Added current and past date forecast; removed photodate boolean from everywhere; improved caching

app.py

@@ -13,7 +13,7 @@ from calendar import monthrange
 import pymongo
 from mongoengine import StringField, ListField, DateTimeField, DictField
 
-def mongo_unavs_call(user_input_start_date, user_input_end_date, user_input_photo_date, user_input_past_date):
+def mongo_unavs_call(user_input_start_date, user_input_end_date, user_input_past_date):
     print("Starting mongo_unavs_call")
     # Connect to the MongoDB database
     user = "dmarroquin"
@@ -201,7 +201,7 @@ def get_unavailabilities(usr_start_date, usr_end_date):
 # --------------------------------------------------------------------------------------- #
 
 
-def nuc_monitor(usr_start_date, usr_end_date, photo_date, past_date):
+def nuc_monitor(usr_start_date, usr_end_date, past_date, mongo_db_data, rte_data):
     # # Slightly changed metadata to fit the data from the RTE API: ST-LAURENT B 2 --> ST LAURENT 2, ....
 
     plants_metadata = {"BELLEVILLE 1": 1310.0, "BELLEVILLE 2": 1310.0, "BLAYAIS 1": 910.0, "BLAYAIS 2": 910.0, 
@@ -221,8 +221,9 @@ def nuc_monitor(usr_start_date, usr_end_date, photo_date, past_date):
 
     # --------------------- INITIAL DATA CLEANING FOR RTE DATA ------------------------ #  
     # unav_API = rte_data.json()
-    rte_stuff = get_unavailabilities(usr_start_date, usr_end_date)
-    unav_API = rte_stuff
+    # rte_stuff = get_unavailabilities(usr_start_date, usr_end_date)
+    # rte_stuff = get_rte_data(usr_start_date, usr_end_date)
+    unav_API = rte_data
     # print(unav_API)
     # Store the unavailabilities in a list
     unavailabilities = []
@@ -260,8 +261,10 @@ def nuc_monitor(usr_start_date, usr_end_date, photo_date, past_date):
     # --------------------- INITIAL DATA CLEANING FOR MONGO DATA ------------------------ #    
 
     # # Create a DataFrame
-    mongo_data = mongo_unavs_call(usr_start_date, usr_end_date, photo_date, past_date)
-    mongo_df = pd.DataFrame(mongo_data)
+    # mongo_data = mongo_unavs_call(usr_start_date, usr_end_date, past_date)
+    # mongo_data = get_mongodb_data(usr_start_date, usr_end_date, past_date)
+
+    mongo_df = pd.DataFrame(mongo_db_data)
 
     # Unpack the dictionaries into separate columns
     mongo_df_unpacked = pd.json_normalize(mongo_df['generation_unavailabilities'])
@@ -310,11 +313,13 @@ def nuc_monitor(usr_start_date, usr_end_date, photo_date, past_date):
     past_date_str = str(past_date)
     current_datetime_str = current_datetime.strftime("%Y-%m-%d")
 
-    if photo_date == True:
-        nuclear_unav = merged_df.copy()[(merged_df.copy()["production_type"] == "NUCLEAR") & (merged_df.copy()["updated_date"] <= past_date_str)]
-        photo_date = True
-    else: # need to add updated_date as a conditional to get the newest for that day
-        nuclear_unav = merged_df.copy()[(merged_df.copy()["production_type"] == "NUCLEAR") & (merged_df.copy()["updated_date"] <= end_date_str)]
+    nuclear_unav = merged_df.copy()[(merged_df.copy()["production_type"] == "NUCLEAR") & (merged_df.copy()["updated_date"] <= past_date_str)]
+
+    # if photo_date == True:
+    #     nuclear_unav = merged_df.copy()[(merged_df.copy()["production_type"] == "NUCLEAR") & (merged_df.copy()["updated_date"] <= past_date_str)]
+    #     photo_date = True
+    # else: # need to add updated_date as a conditional to get the newest for that day
+    #     nuclear_unav = merged_df.copy()[(merged_df.copy()["production_type"] == "NUCLEAR") & (merged_df.copy()["updated_date"] <= end_date_str)]
 
 # --------------------------- HERE IS THE CHANGE TO GET ONLY ACTIVE OR ACTIVE AND INACTIVE --------------------------- #
 
@@ -489,18 +494,11 @@ def nuc_monitor(usr_start_date, usr_end_date, photo_date, past_date):
     output_results = {plant: {str(date): power for date, power in plant_data.items()} for plant, plant_data in output_results.items()}
     # print(output_results)
     # -------------------------------------------------
-    if photo_date == False:
 
-        json_data = json.dumps(output_results)
-        # print(json_data)
-        return json_data
-    else:
-
-        json_data = json.dumps(output_results)
-        # print(json_data)
-        return json_data
+    json_data = json.dumps(output_results)
+    # print(json_data)
+    return json_data
     # -------------------------------------------------
-    return 
 
 @st.cache_data
 def get_rte_data(start_date, end_date):
@@ -508,13 +506,15 @@ def get_rte_data(start_date, end_date):
     print(rte_data)
     return rte_data
 @st.cache_data
-def get_mongodb_data(start_date, end_date, photo_date, past_date):
-    database_data = mongo_unavs_call(start_date, end_date, photo_date, past_date)
+def get_mongodb_data(start_date, end_date, past_date):
+    database_data = mongo_unavs_call(start_date, end_date, past_date)
     return database_data
 
 @st.cache_data
-def get_nucmonitor_data(start_date, end_date, photo_date, past_date):
-    response_nucmonitor = nuc_monitor(start_date, end_date, photo_date, past_date)
+def get_nucmonitor_data(start_date, end_date, past_date):
+    mongo = get_mongodb_data(start_date, end_date, past_date)
+    rte = get_rte_data(start_date, end_date)
+    response_nucmonitor = nuc_monitor(start_date, end_date, past_date, mongo, rte)
     # nucmonitor_data = response_nucmonitor.json()
     # nucmonitor_json = json.loads(nucmonitor_data)
     print(response_nucmonitor)
@@ -528,66 +528,57 @@ def run_app():
     # Get user input (e.g., dates)
     start_date = st.date_input("Start Date")
     end_date = st.date_input("End Date")
-    photo_date = st.checkbox("Photodate")
-
-    if photo_date == True:
-        past_date = st.date_input("Cutoff Date")
-    else:
-        past_date = None
+    past_date = st.date_input("Cutoff Date")
+    current_date = datetime.datetime.now()
 
     with st.form("nucmonitor_form"):
         submitted = st.form_submit_button("Get Nucmonitor")
 
     if not submitted:
-        pass
+        st.write("Form not submitted")
 
     else:
         st.write("Data received from Flask:")
-        df = get_nucmonitor_data(start_date, end_date, photo_date, past_date)
-        # st.sidebar.write("FILTERS")
-
-        st.write(df)  # Display DataFrame
-
-        # Create a line chart using Streamlit
-        st.title("Power Plant Data Visualization")
-        df1 = df.iloc[:-1, :-1]
-        # Create a line chart using Streamlit
-        st.line_chart(df1)
-
-        # ---------------------------------------------------
-        #######################################################
-        #################### FILTERS ##########################
-        #######################################################
-        # if df is not None:
-
-        # st.title("Data Filters")
-        # df_columns_lst = df.columns.tolist()
-        # print("df_columns_lst", df_columns_lst)
-
-        # # Select columns for display
-        # selected_columns = st.sidebar.multiselect("Select Columns to Display", 
-        #     options=df_columns_lst,
-        #     default=df_columns_lst,
-        #     key=None
-        #     )
-
-        # st.sidebar.write('Selected plants:', selected_columns)
-
-        # # Filter rows by checking column 0
-        # # filter_row_contains_value = st.sidebar.checkbox("Filter Rows by Date", False)
-
-        # # filtered_df = df.copy()
-        # print("filtered_df = df.copy()")
-        # filtered_by_plant = df.copy()[selected_columns]
-        # print("filtered_df = filtered_df[selected_columns]")
+        df_nucmonitor = get_nucmonitor_data(start_date, end_date, current_date)
+        df_photo_date = get_nucmonitor_data(start_date, end_date, past_date)
+
+        st.write("Nucmonitor")
+        st.write(df_nucmonitor)  # Display DataFrame
+        
+        st.write("Photo Date")
+        st.write(df_photo_date)
+        
+        # # Create a line chart using Streamlit
+        # st.title("Power Plant Data Visualization")
+        # df1 = df.iloc[:-1, :-1]
+        # # Create a line chart using Streamlit
+        # st.line_chart(df1)
+        # st.write(df1)
+
+        # Get info on current forecast Nucmonitor
+        st.title("Total Energy per Day at Current Forecast")
         
-        # # if filter_row_contains_value:
-        # #     filtered_df = filtered_df[filtered_df.iloc[:, 0].astype(str).str.contains('0', case=False, na=False)]
+        # Remove the final row 'Total'
+        df_nucmonitor_2 = df_nucmonitor.iloc[:-1, :]
+        # Get the last column
+        df_nucmonitor_2 = df_nucmonitor_2.iloc[:, -1]
+        
+        st.write(df_nucmonitor_2)
+
+        st.line_chart(df_nucmonitor_2)
 
-        # st.write("Filtered Data:")
-        # st.write(filtered_by_plant)
-        # print("st.write(filtered_df)")
+        # Get info on past date forecast Nucmonitor
+        st.title("Total Energy per Day at Past Date Forecast")
         
+        # Remove the final row 'Total'
+        df_photo_date_2 = df_photo_date.iloc[:-1, :]
+        # Get the last column
+        df_photo_date_2 = df_photo_date_2.iloc[:, -1]
+        
+        st.write(df_photo_date_2)
+
+        st.line_chart(df_photo_date_2)
+
         # Add a download button
         # Create a BytesIO object to hold the Excel data
         excel_buffer = io.BytesIO()
@@ -603,7 +594,7 @@ def run_app():
 
 
         # Save the DataFrame to the BytesIO object as an Excel file
-        df.to_excel(excel_buffer, index=True)
+        df_nucmonitor_2.to_excel(excel_buffer, index=True)
         # Set the cursor position to the beginning of the BytesIO object
         excel_buffer.seek(0)
 
@@ -615,8 +606,5 @@ def run_app():
             mime="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
         )
 
-
-
-
 if __name__ == '__main__':
     run_app()