I hope I fixed the error where we were not getting all updated_dates up to the specified photo date. I had to fix it at the mongo call bc for some fucking reason the filter wasn't working properly at the dataframe. Golfech test passed

.gitignore

@@ -1,2 +1,3 @@
 /app_with_api.py
-/app_with_rte.py
+/app_with_rte.py
+/venv

app.py

@@ -33,6 +33,7 @@ def mongo_unavs_call(user_input_start_date, user_input_end_date, user_input_past
 
     start_date = f"{user_input_start_date}T00:00:00"
     end_date = f"{user_input_end_date}T23:59:59"
+    past_date = f"{user_input_past_date}T23:59:59"
     
     pipeline = [
         {
@@ -46,7 +47,8 @@ def mongo_unavs_call(user_input_start_date, user_input_end_date, user_input_past
                 "results.generation_unavailabilities.production_type": "NUCLEAR",
                 # "results.generation_unavailabilities.start_date": {"$lte": end_date},
                 # "results.generation_unavailabilities.end_date": {"$gte": start_date},
-                "results.generation_unavailabilities.updated_date": {"$lte": end_date}
+                # "results.generation_unavailabilities.updated_date": {"$lte": end_date}
+                "results.generation_unavailabilities.updated_date": {"$lte": past_date}
             }
         },
         {
@@ -158,12 +160,15 @@ def nuc_monitor(usr_start_date, usr_end_date, past_date, mongo_db_data):
     # end_date_str = usr_end_date.strftime("%Y-%m-%d")
     end_date_str = str(usr_end_date)
     current_datetime = datetime.datetime.now()
-    past_date_str = str(past_date)
+    past_date_str = str(past_date.strftime("%Y-%m-%dT%H:%M:%S%z"))
     current_datetime_str = current_datetime.strftime("%Y-%m-%d")
 
     # nuclear_unav = mongo_unavs.copy()[(mongo_unavs.copy()["production_type"] == "NUCLEAR") & (mongo_unavs.copy()["updated_date"] <= past_date_str)]
-    nuclear_unav = mongo_unavs.copy()[(mongo_unavs.copy()["production_type"] == "NUCLEAR") & (mongo_unavs.copy()["updated_date"] <= past_date_str)
-                                    & (mongo_unavs.copy()["status"] != "DISMISSED")]
+    print(past_date_str)
+    nuclear_unav = mongo_unavs[
+    (mongo_unavs["production_type"] == "NUCLEAR") &
+    # (mongo_unavs["updated_date"] <= past_date_str) &
+    (mongo_unavs["status"] != "DISMISSED")]
 
     # if photo_date == True:
     #     nuclear_unav = merged_df.copy()[(merged_df.copy()["production_type"] == "NUCLEAR") & (merged_df.copy()["updated_date"] <= past_date_str)]
@@ -181,11 +186,17 @@ def nuc_monitor(usr_start_date, usr_end_date, past_date, mongo_db_data):
 
     sorted_df = sorted_df.copy().reset_index(drop=True)
 
+    golfech_1 = sorted_df.copy()[(sorted_df.copy()["name"] == "GOLFECH 1") & (sorted_df.copy()["end_date"] >= start_date_str)]
+    print(golfech_1[['updated_date', 'available_capacity']])
+
     # Filter to get identifiers
     filtered_id_df = sorted_df.copy()
 # --------------------------- !!!!!!!!!!!!!!!!!!!!!!! HERE IS POTENTIAL ERROR!!!!!!!!!!!!!!!!!!!!!!! --------------------------- #
 # I commented this out
-    filtered_id_df.drop_duplicates(subset='identifier', keep='last', inplace=True)
+    filtered_id_df = filtered_id_df.drop_duplicates(subset='identifier', keep='last')
+
+    golfech_1 = filtered_id_df.copy()[(filtered_id_df.copy()["name"] == "GOLFECH 1") & (filtered_id_df.copy()["end_date"] >= start_date_str)]
+    print(golfech_1[['updated_date', 'available_capacity']])
 # --------------------------- !!!!!!!!!!!!!!!!!!!!!!! HERE IS POTENTIAL ERROR!!!!!!!!!!!!!!!!!!!!!!! --------------------------- #
 
     filtered_id_df = filtered_id_df.copy().reset_index(drop=True)
@@ -379,7 +390,17 @@ def get_nucmonitor_data(start_date, end_date, past_date):
     response_nucmonitor = nuc_monitor(start_date, end_date, past_date, mongo)
     # nucmonitor_data = response_nucmonitor.json()
     # nucmonitor_json = json.loads(nucmonitor_data)
-    print(response_nucmonitor)
+    # print(response_nucmonitor)
+    df = pd.read_json(response_nucmonitor)
+    return df
+
+@st.cache_data
+def get_photodate_data(start_date, end_date, past_date):
+    mongo = get_mongodb_data(start_date, end_date, past_date)
+    response_nucmonitor = nuc_monitor(start_date, end_date, past_date, mongo)
+    # nucmonitor_data = response_nucmonitor.json()
+    # nucmonitor_json = json.loads(nucmonitor_data)
+    # print(response_nucmonitor)
     df = pd.read_json(response_nucmonitor)
     return df
 
@@ -404,7 +425,7 @@ def run_app():
     else:
         st.write("Data received from Flask:")
         df_nucmonitor = get_nucmonitor_data(start_date, end_date, current_date)
-        df_photo_date = get_nucmonitor_data(start_date, end_date, past_date)
+        df_photo_date = get_photodate_data(start_date, end_date, past_date)
         # df_winter_date = get_nucmonitor_data(start_date, end_date, winter_date)
         current_date_str = str(current_date.strftime('%Y-%m-%d'))
         past_date_str = str(past_date.strftime('%Y-%m-%d'))
@@ -422,7 +443,7 @@ def run_app():
         # Get the last column
         df_nucmonitor_2 = df_nucmonitor_2.iloc[:, -1]
         
