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Merge branch 'develop' into data_handler

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This commit is contained in:
Matthias
2020-01-21 06:58:48 +01:00
parent 41945138ac 66415d48d4
commit fc2970f41b
50 changed files with 1140 additions and 506 deletions
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6
freqtrade/configuration/cli_options.py
View File

@@ -387,15 +387,13 @@ AVAILABLE_CLI_OPTIONS = {
"indicators1": Arg(
'--indicators1',
help='Set indicators from your strategy you want in the first row of the graph. '
'Space-separated list. Example: `ema3 ema5`. Default: `%(default)s`.',
default=['sma', 'ema3', 'ema5'],
"Space-separated list. Example: `ema3 ema5`. Default: `['sma', 'ema3', 'ema5']`.",
nargs='+',
),
"indicators2": Arg(
'--indicators2',
help='Set indicators from your strategy you want in the third row of the graph. '
'Space-separated list. Example: `fastd fastk`. Default: `%(default)s`.',
default=['macd', 'macdsignal'],
"Space-separated list. Example: `fastd fastk`. Default: `['macd', 'macdsignal']`.",
nargs='+',
),
"plot_limit": Arg(

17
freqtrade/configuration/config_validation.py
View File

@@ -48,11 +48,6 @@ def validate_config_schema(conf: Dict[str, Any]) -> Dict[str, Any]:
conf_schema['required'] = constants.SCHEMA_TRADE_REQUIRED
else:
conf_schema['required'] = constants.SCHEMA_MINIMAL_REQUIRED
# Dynamically allow empty stake-currency
# Since the minimal config specifies this too.
# It's not allowed for Dry-run or live modes
conf_schema['properties']['stake_currency']['enum'] += [''] # type: ignore
try:
FreqtradeValidator(conf_schema).validate(conf)
return conf
@@ -78,12 +73,24 @@ def validate_config_consistency(conf: Dict[str, Any]) -> None:
_validate_trailing_stoploss(conf)
_validate_edge(conf)
_validate_whitelist(conf)
_validate_unlimited_amount(conf)
# validate configuration before returning
logger.info('Validating configuration ...')
validate_config_schema(conf)
def _validate_unlimited_amount(conf: Dict[str, Any]) -> None:
"""
If edge is disabled, either max_open_trades or stake_amount need to be set.
:raise: OperationalException if config validation failed
"""
if (not conf.get('edge', {}).get('enabled')
and conf.get('max_open_trades') == float('inf')
and conf.get('stake_amount') == constants.UNLIMITED_STAKE_AMOUNT):
raise OperationalException("`max_open_trades` and `stake_amount` cannot both be unlimited.")
def _validate_trailing_stoploss(conf: Dict[str, Any]) -> None:
if conf.get('stoploss') == 0.0:

10
freqtrade/configuration/deprecated_settings.py
View File

@@ -80,3 +80,13 @@ def process_temporary_deprecated_settings(config: Dict[str, Any]) -> None:
f"Using precision_filter setting is deprecated and has been replaced by"
"PrecisionFilter. Please refer to the docs on configuration details")
config['pairlists'].append({'method': 'PrecisionFilter'})
if (config.get('edge', {}).get('enabled', False)
and 'capital_available_percentage' in config.get('edge', {})):
logger.warning(
"DEPRECATED: "
"Using 'edge.capital_available_percentage' has been deprecated in favor of "
"'tradable_balance_ratio'. Please migrate your configuration to "
"'tradable_balance_ratio' and remove 'capital_available_percentage' "
"from the edge configuration."
)

24
freqtrade/constants.py
View File

@@ -35,12 +35,6 @@ USER_DATA_FILES = {
'strategy_analysis_example.ipynb': 'notebooks',
}
TIMEFRAMES = [
'1m', '3m', '5m', '15m', '30m',
'1h', '2h', '4h', '6h', '8h', '12h',
'1d', '3d', '1w',
]
SUPPORTED_FIAT = [
"AUD", "BRL", "CAD", "CHF", "CLP", "CNY", "CZK", "DKK",
"EUR", "GBP", "HKD", "HUF", "IDR", "ILS", "INR", "JPY",
@@ -68,13 +62,23 @@ CONF_SCHEMA = {
'type': 'object',
'properties': {
'max_open_trades': {'type': ['integer', 'number'], 'minimum': -1},
'ticker_interval': {'type': 'string', 'enum': TIMEFRAMES},
'stake_currency': {'type': 'string', 'enum': ['BTC', 'XBT', 'ETH', 'USDT', 'EUR', 'USD']},
'ticker_interval': {'type': 'string'},
'stake_currency': {'type': 'string'},
'stake_amount': {
'type': ['number', 'string'],
'minimum': 0.0001,
'pattern': UNLIMITED_STAKE_AMOUNT
},
'tradable_balance_ratio': {
'type': 'number',
'minimum': 0.1,
'maximum': 1,
'default': 0.99
},
'amend_last_stake_amount': {'type': 'boolean', 'default': False},
'last_stake_amount_min_ratio': {
'type': 'number', 'minimum': 0.0, 'maximum': 1.0, 'default': 0.5
},
'fiat_display_currency': {'type': 'string', 'enum': SUPPORTED_FIAT},
'dry_run': {'type': 'boolean'},
'dry_run_wallet': {'type': 'number', 'default': DRY_RUN_WALLET},
@@ -279,7 +283,7 @@ CONF_SCHEMA = {
'max_trade_duration_minute': {'type': 'integer'},
'remove_pumps': {'type': 'boolean'}
},
'required': ['process_throttle_secs', 'allowed_risk', 'capital_available_percentage']
'required': ['process_throttle_secs', 'allowed_risk']
}
},
}
@@ -289,6 +293,8 @@ SCHEMA_TRADE_REQUIRED = [
'max_open_trades',
'stake_currency',
'stake_amount',
'tradable_balance_ratio',
'last_stake_amount_min_ratio',
'dry_run',
'dry_run_wallet',
'bid_strategy',

