Made stop method for uploading and experiment

decanter_ai_sdk/client.py

@@ -520,6 +520,20 @@ def predict_ts(
         )
         return prediction
 
+    def stop_uploading(self, id: str) -> None:
+        if self.api.stop_uploading(id):
+            logging.info("Uploading task: " + id + " stopped successfully.")
+        else:
+            logging.info("This task has already stopped or doesn't exist.")
+        return None
+
+    def stop_training(self, id: str) -> None:
+        if self.api.stop_training(id):
+            logging.info("Experiment: " + id + " stopped successfully.")
+        else:
+            logging.info("This task has already stopped or doesn't exist.")
+        return None
+
     def wait_for_response(self, url, id):
         pbar = tqdm(total=100, desc=url + " task is now pending")
         progress = 0
@@ -530,7 +544,9 @@ def wait_for_response(self, url, id):
                 raise RuntimeError(res["progress_message"])
 
             if res["status"] == "running":
-                pbar.set_description("[" + url + "] " + res["progress_message"])
+                pbar.set_description(
+                    "[" + url + "] " + "id: " + id + " " + res["progress_message"]
+                )
                 pbar.update(int(float(res["progress"]) * 100) - progress)
                 progress = int(float(res["progress"]) * 100)
 

decanter_ai_sdk/web_api/api.py

@@ -42,3 +42,11 @@ def get_table(self, data_id):
     @abstractmethod
     def get_model_list(self, experiment_id, query):
         raise NotImplementedError
+
+    @abstractmethod
+    def stop_uploading(self, id):
+        raise NotImplementedError
+
+    @abstractmethod
+    def stop_training(self, id):
+        raise NotImplementedError

decanter_ai_sdk/web_api/decanter_api.py

@@ -147,3 +147,21 @@ def get_model_list(self, experiment_id, query):  # pragma: no cover
             verify=False,
         )
         return res.json()["model_list"]
+
+    def stop_uploading(self, id) -> bool:  # pragma: no cover
+        res = requests.post(
+            f"{self.url}table/stop",
+            headers=self.auth_headers,
+            verify=False,
+            data={"table_id": id, "project_id": self.project_id},
+        )
+        return res.ok
+
+    def stop_training(self, id) -> bool:  # pragma: no cover
+        res = requests.post(
+            f"{self.url}experiment/stop",
+            headers=self.auth_headers,
+            verify=False,
+            data={"experiment_id": id, "project_id": self.project_id},
+        )
+        return res.ok

decanter_ai_sdk/web_api/iid_testing_api.py

@@ -74,3 +74,13 @@ def get_model_list(self, experiment_id, query):
         f = open(current_path + "/data/model_list.json")
         model_list_data = json.load(f)
         return model_list_data
+
+    def stop_uploading(self, id):
+        if id == "":
+            return False
+        return True
+
+    def stop_training(self, id):
+        if id == "":
+            return False
+        return True

decanter_ai_sdk/web_api/ts_testing_api.py

@@ -74,3 +74,13 @@ def get_model_list(self, experiment_id, query):
         f = open(current_path + "/data/model_list.json")
         model_list_data = json.load(f)
         return model_list_data
+
+    def stop_uploading(self, id):
+        if id == "":
+            return False
+        return True
+
+    def stop_training(self, id):
+        if id == "":
+            return False
+        return True

examples/iid_example.py

@@ -16,11 +16,11 @@ def test_iid():
 
     train_file_path = os.path.join(current_path, "../data/train.csv")
     train_file = open(train_file_path, "rb")
-    train_id = client.upload(train_file, "../data/test_file")
+    train_id = client.upload(train_file, "train_file")
 
     test_file_path = os.path.join(current_path, "../data/test.csv")
     test_file = open(test_file_path, "rb")
-    test_id = client.upload(test_file, "../data/test_file")
+    test_id = client.upload(test_file, "test_file")
 
     print("This will show top 2 uploaded table names and ids: \n")
 

examples/ts_example.py

@@ -9,7 +9,7 @@ def test_iid():
     auth_key = ""  # TODO fill in real authorization key
     project_id = ""  # TODO fill in real project id
     host = ""  # TODO fill in real host
-    print("---From test iid---")
+    print("---From test ts---")
 
     client = Client(auth_key=auth_key, project_id=project_id, host=host)
 

tests/test_mock_iid.py

@@ -22,6 +22,9 @@ def test_iid():
     train_file = open(train_file_path, "rb")
     train_id = client.upload(train_file, "train_file")
 
+    client.stop_uploading(train_id)
+    client.stop_uploading("")
+
     test_file_path = os.path.join(current_path, "../data/test.csv")
     test_file = open(test_file_path, "rb")
     test_id = client.upload(test_file, "test_file")
@@ -43,6 +46,9 @@ def test_iid():
         },
     )
 
+    client.stop_training(experiment.id)
+    client.stop_training("")
+
     best_model = experiment.get_best_model()
     assert (
         experiment.get_best_model_by_metric(

tests/test_mock_ts.py

@@ -23,6 +23,9 @@ def test_ts():
     train_file_df = pd.read_csv(open(train_file_path, "rb"))
     train_id = client.upload(train_file_df, "train_file")
 
+    client.stop_uploading(train_id)
+    client.stop_uploading("")
+
     test_file_path = os.path.join(current_path, "../data/ts_test.csv")
     test_file = open(test_file_path, "rb")
     test_id = client.upload(test_file, "test_file")
@@ -47,6 +50,9 @@ def test_ts():
         custom_feature_types={"Pclass": DataType.numerical},
     )
 
+    client.stop_training(experiment.id)
+    client.stop_training("")
+
     best_model = experiment.get_best_model()
 
     for metric in RegressionMetric: