270 lines
8.6 KiB
Python
Executable File
270 lines
8.6 KiB
Python
Executable File
#!/usr/bin/env python3
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"""
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Script to display when the bot will buy on specific pair(s)
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Mandatory Cli parameters:
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-p / --pairs: pair(s) to examine
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Option but recommended
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-s / --strategy: strategy to use
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Optional Cli parameters
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-d / --datadir: path to pair(s) backtest data
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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(s)
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-db / --db-url: Show trades stored in database
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Indicators recommended
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Row 1: sma, ema3, ema5, ema10, ema50
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Row 3: macd, rsi, fisher_rsi, mfi, slowd, slowk, fastd, fastk
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Example of usage:
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> python3 scripts/plot_dataframe.py --pairs BTC/EUR,XRP/BTC -d user_data/data/
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--indicators1 sma,ema3 --indicators2 fastk,fastd
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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 pathlib import Path
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from typing import Any, Dict, List
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import pandas as pd
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import pytz
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from freqtrade import persistence
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from freqtrade.arguments import Arguments, TimeRange
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from freqtrade.data import history
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from freqtrade.data.btanalysis import BT_DATA_COLUMNS, load_backtest_data
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from freqtrade.plot.plotting import generate_graph, generate_plot_file
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from freqtrade.exchange import Exchange
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from freqtrade.optimize import setup_configuration
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from freqtrade.persistence import Trade
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from freqtrade.resolvers import StrategyResolver
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from freqtrade.state import RunMode
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logger = logging.getLogger(__name__)
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_CONF: Dict[str, Any] = {}
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timeZone = pytz.UTC
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def load_trades(db_url: str = None, exportfilename: str = None) -> pd.DataFrame:
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"""
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Load trades, either from a DB (using dburl) or via a backtest export file.
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:param db_url: Sqlite url (default format sqlite:///tradesv3.dry-run.sqlite)
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:param exportfilename: Path to a file exported from backtesting
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:returns: Dataframe containing Trades
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"""
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# TODO: Document and move to btanalysis
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trades: pd.DataFrame = pd.DataFrame([], columns=BT_DATA_COLUMNS)
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if db_url:
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persistence.init(db_url, clean_open_orders=False)
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columns = ["pair", "profit", "open_time", "close_time",
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"open_rate", "close_rate", "duration"]
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for x in Trade.query.all():
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logger.info("date: {}".format(x.open_date))
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trades = pd.DataFrame([(t.pair, t.calc_profit(),
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t.open_date.replace(tzinfo=timeZone),
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t.close_date.replace(tzinfo=timeZone) if t.close_date else None,
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t.open_rate, t.close_rate,
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t.close_date.timestamp() - t.open_date.timestamp()
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if t.close_date else None)
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for t in Trade.query.all()],
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columns=columns)
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elif exportfilename:
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file = Path(exportfilename)
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if file.exists():
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trades = load_backtest_data(file)
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return trades
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def get_trading_env(args: Namespace):
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"""
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Initalize freqtrade Exchange and Strategy, split pairs recieved in parameter
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:return: Strategy
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"""
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global _CONF
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# Load the configuration
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_CONF.update(setup_configuration(args, RunMode.BACKTEST))
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pairs = args.pairs.split(',')
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if pairs is None:
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logger.critical('Parameter --pairs mandatory;. E.g --pairs ETH/BTC,XRP/BTC')
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exit()
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# Load the strategy
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try:
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strategy = StrategyResolver(_CONF).strategy
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exchange = Exchange(_CONF)
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except AttributeError:
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logger.critical(
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'Impossible to load the strategy. Please check the file "user_data/strategies/%s.py"',
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args.strategy
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)
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exit()
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return [strategy, exchange, pairs]
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def get_tickers_data(strategy, exchange, pairs: List[str], timerange: TimeRange, live: bool):
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"""
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Get tickers data for each pairs on live or local, option defined in args
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:return: dictionary of tickers. output format: {'pair': tickersdata}
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"""
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ticker_interval = strategy.ticker_interval
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tickers = history.load_data(
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datadir=Path(str(_CONF.get("datadir"))),
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pairs=pairs,
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ticker_interval=ticker_interval,
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refresh_pairs=_CONF.get('refresh_pairs', False),
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timerange=timerange,
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exchange=Exchange(_CONF),
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live=live,
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)
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# No ticker found, impossible to download, len mismatch
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for pair, data in tickers.copy().items():
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logger.debug("checking tickers data of pair: %s", pair)
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logger.debug("data.empty: %s", data.empty)
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logger.debug("len(data): %s", len(data))
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if data.empty:
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del tickers[pair]
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logger.info(
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'An issue occured while retreiving data of %s pair, please retry '
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'using -l option for live or --refresh-pairs-cached', pair)
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return tickers
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def generate_dataframe(strategy, tickers, pair) -> pd.DataFrame:
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"""
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Get tickers then Populate strategy indicators and signals, then return the full dataframe
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:return: the DataFrame of a pair
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"""
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dataframes = strategy.tickerdata_to_dataframe(tickers)
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dataframe = dataframes[pair]
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dataframe = strategy.advise_buy(dataframe, {'pair': pair})
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dataframe = strategy.advise_sell(dataframe, {'pair': pair})
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return dataframe
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def extract_trades_of_period(dataframe, trades) -> pd.DataFrame:
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"""
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Compare trades and backtested pair DataFrames to get trades performed on backtested period
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:return: the DataFrame of a trades of period
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"""
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# TODO: Document and move to btanalysis (?)