4
freqtrade/edge/__init__.py
View File

@@ -57,7 +57,9 @@ class Edge:
if self.config['stake_amount'] != constants.UNLIMITED_STAKE_AMOUNT:
raise OperationalException('Edge works only with unlimited stake amount')
self._capital_percentage: float = self.edge_config.get('capital_available_percentage')
# Deprecated capital_available_percentage. Will use tradable_balance_ratio in the future.
self._capital_percentage: float = self.edge_config.get(
'capital_available_percentage', self.config['tradable_balance_ratio'])
self._allowed_risk: float = self.edge_config.get('allowed_risk')
self._since_number_of_days: int = self.edge_config.get('calculate_since_number_of_days', 14)
self._last_updated: int = 0 # Timestamp of pairs last updated time

6
freqtrade/exchange/binance.py
View File

@@ -41,7 +41,7 @@ class Binance(Exchange):
"""
ordertype = "stop_loss_limit"
stop_price = self.symbol_price_prec(pair, stop_price)
stop_price = self.price_to_precision(pair, stop_price)
# Ensure rate is less than stop price
if stop_price <= rate:
@@ -57,9 +57,9 @@ class Binance(Exchange):
params = self._params.copy()
params.update({'stopPrice': stop_price})
amount = self.symbol_amount_prec(pair, amount)
amount = self.amount_to_precision(pair, amount)
rate = self.symbol_price_prec(pair, rate)
rate = self.price_to_precision(pair, rate)
order = self._api.create_order(pair, ordertype, 'sell',
amount, rate, params)

81
freqtrade/exchange/exchange.py
View File

@@ -7,14 +7,15 @@ import inspect
import logging
from copy import deepcopy
from datetime import datetime, timezone
from math import ceil, floor
from math import ceil
from random import randint
from typing import Any, Dict, List, Optional, Tuple
import arrow
import ccxt
import ccxt.async_support as ccxt_async
from ccxt.base.decimal_to_precision import ROUND_DOWN, ROUND_UP
from ccxt.base.decimal_to_precision import (ROUND_DOWN, ROUND_UP, TICK_SIZE,
TRUNCATE, decimal_to_precision)
from pandas import DataFrame
from freqtrade.data.converter import parse_ticker_dataframe
@@ -116,6 +117,7 @@ class Exchange:
self._load_markets()
# Check if all pairs are available
self.validate_stakecurrency(config['stake_currency'])
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', {}))
@@ -188,6 +190,11 @@ class Exchange:
self._load_markets()
return self._api.markets
@property
def precisionMode(self) -> str:
"""exchange ccxt precisionMode"""
return self._api.precisionMode
def get_markets(self, base_currencies: List[str] = None, quote_currencies: List[str] = None,
pairs_only: bool = False, active_only: bool = False) -> Dict:
"""
@@ -210,6 +217,13 @@ class Exchange:
markets = {k: v for k, v in markets.items() if market_is_active(v)}
return markets
def get_quote_currencies(self) -> List[str]:
"""
Return a list of supported quote currencies
"""
markets = self.markets
return sorted(set([x['quote'] for _, x in markets.items()]))
def klines(self, pair_interval: Tuple[str, str], copy=True) -> DataFrame:
if pair_interval in self._klines:
return self._klines[pair_interval].copy() if copy else self._klines[pair_interval]
@@ -259,11 +273,23 @@ class Exchange:
except ccxt.BaseError:
logger.exception("Could not reload markets.")
def validate_stakecurrency(self, stake_currency) -> None:
"""
Checks stake-currency against available currencies on the exchange.
:param stake_currency: Stake-currency to validate
:raise: OperationalException if stake-currency is not available.
"""
quote_currencies = self.get_quote_currencies()
if stake_currency not in quote_currencies:
raise OperationalException(
f"{stake_currency} is not available as stake on {self.name}. "
f"Available currencies are: {', '.join(quote_currencies)}")
def validate_pairs(self, pairs: List[str]) -> None:
"""
Checks if all given pairs are tradable on the current exchange.
Raises OperationalException if one pair is not available.
:param pairs: list of pairs
:raise: OperationalException if one pair is not available
:return: None
"""
@@ -319,6 +345,10 @@ class Exchange:
raise OperationalException(
f"Invalid ticker interval '{timeframe}'. This exchange supports: {self.timeframes}")
if timeframe and timeframe_to_minutes(timeframe) < 1:
raise OperationalException(
f"Timeframes < 1m are currently not supported by Freqtrade.")
def validate_ordertypes(self, order_types: Dict) -> None:
"""
Checks if order-types configured in strategy/config are supported
@@ -362,32 +392,49 @@ class Exchange:
"""
return endpoint in self._api.has and self._api.has[endpoint]
def symbol_amount_prec(self, pair, amount: float):
def amount_to_precision(self, pair, amount: float) -> float:
'''
Returns the amount to buy or sell to a precision the Exchange accepts
Rounded down
Reimplementation of ccxt internal methods - ensuring we can test the result is correct
based on our definitions.
'''
if self.markets[pair]['precision']['amount']:
symbol_prec = self.markets[pair]['precision']['amount']
big_amount = amount * pow(10, symbol_prec)
amount = floor(big_amount) / pow(10, symbol_prec)
amount = float(decimal_to_precision(amount, rounding_mode=TRUNCATE,
precision=self.markets[pair]['precision']['amount'],
counting_mode=self.precisionMode,
))
return amount
def symbol_price_prec(self, pair, price: float):
def price_to_precision(self, pair, price: float) -> float:
'''
Returns the price buying or selling with to the precision the Exchange accepts
Returns the price rounded up to the precision the Exchange accepts.
Partial Reimplementation of ccxt internal method decimal_to_precision(),
which does not support rounding up
TODO: If ccxt supports ROUND_UP for decimal_to_precision(), we could remove this and
align with amount_to_precision().
Rounds up
'''
if self.markets[pair]['precision']['price']:
symbol_prec = self.markets[pair]['precision']['price']
big_price = price * pow(10, symbol_prec)
price = ceil(big_price) / pow(10, symbol_prec)
# price = float(decimal_to_precision(price, rounding_mode=ROUND,
# precision=self.markets[pair]['precision']['price'],
# counting_mode=self.precisionMode,
# ))
if self.precisionMode == TICK_SIZE:
precision = self.markets[pair]['precision']['price']
missing = price % precision
if missing != 0:
price = price - missing + precision
else:
symbol_prec = self.markets[pair]['precision']['price']
big_price = price * pow(10, symbol_prec)
price = ceil(big_price) / pow(10, symbol_prec)
return price
def dry_run_order(self, pair: str, ordertype: str, side: str, amount: float,
rate: float, params: Dict = {}) -> Dict[str, Any]:
order_id = f'dry_run_{side}_{randint(0, 10**6)}'
_amount = self.symbol_amount_prec(pair, amount)
_amount = self.amount_to_precision(pair, amount)
dry_order = {
"id": order_id,
'pair': pair,
@@ -422,13 +469,13 @@ class Exchange:
rate: float, params: Dict = {}) -> Dict:
try:
# Set the precision for amount and price(rate) as accepted by the exchange
amount = self.symbol_amount_prec(pair, amount)
amount = self.amount_to_precision(pair, amount)
needs_price = (ordertype != 'market'
or self._api.options.get("createMarketBuyOrderRequiresPrice", False))
rate = self.symbol_price_prec(pair, rate) if needs_price else None
rate_for_order = self.price_to_precision(pair, rate) if needs_price else None
return self._api.create_order(pair, ordertype, side,
amount, rate, params)
amount, rate_for_order, params)
except ccxt.InsufficientFunds as e:
raise DependencyException(

