diff --git a/tests/distributed/test_basic.py b/tests/distributed/test_basic.py
index aacad0d8e..0fc900834 100644
--- a/tests/distributed/test_basic.py
+++ b/tests/distributed/test_basic.py
@@ -1,20 +1,17 @@
 #!/usr/bin/python
-import numpy as np
-import scipy.sparse
-import pickle
 import xgboost as xgb
 
-# always call this before using distributed module
+# Always call this before using distributed module
 xgb.rabit.init()
 
 # Load file, file will be automatically sharded in distributed mode.
 dtrain = xgb.DMatrix('../../demo/data/agaricus.txt.train')
 dtest = xgb.DMatrix('../../demo/data/agaricus.txt.test')
 
-# specify parameters via map, definition are same as c++ version
-param = {'max_depth':2, 'eta':1, 'silent':1, 'objective':'binary:logistic' }
+# Specify parameters via map, definition are same as c++ version
+param = {'max_depth': 2, 'eta': 1, 'silent': 1, 'objective': 'binary:logistic' }
 
-# specify validations set to watch performance
+# Specify validations set to watch performance
 watchlist  = [(dtest,'eval'), (dtrain,'train')]
 num_round = 20
 
@@ -22,7 +19,7 @@ num_round = 20
 # Currently, this script only support calling train once for fault recovery purpose.
 bst = xgb.train(param, dtrain, num_round, watchlist, early_stopping_rounds=2)
 
-# save the model, only ask process 0 to save the model.
+# Save the model, only ask process 0 to save the model.
 if xgb.rabit.get_rank() == 0:
     bst.save_model("test.model")
     xgb.rabit.tracker_print("Finished training\n")