"""
Leaderboard table components for the leaderboard application.
"""
import streamlit as st
from src.data.processors import get_model_type_style, get_rank_style

def render_leaderboard_table(display_df, metric_columns):
    """
    Render the custom HTML leaderboard table
    
    Args:
        display_df (pandas.DataFrame): The DataFrame with the display data
        metric_columns (list): List of metric column names
    """
    from src.components.header import render_section_header
    
    # Display model ranking header without the box
    render_section_header("Model Rankings")
    
    # Start building the HTML table structure
    html_table = """
    <div class="fixed-table-container">
      <div class="scroll-container">
        <table class="fixed-table">
          <thead>
            <tr class="header-row">
              <th class="fixed-column first-fixed-column" rowspan="2">Rank</th>
              <th class="fixed-column second-fixed-column" rowspan="2">Model + Scaffolding</th>
              <th class="model-type-cell" rowspan="2">Model Type</th>
    """
    
    # Add the metric header
    html_table += f'<th colspan="{len(metric_columns)}" class="metric-header">Margin To Human</th>'
    
    # Continue the table structure
    html_table += """
            </tr>
            <tr class="sub-header">
    """
    
    # Add individual column headers for metrics
    for col in metric_columns:
        column_class = "overall-cell" if col == "Metric Average" else "metric-cell"
        html_table += f'<th class="{column_class}">{col}</th>'
    
    # Close the header and start the body
    html_table += """
            </tr>
          </thead>
          <tbody>
    """
    
    # Add the data rows
    for i, (idx, row) in enumerate(display_df.iterrows()):
        # Define background colors to ensure consistency
        row_bg = "#0a0a0a" if i % 2 == 0 else "#111111"
        
        # Start the row
        html_table += f'<tr class="table-row">'
        
        # Add Rank with medal styling and consistent background
        rank_style = f"background-color: {row_bg};" # Add row background to fixed columns
        rank_styles = get_rank_style(row["Rank"])
        for style_key, style_value in rank_styles.items():
            rank_style += f"{style_key}: {style_value};"
                
        html_table += f'<td class="fixed-column first-fixed-column" style="{rank_style}">{row["Rank"]}</td>'
        
        # Model name fixed column with consistent background
        html_table += f'<td class="fixed-column second-fixed-column" title="{row["Model Name"]}" style="background-color: {row_bg}; font-weight: 500; overflow: hidden; text-overflow: ellipsis; white-space: nowrap; text-align: center;">{row["Model Name"]}</td>'
        
        # Model type cell
        model_type = row["Model Type"]
        type_style = f"background-color: {row_bg};"
        model_type_styles = get_model_type_style(model_type)
        for style_key, style_value in model_type_styles.items():
            if style_value:
                type_style += f"{style_key}: {style_value};"
                
        html_table += f'<td class="table-cell model-type-cell" style="{type_style}">{model_type}</td>'
        
        # Add metric values with minimal styling
        for col in metric_columns:
            cell_class = "table-cell overall-cell" if col == "Metric Average" else "table-cell metric-cell"
            value_text = row[col]
            
            # Simple styling based on positive/negative values
            try:
                value = float(str(row[col]).replace(',', ''))
                if value > 0:
                    cell_class += " positive-value"
                elif value < 0:
                    cell_class += " negative-value"
            except:
                pass
            
            html_table += f'<td class="{cell_class}" style="background-color: {row_bg};">{value_text}</td>'
        
        html_table += "</tr>"
    
    # Close the table
    html_table += """
          </tbody>
        </table>
      </div>
    </div>
    """
    
    # Add metric definition below the table
    metric_definition = """
    <div class="metric-definition">
        <h4>Margin to Human</h4>
        <p> This metric measures what percentage of the top 1 human-to-baseline performance gap an agent can close on challenging Machine Learning Research Competition problems. For example, if the baseline is 100, top human performance is 200, and the agent scores 110, the agent has closed 10% of the gap between baseline and top human performance. Higher percentages indicate models that more effectively approach top human-level research capabilities.</p>
    </div>
    """
    
    # Display the custom HTML table and metric definition
    st.markdown(html_table + metric_definition, unsafe_allow_html=True)

def render_empty_state():
    """
    Render an empty state when no data is available
    """
    st.markdown("""
    <div class="warning-box">
        <strong>No data to display.</strong> Please select at least one task and one model type to view the data.
    </div>
    """, unsafe_allow_html=True)