conflict resolved0

This commit is contained in:
misagh 2018-12-01 10:43:26 +01:00
commit f100432fe8
23 changed files with 717 additions and 122 deletions

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@ -36,7 +36,8 @@
"order_types": {
"buy": "limit",
"sell": "limit",
"stoploss": "market"
"stoploss": "market",
"stoploss_on_exchange": "false"
},
"exchange": {
"name": "bittrex",

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@ -39,7 +39,7 @@ The table below will list all configuration parameters.
| `ask_strategy.use_order_book` | false | No | Allows selling of open traded pair using the rates in Order Book Asks.
| `ask_strategy.order_book_min` | 0 | No | Bot will scan from the top min to max Order Book Asks searching for a profitable rate.
| `ask_strategy.order_book_max` | 0 | No | Bot will scan from the top min to max Order Book Asks searching for a profitable rate.
| `order_types` | None | No | Configure order-types depending on the action (`"buy"`, `"sell"`, `"stoploss"`).
| `order_types` | None | No | Configure order-types depending on the action (`"buy"`, `"sell"`, `"stoploss"`, `"stoploss_on_exchange"`).
| `exchange.name` | bittrex | Yes | Name of the exchange class to use. [List below](#user-content-what-values-for-exchangename).
| `exchange.key` | key | No | API key to use for the exchange. Only required when you are in production mode.
| `exchange.secret` | secret | No | API secret to use for the exchange. Only required when you are in production mode.
@ -141,17 +141,18 @@ end up paying more then would probably have been necessary.
### Understand order_types
`order_types` contains a dict mapping order-types to market-types. This allows to buy using limit orders, sell using limit-orders, and create stoploss orders using market.
`order_types` contains a dict mapping order-types to market-types as well as stoploss on or off exchange type. This allows to buy using limit orders, sell using limit-orders, and create stoploss orders using market. It also allows to set the stoploss "on exchange" which means stoploss order would be placed immediately once the buy order is fulfilled.
This can be set in the configuration or in the strategy. Configuration overwrites strategy configurations.
If this is configured, all 3 values (`"buy"`, `"sell"` and `"stoploss"`) need to be present, otherwise the bot warn about it and will fail to start.
If this is configured, all 4 values (`"buy"`, `"sell"`, `"stoploss"`, `"stoploss_on_exchange"`) need to be present, otherwise the bot warn about it and will fail to start.
The below is the default which is used if this is not configured in either Strategy or configuration.
``` json
"order_types": {
"buy": "limit",
"sell": "limit",
"stoploss": "market"
"stoploss": "market",
"stoploss_on_exchange": False
},
```

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@ -13,7 +13,7 @@ DEFAULT_HYPEROPT = 'DefaultHyperOpts'
DEFAULT_DB_PROD_URL = 'sqlite:///tradesv3.sqlite'
DEFAULT_DB_DRYRUN_URL = 'sqlite://'
UNLIMITED_STAKE_AMOUNT = 'unlimited'
REQUIRED_ORDERTYPES = ['buy', 'sell', 'stoploss']
REQUIRED_ORDERTYPES = ['buy', 'sell', 'stoploss', 'stoploss_on_exchange']
ORDERTYPE_POSSIBILITIES = ['limit', 'market']
@ -109,9 +109,10 @@ CONF_SCHEMA = {
'properties': {
'buy': {'type': 'string', 'enum': ORDERTYPE_POSSIBILITIES},
'sell': {'type': 'string', 'enum': ORDERTYPE_POSSIBILITIES},
'stoploss': {'type': 'string', 'enum': ORDERTYPE_POSSIBILITIES}
'stoploss': {'type': 'string', 'enum': ORDERTYPE_POSSIBILITIES},
'stoploss_on_exchange': {'type': 'boolean'}
},
'required': ['buy', 'sell', 'stoploss']
'required': ['buy', 'sell', 'stoploss', 'stoploss_on_exchange']
},
'exchange': {'$ref': '#/definitions/exchange'},
'edge': {'$ref': '#/definitions/edge'},

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@ -228,6 +228,12 @@ class Exchange(object):
raise OperationalException(
f'Exchange {self.name} does not support market orders.')
if order_types.get('stoploss_on_exchange'):
if self.name is not 'Binance':
raise OperationalException(
'On exchange stoploss is not supported for %s.' % self.name
)
def exchange_has(self, endpoint: str) -> bool:
"""
Checks if exchange implements a specific API endpoint.
@ -334,6 +340,61 @@ class Exchange(object):
except ccxt.BaseError as e:
raise OperationalException(e)
def stoploss_limit(self, pair: str, amount: float, stop_price: float, rate: float) -> Dict:
"""
creates a stoploss limit order.
NOTICE: it is not supported by all exchanges. only binance is tested for now.
"""
# Set the precision for amount and price(rate) as accepted by the exchange
amount = self.symbol_amount_prec(pair, amount)
rate = self.symbol_price_prec(pair, rate)
stop_price = self.symbol_price_prec(pair, stop_price)
# Ensure rate is less than stop price
if stop_price <= rate:
raise OperationalException(
'In stoploss limit order, stop price should be more than limit price')
if self._conf['dry_run']:
order_id = f'dry_run_buy_{randint(0, 10**6)}'
self._dry_run_open_orders[order_id] = {
'info': {},
'id': order_id,
'pair': pair,
'price': stop_price,
'amount': amount,
'type': 'stop_loss_limit',
'side': 'sell',
'remaining': amount,
'datetime': arrow.utcnow().isoformat(),
'status': 'open',
'fee': None
}
return self._dry_run_open_orders[order_id]
try:
return self._api.create_order(pair, 'stop_loss_limit', 'sell',
amount, rate, {'stopPrice': stop_price})
except ccxt.InsufficientFunds as e:
raise DependencyException(
f'Insufficient funds to place stoploss limit order on market {pair}. '
f'Tried to put a stoploss amount {amount} with '
f'stop {stop_price} and limit {rate} (total {rate*amount}).'
f'Message: {e}')
except ccxt.InvalidOrder as e:
raise DependencyException(
f'Could not place stoploss limit order on market {pair}.'
f'Tried to place stoploss amount {amount} with '
f'stop {stop_price} and limit {rate} (total {rate*amount}).'
f'Message: {e}')
except (ccxt.NetworkError, ccxt.ExchangeError) as e:
raise TemporaryError(
f'Could not place stoploss limit order due to {e.__class__.__name__}. Message: {e}')
except ccxt.BaseError as e:
raise OperationalException(e)
@retrier
def get_balance(self, currency: str) -> float:
if self._conf['dry_run']:

