class Backtesting:
current_time=sell_candle_time):
return None
trade.sell_reason = sell.sell_reason
# Checks and adds an exit tag, after checking that the length of the
# sell_row has the length for an exit tag column
if(
len(sell_row) > EXIT_TAG_IDX
and sell_row[EXIT_TAG_IDX] is not None
and len(sell_row[EXIT_TAG_IDX]) > 0
):
trade.sell_reason = sell_row[EXIT_TAG_IDX]
trade.close(closerate, show_msg=False)
return trade
@@ -392,7 +409,7 @@ class Backtesting:
detail_data = detail_data.loc[
(detail_data['date'] >= sell_candle_time) &
(detail_data['date'] < sell_candle_end)
].copy()
].copy()
if len(detail_data) == 0:
# Fall back to "regular" data if no detail data was found for this candle
return self._get_sell_trade_entry_for_candle(trade, sell_row)
@@ -427,7 +444,7 @@ class Backtesting:
default_retval=stake_amount)(
pair=pair, current_time=row[DATE_IDX].to_pydatetime(), current_rate=propose_rate,
proposed_stake=stake_amount, min_stake=min_stake_amount, max_stake=max_stake_amount)
stake_amount = self.wallets._validate_stake_amount(pair, stake_amount, min_stake_amount)
stake_amount = self.wallets.validate_stake_amount(pair, stake_amount, min_stake_amount)
if not stake_amount:
return None

2
freqtrade/optimize/hyperopt.py
View File

@@ -45,7 +45,7 @@ progressbar.streams.wrap_stdout()
logger = logging.getLogger(__name__)
INITIAL_POINTS = 5
INITIAL_POINTS = 30
# Keep no more than SKOPT_MODEL_QUEUE_SIZE models
# in the skopt model queue, to optimize memory consumption

64
freqtrade/optimize/hyperopt_loss_calmar.py Normal file
View File

@@ -0,0 +1,64 @@
"""
CalmarHyperOptLoss
This module defines the alternative HyperOptLoss class which can be used for
Hyperoptimization.
"""
from datetime import datetime
from math import sqrt as msqrt
from typing import Any, Dict
from pandas import DataFrame
from freqtrade.data.btanalysis import calculate_max_drawdown
from freqtrade.optimize.hyperopt import IHyperOptLoss
class CalmarHyperOptLoss(IHyperOptLoss):
"""
Defines the loss function for hyperopt.
This implementation uses the Calmar Ratio calculation.
"""
@staticmethod
def hyperopt_loss_function(
results: DataFrame,
trade_count: int,
min_date: datetime,
max_date: datetime,
config: Dict,
processed: Dict[str, DataFrame],
backtest_stats: Dict[str, Any],
*args,
**kwargs
) -> float:
"""
Objective function, returns smaller number for more optimal results.
Uses Calmar Ratio calculation.
"""
total_profit = backtest_stats["profit_total"]
days_period = (max_date - min_date).days
# adding slippage of 0.1% per trade
total_profit = total_profit - 0.0005
expected_returns_mean = total_profit.sum() / days_period * 100
# calculate max drawdown
try:
_, _, _, high_val, low_val = calculate_max_drawdown(
results, value_col="profit_abs"
)
max_drawdown = (high_val - low_val) / high_val
except ValueError:
max_drawdown = 0
if max_drawdown != 0:
calmar_ratio = expected_returns_mean / max_drawdown * msqrt(365)
else:
# Define high (negative) calmar ratio to be clear that this is NOT optimal.
calmar_ratio = -20.0
# print(expected_returns_mean, max_drawdown, calmar_ratio)
return -calmar_ratio

18
freqtrade/optimize/hyperopt_tools.py
View File

@@ -1,4 +1,3 @@
import io
import logging
from copy import deepcopy
@@ -64,10 +63,11 @@ class HyperoptTools():
'export_time': datetime.now(timezone.utc),
}
logger.info(f"Dumping parameters to {filename}")
rapidjson.dump(final_params, filename.open('w'), indent=2,
default=hyperopt_serializer,
number_mode=rapidjson.NM_NATIVE | rapidjson.NM_NAN
)
with filename.open('w') as f:
rapidjson.dump(final_params, f, indent=2,
default=hyperopt_serializer,
number_mode=rapidjson.NM_NATIVE | rapidjson.NM_NAN
)
@staticmethod
def try_export_params(config: Dict[str, Any], strategy_name: str, params: Dict):
@@ -284,10 +284,10 @@ class HyperoptTools():
return (f"{results_metrics['total_trades']:6d} trades. "
f"{results_metrics['wins']}/{results_metrics['draws']}"
f"/{results_metrics['losses']} Wins/Draws/Losses. "
f"Avg profit {results_metrics['profit_mean'] * 100: 6.2f}%. "
f"Median profit {results_metrics['profit_median'] * 100: 6.2f}%. "
f"Total profit {results_metrics['profit_total_abs']: 11.8f} {stake_currency} "
f"({results_metrics['profit_total'] * 100: 7.2f}%). "
f"Avg profit {results_metrics['profit_mean']:7.2%}. "
f"Median profit {results_metrics['profit_median']:7.2%}. "
f"Total profit {results_metrics['profit_total_abs']:11.8f} {stake_currency} "
f"({results_metrics['profit_total']:8.2%}). "
f"Avg duration {results_metrics['holding_avg']} min."
)

