[pull] develop from freqtrade:develop

docs/freqai.md

@@ -18,7 +18,7 @@ Features include:
 * **Extensibility** - The generalized and robust architecture allows for incorporating any [machine learning library/method](freqai-configuration.md#using-different-prediction-models) available in Python. Eight examples are currently available, including classifiers, regressors, and a convolutional neural network
 * **Smart outlier removal** - Remove outliers from training and prediction data sets using a variety of [outlier detection techniques](freqai-feature-engineering.md#outlier-detection)
 * **Crash resilience** - Store trained models to disk to make reloading from a crash fast and easy, and [purge obsolete files](freqai-running.md#purging-old-model-data) for sustained dry/live runs
-* **Automatic data normalization** - [Normalize the data](freqai-feature-engineering.md#feature-normalization) in a smart and statistically safe way
+* **Automatic data normalization** - [Normalize the data](freqai-feature-engineering.md#building-the-data-pipeline) in a smart and statistically safe way
 * **Automatic data download** - Compute timeranges for data downloads and update historic data (in live deployments)
 * **Cleaning of incoming data** - Handle NaNs safely before training and model inferencing
 * **Dimensionality reduction** - Reduce the size of the training data via [Principal Component Analysis](freqai-feature-engineering.md#data-dimensionality-reduction-with-principal-component-analysis)

freqtrade/freqai/base_models/FreqaiMultiOutputClassifier.py

@@ -3,7 +3,7 @@
 from sklearn.multioutput import MultiOutputClassifier, _fit_estimator
 from sklearn.utils.multiclass import check_classification_targets
 from sklearn.utils.parallel import Parallel, delayed
-from sklearn.utils.validation import has_fit_parameter
+from sklearn.utils.validation import has_fit_parameter, validate_data
 
 from freqtrade.exceptions import OperationalException
 
@@ -36,7 +36,7 @@ def fit(self, X, y, sample_weight=None, fit_params=None):
         if not hasattr(self.estimator, "fit"):
             raise ValueError("The base estimator should implement a fit method")
 
-        y = self._validate_data(X="no_validation", y=y, multi_output=True)
+        y = validate_data(self, X="no_validation", y=y, multi_output=True)
 
         if is_classifier(self):
             check_classification_targets(y)

freqtrade/freqai/base_models/FreqaiMultiOutputRegressor.py

@@ -1,6 +1,6 @@
 from sklearn.multioutput import MultiOutputRegressor, _fit_estimator
 from sklearn.utils.parallel import Parallel, delayed
-from sklearn.utils.validation import has_fit_parameter
+from sklearn.utils.validation import has_fit_parameter, validate_data
 
 
 class FreqaiMultiOutputRegressor(MultiOutputRegressor):
@@ -31,7 +31,7 @@ def fit(self, X, y, sample_weight=None, fit_params=None):
         if not hasattr(self.estimator, "fit"):
             raise ValueError("The base estimator should implement a fit method")
 
-        y = self._validate_data(X="no_validation", y=y, multi_output=True)
+        y = validate_data(self, X="no_validation", y=y, multi_output=True)
 
         if y.ndim == 1:
             raise ValueError(

freqtrade/rpc/rpc.py

@@ -1283,6 +1283,7 @@ def _rpc_get_logs(limit: int | None) -> dict[str, Any]:
                 r.message + ("\n" + r.exc_text if r.exc_text else ""),
             ]
             for r in buffer
+            if hasattr(r, "message")
         ]
 
         # Log format:

requirements-dev.txt

@@ -7,7 +7,7 @@
 -r docs/requirements-docs.txt
 
 coveralls==4.0.1
-ruff==0.8.4
+ruff==0.8.6
 mypy==1.14.1
 pre-commit==4.0.1
 pytest==8.3.4
@@ -22,7 +22,7 @@ isort==5.13.2
 time-machine==2.16.0
 
 # Convert jupyter notebooks to markdown documents
-nbconvert==7.16.4
+nbconvert==7.16.5
 
 # mypy types
 types-cachetools==5.5.0.20240820

requirements-hyperopt.txt

@@ -2,7 +2,7 @@
 -r requirements.txt
 
 # Required for hyperopt
-scipy==1.14.1
+scipy==1.15.0
 scikit-learn==1.6.0
 ft-scikit-optimize==0.9.2
 filelock==3.16.1

tests/exchange/test_binance.py

@@ -1053,3 +1053,6 @@ async def mock_get_trade_hist(pair, *args, **kwargs):
 
     assert fetch_trades_cal[2][1]["params"][pagination_arg] != "0"
     assert fetch_trades_cal[3][1]["params"][pagination_arg] != "0"
+
+    # Clean up event loop to avoid warnings
+    exchange.close()