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", "open_time", "close_time", "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)
if file.exists():
load_backtest_data(file)
else:
trades = pd.DataFrame([], columns=BT_DATA_COLUMNS)
return trades
def test_load_backtest_data_old_format(testdatadir, mocker):
filename = testdatadir / "backtest-result_test222.json"
mocker.patch('freqtrade.data.btanalysis.load_backtest_stats',
return_value=[])
with pytest.raises(
OperationalException,
match=
r"Backtest-results with only trades data are no longer supported."
):
load_backtest_data(filename)
def test_load_backtest_data():
filename = make_testdata_path(None) / "backtest-result_test.json"
bt_data = load_backtest_data(filename)
assert isinstance(bt_data, DataFrame)
assert list(bt_data.columns) == BT_DATA_COLUMNS + ["profitabs"]
assert len(bt_data) == 179
# Test loading from string (must yield same result)
bt_data2 = load_backtest_data(str(filename))
assert bt_data.equals(bt_data2)
with pytest.raises(ValueError, match=r"File .* does not exist\."):
load_backtest_data(str("filename") + "nofile")
def test_load_backtest_data_old_format(testdatadir):
filename = testdatadir / "backtest-result_test.json"
bt_data = load_backtest_data(filename)
assert isinstance(bt_data, DataFrame)
assert list(bt_data.columns
) == BT_DATA_COLUMNS_OLD + ['profit_abs', 'profit_ratio']
assert len(bt_data) == 179
# Test loading from string (must yield same result)
bt_data2 = load_backtest_data(str(filename))
assert bt_data.equals(bt_data2)
with pytest.raises(ValueError, match=r"File .* does not exist\."):
load_backtest_data(str("filename") + "nofile")
def test_generate_profit_graph():
filename = history.make_testdata_path(None) / "backtest-result_test.json"
trades = load_backtest_data(filename)
timerange = Arguments.parse_timerange("20180110-20180112")
pairs = ["POWR/BTC", "XLM/BTC"]
tickers = history.load_data(datadir=None,
pairs=pairs,
ticker_interval='5m',
timerange=timerange)
trades = trades[trades['pair'].isin(pairs)]
fig = generate_profit_graph(pairs, tickers, trades)
assert isinstance(fig, go.Figure)
assert fig.layout.title.text == "Profit plot"
figure = fig.layout.figure
assert len(figure.data) == 4
avgclose = find_trace_in_fig_data(figure.data, "Avg close price")
assert isinstance(avgclose, go.Scattergl)
profit = find_trace_in_fig_data(figure.data, "Profit")
assert isinstance(profit, go.Scattergl)
for pair in pairs:
profit_pair = find_trace_in_fig_data(figure.data, f"Profit {pair}")
assert isinstance(profit_pair, go.Scattergl)
def test_add_profit(testdatadir):
filename = testdatadir / "backtest-result_test.json"
bt_data = load_backtest_data(filename)
timerange = TimeRange.parse_timerange("20180110-20180112")
df = history.load_pair_history(pair="TRX/BTC",
ticker_interval='5m',
datadir=testdatadir,
timerange=timerange)
fig = generate_empty_figure()
cum_profits = create_cum_profit(df.set_index('date'),
bt_data[bt_data["pair"] == 'TRX/BTC'],
"cum_profits",
timeframe="5m")
fig1 = add_profit(fig,
row=2,
data=cum_profits,
column='cum_profits',
name='Profits')
figure = fig1.layout.figure
profits = find_trace_in_fig_data(figure.data, "Profits")
assert isinstance(profits, go.Scatter)
assert profits.yaxis == "y2"
def test_generate_profit_graph(testdatadir):
filename = testdatadir / "backtest-result_test.json"
trades = load_backtest_data(filename)
timerange = TimeRange.parse_timerange("20180110-20180112")
pairs = ["TRX/BTC", "ADA/BTC"]
tickers = history.load_data(datadir=testdatadir,
pairs=pairs,
ticker_interval='5m',
timerange=timerange)
trades = trades[trades['pair'].isin(pairs)]
fig = generate_profit_graph(pairs, tickers, trades, timeframe="5m")
assert isinstance(fig, go.Figure)
assert fig.layout.title.text == "Freqtrade Profit plot"
assert fig.layout.yaxis.title.text == "Price"
assert fig.layout.yaxis2.title.text == "Profit"
assert fig.layout.yaxis3.title.text == "Profit"
figure = fig.layout.figure
assert len(figure.data) == 4
avgclose = find_trace_in_fig_data(figure.data, "Avg close price")
assert isinstance(avgclose, go.Scatter)
profit = find_trace_in_fig_data(figure.data, "Profit")
assert isinstance(profit, go.Scatter)
for pair in pairs:
profit_pair = find_trace_in_fig_data(figure.data, f"Profit {pair}")
assert isinstance(profit_pair, go.Scatter)
def test_create_cum_profit1(testdatadir):
filename = testdatadir / "backtest-result_test.json"
bt_data = load_backtest_data(filename)
# Move close-time to "off" the candle, to make sure the logic still works
bt_data.loc[:, 'close_date'] = bt_data.loc[:, 'close_date'] + DateOffset(
seconds=20)
timerange = TimeRange.parse_timerange("20180110-20180112")
df = load_pair_history(pair="TRX/BTC",
timeframe='5m',
datadir=testdatadir,
timerange=timerange)
cum_profits = create_cum_profit(df.set_index('date'),
bt_data[bt_data["pair"] == 'TRX/BTC'],
"cum_profits",
timeframe="5m")
assert "cum_profits" in cum_profits.columns
assert cum_profits.iloc[0]['cum_profits'] == 0
assert cum_profits.iloc[-1]['cum_profits'] == 0.0798005
with pytest.raises(ValueError, match='Trade dataframe empty.'):
create_cum_profit(df.set_index('date'),
bt_data[bt_data["pair"] == 'NOTAPAIR'],
"cum_profits",
timeframe="5m")
def test_plot_trades(caplog):
fig1 = generage_empty_figure()
# nothing happens when no trades are available
fig = plot_trades(fig1, None)
assert fig == fig1
assert log_has("No trades found.", caplog.record_tuples)
pair = "ADA/BTC"
filename = history.make_testdata_path(None) / "backtest-result_test.json"
trades = load_backtest_data(filename)
trades = trades.loc[trades['pair'] == pair]
fig = plot_trades(fig, trades)
figure = fig1.layout.figure
# Check buys - color, should be in first graph, ...
trade_buy = find_trace_in_fig_data(figure.data, "trade_buy")
assert isinstance(trade_buy, go.Scatter)
assert trade_buy.yaxis == 'y'
assert len(trades) == len(trade_buy.x)
assert trade_buy.marker.color == 'green'
trade_sell = find_trace_in_fig_data(figure.data, "trade_sell")
assert isinstance(trade_sell, go.Scatter)
assert trade_sell.yaxis == 'y'
assert len(trades) == len(trade_sell.x)
assert trade_sell.marker.color == 'red'
def analyse_and_plot_pairs(config: Dict[str, Any]):
"""
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
"""
exchange = ExchangeResolver(config.get('exchange', {}).get('name'), config).exchange
strategy = StrategyResolver(config).strategy
if "pairs" in config:
pairs = config["pairs"].split(',')
else:
pairs = config["exchange"]["pair_whitelist"]
# Set timerange to use
timerange = Arguments.parse_timerange(config["timerange"])
ticker_interval = strategy.ticker_interval
tickers = history.load_data(
datadir=Path(str(config.get("datadir"))),
pairs=pairs,
ticker_interval=config['ticker_interval'],
refresh_pairs=config.get('refresh_pairs', False),
timerange=timerange,
exchange=exchange,
live=config.get("live", False),
)
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)
if config["trade_source"] == "DB":
trades = load_trades_from_db(config["db_url"])
elif config["trade_source"] == "file":
trades = load_backtest_data(Path(config["exportfilename"]))
trades = trades.loc[trades['pair'] == pair]
trades = extract_trades_of_period(dataframe, trades)
fig = generate_graph(
pair=pair,
data=dataframe,
trades=trades,
indicators1=config["indicators1"].split(","),
indicators2=config["indicators2"].split(",")
)
generate_plot_file(fig, pair, ticker_interval)
logger.info('End of ploting process %s plots generated', pair_counter)
def test_analyze_trade_parallelism(default_conf, mocker, testdatadir):
filename = testdatadir / "backtest-result_test.json"