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trades = trades.loc[(trades['open_time'] >= dataframe.iloc[0]['date']) &
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(trades['close_time'] <= dataframe.iloc[-1]['date'])]
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return trades
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def analyse_and_plot_pairs(args: Namespace):
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"""
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From arguments provided in cli:
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-Initialise backtest env
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-Get tickers data
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-Generate Dafaframes populated with indicators and signals
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-Load trades excecuted on same periods
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-Generate Plotly plot objects
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-Generate plot files
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:return: None
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"""
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strategy, exchange, pairs = get_trading_env(args)
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# Set timerange to use
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timerange = Arguments.parse_timerange(args.timerange)
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ticker_interval = strategy.ticker_interval
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tickers = get_tickers_data(strategy, exchange, pairs, timerange, args.live)
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pair_counter = 0
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for pair, data in tickers.items():
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pair_counter += 1
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logger.info("analyse pair %s", pair)
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tickers = {}
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tickers[pair] = data
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dataframe = generate_dataframe(strategy, tickers, pair)
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trades = load_trades(db_url=args.db_url,
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exportfilename=args.exportfilename)
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trades = trades.loc[trades['pair'] == pair]
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trades = extract_trades_of_period(dataframe, trades)
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fig = generate_graph(
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pair=pair,
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data=dataframe,
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trades=trades,
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indicators1=args.indicators1.split(","),
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indicators2=args.indicators2.split(",")
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)
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generate_plot_file(fig, pair, ticker_interval)
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logger.info('End of ploting process %s plots generated', pair_counter)
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def plot_parse_args(args: List[str]) -> Namespace:
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"""
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Parse args passed to the script
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:param args: Cli arguments
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:return: args: Array with all arguments
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"""
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arguments = Arguments(args, 'Graph dataframe')
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arguments.scripts_options()
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arguments.parser.add_argument(
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'--indicators1',
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help='Set indicators from your strategy you want in the first row of the graph. Separate '
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'them with a coma. E.g: ema3,ema5 (default: %(default)s)',
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type=str,
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default='sma,ema3,ema5',
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dest='indicators1',
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)
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arguments.parser.add_argument(
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'--indicators2',
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help='Set indicators from your strategy you want in the third row of the graph. Separate '
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'them with a coma. E.g: fastd,fastk (default: %(default)s)',
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type=str,
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default='macd,macdsignal',
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dest='indicators2',
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)
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arguments.parser.add_argument(
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'--plot-limit',
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help='Specify tick limit for plotting - too high values cause huge files - '
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'Default: %(default)s',
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dest='plot_limit',
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default=750,
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type=int,
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)
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arguments.common_args_parser()
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arguments.optimizer_shared_options(arguments.parser)
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arguments.backtesting_options(arguments.parser)
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return arguments.parse_args()
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def main(sysargv: List[str]) -> None:
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"""
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This function will initiate the bot and start the trading loop.
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:return: None
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"""
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logger.info('Starting Plot Dataframe')
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analyse_and_plot_pairs(
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plot_parse_args(sysargv)
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)
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exit()
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if __name__ == '__main__':
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main(sys.argv[1:])
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