diff --git a/examples/example_m5/main.py b/examples/example_m5/main.py
index 82ff2d3..1d3a39b 100644
--- a/examples/example_m5/main.py
+++ b/examples/example_m5/main.py
@@ -101,7 +101,7 @@ class M5DatasetWorkflow:
 
         m5 = DataLoader()
         idx_list = m5.get_idx_list()
-        algo_list = ['lgb']  # algo_list = ["ridge", "lgb"]
+        algo_list = ["lgb"]  # algo_list = ["ridge", "lgb"]
 
         curr_root = os.path.dirname(os.path.abspath(__file__))
         curr_root = os.path.join(curr_root, "learnware_pool")
diff --git a/examples/example_m5/upload.py b/examples/example_m5/upload.py
index ba0234a..0c9e209 100644
--- a/examples/example_m5/upload.py
+++ b/examples/example_m5/upload.py
@@ -65,7 +65,7 @@ def main():
             "Device": {"Values": ["CPU"], "Type": "Tag"},
             "Scenario": {"Values": ["Business"], "Type": "Tag"},
             "Description": {"Values": "A sales-forecasting model from Walmart store", "Type": "String"},
-            "Name": {"Values": {name}, "Type": "String"},
+            "Name": {"Values": name, "Type": "String"},
         }
         res = session.post(
             submit_url,
diff --git a/examples/example_pfs/upload.py b/examples/example_pfs/upload.py
index 04dbcd8..ed8449f 100644
--- a/examples/example_pfs/upload.py
+++ b/examples/example_pfs/upload.py
@@ -68,7 +68,7 @@ def main():
                 "Values": "A sales-forecasting model from Predict Future Sales Competition on Kaggle",
                 "Type": "String",
             },
-            "Name": {"Values": {name}, "Type": "String"},
+            "Name": {"Values": name, "Type": "String"},
         }
         res = session.post(
             submit_url,
diff --git a/learnware/market/easy.py b/learnware/market/easy.py
index 130d918..0133fa1 100644
--- a/learnware/market/easy.py
+++ b/learnware/market/easy.py
@@ -333,7 +333,7 @@ class EasyMarket(BaseMarket):
         learnware_list: List[Learnware],
         user_rkme: RKMEStatSpecification,
         max_search_num: int,
-        weight_cutoff: float = 0.95
+        weight_cutoff: float = 0.95,
     ) -> Tuple[List[float], List[Learnware]]:
         """Select learnwares based on a total mixture ratio, then recalculate their mixture weights
 
@@ -372,15 +372,15 @@ class EasyMarket(BaseMarket):
                 mixture_list.append(learnware_list[idx])
             else:
                 break
-        
+
         if len(mixture_list) <= 1:
             mixture_list = [learnware_list[sort_by_weight_idx_list[0]]]
             mixture_weight = [1]
         else:
             if len(mixture_list) > max_search_num:
-                mixture_list = mixture_list[:max_search_num] 
+                mixture_list = mixture_list[:max_search_num]
             mixture_weight, _ = self._calculate_rkme_spec_mixture_weight(mixture_list, user_rkme)
-            
+
         return mixture_weight, mixture_list
 
     def _filter_by_rkme_spec_single(
@@ -618,11 +618,11 @@ class EasyMarket(BaseMarket):
             sorted_score_list, single_learnware_list = self._filter_by_rkme_spec_single(
                 sorted_score_list, single_learnware_list
             )
-            if search_method == 'auto':
+            if search_method == "auto":
                 weight_list, mixture_learnware_list = self._search_by_rkme_spec_mixture_auto(
                     learnware_list, user_rkme, max_search_num
                 )
-            elif search_method == 'greedy':
+            elif search_method == "greedy":
                 weight_list, mixture_learnware_list = self._search_by_rkme_spec_mixture_greedy(
                     learnware_list, user_rkme, max_search_num
                 )