192
freqtrade/optimize/optimize_reports.py
View File

@@ -4,7 +4,7 @@ from pathlib import Path
from typing import Any, Dict, List, Union
from numpy import int64
from pandas import DataFrame
from pandas import DataFrame, to_datetime
from tabulate import tabulate
from freqtrade.constants import DATETIME_PRINT_FORMAT, LAST_BT_RESULT_FN, UNLIMITED_STAKE_AMOUNT
@@ -46,11 +46,11 @@ def _get_line_floatfmt(stake_currency: str) -> List[str]:
'.2f', 'd', 's', 's']
def _get_line_header(first_column: str, stake_currency: str) -> List[str]:
def _get_line_header(first_column: str, stake_currency: str, direction: str = 'Buys') -> List[str]:
"""
Generate header lines (goes in line with _generate_result_line())
"""
return [first_column, 'Buys', 'Avg Profit %', 'Cum Profit %',
return [first_column, direction, 'Avg Profit %', 'Cum Profit %',
f'Tot Profit {stake_currency}', 'Tot Profit %', 'Avg Duration',
'Win Draw Loss Win%']
@@ -127,6 +127,38 @@ def generate_pair_metrics(data: Dict[str, Dict], stake_currency: str, starting_b
return tabular_data
def generate_tag_metrics(tag_type: str,
starting_balance: int,
results: DataFrame,
skip_nan: bool = False) -> List[Dict]:
"""
Generates and returns a list of metrics for the given tag trades and the results dataframe
:param starting_balance: Starting balance
:param results: Dataframe containing the backtest results
:param skip_nan: Print "left open" open trades
:return: List of Dicts containing the metrics per pair
"""
tabular_data = []
if tag_type in results.columns:
for tag, count in results[tag_type].value_counts().iteritems():
result = results[results[tag_type] == tag]
if skip_nan and result['profit_abs'].isnull().all():
continue
tabular_data.append(_generate_result_line(result, starting_balance, tag))
# Sort by total profit %:
tabular_data = sorted(tabular_data, key=lambda k: k['profit_total_abs'], reverse=True)
# Append Total
tabular_data.append(_generate_result_line(results, starting_balance, 'TOTAL'))
return tabular_data
else:
return []
def generate_sell_reason_stats(max_open_trades: int, results: DataFrame) -> List[Dict]:
"""
Generate small table outlining Backtest results
@@ -189,7 +221,6 @@ def generate_strategy_comparison(all_results: Dict) -> List[Dict]:
def generate_edge_table(results: dict) -> str:
floatfmt = ('s', '.10g', '.2f', '.2f', '.2f', '.2f', 'd', 'd', 'd')
tabular_data = []
headers = ['Pair', 'Stoploss', 'Win Rate', 'Risk Reward Ratio',
@@ -214,6 +245,41 @@ def generate_edge_table(results: dict) -> str:
floatfmt=floatfmt, tablefmt="orgtbl", stralign="right") # type: ignore
def _get_resample_from_period(period: str) -> str:
if period == 'day':
return '1d'
if period == 'week':
return '1w'
if period == 'month':
return '1M'
raise ValueError(f"Period {period} is not supported.")
def generate_periodic_breakdown_stats(trade_list: List, period: str) -> List[Dict[str, Any]]:
results = DataFrame.from_records(trade_list)
if len(results) == 0:
return []
results['close_date'] = to_datetime(results['close_date'], utc=True)
resample_period = _get_resample_from_period(period)
resampled = results.resample(resample_period, on='close_date')
stats = []
for name, day in resampled:
profit_abs = day['profit_abs'].sum().round(10)
wins = sum(day['profit_abs'] > 0)
draws = sum(day['profit_abs'] == 0)
loses = sum(day['profit_abs'] < 0)
stats.append(
{
'date': name.strftime('%d/%m/%Y'),
'profit_abs': profit_abs,
'wins': wins,
'draws': draws,
'loses': loses
}
)
return stats
def generate_trading_stats(results: DataFrame) -> Dict[str, Any]:
""" Generate overall trade statistics """
if len(results) == 0:
@@ -313,6 +379,10 @@ def generate_strategy_stats(btdata: Dict[str, DataFrame],
pair_results = generate_pair_metrics(btdata, stake_currency=stake_currency,
starting_balance=starting_balance,
results=results, skip_nan=False)
buy_tag_results = generate_tag_metrics("buy_tag", starting_balance=starting_balance,
results=results, skip_nan=False)
sell_reason_stats = generate_sell_reason_stats(max_open_trades=max_open_trades,
results=results)
left_open_results = generate_pair_metrics(btdata, stake_currency=stake_currency,
@@ -329,15 +399,18 @@ def generate_strategy_stats(btdata: Dict[str, DataFrame],
results['open_timestamp'] = results['open_date'].view(int64) // 1e6
results['close_timestamp'] = results['close_date'].view(int64) // 1e6
backtest_days = (max_date - min_date).days
backtest_days = (max_date - min_date).days or 1
strat_stats = {
'trades': results.to_dict(orient='records'),
'locks': [lock.to_json() for lock in content['locks']],
'best_pair': best_pair,
'worst_pair': worst_pair,
'results_per_pair': pair_results,
'results_per_buy_tag': buy_tag_results,
'sell_reason_summary': sell_reason_stats,
'left_open_trades': left_open_results,
# 'days_breakdown_stats': days_breakdown_stats,
'total_trades': len(results),
'total_volume': float(results['stake_amount'].sum()),
'avg_stake_amount': results['stake_amount'].mean() if len(results) > 0 else 0,
@@ -354,7 +427,7 @@ def generate_strategy_stats(btdata: Dict[str, DataFrame],
'backtest_run_start_ts': content['backtest_start_time'],
'backtest_run_end_ts': content['backtest_end_time'],
'trades_per_day': round(len(results) / backtest_days, 2) if backtest_days > 0 else 0,
'trades_per_day': round(len(results) / backtest_days, 2),
'market_change': market_change,
'pairlist': list(btdata.keys()),
'stake_amount': config['stake_amount'],
@@ -506,6 +579,59 @@ def text_table_sell_reason(sell_reason_stats: List[Dict[str, Any]], stake_curren
return tabulate(output, headers=headers, tablefmt="orgtbl", stralign="right")
def text_table_tags(tag_type: str, tag_results: List[Dict[str, Any]], stake_currency: str) -> str:
"""
Generates and returns a text table for the given backtest data and the results dataframe
:param pair_results: List of Dictionaries - one entry per pair + final TOTAL row
:param stake_currency: stake-currency - used to correctly name headers
:return: pretty printed table with tabulate as string
"""
if(tag_type == "buy_tag"):
headers = _get_line_header("TAG", stake_currency)
else:
headers = _get_line_header("TAG", stake_currency, 'Sells')
floatfmt = _get_line_floatfmt(stake_currency)
output = [
[
t['key'] if t['key'] is not None and len(
t['key']) > 0 else "OTHER",
t['trades'],
t['profit_mean_pct'],
t['profit_sum_pct'],
t['profit_total_abs'],
t['profit_total_pct'],
t['duration_avg'],
_generate_wins_draws_losses(
t['wins'],
t['draws'],
t['losses'])] for t in tag_results]
# Ignore type as floatfmt does allow tuples but mypy does not know that
return tabulate(output, headers=headers,
floatfmt=floatfmt, tablefmt="orgtbl", stralign="right")
def text_table_periodic_breakdown(days_breakdown_stats: List[Dict[str, Any]],
stake_currency: str, period: str) -> str:
"""
Generate small table with Backtest results by days
:param days_breakdown_stats: Days breakdown metrics
:param stake_currency: Stakecurrency used
:return: pretty printed table with tabulate as string
"""
headers = [
period.capitalize(),
f'Tot Profit {stake_currency}',
'Wins',
'Draws',
'Losses',
]
output = [[
d['date'], round_coin_value(d['profit_abs'], stake_currency, False),
d['wins'], d['draws'], d['loses'],
] for d in days_breakdown_stats]
return tabulate(output, headers=headers, tablefmt="orgtbl", stralign="right")
def text_table_strategy(strategy_results, stake_currency: str) -> str:
"""
Generate summary table per strategy
@@ -557,19 +683,22 @@ def text_table_add_metrics(strat_results: Dict) -> str:
strat_results['stake_currency'])),
('Absolute profit ', round_coin_value(strat_results['profit_total_abs'],
strat_results['stake_currency'])),
('Total profit %', f"{round(strat_results['profit_total'] * 100, 2):}%"),
('Total profit %', f"{strat_results['profit_total']:.2%}"),
('Trades per day', strat_results['trades_per_day']),
('Avg. daily profit %',
f"{(strat_results['profit_total'] / strat_results['backtest_days']):.2%}"),
('Avg. stake amount', round_coin_value(strat_results['avg_stake_amount'],
strat_results['stake_currency'])),
('Total trade volume', round_coin_value(strat_results['total_volume'],
strat_results['stake_currency'])),
('', ''), # Empty line to improve readability
('Best Pair', f"{strat_results['best_pair']['key']} "
f"{round(strat_results['best_pair']['profit_sum_pct'], 2)}%"),
f"{strat_results['best_pair']['profit_sum']:.2%}"),
('Worst Pair', f"{strat_results['worst_pair']['key']} "
f"{round(strat_results['worst_pair']['profit_sum_pct'], 2)}%"),
('Best trade', f"{best_trade['pair']} {round(best_trade['profit_ratio'] * 100, 2)}%"),
f"{strat_results['worst_pair']['profit_sum']:.2%}"),
('Best trade', f"{best_trade['pair']} {best_trade['profit_ratio']:.2%}"),
('Worst trade', f"{worst_trade['pair']} "
f"{round(worst_trade['profit_ratio'] * 100, 2)}%"),
f"{worst_trade['profit_ratio']:.2%}"),
('Best day', round_coin_value(strat_results['backtest_best_day_abs'],
strat_results['stake_currency'])),
@@ -587,7 +716,7 @@ def text_table_add_metrics(strat_results: Dict) -> str:
('Max balance', round_coin_value(strat_results['csum_max'],
strat_results['stake_currency'])),
('Drawdown', f"{round(strat_results['max_drawdown'] * 100, 2)}%"),
('Drawdown', f"{strat_results['max_drawdown']:.2%}"),
('Drawdown', round_coin_value(strat_results['max_drawdown_abs'],
strat_results['stake_currency'])),
('Drawdown high', round_coin_value(strat_results['max_drawdown_high'],
@@ -596,7 +725,7 @@ def text_table_add_metrics(strat_results: Dict) -> str:
strat_results['stake_currency'])),
('Drawdown Start', strat_results['drawdown_start']),
('Drawdown End', strat_results['drawdown_end']),
('Market change', f"{round(strat_results['market_change'] * 100, 2)}%"),
('Market change', f"{strat_results['market_change']:.2%}"),
]
return tabulate(metrics, headers=["Metric", "Value"], tablefmt="orgtbl")
@@ -614,7 +743,8 @@ def text_table_add_metrics(strat_results: Dict) -> str:
return message
def show_backtest_result(strategy: str, results: Dict[str, Any], stake_currency: str):
def show_backtest_result(strategy: str, results: Dict[str, Any], stake_currency: str,
backtest_breakdown=[]):
"""
Print results for one strategy
"""
@@ -625,6 +755,16 @@ def show_backtest_result(strategy: str, results: Dict[str, Any], stake_currency:
print(' BACKTESTING REPORT '.center(len(table.splitlines()[0]), '='))
print(table)
if results.get('results_per_buy_tag') is not None:
table = text_table_tags(
"buy_tag",
results['results_per_buy_tag'],
stake_currency=stake_currency)
if isinstance(table, str) and len(table) > 0:
print(' BUY TAG STATS '.center(len(table.splitlines()[0]), '='))
print(table)
table = text_table_sell_reason(sell_reason_stats=results['sell_reason_summary'],
stake_currency=stake_currency)
if isinstance(table, str) and len(table) > 0:
@@ -636,6 +776,15 @@ def show_backtest_result(strategy: str, results: Dict[str, Any], stake_currency:
print(' LEFT OPEN TRADES REPORT '.center(len(table.splitlines()[0]), '='))
print(table)
for period in backtest_breakdown:
days_breakdown_stats = generate_periodic_breakdown_stats(
trade_list=results['trades'], period=period)
table = text_table_periodic_breakdown(days_breakdown_stats=days_breakdown_stats,
stake_currency=stake_currency, period=period)
if isinstance(table, str) and len(table) > 0:
print(f' {period.upper()} BREAKDOWN '.center(len(table.splitlines()[0]), '='))
print(table)
table = text_table_add_metrics(results)
if isinstance(table, str) and len(table) > 0:
print(' SUMMARY METRICS '.center(len(table.splitlines()[0]), '='))
@@ -643,6 +792,7 @@ def show_backtest_result(strategy: str, results: Dict[str, Any], stake_currency:
if isinstance(table, str) and len(table) > 0:
print('=' * len(table.splitlines()[0]))
print()
@@ -650,7 +800,9 @@ def show_backtest_results(config: Dict, backtest_stats: Dict):
stake_currency = config['stake_currency']
for strategy, results in backtest_stats['strategy'].items():
show_backtest_result(strategy, results, stake_currency)
show_backtest_result(
strategy, results, stake_currency,
config.get('backtest_breakdown', []))
if len(backtest_stats['strategy']) > 1:
# Print Strategy summary table
@@ -662,3 +814,13 @@ def show_backtest_results(config: Dict, backtest_stats: Dict):
print(table)
print('=' * len(table.splitlines()[0]))
print('\nFor more details, please look at the detail tables above')
def show_sorted_pairlist(config: Dict, backtest_stats: Dict):
if config.get('backtest_show_pair_list', False):
for strategy, results in backtest_stats['strategy'].items():
print(f"Pairs for Strategy {strategy}: \n[")
for result in results['results_per_pair']:
if result["key"] != 'TOTAL':
print(f'"{result["key"]}", // {result["profit_mean"]:.2%}')
print("]")

18
freqtrade/optimize/space/decimalspace.py
View File

@@ -7,11 +7,15 @@ class SKDecimal(Integer):
def __init__(self, low, high, decimals=3, prior="uniform", base=10, transform=None,
name=None, dtype=np.int64):
self.decimals = decimals
_low = int(low * pow(10, self.decimals))
_high = int(high * pow(10, self.decimals))
self.pow_dot_one = pow(0.1, self.decimals)
self.pow_ten = pow(10, self.decimals)
_low = int(low * self.pow_ten)
_high = int(high * self.pow_ten)
# trunc to precision to avoid points out of space
self.low_orig = round(_low * pow(0.1, self.decimals), self.decimals)
self.high_orig = round(_high * pow(0.1, self.decimals), self.decimals)
self.low_orig = round(_low * self.pow_dot_one, self.decimals)
self.high_orig = round(_high * self.pow_dot_one, self.decimals)
super().__init__(_low, _high, prior, base, transform, name, dtype)
@@ -25,9 +29,9 @@ class SKDecimal(Integer):
return self.low_orig <= point <= self.high_orig
def transform(self, Xt):
aa = [int(x * pow(10, self.decimals)) for x in Xt]
return super().transform(aa)
return super().transform([int(v * self.pow_ten) for v in Xt])
def inverse_transform(self, Xt):
res = super().inverse_transform(Xt)
return [round(x * pow(0.1, self.decimals), self.decimals) for x in res]
# equivalent to [round(x * pow(0.1, self.decimals), self.decimals) for x in res]
return [int(v) / self.pow_ten for v in res]

