simplify Dataset class (#163)

* simplify Dataset class

* simplify check output; fix deprecated warning

python-package/lightgbm/sklearn.py

@@ -5,7 +5,7 @@ from __future__ import absolute_import
 import inspect
 
 import numpy as np
-from .basic import LightGBMError, Dataset
+from .basic import LightGBMError, Dataset, IS_PY3
 from .engine import train
 '''sklearn'''
 try:
@@ -26,6 +26,13 @@ except ImportError:
     LGBMLabelEncoder = None
 
 
+def _argc(func):
+    if IS_PY3:
+        return len(inspect.signature(func).parameters)
+    else:
+        return len(inspect.getargspec(func).args)
+
+
 def _objective_function_wrapper(func):
     """Decorate an objective function
     Note: for multi-class task, the y_pred is group by class_id first, then group by row_id
@@ -57,7 +64,7 @@ def _objective_function_wrapper(func):
     def inner(preds, dataset):
         """internal function"""
         labels = dataset.get_label()
-        argc = len(inspect.getargspec(func).args)
+        argc = _argc(func)
         if argc == 2:
             grad, hess = func(labels, preds)
         elif argc == 3:
@@ -122,7 +129,7 @@ def _eval_function_wrapper(func):
     def inner(preds, dataset):
         """internal function"""
         labels = dataset.get_label()
-        argc = len(inspect.getargspec(func).args)
+        argc = _argc(func)
         if argc == 2:
             return func(labels, preds)
         elif argc == 3:

tests/c_api_test/test.py

@@ -189,12 +189,13 @@ def test_booster():
     LIB.LGBM_BoosterCreate(train, c_str("app=binary metric=auc num_leaves=31 verbose=0"), ctypes.byref(booster))
     LIB.LGBM_BoosterAddValidData(booster, test)
     is_finished = ctypes.c_int(0)
-    for i in range(100):
+    for i in range(1, 101):
         LIB.LGBM_BoosterUpdateOneIter(booster, ctypes.byref(is_finished))
         result = np.array([0.0], dtype=np.float64)
         out_len = ctypes.c_ulong(0)
         LIB.LGBM_BoosterGetEval(booster, 0, ctypes.byref(out_len), result.ctypes.data_as(ctypes.POINTER(ctypes.c_double)))
-        print('%d Iteration test AUC %f' % (i, result[0]))
+        if i % 10 == 0:
+            print('%d Iteration test AUC %f' % (i, result[0]))
     LIB.LGBM_BoosterSaveModel(booster, -1, c_str('model.txt'))
     LIB.LGBM_BoosterFree(booster)
     test_free_dataset(train)