-        print(df_nucmonitor_2)
+        # print(df_nucmonitor_2)
 
         st.write(df_nucmonitor_2)
 
@@ -434,7 +455,7 @@ def run_app():
         # Get the last column
         df_photo_date_2 = df_photo_date_2.iloc[:, -1]
         
-        print(df_photo_date_2)
+        # print(df_photo_date_2)
 
         st.write(df_photo_date_2)
 
@@ -476,14 +497,14 @@ def run_app():
         monthly_average_photo_date.index = monthly_average_photo_date.index.strftime('%Y-%m')
 
 
-        print(monthly_average_nucmonitor)
-        print(monthly_average_nucmonitor.index)
-        print(len(monthly_average_nucmonitor.index) < 5)
+        # print(monthly_average_nucmonitor)
+        # print(monthly_average_nucmonitor.index)
+        # print(len(monthly_average_nucmonitor.index) < 5)
         if (len(monthly_average_nucmonitor.index) < 5) or (two_months_before not in monthly_average_nucmonitor.index or two_months_after not in monthly_average_nucmonitor.index):
             df_display_normal_bool = False
 
         else:
-            print(two_months_before, one_month_before, current_date.strftime('%Y-%m'), one_month_after, two_months_after)
+            # print(two_months_before, one_month_before, current_date.strftime('%Y-%m'), one_month_after, two_months_after)
             # Filter DataFrames based on date ranges
             df_nucmonitor_filtered = monthly_average_nucmonitor[
                 (monthly_average_nucmonitor.index == two_months_before) |
@@ -511,10 +532,10 @@ def run_app():
             past_forecast_update = df_photo_date_filtered.tolist()
             delta = [current - past for current, past in zip(current_forecast_update, past_forecast_update)]
 
-            print('Dates:', [two_months_before, one_month_before, current_date.strftime('%Y-%m'), one_month_after, two_months_after])
-            print(f"Forecast update {current_date_str}", current_forecast_update)
-            print(f"Forecast update {past_date_str}", past_forecast_update,)
-            print('Delta', delta)
+            # print('Dates:', [two_months_before, one_month_before, current_date.strftime('%Y-%m'), one_month_after, two_months_after])
+            # print(f"Forecast update {current_date_str}", current_forecast_update)
+            # print(f"Forecast update {past_date_str}", past_forecast_update,)
+            # print('Delta', delta)
 
             # Create a DataFrame for display
             data_avg_expected_normal = {
@@ -541,11 +562,11 @@ def run_app():
         winter_end = f"{current_date.year+1}-03"
         winter_start_str = str(winter_start)
         winter_end_str = str(winter_end)
-        print("winter_start_str", winter_start)
-        print("winter_end_str", winter_end)
-        print("monthly_average_nucmonitor.index", monthly_average_nucmonitor.index)
-        print(monthly_average_nucmonitor.index == winter_start)
-        print(monthly_average_nucmonitor.index == winter_end)
+        # print("winter_start_str", winter_start)
+        # print("winter_end_str", winter_end)
+        # print("monthly_average_nucmonitor.index", monthly_average_nucmonitor.index)
+        # print(monthly_average_nucmonitor.index == winter_start)
+        # print(monthly_average_nucmonitor.index == winter_end)
         if monthly_average_nucmonitor.index.any() != winter_start or monthly_average_nucmonitor.index.any() != winter_end:
             df_display_winter_bool = False
 
@@ -566,8 +587,8 @@ def run_app():
             current_winter_forecast_update = df_nucmonitor_winter.tolist()
             past_winter_forecast_update = df_photo_date_winter.tolist()
             winter_delta = [current - past for current, past in zip(current_winter_forecast_update, past_winter_forecast_update)]
-            print("current_winter_forecast_update:", current_winter_forecast_update)
-            print("past_winter_forecast_update:", past_winter_forecast_update)
+            # print("current_winter_forecast_update:", current_winter_forecast_update)
+            # print("past_winter_forecast_update:", past_winter_forecast_update)
 
             # Create a DataFrame for display
             data_avg_expected_winter = {
@@ -576,7 +597,7 @@ def run_app():
                 f"Forecast update {past_date_str}": past_winter_forecast_update,
                 'Delta': winter_delta
             }
-            print(data_avg_expected_winter)
+            # print(data_avg_expected_winter)
             df_display_winter_bool = True
 
 # --------------------------------- AVERAGE EXPECTED AVAILABILITY WINTER PIPELINE --------------------------------- #
@@ -609,7 +630,7 @@ def run_app():
         
         # Optionally, if you want to reset the index
         # real_forecast = real_forecast.reset_index()
-        print(real_forecast)
+        # print(real_forecast)
         st.write("Real forecast")
         st.line_chart(real_forecast)
 
@@ -620,7 +641,7 @@ def run_app():
         # combined_df.columns = [f'Forecast {current_date_str}', f'Forecast {past_date_str}', 'Real Forecast', f'Winter forecast {winter_start}/{winter_end}']
         combined_df.columns = [f'Forecast {current_date_str}', f'Forecast {past_date_str}', 'Real Forecast']
 
-        print(combined_df)
+        # print(combined_df)
         st.write(f"Graph 1. {start_date} to {end_date}")
         st.line_chart(combined_df)