135
freqtrade/persistence/models.py
View File

@@ -195,6 +195,8 @@ class Order(_DECL_BASE):
@staticmethod
def get_open_orders() -> List['Order']:
"""
Retrieve open orders from the database
:return: List of open orders
"""
return Order.query.filter(Order.ft_is_open.is_(True)).all()
@@ -491,6 +493,13 @@ class LocalTrade():
def update_order(self, order: Dict) -> None:
Order.update_orders(self.orders, order)
def get_exit_order_count(self) -> int:
"""
Get amount of failed exiting orders
assumes full exits.
"""
return len([o for o in self.orders if o.ft_order_side == 'sell'])
def _calc_open_trade_value(self) -> float:
"""
Calculate the open_rate including open_fee.
@@ -775,7 +784,7 @@ class Trade(_DECL_BASE, LocalTrade):
return Trade.query
@staticmethod
def get_open_order_trades():
def get_open_order_trades() -> List['Trade']:
"""
Returns all open trades
NOTE: Not supported in Backtesting.
@@ -853,13 +862,132 @@ class Trade(_DECL_BASE, LocalTrade):
return [
{
'pair': pair,
'profit': profit,
'profit_ratio': profit,
'profit': round(profit * 100, 2), # Compatibility mode
'profit_pct': round(profit * 100, 2),
'profit_abs': profit_abs,
'count': count
}
for pair, profit, profit_abs, count in pair_rates
]
@staticmethod
def get_buy_tag_performance(pair: Optional[str]) -> List[Dict[str, Any]]:
"""
Returns List of dicts containing all Trades, based on buy tag performance
Can either be average for all pairs or a specific pair provided
NOTE: Not supported in Backtesting.
"""
filters = [Trade.is_open.is_(False)]
if(pair is not None):
filters.append(Trade.pair == pair)
buy_tag_perf = Trade.query.with_entities(
Trade.buy_tag,
func.sum(Trade.close_profit).label('profit_sum'),
func.sum(Trade.close_profit_abs).label('profit_sum_abs'),
func.count(Trade.pair).label('count')
).filter(*filters)\
.group_by(Trade.buy_tag) \
.order_by(desc('profit_sum_abs')) \
.all()
return [
{
'buy_tag': buy_tag if buy_tag is not None else "Other",
'profit_ratio': profit,
'profit_pct': round(profit * 100, 2),
'profit_abs': profit_abs,
'count': count
}
for buy_tag, profit, profit_abs, count in buy_tag_perf
]
@staticmethod
def get_sell_reason_performance(pair: Optional[str]) -> List[Dict[str, Any]]:
"""
Returns List of dicts containing all Trades, based on sell reason performance
Can either be average for all pairs or a specific pair provided
NOTE: Not supported in Backtesting.
"""
filters = [Trade.is_open.is_(False)]
if(pair is not None):
filters.append(Trade.pair == pair)
sell_tag_perf = Trade.query.with_entities(
Trade.sell_reason,
func.sum(Trade.close_profit).label('profit_sum'),
func.sum(Trade.close_profit_abs).label('profit_sum_abs'),
func.count(Trade.pair).label('count')
).filter(*filters)\
.group_by(Trade.sell_reason) \
.order_by(desc('profit_sum_abs')) \
.all()
return [
{
'sell_reason': sell_reason if sell_reason is not None else "Other",
'profit_ratio': profit,
'profit_pct': round(profit * 100, 2),
'profit_abs': profit_abs,
'count': count
}
for sell_reason, profit, profit_abs, count in sell_tag_perf
]
@staticmethod
def get_mix_tag_performance(pair: Optional[str]) -> List[Dict[str, Any]]:
"""
Returns List of dicts containing all Trades, based on buy_tag + sell_reason performance
Can either be average for all pairs or a specific pair provided
NOTE: Not supported in Backtesting.
"""
filters = [Trade.is_open.is_(False)]
if(pair is not None):
filters.append(Trade.pair == pair)
mix_tag_perf = Trade.query.with_entities(
Trade.id,
Trade.buy_tag,
Trade.sell_reason,
func.sum(Trade.close_profit).label('profit_sum'),
func.sum(Trade.close_profit_abs).label('profit_sum_abs'),
func.count(Trade.pair).label('count')
).filter(*filters)\
.group_by(Trade.id) \
.order_by(desc('profit_sum_abs')) \
.all()
return_list: List[Dict] = []
for id, buy_tag, sell_reason, profit, profit_abs, count in mix_tag_perf:
buy_tag = buy_tag if buy_tag is not None else "Other"
sell_reason = sell_reason if sell_reason is not None else "Other"
if(sell_reason is not None and buy_tag is not None):
mix_tag = buy_tag + " " + sell_reason
i = 0
if not any(item["mix_tag"] == mix_tag for item in return_list):
return_list.append({'mix_tag': mix_tag,
'profit': profit,
'profit_pct': round(profit * 100, 2),
'profit_abs': profit_abs,
'count': count})
else:
while i < len(return_list):
if return_list[i]["mix_tag"] == mix_tag:
return_list[i] = {
'mix_tag': mix_tag,
'profit': profit + return_list[i]["profit"],
'profit_pct': round(profit + return_list[i]["profit"] * 100, 2),
'profit_abs': profit_abs + return_list[i]["profit_abs"],
'count': 1 + return_list[i]["count"]}
i += 1
return return_list
@staticmethod
def get_best_pair(start_date: datetime = datetime.fromtimestamp(0)):
"""
@@ -896,7 +1024,7 @@ class PairLock(_DECL_BASE):
lock_time = self.lock_time.strftime(DATETIME_PRINT_FORMAT)
lock_end_time = self.lock_end_time.strftime(DATETIME_PRINT_FORMAT)
return (f'PairLock(id={self.id}, pair={self.pair}, lock_time={lock_time}, '
f'lock_end_time={lock_end_time})')
f'lock_end_time={lock_end_time}, reason={self.reason}, active={self.active})')
@staticmethod
def query_pair_locks(pair: Optional[str], now: datetime) -> Query:
@@ -905,7 +1033,6 @@ class PairLock(_DECL_BASE):
:param pair: Pair to check for. Returns all current locks if pair is empty
:param now: Datetime object (generated via datetime.now(timezone.utc)).
"""
filters = [PairLock.lock_end_time > now,
# Only active locks
PairLock.active.is_(True), ]

34
freqtrade/persistence/pairlock_middleware.py
View File

@@ -103,6 +103,36 @@ class PairLocks():
if PairLocks.use_db:
PairLock.query.session.commit()
@staticmethod
def unlock_reason(reason: str, now: Optional[datetime] = None) -> None:
"""
Release all locks for this reason.
:param reason: Which reason to unlock
:param now: Datetime object (generated via datetime.now(timezone.utc)).
defaults to datetime.now(timezone.utc)
"""
if not now:
now = datetime.now(timezone.utc)
if PairLocks.use_db:
# used in live modes
logger.info(f"Releasing all locks with reason '{reason}':")
filters = [PairLock.lock_end_time > now,
PairLock.active.is_(True),
PairLock.reason == reason
]
locks = PairLock.query.filter(*filters)
for lock in locks:
logger.info(f"Releasing lock for {lock.pair} with reason '{reason}'.")
lock.active = False
PairLock.query.session.commit()
else:
# used in backtesting mode; don't show log messages for speed
locks = PairLocks.get_pair_locks(None)
for lock in locks:
if lock.reason == reason:
lock.active = False
@staticmethod
def is_global_lock(now: Optional[datetime] = None) -> bool:
"""
@@ -128,7 +158,9 @@ class PairLocks():
@staticmethod
def get_all_locks() -> List[PairLock]:
"""
Return all locks, also locks with expired end date
"""
if PairLocks.use_db:
return PairLock.query.all()
else:

6
freqtrade/plot/plotting.py
View File

@@ -169,8 +169,8 @@ def add_max_drawdown(fig, row, trades: pd.DataFrame, df_comb: pd.DataFrame,
df_comb.loc[timeframe_to_prev_date(timeframe, lowdate), 'cum_profit'],
],
mode='markers',
name=f"Max drawdown {max_drawdown * 100:.2f}%",
text=f"Max drawdown {max_drawdown * 100:.2f}%",
name=f"Max drawdown {max_drawdown:.2%}",
text=f"Max drawdown {max_drawdown:.2%}",
marker=dict(
symbol='square-open',
size=9,
@@ -192,7 +192,7 @@ def plot_trades(fig, trades: pd.DataFrame) -> make_subplots:
# Trades can be empty
if trades is not None and len(trades) > 0:
# Create description for sell summarizing the trade
trades['desc'] = trades.apply(lambda row: f"{round(row['profit_ratio'] * 100, 1)}%, "
trades['desc'] = trades.apply(lambda row: f"{row['profit_ratio']:.2%}, "
f"{row['sell_reason']}, "
f"{row['trade_duration']} min",
axis=1)

4
freqtrade/plugins/pairlist/PriceFilter.py
View File

@@ -50,7 +50,7 @@ class PriceFilter(IPairList):
"""
active_price_filters = []
if self._low_price_ratio != 0:
active_price_filters.append(f"below {self._low_price_ratio * 100}%")
active_price_filters.append(f"below {self._low_price_ratio:.1%}")
if self._min_price != 0:
active_price_filters.append(f"below {self._min_price:.8f}")
if self._max_price != 0:
@@ -82,7 +82,7 @@ class PriceFilter(IPairList):
changeperc = compare / ticker['last']
if changeperc > self._low_price_ratio:
self.log_once(f"Removed {pair} from whitelist, "
f"because 1 unit is {changeperc * 100:.3f}%", logger.info)
f"because 1 unit is {changeperc:.3%}", logger.info)
return False
# Perform low_amount check

11
freqtrade/plugins/pairlist/ShuffleFilter.py
View File

@@ -5,6 +5,7 @@ import logging
import random
from typing import Any, Dict, List
from freqtrade.enums.runmode import RunMode
from freqtrade.plugins.pairlist.IPairList import IPairList
@@ -18,7 +19,15 @@ class ShuffleFilter(IPairList):
pairlist_pos: int) -> None:
super().__init__(exchange, pairlistmanager, config, pairlistconfig, pairlist_pos)
self._seed = pairlistconfig.get('seed')
# Apply seed in backtesting mode to get comparable results,
# but not in live modes to get a non-repeating order of pairs during live modes.
if config.get('runmode') in (RunMode.LIVE, RunMode.DRY_RUN):
self._seed = None
logger.info("Live mode detected, not applying seed.")
else:
self._seed = pairlistconfig.get('seed')
logger.info(f"Backtesting mode detected, applying seed value: {self._seed}")
self._random = random.Random(self._seed)
@property

4
freqtrade/plugins/pairlist/SpreadFilter.py
View File

@@ -34,7 +34,7 @@ class SpreadFilter(IPairList):
Short whitelist method description - used for startup-messages
"""
return (f"{self.name} - Filtering pairs with ask/bid diff above "
f"{self._max_spread_ratio * 100}%.")
f"{self._max_spread_ratio:.2%}.")
def _validate_pair(self, pair: str, ticker: Dict[str, Any]) -> bool:
"""
@@ -47,7 +47,7 @@ class SpreadFilter(IPairList):
spread = 1 - ticker['bid'] / ticker['ask']
if spread > self._max_spread_ratio:
self.log_once(f"Removed {pair} from whitelist, because spread "
f"{spread * 100:.3f}% > {self._max_spread_ratio * 100}%",
f"{spread * 100:.3%} > {self._max_spread_ratio:.3%}",
logger.info)
return False
else:

12
freqtrade/plugins/pairlist/StaticPairList.py
View File

@@ -4,9 +4,9 @@ Static Pair List provider
Provides pair white list as it configured in config
"""
import logging
from copy import deepcopy
from typing import Any, Dict, List
from freqtrade.exceptions import OperationalException
from freqtrade.plugins.pairlist.IPairList import IPairList
@@ -20,10 +20,6 @@ class StaticPairList(IPairList):
pairlist_pos: int) -> None:
super().__init__(exchange, pairlistmanager, config, pairlistconfig, pairlist_pos)
if self._pairlist_pos != 0:
raise OperationalException(f"{self.name} can only be used in the first position "
"in the list of Pairlist Handlers.")
self._allow_inactive = self._pairlistconfig.get('allow_inactive', False)
@property
@@ -64,4 +60,8 @@ class StaticPairList(IPairList):
:param tickers: Tickers (from exchange.get_tickers()). May be cached.
:return: new whitelist
"""
return pairlist
pairlist_ = deepcopy(pairlist)
for pair in self._config['exchange']['pair_whitelist']:
if pair not in pairlist_:
pairlist_.append(pair)
return pairlist_

4
freqtrade/resolvers/iresolver.py
View File

@@ -91,7 +91,7 @@ class IResolver:
logger.debug(f"Searching for {cls.object_type.__name__} {object_name} in '{directory}'")
for entry in directory.iterdir():
# Only consider python files
if not str(entry).endswith('.py'):
if entry.suffix != '.py':
logger.debug('Ignoring %s', entry)
continue
if entry.is_symlink() and not entry.is_file():
@@ -169,7 +169,7 @@ class IResolver:
objects = []
for entry in directory.iterdir():
# Only consider python files
if not str(entry).endswith('.py'):
if entry.suffix != '.py':
logger.debug('Ignoring %s', entry)
continue
module_path = entry.resolve()

18
freqtrade/resolvers/strategy_resolver.py
View File

@@ -56,17 +56,21 @@ class StrategyResolver(IResolver):
if strategy._ft_params_from_file:
# Set parameters from Hyperopt results file
params = strategy._ft_params_from_file
strategy.minimal_roi = params.get('roi', strategy.minimal_roi)
strategy.minimal_roi = params.get('roi', getattr(strategy, 'minimal_roi', {}))
strategy.stoploss = params.get('stoploss', {}).get('stoploss', strategy.stoploss)
strategy.stoploss = params.get('stoploss', {}).get(
'stoploss', getattr(strategy, 'stoploss', -0.1))
trailing = params.get('trailing', {})
strategy.trailing_stop = trailing.get('trailing_stop', strategy.trailing_stop)
strategy.trailing_stop_positive = trailing.get('trailing_stop_positive',
strategy.trailing_stop_positive)
strategy.trailing_stop = trailing.get(
'trailing_stop', getattr(strategy, 'trailing_stop', False))
strategy.trailing_stop_positive = trailing.get(
'trailing_stop_positive', getattr(strategy, 'trailing_stop_positive', None))
strategy.trailing_stop_positive_offset = trailing.get(
'trailing_stop_positive_offset', strategy.trailing_stop_positive_offset)
'trailing_stop_positive_offset',
getattr(strategy, 'trailing_stop_positive_offset', 0))
strategy.trailing_only_offset_is_reached = trailing.get(
'trailing_only_offset_is_reached', strategy.trailing_only_offset_is_reached)
'trailing_only_offset_is_reached',
getattr(strategy, 'trailing_only_offset_is_reached', 0.0))
# Set attributes
# Check if we need to override configuration

