fix: upgrade deprecated LightGBM API in docs and version constraints

docs/start/integration.rst

@@ -57,16 +57,17 @@ The Custom models need to inherit `qlib.model.base.Model <../reference/api.html#
                 dtrain = lgb.Dataset(x_train.values, label=y_train)
                 dvalid = lgb.Dataset(x_valid.values, label=y_valid)
 
-                # fit the model
+                # fit the model using callbacks (LightGBM >= 3.3.0)
+                early_stopping_callback = lgb.early_stopping(early_stopping_rounds)
+                verbose_eval_callback = lgb.log_evaluation(period=verbose_eval)
+                evals_result_callback = lgb.record_evaluation(evals_result)
                 self.model = lgb.train(
                     self.params,
                     dtrain,
                     num_boost_round=num_boost_round,
                     valid_sets=[dtrain, dvalid],
                     valid_names=["train", "valid"],
-                    early_stopping_rounds=early_stopping_rounds,
-                    verbose_eval=verbose_eval,
-                    evals_result=evals_result,
+                    callbacks=[early_stopping_callback, verbose_eval_callback, evals_result_callback],
                     **kwargs
                 )
 
@@ -94,14 +95,15 @@ The Custom models need to inherit `qlib.model.base.Model <../reference/api.html#
             def finetune(self, dataset: DatasetH, num_boost_round=10, verbose_eval=20):
                 # Based on existing model and finetune by train more rounds
                 dtrain, _ = self._prepare_data(dataset)
+                verbose_eval_callback = lgb.log_evaluation(period=verbose_eval)
                 self.model = lgb.train(
                     self.params,
                     dtrain,
                     num_boost_round=num_boost_round,
                     init_model=self.model,
                     valid_sets=[dtrain],
                     valid_names=["train"],
-                    verbose_eval=verbose_eval,
+                    callbacks=[verbose_eval_callback],
                 )
 
 Configuration File

examples/benchmarks/DoubleEnsemble/requirements.txt

@@ -1,3 +1,3 @@
 pandas==1.1.2
 numpy==1.21.0
-lightgbm==3.1.0
+lightgbm>=3.3.0

examples/hyperparameter/LightGBM/requirements.txt

@@ -1,5 +1,5 @@
 pandas==1.1.2
 numpy==1.21.0
-lightgbm==3.1.0
+lightgbm>=3.3.0
 optuna==2.7.0
 optuna-dashboard==0.4.1

pyproject.toml

@@ -44,7 +44,10 @@ dependencies = [
   "tqdm",
   "pymongo",
   "loguru",
-  "lightgbm",
+  # Since version 3.3.0, lightgbm supports the callback-based API
+  # (early_stopping(), log_evaluation(), record_evaluation()).
+  # The deprecated parameter-based API was removed in lightgbm 4.0.
+  "lightgbm>=3.3.0",
   "gym",
   "cvxpy",
   "joblib",