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@ -54,6 +54,7 @@ class FreqtradeBot(object):
# Init objects
self.config = config
self.strategy: IStrategy = StrategyResolver(self.config).strategy
self.rpc: RPCManager = RPCManager(self)
self.persistence = None
self.exchange = Exchange(self.config)
@ -107,7 +108,7 @@ class FreqtradeBot(object):
})
logger.info('Changing state to: %s', state.name)
if state == State.RUNNING:
self._startup_messages()
self.rpc.startup_messages(self.config)
if state == State.STOPPED:
time.sleep(1)
@ -121,38 +122,6 @@ class FreqtradeBot(object):
min_secs=min_secs)
return state
def _startup_messages(self) -> None:
if self.config.get('dry_run', False):
self.rpc.send_msg({
'type': RPCMessageType.WARNING_NOTIFICATION,
'status': 'Dry run is enabled. All trades are simulated.'
})
stake_currency = self.config['stake_currency']
stake_amount = self.config['stake_amount']
minimal_roi = self.config['minimal_roi']
ticker_interval = self.config['ticker_interval']
exchange_name = self.config['exchange']['name']
strategy_name = self.config.get('strategy', '')
self.rpc.send_msg({
'type': RPCMessageType.CUSTOM_NOTIFICATION,
'status': f'*Exchange:* `{exchange_name}`\n'
f'*Stake per trade:* `{stake_amount} {stake_currency}`\n'
f'*Minimum ROI:* `{minimal_roi}`\n'
f'*Ticker Interval:* `{ticker_interval}`\n'
f'*Strategy:* `{strategy_name}`'
})
if self.config.get('dynamic_whitelist', False):
top_pairs = 'top volume ' + str(self.config.get('dynamic_whitelist', 20))
specific_pairs = ''
else:
top_pairs = 'whitelisted'
specific_pairs = '\n' + ', '.join(self.config['exchange'].get('pair_whitelist', ''))
self.rpc.send_msg({
'type': RPCMessageType.STATUS_NOTIFICATION,
'status': f'Searching for {top_pairs} {stake_currency} pairs to buy and sell...'
f'{specific_pairs}'
})
def _throttle(self, func: Callable[..., Any], min_secs: float, *args, **kwargs) -> Any:
"""
Throttles the given callable that it
@ -487,6 +456,7 @@ class FreqtradeBot(object):
'stake_currency': stake_currency,
'fiat_currency': fiat_currency
})
# Fee is applied twice because we make a LIMIT_BUY and LIMIT_SELL
fee = self.exchange.get_fee(symbol=pair, taker_or_maker='maker')
trade = Trade(
@ -503,6 +473,7 @@ class FreqtradeBot(object):
strategy=self.strategy.get_strategy_name(),
ticker_interval=constants.TICKER_INTERVAL_MINUTES[self.config['ticker_interval']]
)
Trade.session.add(trade)
Trade.session.flush()
@ -551,6 +522,12 @@ class FreqtradeBot(object):
trade.update(order)
if self.strategy.order_types.get('stoploss_on_exchange') and trade.is_open:
result = self.handle_stoploss_on_exchange(trade)
if result:
self.wallets.update()
return result
if trade.is_open and trade.open_order_id is None:
# Check if we can sell our current pair
result = self.handle_trade(trade)
@ -648,13 +625,54 @@ class FreqtradeBot(object):
return True
break
else:
logger.info('checking sell')
logger.debug('checking sell')
if self.check_sell(trade, sell_rate, buy, sell):
return True
logger.info('Found no sell signals for whitelisted currencies. Trying again..')
logger.debug('Found no sell signal for %s.', trade)
return False
def handle_stoploss_on_exchange(self, trade: Trade) -> bool:
"""
Check if trade is fulfilled in which case the stoploss
on exchange should be added immediately if stoploss on exchnage
is enabled.
"""
result = False
# If trade is open and the buy order is fulfilled but there is no stoploss,
# then we add a stoploss on exchange
if not trade.open_order_id and not trade.stoploss_order_id:
if self.edge:
stoploss = self.edge.stoploss(pair=trade.pair)
else:
stoploss = self.strategy.stoploss
stop_price = trade.open_rate * (1 + stoploss)
# limit price should be less than stop price.
# 0.98 is arbitrary here.
limit_price = stop_price * 0.98
stoploss_order_id = self.exchange.stoploss_limit(
pair=trade.pair, amount=trade.amount, stop_price=stop_price, rate=limit_price
)['id']
trade.stoploss_order_id = str(stoploss_order_id)
# Or the trade open and there is already a stoploss on exchange.
# so we check if it is hit ...
elif trade.stoploss_order_id:
logger.debug('Handling stoploss on exchange %s ...', trade)
order = self.exchange.get_order(trade.stoploss_order_id, trade.pair)
if order['status'] == 'closed':
trade.sell_reason = SellType.STOPLOSS_ON_EXCHANGE.value
trade.update(order)
result = True
else:
result = False
return result
def check_sell(self, trade: Trade, sell_rate: float, buy: bool, sell: bool) -> bool:
if self.edge:
stoploss = self.edge.stoploss(trade.pair)
@ -780,9 +798,13 @@ class FreqtradeBot(object):
if sell_reason in (SellType.STOP_LOSS, SellType.TRAILING_STOP_LOSS):
sell_type = 'stoploss'
if self.config.get('dry_run', False) and sell_type == 'stoploss':
if self.config.get('dry_run', False) and sell_type == 'stoploss' and self.strategy.order_types['stoploss_on_exchange']:
limit = trade.stop_loss
# First cancelling stoploss on exchange ...
if self.strategy.order_types.get('stoploss_on_exchange') and trade.stoploss_order_id:
self.exchange.cancel_order(trade.stoploss_order_id, trade.pair)
# Execute sell and update trade record
order_id = self.exchange.sell(pair=str(trade.pair),
ordertype=self.strategy.order_types[sell_type],

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@ -66,6 +66,7 @@ class Backtesting(object):
if self.config.get('strategy_list', None):
# Force one interval
self.ticker_interval = str(self.config.get('ticker_interval'))
self.ticker_interval_mins = constants.TICKER_INTERVAL_MINUTES[self.ticker_interval]
for strat in list(self.config['strategy_list']):
stratconf = deepcopy(self.config)
stratconf['strategy'] = strat
@ -86,6 +87,8 @@ class Backtesting(object):
"""
self.strategy = strategy
self.ticker_interval = self.config.get('ticker_interval')
self.ticker_interval_mins = constants.TICKER_INTERVAL_MINUTES[self.ticker_interval]
self.tickerdata_to_dataframe = strategy.tickerdata_to_dataframe
self.advise_buy = strategy.advise_buy
self.advise_sell = strategy.advise_sell
@ -280,8 +283,13 @@ class Backtesting(object):
processed = args['processed']
max_open_trades = args.get('max_open_trades', 0)
position_stacking = args.get('position_stacking', False)
start_date = args['start_date']
end_date = args['end_date']
trades = []
trade_count_lock: Dict = {}
ticker: Dict = {}
pairs = []
# Create ticker dict
for pair, pair_data in processed.items():
pair_data['buy'], pair_data['sell'] = 0, 0 # cleanup from previous run
@ -296,15 +304,28 @@ class Backtesting(object):
# Convert from Pandas to list for performance reasons
# (Looping Pandas is slow.)
ticker = [x for x in ticker_data.itertuples()]
ticker[pair] = [x for x in ticker_data.itertuples()]
pairs.append(pair)
lock_pair_until: Dict = {}
tmp = start_date + timedelta(minutes=self.ticker_interval_mins)
index = 0
# Loop timerange and test per pair
while tmp < end_date:
# print(f"time: {tmp}")
for i, pair in enumerate(ticker):
try:
row = ticker[pair][index]
except IndexError:
# missing Data for one pair ...
# Warnings for this are shown by `validate_backtest_data`
continue
lock_pair_until = None
for index, row in enumerate(ticker):
if row.buy == 0 or row.sell == 1:
continue # skip rows where no buy signal or that would immediately sell off
if not position_stacking:
if lock_pair_until is not None and row.date <= lock_pair_until:
if pair in lock_pair_until and row.date <= lock_pair_until[pair]:
continue
if max_open_trades > 0:
# Check if max_open_trades has already been reached for the given date
@ -313,17 +334,19 @@ class Backtesting(object):
trade_count_lock[row.date] = trade_count_lock.get(row.date, 0) + 1
trade_entry = self._get_sell_trade_entry(pair, row, ticker[index + 1:],
trade_entry = self._get_sell_trade_entry(pair, row, ticker[pair][index + 1:],
trade_count_lock, args)
if trade_entry:
lock_pair_until = trade_entry.close_time
lock_pair_until[pair] = trade_entry.close_time
trades.append(trade_entry)
else:
# Set lock_pair_until to end of testing period if trade could not be closed
# This happens only if the buy-signal was with the last candle
lock_pair_until = ticker_data.iloc[-1].date
lock_pair_until[pair] = end_date
tmp += timedelta(minutes=self.ticker_interval_mins)
index += 1
return DataFrame.from_records(trades, columns=BacktestResult._fields)
def start(self) -> None:
@ -390,6 +413,8 @@ class Backtesting(object):
'processed': preprocessed,
'max_open_trades': max_open_trades,
'position_stacking': self.config.get('position_stacking', False),
'start_date': min_date,
'end_date': max_date,
}
)

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@ -20,7 +20,7 @@ from skopt.space import Dimension
from freqtrade.arguments import Arguments
from freqtrade.configuration import Configuration
from freqtrade.optimize import load_data
from freqtrade.optimize import load_data, get_timeframe
from freqtrade.optimize.backtesting import Backtesting
from freqtrade.resolvers import HyperOptResolver
@ -167,11 +167,14 @@ class Hyperopt(Backtesting):
self.strategy.stoploss = params['stoploss']
processed = load(TICKERDATA_PICKLE)
min_date, max_date = get_timeframe(processed)
results = self.backtest(
{
'stake_amount': self.config['stake_amount'],
'processed': processed,
'position_stacking': self.config.get('position_stacking', True),
'start_date': min_date,
'end_date': max_date,
}
)
result_explanation = self.format_results(results)

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@ -82,7 +82,7 @@ def check_migrate(engine) -> None:
logger.debug(f'trying {table_back_name}')
# Check for latest column
if not has_column(cols, 'ticker_interval'):
if not has_column(cols, 'stoploss_order_id'):
logger.info(f'Running database migration - backup available as {table_back_name}')
fee_open = get_column_def(cols, 'fee_open', 'fee')
@ -91,6 +91,7 @@ def check_migrate(engine) -> None:
close_rate_requested = get_column_def(cols, 'close_rate_requested', 'null')
stop_loss = get_column_def(cols, 'stop_loss', '0.0')
initial_stop_loss = get_column_def(cols, 'initial_stop_loss', '0.0')
stoploss_order_id = get_column_def(cols, 'stoploss_order_id', 'null')
max_rate = get_column_def(cols, 'max_rate', '0.0')
sell_reason = get_column_def(cols, 'sell_reason', 'null')
strategy = get_column_def(cols, 'strategy', 'null')
@ -106,7 +107,7 @@ def check_migrate(engine) -> None:
(id, exchange, pair, is_open, fee_open, fee_close, open_rate,
open_rate_requested, close_rate, close_rate_requested, close_profit,
stake_amount, amount, open_date, close_date, open_order_id,
stop_loss, initial_stop_loss, max_rate, sell_reason, strategy,
stop_loss, initial_stop_loss, stoploss_order_id, max_rate, sell_reason, strategy,
ticker_interval
)
select id, lower(exchange),
@ -122,7 +123,8 @@ def check_migrate(engine) -> None:
{close_rate_requested} close_rate_requested, close_profit,
stake_amount, amount, open_date, close_date, open_order_id,
{stop_loss} stop_loss, {initial_stop_loss} initial_stop_loss,
{max_rate} max_rate, {sell_reason} sell_reason, {strategy} strategy,
{stoploss_order_id} stoploss_order_id, {max_rate} max_rate,
{sell_reason} sell_reason, {strategy} strategy,
{ticker_interval} ticker_interval
from {table_back_name}
""")
@ -177,6 +179,8 @@ class Trade(_DECL_BASE):
stop_loss = Column(Float, nullable=True, default=0.0)
# absolute value of the initial stop loss
initial_stop_loss = Column(Float, nullable=True, default=0.0)
# stoploss order id which is on exchange
stoploss_order_id = Column(String, nullable=True, index=True)
# absolute value of the highest reached price
max_rate = Column(Float, nullable=True, default=0.0)
sell_reason = Column(String, nullable=True)
@ -249,6 +253,10 @@ class Trade(_DECL_BASE):
self.open_order_id = None
elif order_type == 'limit' and order['side'] == 'sell':
self.close(order['price'])
elif order_type == 'stop_loss_limit':
self.stoploss_order_id = None
logger.info('STOP_LOSS_LIMIT is hit for %s.', self)
self.close(order['average'])
else:
raise ValueError(f'Unknown order type: {order_type}')
cleanup()

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@ -4,7 +4,7 @@ This module contains class to manage RPC communications (Telegram, Slack, ...)
import logging
from typing import List, Dict, Any
from freqtrade.rpc import RPC
from freqtrade.rpc import RPC, RPCMessageType
logger = logging.getLogger(__name__)
@ -51,3 +51,35 @@ class RPCManager(object):
for mod in self.registered_modules:
logger.debug('Forwarding message to rpc.%s', mod.name)
mod.send_msg(msg)
def startup_messages(self, config) -> None:
if config.get('dry_run', False):
self.send_msg({
'type': RPCMessageType.WARNING_NOTIFICATION,
'status': 'Dry run is enabled. All trades are simulated.'
})
stake_currency = config['stake_currency']
stake_amount = config['stake_amount']
minimal_roi = config['minimal_roi']
ticker_interval = config['ticker_interval']
exchange_name = config['exchange']['name']
strategy_name = config.get('strategy', '')
self.send_msg({
'type': RPCMessageType.CUSTOM_NOTIFICATION,
'status': f'*Exchange:* `{exchange_name}`\n'
f'*Stake per trade:* `{stake_amount} {stake_currency}`\n'
f'*Minimum ROI:* `{minimal_roi}`\n'
f'*Ticker Interval:* `{ticker_interval}`\n'
f'*Strategy:* `{strategy_name}`'
})
if config.get('dynamic_whitelist', False):
top_pairs = 'top volume ' + str(config.get('dynamic_whitelist', 20))
specific_pairs = ''
else:
top_pairs = 'whitelisted'
specific_pairs = '\n' + ', '.join(config['exchange'].get('pair_whitelist', ''))
self.send_msg({
'type': RPCMessageType.STATUS_NOTIFICATION,
'status': f'Searching for {top_pairs} {stake_currency} pairs to buy and sell...'
f'{specific_pairs}'
})

