import streamlit as st
import pandas as pd
import re
from datetime import datetime
from typing import List

# Page configuration
st.set_page_config(
    page_title="Scholarship Search (Context Based Search)",
    page_icon="🎓",
    layout="wide"
)

# Load and prepare data
@st.cache_data
def load_scholarships():
    try:
        df = pd.read_csv("scholarships_data.csv", quotechar='"', quoting=1)
        df = df.map(lambda x: x.strip() if isinstance(x, str) else x)
        df.rename(columns=lambda x: x.strip(), inplace=True)
        return df
    except Exception as e:
        st.error(f"Error loading data: {str(e)}")
        st.stop()

# Custom CSS for styling
def load_css():
    st.markdown("""
    <style>
    /* Base styles */
    body {
        font-family: 'Roboto', sans-serif;
        color: #333;
        background-color: #f9f9f9;
    }
    
    /* Header styles */
    .hero-section {
        background: linear-gradient(135deg, #3a7bd5, #00d2ff);
        color: white;
        padding: 1rem;
        border-radius: 0.5rem;
        text-align: center;
        margin-bottom: 1rem;
    }
    
    .hero-title {
        font-size: 2rem;
        font-weight: 600;
        margin-bottom: 0.5rem;
    }
    
    /* Search box */
    .search-container {
        background-color: white;
        border-radius: 0.5rem;
        padding: 1rem;
        margin-bottom: 1rem;
        text-align: center;
    }
    
    /* Results styles */
    .results-container {
        background-color: white;
        border-radius: 0.5rem;
        padding: 1rem;
    }
    
    .results-header {
        color: #3a7bd5;
        font-size: 1.2rem;
        margin-bottom: 1rem;
        font-weight: 500;
    }
    
    /* Scholarship item styles */
    .scholarship-item {
        padding: 1rem;
        margin-bottom: 1rem;
        border-radius: 0.5rem;
        background-color: #ffffff;
        border: 1px solid #e0e0e0;
    }
    
    .scholarship-name {
        font-size: 1.1rem;
        font-weight: 600;
        color: #2c3e50;
        margin-bottom: 0.5rem;
    }
    
    .scholarship-details {
        font-size: 0.9rem;
        color: #666;
        margin-bottom: 0.5rem;
    }
    
    .deadline-tag {
        background-color: #e8f4ff;
        color: #3a7bd5;
        padding: 0.2rem 0.5rem;
        border-radius: 0.25rem;
        font-size: 0.8rem;
        font-weight: 500;
        display: inline-block;
        margin-bottom: 0.5rem;
        border: 1px solid #3a7bd5;
    }
    
    .apply-button {
        background-color: #00b894;
        color: white;
        padding: 0.3rem 0.7rem;
        border-radius: 0.25rem;
        font-size: 0.85rem;
        font-weight: 500;
        text-decoration: none;
        display: inline-block;
    }
    
    .apply-button:hover {
        background-color: #00a383;
        color: white;
    }
    
    /* Search input */
    .stTextInput>div>div>input {
        font-size: 1rem;
        padding: 0.6rem 1rem;
        border-radius: 1.5rem;
        border: 1px solid #ddd;
    }
    
    /* No results message */
    .no-results {
        text-align: center;
        padding: 2rem;
        color: #7f8c8d;
    }
    </style>
    """, unsafe_allow_html=True)

# Format the deadline status
def format_deadline(deadline_str):
    try:
        if not deadline_str or pd.isna(deadline_str) or deadline_str == "N/A":
            return "Open - No specific deadline", "#00b894"
            
        # Handle different date formats
        try:
            deadline = datetime.strptime(deadline_str, "%d-%m-%Y")
        except ValueError:
            try:
                deadline = datetime.strptime(deadline_str, "%Y-%m-%d")
            except ValueError:
                return deadline_str, "#00b894"
        
        today = datetime.now()
        days_left = (deadline - today).days
        
        if days_left < 0:
            return "Expired", "#e74c3c"
        elif days_left <= 7:
            return f"{days_left} days left!", "#ff7675"
        elif days_left <= 30:
            return f"{days_left} days left", "#00b894"
        else:
            return f"{days_left} days left", "#3498db"
    except:
        return deadline_str, "#00b894"