28
freqtrade/rpc/api_server/api_schemas.py
View File

@@ -4,6 +4,7 @@ from typing import Any, Dict, List, Optional, Union
from pydantic import BaseModel
from freqtrade.constants import DATETIME_PRINT_FORMAT
from freqtrade.enums import OrderTypeValues
class Ping(BaseModel):
@@ -63,6 +64,8 @@ class Count(BaseModel):
class PerformanceEntry(BaseModel):
pair: str
profit: float
profit_ratio: float
profit_pct: float
profit_abs: float
count: int
@@ -93,6 +96,7 @@ class Profit(BaseModel):
avg_duration: str
best_pair: str
best_rate: float
best_pair_profit_ratio: float
winning_trades: int
losing_trades: int
@@ -121,7 +125,27 @@ class Daily(BaseModel):
stake_currency: str
class UnfilledTimeout(BaseModel):
buy: Optional[int]
sell: Optional[int]
unit: Optional[str]
exit_timeout_count: Optional[int]
class OrderTypes(BaseModel):
buy: OrderTypeValues
sell: OrderTypeValues
emergencysell: Optional[OrderTypeValues]
forcesell: Optional[OrderTypeValues]
forcebuy: Optional[OrderTypeValues]
stoploss: OrderTypeValues
stoploss_on_exchange: bool
stoploss_on_exchange_interval: Optional[int]
class ShowConfig(BaseModel):
version: str
api_version: float
dry_run: bool
stake_currency: str
stake_amount: Union[float, str]
@@ -134,6 +158,8 @@ class ShowConfig(BaseModel):
trailing_stop_positive: Optional[float]
trailing_stop_positive_offset: Optional[float]
trailing_only_offset_is_reached: Optional[bool]
unfilledtimeout: UnfilledTimeout
order_types: OrderTypes
use_custom_stoploss: Optional[bool]
timeframe: Optional[str]
timeframe_ms: int
@@ -249,10 +275,12 @@ class Logs(BaseModel):
class ForceBuyPayload(BaseModel):
pair: str
price: Optional[float]
ordertype: Optional[OrderTypeValues]
class ForceSellPayload(BaseModel):
tradeid: str
ordertype: Optional[OrderTypeValues]
class BlacklistPayload(BaseModel):

16
freqtrade/rpc/api_server/api_v1.py
View File

@@ -26,6 +26,12 @@ from freqtrade.rpc.rpc import RPCException
logger = logging.getLogger(__name__)
# API version
# Pre-1.1, no version was provided
# Version increments should happen in "small" steps (1.1, 1.12, ...) unless big changes happen.
# 1.11: forcebuy and forcesell accept ordertype
API_VERSION = 1.11
# Public API, requires no auth.
router_public = APIRouter()
# Private API, protected by authentication
@@ -117,12 +123,15 @@ def show_config(rpc: Optional[RPC] = Depends(get_rpc_optional), config=Depends(g
state = ''
if rpc:
state = rpc._freqtrade.state
return RPC._rpc_show_config(config, state)
resp = RPC._rpc_show_config(config, state)
resp['api_version'] = API_VERSION
return resp
@router.post('/forcebuy', response_model=ForceBuyResponse, tags=['trading'])
def forcebuy(payload: ForceBuyPayload, rpc: RPC = Depends(get_rpc)):
trade = rpc._rpc_forcebuy(payload.pair, payload.price)
ordertype = payload.ordertype.value if payload.ordertype else None
trade = rpc._rpc_forcebuy(payload.pair, payload.price, ordertype)
if trade:
return ForceBuyResponse.parse_obj(trade.to_json())
@@ -132,7 +141,8 @@ def forcebuy(payload: ForceBuyPayload, rpc: RPC = Depends(get_rpc)):
@router.post('/forcesell', response_model=ResultMsg, tags=['trading'])
def forcesell(payload: ForceSellPayload, rpc: RPC = Depends(get_rpc)):
return rpc._rpc_forcesell(payload.tradeid)
ordertype = payload.ordertype.value if payload.ordertype else None
return rpc._rpc_forcesell(payload.tradeid, ordertype)
@router.get('/blacklist', response_model=BlacklistResponse, tags=['info', 'pairlist'])

152
freqtrade/rpc/rpc.py
View File

@@ -9,9 +9,11 @@ from typing import Any, Dict, List, Optional, Tuple, Union
import arrow
import psutil
from dateutil.relativedelta import relativedelta
from numpy import NAN, inf, int64, mean
from pandas import DataFrame
from freqtrade import __version__
from freqtrade.configuration.timerange import TimeRange
from freqtrade.constants import CANCEL_REASON, DATETIME_PRINT_FORMAT
from freqtrade.data.history import load_data
@@ -103,9 +105,10 @@ class RPC:
information via rpc.
"""
val = {
'version': __version__,
'dry_run': config['dry_run'],
'stake_currency': config['stake_currency'],
'stake_currency_decimals': decimals_per_coin(config['stake_currency']),
'stake_currency_decimals': decimals_per_coin(config['stake_currency']),
'stake_amount': config['stake_amount'],
'available_capital': config.get('available_capital'),
'max_open_trades': (config['max_open_trades']
@@ -116,7 +119,9 @@ class RPC:
'trailing_stop_positive': config.get('trailing_stop_positive'),
'trailing_stop_positive_offset': config.get('trailing_stop_positive_offset'),
'trailing_only_offset_is_reached': config.get('trailing_only_offset_is_reached'),
'unfilledtimeout': config.get('unfilledtimeout'),
'use_custom_stoploss': config.get('use_custom_stoploss'),
'order_types': config.get('order_types'),
'bot_name': config.get('bot_name', 'freqtrade'),
'timeframe': config.get('timeframe'),
'timeframe_ms': timeframe_to_msecs(config['timeframe']
@@ -219,9 +224,8 @@ class RPC:
trade.pair, refresh=False, side="sell")
except (PricingError, ExchangeError):
current_rate = NAN
trade_percent = (100 * trade.calc_profit_ratio(current_rate))
trade_profit = trade.calc_profit(current_rate)
profit_str = f'{trade_percent:.2f}%'
profit_str = f'{trade.calc_profit_ratio(current_rate):.2%}'
if self._fiat_converter:
fiat_profit = self._fiat_converter.convert_amount(
trade_profit,
@@ -250,7 +254,7 @@ class RPC:
def _rpc_daily_profit(
self, timescale: int,
stake_currency: str, fiat_display_currency: str) -> Dict[str, Any]:
today = datetime.utcnow().date()
today = datetime.now(timezone.utc).date()
profit_days: Dict[date, Dict] = {}
if not (isinstance(timescale, int) and timescale > 0):
@@ -289,6 +293,91 @@ class RPC:
'data': data
}
def _rpc_weekly_profit(
self, timescale: int,
stake_currency: str, fiat_display_currency: str) -> Dict[str, Any]:
today = datetime.now(timezone.utc).date()
first_iso_day_of_week = today - timedelta(days=today.weekday()) # Monday
profit_weeks: Dict[date, Dict] = {}
if not (isinstance(timescale, int) and timescale > 0):
raise RPCException('timescale must be an integer greater than 0')
for week in range(0, timescale):
profitweek = first_iso_day_of_week - timedelta(weeks=week)
trades = Trade.get_trades(trade_filter=[
Trade.is_open.is_(False),
Trade.close_date >= profitweek,
Trade.close_date < (profitweek + timedelta(weeks=1))
]).order_by(Trade.close_date).all()
curweekprofit = sum(
trade.close_profit_abs for trade in trades if trade.close_profit_abs is not None)
profit_weeks[profitweek] = {
'amount': curweekprofit,
'trades': len(trades)
}
data = [
{
'date': key,
'abs_profit': value["amount"],
'fiat_value': self._fiat_converter.convert_amount(
value['amount'],
stake_currency,
fiat_display_currency
) if self._fiat_converter else 0,
'trade_count': value["trades"],
}
for key, value in profit_weeks.items()
]
return {
'stake_currency': stake_currency,
'fiat_display_currency': fiat_display_currency,
'data': data
}
def _rpc_monthly_profit(
self, timescale: int,
stake_currency: str, fiat_display_currency: str) -> Dict[str, Any]:
first_day_of_month = datetime.now(timezone.utc).date().replace(day=1)
profit_months: Dict[date, Dict] = {}
if not (isinstance(timescale, int) and timescale > 0):
raise RPCException('timescale must be an integer greater than 0')
for month in range(0, timescale):
profitmonth = first_day_of_month - relativedelta(months=month)
trades = Trade.get_trades(trade_filter=[
Trade.is_open.is_(False),
Trade.close_date >= profitmonth,
Trade.close_date < (profitmonth + relativedelta(months=1))
]).order_by(Trade.close_date).all()
curmonthprofit = sum(
trade.close_profit_abs for trade in trades if trade.close_profit_abs is not None)
profit_months[profitmonth] = {
'amount': curmonthprofit,
'trades': len(trades)
}
data = [
{
'date': f"{key.year}-{key.month:02d}",
'abs_profit': value["amount"],
'fiat_value': self._fiat_converter.convert_amount(
value['amount'],
stake_currency,
fiat_display_currency
) if self._fiat_converter else 0,
'trade_count': value["trades"],
}
for key, value in profit_months.items()
]
return {
'stake_currency': stake_currency,
'fiat_display_currency': fiat_display_currency,
'data': data
}
def _rpc_trade_history(self, limit: int, offset: int = 0, order_by_id: bool = False) -> Dict:
""" Returns the X last trades """
order_by = Trade.id if order_by_id else Trade.close_date.desc()
@@ -444,7 +533,8 @@ class RPC:
'latest_trade_timestamp': int(last_date.timestamp() * 1000) if last_date else 0,
'avg_duration': str(timedelta(seconds=sum(durations) / num)).split('.')[0],
'best_pair': best_pair[0] if best_pair else '',
'best_rate': round(best_pair[1] * 100, 2) if best_pair else 0,
'best_rate': round(best_pair[1] * 100, 2) if best_pair else 0, # Deprecated
'best_pair_profit_ratio': best_pair[1] if best_pair else 0,
'winning_trades': winning_trades,
'losing_trades': losing_trades,
}
@@ -550,7 +640,7 @@ class RPC:
return {'status': 'No more buy will occur from now. Run /reload_config to reset.'}
def _rpc_forcesell(self, trade_id: str) -> Dict[str, str]:
def _rpc_forcesell(self, trade_id: str, ordertype: Optional[str] = None) -> Dict[str, str]:
"""
Handler for forcesell <id>.
Sells the given trade at current price
@@ -574,7 +664,11 @@ class RPC:
current_rate = self._freqtrade.exchange.get_rate(
trade.pair, refresh=False, side="sell")
sell_reason = SellCheckTuple(sell_type=SellType.FORCE_SELL)
self._freqtrade.execute_trade_exit(trade, current_rate, sell_reason)
order_type = ordertype or self._freqtrade.strategy.order_types.get(
"forcesell", self._freqtrade.strategy.order_types["sell"])
self._freqtrade.execute_trade_exit(
trade, current_rate, sell_reason, ordertype=order_type)
# ---- EOF def _exec_forcesell ----
if self._freqtrade.state != State.RUNNING:
@@ -602,7 +696,8 @@ class RPC:
self._freqtrade.wallets.update()
return {'result': f'Created sell order for trade {trade_id}.'}
def _rpc_forcebuy(self, pair: str, price: Optional[float]) -> Optional[Trade]:
def _rpc_forcebuy(self, pair: str, price: Optional[float],
order_type: Optional[str] = None) -> Optional[Trade]:
"""
Handler for forcebuy <asset> <price>
Buys a pair trade at the given or current price
@@ -630,7 +725,10 @@ class RPC:
stakeamount = self._freqtrade.wallets.get_trade_stake_amount(pair)
# execute buy
if self._freqtrade.execute_entry(pair, stakeamount, price, forcebuy=True):
if not order_type:
order_type = self._freqtrade.strategy.order_types.get(
'forcebuy', self._freqtrade.strategy.order_types['buy'])
if self._freqtrade.execute_entry(pair, stakeamount, price, ordertype=order_type):
Trade.commit()
trade = Trade.get_trades([Trade.is_open.is_(True), Trade.pair == pair]).first()
return trade
@@ -682,10 +780,36 @@ class RPC:
Shows a performance statistic from finished trades
"""
pair_rates = Trade.get_overall_performance()
# Round and convert to %
[x.update({'profit': round(x['profit'] * 100, 2)}) for x in pair_rates]
return pair_rates
def _rpc_buy_tag_performance(self, pair: Optional[str]) -> List[Dict[str, Any]]:
"""
Handler for buy tag performance.
Shows a performance statistic from finished trades
"""
buy_tags = Trade.get_buy_tag_performance(pair)
return buy_tags
def _rpc_sell_reason_performance(self, pair: Optional[str]) -> List[Dict[str, Any]]:
"""
Handler for sell reason performance.
Shows a performance statistic from finished trades
"""
sell_reasons = Trade.get_sell_reason_performance(pair)
return sell_reasons
def _rpc_mix_tag_performance(self, pair: Optional[str]) -> List[Dict[str, Any]]:
"""
Handler for mix tag (buy_tag + sell_reason) performance.
Shows a performance statistic from finished trades
"""
mix_tags = Trade.get_mix_tag_performance(pair)
return mix_tags
def _rpc_count(self) -> Dict[str, float]:
""" Returns the number of trades running """
if self._freqtrade.state != State.RUNNING:
@@ -793,15 +917,15 @@ class RPC:
if has_content:
dataframe.loc[:, '__date_ts'] = dataframe.loc[:, 'date'].view(int64) // 1000 // 1000
# Move open to separate column when signal for easy plotting
# Move signal close to separate column when signal for easy plotting
if 'buy' in dataframe.columns:
buy_mask = (dataframe['buy'] == 1)
buy_signals = int(buy_mask.sum())
dataframe.loc[buy_mask, '_buy_signal_open'] = dataframe.loc[buy_mask, 'open']
dataframe.loc[buy_mask, '_buy_signal_close'] = dataframe.loc[buy_mask, 'close']
if 'sell' in dataframe.columns:
sell_mask = (dataframe['sell'] == 1)
sell_signals = int(sell_mask.sum())
dataframe.loc[sell_mask, '_sell_signal_open'] = dataframe.loc[sell_mask, 'open']
dataframe.loc[sell_mask, '_sell_signal_close'] = dataframe.loc[sell_mask, 'close']
dataframe = dataframe.replace([inf, -inf], NAN)
dataframe = dataframe.replace({NAN: None})

