fixes #51: change from loop to asyncio.run

fixes #51: Correct trailing whitespace and EOF.

app.py

@@ -148,8 +148,8 @@ async def inference_request():
     """
     Performs inference on an image, and returns the results.
     The image and inference results are uploaded to a folder in the user's container.
-    """  
-     
+    """
+
     seconds = time.perf_counter() # transform into logging
     try:
         print("Entering inference request") # Transform into logging
@@ -164,16 +164,16 @@ async def inference_request():
 
         if not (folder_name and container_name and imageDims and image_base64):
             return jsonify(["missing request arguments"]), 400
-        
+
         if not pipelines_endpoints.get(pipeline_name):
             return jsonify([f"Model {pipeline_name} not found"]), 400
-        
+
         header, encoded_data = image_base64.split(",", 1)
 
         # Validate image header
         if not header.startswith("data:image/"):
             return jsonify(["Invalid image header"]), 400
-        
+
         image_bytes = base64.b64decode(encoded_data)
         container_client = await azure_storage_api.mount_container(
             connection_string, container_name, create_container=True
@@ -205,7 +205,7 @@ async def inference_request():
         except urllib.error.HTTPError as error:
             print(error)
             return jsonify(["endpoint cannot be reached" + str(error.code)]), 400
-        
+
         # upload the inference results to the user's container as async task
         result_json_string = json.dumps(processed_result_json)
 
@@ -218,12 +218,12 @@ async def inference_request():
         )
         # return the inference results to the client
         print(f"Took: {'{:10.4f}'.format(time.perf_counter() - seconds)} seconds")
-        return jsonify(processed_result_json), 200 
+        return jsonify(processed_result_json), 200
 
     except InferenceRequestError as error:
         print(error)
         return jsonify(["InferenceRequestError: " + str(error)]), 400
-    
+
     except Exception as error:
         print(error)
         return jsonify(["Unexpected error occured"]), 500
@@ -234,11 +234,11 @@ async def get_seed_data(seed_name):
     """
     Returns JSON containing requested seed data
     """
-    if seed_name in CACHE['seeds']:  
+    if seed_name in CACHE['seeds']:
         return jsonify(CACHE['seeds'][seed_name]), 200
     else:
         return jsonify(f"No information found for {seed_name}."), 400
-    
+
 
 @app.get("/reload-seed-data")
 async def reload_seed_data():
@@ -257,7 +257,7 @@ async def get_model_endpoints_metadata():
     """
     Returns JSON containing the deployed endpoints' metadata
     """
-    if CACHE['endpoints']:  
+    if CACHE['endpoints']:
         return jsonify(CACHE['endpoints']), 200
     else:
         return jsonify("Error retrieving model endpoints metadata.", 400)
@@ -329,7 +329,7 @@ async def get_pipelines(mock:bool = False):
         cipher_suite = Fernet(FERNET_KEY)
     # Get all the api_call function and map them in a dictionary
     api_call_function = {func.split("from_")[1]: getattr(model_module, func) for func in dir(model_module) if "inference" in func.split("_")}
-    # Get all the inference functions and map them in a dictionary 
+    # Get all the inference functions and map them in a dictionary
     inference_functions = {func: getattr(inference, func) for func in dir(inference) if "process" in func.split("_")}
 
     models = ()
@@ -363,11 +363,11 @@ async def before_serving():
         # Check: do environment variables exist?
         if connection_string is None:
             raise ServerError("Missing environment variable: NACHET_AZURE_STORAGE_CONNECTION_STRING")
-        
+
         if FERNET_KEY is None:
             raise ServerError("Missing environment variable: FERNET_KEY")
 
-        # Check: are environment variables correct? 
+        # Check: are environment variables correct?
         if not bool(re.match(connection_string_regex, connection_string)):
             raise ServerError("Incorrect environment variable: NACHET_AZURE_STORAGE_CONNECTION_STRING")
 
