Address points stated in comments

This commit is contained in:
hroff-1902 2020-02-15 20:43:11 +03:00
parent fdd362299f
commit 6139239b86
3 changed files with 14 additions and 89 deletions

View File

@ -41,18 +41,21 @@ def start_list_exchanges(args: Dict[str, Any]) -> None:
def _print_objs_tabular(objs: List, print_colorized: bool) -> None: def _print_objs_tabular(objs: List, print_colorized: bool) -> None:
if print_colorized: if print_colorized:
colorama_init(autoreset=True) colorama_init(autoreset=True)
red = Fore.RED
yellow = Fore.YELLOW
reset = Style.RESET_ALL
else:
red = ''
yellow = ''
reset = ''
names = [s['name'] for s in objs] names = [s['name'] for s in objs]
objss_to_print = [{ objss_to_print = [{
'name': s['name'] if s['name'] else "--", 'name': s['name'] if s['name'] else "--",
'location': s['location'].name, 'location': s['location'].name,
'status': (((Fore.RED if print_colorized else '') + 'status': (red + "LOAD FAILED" + reset if s['class'] is None
"LOAD FAILED" + (Style.RESET_ALL if print_colorized else ''))
if s['class'] is None
else "OK" if names.count(s['name']) == 1 else "OK" if names.count(s['name']) == 1
else ((Fore.YELLOW if print_colorized else '') + else yellow + "DUPLICATE NAME" + reset)
"DUPLICATE NAME" +
(Style.RESET_ALL if print_colorized else '')))
} for s in objs] } for s in objs]
print(tabulate(objss_to_print, headers='keys', tablefmt='pipe')) print(tabulate(objss_to_print, headers='keys', tablefmt='pipe'))

View File

@ -87,7 +87,7 @@ class IResolver:
continue continue
module_path = entry.resolve() module_path = entry.resolve()
obj = next(cls._get_valid_object(module_path, object_name), None) # noqa obj = next(cls._get_valid_object(module_path, object_name), None)
if obj: if obj:
return (obj, module_path) return (obj, module_path)

View File

@ -1,87 +1,9 @@
# The strategy which fails to load due to non-existent dependency
# --- Do not remove these libs ---
from freqtrade.strategy.interface import IStrategy
from pandas import DataFrame
# --------------------------------
# Add your lib to import here
import talib.abstract as ta
import nonexiting_module # noqa import nonexiting_module # noqa
from freqtrade.strategy.interface import IStrategy
# This class is a sample. Feel free to customize it.
class TestStrategyLegacy(IStrategy): class TestStrategyLegacy(IStrategy):
""" pass
This is a test strategy using the legacy function headers, which will be
removed in a future update.
Please do not use this as a template, but refer to user_data/strategy/sample_strategy.py
for a uptodate version of this template.
"""
# Minimal ROI designed for the strategy.
# This attribute will be overridden if the config file contains "minimal_roi"
minimal_roi = {
"40": 0.0,
"30": 0.01,
"20": 0.02,
"0": 0.04
}
# Optimal stoploss designed for the strategy
# This attribute will be overridden if the config file contains "stoploss"
stoploss = -0.10
# Optimal ticker interval for the strategy
ticker_interval = '5m'
def populate_indicators(self, dataframe: DataFrame) -> DataFrame:
"""
Adds several different TA indicators to the given DataFrame
Performance Note: For the best performance be frugal on the number of indicators
you are using. Let uncomment only the indicator you are using in your strategies
or your hyperopt configuration, otherwise you will waste your memory and CPU usage.
"""
# Momentum Indicator
# ------------------------------------
# ADX
dataframe['adx'] = ta.ADX(dataframe)
# TEMA - Triple Exponential Moving Average
dataframe['tema'] = ta.TEMA(dataframe, timeperiod=9)
return dataframe
def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:
"""
Based on TA indicators, populates the buy signal for the given dataframe
:param dataframe: DataFrame
:return: DataFrame with buy column
"""
dataframe.loc[
(
(dataframe['adx'] > 30) &
(dataframe['tema'] > dataframe['tema'].shift(1)) &
(dataframe['volume'] > 0)
),
'buy'] = 1
return dataframe
def populate_sell_trend(self, dataframe: DataFrame) -> DataFrame:
"""
Based on TA indicators, populates the sell signal for the given dataframe
:param dataframe: DataFrame
:return: DataFrame with buy column
"""
dataframe.loc[
(
(dataframe['adx'] > 70) &
(dataframe['tema'] < dataframe['tema'].shift(1)) &
(dataframe['volume'] > 0)
),
'sell'] = 1
return dataframe