import streamlit as st
import pandas as pd
import os
from io import BytesIO
from zipfile import ZipFile
html_subject = """
Upload a CSV file
"""
st.markdown(html_subject, unsafe_allow_html=True)
# Step 1: Upload CSV file
uploaded_file = st.file_uploader("", type=["csv"])
if uploaded_file is not None:
# Step 2: Read the CSV file into a DataFrame
df = pd.read_csv(uploaded_file)
if 'Invoice_No' not in df.columns:
st.error("The uploaded CSV does not contain the 'Invoice_No' column.")
else:
# Step 3: Split the DataFrame based on unique Invoice_No values
invoice_groups = df.groupby('Invoice_No')
# Step 4: Generate CSV files for each Invoice_No and add them to a ZIP archive
zip_buffer_csv = BytesIO()
with ZipFile(zip_buffer_csv, "a") as zip_file:
for invoice_no, group in invoice_groups:
csv_buffer = BytesIO()
group.to_csv(csv_buffer, index=False)
zip_file.writestr(f"{invoice_no}.csv", csv_buffer.getvalue())
zip_buffer_csv.seek(0) # Move to the beginning of the buffer
# Step 5: Generate Excel files for each Invoice_No and add them to a ZIP archive
zip_buffer_xlsx = BytesIO()
with ZipFile(zip_buffer_xlsx, "a") as zip_file:
for invoice_no, group in invoice_groups:
excel_buffer = BytesIO()
with pd.ExcelWriter(excel_buffer, engine='xlsxwriter') as writer:
group.to_excel(writer, index=False, sheet_name=str(invoice_no))
excel_buffer.seek(0)
zip_file.writestr(f"{invoice_no}.xlsx", excel_buffer.getvalue())
zip_buffer_xlsx.seek(0) # Move to the beginning of the buffer
# Step 6: Provide download buttons for both ZIP files (CSV and Excel)
button_styles = """
"""
st.markdown(button_styles, unsafe_allow_html=True)
# Download buttons
st.download_button(
label="Download Invoice ZIP (CSV)",
data=zip_buffer_csv,
file_name="invoices_csv.zip",
mime="application/zip"
)
st.download_button(
label="Download Invoice ZIP (Excel)",
data=zip_buffer_xlsx,
file_name="invoices_xlsx.zip",
mime="application/zip"
)