Update main.py

main.py

@@ -78,52 +78,46 @@ def your_continuous_function_old(X_Tenant):
 #     # Start the continuous function as a background task.
 #     asyncio.create_task(your_continuous_function())
 
-async def fetch_data(session, url, headers):
-    async with session.get(url, headers=headers) as response:
-        return await response.json()
-
-
-async def your_continuous_function(X_Tenant):
-    combined_df = pd.DataFrame()
-    base_url = "https://dev3.api.curfox.parallaxtec.com/api/ml/order-list"
-    headers = {
-        'Accept': 'application/json',
-        'X-Tenant': X_Tenant,
-        'Authorization': 'Bearer eyJ0eXAiOiJKV1QiLCJhbGciOiJSUzI1NiJ9.eyJhdWQiOiIxIiwianRpIjoiZWQzYjVkN2JkNTU5YmQxNWNmYzdiNThhM2UyZDlmNGEyMGQzMDFjMWY4ZWVlNDY2ZDBlZTAxYmMzZmVjMTU1ZWNjNzMxOWUxMGUxZGY3NDMiLCJpYXQiOjE3MDIyNzIyMDcuNjg0OTE2LCJuYmYiOjE3MDIyNzIyMDcuNjg0OTIzLCJleHAiOjE3MzM4OTQ2MDcuNjczNDYyLCJzdWIiOiIxIiwic2NvcGVzIjpbXX0.NFZvGO0GjoD7u3FRiIewRRoWu7ouUmKTKnCei8LMwQWzLntBLYcj_Bs21amjcHtzdbQNyCovHSDHJQaLJnD04kY1JRAdDC_OLi2YiZoSvnSJxNjWiuC4kwNE59Ndwu3o2iAzB-nd1EvyMnU_na7WxICRP8OegrpM-_q6M-wgnv7igaNeWjdxnXdtxbr-Zz7N2Xv2skWZwoDce37kWvH1tK7eqMK0uWqqyhBpli22CmkKPduHUNKMNOEnGTskeDaTuX5za2Lr8CNa34_FdKu3Y5CrFMGDBHT_UGALocpr80_38iifXm7WDl6ZIA1iYy6dBvCTeoC_aFo1X5FIrFbJgMCokW4VH0Q2ljm9ty0W7ATAiKrM1GIVFS5Dir4A1KI3LSeE459SqZpqsoJmaU95zSYbfnU_oZ9UpvW59nFgD6yJ8hGHyYnjhCS0jmxk3cq93T9X1rNWo2t0A3XYXgqZYnZrZpdrSbn-JVoX_NW1QC6RtmAGm7AtZ3GBrzxwu3m_7MicMI7Tu4W6d2WD9kZjq0khBUrm2DVZJzN2BRmH-a7JkAqJ0icpHQ_2Tc6T-95axebp6QEmHHXBKILNNwWxucZ0l-Ny0TuUivqn0m9gSJJDkA8ssWyBkzzJ9fUeRmJGbUFTeemPhMrF3_cvTUZ0J7IC2CK7qWePcHPQ-sy0is4'
-    }
-    
-    async with aiohttp.ClientSession() as session:
-        # Fetch the order count to determine the number of pages
-        order_metadata_url = "https://dev3.api.curfox.parallaxtec.com/api/ml/order-metadata"
-        metadata_response = await fetch_data(session, order_metadata_url, headers)
-        order_count = metadata_response["data"]["order_count"] // 200 + 2
-        
-        tasks = []
-        for page in range(1, 30):
-            page_url = f"{base_url}?sort=id&paginate=200&page={page}"
-            tasks.append(fetch_data(session, page_url, headers))
+async def fetch_page(session, page ,X_Tenant):
+    try:
+        url = f"https://dev3.api.curfox.parallaxtec.com/api/ml/order-list?sort=id&paginate=200&page={page}"
         
-        responses = await asyncio.gather(*tasks)
-        
-        for json_response in responses:
-            data = json_response.get('data', [])
-            if data:
-                df = pd.json_normalize(data)
-                combined_df = pd.concat([combined_df, df], ignore_index=True)
-        
-        # After processing, you can return the DataFrame as a response or save it as needed.
-        # Here, for example, we're just returning the number of rows fetched.
+        headers = {
+            'Accept': 'application/json',
+            'X-Tenant': X_Tenant,#'royalexpress',
+        }
         
-        print("data collected....")
-        data = combined_df[combined_df['status.name'].isin(['RETURN TO CLIENT', 'DELIVERED'])]
-        data = data[['delivery_possibility','status.name']]
-        data = data[data['delivery_possibility'].between(0, 100)]
-        return data
+        async with session.get(url, headers=headers) as response:
+            json_response = await response.json()
+            data = json_response['data']
+            df = pd.json_normalize(data)
+            return df
+    except Exception as e:
+        print(f"Failed to fetch data for page {page}: {e}")
+        return pd.DataFrame()  # Return an empty DataFrame in case of error
+  
 
 
 @app.get("/kpi_results")
 async def read_root(X_Tenant):
-    data = await your_continuous_function(X_Tenant)
+    combined_df = pd.DataFrame()
+
+    async with aiohttp.ClientSession() as session:
+        tasks = [fetch_page(session, page, X_Tenant) for page in range(1, 30)]
+        results = await asyncio.gather(*tasks)
+        
+        # Combine all the DataFrames from each page
+        combined_df = pd.concat(results, ignore_index=True)
+    
+    print("Data collected....")
+    
+    # Filter the data
+    filtered_data = combined_df[combined_df['status.name'].isin(['RETURN TO CLIENT', 'DELIVERED'])]
+    filtered_data = filtered_data[['delivery_possibility', 'status.name']]
+    filtered_data = filtered_data[filtered_data['delivery_possibility'].between(0, 100)]
+    
+    # existing code===========================
+    data = filtered_data
     status_counts_more_than_80 = data[data['delivery_possibility'] > 80]['status.name'].value_counts()
     
     status_counts_50_to_80 = data[(data['delivery_possibility'] >= 50) & (data['delivery_possibility'] <= 80)]['status.name'].value_counts()