bt_data = load_backtest_data(filename)
res = analyze_trade_parallelism(bt_data, "5m")
assert isinstance(res, DataFrame)
assert 'open_trades' in res.columns
assert res['open_trades'].max() == 3
assert res['open_trades'].min() == 0
def test_generate_profit_graph(testdatadir):
filename = testdatadir / "backtest_results/backtest-result_new.json"
trades = load_backtest_data(filename)
timerange = TimeRange.parse_timerange("20180110-20180112")
pairs = ["TRX/BTC", "XLM/BTC"]
trades = trades[
trades['close_date'] < pd.Timestamp('2018-01-12', tz='UTC')]
data = history.load_data(datadir=testdatadir,
pairs=pairs,
timeframe='5m',
timerange=timerange)
trades = trades[trades['pair'].isin(pairs)]
fig = generate_profit_graph(pairs,
data,
trades,
timeframe="5m",
stake_currency='BTC')
assert isinstance(fig, go.Figure)
assert fig.layout.title.text == "Freqtrade Profit plot"
assert fig.layout.yaxis.title.text == "Price"
assert fig.layout.yaxis2.title.text == "Profit BTC"
assert fig.layout.yaxis3.title.text == "Profit BTC"
figure = fig.layout.figure
assert len(figure.data) == 7
avgclose = find_trace_in_fig_data(figure.data, "Avg close price")
assert isinstance(avgclose, go.Scatter)
profit = find_trace_in_fig_data(figure.data, "Profit")
assert isinstance(profit, go.Scatter)
drawdown = find_trace_in_fig_data(figure.data, "Max drawdown 35.69%")
assert isinstance(drawdown, go.Scatter)
parallel = find_trace_in_fig_data(figure.data, "Parallel trades")
assert isinstance(parallel, go.Scatter)
underwater = find_trace_in_fig_data(figure.data, "Underwater Plot")
assert isinstance(underwater, go.Scatter)
for pair in pairs:
profit_pair = find_trace_in_fig_data(figure.data, f"Profit {pair}")
assert isinstance(profit_pair, go.Scatter)
with pytest.raises(OperationalException, match=r"No trades found.*"):
# Pair cannot be empty - so it's an empty dataframe.
generate_profit_graph(pairs,
data,
trades.loc[trades['pair'].isnull()],
timeframe="5m",
stake_currency='BTC')
def test_calculate_csum(testdatadir):
filename = testdatadir / "backtest-result_test.json"
bt_data = load_backtest_data(filename)
csum_min, csum_max = calculate_csum(bt_data)
assert isinstance(csum_min, float)
assert isinstance(csum_max, float)
assert csum_min < 0.01
assert csum_max > 0.02
with pytest.raises(ValueError, match='Trade dataframe empty.'):
csum_min, csum_max = calculate_csum(DataFrame())
def test_calculate_max_drawdown(testdatadir):
filename = testdatadir / "backtest-result_test.json"
bt_data = load_backtest_data(filename)
drawdown, h, low = calculate_max_drawdown(bt_data)
assert isinstance(drawdown, float)
assert pytest.approx(drawdown) == 0.21142322
assert isinstance(h, Timestamp)
assert isinstance(low, Timestamp)
assert h == Timestamp('2018-01-24 14:25:00', tz='UTC')
assert low == Timestamp('2018-01-30 04:45:00', tz='UTC')
with pytest.raises(ValueError, match='Trade dataframe empty.'):
drawdown, h, low = calculate_max_drawdown(DataFrame())
def test_create_cum_profit():
filename = make_testdata_path(None) / "backtest-result_test.json"
bt_data = load_backtest_data(filename)
timerange = TimeRange.parse_timerange("20180110-20180112")
df = load_pair_history(pair="POWR/BTC", ticker_interval='5m',
datadir=None, timerange=timerange)
cum_profits = create_cum_profit(df.set_index('date'),
bt_data[bt_data["pair"] == 'POWR/BTC'],
"cum_profits")
assert "cum_profits" in cum_profits.columns
assert cum_profits.iloc[0]['cum_profits'] == 0
assert cum_profits.iloc[-1]['cum_profits'] == 0.0798005
def test_generate_trading_stats(testdatadir):
filename = testdatadir / "backtest-result_new.json"
bt_data = load_backtest_data(filename)
res = generate_trading_stats(bt_data)
assert isinstance(res, dict)
assert res['winner_holding_avg'] == timedelta(seconds=1440)
assert res['loser_holding_avg'] == timedelta(days=1, seconds=21420)
