import streamlit as st import pandas as pd import mysql.connector from datetime import datetime, date, timedelta from sqlalchemy import create_engine import os from dotenv import load_dotenv import altair as alt load_dotenv() def get_filtered_data(customer_id, service_id, start_date, end_date): """ Fetches the user count data grouped by month within the specified date range. """ db_url = ( f"mysql+mysqlconnector://{os.getenv('MYSQL_USER')}:" f"{os.getenv('MYSQL_PASSWORD')}@{os.getenv('MYSQL_HOST')}/" f"{os.getenv('MYSQL_DATABASE')}" ) engine = create_engine(db_url) query = f""" SELECT DATE_FORMAT(add_date, '%Y-%m') AS day, count as count FROM Kunden.`daily.users.count_by_services` WHERE customer_ID = {customer_id} AND services_ID = {service_id} AND add_date BETWEEN '{start_date}' AND '{end_date}' ORDER BY DATE_FORMAT(add_date, '%Y-%m'); """ service_reporting = pd.read_sql_query(query, engine) #engine.close() return service_reporting def get_user_online(customer_id,service_id,start_date,end_date): db_url = ( f"mysql+mysqlconnector://{os.getenv('MYSQL_USER')}:" f"{os.getenv('MYSQL_PASSWORD')}@{os.getenv('MYSQL_HOST')}/" f"{os.getenv('MYSQL_DATABASE')}" ) engine = create_engine(db_url) if service_id == 100: user_info = "sr.primarymail" else: user_info = "sr.username" query = f""" SELECT {user_info} as username FROM Kunden.`daily.user.online` sr WHERE sr.customer_ID = {customer_id} AND sr.services_ID = {service_id} AND sr.timestamp BETWEEN '{start_date}' AND '{end_date}' GROUP BY {user_info} ORDER BY {user_info}; """ user_online = pd.read_sql_query(query, engine) user_online_count= user_online.shape[0] #mydb.close() return user_online, user_online_count def get_max_user_count(customer_id, service_id, start_date, end_date): """ Fetches the maximum user count within the specified date range. """ db_url = ( f"mysql+mysqlconnector://{os.getenv('MYSQL_USER')}:" f"{os.getenv('MYSQL_PASSWORD')}@{os.getenv('MYSQL_HOST')}/" f"{os.getenv('MYSQL_DATABASE')}" ) engine = create_engine(db_url) user_info = "sr.username" query = f""" SELECT MAX(username) as max_count FROM Kunden.`daily.user.enabled` WHERE customer_ID = {customer_id} AND services_ID = {service_id} AND timestamp BETWEEN '{start_date}' AND '{end_date}' """ max_user_count = pd.read_sql_query(query, engine) #mydb.close() return max_user_count.iloc[0]['max_count'] if not max_user_count.empty else 0 def get_active_users(customer_id, service_id, start_date, end_date): """ Fetch all active users for the given customer, service, and date range based on the most recent activity and status. """ db_url = ( f"mysql+mysqlconnector://{os.getenv('MYSQL_USER')}:" f"{os.getenv('MYSQL_PASSWORD')}@{os.getenv('MYSQL_HOST')}/" f"{os.getenv('MYSQL_DATABASE')}" ) engine = create_engine(db_url) if service_id == 100: user_info = "sr.primarymail" else: user_info = "sr.username" query = f""" SELECT {user_info} as username FROM Kunden.`daily.user.enabled` sr WHERE sr.customer_ID = {customer_id} AND sr.services_ID = {service_id} AND sr.timestamp = '{start_date}' ORDER BY {user_info}; """ active_users = pd.read_sql_query(query, engine) user_active_count = active_users.shape[0] return active_users, user_active_count def get_user_not_online(customer_id,service_id,start_date,end_date): db_url = ( f"mysql+mysqlconnector://{os.getenv('MYSQL_USER')}:" f"{os.getenv('MYSQL_PASSWORD')}@{os.getenv('MYSQL_HOST')}/" f"{os.getenv('MYSQL_DATABASE')}" ) engine = create_engine(db_url) if service_id == 100: user_info = "primarymail" else: user_info = "username" query = f""" SELECT {user_info} as username FROM Kunden.`daily.user.notonline` sr WHERE sr.customer_ID = {customer_id} AND sr.services_ID = {service_id} AND sr.timestamp BETWEEN '{start_date}' AND '{end_date}' GROUP BY {user_info} ORDER BY {user_info}; """ not_active_users = pd.read_sql_query(query, engine) user_not_online_count = not_active_users.shape[0] return not_active_users, user_not_online_count def get_initial_data(): db_url = ( f"mysql+mysqlconnector://{os.getenv('MYSQL_USER')}:" f"{os.getenv('MYSQL_PASSWORD')}@{os.getenv('MYSQL_HOST')}/" f"{os.getenv('MYSQL_DATABASE')}" ) engine = create_engine(db_url) # Fetch unique service IDs and names service_id_query = """ SELECT DISTINCT s.service_ID, s.name FROM Kunden.