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rename to buy_tag

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This commit is contained in:
kevinjulian
2021-07-21 20:05:35 +07:00
parent db1e676639
commit 49886874aa
15 changed files with 47 additions and 47 deletions
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2
freqtrade/data/btanalysis.py
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@@ -30,7 +30,7 @@ BT_DATA_COLUMNS = ['pair', 'stake_amount', 'amount', 'open_date', 'close_date',
'fee_open', 'fee_close', 'trade_duration',
'profit_ratio', 'profit_abs', 'sell_reason',
'initial_stop_loss_abs', 'initial_stop_loss_ratio', 'stop_loss_abs',
'stop_loss_ratio', 'min_rate', 'max_rate', 'is_open', 'buy_signal_name']
'stop_loss_ratio', 'min_rate', 'max_rate', 'is_open', 'buy_tag']
def get_latest_optimize_filename(directory: Union[Path, str], variant: str) -> str:

2
freqtrade/enums/__init__.py
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@@ -3,5 +3,5 @@ from freqtrade.enums.backteststate import BacktestState
from freqtrade.enums.rpcmessagetype import RPCMessageType
from freqtrade.enums.runmode import NON_UTIL_MODES, OPTIMIZE_MODES, TRADING_MODES, RunMode
from freqtrade.enums.selltype import SellType
from freqtrade.enums.signaltype import SignalNameType, SignalType
from freqtrade.enums.signaltype import SignalTagType, SignalType
from freqtrade.enums.state import State

4
freqtrade/enums/signaltype.py
View File

@@ -9,8 +9,8 @@ class SignalType(Enum):
SELL = "sell"
class SignalNameType(Enum):
class SignalTagType(Enum):
"""
Enum for signal columns
"""
BUY_SIGNAL_NAME = "buy_signal_name"
BUY_TAG = "buy_tag"

12
freqtrade/freqtradebot.py
View File

@@ -420,7 +420,7 @@ class FreqtradeBot(LoggingMixin):
return False
# running get_signal on historical data fetched
(buy, sell, buy_signal_name) = self.strategy.get_signal(
(buy, sell, buy_tag) = self.strategy.get_signal(
pair,
self.strategy.timeframe,
analyzed_df
@@ -431,13 +431,13 @@ class FreqtradeBot(LoggingMixin):
bid_check_dom = self.config.get('bid_strategy', {}).get('check_depth_of_market', {})
if ((bid_check_dom.get('enabled', False)) and
(bid_check_dom.get('bids_to_ask_delta', 0) > 0)):
(bid_check_dom.get('bids_to_ask_delta', 0) > 0)):
if self._check_depth_of_market_buy(pair, bid_check_dom):
return self.execute_buy(pair, stake_amount, buy_signal_name=buy_signal_name)
return self.execute_buy(pair, stake_amount, buy_tag=buy_tag)
else:
return False
return self.execute_buy(pair, stake_amount, buy_signal_name=buy_signal_name)
return self.execute_buy(pair, stake_amount, buy_tag=buy_tag)
else:
return False
@@ -466,7 +466,7 @@ class FreqtradeBot(LoggingMixin):
return False
def execute_buy(self, pair: str, stake_amount: float, price: Optional[float] = None,
forcebuy: bool = False, buy_signal_name: str = '') -> bool:
forcebuy: bool = False, buy_tag: str = '') -> bool:
"""
Executes a limit buy for the given pair
:param pair: pair for which we want to create a LIMIT_BUY
@@ -569,7 +569,7 @@ class FreqtradeBot(LoggingMixin):
exchange=self.exchange.id,
open_order_id=order_id,
strategy=self.strategy.get_strategy_name(),
buy_signal_name=buy_signal_name,
buy_tag=buy_tag,
timeframe=timeframe_to_minutes(self.config['timeframe'])
)
trade.orders.append(order_obj)

