Reports-Visual/pages/services_reporting.py

132 lines
4.8 KiB
Python

import streamlit as st
import pandas as pd
import mysql.connector
from datetime import datetime, date
import os
from dotenv import load_dotenv
load_dotenv()
st.set_page_config(page_title="Reporting")
def get_filtered_data(customer_id, service_id, start_date, end_date):
mydb = mysql.connector.connect(
host=os.getenv("MYSQL_HOST"),
user=os.getenv("MYSQL_USER"),
password=os.getenv("MYSQL_PASSWORD"),
database=os.getenv("MYSQL_DATABASE")
)
# Prepare the query
query = f"""
SELECT DATE_FORMAT(sr.reportingdate, '%Y-%m') AS month,
COUNT(DISTINCT sr.username) as count
FROM Kunden.`services.reporting` sr
JOIN Kunden.services s ON sr.service_ID = s.service_ID
WHERE sr.customer_ID = {customer_id}
AND sr.service_ID = {service_id}
AND sr.username NOT LIKE '%admin%'
AND sr.username NOT LIKE '%test%'
AND sr.reportingdate BETWEEN '{start_date}' AND '{end_date}'
GROUP BY DATE_FORMAT(sr.reportingdate, '%Y-%m')
ORDER BY DATE_FORMAT(sr.reportingdate, '%Y-%m');
"""
service_reporting = pd.read_sql_query(query, mydb)
mydb.close()
return service_reporting
def get_initial_data():
mydb = mysql.connector.connect(
host=os.getenv("MYSQL_HOST"),
user=os.getenv("MYSQL_USER"),
password=os.getenv("MYSQL_PASSWORD"),
database=os.getenv("MYSQL_DATABASE")
)
# 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, mydb)
# 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, mydb)
# 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, mydb)
mydb.close()
return service_ids, customers, date_range
def generate_month_range(min_date, max_date):
months = pd.date_range(start=min_date, end=max_date, freq='MS').strftime("%Y-%m").tolist()
return months
def services_reporting():
st.title("Reporting :mag_right:")
# Get initial data for widgets
initial_service_ids, customers, initial_date_range = get_initial_data()
# Combine service_ID and name for display
service_options = initial_service_ids.apply(lambda row: f"{row['service_ID']} - {row['name']}", axis=1)
# Add selection widget for customer ID
selected_customer = st.selectbox(
'Select Customer',
customers.apply(lambda row: f"{row['customer_ID']} - {row['companyname']} - {row['customer']}", axis=1).tolist()
)
# Extract customer_ID from selected option
selected_customer_id = int(selected_customer.split(' - ')[0])
# Add selection widget for service ID
selected_service = st.selectbox(
'Select Service',
service_options.tolist()
)
# Extract service_ID from selected option
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]
# Generate month options for dropdown
month_options = generate_month_range(min_date, max_date)
# Add dropdown for start and end months
start_month = st.selectbox('Start Month', month_options)
end_month = st.selectbox('End Month', month_options, index=len(month_options) - 1)
# Convert 'YYYY-MM' to 'YYYY-MM-DD' format for SQL query
start_date = datetime.strptime(start_month, '%Y-%m').date().replace(day=1)
end_date = datetime.strptime(end_month, '%Y-%m').date().replace(day=1)
end_date = (end_date.replace(day=28) + pd.DateOffset(days=4)).replace(day=1) - pd.DateOffset(days=1) # last day of the month
# Add a button to apply filters
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)
# Sort the data by month
filtered_data = filtered_data.sort_values('month')
# Create a bar chart with the filtered data
if not filtered_data.empty:
st.bar_chart(filtered_data.set_index('month')['count'])
else:
st.write("No data available for the selected filters.")