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import pandas as pd
import streamlit as st
# Set page configuration with a title and layout
st.set_page_config(page_title="Umami Data Processing", layout="wide")
# Display the main title of the application
st.title("Umami Data Processing")
st.subheader('Importing CSVs from Umami Cloud to Self-Hosted Umami Data Processing Online')
# Provide a link to a tutorial for more detailed instructions
st.markdown("""
For detailed instructions on how to use this tool, please visit [myblog](https://blog.closex.org/posts/29bdb155/) or [Youtube Video]().
""")
# Widget to upload the CSV file
uploaded_file = st.file_uploader("Choose an Umami Cloud CSV file", type=['csv'])
# Text input for new website ID
new_website_id = st.text_input("Enter the new website ID:")
if uploaded_file is not None and new_website_id:
# Load the CSV file
df = pd.read_csv(uploaded_file)
# Update the website_id column with the user-provided website ID
df['website_id'] = new_website_id
# Define the columns for the website_event table
website_event_columns = [
'event_id', 'website_id', 'session_id', 'created_at', 'url_path',
'url_query', 'referrer_path', 'referrer_query', 'referrer_domain',
'page_title', 'event_type', 'event_name', 'visit_id'
]
# Create DataFrame for website_event data
df_website_event = df[website_event_columns]
df_website_event.to_csv('website_event.csv', index=False)
st.download_button(label="Download Website Event CSV", data=df_website_event.to_csv(index=False), file_name='website_event.csv', mime='text/csv')
# Define the columns for the session table
session_columns = [
'session_id', 'website_id', 'hostname', 'browser', 'os', 'device',
'screen', 'language', 'country', 'subdivision1', 'subdivision2',
'city', 'created_at'
]
# Create DataFrame for session data
df_session = df[session_columns]
df_session.to_csv('session.csv', index=False)
st.download_button(label="Download Session CSV", data=df_session.to_csv(index=False), file_name='session.csv', mime='text/csv')
st.success("Successfully generated website_event.csv and session.csv")
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