From 22e7ad8ec1e476e4190a38e18e28a020b4f8530d Mon Sep 17 00:00:00 2001 From: Matthias Date: Fri, 25 Jan 2019 06:42:29 +0100 Subject: [PATCH] Change back to LF lineendings --- scripts/plot_dataframe.py | 920 +++++++++++++++++++------------------- 1 file changed, 460 insertions(+), 460 deletions(-) diff --git a/scripts/plot_dataframe.py b/scripts/plot_dataframe.py index b1c792a22..bb9c04206 100755 --- a/scripts/plot_dataframe.py +++ b/scripts/plot_dataframe.py @@ -1,460 +1,460 @@ -#!/usr/bin/env python3 -""" -Script to display when the bot will buy on specific pair(s) - -Mandatory Cli parameters: --p / --pairs: pair(s) to examine - -Option but recommended --s / --strategy: strategy to use - - -Optional Cli parameters --d / --datadir: path to pair(s) backtest data ---timerange: specify what timerange of data to use. --l / --live: Live, to download the latest ticker for the pair(s) --db / --db-url: Show trades stored in database - - -Indicators recommended -Row 1: sma, ema3, ema5, ema10, ema50 -Row 3: macd, rsi, fisher_rsi, mfi, slowd, slowk, fastd, fastk - -Example of usage: -> python3 scripts/plot_dataframe.py --pairs BTC/EUR,XRP/BTC -d user_data/data/ --indicators1 sma,ema3 ---indicators2 fastk,fastd -""" -import json -import logging -import sys -import os -from argparse import Namespace -from pathlib import Path -from typing import Dict, List, Any - -import pandas as pd -import plotly.graph_objs as go -import pytz - -from plotly import tools -from plotly.offline import plot - -from freqtrade import persistence -from freqtrade.arguments import Arguments, TimeRange -from freqtrade.data import history -from freqtrade.exchange import Exchange -from freqtrade.optimize.backtesting import setup_configuration -from freqtrade.persistence import Trade -from freqtrade.resolvers import StrategyResolver - -logger = logging.getLogger(__name__) -_CONF: Dict[str, Any] = {} - -timeZone = pytz.UTC - - -def load_trades(args: Namespace, pair: str, timerange: TimeRange) -> pd.DataFrame: - trades: pd.DataFrame = pd.DataFrame() - if args.db_url: - persistence.init(_CONF) - columns = ["pair", "profit", "opents", "closets", "open_rate", "close_rate", "duration"] - - for x in Trade.query.all(): - print("date: {}".format(x.open_date)) - - trades = pd.DataFrame([(t.pair, t.calc_profit(), - t.open_date.replace(tzinfo=timeZone), - t.close_date.replace(tzinfo=timeZone) if t.close_date else None, - t.open_rate, t.close_rate, - t.close_date.timestamp() - t.open_date.timestamp() - if t.close_date else None) - for t in Trade.query.filter(Trade.pair.is_(pair)).all()], - columns=columns) - - elif args.exportfilename: - file = Path(args.exportfilename) - # must align with columns in backtest.py - columns = ["pair", "profit", "opents", "closets", "index", "duration", - "open_rate", "close_rate", "open_at_end", "sell_reason"] - if os.path.exists(file): - with file.open() as f: - data = json.load(f) - trades = pd.DataFrame(data, columns=columns) - trades = trades.loc[trades["pair"] == pair] - if timerange: - if timerange.starttype == 'date': - trades = trades.loc[trades["opents"] >= timerange.startts] - if timerange.stoptype == 'date': - trades = trades.loc[trades["opents"] <= timerange.stopts] - - trades['opents'] = pd.to_datetime( - trades['opents'], - unit='s', - utc=True, - infer_datetime_format=True) - trades['closets'] = pd.to_datetime( - trades['closets'], - unit='s', - utc=True, - infer_datetime_format=True) - else: - trades = pd.DataFrame([], columns=columns) - - return trades - - -def generate_plot_file(fig, pair, tick_interval, is_last) -> None: - """ - Generate a plot html file from pre populated fig plotly object - :return: None - """ - logger.info('Generate plot file for %s', pair) - - pair_name = pair.replace("/", "_") - file_name = 'freqtrade-plot-' + pair_name + '-' + tick_interval + '.html' - - if not os.path.exists('user_data/plots'): - try: - os.makedirs('user_data/plots') - except OSError as e: - raise - - plot(fig, filename=str(Path('user_data/plots').joinpath(file_name)), auto_open=False) - if is_last: - plot(fig, filename=str(Path('user_data').joinpath('freqtrade-plot.html')), auto_open=False) - - -def