416
freqtrade/rpc/telegram.py
View File

@@ -107,11 +107,12 @@ class Telegram(RPCHandler):
# this needs refactoring of the whole telegram module (same
# problem in _help()).
valid_keys: List[str] = [r'/start$', r'/stop$', r'/status$', r'/status table$',
r'/trades$', r'/performance$', r'/daily$', r'/daily \d+$',
r'/profit$', r'/profit \d+',
r'/trades$', r'/performance$', r'/buys', r'/sells', r'/mix_tags',
r'/daily$', r'/daily \d+$', r'/profit$', r'/profit \d+',
r'/stats$', r'/count$', r'/locks$', r'/balance$',
r'/stopbuy$', r'/reload_config$', r'/show_config$',
r'/logs$', r'/whitelist$', r'/blacklist$', r'/edge$',
r'/weekly$', r'/weekly \d+$', r'/monthly$', r'/monthly \d+$',
r'/forcebuy$', r'/help$', r'/version$']
# Create keys for generation
valid_keys_print = [k.replace('$', '') for k in valid_keys]
@@ -154,8 +155,13 @@ class Telegram(RPCHandler):
CommandHandler('trades', self._trades),
CommandHandler('delete', self._delete_trade),
CommandHandler('performance', self._performance),
CommandHandler('buys', self._buy_tag_performance),
CommandHandler('sells', self._sell_reason_performance),
CommandHandler('mix_tags', self._mix_tag_performance),
CommandHandler('stats', self._stats),
CommandHandler('daily', self._daily),
CommandHandler('weekly', self._weekly),
CommandHandler('monthly', self._monthly),
CommandHandler('count', self._count),
CommandHandler('locks', self._locks),
CommandHandler(['unlock', 'delete_locks'], self._delete_locks),
@@ -172,9 +178,15 @@ class Telegram(RPCHandler):
callbacks = [
CallbackQueryHandler(self._status_table, pattern='update_status_table'),
CallbackQueryHandler(self._daily, pattern='update_daily'),
CallbackQueryHandler(self._weekly, pattern='update_weekly'),
CallbackQueryHandler(self._monthly, pattern='update_monthly'),
CallbackQueryHandler(self._profit, pattern='update_profit'),
CallbackQueryHandler(self._balance, pattern='update_balance'),
CallbackQueryHandler(self._performance, pattern='update_performance'),
CallbackQueryHandler(self._buy_tag_performance, pattern='update_buy_tag_performance'),
CallbackQueryHandler(self._sell_reason_performance,
pattern='update_sell_reason_performance'),
CallbackQueryHandler(self._mix_tag_performance, pattern='update_mix_tag_performance'),
CallbackQueryHandler(self._count, pattern='update_count'),
CallbackQueryHandler(self._forcebuy_inline),
]
@@ -208,26 +220,28 @@ class Telegram(RPCHandler):
msg['stake_amount'], msg['stake_currency'], msg['fiat_currency'])
else:
msg['stake_amount_fiat'] = 0
is_fill = msg['type'] == RPCMessageType.BUY_FILL
emoji = '\N{CHECK MARK}' if is_fill else '\N{LARGE BLUE CIRCLE}'
content = []
content.append(
f"\N{LARGE BLUE CIRCLE} *{msg['exchange']}:* Buying {msg['pair']}"
message = (
f"{emoji} *{msg['exchange']}:* {'Bought' if is_fill else 'Buying'} {msg['pair']}"
f" (#{msg['trade_id']})\n"
)
if msg.get('buy_tag', None):
content.append(f"*Buy Tag:* `{msg['buy_tag']}`\n")
content.append(f"*Amount:* `{msg['amount']:.8f}`\n")
content.append(f"*Open Rate:* `{msg['limit']:.8f}`\n")
content.append(f"*Current Rate:* `{msg['current_rate']:.8f}`\n")
content.append(
f"*Total:* `({round_coin_value(msg['stake_amount'], msg['stake_currency'])}"
)
if msg.get('fiat_currency', None):
content.append(
f", {round_coin_value(msg['stake_amount_fiat'], msg['fiat_currency'])}"
)
message += f"*Buy Tag:* `{msg['buy_tag']}`\n" if msg.get('buy_tag', None) else ""
message += f"*Amount:* `{msg['amount']:.8f}`\n"
if msg['type'] == RPCMessageType.BUY_FILL:
message += f"*Open Rate:* `{msg['open_rate']:.8f}`\n"
elif msg['type'] == RPCMessageType.BUY:
message += f"*Open Rate:* `{msg['limit']:.8f}`\n"\
f"*Current Rate:* `{msg['current_rate']:.8f}`\n"
message += f"*Total:* `({round_coin_value(msg['stake_amount'], msg['stake_currency'])}"
if msg.get('fiat_currency', None):
message += f", {round_coin_value(msg['stake_amount_fiat'], msg['fiat_currency'])}"
message = ''.join(content)
message += ")`"
return message
@@ -238,6 +252,7 @@ class Telegram(RPCHandler):
microsecond=0) - msg['open_date'].replace(microsecond=0)
msg['duration_min'] = msg['duration'].total_seconds() / 60
msg['buy_tag'] = msg['buy_tag'] if "buy_tag" in msg.keys() else None
msg['emoji'] = self._get_sell_emoji(msg)
# Check if all sell properties are available.
@@ -246,53 +261,57 @@ class Telegram(RPCHandler):
and self._rpc._fiat_converter):
msg['profit_fiat'] = self._rpc._fiat_converter.convert_amount(
msg['profit_amount'], msg['stake_currency'], msg['fiat_currency'])
msg['profit_extra'] = (' ({gain}: {profit_amount:.8f} {stake_currency}'
' / {profit_fiat:.3f} {fiat_currency})').format(**msg)
msg['profit_extra'] = (
f" ({msg['gain']}: {msg['profit_amount']:.8f} {msg['stake_currency']}"
f" / {msg['profit_fiat']:.3f} {msg['fiat_currency']})")
else:
msg['profit_extra'] = ''
is_fill = msg['type'] == RPCMessageType.SELL_FILL
message = (
f"{msg['emoji']} *{msg['exchange']}:* "
f"{'Sold' if is_fill else 'Selling'} {msg['pair']} (#{msg['trade_id']})\n"
f"*{'Profit' if is_fill else 'Unrealized Profit'}:* "
f"`{msg['profit_ratio']:.2%}{msg['profit_extra']}`\n"
f"*Buy Tag:* `{msg['buy_tag']}`\n"
f"*Sell Reason:* `{msg['sell_reason']}`\n"
f"*Duration:* `{msg['duration']} ({msg['duration_min']:.1f} min)`\n"
f"*Amount:* `{msg['amount']:.8f}`\n"
f"*Open Rate:* `{msg['open_rate']:.8f}`\n")
message = ("{emoji} *{exchange}:* Selling {pair} (#{trade_id})\n"
"*Profit:* `{profit_percent:.2f}%{profit_extra}`\n"
"*Sell Reason:* `{sell_reason}`\n"
"*Duration:* `{duration} ({duration_min:.1f} min)`\n"
"*Amount:* `{amount:.8f}`\n"
"*Open Rate:* `{open_rate:.8f}`\n"
"*Current Rate:* `{current_rate:.8f}`\n"
"*Close Rate:* `{limit:.8f}`").format(**msg)
if msg['type'] == RPCMessageType.SELL:
message += (f"*Current Rate:* `{msg['current_rate']:.8f}`\n"
f"*Close Rate:* `{msg['limit']:.8f}`")
elif msg['type'] == RPCMessageType.SELL_FILL:
message += f"*Close Rate:* `{msg['close_rate']:.8f}`"
return message
def compose_message(self, msg: Dict[str, Any], msg_type: RPCMessageType) -> str:
if msg_type == RPCMessageType.BUY:
if msg_type in [RPCMessageType.BUY, RPCMessageType.BUY_FILL]:
message = self._format_buy_msg(msg)
elif msg_type in [RPCMessageType.SELL, RPCMessageType.SELL_FILL]:
message = self._format_sell_msg(msg)
elif msg_type in (RPCMessageType.BUY_CANCEL, RPCMessageType.SELL_CANCEL):
msg['message_side'] = 'buy' if msg_type == RPCMessageType.BUY_CANCEL else 'sell'
message = ("\N{WARNING SIGN} *{exchange}:* "
"Cancelling open {message_side} Order for {pair} (#{trade_id}). "
"Reason: {reason}.".format(**msg))
elif msg_type == RPCMessageType.BUY_FILL:
message = ("\N{LARGE CIRCLE} *{exchange}:* "
"Buy order for {pair} (#{trade_id}) filled "
"for {open_rate}.".format(**msg))
elif msg_type == RPCMessageType.SELL_FILL:
message = ("\N{LARGE CIRCLE} *{exchange}:* "
"Sell order for {pair} (#{trade_id}) filled "
"for {close_rate}.".format(**msg))
elif msg_type == RPCMessageType.SELL:
message = self._format_sell_msg(msg)
elif msg_type == RPCMessageType.PROTECTION_TRIGGER:
message = (
"*Protection* triggered due to {reason}. "
"`{pair}` will be locked until `{lock_end_time}`."
).format(**msg)
elif msg_type == RPCMessageType.PROTECTION_TRIGGER_GLOBAL:
message = (
"*Protection* triggered due to {reason}. "
"*All pairs* will be locked until `{lock_end_time}`."
).format(**msg)
elif msg_type == RPCMessageType.STATUS:
message = '*Status:* `{status}`'.format(**msg)
@@ -344,7 +363,7 @@ class Telegram(RPCHandler):
elif float(msg['profit_percent']) >= 0.0:
return "\N{EIGHT SPOKED ASTERISK}"
elif msg['sell_reason'] == "stop_loss":
return"\N{WARNING SIGN}"
return "\N{WARNING SIGN}"
else:
return "\N{CROSS MARK}"
@@ -384,19 +403,19 @@ class Telegram(RPCHandler):
"*Close Rate:* `{close_rate}`" if r['close_rate'] else "",
"*Current Rate:* `{current_rate:.8f}`",
("*Current Profit:* " if r['is_open'] else "*Close Profit: *")
+ "`{profit_pct:.2f}%`",
+ "`{profit_ratio:.2%}`",
]
if (r['stop_loss_abs'] != r['initial_stop_loss_abs']
and r['initial_stop_loss_pct'] is not None):
and r['initial_stop_loss_ratio'] is not None):
# Adding initial stoploss only if it is different from stoploss
lines.append("*Initial Stoploss:* `{initial_stop_loss_abs:.8f}` "
"`({initial_stop_loss_pct:.2f}%)`")
"`({initial_stop_loss_ratio:.2%})`")
# Adding stoploss and stoploss percentage only if it is not None
lines.append("*Stoploss:* `{stop_loss_abs:.8f}` " +
("`({stop_loss_pct:.2f}%)`" if r['stop_loss_pct'] else ""))
("`({stop_loss_ratio:.2%})`" if r['stop_loss_ratio'] else ""))
lines.append("*Stoploss distance:* `{stoploss_current_dist:.8f}` "
"`({stoploss_current_dist_pct:.2f}%)`")
"`({stoploss_current_dist_ratio:.2%})`")
if r['open_order']:
if r['sell_order_status']:
lines.append("*Open Order:* `{open_order}` - `{sell_order_status}`")
@@ -492,6 +511,86 @@ class Telegram(RPCHandler):
except RPCException as e:
self._send_msg(str(e))
@authorized_only
def _weekly(self, update: Update, context: CallbackContext) -> None:
"""
Handler for /weekly <n>
Returns a weekly profit (in BTC) over the last n weeks.
:param bot: telegram bot
:param update: message update
:return: None
"""
stake_cur = self._config['stake_currency']
fiat_disp_cur = self._config.get('fiat_display_currency', '')
try:
timescale = int(context.args[0]) if context.args else 8
except (TypeError, ValueError, IndexError):
timescale = 8
try:
stats = self._rpc._rpc_weekly_profit(
timescale,
stake_cur,
fiat_disp_cur
)
stats_tab = tabulate(
[[week['date'],
f"{round_coin_value(week['abs_profit'], stats['stake_currency'])}",
f"{week['fiat_value']:.3f} {stats['fiat_display_currency']}",
f"{week['trade_count']} trades"] for week in stats['data']],
headers=[
'Monday',
f'Profit {stake_cur}',
f'Profit {fiat_disp_cur}',
'Trades',
],
tablefmt='simple')
message = f'<b>Weekly Profit over the last {timescale} weeks ' \
f'(starting from Monday)</b>:\n<pre>{stats_tab}</pre> '
self._send_msg(message, parse_mode=ParseMode.HTML, reload_able=True,
callback_path="update_weekly", query=update.callback_query)
except RPCException as e:
self._send_msg(str(e))
@authorized_only
def _monthly(self, update: Update, context: CallbackContext) -> None:
"""
Handler for /monthly <n>
Returns a monthly profit (in BTC) over the last n months.
:param bot: telegram bot
:param update: message update
:return: None
"""
stake_cur = self._config['stake_currency']
fiat_disp_cur = self._config.get('fiat_display_currency', '')
try:
timescale = int(context.args[0]) if context.args else 6
except (TypeError, ValueError, IndexError):
timescale = 6
try:
stats = self._rpc._rpc_monthly_profit(
timescale,
stake_cur,
fiat_disp_cur
)
stats_tab = tabulate(
[[month['date'],
f"{round_coin_value(month['abs_profit'], stats['stake_currency'])}",
f"{month['fiat_value']:.3f} {stats['fiat_display_currency']}",
f"{month['trade_count']} trades"] for month in stats['data']],
headers=[
'Month',
f'Profit {stake_cur}',
f'Profit {fiat_disp_cur}',
'Trades',
],
tablefmt='simple')
message = f'<b>Monthly Profit over the last {timescale} months' \
f'</b>:\n<pre>{stats_tab}</pre> '
self._send_msg(message, parse_mode=ParseMode.HTML, reload_able=True,
callback_path="update_monthly", query=update.callback_query)
except RPCException as e:
self._send_msg(str(e))
@authorized_only
def _profit(self, update: Update, context: CallbackContext) -> None:
"""
@@ -519,11 +618,11 @@ class Telegram(RPCHandler):
fiat_disp_cur,
start_date)
profit_closed_coin = stats['profit_closed_coin']
profit_closed_percent_mean = stats['profit_closed_percent_mean']
profit_closed_ratio_mean = stats['profit_closed_ratio_mean']