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@ -32,7 +32,8 @@ class DefaultStrategy(IStrategy):
order_types = {
'buy': 'limit',
'sell': 'limit',
'stoploss': 'limit'
'stoploss': 'limit',
'stoploss_on_exchange': False
}
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:

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@ -33,6 +33,7 @@ class SellType(Enum):
"""
ROI = "roi"
STOP_LOSS = "stop_loss"
STOPLOSS_ON_EXCHANGE = "stoploss_on_exchange"
TRAILING_STOP_LOSS = "trailing_stop_loss"
SELL_SIGNAL = "sell_signal"
FORCE_SELL = "force_sell"
@ -74,7 +75,8 @@ class IStrategy(ABC):
order_types: Dict = {
'buy': 'limit',
'sell': 'limit',
'stoploss': 'limit'
'stoploss': 'limit',
'stoploss_on_exchange': False
}
# run "populate_indicators" only for new candle
@ -221,11 +223,17 @@ class IStrategy(ABC):
# Set current rate to low for backtesting sell
current_rate = low or rate
current_profit = trade.calc_profit_percent(current_rate)
stoplossflag = self.stop_loss_reached(current_rate=current_rate, trade=trade,
current_time=date, current_profit=current_profit,
force_stoploss=force_stoploss)
if self.order_types.get('stoploss_on_exchange'):
stoplossflag = SellCheckTuple(sell_flag=False, sell_type=SellType.NONE)
else:
stoplossflag = self.stop_loss_reached(current_rate=current_rate, trade=trade,
current_time=date, current_profit=current_profit,
force_stoploss=force_stoploss)
if stoplossflag.sell_flag:
return stoplossflag
# Set current rate to low for backtesting sell
current_rate = high or rate
current_profit = trade.calc_profit_percent(current_rate)

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@ -26,20 +26,21 @@ def log_has(line, logs):
False)
def patch_exchange(mocker, api_mock=None) -> None:
def patch_exchange(mocker, api_mock=None, id='bittrex') -> None:
mocker.patch('freqtrade.exchange.Exchange._load_markets', MagicMock(return_value={}))
mocker.patch('freqtrade.exchange.Exchange.validate_timeframes', MagicMock())
mocker.patch('freqtrade.exchange.Exchange.validate_ordertypes', MagicMock())
mocker.patch('freqtrade.exchange.Exchange.name', PropertyMock(return_value="Bittrex"))
mocker.patch('freqtrade.exchange.Exchange.id', PropertyMock(return_value="bittrex"))
mocker.patch('freqtrade.exchange.Exchange.id', PropertyMock(return_value=id))
mocker.patch('freqtrade.exchange.Exchange.name', PropertyMock(return_value=id.title()))
if api_mock:
mocker.patch('freqtrade.exchange.Exchange._init_ccxt', MagicMock(return_value=api_mock))
else:
mocker.patch('freqtrade.exchange.Exchange._init_ccxt', MagicMock())
def get_patched_exchange(mocker, config, api_mock=None) -> Exchange:
patch_exchange(mocker, api_mock)
def get_patched_exchange(mocker, config, api_mock=None, id='bittrex') -> Exchange:
patch_exchange(mocker, api_mock, id)
exchange = Exchange(config)
return exchange

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@ -362,18 +362,41 @@ def test_validate_order_types(default_conf, mocker):
mocker.patch('freqtrade.exchange.Exchange._init_ccxt', MagicMock(return_value=api_mock))
mocker.patch('freqtrade.exchange.Exchange._load_markets', MagicMock(return_value={}))
mocker.patch('freqtrade.exchange.Exchange.validate_timeframes', MagicMock())
default_conf['order_types'] = {'buy': 'limit', 'sell': 'limit', 'stoploss': 'market'}
mocker.patch('freqtrade.exchange.Exchange.name', 'Bittrex')
default_conf['order_types'] = {
'buy': 'limit',
'sell': 'limit',
'stoploss': 'market',
'stoploss_on_exchange': False
}
Exchange(default_conf)
type(api_mock).has = PropertyMock(return_value={'createMarketOrder': False})
mocker.patch('freqtrade.exchange.Exchange._init_ccxt', MagicMock(return_value=api_mock))
default_conf['order_types'] = {'buy': 'limit', 'sell': 'limit', 'stoploss': 'market'}
default_conf['order_types'] = {
'buy': 'limit',
'sell': 'limit',
'stoploss': 'market',
'stoploss_on_exchange': 'false'
}
with pytest.raises(OperationalException,
match=r'Exchange .* does not support market orders.'):
Exchange(default_conf)
default_conf['order_types'] = {
'buy': 'limit',
'sell': 'limit',
'stoploss': 'limit',
'stoploss_on_exchange': True
}
with pytest.raises(OperationalException,
match=r'On exchange stoploss is not supported for .*'):
Exchange(default_conf)
def test_validate_order_types_not_in_config(default_conf, mocker):
api_mock = MagicMock()
@ -1122,3 +1145,85 @@ def test_get_fee(default_conf, mocker):
ccxt_exceptionhandlers(mocker, default_conf, api_mock,
'get_fee', 'calculate_fee')
def test_stoploss_limit_order(default_conf, mocker):
api_mock = MagicMock()
order_id = 'test_prod_buy_{}'.format(randint(0, 10 ** 6))
order_type = 'stop_loss_limit'
api_mock.create_order = MagicMock(return_value={
'id': order_id,
'info': {
'foo': 'bar'
}
})
default_conf['dry_run'] = False
mocker.patch('freqtrade.exchange.Exchange.symbol_amount_prec', lambda s, x, y: y)
mocker.patch('freqtrade.exchange.Exchange.symbol_price_prec', lambda s, x, y: y)
exchange = get_patched_exchange(mocker, default_conf, api_mock, 'binance')
with pytest.raises(OperationalException):
order = exchange.stoploss_limit(pair='ETH/BTC', amount=1, stop_price=190, rate=200)
api_mock.create_order.reset_mock()
order = exchange.stoploss_limit(pair='ETH/BTC', amount=1, stop_price=220, rate=200)
assert 'id' in order
assert 'info' in order
assert order['id'] == order_id
assert api_mock.create_order.call_args[0][0] == 'ETH/BTC'
assert api_mock.create_order.call_args[0][1] == order_type
assert api_mock.create_order.call_args[0][2] == 'sell'
assert api_mock.create_order.call_args[0][3] == 1
assert api_mock.create_order.call_args[0][4] == 200
assert api_mock.create_order.call_args[0][5] == {'stopPrice': 220}
# test exception handling
with pytest.raises(DependencyException):
api_mock.create_order = MagicMock(side_effect=ccxt.InsufficientFunds)
exchange = get_patched_exchange(mocker, default_conf, api_mock)
exchange.stoploss_limit(pair='ETH/BTC', amount=1, stop_price=220, rate=200)
with pytest.raises(DependencyException):
api_mock.create_order = MagicMock(side_effect=ccxt.InvalidOrder)
exchange = get_patched_exchange(mocker, default_conf, api_mock)
exchange.stoploss_limit(pair='ETH/BTC', amount=1, stop_price=220, rate=200)
with pytest.raises(TemporaryError):
api_mock.create_order = MagicMock(side_effect=ccxt.NetworkError)
exchange = get_patched_exchange(mocker, default_conf, api_mock)
exchange.stoploss_limit(pair='ETH/BTC', amount=1, stop_price=220, rate=200)
with pytest.raises(OperationalException):
api_mock.create_order = MagicMock(side_effect=ccxt.BaseError)
exchange = get_patched_exchange(mocker, default_conf, api_mock)
exchange.stoploss_limit(pair='ETH/BTC', amount=1, stop_price=220, rate=200)
def test_stoploss_limit_order_dry_run(default_conf, mocker):
api_mock = MagicMock()
order_type = 'stop_loss_limit'
default_conf['dry_run'] = True
mocker.patch('freqtrade.exchange.Exchange.symbol_amount_prec', lambda s, x, y: y)
mocker.patch('freqtrade.exchange.Exchange.symbol_price_prec', lambda s, x, y: y)
exchange = get_patched_exchange(mocker, default_conf, api_mock, 'binance')
with pytest.raises(OperationalException):
order = exchange.stoploss_limit(pair='ETH/BTC', amount=1, stop_price=190, rate=200)
api_mock.create_order.reset_mock()
order = exchange.stoploss_limit(pair='ETH/BTC', amount=1, stop_price=220, rate=200)
assert 'id' in order
assert 'info' in order
assert 'type' in order
assert order['type'] == order_type
assert order['price'] == 220
assert order['amount'] == 1