12
freqtrade/optimize/backtesting.py
View File

@@ -43,7 +43,7 @@ CLOSE_IDX = 3
SELL_IDX = 4
LOW_IDX = 5
HIGH_IDX = 6
BUY_SIGNAL_NAME_IDX = 7
buy_tag_IDX = 7
class Backtesting:
@@ -210,7 +210,7 @@ class Backtesting:
"""
# Every change to this headers list must evaluate further usages of the resulting tuple
# and eventually change the constants for indexes at the top
headers = ['date', 'buy', 'open', 'close', 'sell', 'low', 'high', 'buy_signal_name']
headers = ['date', 'buy', 'open', 'close', 'sell', 'low', 'high', 'buy_tag']
data: Dict = {}
self.progress.init_step(BacktestState.CONVERT, len(processed))
@@ -221,7 +221,7 @@ class Backtesting:
if not pair_data.empty:
pair_data.loc[:, 'buy'] = 0 # cleanup if buy_signal is exist
pair_data.loc[:, 'sell'] = 0 # cleanup if sell_signal is exist
pair_data.loc[:, 'buy_signal_name'] = '' # cleanup if buy_signal_name is exist
pair_data.loc[:, 'buy_tag'] = '' # cleanup if buy_tag is exist
df_analyzed = self.strategy.advise_sell(
self.strategy.advise_buy(pair_data, {'pair': pair}), {'pair': pair})[headers].copy()
@@ -230,7 +230,7 @@ class Backtesting:
# from the previous candle
df_analyzed.loc[:, 'buy'] = df_analyzed.loc[:, 'buy'].shift(1)
df_analyzed.loc[:, 'sell'] = df_analyzed.loc[:, 'sell'].shift(1)
df_analyzed.loc[:, 'buy_signal_name'] = df_analyzed.loc[:, 'buy_signal_name'].shift(1)
df_analyzed.loc[:, 'buy_tag'] = df_analyzed.loc[:, 'buy_tag'].shift(1)
df_analyzed.drop(df_analyzed.head(1).index, inplace=True)
@@ -265,7 +265,7 @@ class Backtesting:
# Worst case: price reaches stop_positive_offset and dives down.
stop_rate = (sell_row[OPEN_IDX] *
(1 + abs(self.strategy.trailing_stop_positive_offset) -
abs(self.strategy.trailing_stop_positive)))
abs(self.strategy.trailing_stop_positive)))
else:
# Worst case: price ticks tiny bit above open and dives down.
stop_rate = sell_row[OPEN_IDX] * (1 - abs(trade.stop_loss_pct))
@@ -370,7 +370,7 @@ class Backtesting:
fee_open=self.fee,
fee_close=self.fee,
is_open=True,
buy_signal_name=row[BUY_SIGNAL_NAME_IDX],
buy_tag=row[buy_tag_IDX],
exchange='backtesting',
)
return trade

8
freqtrade/persistence/migrations.py
View File

@@ -47,7 +47,7 @@ def migrate_trades_table(decl_base, inspector, engine, table_back_name: str, col
min_rate = get_column_def(cols, 'min_rate', 'null')
sell_reason = get_column_def(cols, 'sell_reason', 'null')
strategy = get_column_def(cols, 'strategy', 'null')
buy_signal_name = get_column_def(cols, 'buy_signal_name', 'null')
buy_tag = get_column_def(cols, 'buy_tag', 'null')
# If ticker-interval existed use that, else null.
if has_column(cols, 'ticker_interval'):
timeframe = get_column_def(cols, 'timeframe', 'ticker_interval')
@@ -81,7 +81,7 @@ def migrate_trades_table(decl_base, inspector, engine, table_back_name: str, col
stake_amount, amount, amount_requested, open_date, close_date, open_order_id,
stop_loss, stop_loss_pct, initial_stop_loss, initial_stop_loss_pct,
stoploss_order_id, stoploss_last_update,
max_rate, min_rate, sell_reason, sell_order_status, strategy, buy_signal_name,
max_rate, min_rate, sell_reason, sell_order_status, strategy, buy_tag,
timeframe, open_trade_value, close_profit_abs
)
select id, lower(exchange),
@@ -104,7 +104,7 @@ def migrate_trades_table(decl_base, inspector, engine, table_back_name: str, col
{stoploss_order_id} stoploss_order_id, {stoploss_last_update} stoploss_last_update,
{max_rate} max_rate, {min_rate} min_rate, {sell_reason} sell_reason,
{sell_order_status} sell_order_status,
{strategy} strategy, {buy_signal_name} buy_signal_name, {timeframe} timeframe,
{strategy} strategy, {buy_tag} buy_tag, {timeframe} timeframe,
{open_trade_value} open_trade_value, {close_profit_abs} close_profit_abs
from {table_back_name}
"""))
@@ -168,7 +168,7 @@ def check_migrate(engine, decl_base, previous_tables) -> None:
inspector = inspect(engine)
cols = inspector.get_columns('trades')
if not has_column(cols, 'buy_signal_name'):
if not has_column(cols, 'buy_tag'):
logger.info(f'Running database migration for trades - backup: {table_back_name}')
migrate_trades_table(decl_base, inspector, engine, table_back_name, cols)
# Reread columns - the above recreated the table!