`services.reporting` sr JOIN Kunden.services s ON sr.service_ID = s.service_ID """ service_ids = pd.read_sql_query(service_id_query, engine) # Fetch customer information customer_query = """ SELECT c.customer_ID, c.customer, co.companyname FROM Kunden.company co JOIN Kunden.customers c ON co.customer_ID = c.customer_ID JOIN Kunden.`services.reporting`sr ON sr.customer_ID = co.customer_ID GROUP BY c.customer_ID, c.customer, co.companyname; """ customers = pd.read_sql_query(customer_query, engine) # Fetch date range date_query = """ SELECT MIN(reportingdate) AS min_date, MAX(reportingdate) AS max_date FROM Kunden.`services.reporting` """ date_range = pd.read_sql_query(date_query, engine) return service_ids, customers, date_range def services_reporting(): st.title("Reporting :mag_right:") # Get initial data for widgets initial_service_ids, customers, initial_date_range = get_initial_data() service_options = initial_service_ids.apply(lambda row: f"{row['service_ID']} - {row['name']}", axis=1) # Selection widget for customer ID customer_dict = {f"{row['companyname']} - {row['customer']}": row['customer_ID'] for _, row in customers.iterrows()} # Selectbox with only the customer name and company displayed selected_customer = st.selectbox( 'Select Customer', list(customer_dict.keys()) # Display only companyname and customer ) # Get the corresponding customer ID selected_customer_id = customer_dict[selected_customer] # Selection widget for service ID selected_service = st.selectbox( 'Select Service', service_options.tolist() ) selected_service_id = int(selected_service.split(' - ')[0]) # Convert date range to datetime objects min_date = initial_date_range['min_date'][0] max_date = initial_date_range['max_date'][0] min_date = (date.today().replace(day=1) - timedelta(days=1)).replace(day=1) start_date = st.date_input('Start Date', min_date) end_date = st.date_input('End Date', initial_date_range['max_date'][0]) if st.button('Apply Filters'): # Fetch filtered data from the database filtered_data = get_filtered_data(selected_customer_id, selected_service_id, start_date, end_date) # Fetch max user count in the selected range max_count = get_active_users(selected_customer_id, selected_service_id, start_date, end_date) # Sort the data by day filtered_data = filtered_data.sort_values('day') if not filtered_data.empty: # Highlight the max value in the chart filtered_data['color'] = filtered_data['count'].apply(lambda x: 'red' if x == max_count else 'steelblue') # Create an Altair bar chart bars = alt.Chart(filtered_data).mark_bar().encode( x='day:O', y='count:Q', color=alt.Color('color:N', scale=None, legend=None) ) # Add text labels to bars text = bars.mark_text( align='center', baseline='middle', dy=-10 ).encode( text='count:Q' ) # Combine bars and text into a single chart chart = (bars + text).properties( title='User Enabled' ) # Fetch the data for users not online, online, and active users not_user_online, max_count_user_not_online = get_user_not_online(selected_customer_id, selected_service_id, start_date, end_date) user_online, user_online_count = get_user_online(selected_customer_id, selected_service_id, start_date, end_date) active_users_data, user_active_count = get_active_users(selected_customer_id, selected_service_id, min_date, end_date) # Create three columns for each DataFrame col1, col2, col3, col4, col5 = st.columns([2,2,2,2,2]) # Display each DataFrame in a separate column # with col4: # st.subheader(f"{selected_service.split(' - ')[1]} - User not Online") # st.metric(label="1",label_visibility="hidden", value=max_count_user_not_online) # st.data_editor(not_user_online['username'],key="2",use_container_width=True, hide_index=True) with col2: st.subheader(f"{selected_service.split(' - ')[1]} - Enabled Users") st.metric(label="1",label_visibility="hidden", value=user_active_count) st.data_editor(active_users_data, hide_index=True) with col3: st.subheader(f"{selected_service.split(' - ')[1]} - User Online") st.metric(label="1",label_visibility="hidden", value=user_online_count) st.data_editor(user_online,key=2,hide_index=True) st.altair_chart(chart, use_container_width=True) else: st.write("No data available for the selected filters.")