Merge branch 'develop' into optuna

tests/optimize/__init__.py

@@ -69,8 +69,8 @@ def _build_backtest_dataframe(data):
     ]
     if len(data[0]) == 8:
         # No short columns
-        data = [d + [0, 0] for d in data]
-    columns = columns + ["enter_tag"] if len(data[0]) == 11 else columns
+        data = [[*d, 0, 0] for d in data]
+    columns = [*columns, "enter_tag"] if len(data[0]) == 11 else columns
 
     frame = DataFrame.from_records(data, columns=columns)
     frame["date"] = frame["date"].apply(_get_frame_time_from_offset)

tests/optimize/test_backtest_detail.py

@@ -102,7 +102,7 @@ tc3 = BTContainer(
 )
 
 # Test 4: Minus 3% / recovery +15%
-# Candle Data for test 3 – Candle drops 3% Closed 15% up
+# Candle Data for test 3 - Candle drops 3% Closed 15% up
 # Test with Stop-loss at 2% ROI 6%
 # Stop-Loss Triggered 2% Loss
 tc4 = BTContainer(

tests/optimize/test_backtesting.py

@@ -828,6 +828,7 @@ def test_backtest_one(default_conf, mocker, testdatadir) -> None:
                     },
                 ],
             ],
+            "funding_fees": [0.0, 0.0],
         }
     )
     pd.testing.assert_frame_equal(results, expected)
@@ -991,7 +992,7 @@ def test_backtest_one_detail_futures(
         timerange=timerange,
         candle_type=CandleType.FUTURES,
     )
-    backtesting.load_bt_data_detail()
+    backtesting._load_bt_data_detail()
     processed = backtesting.strategy.advise_all_indicators(data)
     min_date, max_date = get_timerange(processed)
 
@@ -1119,7 +1120,7 @@ def test_backtest_one_detail_futures_funding_fees(
         timerange=timerange,
         candle_type=CandleType.FUTURES,
     )
-    backtesting.load_bt_data_detail()
+    backtesting._load_bt_data_detail()
     processed = backtesting.strategy.advise_all_indicators(data)
     min_date, max_date = get_timerange(processed)
 
@@ -2576,7 +2577,7 @@ def test_backtest_start_multi_strat_caching(
         ],
     )
     mocker.patch.multiple(
-        "freqtrade.data.btanalysis",
+        "freqtrade.data.btanalysis.bt_fileutils",
         load_backtest_metadata=load_backtest_metadata,
         load_backtest_stats=load_backtest_stats,
     )

tests/optimize/test_backtesting_adjust_position.py

@@ -80,6 +80,7 @@ def test_backtest_position_adjustment(default_conf, fee, mocker, testdatadir) ->
             "is_short": [False, False],
             "open_timestamp": [1517251200000, 1517283000000],
             "close_timestamp": [1517263200000, 1517285400000],
+            "funding_fees": [0.0, 0.0],
         }
     )
     results_no = results.drop(columns=["orders"])

tests/optimize/test_hyperopt.py

@@ -685,7 +685,7 @@ def test_print_json_spaces_all(mocker, hyperopt_conf, capsys) -> None:
         '{"params":{"mfi-value":null,"sell-mfi-value":null},"minimal_roi"'
         ':{},"stoploss":null,"trailing_stop":null,"max_open_trades":null}'
     )
-    assert result_str in out  # noqa: E501
+    assert result_str in out
     # Should be called for historical candle data
     assert dumper.call_count == 1
     assert dumper2.call_count == 1
@@ -742,7 +742,7 @@ def test_print_json_spaces_default(mocker, hyperopt_conf, capsys) -> None:
     assert (
         '{"params":{"mfi-value":null,"sell-mfi-value":null},"minimal_roi":{},"stoploss":null}'
         in out
-    )  # noqa: E501
+    )
     # Should be called for historical candle data
     assert dumper.call_count == 1
     assert dumper2.call_count == 1