@@ -385,4 +385,3 @@ async def before_serving():
 
 if __name__ == "__main__":
     app.run(debug=True, host="0.0.0.0", port=8080)
-

azure_storage/azure_storage_api.py

@@ -265,7 +265,7 @@ async def get_pipeline_info(
             container_client = blob_service_client.get_container_client(
                 pipeline_container_name
             )
-            
+
             blob_list = container_client.list_blobs()
             for blob in blob_list:
                 if blob.name.split(".")[-1] != "json":
@@ -280,19 +280,19 @@ async def get_pipeline_info(
                 raise PipelineNotFoundError(
                     "This version of the pipeline was not found."
                 )
-        
+
     except PipelineNotFoundError as error:
         print(error)
         return False
-    
+
     except FolderListError as error:
         print(error)
         return False
 
 def insert_new_version_pipeline(
         pipelines_json: dict,
         connection_string: str,
-        pipleine_container_name: str
+        pipeline_container_name: str
     ) -> bool:
     """
     Inserts a new version of a pipeline JSON into an Azure Blob Storage container.
@@ -312,7 +312,7 @@ def insert_new_version_pipeline(
 
         if blob_service_client:
             container_client = blob_service_client.get_container_client(
-                pipleine_container_name
+                pipeline_container_name
             )
 
             json_name = "{}/{}.json".format("pipelines", pipelines_json.get("version"))

docs/nachet-inference-documentation.md

@@ -79,7 +79,7 @@ sequenceDiagram
     Backend-)Frontend: error 500 Failed to retrieve data from the repository
     end
     Note over Backend,Blob storage: end of initialisation
-   
+
     Client->>+Frontend: applicationStart()
     Frontend-)Backend: HTTP POST req.
     Backend-)Backend: get_model_endpoints_metadata()
@@ -103,7 +103,7 @@ sequenceDiagram
     Backend-)Backend: mount_container(connection_string(Environnement Variable, container_name))
     Backend-)+Blob storage: HTTP POST req.
     Blob storage--)-Backend: container_client
-    
+
     Backend-)Backend: Generate Hash(image_bytes)
 
     Backend-)Backend: upload_image(container_client, folder_name, image_bytes, hash_value)
@@ -260,7 +260,7 @@ async def get_pipeline(mock:bool = False):
         cipher_suite = Fernet(FERNET_KEY)
     # Get all the api_call function and map them in a dictionary
     api_call_function = {func.split("from_")[1]: getattr(model_module, func) for func in dir(model_module) if "inference" in func.split("_")}
-    # Get all the inference functions and map them in a dictionary 
+    # Get all the inference functions and map them in a dictionary
     inference_functions = {func: getattr(inference, func) for func in dir(inference) if "process" in func.split("_")}
 
     models = ()
@@ -275,12 +275,12 @@ async def get_pipeline(mock:bool = False):
             model.get("deployment_platform")
         )
         models += (m,)
-    
+
     # Build the pipeline to call the models in order in the inference request
     for pipeline in result_json.get("pipelines"):
         CACHE["pipelines"][pipeline.get("pipeline_name")] = tuple([m for m in models if m.name in pipeline.get("models")])
 