profit_closed_percent = stats['profit_closed_percent']
profit_closed_fiat = stats['profit_closed_fiat']
profit_all_coin = stats['profit_all_coin']
profit_all_percent_mean = stats['profit_all_percent_mean']
profit_all_ratio_mean = stats['profit_all_ratio_mean']
profit_all_percent = stats['profit_all_percent']
profit_all_fiat = stats['profit_all_fiat']
trade_count = stats['trade_count']
@@ -531,7 +630,7 @@ class Telegram(RPCHandler):
latest_trade_date = stats['latest_trade_date']
avg_duration = stats['avg_duration']
best_pair = stats['best_pair']
best_rate = stats['best_rate']
best_pair_profit_ratio = stats['best_pair_profit_ratio']
if stats['trade_count'] == 0:
markdown_msg = 'No trades yet.'
else:
@@ -539,7 +638,7 @@ class Telegram(RPCHandler):
if stats['closed_trade_count'] > 0:
markdown_msg = ("*ROI:* Closed trades\n"
f"∙ `{round_coin_value(profit_closed_coin, stake_cur)} "
f"({profit_closed_percent_mean:.2f}%) "
f"({profit_closed_ratio_mean:.2%}) "
f"({profit_closed_percent} \N{GREEK CAPITAL LETTER SIGMA}%)`\n"
f"∙ `{round_coin_value(profit_closed_fiat, fiat_disp_cur)}`\n")
else:
@@ -548,7 +647,7 @@ class Telegram(RPCHandler):
markdown_msg += (
f"*ROI:* All trades\n"
f"∙ `{round_coin_value(profit_all_coin, stake_cur)} "
f"({profit_all_percent_mean:.2f}%) "
f"({profit_all_ratio_mean:.2%}) "
f"({profit_all_percent} \N{GREEK CAPITAL LETTER SIGMA}%)`\n"
f"∙ `{round_coin_value(profit_all_fiat, fiat_disp_cur)}`\n"
f"*Total Trade Count:* `{trade_count}`\n"
@@ -559,7 +658,7 @@ class Telegram(RPCHandler):
)
if stats['closed_trade_count'] > 0:
markdown_msg += (f"\n*Avg. Duration:* `{avg_duration}`\n"
f"*Best Performing:* `{best_pair}: {best_rate:.2f}%`")
f"*Best Performing:* `{best_pair}: {best_pair_profit_ratio:.2%}`")
self._send_msg(markdown_msg, reload_able=True, callback_path="update_profit",
query=update.callback_query)
@@ -588,10 +687,16 @@ class Telegram(RPCHandler):
count['losses']
] for reason, count in stats['sell_reasons'].items()
]
sell_reasons_msg = tabulate(
sell_reasons_tabulate,
headers=['Sell Reason', 'Sells', 'Wins', 'Losses']
)
sell_reasons_msg = 'No trades yet.'
for reason in chunks(sell_reasons_tabulate, 25):
sell_reasons_msg = tabulate(
reason,
headers=['Sell Reason', 'Sells', 'Wins', 'Losses']
)
if len(sell_reasons_tabulate) > 25:
self._send_msg(sell_reasons_msg, ParseMode.MARKDOWN)
sell_reasons_msg = ''
durations = stats['durations']
duration_msg = tabulate(
[
@@ -662,10 +767,10 @@ class Telegram(RPCHandler):
output += ("\n*Estimated Value*:\n"
f"\t`{result['stake']}: "
f"{round_coin_value(result['total'], result['stake'], False)}`"
f" `({result['starting_capital_pct']}%)`\n"
f" `({result['starting_capital_ratio']:.2%})`\n"
f"\t`{result['symbol']}: "
f"{round_coin_value(result['value'], result['symbol'], False)}`"
f" `({result['starting_capital_fiat_pct']}%)`\n")
f" `({result['starting_capital_fiat_ratio']:.2%})`\n")
self._send_msg(output, reload_able=True, callback_path="update_balance",
query=update.callback_query)
except RPCException as e:
@@ -800,7 +905,7 @@ class Telegram(RPCHandler):
trades_tab = tabulate(
[[arrow.get(trade['close_date']).humanize(),
trade['pair'] + " (#" + str(trade['trade_id']) + ")",
f"{(100 * trade['close_profit']):.2f}% ({trade['close_profit_abs']})"]
f"{(trade['close_profit']):.2%} ({trade['close_profit_abs']})"]
for trade in trades['trades']],
headers=[
'Close Date',
@@ -852,7 +957,7 @@ class Telegram(RPCHandler):
stat_line = (
f"{i+1}.\t <code>{trade['pair']}\t"
f"{round_coin_value(trade['profit_abs'], self._config['stake_currency'])} "
f"({trade['profit']:.2f}%) "
f"({trade['profit_ratio']:.2%}) "
f"({trade['count']})</code>\n")
if len(output + stat_line) >= MAX_TELEGRAM_MESSAGE_LENGTH:
@@ -867,6 +972,111 @@ class Telegram(RPCHandler):
except RPCException as e:
self._send_msg(str(e))
@authorized_only
def _buy_tag_performance(self, update: Update, context: CallbackContext) -> None:
"""
Handler for /buys PAIR .
Shows a performance statistic from finished trades
:param bot: telegram bot
:param update: message update
:return: None
"""
try:
pair = None
if context.args and isinstance(context.args[0], str):
pair = context.args[0]
trades = self._rpc._rpc_buy_tag_performance(pair)
output = "<b>Buy Tag Performance:</b>\n"
for i, trade in enumerate(trades):
stat_line = (
f"{i+1}.\t <code>{trade['buy_tag']}\t"
f"{round_coin_value(trade['profit_abs'], self._config['stake_currency'])} "
f"({trade['profit_ratio']:.2%}) "
f"({trade['count']})</code>\n")
if len(output + stat_line) >= MAX_TELEGRAM_MESSAGE_LENGTH:
self._send_msg(output, parse_mode=ParseMode.HTML)
output = stat_line
else:
output += stat_line
self._send_msg(output, parse_mode=ParseMode.HTML,
reload_able=True, callback_path="update_buy_tag_performance",
query=update.callback_query)
except RPCException as e:
self._send_msg(str(e))
@authorized_only
def _sell_reason_performance(self, update: Update, context: CallbackContext) -> None:
"""
Handler for /sells.
Shows a performance statistic from finished trades
:param bot: telegram bot
:param update: message update
:return: None
"""
try:
pair = None
if context.args and isinstance(context.args[0], str):
pair = context.args[0]
trades = self._rpc._rpc_sell_reason_performance(pair)
output = "<b>Sell Reason Performance:</b>\n"
for i, trade in enumerate(trades):
stat_line = (
f"{i+1}.\t <code>{trade['sell_reason']}\t"
f"{round_coin_value(trade['profit_abs'], self._config['stake_currency'])} "
f"({trade['profit_ratio']:.2%}) "
f"({trade['count']})</code>\n")
if len(output + stat_line) >= MAX_TELEGRAM_MESSAGE_LENGTH:
self._send_msg(output, parse_mode=ParseMode.HTML)
output = stat_line
else:
output += stat_line
self._send_msg(output, parse_mode=ParseMode.HTML,
reload_able=True, callback_path="update_sell_reason_performance",
query=update.callback_query)
except RPCException as e:
self._send_msg(str(e))
@authorized_only
def _mix_tag_performance(self, update: Update, context: CallbackContext) -> None:
"""
Handler for /mix_tags.
Shows a performance statistic from finished trades
:param bot: telegram bot
:param update: message update
:return: None
"""
try:
pair = None
if context.args and isinstance(context.args[0], str):
pair = context.args[0]
trades = self._rpc._rpc_mix_tag_performance(pair)
output = "<b>Mix Tag Performance:</b>\n"
for i, trade in enumerate(trades):
stat_line = (
f"{i+1}.\t <code>{trade['mix_tag']}\t"
f"{round_coin_value(trade['profit_abs'], self._config['stake_currency'])} "
f"({trade['profit']:.2%}) "
f"({trade['count']})</code>\n")
if len(output + stat_line) >= MAX_TELEGRAM_MESSAGE_LENGTH:
self._send_msg(output, parse_mode=ParseMode.HTML)
output = stat_line
else:
output += stat_line
self._send_msg(output, parse_mode=ParseMode.HTML,
reload_able=True, callback_path="update_mix_tag_performance",
query=update.callback_query)
except RPCException as e:
self._send_msg(str(e))
@authorized_only
def _count(self, update: Update, context: CallbackContext) -> None:
"""
@@ -1033,42 +1243,58 @@ class Telegram(RPCHandler):
:return: None
"""
forcebuy_text = ("*/forcebuy <pair> [<rate>]:* `Instantly buys the given pair. "
"Optionally takes a rate at which to buy.` \n")
message = ("*/start:* `Starts the trader`\n"
"*/stop:* `Stops the trader`\n"
"*/status <trade_id>|[table]:* `Lists all open trades`\n"
" *<trade_id> :* `Lists one or more specific trades.`\n"
" `Separate multiple <trade_id> with a blank space.`\n"
" *table :* `will display trades in a table`\n"
" `pending buy orders are marked with an asterisk (*)`\n"
" `pending sell orders are marked with a double asterisk (**)`\n"
"*/trades [limit]:* `Lists last closed trades (limited to 10 by default)`\n"
"*/profit [<n>]:* `Lists cumulative profit from all finished trades, "
"over the last n days`\n"
"*/forcesell <trade_id>|all:* `Instantly sells the given trade or all trades, "
"regardless of profit`\n"
f"{forcebuy_text if self._config.get('forcebuy_enable', False) else ''}"
"*/delete <trade_id>:* `Instantly delete the given trade in the database`\n"
"*/performance:* `Show performance of each finished trade grouped by pair`\n"
"*/daily <n>:* `Shows profit or loss per day, over the last n days`\n"
"*/stats:* `Shows Wins / losses by Sell reason as well as "
"Avg. holding durationsfor buys and sells.`\n"
"*/count:* `Show number of active trades compared to allowed number of trades`\n"
"*/locks:* `Show currently locked pairs`\n"
"*/unlock <pair|id>:* `Unlock this Pair (or this lock id if it's numeric)`\n"
"*/balance:* `Show account balance per currency`\n"
"*/stopbuy:* `Stops buying, but handles open trades gracefully` \n"
"*/reload_config:* `Reload configuration file` \n"
"*/show_config:* `Show running configuration` \n"
"*/logs [limit]:* `Show latest logs - defaults to 10` \n"
"*/whitelist:* `Show current whitelist` \n"
"*/blacklist [pair]:* `Show current blacklist, or adds one or more pairs "
"to the blacklist.` \n"
"*/edge:* `Shows validated pairs by Edge if it is enabled` \n"
"*/help:* `This help message`\n"
"*/version:* `Show version`")
"Optionally takes a rate at which to buy "
"(only applies to limit orders).` \n")
message = (
"_BotControl_\n"
"------------\n"
"*/start:* `Starts the trader`\n"
"*/stop:* Stops the trader\n"
"*/stopbuy:* `Stops buying, but handles open trades gracefully` \n"
"*/forcesell <trade_id>|all:* `Instantly sells the given trade or all trades, "
"regardless of profit`\n"
f"{forcebuy_text if self._config.get('forcebuy_enable', False) else ''}"
"*/delete <trade_id>:* `Instantly delete the given trade in the database`\n"
"*/whitelist:* `Show current whitelist` \n"
"*/blacklist [pair]:* `Show current blacklist, or adds one or more pairs "
"to the blacklist.` \n"
"*/reload_config:* `Reload configuration file` \n"
"*/unlock <pair|id>:* `Unlock this Pair (or this lock id if it's numeric)`\n"
self._send_msg(message)
"_Current state_\n"
"------------\n"
"*/show_config:* `Show running configuration` \n"
"*/locks:* `Show currently locked pairs`\n"
"*/balance:* `Show account balance per currency`\n"
"*/logs [limit]:* `Show latest logs - defaults to 10` \n"
"*/count:* `Show number of active trades compared to allowed number of trades`\n"
"*/edge:* `Shows validated pairs by Edge if it is enabled` \n"
"_Statistics_\n"
"------------\n"
"*/status <trade_id>|[table]:* `Lists all open trades`\n"
" *<trade_id> :* `Lists one or more specific trades.`\n"
" `Separate multiple <trade_id> with a blank space.`\n"
" *table :* `will display trades in a table`\n"
" `pending buy orders are marked with an asterisk (*)`\n"
" `pending sell orders are marked with a double asterisk (**)`\n"
"*/buys <pair|none>:* `Shows the buy_tag performance`\n"
"*/sells <pair|none>:* `Shows the sell reason performance`\n"
"*/mix_tags <pair|none>:* `Shows combined buy tag + sell reason performance`\n"
"*/trades [limit]:* `Lists last closed trades (limited to 10 by default)`\n"
"*/profit [<n>]:* `Lists cumulative profit from all finished trades, "
"over the last n days`\n"
"*/performance:* `Show performance of each finished trade grouped by pair`\n"
"*/daily <n>:* `Shows profit or loss per day, over the last n days`\n"
"*/weekly <n>:* `Shows statistics per week, over the last n weeks`\n"
"*/monthly <n>:* `Shows statistics per month, over the last n months`\n"
"*/stats:* `Shows Wins / losses by Sell reason as well as "
"Avg. holding durationsfor buys and sells.`\n"
"*/help:* `This help message`\n"
"*/version:* `Show version`"
)
self._send_msg(message, parse_mode=ParseMode.MARKDOWN)
@authorized_only
def _version(self, update: Update, context: CallbackContext) -> None:

