152 lines
5.4 KiB
Python
152 lines
5.4 KiB
Python
import streamlit as st
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import pandas as pd
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import subprocess
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import mysql.connector
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from datetime import datetime, timedelta
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import os
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from dotenv import load_dotenv
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load_dotenv()
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total_time_unit = []
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def get_filtered_users(customer_id, start_date, end_date):
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mydb = mysql.connector.connect(
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host=os.getenv("MYSQL_HOST"),
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user=os.getenv("MYSQL_USER"),
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password=os.getenv("MYSQL_PASSWORD"),
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database=os.getenv("MYSQL_DATABASE")
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)
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# Prepare the base query with date filter
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query = f"""
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SELECT number, title, createdate, time FROM Kunden.tickets
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WHERE closedate BETWEEN '{start_date}' AND '{end_date}'
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"""
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if customer_id:
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query += f" AND customer_ID = {customer_id}"
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query += " ORDER BY createdate"
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users = pd.read_sql_query(query, mydb)
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mydb.close()
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# Format date columns
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for column in users.select_dtypes(include=['datetime64[ns]', 'datetime64[ns, UTC]']).columns:
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users[column] = users[column].dt.strftime('%d.%m.%Y')
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# Convert 'time' to integer
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users.iloc[:, 3] = users.iloc[:, 3].str.split('.').str[0]
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users['time'] = users['time'].astype(int)
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# Create hyperlink for ticket number
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base_url = "https://ticket.stines.de/#ticket/zoom/number/"
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users['Link'] = users['number'].apply(lambda x: f'<a href="{base_url}{x}" target="_blank">{x}</a>')
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return users
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def get_initial_data():
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mydb = mysql.connector.connect(
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host=os.getenv("MYSQL_HOST"),
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user=os.getenv("MYSQL_USER"),
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password=os.getenv("MYSQL_PASSWORD"),
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database=os.getenv("MYSQL_DATABASE")
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)
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# Fetch unique service IDs and names
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service_id_query = """
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SELECT DISTINCT s.service_ID, s.name
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FROM Kunden.services s
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"""
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service_ids = pd.read_sql_query(service_id_query, mydb)
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# Fetch customer information
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customer_query = """
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SELECT DISTINCT c.customer_ID, c.customer, co.companyname
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FROM Kunden.company co
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JOIN Kunden.customers c ON co.customer_ID = c.customer_ID
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"""
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customers = pd.read_sql_query(customer_query, mydb)
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mydb.close()
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return service_ids, customers
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def run_script_and_list_documents():
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output_area = st.empty() # Placeholder for output
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document_paths = [] # List to store generated document paths
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# Directory where the script should be run
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working_directory = "apps/ticket_export/exports"
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# Run the script in the specified directory
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result = subprocess.run(
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["python3", "apps/ticket_export/main.py"],
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capture_output=True,
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text=True
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)
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# Search for generated documents in the working directory
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for filename in os.listdir(working_directory):
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if filename.endswith(".docx"):
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full_path = os.path.join(working_directory, filename)
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document_paths.append(full_path)
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# Display the list of generated documents and offer them for download
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if document_paths:
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st.write("Generated Documents:")
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for doc_path in document_paths:
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with open(doc_path, "rb") as file:
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st.download_button(
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label=f"Download {os.path.basename(doc_path)}",
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data=file,
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file_name=os.path.basename(doc_path),
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mime="application/vnd.openxmlformats-officedocument.wordprocessingml.document"
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)
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else:
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st.write("No documents found.")
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def ticket_filter():
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st.title("Ticket Filter :mag_right:")
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# Get initial data for widgets
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initial_service_ids, customers = get_initial_data()
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# Add selection widget for customer ID
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selected_customer = st.selectbox(
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'Select Customer',
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["All"] + customers.apply(lambda row: f"{row['customer_ID']} - {row['companyname']} - {row['customer']}",
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axis=1).tolist()
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)
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# Extract customer_ID from selected option
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selected_customer_id = None if selected_customer == "All" else int(selected_customer.split(' - ')[0])
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# Add date range picker
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start_date = st.date_input("Start Date", datetime.now() - timedelta(days=30))
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end_date = st.date_input("End Date", datetime.now())
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if st.button("Create Invoice"):
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st.write("Running the script...")
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run_script_and_list_documents()
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# Add a button to apply filters
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if st.button('Apply Filters'):
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if start_date > end_date:
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st.error("Error: End date must be greater than or equal to start date.")
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else:
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# Fetch filtered data from the database
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filtered_data = get_filtered_users(selected_customer_id, start_date, end_date)
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if not filtered_data.empty:
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st.markdown(filtered_data.to_html(escape=False), unsafe_allow_html=True)
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# Convert DataFrame to CSV
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csv = filtered_data.drop(columns=['Link']).to_csv(index=False)
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st.write(f"Total Time Unit: {filtered_data['time'].sum()}")
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# Create a download button with a custom file name
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st.download_button(
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label="Download CSV",
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data=csv,
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file_name=f"filtered_data_{selected_customer}.csv", # Custom file name
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mime='text/csv',
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)
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else:
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st.write("No data available for the selected filters.")
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if __name__ == "__main__":
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ticket_filter() |