View File

@ -4,9 +4,10 @@ import arrow
from pandas import DataFrame
from freqtrade.strategy.interface import SellType
from freqtrade.constants import TICKER_INTERVAL_MINUTES
ticker_start_time = arrow.get(2018, 10, 3)
ticker_interval_in_minute = 60
tests_ticker_interval = "1h"
class BTrade(NamedTuple):
@ -30,8 +31,8 @@ class BTContainer(NamedTuple):
def _get_frame_time_from_offset(offset):
return ticker_start_time.shift(
minutes=(offset * ticker_interval_in_minute)).datetime.replace(tzinfo=None)
return ticker_start_time.shift(minutes=(offset * TICKER_INTERVAL_MINUTES[tests_ticker_interval])
).datetime.replace(tzinfo=None)
def _build_backtest_dataframe(ticker_with_signals):

View File

@ -6,10 +6,11 @@ from pandas import DataFrame
import pytest
from freqtrade.optimize import get_timeframe
from freqtrade.optimize.backtesting import Backtesting
from freqtrade.strategy.interface import SellType
from freqtrade.tests.optimize import (BTrade, BTContainer, _build_backtest_dataframe,
_get_frame_time_from_offset)
_get_frame_time_from_offset, tests_ticker_interval)
from freqtrade.tests.conftest import patch_exchange
@ -147,6 +148,7 @@ def test_backtest_results(default_conf, fee, mocker, caplog, data) -> None:
"""
default_conf["stoploss"] = data.stop_loss
default_conf["minimal_roi"] = {"0": data.roi}
default_conf['ticker_interval'] = tests_ticker_interval
mocker.patch('freqtrade.exchange.Exchange.get_fee', MagicMock(return_value=0.0))
patch_exchange(mocker)
frame = _build_backtest_dataframe(data.data)
@ -158,29 +160,21 @@ def test_backtest_results(default_conf, fee, mocker, caplog, data) -> None:
pair = 'UNITTEST/BTC'
# Dummy data as we mock the analyze functions
data_processed = {pair: DataFrame()}
min_date, max_date = get_timeframe({pair: frame})
results = backtesting.backtest(
{
'stake_amount': default_conf['stake_amount'],
'processed': data_processed,
'max_open_trades': 10,
'start_date': min_date,
'end_date': max_date,
}
)
print(results.T)
assert len(results) == len(data.trades)
assert round(results["profit_percent"].sum(), 3) == round(data.profit_perc, 3)
# if data.sell_r == SellType.STOP_LOSS:
# assert log_has("Stop loss hit.", caplog.record_tuples)
# else:
# assert not log_has("Stop loss hit.", caplog.record_tuples)
# log_test = (f'Force_selling still open trade UNITTEST/BTC with '
# f'{results.iloc[-1].profit_percent} perc - {results.iloc[-1].profit_abs}')
# if data.sell_r == SellType.FORCE_SELL:
# assert log_has(log_test,
# caplog.record_tuples)
# else:
# assert not log_has(log_test,
# caplog.record_tuples)
for c, trade in enumerate(data.trades):
res = results.iloc[c]
assert res.sell_reason == trade.sell_reason