43
freqtrade/rpc/webhook.py
View File

@@ -2,6 +2,7 @@
This module manages webhook communication
"""
import logging
import time
from typing import Any, Dict
from requests import RequestException, post
@@ -28,12 +29,9 @@ class Webhook(RPCHandler):
super().__init__(rpc, config)
self._url = self._config['webhook']['url']
self._format = self._config['webhook'].get('format', 'form')
if self._format != 'form' and self._format != 'json':
raise NotImplementedError('Unknown webhook format `{}`, possible values are '
'`form` (default) and `json`'.format(self._format))
self._retries = self._config['webhook'].get('retries', 0)
self._retry_delay = self._config['webhook'].get('retry_delay', 0.1)
def cleanup(self) -> None:
"""
@@ -77,13 +75,30 @@ class Webhook(RPCHandler):
def _send_msg(self, payload: dict) -> None:
"""do the actual call to the webhook"""
try:
if self._format == 'form':
post(self._url, data=payload)
elif self._format == 'json':
post(self._url, json=payload)
else:
raise NotImplementedError('Unknown format: {}'.format(self._format))
success = False
attempts = 0
while not success and attempts <= self._retries:
if attempts:
if self._retry_delay:
time.sleep(self._retry_delay)
logger.info("Retrying webhook...")
except RequestException as exc:
logger.warning("Could not call webhook url. Exception: %s", exc)
attempts += 1
try:
if self._format == 'form':
response = post(self._url, data=payload)
elif self._format == 'json':
response = post(self._url, json=payload)
elif self._format == 'raw':
response = post(self._url, data=payload['data'],
headers={'Content-Type': 'text/plain'})
else:
raise NotImplementedError('Unknown format: {}'.format(self._format))
# Throw a RequestException if the post was not successful
response.raise_for_status()
success = True
except RequestException as exc:
logger.warning("Could not call webhook url. Exception: %s", exc)

5
freqtrade/strategy/hyper.py
View File

@@ -292,7 +292,7 @@ class BooleanParameter(CategoricalParameter):
load=load, **kwargs)
class HyperStrategyMixin(object):
class HyperStrategyMixin:
"""
A helper base class which allows HyperOptAuto class to reuse implementations of buy/sell
strategy logic.
@@ -381,7 +381,8 @@ class HyperStrategyMixin(object):
if filename.is_file():
logger.info(f"Loading parameters from file {filename}")
try:
params = json_load(filename.open('r'))
with filename.open('r') as f:
params = json_load(f)
if params.get('strategy_name') != self.__class__.__name__:
raise OperationalException('Invalid parameter file provided.')
return params

11
freqtrade/strategy/informative_decorator.py
View File

@@ -80,12 +80,11 @@ def _create_and_merge_informative_pair(strategy, dataframe: DataFrame, metadata:
# Not specifying an asset will define informative dataframe for current pair.
asset = metadata['pair']
if '/' in asset:
base, quote = asset.split('/')
else:
# When futures are supported this may need reevaluation.
# base, quote = asset, ''
raise OperationalException('Not implemented.')
market = strategy.dp.market(asset)
if market is None:
raise OperationalException(f'Market {asset} is not available.')
base = market['base']
quote = market['quote']
# Default format. This optimizes for the common case: informative pairs using same stake
# currency. When quote currency matches stake currency, column name will omit base currency.