61
freqtrade/freqtradebot.py
View File

@@ -63,8 +63,7 @@ class FreqtradeBot:
self.exchange = ExchangeResolver.load_exchange(self.config['exchange']['name'], self.config)
persistence.init(self.config.get('db_url', None),
clean_open_orders=self.config.get('dry_run', False))
persistence.init(self.config.get('db_url', None), clean_open_orders=self.config['dry_run'])
self.wallets = Wallets(self.config, self.exchange)
@@ -250,12 +249,16 @@ class FreqtradeBot:
return used_rate
def get_trade_stake_amount(self, pair) -> Optional[float]:
def get_trade_stake_amount(self, pair) -> float:
"""
Calculate stake amount for the trade
:return: float: Stake amount
:raise: DependencyException if the available stake amount is too low
"""
stake_amount: Optional[float]
stake_amount: float
# Ensure wallets are uptodate.
self.wallets.update()
if self.edge:
stake_amount = self.edge.stake_amount(
pair,
@@ -270,26 +273,52 @@ class FreqtradeBot:
return self._check_available_stake_amount(stake_amount)
def _calculate_unlimited_stake_amount(self) -> Optional[float]:
def _get_available_stake_amount(self) -> float:
"""
Return the total currently available balance in stake currency,
respecting tradable_balance_ratio.
Calculated as
<open_trade stakes> + free amount ) * tradable_balance_ratio - <open_trade stakes>
"""
val_tied_up = Trade.total_open_trades_stakes()
# Ensure <tradable_balance_ratio>% is used from the overall balance
# Otherwise we'd risk lowering stakes with each open trade.
# (tied up + current free) * ratio) - tied up
available_amount = ((val_tied_up + self.wallets.get_free(self.config['stake_currency'])) *
self.config['tradable_balance_ratio']) - val_tied_up
return available_amount
def _calculate_unlimited_stake_amount(self) -> float:
"""
Calculate stake amount for "unlimited" stake amount
:return: None if max number of trades reached
:return: 0 if max number of trades reached, else stake_amount to use.
"""
free_open_trades = self.get_free_open_trades()
if not free_open_trades:
return None
available_amount = self.wallets.get_free(self.config['stake_currency'])
return 0
available_amount = self._get_available_stake_amount()
return available_amount / free_open_trades
def _check_available_stake_amount(self, stake_amount: Optional[float]) -> Optional[float]:
def _check_available_stake_amount(self, stake_amount: float) -> float:
"""
Check if stake amount can be fulfilled with the available balance
for the stake currency
:return: float: Stake amount
"""
available_amount = self.wallets.get_free(self.config['stake_currency'])
available_amount = self._get_available_stake_amount()
if stake_amount is not None and available_amount < stake_amount:
if self.config['amend_last_stake_amount']:
# Remaining amount needs to be at least stake_amount * last_stake_amount_min_ratio
# Otherwise the remaining amount is too low to trade.
if available_amount > (stake_amount * self.config['last_stake_amount_min_ratio']):
stake_amount = min(stake_amount, available_amount)
else:
stake_amount = 0
if available_amount < stake_amount:
raise DependencyException(
f"Available balance ({available_amount} {self.config['stake_currency']}) is "
f"lower than stake amount ({stake_amount} {self.config['stake_currency']})"
@@ -872,15 +901,19 @@ class FreqtradeBot:
:return: amount to sell
:raise: DependencyException: if available balance is not within 2% of the available amount.
"""
# Update wallets to ensure amounts tied up in a stoploss is now free!
self.wallets.update()
wallet_amount = self.wallets.get_free(pair.split('/')[0])
logger.debug(f"{pair} - Wallet: {wallet_amount} - Trade-amount: {amount}")
if wallet_amount > amount:
if wallet_amount >= amount:
return amount
elif wallet_amount > amount * 0.98:
logger.info(f"{pair} - Falling back to wallet-amount.")
return wallet_amount
else:
raise DependencyException("Not enough amount to sell.")
raise DependencyException(
f"Not enough amount to sell. Trade-amount: {amount}, Wallet: {wallet_amount}")
def execute_sell(self, trade: Trade, limit: float, sell_reason: SellType) -> None:
"""
@@ -896,7 +929,7 @@ class FreqtradeBot:
# if stoploss is on exchange and we are on dry_run mode,
# we consider the sell price stop price
if self.config.get('dry_run', False) and sell_type == 'stoploss' \
if self.config['dry_run'] and sell_type == 'stoploss' \
and self.strategy.order_types['stoploss_on_exchange']:
limit = trade.stop_loss

112
freqtrade/optimize/backtesting.py
View File

@@ -10,7 +10,6 @@ from pathlib import Path
from typing import Any, Dict, List, NamedTuple, Optional
from pandas import DataFrame
from tabulate import tabulate
from freqtrade.configuration import (TimeRange, remove_credentials,
validate_config_consistency)
@@ -20,6 +19,9 @@ from freqtrade.data.dataprovider import DataProvider
from freqtrade.exceptions import OperationalException
from freqtrade.exchange import timeframe_to_minutes, timeframe_to_seconds
from freqtrade.misc import file_dump_json
from freqtrade.optimize.optimize_reports import (
generate_text_table, generate_text_table_sell_reason,
generate_text_table_strategy)
from freqtrade.persistence import Trade
from freqtrade.resolvers import ExchangeResolver, StrategyResolver
from freqtrade.state import RunMode
@@ -131,96 +133,6 @@ class Backtesting:
return data, timerange
def _generate_text_table(self, data: Dict[str, Dict], results: DataFrame,
skip_nan: bool = False) -> str:
"""
Generates and returns a text table for the given backtest data and the results dataframe
:return: pretty printed table with tabulate as str
"""
stake_currency = str(self.config.get('stake_currency'))
max_open_trades = self.config.get('max_open_trades')
floatfmt = ('s', 'd', '.2f', '.2f', '.8f', '.2f', 'd', '.1f', '.1f')
tabular_data = []
headers = ['pair', 'buy count', 'avg profit %', 'cum profit %',
'tot profit ' + stake_currency, 'tot profit %', 'avg duration',
'profit', 'loss']
for pair in data:
result = results[results.pair == pair]
if skip_nan and result.profit_abs.isnull().all():
continue
tabular_data.append([
pair,
len(result.index),
result.profit_percent.mean() * 100.0,
result.profit_percent.sum() * 100.0,
result.profit_abs.sum(),
result.profit_percent.sum() * 100.0 / max_open_trades,
str(timedelta(
minutes=round(result.trade_duration.mean()))) if not result.empty else '0:00',
len(result[result.profit_abs > 0]),
len(result[result.profit_abs < 0])
])
# Append Total
tabular_data.append([
'TOTAL',
len(results.index),
results.profit_percent.mean() * 100.0,
results.profit_percent.sum() * 100.0,
results.profit_abs.sum(),
results.profit_percent.sum() * 100.0 / max_open_trades,
str(timedelta(
minutes=round(results.trade_duration.mean()))) if not results.empty else '0:00',
len(results[results.profit_abs > 0]),
len(results[results.profit_abs < 0])
])
# Ignore type as floatfmt does allow tuples but mypy does not know that
return tabulate(tabular_data, headers=headers,
floatfmt=floatfmt, tablefmt="pipe") # type: ignore
def _generate_text_table_sell_reason(self, data: Dict[str, Dict], results: DataFrame) -> str:
"""
Generate small table outlining Backtest results
"""
tabular_data = []
headers = ['Sell Reason', 'Count', 'Profit', 'Loss']
for reason, count in results['sell_reason'].value_counts().iteritems():
profit = len(results[(results['sell_reason'] == reason) & (results['profit_abs'] >= 0)])
loss = len(results[(results['sell_reason'] == reason) & (results['profit_abs'] < 0)])
tabular_data.append([reason.value, count, profit, loss])
return tabulate(tabular_data, headers=headers, tablefmt="pipe")
def _generate_text_table_strategy(self, all_results: dict) -> str:
"""
Generate summary table per strategy
"""
stake_currency = str(self.config.get('stake_currency'))
max_open_trades = self.config.get('max_open_trades')
floatfmt = ('s', 'd', '.2f', '.2f', '.8f', '.2f', 'd', '.1f', '.1f')
tabular_data = []
headers = ['Strategy', 'buy count', 'avg profit %', 'cum profit %',
'tot profit ' + stake_currency, 'tot profit %', 'avg duration',
'profit', 'loss']
for strategy, results in all_results.items():
tabular_data.append([
strategy,
len(results.index),
results.profit_percent.mean() * 100.0,
results.profit_percent.sum() * 100.0,
results.profit_abs.sum(),
results.profit_percent.sum() * 100.0 / max_open_trades,
str(timedelta(
minutes=round(results.trade_duration.mean()))) if not results.empty else '0:00',
len(results[results.profit_abs > 0]),
len(results[results.profit_abs < 0])
])
# Ignore type as floatfmt does allow tuples but mypy does not know that
return tabulate(tabular_data, headers=headers,
floatfmt=floatfmt, tablefmt="pipe") # type: ignore
def _store_backtest_result(self, recordfilename: Path, results: DataFrame,
strategyname: Optional[str] = None) -> None:
@@ -386,7 +298,7 @@ class Backtesting:
"""
# Arguments are long and noisy, so this is commented out.
# Uncomment if you need to debug the backtest() method.
# logger.debug(f"Start backtest, args: {args}")
# logger.debug(f"Start backtest, args: {args}")
processed = args['processed']
stake_amount = args['stake_amount']
max_open_trades = args.get('max_open_trades', 0)
@@ -511,16 +423,24 @@ class Backtesting:
print(f"Result for strategy {strategy}")
print(' BACKTESTING REPORT '.center(133, '='))
print(self._generate_text_table(data, results))
print(generate_text_table(data,
stake_currency=self.config['stake_currency'],
max_open_trades=self.config['max_open_trades'],
results=results))
print(' SELL REASON STATS '.center(133, '='))
print(self._generate_text_table_sell_reason(data, results))
print(generate_text_table_sell_reason(data, results))
print(' LEFT OPEN TRADES REPORT '.center(133, '='))
print(self._generate_text_table(data, results.loc[results.open_at_end], True))
print(generate_text_table(data,
stake_currency=self.config['stake_currency'],
max_open_trades=self.config['max_open_trades'],
results=results.loc[results.open_at_end], skip_nan=True))
print()
if len(all_results) > 1:
# Print Strategy summary table
print(' Strategy Summary '.center(133, '='))
print(self._generate_text_table_strategy(all_results))
print(generate_text_table_strategy(self.config['stake_currency'],
self.config['max_open_trades'],
all_results=all_results))
print('\nFor more details, please look at the detail tables above')

32
freqtrade/optimize/edge_cli.py
View File

@@ -6,13 +6,12 @@ This module contains the edge backtesting interface
import logging
from typing import Any, Dict
from tabulate import tabulate
from freqtrade import constants
from freqtrade.configuration import (TimeRange, remove_credentials,
validate_config_consistency)
from freqtrade.edge import Edge
from freqtrade.resolvers import StrategyResolver, ExchangeResolver
from freqtrade.optimize.optimize_reports import generate_edge_table
from freqtrade.resolvers import ExchangeResolver, StrategyResolver
logger = logging.getLogger(__name__)
@@ -44,33 +43,8 @@ class EdgeCli:
self.edge._timerange = TimeRange.parse_timerange(None if self.config.get(
'timerange') is None else str(self.config.get('timerange')))
def _generate_edge_table(self, results: dict) -> str:
floatfmt = ('s', '.10g', '.2f', '.2f', '.2f', '.2f', 'd', '.d')
tabular_data = []
headers = ['pair', 'stoploss', 'win rate', 'risk reward ratio',
'required risk reward', 'expectancy', 'total number of trades',
'average duration (min)']
for result in results.items():
if result[1].nb_trades > 0:
tabular_data.append([
result[0],
result[1].stoploss,
result[1].winrate,
result[1].risk_reward_ratio,
result[1].required_risk_reward,
result[1].expectancy,
result[1].nb_trades,
round(result[1].avg_trade_duration)
])
# Ignore type as floatfmt does allow tuples but mypy does not know that
return tabulate(tabular_data, headers=headers,
floatfmt=floatfmt, tablefmt="pipe") # type: ignore
def start(self) -> None:
result = self.edge.calculate()
if result:
print('') # blank line for readability
print(self._generate_edge_table(self.edge._cached_pairs))
print(generate_edge_table(self.edge._cached_pairs))

135
freqtrade/optimize/optimize_reports.py Normal file
View File

@@ -0,0 +1,135 @@
from datetime import timedelta
from typing import Dict
from pandas import DataFrame
from tabulate import tabulate
def generate_text_table(data: Dict[str, Dict], stake_currency: str, max_open_trades: int,
results: DataFrame, skip_nan: bool = False) -> str:
"""
Generates and returns a text table for the given backtest data and the results dataframe
:param data: Dict of <pair: dataframe> containing data that was used during backtesting.
:param stake_currency: stake-currency - used to correctly name headers
:param max_open_trades: Maximum allowed open trades
:param results: Dataframe containing the backtest results
:param skip_nan: Print "left open" open trades
:return: pretty printed table with tabulate as string
"""
floatfmt = ('s', 'd', '.2f', '.2f', '.8f', '.2f', 'd', '.1f', '.1f')
tabular_data = []
headers = ['pair', 'buy count', 'avg profit %', 'cum profit %',
f'tot profit {stake_currency}', 'tot profit %', 'avg duration',
'profit', 'loss']
for pair in data:
result = results[results.pair == pair]
if skip_nan and result.profit_abs.isnull().all():
continue
tabular_data.append([
pair,
len(result.index),
result.profit_percent.mean() * 100.0,
result.profit_percent.sum() * 100.0,
result.profit_abs.sum(),
result.profit_percent.sum() * 100.0 / max_open_trades,
str(timedelta(
minutes=round(result.trade_duration.mean()))) if not result.empty else '0:00',
len(result[result.profit_abs > 0]),
len(result[result.profit_abs < 0])
])
# Append Total
tabular_data.append([
'TOTAL',
len(results.index),
results.profit_percent.mean() * 100.0,
results.profit_percent.sum() * 100.0,
results.profit_abs.sum(),
results.profit_percent.sum() * 100.0 / max_open_trades,
str(timedelta(
minutes=round(results.trade_duration.mean()))) if not results.empty else '0:00',
len(results[results.profit_abs > 0]),
len(results[results.profit_abs < 0])
])
# Ignore type as floatfmt does allow tuples but mypy does not know that
return tabulate(tabular_data, headers=headers,
floatfmt=floatfmt, tablefmt="pipe") # type: ignore
def generate_text_table_sell_reason(data: Dict[str, Dict], results: DataFrame) -> str:
"""
Generate small table outlining Backtest results
:param data: Dict of <pair: dataframe> containing data that was used during backtesting.
:param results: Dataframe containing the backtest results
:return: pretty printed table with tabulate as string
"""
tabular_data = []
headers = ['Sell Reason', 'Count', 'Profit', 'Loss', 'Profit %']
for reason, count in results['sell_reason'].value_counts().iteritems():
result = results.loc[results['sell_reason'] == reason]
profit = len(result[result['profit_abs'] >= 0])
loss = len(result[results['profit_abs'] < 0])
profit_mean = round(result['profit_percent'].mean() * 100.0, 2)
tabular_data.append([reason.value, count, profit, loss, profit_mean])
return tabulate(tabular_data, headers=headers, tablefmt="pipe")
def generate_text_table_strategy(stake_currency: str, max_open_trades: str,
all_results: Dict) -> str:
"""
Generate summary table per strategy
:param stake_currency: stake-currency - used to correctly name headers
:param max_open_trades: Maximum allowed open trades used for backtest
:param all_results: Dict of <Strategyname: BacktestResult> containing results for all strategies
:return: pretty printed table with tabulate as string
"""
floatfmt = ('s', 'd', '.2f', '.2f', '.8f', '.2f', 'd', '.1f', '.1f')
tabular_data = []
headers = ['Strategy', 'buy count', 'avg profit %', 'cum profit %',
f'tot profit {stake_currency}', 'tot profit %', 'avg duration',
'profit', 'loss']
for strategy, results in all_results.items():
tabular_data.append([
strategy,
len(results.index),
results.profit_percent.mean() * 100.0,
results.profit_percent.sum() * 100.0,
results.profit_abs.sum(),
results.profit_percent.sum() * 100.0 / max_open_trades,
str(timedelta(
minutes=round(results.trade_duration.mean()))) if not results.empty else '0:00',
len(results[results.profit_abs > 0]),
len(results[results.profit_abs < 0])
])
# Ignore type as floatfmt does allow tuples but mypy does not know that
return tabulate(tabular_data, headers=headers,
floatfmt=floatfmt, tablefmt="pipe") # type: ignore
def generate_edge_table(results: dict) -> str:
floatfmt = ('s', '.10g', '.2f', '.2f', '.2f', '.2f', 'd', '.d')
tabular_data = []
headers = ['pair', 'stoploss', 'win rate', 'risk reward ratio',
'required risk reward', 'expectancy', 'total number of trades',
'average duration (min)']
for result in results.items():
if result[1].nb_trades > 0:
tabular_data.append([
result[0],
result[1].stoploss,
result[1].winrate,
result[1].risk_reward_ratio,
result[1].required_risk_reward,
result[1].expectancy,
result[1].nb_trades,
round(result[1].avg_trade_duration)
])
# Ignore type as floatfmt does allow tuples but mypy does not know that
return tabulate(tabular_data, headers=headers,
floatfmt=floatfmt, tablefmt="pipe") # type: ignore

