Updated requirements.txt to resolve ModuleNotFoundError in GitHub Act…

…ions workflow.

notebooks/Exploring_API_Functions_Authentication.ipynb

@@ -17,7 +17,10 @@
     "import datetime\n",
     "import os\n",
     "from dotenv import load_dotenv \n",
-    "from pathlib import Path"
+    "from pathlib import Path\n",
+    "import nest_asyncio\n",
+    "\n",
+    "nest_asyncio.apply()"
    ]
   },
   {
@@ -269,13 +272,15 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# 1 day raw historical data\n",
-    "one_day_raw_historical_data = opc_data.get_raw_historical_values(\n",
-    "    start_time = datetime.datetime(2024, 7, 13, 00, 00),\n",
-    "    end_time = datetime.datetime(2024, 7, 13, 23, 59),\n",
+    "# 1 day aggregated historical data\n",
+    "one_day_historical_data = opc_data.get_historical_aggregated_values(\n",
+    "    start_time=(datetime.datetime.now() - datetime.timedelta(30)),\n",
+    "    end_time=(datetime.datetime.now() - datetime.timedelta(29)),\n",
+    "    pro_interval=60*1000,\n",
+    "    agg_name=\"Average\",\n",
     "    variable_list=string_sets_for_first_park.variables_as_list([\"DCPower\"])\n",
     ")\n",
-    "one_day_raw_historical_data"
+    "one_day_historical_data"
    ]
   },
   {
@@ -284,15 +289,13 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# 1 day aggregated historical data\n",
-    "one_day_historical_data = opc_data.get_historical_aggregated_values(\n",
-    "    start_time=(datetime.datetime.now() - datetime.timedelta(30)),\n",
-    "    end_time=(datetime.datetime.now() - datetime.timedelta(29)),\n",
-    "    pro_interval=60*1000,\n",
-    "    agg_name=\"Average\",\n",
+    "# 1 day raw historical data\n",
+    "one_day_raw_historical_data = opc_data.get_raw_historical_values(\n",
+    "    start_time = datetime.datetime(2024, 7, 13, 00, 00),\n",
+    "    end_time = datetime.datetime(2024, 7, 13, 23, 59),\n",
     "    variable_list=string_sets_for_first_park.variables_as_list([\"DCPower\"])\n",
     ")\n",
-    "one_day_historical_data"
+    "one_day_raw_historical_data"
    ]
   },
   {

requirements.txt

@@ -1,3 +1,4 @@
+nest_asyncio
 sphinx_rtd_theme
 tox
 ipykernel

src/pyprediktormapclient/opc_ua.py

@@ -129,7 +129,8 @@ class WriteReturn(BaseModel):
 class AsyncIONotebookHelper:
     @staticmethod
     def run_coroutine(coroutine):
-        return asyncio.get_event_loop().run_until_complete(coroutine)
+        loop = asyncio.get_event_loop()
+        return loop.run_until_complete(coroutine)
 
 class Config:
         arbitrary_types_allowed = True
@@ -347,22 +348,40 @@ def _process_df(self, df_result: pd.DataFrame, columns: Dict[str, str]) -> pd.Da
     async def _make_request(self, endpoint: str, body: dict, max_retries: int, retry_delay: int):
         for attempt in range(max_retries):
             try:
+                logging.info(f"Attempt {attempt + 1} of {max_retries}")
                 async with ClientSession() as session:
-                    async with session.post(
-                        f"{self.rest_url}{endpoint}",
-                        json=body,
-                        headers=self.headers
-                    ) as response:
-                        response.raise_for_status()
+                    url = f"{self.rest_url}{endpoint}"
+                    logging.info(f"Making POST request to {url}")
+                    logging.debug(f"Request body: {body}")
+                    logging.debug(f"Request headers: {self.headers}")
+
+                    async with session.post(url, json=body, headers=self.headers) as response:
+                        logging.info(f"Response received: Status {response.status}")
+
+                        if response.status >= 400:
+                            error_text = await response.text()
+                            logging.error(f"HTTP error {response.status}: {error_text}")
+                            response.raise_for_status()  
+
                         return await response.json()
+
+            except aiohttp.ClientResponseError as e:
+                if e.status == 500:
+                    logging.error(f"Server Error: {e}")
+                    raise  # For 500 errors, we might want to fail fast
+                logging.error(f"ClientResponseError: {e}")
             except aiohttp.ClientError as e:
-                if attempt < max_retries - 1:
-                    wait_time = retry_delay * (2 ** attempt)
-                    logger.warning(f"Request failed. Retrying in {wait_time} seconds...")
-                    await asyncio.sleep(wait_time)
-                else:
-                    logger.error(f"Max retries reached. Error: {e}")
-                    raise RuntimeError(f'Error message {e}')
+                logging.error(f"ClientError in POST request: {e}")
+            except Exception as e:
+                logging.error(f"Unexpected error in _make_request: {e}")
+
+            if attempt < max_retries - 1:
+                wait_time = retry_delay * (2 ** attempt)
+                logging.warning(f"Request failed. Retrying in {wait_time} seconds...")
+                await asyncio.sleep(wait_time)
+            else:
+                logging.error(f"Max retries reached.")
+                raise RuntimeError('Max retries reached')
 
     def _process_content(self, content: dict) -> pd.DataFrame:
         self._check_content(content)
@@ -467,8 +486,9 @@ async def get_raw_historical_values_asyn(
         return self._process_df(combined_df, columns)
 
     def get_raw_historical_values(self, *args, **kwargs):
-        return self.helper.run_coroutine(self.get_raw_historical_values_asyn(*args, **kwargs))
-
+            result = self.helper.run_coroutine(self.get_raw_historical_values_asyn(*args, **kwargs))
+            return result
+
 
     async def get_historical_aggregated_values_asyn(
         self,
@@ -508,7 +528,8 @@ async def get_historical_aggregated_values_asyn(
         return self._process_df(combined_df, columns)
 
     def get_historical_aggregated_values(self, *args, **kwargs):
-        return self.helper.run_coroutine(self.get_historical_aggregated_values_asyn(*args, **kwargs))
+        result = self.helper.run_coroutine(self.get_historical_aggregated_values_asyn(*args, **kwargs))
+        return result
 
 
     def write_values(self, variable_list: List[WriteVariables]) -> List: