use native python logger
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@@ -10,7 +10,7 @@ Optional Cli parameters
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--timerange: specify what timerange of data to use.
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-l / --live: Live, to download the latest ticker for the pair
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"""
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import logging
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import sys
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from argparse import Namespace
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from os import path
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@@ -22,13 +22,12 @@ import gzip
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from freqtrade.arguments import Arguments
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from freqtrade import misc
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from freqtrade.logger import Logger
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from pandas import DataFrame
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from freqtrade.constants import Constants
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import dateutil.parser
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logger = Logger(name="freqtrade").get_logger()
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logger = logging.getLogger('freqtrade')
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def load_old_file(filename) -> (List[Dict], bool):
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@@ -11,7 +11,7 @@ Optional Cli parameters
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--timerange: specify what timerange of data to use.
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-l / --live: Live, to download the latest ticker for the pair
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"""
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import logging
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import sys
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from argparse import Namespace
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@@ -24,11 +24,10 @@ import plotly.graph_objs as go
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from freqtrade.arguments import Arguments
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from freqtrade.analyze import Analyze
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from freqtrade import exchange
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from freqtrade.logger import Logger
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import freqtrade.optimize as optimize
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logger = Logger(name="Graph dataframe").get_logger()
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logger = logging.getLogger('freqtrade')
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def plot_analyzed_dataframe(args: Namespace) -> None:
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@@ -10,7 +10,7 @@ Optional Cli parameters
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-s / --strategy: strategy to use
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--timerange: specify what timerange of data to use.
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"""
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import logging
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import sys
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import json
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from argparse import Namespace
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@@ -24,14 +24,13 @@ import plotly.graph_objs as go
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from freqtrade.arguments import Arguments
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from freqtrade.configuration import Configuration
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from freqtrade.analyze import Analyze
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from freqtrade.logger import Logger
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from freqtrade.constants import Constants
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import freqtrade.optimize as optimize
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import freqtrade.misc as misc
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logger = Logger(name="Graph profits").get_logger()
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logger = logging.getLogger('freqtrade')
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# data:: [ pair, profit-%, enter, exit, time, duration]
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