4
freqtrade/pairlist/PrecisionFilter.py
View File

@@ -35,8 +35,8 @@ class PrecisionFilter(IPairList):
"""
stop_price = ticker['ask'] * stoploss
# Adjust stop-prices to precision
sp = self._exchange.symbol_price_prec(ticker["symbol"], stop_price)
stop_gap_price = self._exchange.symbol_price_prec(ticker["symbol"], stop_price * 0.99)
sp = self._exchange.price_to_precision(ticker["symbol"], stop_price)
stop_gap_price = self._exchange.price_to_precision(ticker["symbol"], stop_price * 0.99)
logger.debug(f"{ticker['symbol']} - {sp} : {stop_gap_price}")
if sp <= stop_gap_price:
logger.info(f"Removed {ticker['symbol']} from whitelist, "

135
freqtrade/plot/plotting.py
View File

@@ -58,21 +58,27 @@ def init_plotscript(config):
}
def add_indicators(fig, row, indicators: List[str], data: pd.DataFrame) -> make_subplots:
def add_indicators(fig, row, indicators: Dict[str, Dict], data: pd.DataFrame) -> make_subplots:
"""
Generator all the indicator selected by the user for a specific row
Generate all the indicators selected by the user for a specific row, based on the configuration
:param fig: Plot figure to append to
:param row: row number for this plot
:param indicators: List of indicators present in the dataframe
:param indicators: Dict of Indicators with configuration options.
Dict key must correspond to dataframe column.
:param data: candlestick DataFrame
"""
for indicator in indicators:
for indicator, conf in indicators.items():
logger.debug(f"indicator {indicator} with config {conf}")
if indicator in data:
kwargs = {'x': data['date'],
'y': data[indicator].values,
'mode': 'lines',
'name': indicator
}
if 'color' in conf:
kwargs.update({'line': {'color': conf['color']}})
scatter = go.Scatter(
x=data['date'],
y=data[indicator].values,
mode='lines',
name=indicator
**kwargs
)
fig.add_trace(scatter, row, 1)
else:
@@ -111,11 +117,31 @@ 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['profitperc'] * 100, 1)}%, "
f"{row['sell_reason']}, {row['duration']} min",
axis=1)
trade_buys = go.Scatter(
x=trades["open_time"],
y=trades["open_rate"],
mode='markers',
name='trade_buy',
name='Trade buy',
text=trades["desc"],
marker=dict(
symbol='circle-open',
size=11,
line=dict(width=2),
color='cyan'
)
)
trade_sells = go.Scatter(
x=trades.loc[trades['profitperc'] > 0, "close_time"],
y=trades.loc[trades['profitperc'] > 0, "close_rate"],
text=trades.loc[trades['profitperc'] > 0, "desc"],
mode='markers',
name='Sell - Profit',
marker=dict(
symbol='square-open',
size=11,
@@ -123,16 +149,12 @@ def plot_trades(fig, trades: pd.DataFrame) -> make_subplots:
color='green'
)
)
# Create description for sell summarizing the trade
desc = trades.apply(lambda row: f"{round(row['profitperc'] * 100, 1)}%, "
f"{row['sell_reason']}, {row['duration']} min",
axis=1)
trade_sells = go.Scatter(
x=trades["close_time"],
y=trades["close_rate"],
text=desc,
trade_sells_loss = go.Scatter(
x=trades.loc[trades['profitperc'] <= 0, "close_time"],
y=trades.loc[trades['profitperc'] <= 0, "close_rate"],
text=trades.loc[trades['profitperc'] <= 0, "desc"],
mode='markers',
name='trade_sell',
name='Sell - Loss',
marker=dict(
symbol='square-open',
size=11,
@@ -142,14 +164,53 @@ def plot_trades(fig, trades: pd.DataFrame) -> make_subplots:
)
fig.add_trace(trade_buys, 1, 1)
fig.add_trace(trade_sells, 1, 1)
fig.add_trace(trade_sells_loss, 1, 1)
else:
logger.warning("No trades found.")
return fig
def generate_candlestick_graph(pair: str, data: pd.DataFrame, trades: pd.DataFrame = None,
def create_plotconfig(indicators1: List[str], indicators2: List[str],
plot_config: Dict[str, Dict]) -> Dict[str, Dict]:
"""
Combines indicators 1 and indicators 2 into plot_config if necessary
:param indicators1: List containing Main plot indicators
:param indicators2: List containing Sub plot indicators
:param plot_config: Dict of Dicts containing advanced plot configuration
