main.py

import streamlit as st
from app.data_loader import (
    fetch_data,
    fetch_sessions,
    fetch_sector_data,
    fetch_laps,
    fetch_stints,
    fetch_pit_stop,
    fetch_drivers
)
from app.data_processor import (
    process_sector_times,
    process_lap_data,
    process_stints,
    process_pit_stops,
    build_driver_color_map
)
from app.visualizer import (
    plot_sector_times,
    plot_lap_times,
    plot_tire_strategy,
    plot_pit_stop
)

st.set_page_config(page_title="F1 Strategy Dashboard", layout="wide")

st.title("🏎️ Formula 1 Strategy Dashboard")
st.markdown("_Powered by OpenF1.org • Built by Attila Bordan • Improvements by Jilliana Alvarez_")

col1, col2 = st.columns(2)

with col1:
    # Step 1: Select Year and Country dynamically
    available_years = [2023, 2024, 2025]
    selected_year = st.selectbox("Select Year", available_years, index=len(available_years) - 1)

    # Fetch all meetings for selected year
    all_meetings = fetch_data("meetings", {"year": selected_year})

    if all_meetings.empty:
        st.error("No meetings found for this year.")
        st.stop()

    available_countries = sorted(all_meetings["country_name"].dropna().unique())
    selected_country = st.selectbox("Select Country", available_countries)

    # Filter meetings for selected year and country
    filtered_meetings = all_meetings[all_meetings["country_name"] == selected_country].copy()
    filtered_meetings["label"] = filtered_meetings["meeting_name"] + " - " + filtered_meetings["location"]
    filtered_meetings = filtered_meetings.sort_values(by="meeting_key", ascending=False)

with col2:
    selected_meeting = st.selectbox("Select Grand Prix", filtered_meetings["label"], disabled=True)
    selected_meeting_key = filtered_meetings.loc[
        filtered_meetings["label"] == selected_meeting, "meeting_key"
    ].values[0]
    sessions = fetch_sessions(selected_meeting_key)
    selected_session = st.selectbox("Select Session", sessions["label"])
    sessions["session_type"] = sessions["label"].str.extract(r"^(.*?)\s\(")
    selected_session_type = sessions.loc[sessions["label"] == selected_session, "session_type"].values[0]
    selected_session_key = sessions.loc[sessions["label"] == selected_session, "session_key"].values[0]

st.markdown(f"### 🏁 Session Overview: `{selected_session}`")
with st.expander("📋 Session Details", expanded=False):
    st.write(f"**Meeting Key:** {selected_meeting_key}")
    st.write(f"**Session Key:** {selected_session_key}")

# Fetch and preprocess driver info
driver_df = fetch_drivers(selected_session_key)
driver_df["driver_number"] = driver_df["driver_number"].astype(str)
driver_color_map = build_driver_color_map(driver_df)
driver_info = driver_df[["driver_number", "name_acronym"]]

# Sector times
sector_df = fetch_sector_data(selected_session_key)
sector_df["driver_number"] = sector_df["driver_number"].astype(str)
    # Let user select driver and lap.
driver_options = {
    f"{row['driver_number']} - {row['name_acronym']}": row['driver_number']
    for _, row in driver_df.iterrows()
}
selected_driver_label = st.selectbox("Select Driver", list(driver_options.keys()))
selected_driver = driver_options[selected_driver_label]

available_laps = sector_df[sector_df["driver_number"] == selected_driver]["lap_number"].unique()
if len(available_laps) == 0:
    st.warning("No laps available for the selected driver.")
    st.stop()
selected_lap = st.selectbox("Select Lap", available_laps)

driver_name_row = driver_df[driver_df["driver_number"] == selected_driver ]
if not driver_name_row.empty:
    driver_name = driver_name_row["name_acronym"].values[0]
else:
    driver_name = selected_driver

filtered = sector_df[
    (sector_df["driver_number"] == selected_driver)&
    (sector_df["lap_number"] == selected_lap)
]


fig = plot_sector_times(sector_df, selected_driver, selected_lap, driver_name)
if fig:
        st.plotly_chart(fig)
else:
        st.warning("No sector data for selected driver/lap.")

# Lap Times
with st.expander(f"📈 Lap Time Chart for {selected_session_type} at {selected_country} {selected_year}",
                 expanded=True):
    lap_df = fetch_laps(selected_session_key)
    processed_df = process_lap_data(lap_df)

    # Merge name_acronym into the lap data
    processed_df["driver_number"] = processed_df["driver_number"].astype(str)
    processed_df = processed_df.merge(driver_info, on="driver_number", how="left")

    if processed_df.empty:
        st.warning("No lap time data found.")
    else:
        fig = plot_lap_times(processed_df, driver_color_map)
        st.plotly_chart(fig, use_container_width=True)

# Tire Strategy
with st.expander(f"🛞 Tire strategy for {selected_session_type} at {selected_country} {selected_year}", expanded=True):
    stints = fetch_stints(selected_session_key)
    stints_df = process_stints(stints)
    stints_df["driver_number"] = stints_df["driver_number"].astype(str)
    stints_df = stints_df.merge(driver_info, on="driver_number", how="left")

    if stints_df.empty:
        st.warning("No tire strategy data found.")
    else:
        fig = plot_tire_strategy(stints_df, driver_color_map)
        st.plotly_chart(fig, use_container_width=True)

# Pit Stops
with st.expander(f"⏱  Pit stop durations for {selected_session_type} at {selected_country} {selected_year}",
                 expanded=True):
    pit_stop = fetch_pit_stop(selected_session_key)
    pit_stop_df = process_pit_stops(pit_stop)
    pit_stop_df["driver_number"] = pit_stop_df["driver_number"].astype(str)
    pit_stop_df = pit_stop_df.merge(driver_info, on="driver_number", how="left")

    if pit_stop_df.empty:
        st.warning("No pit stop data found.")
    else:
        fig = plot_pit_stop(pit_stop_df, driver_color_map)
        st.plotly_chart(fig, use_container_width=True)

if processed_df.empty:
    st.info("Lap data is not available for this session.")