8
freqtrade/persistence/models.py
View File

@@ -257,7 +257,7 @@ class LocalTrade():
sell_reason: str = ''
sell_order_status: str = ''
strategy: str = ''
buy_signal_name: str = ''
buy_tag: str = ''
timeframe: Optional[int] = None
def __init__(self, **kwargs):
@@ -289,7 +289,7 @@ class LocalTrade():
'amount_requested': round(self.amount_requested, 8) if self.amount_requested else None,
'stake_amount': round(self.stake_amount, 8),
'strategy': self.strategy,
'buy_signal_name': self.buy_signal_name,
'buy_tag': self.buy_tag,
'timeframe': self.timeframe,
'fee_open': self.fee_open,
@@ -638,7 +638,7 @@ class LocalTrade():
# skip case if trailing-stop changed the stoploss already.
if (trade.stop_loss == trade.initial_stop_loss
and trade.initial_stop_loss_pct != desired_stoploss):
and trade.initial_stop_loss_pct != desired_stoploss):
# Stoploss value got changed
logger.info(f"Stoploss for {trade} needs adjustment...")
@@ -705,7 +705,7 @@ class Trade(_DECL_BASE, LocalTrade):
sell_reason = Column(String(100), nullable=True)
sell_order_status = Column(String(100), nullable=True)
strategy = Column(String(100), nullable=True)
buy_signal_name = Column(String(100), nullable=True)
buy_tag = Column(String(100), nullable=True)
timeframe = Column(Integer, nullable=True)
def __init__(self, **kwargs):

12
freqtrade/strategy/interface.py
View File

@@ -13,7 +13,7 @@ from pandas import DataFrame
from freqtrade.constants import ListPairsWithTimeframes
from freqtrade.data.dataprovider import DataProvider
from freqtrade.enums import SellType, SignalNameType, SignalType
from freqtrade.enums import SellType, SignalTagType, SignalType
from freqtrade.exceptions import OperationalException, StrategyError
from freqtrade.exchange import timeframe_to_minutes, timeframe_to_seconds
from freqtrade.exchange.exchange import timeframe_to_next_date
@@ -422,7 +422,7 @@ class IStrategy(ABC, HyperStrategyMixin):
logger.debug("Skipping TA Analysis for already analyzed candle")
dataframe['buy'] = 0
dataframe['sell'] = 0
dataframe['buy_signal_name'] = ''
dataframe['buy_tag'] = ''
# Other Defs in strategy that want to be called every loop here
# twitter_sell = self.watch_twitter_feed(dataframe, metadata)
@@ -525,9 +525,9 @@ class IStrategy(ABC, HyperStrategyMixin):
)
return False, False, ''
(buy, sell, buy_signal_name) = latest[SignalType.BUY.value] == 1,\
(buy, sell, buy_tag) = latest[SignalType.BUY.value] == 1,\
latest[SignalType.SELL.value] == 1,\
latest.get(SignalNameType.BUY_SIGNAL_NAME.value, '')
latest.get(SignalTagType.BUY_TAG.value, '')
logger.debug('trigger: %s (pair=%s) buy=%s sell=%s',
latest['date'], pair, str(buy), str(sell))
timeframe_seconds = timeframe_to_seconds(timeframe)
@@ -535,8 +535,8 @@ class IStrategy(ABC, HyperStrategyMixin):
current_time=datetime.now(timezone.utc),
timeframe_seconds=timeframe_seconds,
buy=buy):
return False, sell, buy_signal_name
return buy, sell, buy_signal_name
return False, sell, buy_tag
return buy, sell, buy_tag
def ignore_expired_candle(self, latest_date: datetime, current_time: datetime,
timeframe_seconds: int, buy: bool):