:return: plot_config - eventually with indicators 1 and 2
"""
if plot_config:
if indicators1:
plot_config['main_plot'] = {ind: {} for ind in indicators1}
if indicators2:
plot_config['subplots'] = {'Other': {ind: {} for ind in indicators2}}
if not plot_config:
# If no indicators and no plot-config given, use defaults.
if not indicators1:
indicators1 = ['sma', 'ema3', 'ema5']
if not indicators2:
indicators2 = ['macd', 'macdsignal']
# Create subplot configuration if plot_config is not available.
plot_config = {
'main_plot': {ind: {} for ind in indicators1},
'subplots': {'Other': {ind: {} for ind in indicators2}},
}
if 'main_plot' not in plot_config:
plot_config['main_plot'] = {}
if 'subplots' not in plot_config:
plot_config['subplots'] = {}
return plot_config
def generate_candlestick_graph(pair: str, data: pd.DataFrame, trades: pd.DataFrame = None, *,
indicators1: List[str] = [],
indicators2: List[str] = [],) -> go.Figure:
indicators2: List[str] = [],
plot_config: Dict[str, Dict] = {},
) -> go.Figure:
"""
Generate the graph from the data generated by Backtesting or from DB
Volume will always be ploted in row2, so Row 1 and 3 are to our disposal for custom indicators
@@ -158,21 +219,26 @@ def generate_candlestick_graph(pair: str, data: pd.DataFrame, trades: pd.DataFra
:param trades: All trades created
:param indicators1: List containing Main plot indicators
:param indicators2: List containing Sub plot indicators
:return: None
:param plot_config: Dict of Dicts containing advanced plot configuration
:return: Plotly figure
"""
plot_config = create_plotconfig(indicators1, indicators2, plot_config)
rows = 2 + len(plot_config['subplots'])
row_widths = [1 for _ in plot_config['subplots']]
# Define the graph
fig = make_subplots(
rows=3,
rows=rows,
cols=1,
shared_xaxes=True,
row_width=[1, 1, 4],
row_width=row_widths + [1, 4],
vertical_spacing=0.0001,
)
fig['layout'].update(title=pair)
fig['layout']['yaxis1'].update(title='Price')
fig['layout']['yaxis2'].update(title='Volume')
fig['layout']['yaxis3'].update(title='Other')
for i, name in enumerate(plot_config['subplots']):
fig['layout'][f'yaxis{3 + i}'].update(title=name)
fig['layout']['xaxis']['rangeslider'].update(visible=False)
# Common information
@@ -242,12 +308,13 @@ def generate_candlestick_graph(pair: str, data: pd.DataFrame, trades: pd.DataFra
)
fig.add_trace(bb_lower, 1, 1)
fig.add_trace(bb_upper, 1, 1)
if 'bb_upperband' in indicators1 and 'bb_lowerband' in indicators1:
indicators1.remove('bb_upperband')
indicators1.remove('bb_lowerband')
if ('bb_upperband' in plot_config['main_plot']
and 'bb_lowerband' in plot_config['main_plot']):
del plot_config['main_plot']['bb_upperband']
del plot_config['main_plot']['bb_lowerband']
# Add indicators to main plot
fig = add_indicators(fig=fig, row=1, indicators=indicators1, data=data)
fig = add_indicators(fig=fig, row=1, indicators=plot_config['main_plot'], data=data)
fig = plot_trades(fig, trades)
@@ -258,11 +325,14 @@ def generate_candlestick_graph(pair: str, data: pd.DataFrame, trades: pd.DataFra
name='Volume',
marker_color='DarkSlateGrey',
marker_line_color='DarkSlateGrey'
)
)
fig.add_trace(volume, 2, 1)
# Add indicators to separate row
fig = add_indicators(fig=fig, row=3, indicators=indicators2, data=data)
for i, name in enumerate(plot_config['subplots']):
fig = add_indicators(fig=fig, row=3 + i,
indicators=plot_config['subplots'][name],
data=data)
return fig
@@ -363,8 +433,9 @@ def load_and_plot_trades(config: Dict[str, Any]):
pair=pair,
data=dataframe,
trades=trades_pair,
indicators1=config["indicators1"],
indicators2=config["indicators2"],
indicators1=config.get("indicators1", []),
indicators2=config.get("indicators2", []),
plot_config=strategy.plot_config if hasattr(strategy, 'plot_config') else {}
)
store_plot_file(fig, filename=generate_plot_filename(pair, config['ticker_interval']),