get_trading_env(args: Namespace): - """ - Initalize freqtrade Exchange and Strategy, split pairs recieved in parameter - :return: Strategy - """ - global _CONF - - # Load the configuration - _CONF.update(setup_configuration(args)) - print(_CONF) - - pairs = args.pairs.split(',') - if pairs is None: - logger.critical('Parameter --pairs mandatory;. E.g --pairs ETH/BTC,XRP/BTC') - exit() - - # Load the strategy - try: - strategy = StrategyResolver(_CONF).strategy - exchange = Exchange(_CONF) - except AttributeError: - logger.critical( - 'Impossible to load the strategy. Please check the file "user_data/strategies/%s.py"', - args.strategy - ) - exit() - - return [strategy, exchange, pairs] - - -def get_tickers_data(strategy, exchange, pairs: List[str], args): - """ - Get tickers data for each pairs on live or local, option defined in args - :return: dictinnary of tickers. output format: {'pair': tickersdata} - """ - - tick_interval = strategy.ticker_interval - timerange = Arguments.parse_timerange(args.timerange) - - tickers = {} - if args.live: - logger.info('Downloading pairs.') - exchange.refresh_tickers(pairs, tick_interval) - for pair in pairs: - tickers[pair] = exchange.klines(pair) - else: - tickers = history.load_data( - datadir=Path(_CONF.get("datadir")), - pairs=pairs, - ticker_interval=tick_interval, - refresh_pairs=_CONF.get('refresh_pairs', False), - timerange=timerange, - exchange=Exchange(_CONF) - ) - - # No ticker found, impossible to download, len mismatch - for pair, data in tickers.copy().items(): - logger.debug("checking tickers data of pair: %s", pair) - logger.debug("data.empty: %s", data.empty) - logger.debug("len(data): %s", len(data)) - if data.empty: - del tickers[pair] - logger.info( - 'An issue occured while retreiving datas of %s pair, please retry ' - 'using -l option for live or --refresh-pairs-cached', pair) - return tickers - - -def generate_dataframe(strategy, tickers, pair) -> pd.DataFrame: - """ - Get tickers then Populate strategy indicators and signals, then return the full dataframe - :return: the DataFrame of a pair - """ - - dataframes = strategy.tickerdata_to_dataframe(tickers) - dataframe = dataframes[pair] - dataframe = strategy.advise_buy(dataframe, {'pair': pair}) - dataframe = strategy.advise_sell(dataframe, {'pair': pair}) - - return dataframe - - -def extract_trades_of_period(dataframe, trades) -> pd.DataFrame: - """ - Compare trades and backtested pair DataFrames to get trades performed on backtested period - :return: the DataFrame of a trades of period - """ - trades = trades.loc[trades['opents'] >= dataframe.iloc[0]['date']] - return trades - - -def generate_graph(pair, trades: pd.DataFrame, data: pd.DataFrame, args) -> tools.make_subplots: - """ - Generate the graph from the data generated by Backtesting or from DB - :param pair: Pair to Display on the graph - :param trades: All trades created - :param data: Dataframe - :param args: sys.argv that contrains the two params indicators1, and indicators2 - :return: None - """ - - # Define the graph - fig = tools.make_subplots( - rows=3, - cols=1, - shared_xaxes=True, - row_width=[1, 1, 4], - vertical_spacing=0.0001, - ) - fig['layout'].update(title=pair) - fig['layout']['yaxis1'].update(title='Price') - fig['layout']['yaxis2'].update(title='Volume') - fig['layout']['yaxis3'].update(title='Other') - fig['layout']['xaxis']['rangeslider'].update(visible=False) - - # Common information - candles = go.Candlestick( - x=data.date, - open=data.open, - high=data.high, - low=data.low, - close=data.close, - name='Price' - ) - - df_buy = data[data['buy'] == 1] - buys = go.Scattergl( - x=df_buy.date, - y=df_buy.close, - mode='markers', - name='buy', - marker=dict( - symbol='triangle-up-dot', - size=9, - line=dict(width=1), - color='green', - ) - ) - df_sell = data[data['sell'] == 1] - sells = go.Scattergl( - x=df_sell.date, - y=df_sell.close, - mode='markers', - name='sell', - marker=dict( - symbol='triangle-down-dot', - size=9, - line=dict(width=1), - color='red', - ) - ) - - trade_buys = go.Scattergl( - x=trades["opents"], - y=trades["open_rate"], - mode='markers', - name='trade_buy', - marker=dict( - symbol='square-open', - size=11, - line=dict(width=2), - color='green' - ) - ) - trade_sells = go.Scattergl( - x=trades["closets"], - y=trades["close_rate"], - mode='markers', - name='trade_sell', - marker=dict( - symbol='square-open', - size=11, - line=dict(width=2), - color='red' - ) - ) - - # Row 1 - fig.append_trace(candles, 1, 1) - - if 'bb_lowerband' in data and 'bb_upperband' in data: - bb_lower = go.Scatter( - x=data.date, - y=data.bb_lowerband, - name='BB lower', - line={'color': 'rgba(255,255,255,0)'}, - ) - bb_upper = go.Scatter( - x=data.date, - y=data.bb_upperband, - name='BB upper', - fill="tonexty", - fillcolor="rgba(0,176,246,0.2)", - line={'color': 'rgba(255,255,255,0)'}, - ) - fig.append_trace(bb_lower, 1, 1) - fig.append_trace(bb_upper, 1, 1) - - fig = generate_row(fig=fig, row=1, raw_indicators=args.indicators1, data=data) - fig.append_trace(buys, 1, 1) - fig.append_trace(sells, 1, 1) - fig.append_trace(trade_buys, 1, 1) - fig.append_trace(trade_sells, 1, 1) - - # Row 2 - volume = go.Bar( - x=data['date'], - y=data['volume'], - name='Volume' - ) - fig.append_trace(volume, 2, 1) - - # Row 3 - fig = generate_row(fig=fig, row=3, raw_indicators=args.indicators2, data=data) - - return fig - - -def generate_row(fig, row, raw_indicators, data) -> tools.make_subplots: - """ - Generator all the indicator selected by the user for a specific row - """ - for indicator in raw_indicators.split(','): - if indicator in data: - scattergl = go.Scattergl( - x=data['date'], - y=data[indicator], - name=indicator - ) - fig.append_trace(scattergl, row, 1) - else: - logger.info( - 'Indicator "%s" ignored. Reason: This indicator is not found ' - 'in your strategy.', - indicator - ) - - return fig - - -def plot_parse_args(args: List[str]) -> Namespace: - """ - Parse args passed to the script - :param args: Cli arguments - :return: args: Array with all arguments - """ - arguments = Arguments(args, 'Graph dataframe') - arguments.scripts_options() - arguments.parser.add_argument( - '--indicators1', - help='Set indicators from your strategy you want in the first row of the graph. Separate ' - 'them with a coma. E.g: ema3,ema5 (default: %(default)s)', - type=str, - default='sma,ema3,ema5', - dest='indicators1', - ) - - arguments.parser.add_argument( - '--indicators2', - help='Set indicators from your strategy you want in the third row of the graph. Separate ' - 'them with a coma. E.g: fastd,fastk (default: %(default)s)', - type=str, - default='macd', - dest='indicators2', - ) - arguments.parser.add_argument( - '--plot-limit', - help='Specify tick limit for plotting - too high values cause huge files - ' - 'Default: %(default)s', - dest='plot_limit', - default=750, - type=int, - ) - arguments.common_args_parser() - arguments.optimizer_shared_options(arguments.parser) - arguments.backtesting_options(arguments.parser) - return arguments.parse_args() - - -def analyse_and_plot_pairs(args: Namespace): - """ - From arguments provided in cli: - -Initialise backtest env - -Get tickers data - -Generate Dafaframes populated with indicators and signals - -Load trades excecuted on same periods - -Generate Plotly plot objects - -Generate plot files - :return: None - """ - strategy, exchange, pairs = get_trading_env(args) - # Set timerange to use - timerange = Arguments.parse_timerange(args.timerange) - tick_interval = strategy.ticker_interval - - tickers = get_tickers_data(strategy, exchange, pairs, args) - pair_counter = 0 - for pair, data in tickers.items(): - pair_counter += 1 - logger.info("analyse pair %s", pair) - tickers = {} - tickers[pair] = data - dataframe = generate_dataframe(strategy, tickers, pair) - - trades = load_trades(args, pair, timerange) - trades = extract_trades_of_period(dataframe, trades) - - fig = generate_graph( - pair=pair, - trades=trades, - data=dataframe, - args=args - ) - - is_last = (False, True)[pair_counter == len(tickers)] - generate_plot_file(fig, pair, tick_interval, is_last) - - logger.info('End of ploting process %s plots generated', pair_counter) - - -def main(sysargv: List[str]) -> None: - """ - This function will initiate the bot and start the trading loop. - :return: None - """ - logger.info('Starting Plot Dataframe') - analyse_and_plot_pairs( - plot_parse_args(sysargv) - ) - exit() - - -if __name__ == '__main__': - main(sys.argv[1:]) +#!