# Highlight search terms in text
def highlight_text(text, search_terms):
    if not search_terms or not text:
        return text
    
    # Convert search terms to a list if it's a string
    if isinstance(search_terms, str):
        search_terms = [search_terms]
    
    # Highlight each search term
    for term in search_terms:
        if term.strip():
            pattern = re.compile(re.escape(term.strip()), re.IGNORECASE)
            text = pattern.sub(f'<span class="highlight">{term}</span>', text)
    
    return text

# Display scholarship results
def display_scholarships(df: pd.DataFrame, search_terms: List[str] = None) -> None:
    if df.empty:
        st.markdown('<div class="no-results">No scholarships found. Try a different search term.</div>', unsafe_allow_html=True)
        return

    st.markdown(f"<div class='results-header'>Found {len(df)} scholarships</div>", unsafe_allow_html=True)

    for _, row in df.iterrows():
        name = row['Scholarship Name']
        eligibility = row['Eligibility']
        deadline = row['Deadline'] if 'Deadline' in row else ""
        link = row['Link']

        # Format deadline text and color
        deadline_text, deadline_color = format_deadline(deadline)

        # Highlight search terms if provided
        if search_terms:
            name = highlight_text(name, search_terms)
            eligibility = highlight_text(eligibility, search_terms)

        # Generate the scholarship card
        scholarship_html = f"""
        <div class="scholarship-item">
            <div class="scholarship-name">{name}</div>
            <div class="deadline-tag">⏰ {deadline_text}</div>
            <div class="scholarship-details">{eligibility}</div>
            <a href="{link}" target="_blank" class="apply-button">Apply Now</a>
        </div>
        """
        
        st.markdown(scholarship_html, unsafe_allow_html=True)

# App header
def display_header():
    st.markdown("""
    <div class="hero-section">
        <h1 class="hero-title">🎓 Scholarship Search</h1>
    </div>
    """, unsafe_allow_html=True)

# Simplified search function
def search_scholarships(df: pd.DataFrame, query: str) -> pd.DataFrame:
    if not query:
        return df.head(10)

    search_terms = query.split()
    filtered_df = df.copy()
    
    for term in search_terms:
        if term.strip():
            filtered_df = filtered_df[
                filtered_df['Scholarship Name'].str.contains(term, case=False, na=False) |
                filtered_df['Eligibility'].str.contains(term, case=False, na=False)
            ]
    
    return filtered_df.head(15)

# Main function
def main():
    # Load custom CSS
    load_css()
    
    # Load scholarship data
    df = load_scholarships()

    # Display header
    display_header()

    # Search container
    st.markdown('<div class="search-container">', unsafe_allow_html=True)
    st.markdown('<div class="search-input-container">', unsafe_allow_html=True)
    
    # Create a layout with a text input and a button side by side
    col1, col2 = st.columns([5, 1])
    with col1:
        search_term = st.text_input("", placeholder="🔍 Search for scholarships (e.g., 'engineering scholarships')")
    with col2:
        st.markdown("<div style='margin-top: 27px;'>", unsafe_allow_html=True)
        search_button = st.button("Search")
        st.markdown("</div>", unsafe_allow_html=True)
    
    # Example queries
    example_queries = [
        "undergraduate scholarships",
        "engineering scholarships",
        "international scholarships",
        "research fellowships"
    ]
    
    # Display example queries
    st.markdown("<div style='text-align: center; font-size: 0.9em; margin-top: 10px;'>Try: " + 
                " | ".join([f"<a href='#' onclick='document.querySelector(\".stTextInput input\").value=\"{query}\"; return false;'>{query}</a>" for query in example_queries]) +
                "</div>", unsafe_allow_html=True)
    
    st.markdown('</div>', unsafe_allow_html=True)
    st.markdown('</div>', unsafe_allow_html=True)

    # Results container
    st.markdown('<div class="results-container">', unsafe_allow_html=True)

    # Process search
    if search_button or search_term:
        with st.spinner("Searching for scholarships..."):
            results_df = search_scholarships(df, search_term)
            display_scholarships(results_df, search_term.split())
    else:
        # Display initial scholarships
        display_scholarships(df.head(10))

    st.markdown('</div>', unsafe_allow_html=True)

if __name__ == "__main__":
    main()