View File

@ -13,6 +13,7 @@ from arrow import Arrow
from freqtrade import DependencyException, constants, optimize
from freqtrade.arguments import Arguments, TimeRange
from freqtrade.optimize import get_timeframe
from freqtrade.optimize.backtesting import (Backtesting, setup_configuration,
start)
from freqtrade.tests.conftest import log_has, patch_exchange
@ -86,17 +87,21 @@ def load_data_test(what):
def simple_backtest(config, contour, num_results, mocker) -> None:
patch_exchange(mocker)
config['ticker_interval'] = '1m'
backtesting = Backtesting(config)
data = load_data_test(contour)
processed = backtesting.strategy.tickerdata_to_dataframe(data)
min_date, max_date = get_timeframe(processed)
assert isinstance(processed, dict)
results = backtesting.backtest(
{
'stake_amount': config['stake_amount'],
'processed': processed,
'max_open_trades': 1,
'position_stacking': False
'position_stacking': False,
'start_date': min_date,
'end_date': max_date,
}
)
# results :: <class 'pandas.core.frame.DataFrame'>
@ -123,12 +128,16 @@ def _make_backtest_conf(mocker, conf=None, pair='UNITTEST/BTC', record=None):
data = trim_dictlist(data, -201)
patch_exchange(mocker)
backtesting = Backtesting(conf)
processed = backtesting.strategy.tickerdata_to_dataframe(data)
min_date, max_date = get_timeframe(processed)
return {
'stake_amount': conf['stake_amount'],
'processed': backtesting.strategy.tickerdata_to_dataframe(data),
'processed': processed,
'max_open_trades': 10,
'position_stacking': False,
'record': record
'record': record,
'start_date': min_date,
'end_date': max_date,
}
@ -449,7 +458,7 @@ def test_backtesting_start(default_conf, mocker, caplog) -> None:
)
default_conf['exchange']['pair_whitelist'] = ['UNITTEST/BTC']
default_conf['ticker_interval'] = "1m"
default_conf['ticker_interval'] = '1m'
default_conf['live'] = False
default_conf['datadir'] = None
default_conf['export'] = None
@ -505,12 +514,15 @@ def test_backtest(default_conf, fee, mocker) -> None:
data = optimize.load_data(None, ticker_interval='5m', pairs=['UNITTEST/BTC'])
data = trim_dictlist(data, -200)
data_processed = backtesting.strategy.tickerdata_to_dataframe(data)
min_date, max_date = get_timeframe(data_processed)
results = backtesting.backtest(
{
'stake_amount': default_conf['stake_amount'],
'processed': data_processed,
'max_open_trades': 10,
'position_stacking': False
'position_stacking': False,
'start_date': min_date,
'end_date': max_date,
}
)
assert not results.empty
@ -554,12 +566,16 @@ def test_backtest_1min_ticker_interval(default_conf, fee, mocker) -> None:
# Run a backtesting for an exiting 5min ticker_interval
data = optimize.load_data(None, ticker_interval='1m', pairs=['UNITTEST/BTC'])
data = trim_dictlist(data, -200)
processed = backtesting.strategy.tickerdata_to_dataframe(data)
min_date, max_date = get_timeframe(processed)
results = backtesting.backtest(
{
'stake_amount': default_conf['stake_amount'],
'processed': backtesting.strategy.tickerdata_to_dataframe(data),
'processed': processed,
'max_open_trades': 1,
'position_stacking': False
'position_stacking': False,
'start_date': min_date,
'end_date': max_date,
}
)
assert not results.empty
@ -583,25 +599,13 @@ def test_processed(default_conf, mocker) -> None:
def test_backtest_pricecontours(default_conf, fee, mocker) -> None:
mocker.patch('freqtrade.exchange.Exchange.get_fee', fee)
tests = [['raise', 18], ['lower', 0], ['sine', 19]]
# We need to enable sell-signal - otherwise it sells on ROI!!
default_conf['experimental'] = {"use_sell_signal": True}
for [contour, numres] in tests:
simple_backtest(default_conf, contour, numres, mocker)
# Test backtest using offline data (testdata directory)
def test_backtest_ticks(default_conf, fee, mocker):
mocker.patch('freqtrade.exchange.Exchange.get_fee', fee)
patch_exchange(mocker)
ticks = [1, 5]
fun = Backtesting(default_conf).advise_buy
for _ in ticks:
backtest_conf = _make_backtest_conf(mocker, conf=default_conf)
backtesting = Backtesting(default_conf)
backtesting.advise_buy = fun # Override
backtesting.advise_sell = fun # Override
results = backtesting.backtest(backtest_conf)
assert not results.empty
def test_backtest_clash_buy_sell(mocker, default_conf):
# Override the default buy trend function in our default_strategy
def fun(dataframe=None, pair=None):
@ -636,14 +640,92 @@ def test_backtest_alternate_buy_sell(default_conf, fee, mocker):
mocker.patch('freqtrade.exchange.Exchange.get_fee', fee)
mocker.patch('freqtrade.optimize.backtesting.file_dump_json', MagicMock())
backtest_conf = _make_backtest_conf(mocker, conf=default_conf, pair='UNITTEST/BTC')
# We need to enable sell-signal - otherwise it sells on ROI!!
default_conf['experimental'] = {"use_sell_signal": True}
default_conf['ticker_interval'] = '1m'
backtesting = Backtesting(default_conf)
backtesting.advise_buy = _trend_alternate # Override
backtesting.advise_sell = _trend_alternate # Override
results = backtesting.backtest(backtest_conf)
backtesting._store_backtest_result("test_.json", results)
assert len(results) == 4
# 200 candles in backtest data
# won't buy on first (shifted by 1)
# 100 buys signals
assert len(results) == 99
# One trade was force-closed at the end
assert len(results.loc[results.open_at_end]) == 1
assert len(results.loc[results.open_at_end]) == 0
def test_backtest_multi_pair(default_conf, fee, mocker):
def evaluate_result_multi(results, freq, max_open_trades):
# Find overlapping trades by expanding each trade once per period
# and then counting overlaps
dates = [pd.Series(pd.date_range(row[1].open_time, row[1].close_time, freq=freq))
for row in results[['open_time', 'close_time']].iterrows()]
deltas = [len(x) for x in dates]
dates = pd.Series(pd.concat(dates).values, name='date')
df2 = pd.DataFrame(np.repeat(results.values, deltas, axis=0), columns=results.columns)
df2 = df2.astype(dtype={"open_time": "datetime64", "close_time": "datetime64"})
df2 = pd.concat([dates, df2], axis=1)
df2 = df2.set_index('date')
df_final = df2.resample(freq)[['pair']].count()
return df_final[df_final['pair'] > max_open_trades]
def _trend_alternate_hold(dataframe=None, metadata=None):
"""
Buy every 8th candle - sell every other 8th -2 (hold on to pairs a bit)
"""
multi = 8
dataframe['buy'] = np.where(dataframe.index % multi == 0, 1, 0)
dataframe['sell'] = np.where((dataframe.index + multi - 2) % multi == 0, 1, 0)
if metadata['pair'] in('ETH/BTC', 'LTC/BTC'):
dataframe['buy'] = dataframe['buy'].shift(-4)
dataframe['sell'] = dataframe['sell'].shift(-4)
return dataframe
mocker.patch('freqtrade.exchange.Exchange.get_fee', fee)
patch_exchange(mocker)
pairs = ['ADA/BTC', 'DASH/BTC', 'ETH/BTC', 'LTC/BTC', 'NXT/BTC']
data = optimize.load_data(None, ticker_interval='5m', pairs=pairs)
data = trim_dictlist(data, -500)
# We need to enable sell-signal - otherwise it sells on ROI!!
default_conf['experimental'] = {"use_sell_signal": True}
default_conf['ticker_interval'] = '5m'
backtesting = Backtesting(default_conf)
backtesting.advise_buy = _trend_alternate_hold # Override
backtesting.advise_sell = _trend_alternate_hold # Override
data_processed = backtesting.strategy.tickerdata_to_dataframe(data)
min_date, max_date = get_timeframe(data_processed)
backtest_conf = {
'stake_amount': default_conf['stake_amount'],
'processed': data_processed,
'max_open_trades': 3,
'position_stacking': False,
'start_date': min_date,
'end_date': max_date,
}
results = backtesting.backtest(backtest_conf)
# Make sure we have parallel trades
assert len(evaluate_result_multi(results, '5min', 2)) > 0
# make sure we don't have trades with more than configured max_open_trades
assert len(evaluate_result_multi(results, '5min', 3)) == 0
backtest_conf = {
'stake_amount': default_conf['stake_amount'],
'processed': data_processed,
'max_open_trades': 1,
'position_stacking': False,
'start_date': min_date,
'end_date': max_date,
}
results = backtesting.backtest(backtest_conf)
assert len(evaluate_result_multi(results, '5min', 1)) == 0
def test_backtest_record(default_conf, fee, mocker):

View File

@ -1,11 +1,12 @@
# pragma pylint: disable=missing-docstring,W0212,C0103
from datetime import datetime
import os
from unittest.mock import MagicMock
import pandas as pd
import pytest
from freqtrade.optimize.__init__ import load_tickerdata_file
from freqtrade.optimize import load_tickerdata_file
from freqtrade.optimize.hyperopt import Hyperopt, start
from freqtrade.resolvers import StrategyResolver
from freqtrade.tests.conftest import log_has, patch_exchange
@ -293,6 +294,10 @@ def test_generate_optimizer(mocker, default_conf) -> None:
'freqtrade.optimize.hyperopt.Hyperopt.backtest',
MagicMock(return_value=backtest_result)
)
mocker.patch(
'freqtrade.optimize.hyperopt.get_timeframe',
MagicMock(return_value=(datetime(2017, 12, 10), datetime(2017, 12, 13)))
)
patch_exchange(mocker)
mocker.patch('freqtrade.optimize.hyperopt.load', MagicMock())