/usr/bin/env python3 +""" +Script to display when the bot will buy on specific pair(s) + +Mandatory Cli parameters: +-p / --pairs: pair(s) to examine + +Option but recommended +-s / --strategy: strategy to use + + +Optional Cli parameters +-d / --datadir: path to pair(s) backtest data +--timerange: specify what timerange of data to use. +-l / --live: Live, to download the latest ticker for the pair(s) +-db / --db-url: Show trades stored in database + + +Indicators recommended +Row 1: sma, ema3, ema5, ema10, ema50 +Row 3: macd, rsi, fisher_rsi, mfi, slowd, slowk, fastd, fastk + +Example of usage: +> python3 scripts/plot_dataframe.py --pairs BTC/EUR,XRP/BTC -d user_data/data/ --indicators1 sma,ema3 +--indicators2 fastk,fastd +""" +import json +import logging +import sys +import os +from argparse import Namespace +from pathlib import Path +from typing import Dict, List, Any + +import pandas as pd +import plotly.graph_objs as go +import pytz + +from plotly import tools +from plotly.offline import plot + +from freqtrade import persistence +from freqtrade.arguments import Arguments, TimeRange +from freqtrade.data import history +from freqtrade.exchange import Exchange +from freqtrade.optimize.backtesting import setup_configuration +from freqtrade.persistence import Trade +from freqtrade.resolvers import StrategyResolver + +logger = logging.getLogger(__name__) +_CONF: Dict[str, Any] = {} + +timeZone = pytz.UTC + + +def load_trades(args: Namespace, pair: str, timerange: TimeRange) -> pd.DataFrame: + trades: pd.DataFrame = pd.DataFrame() + if args.db_url: + persistence.init(_CONF) + columns = ["pair", "profit", "opents", "closets", "open_rate", "close_rate", "duration"] + + for x in Trade.query.all(): + print("date: {}".format(x.open_date)) + + trades = pd.DataFrame([(t.pair, t.calc_profit(), + t.open_date.replace(tzinfo=timeZone), + t.close_date.replace(tzinfo=timeZone) if t.close_date else None, + t.open_rate, t.close_rate, + t.close_date.timestamp() - t.open_date.timestamp() + if t.close_date else None) + for t in Trade.query.filter(Trade.pair.is_(pair)).all()], + columns=columns) + + elif args.exportfilename: + file = Path(args.exportfilename) + # must align with columns in backtest.py + columns = ["pair", "profit", "opents", "closets", "index", "duration", + "open_rate", "close_rate", "open_at_end", "sell_reason"] + if os.path.exists(file): + with file.open() as f: + data = json.load(f) + trades = pd.DataFrame(data, columns=columns) + trades = trades.loc[trades["pair"] == pair] + if timerange: + if timerange.starttype == 'date': + trades = trades.loc[trades["opents"] >= timerange.startts] + if timerange.stoptype == 'date': + trades = trades.loc[trades["opents"] <= timerange.stopts] + + trades['opents'] = pd.to_datetime( + trades['opents'], + unit='s', + utc=True, + infer_datetime_format=True) + trades['closets'] = pd.to_datetime( + trades['closets'], + unit='s', + utc=True, + infer_datetime_format=True) + else: + trades = pd.DataFrame([], columns=columns) + + return trades + + +def generate_plot_file(fig, pair, tick_interval, is_last) -> None: + """ + Generate a plot html file from pre populated fig plotly object + :return: None + """ + logger.info('Generate plot file for %s', pair) + + pair_name = pair.replace("/", "_") + file_name = 'freqtrade-plot-' + pair_name + '-' + tick_interval + '.html' + + if not os.path.exists('user_data/plots'): + try: + os.makedirs('user_data/plots') + except OSError as e: + raise + + plot(fig, filename=str(Path('user_data/plots').joinpath(file_name)), auto_open=False) + if is_last: + plot(fig, filename=str(Path('user_data').joinpath('freqtrade-plot.html')), auto_open=False) + + +def get_trading_env(args: Namespace): + """ + Initalize freqtrade Exchange and Strategy, split pairs recieved in parameter + :return: Strategy + """ + global _CONF + + # Load the configuration + _CONF.update(setup_configuration(args)) + print(_CONF) + + pairs = args.pairs.split(',') + if pairs is None: + logger.critical('Parameter --pairs mandatory;. E.g --pairs ETH/BTC,XRP/BTC') + exit() + + # Load the strategy + try: + strategy = StrategyResolver(_CONF).strategy + exchange = Exchange(_CONF) + except AttributeError: + logger.critical( + 'Impossible to load the strategy. Please check the file "user_data/strategies/%s.py"', + args.strategy + ) + exit() + + return [strategy, exchange, pairs] + + +def get_tickers_data(strategy, exchange, pairs: List[str], args): + """ + Get tickers data for each pairs on live or local, option defined in args + :return: dictinnary of tickers. output format: {'pair': tickersdata} + """ + + tick_interval = strategy.ticker_interval + timerange = Arguments.parse_timerange(args.timerange) + + tickers = {} + if args.live: + logger.info('Downloading pairs.') + exchange.refresh_tickers(pairs, tick_interval) + for pair in pairs: + tickers[pair] = exchange.klines(pair) + else: + tickers = history.load_data( + datadir=Path(_CONF.get("datadir")), + pairs=pairs, + ticker_interval=tick_interval, + refresh_pairs=_CONF.get('refresh_pairs', False), + timerange=timerange, + exchange=Exchange(_CONF) + ) + + # No ticker found, impossible to download, len mismatch + for pair, data in tickers.copy().items(): + logger.debug("checking tickers data of pair: %s", pair) + logger.debug("data.empty: %s", data.empty) + logger.debug("len(data): %s", len(data)) + if data.empty: + del tickers[pair] + logger.info( + 'An issue occured while retreiving datas of %s pair, please retry ' + 'using -l option for live or --refresh-pairs-cached', pair) + return tickers + + +def generate_dataframe(strategy, tickers, pair) -> pd.DataFrame: + """ + Get tickers then Populate strategy indicators and signals, then return the full dataframe + :return: the DataFrame of a pair + """ + + dataframes = strategy.tickerdata_to_dataframe(tickers) + dataframe = dataframes[pair] + dataframe = strategy.advise_buy(dataframe, {'pair': pair}) + dataframe = strategy.advise_sell(dataframe, {'pair': pair}) + + return dataframe + + +def extract_trades_of_period(dataframe, trades) -> pd.DataFrame: + """ + Compare trades and backtested pair DataFrames to get trades performed on backtested period + :return: the DataFrame of a trades of period + """ + trades = trades.loc[trades['opents'] >= dataframe.iloc[0]['date']] + return trades + + +def generate_graph(pair, trades: pd.DataFrame, data: pd.DataFrame, args) -> tools.make_subplots: + """ + Generate the graph from the data generated by Backtesting or from DB + :param pair: Pair to Display on the graph + :param trades: All trades created + :param data: Dataframe + :param args: sys.argv that contrains the two params indicators1, and indicators2 + :return: None + """ + + # Define the graph + fig = tools.make_subplots( + rows=3, + cols=1, + shared_xaxes=True, + row_width=[1, 1, 4], + vertical_spacing=0.0001, + ) + fig['layout'].update(title=pair) + fig['layout']['yaxis1'].update(title='Price') + fig['layout']['yaxis2'].update(title='Volume') + fig['layout']['yaxis3'].update(title='Other') + fig['layout']['xaxis']['rangeslider'].update(visible=False) + + # Common information + candles = go.Candlestick( + x=data.date, + open=data.open, + high=data.high, + low=data.low, + close=data.close, + name='Price' + ) + + df_buy = data[data['buy'] == 1] + buys = go.Scattergl( + x=df_buy.date, + y=df_buy.close, + mode='markers', + name='buy', + marker=dict( + symbol='triangle-up-dot', + size=9, + line=dict(width=1), + color='green', + ) + ) + df_sell = data[data['sell'] == 1] + sells = go.Scattergl( + x=df_sell.date, + y=df_sell.close, + mode='markers', + name='sell', + marker=dict( + symbol='triangle-down-dot', + size=9, + line=dict(width=1), + color='red', + ) + ) + + trade_buys = go.Scattergl( + x=trades["opents"], + y=trades["open_rate"], + mode='markers', + name='trade_buy', + marker=dict( + symbol='square-open', + size=11, + line=dict(width=2), + color='green' + ) + ) + trade_sells = go.Scattergl( + x=trades["closets"], + y=trades["close_rate"], + mode='markers', + name='trade_sell', + marker=dict( + symbol='square-open', + size=11, + line=dict(width=2), + color='red' + ) + ) + + # Row 1 + fig.append_trace(candles, 1, 1) + + if 'bb_lowerband' in data and 'bb_upperband' in data: + bb_lower = go.Scatter( + x=data.date, + y=data.bb_lowerband, + name='BB lower', + line={'color': 'rgba(255,255,255,0)'}, + ) + bb_upper = go.Scatter( + x=data.date, + y=data.bb_upperband, + name='BB upper', + fill="tonexty", + fillcolor="rgba(0,176,246,0.2)", + line={'color': 'rgba(255,255,255,0)'}, + ) + fig.append_trace(bb_lower, 1, 1) + fig.append_trace(bb_upper, 1, 1) + + fig = generate_row(fig=fig, row=1, raw_indicators=args.indicators1, data=data) + fig.append_trace(buys, 1, 1) + fig.append_trace(sells, 1, 1) + fig.append_trace(trade_buys, 1, 1) + fig.append_trace(trade_sells, 1, 1) + + # Row 2 + volume = go.Bar( + x=data['date'], + y=data['volume'], + name='Volume' + ) + fig.append_trace(volume, 2, 1) + + # Row 3 + fig = generate_row(fig=fig, row=3, raw_indicators=args.indicators2, data=data) + + return fig + + +def generate_row(fig, row, raw_indicators, data) -> tools.make_subplots: + """ + Generator all the indicator selected by the user for a specific row + """ + for indicator in raw_indicators.split(','): + if indicator in data: + scattergl = go.Scattergl( + x=data['date'], + y=data[indicator], + name=indicator + ) + fig.append_trace(scattergl, row, 1) + else: + logger.info( + 'Indicator "%s" ignored. Reason: This indicator is not found ' + 'in your strategy.', + indicator + ) + + return fig + + +def plot_parse_args(args: List[str]) -> Namespace: + """ + Parse args passed to the script + :param args: Cli arguments + :return: args: Array with all arguments + """ + arguments = Arguments(args, 'Graph dataframe') + arguments.scripts_options() + arguments.parser.add_argument( + '--indicators1', + help='Set indicators from your strategy you want in the first row of the graph. Separate ' + 'them with a coma. E.g: ema3,ema5 (default: %(default)s)', + type=str, + default='sma,ema3,ema5', + dest='indicators1', + ) + + arguments.parser.add_argument( + '--indicators2', + help='Set indicators from your strategy you want in the third row of the graph. Separate ' + 'them with a coma. E.g: fastd,fastk (default: %(default)s)', + type=str, + default='macd', + dest='indicators2', + ) + arguments.parser.add_argument( + '--plot-limit', + help='Specify tick limit for plotting - too high values cause huge files - ' + 'Default: %(default)s', + dest='plot_limit', + default=750, + type=int, + ) + arguments.common_args_parser() + arguments.optimizer_shared_options(arguments.parser) + arguments.backtesting_options(arguments.parser) + return arguments.parse_args() + + +def analyse_and_plot_pairs(args: Namespace): + """ + From arguments provided in cli: + -Initialise backtest env + -Get tickers data + -Generate Dafaframes populated with indicators and signals + -Load trades excecuted on same periods + -Generate Plotly plot objects + -Generate plot files + :return: None + """ + strategy, exchange, pairs = get_trading_env(args) + # Set timerange to use + timerange = Arguments.parse_timerange(args.timerange) + tick_interval = strategy.ticker_interval + + tickers = get_tickers_data(strategy, exchange, pairs, args) + pair_counter = 0 + for pair, data in tickers.items(): + pair_counter += 1 + logger.info("analyse pair %s", pair) + tickers = {} + tickers[pair] = data + dataframe = generate_dataframe(strategy, tickers, pair) + + trades = load_trades(args, pair, timerange) + trades = extract_trades_of_period(dataframe, trades) + + fig = generate_graph( + pair=pair, + trades=trades, + data=dataframe, + args=args + ) + + is_last = (False, True)[pair_counter == len(tickers)] + generate_plot_file(fig, pair, tick_interval, is_last) + + logger.info('End of ploting process %s plots generated', pair_counter) + + +def main(sysargv: List[str]) -> None: + """ + This function will initiate the bot and start the trading loop. + :return: None + """ + logger.info('Starting Plot Dataframe') + analyse_and_plot_pairs( + plot_parse_args(sysargv) + ) + exit() + + +if __name__ == '__main__': + main(sys.argv[1:])