app.py

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

st.set_page_config(layout="wide")


# 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():
    # Generate approval attributes
    cyber_approved = [random.choice([True, False]) for _ in range(50)]
    accessibility_approved = [random.choice([True, False]) for _ in range(50)]
    privacy_approved = [random.choice([True, False]) for _ in range(50)]

    review_statuses = []
    not_approved_reasons = []
    for cyber, accessibility, privacy in zip(cyber_approved, accessibility_approved, privacy_approved):
        if cyber and accessibility and privacy:  # All approvals are True
            review_statuses.append("Approved")
            not_approved_reasons.append(None)
        elif not cyber and not accessibility and not privacy:  # All approvals are False
            review_statuses.append("Not Approved")
            not_approved_reasons.append(random.choice(["Security Concern", "Licensing Issue", "Privacy Issue", "Compliance Requirement"]))
        else:  # Mixed approvals
            review_statuses.append("Under Review")
            not_approved_reasons.append(None)
            
    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": cyber_approved,
        "Accessibility Approved": accessibility_approved,
        "Privacy Approved": privacy_approved,
        "Review Date": [random_date() for _ in range(50)],
        "Review Status": review_statuses,
        "Not Approved Reason": not_approved_reasons
}
    return pd.DataFrame(products)

# Function to filter the catalog based on multiple attributes with AND logic
@st.cache_data
def filter_catalog(catalog, search_query=None, selected_category=None, cyber_approved=None, accessibility_approved=None, privacy_approved=None,review_status=None):
    filtered = catalog
    if search_query:
        filtered = filtered[filtered.apply(lambda row: search_query.lower() in str(row).lower(), axis=1)]
    if selected_category and selected_category != 'All':
        filtered = filtered[filtered["Category"] == selected_category]
    if cyber_approved:
        filtered = filtered[filtered["Cyber Approved"] == True]
    if accessibility_approved:
        filtered = filtered[filtered["Accessibility Approved"] == True]
    if privacy_approved:
        filtered = filtered[filtered["Privacy Approved"] == True]
    if review_status and review_status != 'All':
        filtered = filtered[filtered["Review Status"] == review_status]
    return filtered

catalog = load_catalog()


st.markdown("""
<style>
.custom-header {
    font-size: 24px;
    font-weight: bold;
    color: #4f8bf9;
    margin-bottom: 10px;
}
.custom-text {
    font-size: 16px;
    margin-bottom: 20px;
}
.custom-button {
    margin: 5px;
}
.stButton>button {
    border: 2px solid #4f8bf9;
    border-radius: 20px;
    color: #4f8bf9;
}
.status-true {
    color: green;
}
.stDataFrame {
    font-size: 14px;
}
</style>
""", unsafe_allow_html=True)







# Streamlit app layout
st.markdown('<p class="custom-header">Enterprise Software Product Catalog</p>', unsafe_allow_html=True)
st.markdown('<p class="custom-text">This is the source of truth for app approval statuses within the enterprise.</p>', unsafe_allow_html=True)



# Sidebar for Advanced Search and Filtering
with st.sidebar:
    st.markdown('<p class="custom-header">Advanced Search Options</p>', unsafe_allow_html=True)
    search_query = st.text_input("Search by Any Attribute", key='search_query')
    selected_category = st.selectbox("Select Category", ['All'] + list(catalog["Category"].unique()), key='search_category')
    cyber_approved = st.checkbox("Cyber Approved", key='cyber_approved')
    accessibility_approved = st.checkbox("Accessibility Approved", key='accessibility_approved')
    privacy_approved = st.checkbox("Privacy Approved", key='privacy_approved')
    review_status_options = ['All', 'Approved', 'Under Review', 'Not Approved']
    review_status = st.selectbox("Select Review Status", options=review_status_options, key='review_status')


# Apply the enhanced filter based on user input
filtered_catalog = filter_catalog(catalog, search_query, selected_category, cyber_approved, accessibility_approved, privacy_approved, review_status)



# Display the filtered product catalog
st.markdown('<p class="custom-header">Product Catalog</p>', unsafe_allow_html=True)
st.dataframe(filtered_catalog.style.applymap(lambda x: "background-color: #ffffff"))

for index, row in filtered_catalog.iterrows():
    with st.expander(f"{row['Product Name']}"):
        st.markdown(f"""
            <div>
                <p><b>Category:</b> {row['Category']}</p>
                <p><b>Cyber Approved:</b> <span class='{"status-true" if row["Cyber Approved"] else ""}'>{'Yes' if row['Cyber Approved'] else 'No'}</span></p>
                <p><b>Accessibility Approved:</b> <span class='{"status-true" if row["Accessibility Approved"] else ""}'>{'Yes' if row['Accessibility Approved'] else 'No'}</span></p>
                <p><b>Privacy Approved:</b> <span class='{"status-true" if row["Privacy Approved"] else ""}'>{'Yes' if row['Privacy Approved'] else 'No'}</span></p>
                <p><b>Review Date:</b> {row['Review Date']}</p>
                <p><b>Review Status:</b> {row['Review Status']}</p>
                {'<p><b>Not Approved Reason:</b> '+row['Not Approved Reason']+'</p>' if row['Review Status'] == 'Not Approved' else ''}
            </div>
        """, unsafe_allow_html=True)