import streamlit as st
from streamlit_calendar import calendar
import pandas as pd
import database
import datetime

# --- Configuration ---
st.set_page_config(page_title="Work Tracker", layout="wide")

# --- Database Init ---
if "db_initialized" not in st.session_state:
    database.init_db()
    st.session_state["db_initialized"] = True

# --- UI Layout ---
st.title("📅 Work Hours Tracker")

col1, col2 = st.columns([2, 1])

# --- Calendar Section ---
with col1:
    st.subheader("Select Work Days")
    
    # Fetch existing data to populate calendar
    df = database.get_all_days()
    
    # Format events for streamlit-calendar
    events = []
    if not df.empty:
        for date_str in df['date']:
            events.append({
                "title": "Worked",
                "start": date_str,
                "allDay": True,
                "color": "#4CAF50" # Green for worked days
            })

    # Calendar options
    calendar_options = {
        "headerToolbar": {
            "left": "today prev,next",
            "center": "title",
            "right": "dayGridMonth,dayGridWeek"
        },
        "initialView": "dayGridMonth",
        "selectable": True,
    }

    # Render Calendar
    cal = calendar(events=events, options=calendar_options, key="calendar")

    # Handle Click Events
    if cal.get("callback") == "dateClick":
        clicked_date = cal["dateClick"]["dateStr"]
        database.toggle_day(clicked_date)
        st.rerun() # Refresh to update calendar and stats

# --- Statistics Section ---
with col2:
    st.subheader("Statistics")
    
    if not df.empty:
        # Convert to datetime
        df['date'] = pd.to_datetime(df['date'])
        df = df.sort_values('date')
        
        # Calculate weekly stats
        # Resample to weekly frequency (W-MON)
        weekly_counts = df.resample('W-MON', on='date').size()
        
        if not weekly_counts.empty:
            avg_days_per_week = weekly_counts.mean()
            st.metric("Avg Days / Week (Total)", f"{avg_days_per_week:.2f}")

            # Plotting
            st.line_chart(weekly_counts, use_container_width=True)
            
            # Monthly breakdown
            monthly_counts = df.resample('M', on='date').size()
            st.write("### Monthly Breakdown")
            st.dataframe(monthly_counts.rename("Days Worked"))
            
    else:
        st.info("No work days logged yet. Click dates on the calendar.")

# --- Debugging (Optional) ---
# with st.expander("Raw Data"):
#     st.dataframe(df)