assert 'wins' in res
assert 'losses' in res
assert 'draws' in res
# Select empty dataframe!
res = generate_trading_stats(bt_data.loc[bt_data['open_date'] == '2000-01-01', :])
assert res['wins'] == 0
assert res['losses'] == 0
def test_generate_periodic_breakdown_stats(testdatadir):
filename = testdatadir / "backtest_results/backtest-result_new.json"
bt_data = load_backtest_data(filename).to_dict(orient='records')
res = generate_periodic_breakdown_stats(bt_data, 'day')
assert isinstance(res, list)
assert len(res) == 21
day = res[0]
assert 'date' in day
assert 'draws' in day
assert 'loses' in day
assert 'wins' in day
assert 'profit_abs' in day
# Select empty dataframe!
res = generate_periodic_breakdown_stats([], 'day')
assert res == []
def test_create_cum_profit(testdatadir):
filename = testdatadir / "backtest-result_test.json"
bt_data = load_backtest_data(filename)
timerange = TimeRange.parse_timerange("20180110-20180112")
df = load_pair_history(pair="TRX/BTC",
timeframe='5m',
datadir=testdatadir,
timerange=timerange)
cum_profits = create_cum_profit(df.set_index('date'),
bt_data[bt_data["pair"] == 'TRX/BTC'],
"cum_profits",
timeframe="5m")
assert "cum_profits" in cum_profits.columns
assert cum_profits.iloc[0]['cum_profits'] == 0
assert cum_profits.iloc[-1]['cum_profits'] == 0.0798005
def test_generate_daily_stats(testdatadir):
filename = testdatadir / "backtest-result_new.json"
bt_data = load_backtest_data(filename)
res = generate_daily_stats(bt_data)
assert isinstance(res, dict)
assert round(res['backtest_best_day'], 4) == 0.1796
assert round(res['backtest_worst_day'], 4) == -0.1468
assert res['winning_days'] == 14
assert res['draw_days'] == 4
assert res['losing_days'] == 3
# Select empty dataframe!
res = generate_daily_stats(bt_data.loc[bt_data['open_date'] == '2000-01-01', :])
assert isinstance(res, dict)
assert round(res['backtest_best_day'], 4) == 0.0
assert res['winning_days'] == 0
assert res['draw_days'] == 0
assert res['losing_days'] == 0
def test_calculate_max_drawdown(testdatadir):
filename = testdatadir / "backtest-result_new.json"
bt_data = load_backtest_data(filename)
_, hdate, lowdate, hval, lval, drawdown = calculate_max_drawdown(
bt_data, value_col="profit_abs")
assert isinstance(drawdown, float)
assert pytest.approx(drawdown) == 0.12071099
assert isinstance(hdate, Timestamp)
assert isinstance(lowdate, Timestamp)
assert isinstance(hval, float)
assert isinstance(lval, float)
assert hdate == Timestamp('2018-01-25 01:30:00', tz='UTC')
assert lowdate == Timestamp('2018-01-25 03:50:00', tz='UTC')
underwater = calculate_underwater(bt_data)
assert isinstance(underwater, DataFrame)
with pytest.raises(ValueError, match='Trade dataframe empty.'):
calculate_max_drawdown(DataFrame())
with pytest.raises(ValueError, match='Trade dataframe empty.'):
calculate_underwater(DataFrame())
def test_plot_trades(testdatadir, caplog):
fig1 = generate_empty_figure()
# nothing happens when no trades are available
fig = plot_trades(fig1, None)
assert fig == fig1
assert log_has("No trades found.", caplog)
pair = "ADA/BTC"
filename = testdatadir / "backtest-result_test.json"
trades = load_backtest_data(filename)
trades = trades.loc[trades['pair'] == pair]
fig = plot_trades(fig, trades)
figure = fig1.layout.figure
# Check buys - color, should be in first graph, ...
trade_buy = find_trace_in_fig_data(figure.data, 'Trade buy')
assert isinstance(trade_buy, go.Scatter)
assert trade_buy.yaxis == 'y'
assert len(trades) == len(trade_buy.x)
assert trade_buy.marker.color == 'cyan'
assert trade_buy.marker.symbol == 'circle-open'
assert trade_buy.text[0] == '4.0%, roi, 15 min'
trade_sell = find_trace_in_fig_data(figure.data, 'Sell - Profit')
assert isinstance(trade_sell, go.Scatter)
assert trade_sell.yaxis == 'y'
assert len(trades.loc[trades['profit_percent'] > 0]) == len(trade_sell.x)
assert trade_sell.marker.color == 'green'
assert trade_sell.marker.symbol == 'square-open'
assert trade_sell.text[0] == '4.0%, roi, 15 min'
trade_sell_loss = find_trace_in_fig_data(figure.data, 'Sell - Loss')
assert isinstance(trade_sell_loss, go.Scatter)
assert trade_sell_loss.yaxis == 'y'
assert len(trades.loc[trades['profit_percent'] <= 0]) == len(
trade_sell_loss.x)
assert trade_sell_loss.marker.color == 'red'
assert trade_sell_loss.marker.symbol == 'square-open'
assert trade_sell_loss.text[5] == '-10.4%, stop_loss, 720 min'
def test_load_backtest_data_new_format(testdatadir):
filename = testdatadir / "backtest-result_new.json"
bt_data = load_backtest_data(filename)
assert isinstance(bt_data, DataFrame)
assert set(bt_data.columns) == set(BT_DATA_COLUMNS_MID)
assert len(bt_data) == 179
# Test loading from string (must yield same result)
bt_data2 = load_backtest_data(str(filename))
assert bt_data.equals(bt_data2)
# Test loading from folder (must yield same result)
bt_data3 = load_backtest_data(testdatadir)
assert bt_data.equals(bt_data3)
with pytest.raises(ValueError, match=r"File .* does not exist\."):
load_backtest_data(str("filename") + "nofile")
with pytest.raises(ValueError, match=r"Unknown dataformat."):
load_backtest_data(testdatadir / LAST_BT_RESULT_FN)
def test_load_backtest_data_multi(testdatadir):
filename = testdatadir / "backtest-result_multistrat.json"
for strategy in ('DefaultStrategy', 'TestStrategy'):
bt_data = load_backtest_data(filename, strategy=strategy)
assert isinstance(bt_data, DataFrame)
assert set(bt_data.columns) == set(BT_DATA_COLUMNS_MID)
assert len(bt_data) == 179
# Test loading from string (must yield same result)
bt_data2 = load_backtest_data(str(filename), strategy=strategy)
assert bt_data.equals(bt_data2)
with pytest.raises(
ValueError,
match=r"Strategy XYZ not available in the backtest result\."):
load_backtest_data(filename, strategy='XYZ')
with pytest.raises(
ValueError,
match=r"Detected backtest result with more than one strategy.*"):
load_backtest_data(filename)