-    return result_json.get("pipelines") 
+    return result_json.get("pipelines")
 
 ```
 

model_inference/inference.py

@@ -45,7 +45,7 @@ async def process_image_slicing(image_bytes: bytes, result_json: dict) -> list:
         img.save(buffered, format)
 
         cropped_images[i] = base64.b64encode(buffered.getvalue()) #.decode("utf8")
-    
+
     return cropped_images
 
 async def process_swin_result(img_box:dict, results: dict) -> list:
@@ -61,7 +61,7 @@ async def process_swin_result(img_box:dict, results: dict) -> list:
         img_box[0]['boxes'][i]['label'] = result[0].get("label")
         img_box[0]['boxes'][i]['score'] = result[0].get("score")
         img_box[0]['boxes'][i]["topN"] = [d for d in result]
-    
+
     return img_box
 
 async def process_inference_results(data, imageDims):

model_inference/model_module.py

@@ -51,7 +51,7 @@ async def request_inference_from_seed_detector(model: namedtuple, previous_resul
 
     Returns:
         dict: A dictionary containing the result JSON and the images generated from the inference.
-    
+
     Raises:
         InferenceRequestError: If an error occurs while processing the request.
     """
@@ -67,7 +67,7 @@ async def request_inference_from_seed_detector(model: namedtuple, previous_resul
         }
     except Exception as e:
         raise InferenceRequestError(f"An error occurred while processing the request:\n {str(e)}")
-    
+
 
 async def request_inference_from_nachet_6seeds(model: namedtuple, previous_result: str):
     """
@@ -93,7 +93,7 @@ async def request_inference_from_nachet_6seeds(model: namedtuple, previous_resul
 
     except Exception as e:
         raise InferenceRequestError(f"An error occurred while processing the request:\n {str(e)}")
-   
+
 async def request_inference_from_test(model: namedtuple, previous_result: str):
     """
     Requests a test case inference.

model_request/model_request.py

@@ -24,14 +24,14 @@ async def request_factory(img_bytes: str | bytes, model: namedtuple) -> Request:
     if deployment_platform in supported_deployment_platform:
         headers[model.deployment_platform[deployment_platform]] = model.name
 
-    if isinstance(img_bytes, str): 
+    if isinstance(img_bytes, str):
         data = {
             "input_data": {
                 "columns": ["image"],
                 "index": [0],
                 "data": [img_bytes],
             }
-        } 
+        }
         body = str.encode(json.dumps(data))
     elif isinstance(img_bytes, bytes):
         body = img_bytes

tests/test_azure_storage_api.py

@@ -170,7 +170,7 @@ def test_get_pipeline_info_successful(self, MockFromConnectionString,):
         mock_blob_service_client.get_container_client.return_value = (
             mock_container_client
         )
-    
+
         connection_string = "test_connection_string"
         mock_blob_name = "test_blob"
         mock_version = "v1"

tests/test_inference_request.py

@@ -13,9 +13,8 @@ def setUp(self) -> None:
         Set up the test environment before running each test case.
         """
          # Start the test pipeline
-        self.loop = asyncio.get_event_loop()    
         self.test = app.test_client()
-        response = self.loop.run_until_complete(
+        response = asyncio.run(
             self.test.get("/test")
         )
         self.pipeline = json.loads(asyncio.run(response.get_data()))[0]
@@ -38,7 +37,7 @@ def tearDown(self) -> None:
 
     @patch("azure.storage.blob.BlobServiceClient.from_connection_string")
     def test_inference_request_successful(self, MockFromConnectionString):
-        
+
         # Mock azure client services
         mock_blob = Mock()
         mock_blob.readall.return_value = bytes(self.image_src, encoding="utf-8")
@@ -73,7 +72,7 @@ def test_inference_request_successful(self, MockFromConnectionString):
         }
 
         # Test the answers from inference_request
-        response = self.loop.run_until_complete(
+        response = asyncio.run(
             self.test.post(
                 '/inf',
                 headers={
@@ -121,7 +120,7 @@ def test_inference_request_unsuccessfull(self, MockFromConnectionString):
         expected = 500
 
         # Test the answers from inference_request
-        response = self.loop.run_until_complete(
+        response = asyncio.run(
             self.test.post(
                 '/inf',
                 headers={
@@ -157,8 +156,8 @@ def test_inference_request_missing_argument(self):
 
         for k, v in data.items():
             if k != "model_name":
-                data[k] = ""        
-                response = self.loop.run_until_complete(
+                data[k] = ""
+                response = asyncio.run(
                     self.test.post(
                         '/inf',
                         headers={
@@ -177,7 +176,7 @@ def test_inference_request_missing_argument(self):
 
         if len(responses) > 1:
             raise ValueError(f"Different errors messages were given; expected only 'missing request arguments', {responses}")
-        
+
         print(expected == result_json[0])
         print(response.status_code == 400)
         self.assertEqual(result_json[0], expected)
@@ -188,7 +187,7 @@ def test_inference_request_wrong_pipeline_name(self):
         expected = ("Model wrong_pipeline_name not found")
 
         # Test the answers from inference_request
-        response = self.loop.run_until_complete(
+        response = asyncio.run(
             self.test.post(
                 '/inf',
                 headers={
@@ -217,7 +216,7 @@ def test_inference_request_wrong_header(self):
         expected = ("Invalid image header")
 
         # Test the answers from inference_request
-        response = self.loop.run_until_complete(
+        response = asyncio.run(
             self.test.post(
                 '/inf',
                 headers={
@@ -243,4 +242,3 @@ def test_inference_request_wrong_header(self):
 
 if __name__ == '__main__':
     unittest.main()
-