8
freqtrade/rpc/rpc.py
View File

@@ -88,7 +88,7 @@ class RPC:
"""
config = self._freqtrade.config
val = {
'dry_run': config.get('dry_run', False),
'dry_run': config['dry_run'],
'stake_currency': config['stake_currency'],
'stake_amount': config['stake_amount'],
'minimal_roi': config['minimal_roi'].copy(),
@@ -306,6 +306,8 @@ class RPC:
except (TemporaryError, DependencyException):
raise RPCException('Error getting current tickers.')
self._freqtrade.wallets.update(require_update=False)
for coin, balance in self._freqtrade.wallets.get_all_balances().items():
if not balance.total:
continue
@@ -335,7 +337,7 @@ class RPC:
'stake': stake_currency,
})
if total == 0.0:
if self._freqtrade.config.get('dry_run', False):
if self._freqtrade.config['dry_run']:
raise RPCException('Running in Dry Run, balances are not available.')
else:
raise RPCException('All balances are zero.')
@@ -349,7 +351,7 @@ class RPC:
'symbol': symbol,
'value': value,
'stake': stake_currency,
'note': 'Simulated balances' if self._freqtrade.config.get('dry_run', False) else ''
'note': 'Simulated balances' if self._freqtrade.config['dry_run'] else ''
}
def _rpc_start(self) -> Dict[str, str]:

2
freqtrade/rpc/rpc_manager.py
View File

@@ -62,7 +62,7 @@ class RPCManager:
logger.error(f"Message type {msg['type']} not implemented by handler {mod.name}.")
def startup_messages(self, config, pairlist) -> None:
if config.get('dry_run', False):
if config['dry_run']:
self.send_msg({
'type': RPCMessageType.WARNING_NOTIFICATION,
'status': 'Dry run is enabled. All trades are simulated.'

7
freqtrade/strategy/interface.py
View File

@@ -112,6 +112,9 @@ class IStrategy(ABC):
dp: Optional[DataProvider] = None
wallets: Optional[Wallets] = None
# Definition of plot_config. See plotting documentation for more details.
plot_config: Dict = {}
def __init__(self, config: dict) -> None:
self.config = config
# Dict to determine if analysis is necessary
@@ -386,9 +389,11 @@ class IStrategy(ABC):
trade.adjust_stop_loss(high or current_rate, stop_loss_value)
# evaluate if the stoploss was hit if stoploss is not on exchange
# in Dry-Run, this handles stoploss logic as well, as the logic will not be different to
# regular stoploss handling.
if ((self.stoploss is not None) and
(trade.stop_loss >= current_rate) and
(not self.order_types.get('stoploss_on_exchange'))):
(not self.order_types.get('stoploss_on_exchange') or self.config['dry_run'])):
sell_type = SellType.STOP_LOSS

2
freqtrade/templates/base_strategy.py.j2
View File

@@ -78,7 +78,7 @@ class {{ strategy }}(IStrategy):
'buy': 'gtc',
'sell': 'gtc'
}
{{ plot_config | indent(4) }}
def informative_pairs(self):
"""
Define additional, informative pair/interval combinations to be cached from the exchange.

16
freqtrade/templates/sample_strategy.py
View File

@@ -80,6 +80,22 @@ class SampleStrategy(IStrategy):
'sell': 'gtc'
}
plot_config = {
'main_plot': {
'tema': {},
'sar': {'color': 'white'},
},
'subplots': {
"MACD": {
'macd': {'color': 'blue'},
'macdsignal': {'color': 'orange'},
},
"RSI": {
'rsi': {'color': 'red'},
}
}
}
def informative_pairs(self):
"""
Define additional, informative pair/interval combinations to be cached from the exchange.

18
freqtrade/templates/subtemplates/plot_config_full.j2 Normal file
View File

@@ -0,0 +1,18 @@
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'},
},
"RSI": {
'rsi': {'color': 'red'},
}
}
}

0
freqtrade/templates/subtemplates/plot_config_minimal.j2 Normal file
View File

2
freqtrade/utils.py
View File

@@ -104,12 +104,14 @@ def deploy_new_strategy(strategy_name, strategy_path: Path, subtemplate: str):
indicators = render_template(templatefile=f"subtemplates/indicators_{subtemplate}.j2",)
buy_trend = render_template(templatefile=f"subtemplates/buy_trend_{subtemplate}.j2",)
sell_trend = render_template(templatefile=f"subtemplates/sell_trend_{subtemplate}.j2",)
plot_config = render_template(templatefile=f"subtemplates/plot_config_{subtemplate}.j2",)
strategy_text = render_template(templatefile='base_strategy.py.j2',
arguments={"strategy": strategy_name,
"indicators": indicators,
"buy_trend": buy_trend,
"sell_trend": sell_trend,
"plot_config": plot_config,
})
logger.info(f"Writing strategy to `{strategy_path}`.")

28
freqtrade/wallets.py
View File

@@ -2,7 +2,10 @@
""" Wallet """
import logging
from typing import Dict, NamedTuple, Any
from typing import Any, Dict, NamedTuple
import arrow
from freqtrade.exchange import Exchange
from freqtrade.persistence import Trade
@@ -24,7 +27,7 @@ class Wallets:
self._exchange = exchange
self._wallets: Dict[str, Wallet] = {}
self.start_cap = config['dry_run_wallet']
self._last_wallet_refresh = 0
self.update()
def get_free(self, currency) -> float:
@@ -95,12 +98,21 @@ class Wallets:
balances[currency].get('total', None)
)
def update(self) -> None:
if self._config['dry_run']:
self._update_dry()
else:
self._update_live()
logger.info('Wallets synced.')
def update(self, require_update: bool = True) -> None:
"""
Updates wallets from the configured version.
By default, updates from the exchange.
Update-skipping should only be used for user-invoked /balance calls, since
for trading operations, the latest balance is needed.
:param require_update: Allow skipping an update if balances were recently refreshed
"""
if (require_update or (self._last_wallet_refresh + 3600 < arrow.utcnow().timestamp)):
if self._config['dry_run']:
self._update_dry()
else:
self._update_live()
logger.info('Wallets synced.')
self._last_wallet_refresh = arrow.utcnow().timestamp
def get_all_balances(self) -> Dict[str, Any]:
return self._wallets