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 = {
    "Product Name": [
        "Notepad++", "WinRAR", "7-Zip", "CCleaner", "TeamViewer",
        "FileZilla", "PuTTY", "WinSCP", "Everything", "Greenshot",
        "Visual Studio Code", "JetBrains IntelliJ IDEA", "Sublime Text", "Atom", "Eclipse",
        "PyCharm", "NetBeans", "Xcode", "Android Studio", "GitLab",
        "Norton Antivirus", "McAfee Total Protection", "Kaspersky Internet Security", "Bitdefender Antivirus Plus", "Avast Free Antivirus",
        "Sophos Home", "Trend Micro Antivirus+", "ESET NOD32 Antivirus", "F-Secure SAFE", "Malwarebytes",
        "Microsoft Office 365", "Google Workspace", "Slack", "Trello", "Asana",
        "Zoom", "Evernote", "Notion", "Dropbox", "Adobe Acrobat Reader",
        "Adobe Photoshop", "Adobe Illustrator", "Adobe Premiere Pro", "Final Cut Pro", "Sketch",
        "Blender", "Autodesk Maya", "CorelDRAW", "GIMP", "Inkscape"
    ],
    "Category": [
        "Utility Tools", "Utility Tools", "Utility Tools", "Utility Tools", "Utility Tools",
        "Utility Tools", "Utility Tools", "Utility Tools", "Utility Tools", "Utility Tools",
        "Development Tools", "Development Tools", "Development Tools", "Development Tools", "Development Tools",
        "Development Tools", "Development Tools", "Development Tools", "Development Tools", "Development Tools",
        "Security Software", "Security Software", "Security Software", "Security Software", "Security Software",
        "Security Software", "Security Software", "Security Software", "Security Software", "Security Software",
        "Productivity Software", "Productivity Software", "Productivity Software", "Productivity Software", "Productivity Software",
        "Productivity Software", "Productivity Software", "Productivity Software", "Productivity Software", "Productivity Software",
        "Creative Software", "Creative Software", "Creative Software", "Creative Software", "Creative Software",
        "Creative Software", "Creative Software", "Creative Software", "Creative Software", "Creative Software"
    ],
    "Cyber Approved": [True] * 50,
    "Accessibility Approved": [True] * 50,
    "Privacy Approved": [True] * 50,
    "Review Date": [datetime.now().strftime("%Y-%m-%d")] * 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)