with open('app.py', 'w') as f:
    f.write('# Superstore Sales Dashboard\n')
    f.write('# Built step by step from a real retail dataset\n\n')
print('app.py created')

page_setup = '''import streamlit as st
import pandas as pd

st.set_page_config(page_title='Superstore Dashboard', layout='wide')

st.title('Superstore Sales Dashboard')
st.write('An interactive view of a real US retail sales dataset, nearly 10,000 genuine orders.')

@st.cache_data
def load_data():
    df = pd.read_csv('superstore_sales.csv')
    df['Order Date'] = pd.to_datetime(df['Order Date'])
    return df

sales = load_data()
'''

with open('app.py', 'a') as f:
    f.write(page_setup)
print('Page setup and data loading written')

widgets_code = '''
st.sidebar.header('Filters')
region_choice = st.sidebar.multiselect('Region', sorted(sales['Region'].unique()), default=sorted(sales['Region'].unique()))
category_choice = st.sidebar.selectbox('Category', ['All'] + sorted(sales['Category'].unique()))
min_sales = st.sidebar.slider('Minimum order sales ($)', 0, 500, 0)
show_raw = st.sidebar.checkbox('Show raw data table')
'''

with open('app.py', 'a') as f:
    f.write(widgets_code)
print('Widgets written')

filter_code = '''
filtered = sales[sales['Region'].isin(region_choice) & (sales['Sales'] >= min_sales)]
if category_choice != 'All':
    filtered = filtered[filtered['Category'] == category_choice]

col1, col2, col3 = st.columns(3)
col1.metric('Orders shown', len(filtered))
col2.metric('Total sales', f"${filtered['Sales'].sum():,.0f}")
col3.metric('Total profit', f"${filtered['Profit'].sum():,.0f}")

if show_raw:
    st.dataframe(filtered)
'''

with open('app.py', 'a') as f:
    f.write(filter_code)
print('Filtering and metrics written')

charts_code = '''
st.subheader('Sales by Sub-Category')
subcat_totals = filtered.groupby('Sub-Category')['Sales'].sum().sort_values(ascending=False)
st.bar_chart(subcat_totals)

st.subheader('Monthly Sales Trend')
monthly = filtered.set_index('Order Date')['Sales'].resample('ME').sum()
st.line_chart(monthly)
'''

with open('app.py', 'a') as f:
    f.write(charts_code)
print('Charts written')

tabs_code = '''
tab1, tab2 = st.tabs(['By Region', 'About This Data'])

with tab1:
    region_totals = filtered.groupby('Region')['Profit'].sum().sort_values(ascending=False)
    st.bar_chart(region_totals)

with tab2:
    st.write('This dashboard uses the real Sample Superstore dataset, a well-known US retail sales dataset.')
    st.write(f"Date range in the full dataset: {sales['Order Date'].min().date()} to {sales['Order Date'].max().date()}.")
'''

with open('app.py', 'a') as f:
    f.write(tabs_code)
print('Tabs written')

download_code = '''
st.sidebar.divider()
csv_data = filtered.to_csv(index=False).encode('utf-8')
st.sidebar.download_button(
    label='Download filtered data as CSV',
    data=csv_data,
    file_name='filtered_superstore_sales.csv',
    mime='text/csv',
)

st.divider()
st.caption('Built with Streamlit and pandas, on the real Sample Superstore dataset.')
'''

with open('app.py', 'a') as f:
    f.write(download_code)
print('Download button and footer written')

import py_compile
py_compile.compile('app.py', doraise=True)
with open('app.py') as f:
    final_line_count = len(f.readlines())
print(f'app.py is valid and complete: {final_line_count} lines')