tests/optimize/test_hyperoptloss.py

@@ -153,6 +153,7 @@ def test_loss_calculation_has_limited_profit(hyperopt_conf, hyperopt_results) ->
         "SharpeHyperOptLossDaily",
         "MaxDrawDownHyperOptLoss",
         "MaxDrawDownRelativeHyperOptLoss",
+        "MaxDrawDownPerPairHyperOptLoss",
         "CalmarHyperOptLoss",
         "ProfitDrawDownHyperOptLoss",
         "MultiMetricHyperOptLoss",
@@ -165,6 +166,34 @@ def test_loss_functions_better_profits(default_conf, hyperopt_results, lossfunct
     results_under = hyperopt_results.copy()
     results_under["profit_abs"] = hyperopt_results["profit_abs"] / 2 - 0.2
     results_under["profit_ratio"] = hyperopt_results["profit_ratio"] / 2
+    pair_results = [
+        {
+            "key": "ETH/USDT",
+            "max_drawdown_abs": 50.0,
+            "profit_total_abs": 100.0,
+        },
+        {
+            "key": "BTC/USDT",
+            "max_drawdown_abs": 50.0,
+            "profit_total_abs": 100.0,
+        },
+    ]
+    pair_results_over = [
+        {
+            **p,
+            "max_drawdown_abs": p["max_drawdown_abs"] * 0.5,
+            "profit_total_abs": p["profit_total_abs"] * 2,
+        }
+        for p in pair_results
+    ]
+    pair_results_under = [
+        {
+            **p,
+            "max_drawdown_abs": p["max_drawdown_abs"] * 2,
+            "profit_total_abs": p["profit_total_abs"] * 0.5,
+        }
+        for p in pair_results
+    ]
 
     default_conf.update({"hyperopt_loss": lossfunction})
     hl = HyperOptLossResolver.load_hyperoptloss(default_conf)
@@ -175,7 +204,10 @@ def test_loss_functions_better_profits(default_conf, hyperopt_results, lossfunct
         max_date=datetime(2019, 5, 1),
         config=default_conf,
         processed=None,
-        backtest_stats={"profit_total": hyperopt_results["profit_abs"].sum()},
+        backtest_stats={
+            "profit_total": hyperopt_results["profit_abs"].sum(),
+            "results_per_pair": pair_results,
+        },
         starting_balance=default_conf["dry_run_wallet"],
     )
     over = hl.hyperopt_loss_function(
@@ -185,7 +217,10 @@ def test_loss_functions_better_profits(default_conf, hyperopt_results, lossfunct
         max_date=datetime(2019, 5, 1),
         config=default_conf,
         processed=None,
-        backtest_stats={"profit_total": results_over["profit_abs"].sum()},
+        backtest_stats={
+            "profit_total": results_over["profit_abs"].sum(),
+            "results_per_pair": pair_results_over,
+        },
         starting_balance=default_conf["dry_run_wallet"],
     )
     under = hl.hyperopt_loss_function(
@@ -195,7 +230,10 @@ def test_loss_functions_better_profits(default_conf, hyperopt_results, lossfunct
         max_date=datetime(2019, 5, 1),
         config=default_conf,
         processed=None,
-        backtest_stats={"profit_total": results_under["profit_abs"].sum()},
+        backtest_stats={
+            "profit_total": results_under["profit_abs"].sum(),
+            "results_per_pair": pair_results_under,
+        },
         starting_balance=default_conf["dry_run_wallet"],
     )
     assert over < correct

tests/optimize/test_optimize_reports.py

@@ -68,11 +68,21 @@ def test_text_table_bt_results(capsys):
             "profit_ratio": [0.1, 0.2, -0.05],
             "profit_abs": [0.2, 0.4, -0.1],
             "trade_duration": [10, 30, 20],
+            "close_date": [
+                dt_utc(2017, 11, 14, 21, 35, 00),
+                dt_utc(2017, 11, 14, 22, 10, 00),
+                dt_utc(2017, 11, 14, 22, 43, 00),
+            ],
         }
     )
 
