Merge branch 'freqtrade:develop' into develop

.pre-commit-config.yaml

@@ -30,7 +30,7 @@ repos:
 
   - repo: https://github.com/charliermarsh/ruff-pre-commit
     # Ruff version.
-    rev: 'v0.0.270'
+    rev: 'v0.1.1'
     hooks:
       - id: ruff
 

docs/strategy-customization.md

@@ -1008,6 +1008,10 @@ The following lists some common patterns which should be avoided to prevent frus
 - don't use `dataframe['volume'].mean()`. This uses the full DataFrame for backtesting, including data from the future. Use `dataframe['volume'].rolling(<window>).mean()` instead
 - don't use `.resample('1h')`. This uses the left border of the interval, so moves data from an hour to the start of the hour. Use `.resample('1h', label='right')` instead.
 
+!!! Hint "Identifying problems"
+    You may also want to check the 2 helper commands [lookahead-analysis](lookahead-analysis.md) and [recursive-analysis](recursive-analysis.md), which can each help you figure out problems with your strategy in different ways.
+    Please treat them as what they are - helpers to identify most common problems. A negative result of each does not guarantee that there's none of the above errors included.
+
 ### Colliding signals
 
 When conflicting signals collide (e.g. both `'enter_long'` and `'exit_long'` are 1), freqtrade will do nothing and ignore the entry signal. This will avoid trades that enter, and exit immediately. Obviously, this can potentially lead to missed entries.

freqtrade/freqai/data_drawer.py

@@ -296,8 +296,7 @@ def set_initial_return_values(self, pair: str,
                            f"for more than {len(dataframe.index)} candles.")
 
         df_concat = pd.concat([hist_preds, new_pred], ignore_index=True, keys=hist_preds.keys())
-        # remove last row because we will append that later in append_model_predictions()
-        df_concat = df_concat.iloc[:-1]
+
         # any missing values will get zeroed out so users can see the exact
         # downtime in FreqUI
         df_concat = df_concat.fillna(0)

tests/freqai/test_freqai_datadrawer.py

@@ -179,10 +179,9 @@ def test_set_initial_return_values(mocker, freqai_conf):
     hist_pred_df = freqai.dd.historic_predictions[pair]
     model_return_df = freqai.dd.model_return_values[pair]
 
-    assert (hist_pred_df['date_pred'].iloc[-1] ==
-            pd.Timestamp(end_x_plus_5) - pd.Timedelta(days=1))
+    assert hist_pred_df['date_pred'].iloc[-1] == pd.Timestamp(end_x_plus_5)
     assert 'date_pred' in hist_pred_df.columns
-    assert hist_pred_df.shape[0] == 7  # Total rows: 5 from historic and 2 new zeros
+    assert hist_pred_df.shape[0] == 8
 
     # compare values in model_return_df with hist_pred_df
     assert (model_return_df["value"].values ==
@@ -234,9 +233,9 @@ def test_set_initial_return_values_warning(mocker, freqai_conf):
     hist_pred_df = freqai.dd.historic_predictions[pair]
     model_return_df = freqai.dd.model_return_values[pair]
 
-    assert hist_pred_df['date_pred'].iloc[-1] == pd.Timestamp(end_x_plus_5) - pd.Timedelta(days=1)
+    assert hist_pred_df['date_pred'].iloc[-1] == pd.Timestamp(end_x_plus_5)
     assert 'date_pred' in hist_pred_df.columns
-    assert hist_pred_df.shape[0] == 9  # Total rows: 5 from historic and 4 new zeros
+    assert hist_pred_df.shape[0] == 10
 
     # compare values in model_return_df with hist_pred_df
     assert (model_return_df["value"].values == hist_pred_df.tail(