View File

@ -113,3 +113,23 @@ def test_init_webhook_enabled(mocker, default_conf, caplog) -> None:
assert log_has('Enabling rpc.webhook ...', caplog.record_tuples)
assert len(rpc_manager.registered_modules) == 1
assert 'webhook' in [mod.name for mod in rpc_manager.registered_modules]
def test_startupmessages_telegram_enabled(mocker, default_conf, caplog) -> None:
telegram_mock = mocker.patch('freqtrade.rpc.telegram.Telegram.send_msg', MagicMock())
mocker.patch('freqtrade.rpc.telegram.Telegram._init', MagicMock())
freqtradebot = get_patched_freqtradebot(mocker, default_conf)
rpc_manager = RPCManager(freqtradebot)
rpc_manager.startup_messages(default_conf)
assert telegram_mock.call_count == 3
assert "*Exchange:* `bittrex`" in telegram_mock.call_args_list[1][0][0]['status']
telegram_mock.reset_mock()
default_conf['dry_run'] = True
default_conf['dynamic_whitelist'] = 20
rpc_manager.startup_messages(default_conf)
assert telegram_mock.call_count == 3
assert "Dry run is enabled." in telegram_mock.call_args_list[0][0][0]['status']

View File

@ -189,7 +189,8 @@ def test_strategy_override_order_types(caplog):
order_types = {
'buy': 'market',
'sell': 'limit',
'stoploss': 'limit'
'stoploss': 'limit',
'stoploss_on_exchange': True,
}
config = {
@ -199,13 +200,14 @@ def test_strategy_override_order_types(caplog):
resolver = StrategyResolver(config)
assert resolver.strategy.order_types
for method in ['buy', 'sell', 'stoploss']:
for method in ['buy', 'sell', 'stoploss', 'stoploss_on_exchange']:
assert resolver.strategy.order_types[method] == order_types[method]
assert ('freqtrade.resolvers.strategy_resolver',
logging.INFO,
"Override strategy 'order_types' with value in config file:"
" {'buy': 'market', 'sell': 'limit', 'stoploss': 'limit'}."
" {'buy': 'market', 'sell': 'limit', 'stoploss': 'limit',"
" 'stoploss_on_exchange': True}."
) in caplog.record_tuples
config = {
@ -263,13 +265,13 @@ def test_call_deprecated_function(result, monkeypatch):
assert resolver.strategy._sell_fun_len == 2
indicator_df = resolver.strategy.advise_indicators(result, metadata=metadata)
assert type(indicator_df) is DataFrame
assert isinstance(indicator_df, DataFrame)
assert 'adx' in indicator_df.columns
buydf = resolver.strategy.advise_buy(result, metadata=metadata)
assert type(buydf) is DataFrame
assert isinstance(buydf, DataFrame)
assert 'buy' in buydf.columns
selldf = resolver.strategy.advise_sell(result, metadata=metadata)
assert type(selldf) is DataFrame
assert isinstance(selldf, DataFrame)
assert 'sell' in selldf

