Add application file

app.py

@@ -0,0 +1,97 @@
+import streamlit as st
+import requests
+import pandas as pd
+import json
+import io
+import datetime
+
+st.title("Nucmonitor 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
+
+@st.cache_data
+def get_nucmonitor_data(start_date, end_date, photo_date, past_date):
+    response_nucmonitor = requests.get(f"http://127.0.0.1:5000/nucpy/v1/nucmonitor?start_date={start_date}&end_date={end_date}&photo_date={photo_date}&past_date={past_date}")
+    nucmonitor_data = response_nucmonitor.json()
+    nucmonitor_json = json.loads(nucmonitor_data)
+    df = pd.DataFrame(nucmonitor_json)
+    return df
+
+with st.form("nucmonitor_form"):
+    submitted = st.form_submit_button("Get Nucmonitor")
+
+if submitted:
+    df = get_nucmonitor_data(start_date, end_date, photo_date, past_date)
+    st.sidebar.write("FILTERS")
+    st.write("Data received from Flask:")
+
+    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)
+
+    if df is not None:
+        st.title("Data Filters")
+        df_columns_lst = df.columns.tolist()
+        print(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_df = filtered_df[selected_columns]
+        print("filtered_df = filtered_df[selected_columns]")
+        # if filter_row_contains_value:
+        #     filtered_df = filtered_df[filtered_df.iloc[:, 0].astype(str).str.contains('0', case=False, na=False)]
+
+        st.write("Filtered Data:")
+        st.write(filtered_df)
+        print("st.write(filtered_df)")
+        
+        # Add a download button
+        current_datetime = datetime.datetime.now()
+        current_year = current_datetime.strftime('%Y')
+        current_month = current_datetime.strftime('%m')
+        current_day = current_datetime.strftime('%d')
+        current_hour = current_datetime.strftime('%H')
+        current_minute = current_datetime.strftime('%M')
+        current_second = current_datetime.strftime('%S')
+
+        # Create a BytesIO object to hold the Excel data
+        excel_buffer = io.BytesIO()
+
+        # Save the DataFrame to the BytesIO object as an Excel file
+        filtered_df.to_excel(excel_buffer, index=True)
+
+        # Set the cursor position to the beginning of the BytesIO object
+        excel_buffer.seek(0)
+
+        # Provide the BytesIO object to the download button
+        download_button = st.download_button(
+            label="Download Excel",
+            data=excel_buffer,
+            file_name=f"nucmonitor_data_{current_year}-{current_month}-{current_day}-h{current_hour}m{current_minute}s{current_second}.xlsx",
+            mime="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
+        )