def create_candles_data(symbol, time_frame, new_data, bot, list_arrays,
in_backtesting):
candles_key = "candles"
real_trades_key = "real_trades"
simulated_trades_key = "simulated_trades"
result_dict = {
candles_key: [],
real_trades_key: [],
simulated_trades_key: [],
}
if not in_backtesting:
add_to_symbol_data_history(symbol, new_data, time_frame, False)
data = get_symbol_data_history(symbol, time_frame)
else:
data = new_data
data_x = convert_timestamps_to_datetime(
data[PriceIndexes.IND_PRICE_TIME.value],
time_format="%y-%m-%d %H:%M:%S",
force_timezone=False)
real_trades_history, simulated_trades_history = get_trades_history(
bot, symbol)
if real_trades_history:
result_dict[real_trades_key] = _format_trades(real_trades_history)
if real_trades_history:
result_dict[simulated_trades_key] = _format_trades(
simulated_trades_history)
if list_arrays:
result_dict[candles_key] = {
PriceStrings.STR_PRICE_TIME.value:
data_x,
PriceStrings.STR_PRICE_CLOSE.value:
data[PriceIndexes.IND_PRICE_CLOSE.value].tolist(),
PriceStrings.STR_PRICE_LOW.value:
data[PriceIndexes.IND_PRICE_LOW.value].tolist(),
PriceStrings.STR_PRICE_OPEN.value:
data[PriceIndexes.IND_PRICE_OPEN.value].tolist(),
PriceStrings.STR_PRICE_HIGH.value:
data[PriceIndexes.IND_PRICE_HIGH.value].tolist()
}
else:
result_dict[candles_key] = {
PriceStrings.STR_PRICE_TIME.value:
data_x,
PriceStrings.STR_PRICE_CLOSE.value:
data[PriceIndexes.IND_PRICE_CLOSE.value],
PriceStrings.STR_PRICE_LOW.value:
data[PriceIndexes.IND_PRICE_LOW.value],
PriceStrings.STR_PRICE_OPEN.value:
data[PriceIndexes.IND_PRICE_OPEN.value],
PriceStrings.STR_PRICE_HIGH.value:
data[PriceIndexes.IND_PRICE_HIGH.value]
}
return result_dict
def get_currency_graph_update(exchange_name, symbol, time_frame, cryptocurrency_name):
symbol_evaluator_list = get_bot().get_symbol_evaluator_list()
exchange_list = get_bot().get_exchanges_list()
if time_frame is not None:
if len(symbol_evaluator_list) > 0:
evaluator_thread_managers = symbol_evaluator_list[symbol].get_evaluator_thread_managers(
exchange_list[exchange_name])
if time_frame in evaluator_thread_managers:
evaluator_thread_manager = evaluator_thread_managers[time_frame]
df = evaluator_thread_manager.get_evaluator().get_data()
if df is not None:
symbol_tag, pair_tag = Exchange.split_symbol(symbol)
add_to_symbol_data_history(symbol, df, time_frame)
df = get_symbol_data_history(symbol, time_frame)
# df.loc[:, PriceStrings.STR_PRICE_TIME.value] /= 1000
X = df[PriceStrings.STR_PRICE_TIME.value]
Y = df[PriceStrings.STR_PRICE_CLOSE.value]
# Candlestick
data = go.Ohlc(x=df[PriceStrings.STR_PRICE_TIME.value],
open=df[PriceStrings.STR_PRICE_OPEN.value],
high=df[PriceStrings.STR_PRICE_HIGH.value],
low=df[PriceStrings.STR_PRICE_LOW.value],
close=df[PriceStrings.STR_PRICE_CLOSE.value])
real_trades_prices, real_trades_times, simulated_trades_prices, simulated_trades_times = \
get_trades_by_times_and_prices()
real_trades_points = go.Scatter(
x=real_trades_prices,
y=real_trades_times,
mode='markers',
name='markers'
)
simulated_trades_points = go.Scatter(
x=simulated_trades_times,
y=simulated_trades_prices,
mode='markers',
name='markers'
)
return {'data': [data, real_trades_points, simulated_trades_points],
'layout': go.Layout(
title="{} real time data (per time frame)".format(cryptocurrency_name),
xaxis=dict(range=[min(X), max(X)],
title=TIME_AXIS_TITLE),
yaxis=dict(range=[min(Y) * 0.98, max(Y) * 1.02],
title=pair_tag)
)}
return None
def get_currency_graph_update(exchange_name, symbol, time_frame, cryptocurrency_name):
symbol_evaluator_list = get_bot().get_symbol_evaluator_list()
exchange_list = get_bot().get_exchanges_list()
if time_frame is not None:
if len(symbol_evaluator_list) > 0:
evaluator_thread_managers = symbol_evaluator_list[symbol].get_evaluator_thread_managers(
exchange_list[exchange_name])
if time_frame in evaluator_thread_managers:
evaluator_thread_manager = evaluator_thread_managers[time_frame]