     pair_results = generate_pair_metrics(
-        ["ETH/BTC"], stake_currency="BTC", starting_balance=4, results=results
+        ["ETH/BTC"],
+        stake_currency="BTC",
+        starting_balance=4,
+        results=results,
+        min_date=dt_from_ts(1510688220),
+        max_date=dt_from_ts(1510700340),
     )
     text_table_bt_results(pair_results, stake_currency="BTC", title="title")
     text = capsys.readouterr().out
@@ -420,6 +430,10 @@ def test_generate_pair_metrics():
             "profit_ratio": [0.1, 0.2],
             "profit_abs": [0.2, 0.4],
             "trade_duration": [10, 30],
+            "close_date": [
+                dt_utc(2017, 11, 14, 21, 35, 00),
+                dt_utc(2017, 11, 14, 22, 10, 00),
+            ],
             "wins": [2, 0],
             "draws": [0, 0],
             "losses": [0, 0],
@@ -427,7 +441,12 @@ def test_generate_pair_metrics():
     )
 
     pair_results = generate_pair_metrics(
-        ["ETH/BTC"], stake_currency="BTC", starting_balance=2, results=results
+        ["ETH/BTC"],
+        stake_currency="BTC",
+        starting_balance=2,
+        results=results,
+        min_date=dt_from_ts(1510688220),
+        max_date=dt_from_ts(1510700340),
     )
     assert isinstance(pair_results, list)
     assert len(pair_results) == 2
@@ -512,6 +531,11 @@ def test_text_table_exit_reason(capsys):
             "profit_ratio": [0.1, 0.2, -0.1],
             "profit_abs": [0.2, 0.4, -0.2],
             "trade_duration": [10, 30, 10],
+            "close_date": [
+                dt_utc(2017, 11, 14, 21, 35, 00),
+                dt_utc(2017, 11, 14, 22, 10, 00),
+                dt_utc(2017, 11, 14, 22, 43, 00),
+            ],
             "wins": [2, 0, 0],
             "draws": [0, 0, 0],
             "losses": [0, 0, 1],
@@ -520,7 +544,12 @@ def test_text_table_exit_reason(capsys):
     )
 
     exit_reason_stats = generate_tag_metrics(
-        "exit_reason", starting_balance=22, results=results, skip_nan=False
+        "exit_reason",
+        starting_balance=22,
+        results=results,
+        min_date=dt_from_ts(1510688220),
+        max_date=dt_from_ts(1510700340),
+        skip_nan=False,
     )
     text_table_tags("exit_tag", exit_reason_stats, "BTC")
     text = capsys.readouterr().out
@@ -550,6 +579,11 @@ def test_generate_sell_reason_stats():
             "profit_ratio": [0.1, 0.2, -0.1],
             "profit_abs": [0.2, 0.4, -0.2],
             "trade_duration": [10, 30, 10],
+            "close_date": [
+                dt_utc(2017, 11, 14, 21, 35, 00),
+                dt_utc(2017, 11, 14, 22, 10, 00),
+                dt_utc(2017, 11, 14, 22, 43, 00),
+            ],
             "wins": [2, 0, 0],
             "draws": [0, 0, 0],
             "losses": [0, 0, 1],
@@ -558,7 +592,12 @@ def test_generate_sell_reason_stats():
     )
 
     exit_reason_stats = generate_tag_metrics(
-        "exit_reason", starting_balance=22, results=results, skip_nan=False
+        "exit_reason",
+        starting_balance=22,
+        results=results,
+        min_date=dt_from_ts(1510688220),
+        max_date=dt_from_ts(1510700340),
+        skip_nan=False,
     )
     roi_result = exit_reason_stats[0]
     assert roi_result["key"] == "roi"