29
freqtrade/strategy/interface.py
View File

@@ -30,7 +30,7 @@ logger = logging.getLogger(__name__)
CUSTOM_SELL_MAX_LENGTH = 64
class SellCheckTuple(object):
class SellCheckTuple:
"""
NamedTuple for Sell type + reason
"""
@@ -65,9 +65,9 @@ class IStrategy(ABC, HyperStrategyMixin):
_populate_fun_len: int = 0
_buy_fun_len: int = 0
_sell_fun_len: int = 0
_ft_params_from_file: Dict = {}
_ft_params_from_file: Dict
# associated minimal roi
minimal_roi: Dict
minimal_roi: Dict = {}
# associated stoploss
stoploss: float
@@ -443,6 +443,15 @@ class IStrategy(ABC, HyperStrategyMixin):
"""
PairLocks.unlock_pair(pair, datetime.now(timezone.utc))
def unlock_reason(self, reason: str) -> None:
"""
Unlocks all pairs previously locked using lock_pair with specified reason.
Not used by freqtrade itself, but intended to be used if users lock pairs
manually from within the strategy, to allow an easy way to unlock pairs.
:param reason: Unlock pairs to allow trading again
"""
PairLocks.unlock_reason(reason, datetime.now(timezone.utc))
def is_pair_locked(self, pair: str, candle_date: datetime = None) -> bool:
"""
Checks if a pair is currently locked
@@ -500,6 +509,7 @@ class IStrategy(ABC, HyperStrategyMixin):
dataframe['buy'] = 0
dataframe['sell'] = 0
dataframe['buy_tag'] = None
dataframe['exit_tag'] = None
# Other Defs in strategy that want to be called every loop here
# twitter_sell = self.watch_twitter_feed(dataframe, metadata)
@@ -577,7 +587,7 @@ class IStrategy(ABC, HyperStrategyMixin):
pair: str,
timeframe: str,
dataframe: DataFrame
) -> Tuple[bool, bool, Optional[str]]:
) -> Tuple[bool, bool, Optional[str], Optional[str]]:
"""
Calculates current signal based based on the buy / sell columns of the dataframe.
Used by Bot to get the signal to buy or sell
@@ -588,7 +598,7 @@ class IStrategy(ABC, HyperStrategyMixin):
"""
if not isinstance(dataframe, DataFrame) or dataframe.empty:
logger.warning(f'Empty candle (OHLCV) data for pair {pair}')
return False, False, None
return False, False, None, None
latest_date = dataframe['date'].max()
latest = dataframe.loc[dataframe['date'] == latest_date].iloc[-1]
@@ -603,7 +613,7 @@ class IStrategy(ABC, HyperStrategyMixin):
'Outdated history for pair %s. Last tick is %s minutes old',
pair, int((arrow.utcnow() - latest_date).total_seconds() // 60)
)
return False, False, None
return False, False, None, None
buy = latest[SignalType.BUY.value] == 1
@@ -612,6 +622,7 @@ class IStrategy(ABC, HyperStrategyMixin):
sell = latest[SignalType.SELL.value] == 1
buy_tag = latest.get(SignalTagType.BUY_TAG.value, None)
exit_tag = latest.get(SignalTagType.EXIT_TAG.value, None)
logger.debug('trigger: %s (pair=%s) buy=%s sell=%s',
latest['date'], pair, str(buy), str(sell))
@@ -620,8 +631,8 @@ class IStrategy(ABC, HyperStrategyMixin):
current_time=datetime.now(timezone.utc),
timeframe_seconds=timeframe_seconds,
buy=buy):
return False, sell, buy_tag
return buy, sell, buy_tag
return False, sell, buy_tag, exit_tag
return buy, sell, buy_tag, exit_tag
def ignore_expired_candle(self, latest_date: datetime, current_time: datetime,
timeframe_seconds: int, buy: bool):
@@ -754,7 +765,7 @@ class IStrategy(ABC, HyperStrategyMixin):
if self.trailing_stop_positive is not None and high_profit > sl_offset:
stop_loss_value = self.trailing_stop_positive
logger.debug(f"{trade.pair} - Using positive stoploss: {stop_loss_value} "
f"offset: {sl_offset:.4g} profit: {current_profit:.4f}%")
f"offset: {sl_offset:.4g} profit: {current_profit:.2%}")
trade.adjust_stop_loss(high or current_rate, stop_loss_value)

4
freqtrade/strategy/strategy_wrapper.py
View File

@@ -1,4 +1,5 @@
import logging
from copy import deepcopy
from freqtrade.exceptions import StrategyError
@@ -14,6 +15,9 @@ def strategy_safe_wrapper(f, message: str = "", default_retval=None, supress_err
"""
def wrapper(*args, **kwargs):
try:
if 'trade' in kwargs:
# Protect accidental modifications from within the strategy
kwargs['trade'] = deepcopy(kwargs['trade'])
return f(*args, **kwargs)
except ValueError as error:
logger.warning(

3
freqtrade/templates/base_config.json.j2
View File

@@ -10,8 +10,7 @@
"stake_currency": "{{ stake_currency }}",
"stake_amount": {{ stake_amount }},
"tradable_balance_ratio": 0.99,
"fiat_display_currency": "{{ fiat_display_currency }}",
"timeframe": "{{ timeframe }}",
"fiat_display_currency": "{{ fiat_display_currency }}",{{ ('\n "timeframe": "' + timeframe + '",') if timeframe else '' }}
"dry_run": {{ dry_run | lower }},
"cancel_open_orders_on_exit": false,
"unfilledtimeout": {

12
freqtrade/templates/base_strategy.py.j2
View File

@@ -12,6 +12,7 @@ from freqtrade.strategy import (BooleanParameter, CategoricalParameter, DecimalP
# --------------------------------
# Add your lib to import here
import talib.abstract as ta
import pandas_ta as pta
import freqtrade.vendor.qtpylib.indicators as qtpylib
@@ -36,6 +37,9 @@ class {{ strategy }}(IStrategy):
# Check the documentation or the Sample strategy to get the latest version.
INTERFACE_VERSION = 2
# Optimal timeframe for the strategy.
timeframe = '5m'
# Minimal ROI designed for the strategy.
# This attribute will be overridden if the config file contains "minimal_roi".
minimal_roi = {
@@ -54,9 +58,6 @@ class {{ strategy }}(IStrategy):
# trailing_stop_positive = 0.01
# trailing_stop_positive_offset = 0.0 # Disabled / not configured
# Optimal timeframe for the strategy.
timeframe = '5m'
# Run "populate_indicators()" only for new candle.
process_only_new_candles = False
@@ -68,6 +69,10 @@ class {{ strategy }}(IStrategy):
# Number of candles the strategy requires before producing valid signals
startup_candle_count: int = 30
# Strategy parameters
buy_rsi = IntParameter(10, 40, default=30, space="buy")
sell_rsi = IntParameter(60, 90, default=70, space="sell")
# Optional order type mapping.
order_types = {
'buy': 'limit',
@@ -82,6 +87,7 @@ class {{ strategy }}(IStrategy):
'sell': 'gtc'
}
{{ plot_config | indent(4) }}
def informative_pairs(self):
"""
Define additional, informative pair/interval combinations to be cached from the exchange.

2
freqtrade/templates/strategy_analysis_example.ipynb
View File

@@ -79,7 +79,9 @@
"source": [
"# Load strategy using values set above\n",
"from freqtrade.resolvers import StrategyResolver\n",
"from freqtrade.data.dataprovider import DataProvider\n",
"strategy = StrategyResolver.load_strategy(config)\n",
"strategy.dp = DataProvider(config, None, None)\n",
"\n",
"# Generate buy/sell signals using strategy\n",
"df = strategy.analyze_ticker(candles, {'pair': pair})\n",

2
freqtrade/templates/subtemplates/buy_trend_full.j2
View File

@@ -1,3 +1,3 @@
(qtpylib.crossed_above(dataframe['rsi'], 30)) & # Signal: RSI crosses above 30
(qtpylib.crossed_above(dataframe['rsi'], self.buy_rsi.value)) & # Signal: RSI crosses above buy_rsi
(dataframe['tema'] <= dataframe['bb_middleband']) & # Guard: tema below BB middle
(dataframe['tema'] > dataframe['tema'].shift(1)) & # Guard: tema is raising

2
freqtrade/templates/subtemplates/buy_trend_minimal.j2
View File

@@ -1 +1 @@
(qtpylib.crossed_above(dataframe['rsi'], 30)) & # Signal: RSI crosses above 30
(qtpylib.crossed_above(dataframe['rsi'], self.buy_rsi.value)) & # Signal: RSI crosses above buy_rsi

12
freqtrade/templates/subtemplates/exchange_okex.j2 Normal file
View File

@@ -0,0 +1,12 @@
"exchange": {
"name": "{{ exchange_name | lower }}",
"key": "{{ exchange_key }}",
"secret": "{{ exchange_secret }}",
"password": "{{ exchange_key_password }}",
"ccxt_config": {},
"ccxt_async_config": {},
"pair_whitelist": [
],
"pair_blacklist": [
]
}

30
freqtrade/templates/subtemplates/plot_config_full.j2
View File

@@ -1,18 +1,20 @@
plot_config = {
# Main plot indicators (Moving averages, ...)
'main_plot': {
'tema': {},
'sar': {'color': 'white'},
},
'subplots': {
# Subplots - each dict defines one additional plot
"MACD": {
'macd': {'color': 'blue'},
'macdsignal': {'color': 'orange'},
@property
def plot_config(self):
return {
# Main plot indicators (Moving averages, ...)
'main_plot': {
'tema': {},
'sar': {'color': 'white'},
},
"RSI": {
'rsi': {'color': 'red'},
'subplots': {
# Subplots - each dict defines one additional plot
"MACD": {
'macd': {'color': 'blue'},
'macdsignal': {'color': 'orange'},
},
"RSI": {
'rsi': {'color': 'red'},
}
}
}
}

2
freqtrade/templates/subtemplates/sell_trend_full.j2
View File

@@ -1,3 +1,3 @@
(qtpylib.crossed_above(dataframe['rsi'], 70)) & # Signal: RSI crosses above 70
(qtpylib.crossed_above(dataframe['rsi'], self.sell_rsi.value)) & # Signal: RSI crosses above sell_rsi
(dataframe['tema'] > dataframe['bb_middleband']) & # Guard: tema above BB middle
(dataframe['tema'] < dataframe['tema'].shift(1)) & # Guard: tema is falling

2
freqtrade/templates/subtemplates/sell_trend_minimal.j2
View File

@@ -1 +1 @@
(qtpylib.crossed_above(dataframe['rsi'], 70)) & # Signal: RSI crosses above 70
(qtpylib.crossed_above(dataframe['rsi'], self.sell_rsi.value)) & # Signal: RSI crosses above sell_rsi

18
freqtrade/wallets.py
View File

@@ -73,7 +73,7 @@ class Wallets:
tot_profit = Trade.get_total_closed_profit()
else:
tot_profit = LocalTrade.total_profit
tot_in_trades = sum([trade.stake_amount for trade in open_trades])
tot_in_trades = sum(trade.stake_amount for trade in open_trades)
current_stake = self.start_cap + tot_profit - tot_in_trades
_wallets[self._config['stake_currency']] = Wallet(
@@ -238,7 +238,7 @@ class Wallets:
return self._check_available_stake_amount(stake_amount, available_amount)
def _validate_stake_amount(self, pair, stake_amount, min_stake_amount):
def validate_stake_amount(self, pair, stake_amount, min_stake_amount):
if not stake_amount:
logger.debug(f"Stake amount is {stake_amount}, ignoring possible trade for {pair}.")
return 0
@@ -250,17 +250,27 @@ class Wallets:
logger.warning("Minimum stake amount > available balance.")
return 0
if min_stake_amount is not None and stake_amount < min_stake_amount:
stake_amount = min_stake_amount
if self._log:
logger.info(
f"Stake amount for pair {pair} is too small "
f"({stake_amount} < {min_stake_amount}), adjusting to {min_stake_amount}."
)
if stake_amount * 1.3 < min_stake_amount:
# Top-cap stake-amount adjustments to +30%.
if self._log:
logger.info(
f"Adjusted stake amount for pair {pair} is more than 30% bigger than "
f"the desired stake ({stake_amount} * 1.3 > {max_stake_amount}), "
f"ignoring trade."
)
return 0
stake_amount = min_stake_amount
if stake_amount > max_stake_amount:
stake_amount = max_stake_amount
if self._log:
logger.info(
f"Stake amount for pair {pair} is too big "
f"({stake_amount} > {max_stake_amount}), adjusting to {max_stake_amount}."
)
stake_amount = max_stake_amount
return stake_amount