[MNT] format code

learnware/client/container.py

@@ -127,11 +127,11 @@ class LearnwaresContainer:
             )
             for _learnware, _zippath in zip(learnware_list, learnware_zippaths)
         ]
-        
+
         model_list = [_learnware.get_model() for _learnware in self.learnware_list]
         with ProcessPoolExecutor(max_workers=max(os.cpu_count() // 2, 1)) as executor:
             executor.map(self._initialize_model_container, model_list)
-            
+
         atexit.register(self.cleanup)
 
     @staticmethod
@@ -144,7 +144,7 @@ class LearnwaresContainer:
 
     def get_learnware_list_with_container(self):
         return self.learnware_list
-    
+
     def cleanup(self):
         for _learnware in self.learnware_list:
-            self._destroy_model_container(_learnware.get_model())
+            self._destroy_model_container(_learnware.get_model())

learnware/client/learnware_client.py

@@ -310,7 +310,12 @@ class LearnwareClient:
 
         return semantic_conf[key.value]["Values"]
 
-    def load_learnware(self, learnware_path: Union[str, List[str]] = None, learnware_id: Union[str, List[str]] = None, runnable_option: str = None):
+    def load_learnware(
+        self,
+        learnware_path: Union[str, List[str]] = None,
+        learnware_id: Union[str, List[str]] = None,
+        runnable_option: str = None,
+    ):
         """Load learnware by learnware zip file or learnware id (zip file has higher priority)
 
         Parameters
@@ -334,14 +339,14 @@ class LearnwareClient:
 
         if learnware_path is None and learnware_id is None:
             raise ValueError("Requires one of learnware_path or learnware_id")
-        
+
         def _get_learnware_by_id(_learnware_id):
             self.tempdir_list.append(tempfile.TemporaryDirectory(prefix="learnware_"))
             tempdir = self.tempdir_list[-1].name
             zip_path = os.path.join(tempdir, f"{str(uuid.uuid4())}.zip")
             self.download_learnware(_learnware_id, zip_path)
             return zip_path, _get_learnware_by_path(zip_path, tempdir=tempdir)
-        
+
         def _get_learnware_by_path(_learnware_zippath, tempdir=None):
             if tempdir is None:
                 self.tempdir_list.append(tempfile.TemporaryDirectory(prefix="learnware_"))
@@ -368,7 +373,7 @@ class LearnwareClient:
                     semantic_specification = json.load(fin)
 
             return learnware.get_learnware_from_dirpath(learnware_id, semantic_specification, tempdir)
-        
+
         learnware_list = []
         zip_paths = []
         if learnware_path is not None:
@@ -376,7 +381,7 @@ class LearnwareClient:
                 zip_paths = [learnware_path]
             elif isinstance(learnware_path, list):
                 zip_paths = learnware_path
-        
+
             for zip_path in zip_paths:
                 learnware_obj = _get_learnware_by_path(zip_path)
                 learnware_list.append(learnware_obj)
@@ -385,12 +390,12 @@ class LearnwareClient:
                 id_list = [learnware_id]
             elif isinstance(learnware_id, list):
                 id_list = learnware_id
-            
+
             for idx in id_list:
                 zip_path, learnware_obj = _get_learnware_by_id(idx)
                 zip_paths.append(zip_path)
                 learnware_list.append(learnware_obj)
-        
+
         if runnable_option is not None:
             if runnable_option == "normal":
                 for i in range(len(learnware_list)):
@@ -398,7 +403,7 @@ class LearnwareClient:
             elif runnable_option == "conda_env":
                 env_container = LearnwaresContainer(learnware_list, zip_paths)
                 learnware_list = env_container.get_learnware_list_with_container()
-        
+
         if len(learnware_list) == 1:
             return learnware_list[0]
         else:

tests/test_client/test_load.py

@@ -11,7 +11,6 @@ from learnware.learnware.reuse import AveragingReuser
 
 
 class TestLearnwareLoad(unittest.TestCase):
-
     def setUp(self):
         unittest.TestCase.setUpClass()
         email = "liujd@lamda.nju.edu.cn"
@@ -27,8 +26,11 @@ class TestLearnwareLoad(unittest.TestCase):
     def test_load_single_learnware_by_zippath(self):
         for (learnware_id, zip_path) in zip(self.learnware_ids, self.zip_paths):
             self.client.download_learnware(learnware_id, zip_path)
-            
-        learnware_list = [self.client.load_learnware(learnware_path=zippath, runnable_option="conda_env") for zippath in self.zip_paths]
+
+        learnware_list = [
+            self.client.load_learnware(learnware_path=zippath, runnable_option="conda_env")
+            for zippath in self.zip_paths
+        ]
         reuser = AveragingReuser(learnware_list, mode="vote_by_label")
         input_array = np.random.random(size=(20, 13))
         print(reuser.predict(input_array))
@@ -39,7 +41,7 @@ class TestLearnwareLoad(unittest.TestCase):
     def test_load_multi_learnware_by_zippath(self):
         for (learnware_id, zip_path) in zip(self.learnware_ids, self.zip_paths):
             self.client.download_learnware(learnware_id, zip_path)
-        
+
         learnware_list = self.client.load_learnware(learnware_path=self.zip_paths, runnable_option="conda_env")
         reuser = AveragingReuser(learnware_list, mode="vote_by_label")
         input_array = np.random.random(size=(20, 13))
@@ -47,9 +49,11 @@ class TestLearnwareLoad(unittest.TestCase):
 
         for learnware in learnware_list:
             print(learnware.id, learnware.predict(input_array))
-            
+
     def test_load_single_learnware_by_id(self):
-        learnware_list = [self.client.load_learnware(learnware_id=idx, runnable_option="conda_env") for idx in self.learnware_ids]
+        learnware_list = [
+            self.client.load_learnware(learnware_id=idx, runnable_option="conda_env") for idx in self.learnware_ids
+        ]
         reuser = AveragingReuser(learnware_list, mode="vote_by_label")
         input_array = np.random.random(size=(20, 13))
         print(reuser.predict(input_array))
@@ -57,7 +61,7 @@ class TestLearnwareLoad(unittest.TestCase):
         for learnware in learnware_list:
             print(learnware.id, learnware.predict(input_array))
 
-    def test_load_multi_learnware_by_id(self):        
+    def test_load_multi_learnware_by_id(self):
         learnware_list = self.client.load_learnware(learnware_id=self.learnware_ids, runnable_option="conda_env")
         reuser = AveragingReuser(learnware_list, mode="vote_by_label")
         input_array = np.random.random(size=(20, 13))
@@ -67,5 +71,5 @@ class TestLearnwareLoad(unittest.TestCase):
             print(learnware.id, learnware.predict(input_array))
 
 
-if __name__ == '__main__':
-    unittest.main()
+if __name__ == "__main__":
+    unittest.main()