data = evaluator_thread_manager.get_evaluator().get_data()
if data is not None:
_, pair_tag = split_symbol(symbol)
add_to_symbol_data_history(symbol, data, time_frame)
data = get_symbol_data_history(symbol, time_frame)
# data.loc[:, PriceStrings.STR_PRICE_TIME.value] /= 1000
data_x = data[PriceIndexes.IND_PRICE_TIME.value]
data_y = data[PriceIndexes.IND_PRICE_CLOSE.value]
# Candlestick
ohlc_graph = go.Ohlc(x=data[PriceIndexes.IND_PRICE_TIME.value],
open=data[PriceIndexes.IND_PRICE_OPEN.value],
high=data[PriceIndexes.IND_PRICE_HIGH.value],
low=data[PriceIndexes.IND_PRICE_LOW.value],
close=data[PriceIndexes.IND_PRICE_CLOSE.value])
real_trades_prices, real_trades_times, simulated_trades_prices, simulated_trades_times = \
get_trades_by_times_and_prices()
real_trades_points = go.Scatter(
x=real_trades_prices,
y=real_trades_times,
mode='markers',
name='markers'
)
simulated_trades_points = go.Scatter(
x=simulated_trades_times,
y=simulated_trades_prices,
mode='markers',
name='markers'
)
return {'data': [ohlc_graph, real_trades_points, simulated_trades_points],
'layout': go.Layout(
title="{} real time data (per time frame)".format(cryptocurrency_name),
xaxis=dict(range=[min(data_x), max(data_x)],
title=TIME_AXIS_TITLE),
yaxis=dict(range=[min(data_y) * 0.98, max(data_y) * 1.02],
title=pair_tag)
)}
return None
def get_currency_price_graph_update(exchange_name,
symbol,
time_frame,
list_arrays=True,
backtesting=False):
bot = get_bot()
if backtesting and bot.get_tools() and bot.get_tools(
)[BOT_TOOLS_BACKTESTING]:
bot = bot.get_tools()[BOT_TOOLS_BACKTESTING].get_bot()
symbol = parse_get_symbol(symbol)
symbol_evaluator_list = bot.get_symbol_evaluator_list()
in_backtesting = Backtesting.enabled(get_global_config()) or backtesting
exchange = exchange_name
exchange_list = bot.get_exchanges_list()
if backtesting:
exchanges = [key for key in exchange_list if exchange_name in key]
if exchanges:
exchange = exchanges[0]
if time_frame is not None:
if symbol_evaluator_list:
evaluator_thread_managers = symbol_evaluator_list[
symbol].get_evaluator_thread_managers(exchange_list[exchange])
if time_frame in evaluator_thread_managers:
evaluator_thread_manager = evaluator_thread_managers[
time_frame]
data = evaluator_thread_manager.get_evaluator().get_data()
if data is not None:
candles_key = "candles"
real_trades_key = "real_trades"
simulated_trades_key = "simulated_trades"
result_dict = {
candles_key: [],
real_trades_key: [],
simulated_trades_key: [],
}
_, pair_tag = split_symbol(symbol)
add_to_symbol_data_history(symbol, data, time_frame,
in_backtesting)
data = get_symbol_data_history(symbol, time_frame)
data_x = convert_timestamps_to_datetime(
data[PriceIndexes.IND_PRICE_TIME.value],
time_format="%y-%m-%d %H:%M:%S",
force_timezone=False)
real_trades_history, simulated_trades_history = get_trades_history(
bot, symbol)
if real_trades_history:
result_dict[real_trades_key] = _format_trades(
real_trades_history)
if real_trades_history:
result_dict[simulated_trades_key] = _format_trades(
simulated_trades_history)
if list_arrays:
result_dict[candles_key] = {
PriceStrings.STR_PRICE_TIME.value:
data_x,
PriceStrings.STR_PRICE_CLOSE.value:
data[PriceIndexes.IND_PRICE_CLOSE.value].tolist(),
PriceStrings.STR_PRICE_LOW.value:
data[PriceIndexes.IND_PRICE_LOW.value].tolist(),
PriceStrings.STR_PRICE_OPEN.value:
data[PriceIndexes.IND_PRICE_OPEN.value].tolist(),
PriceStrings.STR_PRICE_HIGH.value:
data[PriceIndexes.IND_PRICE_HIGH.value].tolist()
}
else:
result_dict[candles_key] = {
PriceStrings.STR_PRICE_TIME.value:
data_x,
PriceStrings.STR_PRICE_CLOSE.value:
data[PriceIndexes.IND_PRICE_CLOSE.value],
PriceStrings.STR_PRICE_LOW.value:
data[PriceIndexes.IND_PRICE_LOW.value],
PriceStrings.STR_PRICE_OPEN.value:
data[PriceIndexes.IND_PRICE_OPEN.value],
PriceStrings.STR_PRICE_HIGH.value:
data[PriceIndexes.IND_PRICE_HIGH.value]
}
return result_dict
return None