SQUASH: Application: Review do_POST of Executor

Author: matteonardelli

examples/sentiment-analysis/src/executor.py

@@ -16,9 +16,15 @@
 
 class Executor(BaseHTTPRequestHandler):
     def do_POST(self):
-        content_length = int(self.headers['Content-Length']) 
-        post_data = self.rfile.read(content_length) 
-        request = json.loads(post_data.decode('utf-8'))
+        content_length = 0
+        post_data = None
+        request = { }
+        raw_content_length = self.headers['Content-Length']
+        if raw_content_length:
+            content_length = int(raw_content_length)
+            post_data = self.rfile.read(content_length)
+            print(f" POST: Received post_data: {post_data}")
+            request = json.loads(post_data.decode('utf-8'))
 
         if not "invoke" in self.path:
             self.send_response(404)
@@ -57,14 +63,13 @@ def do_POST(self):
                         }
                     }
                 '''
-                print(params)
                 data_url = str(params.get("data_url", DATA_URL))
                 local_temp_dir = str(params.get("local_dir", OUTPUT_PATH))
                 data_object_name = str(params.get("object_name", OBJECT_NAME))
 
                 print(f"Running function 'retriever' with params {data_url}, {local_temp_dir}, {data_object_name}")
                 result = retriever.handler(data_url=data_url, local_temp_path=local_temp_dir, object_name=data_object_name)
-                # result = True
+
             elif func == "train" or HANDLER_ENV.lower() == "train":
                 ''' Invocation example: 
                 
@@ -83,9 +88,9 @@ def do_POST(self):
                         }
                     }
                 '''
-                print(f"Running function 'handle_train' with params {params}, {context}")
+                print(f"Running function 'train' with params {params}")
                 result = ml_model.handler_train(params, context)
-                
+
             elif func == "evaluate" or HANDLER_ENV.lower() == "evaluate":
                 ''' Invocation example: