Code Editor for app.py

import streamlit as st
import pandas as pd
import numpy as np

# Configure page layout
st.set_page_config(page_title="SiSuite", layout="wide")

# Custom CSS for styling
st.markdown("""
<style>
    .sidebar .sidebar-content {
        background-color: #2E3B4E;
        color: white;
    }
    
    .metric-card {
        background-color: white;
        padding: 1rem;
        border-radius: 0.5rem;
        box-shadow: 0 2px 4px rgba(0,0,0,0.1);
        margin-bottom: 1rem;
    }
    
    .status-new {
        background-color: #28a745;
        color: white;
        padding: 2px 8px;
        border-radius: 12px;
        font-size: 0.8rem;
    }
    
    .status-active {
        background-color: #007bff;
        color: white;
        padding: 2px 8px;
        border-radius: 12px;
        font-size: 0.8rem;
    }
    
    .status-pending {
        background-color: #ffc107;
        color: black;
        padding: 2px 8px;
        border-radius: 12px;
        font-size: 0.8rem;
    }
    
    .status-archived {
        background-color: #6c757d;
        color: white;
        padding: 2px 8px;
        border-radius: 12px;
        font-size: 0.8rem;
    }
</style>
""", unsafe_allow_html=True)

# Sidebar
with st.sidebar:
    st.markdown("### 🔍 SiSuite")
    st.markdown("---")
    st.markdown("**Quick links**")
    st.markdown("📊 Dashboard")
    st.markdown("📋 Activity")
    st.markdown("📈 Documents")
    st.markdown("📁 Instruction manual")
    st.markdown("---")
    st.markdown("**Toolkits**")
    st.markdown("📊 Analytics")
    st.markdown("📄 Documents")
    st.markdown("🏷️ Tags")
    st.markdown("💾 Element database")
    st.markdown("---")
    st.markdown("**Account settings**")
    st.markdown("⚙️ Preferences")
    st.markdown("📊 Proprietary")
    st.markdown("📧 Alerts")

# Main content
st.title("Dashboard")

# Create two columns for the main content
col1, col2 = st.columns(2)

with col1:
    st.subheader("Element records (non-Current revisions)")
    
    # Create sample data for element records
    element_data = {
        'Tag/Name': ['Amine Recovery-01-EBC-Baruya', 'Alternating Valves-TA01', 'DL', 'TaH', 'Hydraulic system 942-502', 'Approx-nal'],
        'Revisions number': [2.0, 1.0, 0.0, 0.0, 2.0, 0.0],
        'Current status': ['New', 'New', 'New', 'New', 'New', 'New'],
        'Actions': ['⚙️', '⚙️', '⚙️', '⚙️', '⚙️', '⚙️']
    }
    
    df_elements = pd.DataFrame(element_data)
    st.dataframe(df_elements, use_container_width=True, hide_index=True)
    
    st.subheader("FMEA documents (non-Current revisions)")
    
    # Create sample data for FMEA documents
    fmea_data = {
        'Tag/Name': ['Amine plant system', 'Downcast FSMA'],
        'Revisions number': [2.0, 1.0],
        'Current status': ['Pending', 'New'],
        'Actions': ['⚙️', '⚙️']
    }
    
    df_fmea = pd.DataFrame(fmea_data)
    st.dataframe(df_fmea, use_container_width=True, hide_index=True)

with col2:
    st.subheader("Evaluation records (non-Current revisions)")
    
    # Create sample data for evaluation records
    eval_data = {
        'Tag/Name': ['Amine-XDS-05-Valve', 'Server for Element Demo Model-Gener'],
        'Revisions number': [0.0, 1.0],
        'Current status': ['New', 'New'],
        'Actions': ['⚙️', '⚙️']
    }
    
    df_eval = pd.DataFrame(eval_data)
    st.dataframe(df_eval, use_container_width=True, hide_index=True)
    
    st.subheader("LIDPAs (non-Current revisions)")
    
    # Create sample data for LIDPAs
    lidpa_data = {
        'Tag/Name': [
            'LAST REQUEST 12932',
            'Clean 23',
            'LMC',
            'Auto-Cleanup',
            'Mild Discharge Gas Release Protection',
            'FD01',
            'Jorom Rach Safre Spring',
            'Safeguard for FH-01 DABA FI/HI/23ACFS',
            'Jorom Disc 12'
        ],
        'Revisions number': [1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
        'Current status': ['Active', 'New', 'New', 'New', 'New', 'Active', 'Active', 'Active', 'New'],
        'Actions': ['⚙️', '⚙️', '⚙️', '⚙️', '⚙️', '⚙️', '⚙️', '⚙️', '⚙️']
    }
    
    df_lidpa = pd.DataFrame(lidpa_data)
    st.dataframe(df_lidpa, use_container_width=True, hide_index=True)