View File

@ -874,6 +874,100 @@ def test_execute_buy(mocker, default_conf, fee, markets, limit_buy_order) -> Non
assert call_args['amount'] == stake_amount / fix_price
def test_add_stoploss_on_exchange(mocker, default_conf, limit_buy_order) -> None:
patch_RPCManager(mocker)
patch_exchange(mocker)
mocker.patch('freqtrade.freqtradebot.FreqtradeBot.handle_trade', MagicMock(return_value=True))
mocker.patch('freqtrade.exchange.Exchange.get_order', return_value=limit_buy_order)
mocker.patch('freqtrade.exchange.Exchange.get_trades_for_order', return_value=[])
mocker.patch('freqtrade.freqtradebot.FreqtradeBot.get_real_amount',
return_value=limit_buy_order['amount'])
stoploss_limit = MagicMock(return_value={'id': 13434334})
mocker.patch('freqtrade.exchange.Exchange.stoploss_limit', stoploss_limit)
freqtrade = FreqtradeBot(default_conf)
freqtrade.strategy.order_types['stoploss_on_exchange'] = True
trade = MagicMock()
trade.open_order_id = None
trade.stoploss_order_id = None
trade.is_open = True
freqtrade.process_maybe_execute_sell(trade)
assert trade.stoploss_order_id == '13434334'
assert stoploss_limit.call_count == 1
assert trade.is_open is True
def test_handle_stoploss_on_exchange(mocker, default_conf, fee, caplog,
markets, limit_buy_order, limit_sell_order) -> None:
stoploss_limit = MagicMock(return_value={'id': 13434334})
patch_RPCManager(mocker)
patch_exchange(mocker)
mocker.patch.multiple(
'freqtrade.exchange.Exchange',
get_ticker=MagicMock(return_value={
'bid': 0.00001172,
'ask': 0.00001173,
'last': 0.00001172
}),
buy=MagicMock(return_value={'id': limit_buy_order['id']}),
sell=MagicMock(return_value={'id': limit_sell_order['id']}),
get_fee=fee,
get_markets=markets,
stoploss_limit=stoploss_limit
)
freqtrade = FreqtradeBot(default_conf)
patch_get_signal(freqtrade)
# First case: when stoploss is not yet set but the order is open
# should get the stoploss order id immediately
# and should return false as no trade actually happened
trade = MagicMock()
trade.is_open = True
trade.open_order_id = None
trade.stoploss_order_id = None
assert freqtrade.handle_stoploss_on_exchange(trade) is False
assert stoploss_limit.call_count == 1
assert trade.stoploss_order_id == "13434334"
# Second case: when stoploss is set but it is not yet hit
# should do nothing and return false
trade.is_open = True
trade.open_order_id = None
trade.stoploss_order_id = 100
hanging_stoploss_order = MagicMock(return_value={'status': 'open'})
mocker.patch('freqtrade.exchange.Exchange.get_order', hanging_stoploss_order)
assert freqtrade.handle_stoploss_on_exchange(trade) is False
assert trade.stoploss_order_id == 100
# Third case: when stoploss is set and it is hit
# should unset stoploss_order_id and return true
# as a trade actually happened
freqtrade.create_trade()
trade = Trade.query.first()
trade.is_open = True
trade.open_order_id = None
trade.stoploss_order_id = 100
assert trade
stoploss_order_hit = MagicMock(return_value={
'status': 'closed',
'type': 'stop_loss_limit',
'price': 3,
'average': 2
})
mocker.patch('freqtrade.exchange.Exchange.get_order', stoploss_order_hit)
assert freqtrade.handle_stoploss_on_exchange(trade) is True
assert log_has('STOP_LOSS_LIMIT is hit for {}.'.format(trade), caplog.record_tuples)
assert trade.stoploss_order_id is None
assert trade.is_open is False
def test_process_maybe_execute_buy(mocker, default_conf) -> None:
freqtrade = get_patched_freqtradebot(mocker, default_conf)
@ -1469,8 +1563,9 @@ def test_execute_sell_down_live(default_conf, ticker, fee,
} == last_msg
def test_execute_sell_down_dry_run(default_conf, ticker, fee,
ticker_sell_down, markets, mocker) -> None:
def test_execute_sell_down_stoploss_on_exchange_dry_run(default_conf, ticker, fee,
ticker_sell_down,
markets, mocker) -> None:
rpc_mock = patch_RPCManager(mocker)
mocker.patch.multiple(
'freqtrade.exchange.Exchange',
@ -1495,15 +1590,16 @@ def test_execute_sell_down_dry_run(default_conf, ticker, fee,
)
default_conf['dry_run'] = True
freqtrade.strategy.order_types['stoploss_on_exchange'] = True
# Setting trade stoploss to 0.01
trade.stop_loss = 0.00001099 * 0.99
trade.stop_loss = 0.00001099 * 0.99
freqtrade.execute_sell(trade=trade, limit=ticker_sell_down()['bid'],
sell_reason=SellType.STOP_LOSS)
assert rpc_mock.call_count == 2
last_msg = rpc_mock.call_args_list[-1][0][0]
assert {
'type': RPCMessageType.SELL_NOTIFICATION,
'exchange': 'Bittrex',
@ -1521,6 +1617,129 @@ def test_execute_sell_down_dry_run(default_conf, ticker, fee,
} == last_msg
def test_execute_sell_with_stoploss_on_exchange(default_conf,
ticker, fee, ticker_sell_up,
markets, mocker) -> None:
default_conf['exchange']['name'] = 'binance'
rpc_mock = patch_RPCManager(mocker)
mocker.patch.multiple(
'freqtrade.exchange.Exchange',
_load_markets=MagicMock(return_value={}),
get_ticker=ticker,
get_fee=fee,
get_markets=markets
)
stoploss_limit = MagicMock(return_value={
'id': 123,
'info': {
'foo': 'bar'
}
})
cancel_order = MagicMock(return_value=True)
mocker.patch('freqtrade.exchange.Exchange.symbol_amount_prec', lambda s, x, y: y)
mocker.patch('freqtrade.exchange.Exchange.symbol_price_prec', lambda s, x, y: y)
mocker.patch('freqtrade.exchange.Exchange.stoploss_limit', stoploss_limit)
mocker.patch('freqtrade.exchange.Exchange.cancel_order', cancel_order)
freqtrade = FreqtradeBot(default_conf)
freqtrade.strategy.order_types['stoploss_on_exchange'] = True
patch_get_signal(freqtrade)
# Create some test data
freqtrade.create_trade()
trade = Trade.query.first()
assert trade
freqtrade.process_maybe_execute_sell(trade)
# Increase the price and sell it
mocker.patch.multiple(
'freqtrade.exchange.Exchange',
get_ticker=ticker_sell_up
)
freqtrade.execute_sell(trade=trade, limit=ticker_sell_up()['bid'],
sell_reason=SellType.SELL_SIGNAL)
trade = Trade.query.first()
assert trade
assert cancel_order.call_count == 1
assert rpc_mock.call_count == 2
def test_may_execute_sell_after_stoploss_on_exchange_hit(default_conf,
ticker, fee,
limit_buy_order,
markets, mocker) -> None:
default_conf['exchange']['name'] = 'binance'
rpc_mock = patch_RPCManager(mocker)
mocker.patch.multiple(
'freqtrade.exchange.Exchange',
_load_markets=MagicMock(return_value={}),
get_ticker=ticker,
get_fee=fee,
get_markets=markets
)
stoploss_limit = MagicMock(return_value={
'id': 123,
'info': {
'foo': 'bar'
}
})
mocker.patch('freqtrade.exchange.Exchange.symbol_amount_prec', lambda s, x, y: y)
mocker.patch('freqtrade.exchange.Exchange.symbol_price_prec', lambda s, x, y: y)
mocker.patch('freqtrade.exchange.Exchange.stoploss_limit', stoploss_limit)
freqtrade = FreqtradeBot(default_conf)
freqtrade.strategy.order_types['stoploss_on_exchange'] = True
patch_get_signal(freqtrade)
# Create some test data
freqtrade.create_trade()
trade = Trade.query.first()
freqtrade.process_maybe_execute_sell(trade)
assert trade
assert trade.stoploss_order_id == '123'
assert trade.open_order_id is None
# Assuming stoploss on exchnage is hit
# stoploss_order_id should become None
# and trade should be sold at the price of stoploss
stoploss_limit_executed = MagicMock(return_value={
"id": "123",
"timestamp": 1542707426845,
"datetime": "2018-11-20T09:50:26.845Z",
"lastTradeTimestamp": None,
"symbol": "BTC/USDT",
"type": "stop_loss_limit",
"side": "sell",
"price": 1.08801,
"amount": 90.99181074,
"cost": 99.0000000032274,
"average": 1.08801,
"filled": 90.99181074,
"remaining": 0.0,
"status": "closed",
"fee": None,
"trades": None
})
mocker.patch('freqtrade.exchange.Exchange.get_order', stoploss_limit_executed)
freqtrade.process_maybe_execute_sell(trade)
assert trade.stoploss_order_id is None
assert trade.is_open is False
print(trade.sell_reason)
assert trade.sell_reason == SellType.STOPLOSS_ON_EXCHANGE.value
assert rpc_mock.call_count == 1
def test_execute_sell_without_conf_sell_up(default_conf, ticker, fee,
ticker_sell_up, markets, mocker) -> None:
rpc_mock = patch_RPCManager(mocker)

View File

@ -426,6 +426,7 @@ def test_migrate_new(mocker, default_conf, fee, caplog):
max_rate FLOAT,
sell_reason VARCHAR,
strategy VARCHAR,
ticker_interval INTEGER,
PRIMARY KEY (id),
CHECK (is_open IN (0, 1))
);"""
@ -471,6 +472,7 @@ def test_migrate_new(mocker, default_conf, fee, caplog):
assert trade.sell_reason is None
assert trade.strategy is None
assert trade.ticker_interval is None
assert trade.stoploss_order_id is None
assert log_has("trying trades_bak1", caplog.record_tuples)
assert log_has("trying trades_bak2", caplog.record_tuples)
assert log_has("Running database migration - backup available as trades_bak2",

View File

@ -1,4 +1,4 @@
ccxt==1.17.556
ccxt==1.17.563
SQLAlchemy==1.2.14
python-telegram-bot==11.1.0
arrow==0.12.1

View File

@ -7,7 +7,7 @@ from pandas import DataFrame
# Add your lib to import here
import talib.abstract as ta
import freqtrade.vendor.qtpylib.indicators as qtpylib
import numpy # noqa
import numpy # noqa
# This class is a sample. Feel free to customize it.
@ -52,7 +52,8 @@ class TestStrategy(IStrategy):
order_types = {
'buy': 'limit',
'sell': 'limit',
'stoploss': 'market'
'stoploss': 'market',
'stoploss_on_exchange': False
}
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame: