app.py

import streamlit as st
import pandas as pd
import random
from datetime import datetime, timedelta

# Helper function to generate a random date within the last year
def random_date():
    start_date = datetime.now() - timedelta(days=365)
    random_days = random.randint(0, 365)
    return (start_date + timedelta(days=random_days)).strftime("%Y-%m-%d")

# Function to load and cache the product catalog
@st.cache_data
def load_catalog():
    products = {
        # Products and categories as defined previously...
        "Review Date": [random_date() for _ in range(50)]
    }
    return pd.DataFrame(products)

# Cached function for filtering the catalog
@st.cache_data
def filter_catalog(catalog, category=None, cyber_approved=None, accessibility_approved=None, privacy_approved=None, search_query=None):
    filtered = catalog
    if category:
        filtered = filtered[filtered["Category"].isin(category)]
    if cyber_approved is not None:
        filtered = filtered[filtered["Cyber Approved"] == cyber_approved]
    if accessibility_approved is not None:
        filtered = filtered[filtered["Accessibility Approved"] == accessibility_approved]
    if privacy_approved is not None:
        filtered = filtered[filtered["Privacy Approved"] == privacy_approved]
    if search_query:
        filtered = filtered[filtered["Product Name"].str.contains(search_query, case=False)]
    return filtered

# Load the catalog
catalog = load_catalog()


# Assuming load_catalog is defined and loads data correctly
catalog = load_catalog()

# Quick check to ensure 'Category' column exists
if 'Category' not in catalog.columns:
    st.error("The 'Category' column is missing from the DataFrame.")
else:
    category = st.sidebar.multiselect("Filter by Category", options=catalog["Category"].unique())



# Streamlit app layout
st.title("Enterprise Software Product Catalog")
st.write("This is the source of truth for app approval statuses within the enterprise.")

# Sidebar for filters
category = st.sidebar.multiselect("Filter by Category", options=catalog["Category"].unique())
cyber_approved = st.sidebar.checkbox("Cyber Approved", value=True, key="cyber")
accessibility_approved = st.sidebar.checkbox("Accessibility Approved", value=True, key="accessibility")
privacy_approved = st.sidebar.checkbox("Privacy Approved", value=True, key="privacy")
search_query = st.sidebar.text_input("Search Products", key="search")

# Apply filters based on user input
filtered_catalog = filter_catalog(
    catalog,
    category=category,
    cyber_approved=cyber_approved,
    accessibility_approved=accessibility_approved,
    privacy_approved=privacy_approved,
    search_query=search_query
)

# Display the filtered product catalog
st.dataframe(filtered_catalog)