import pandas
import psycopg2  # pip3 install types-psycopg2
import matplotlib.pyplot as plt
from getpass import getpass
import json
import folium
from folium.plugins import BeautifyIcon
from typing import Union

def create_tables(connection: psycopg2.connection, filename: str):
    cur = connection.cursor()
    with open(filename) as f:
        cur.execute(f.read())
    connection.commit()
    cur.close()

def load_currencies(connection: psycopg2.connection, filename: str):
    cur = connection.cursor()
    with open(filename) as f:
        for iso, full_name in json.load(f).items():
            cur.execute("INSERT INTO currency VALUES (%s, %s);", (iso, full_name))
    connection.commit()
    cur.close()

def format_price(price: Union[float, str]) -> float:
    if isinstance(price, float):
        return price
    return float(price.replace(',', ''))

def format_award(award: str) -> int:
    if award == '3 MICHELIN Stars':
        return 3
    if award == '2 MICHELIN Stars':
        return 2
    if award == '1 MICHELIN Star':
        return 1
    return 0

def color_award(stars: int) -> str:
    if stars == 3:
        return 'orange'
    if stars == 2:
        return '#c0c0c0'
    if stars == 1:
        return '#c49c48'
    return '#132b5e'

def stars_radius(stars: int) -> int:
    if stars > 1:
        return 5
    if stars == 1:
        return 4
    return 3

def load_restaurants(connection: psycopg2.connection, filename: str):
    cur = connection.cursor()

    df = pandas.DataFrame(pandas.read_csv(filename))

    for row in df.itertuples():
        cur.execute("INSERT INTO restaurant (name, location, min_price, max_price, currency, latitude, longitude, phone_number, url, website_url, stars) VALUES (%s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s) RETURNING id;",
            (row.Name, row.Location, format_price(row.MinPrice), format_price(row.MaxPrice), row.Currency if not pandas.isnull(row.Currency) else None, row.Latitude, row.Longitude, row.PhoneNumber, row.Url, row.WebsiteUrl, format_award(row.Award))
        )
        restaurant_id = cur.fetchone()[0]
        for cuisine in row.Cuisine.split(', '):
            #cur.execute("INSERT INTO cuisine (name) VALUES (%s) ON CONFLICT DO NOTHING RETURNING id;", (cuisine,))
            cur.execute("INSERT INTO cuisine (name) VALUES (%s) ON CONFLICT (name) DO UPDATE SET name = EXCLUDED.name RETURNING id;", (cuisine,))
            cuisine_id = cur.fetchone()[0]
            cur.execute("INSERT INTO cuisine_restaurant VALUES (%s, %s);", (restaurant_id, cuisine_id))

    connection.commit()
    cur.close()

def cuisine(connection: psycopg2.connection):
    df = pandas.read_sql("""SELECT c.name, COUNT(*) restaurants
    FROM cuisine_restaurant cr
    INNER JOIN cuisine c ON c.id = cr.cuisine
    GROUP BY c.id
    ORDER BY 2 DESC
    LIMIT 20;""", con=connection)

    fig = df.plot.barh(x='name', y='restaurants', legend=False)
    fig.invert_yaxis()
    fig.set_title('Most common cuisine types in the Michelin guide')
    fig.set_xlabel('Cuisine type')
    fig.set_ylabel('Number of restaurants')
    fig.bar_label(fig.containers[0]) # Show values

def currencies(connection: psycopg2.connection):
    df = pandas.read_sql("""SELECT c.iso, c.full_name, COUNT(*) restaurants
    FROM restaurant r
    INNER JOIN currency c ON c.iso = r.currency
    GROUP BY c.iso
    ORDER BY 3 DESC
    LIMIT 10;""", con=connection)

    fig = df.plot.bar(x='iso', y='restaurants', legend=False, rot=0)
    fig.set_title('Most common accepted currencies in the Michelin guide')
    fig.set_xlabel('Currency')
    fig.set_ylabel('Number of restaurants')
    fig.bar_label(fig.containers[0]) # Show values

def prices(connection: psycopg2.connection):
    df = pandas.read_sql("""SELECT CASE WHEN min_price < 10 THEN '< 10'
            WHEN min_price >= 10 AND min_price < 15 THEN '[10;15[' 
            WHEN min_price >= 15 AND min_price < 20 THEN '[15;20[' 
            WHEN min_price >= 20 AND min_price < 30 THEN '[20;30[' 
            WHEN min_price >= 30 AND min_price < 50 THEN '[30;50[' 
            WHEN min_price >= 50 AND min_price < 100 THEN '[50;100[' 
            WHEN min_price >= 100 AND min_price < 200 THEN '[100;200[' 
            WHEN min_price >= 200 AND min_price < 500 THEN '[200;500[' 
            WHEN min_price >= 500 AND min_price < 1000 THEN '[500;1000[' 
            WHEN min_price >= 1000 THEN '>= 1000' 
        END min_price_range,
    COUNT(*) nb
FROM restaurant
WHERE currency = 'EUR'
GROUP BY min_price_range;""", con=connection)

    fig = df.plot.pie(y='nb', labels=df['min_price_range'], legend=False)

def map(connection: psycopg2.connection):
    map_osm = folium.Map(zoom_start=4)
    groups = [folium.FeatureGroup('Bib Gourmand' if stars == 0 else str(stars) + ' stars') for stars in range(4)]
    df = pandas.read_sql("""SELECT latitude, longitude, name, min_price, max_price, currency, stars FROM restaurant;""", con=connection)
    #df['color'] = df.apply(color_award, axis=1)
    for _, latitude, longitude, name, min_price, max_price, currency, stars in df[['latitude', 'longitude', 'name', 'min_price', 'max_price', 'currency', 'stars']].itertuples():
        is_star = stars != 0
        popup = (
            "<strong>{name}</strong><br>"
            "From {min_price} to {max_price} {currency}<br>"
            "{award}<br>"
            "______________________"
        ).format(name=name, min_price=min_price, max_price=max_price, currency=currency, award=str(stars) + ' stars' if is_star else 'Bib Gourmand')
        color = color_award(stars)
        if stars == 3:
            icon = BeautifyIcon(icon='star', inner_icon_style=('color:' + color), border_color='transparent', background_color='transparent')
            folium.Marker(location=[latitude, longitude], popup=popup, radius=stars_radius(stars), fill=True, fill_opacity=1, icon=icon).add_to(groups[stars])
        else:
            folium.CircleMarker(location=[latitude, longitude], popup=popup, color=color, fill_color=color, radius=stars_radius(stars), fill=True, fill_opacity=1).add_to(groups[stars])
    for group in groups:
        map_osm.add_child(group)
    map_osm.add_child(folium.map.LayerControl())
    map_osm.save('/tmp/test_map.html')


if __name__ == '__main__':
    db_host = input('Nom d\'hôte : ')
    if not db_host:
        db_host = 'berlin'
    db_name = input('Nom de la base de données : ')
    if not db_name:
        db_name = 'dbclfreville2'
    db_user = input('Utilisateur : ')
    if not db_user:
        db_user = 'clfreville2'
    db_password = getpass('Mot de passe : ')

    connection = psycopg2.connect(host=db_host, port=5432, database=db_name, user=db_user, password=db_password)

    #create_tables(connection, 'table.sql')
    #load_currencies(connection, 'currencies.json')
    #load_restaurants(connection, 'michelin_my_maps.csv')
    cuisine(connection)
    currencies(connection)
    prices(connection)
    #map(connection)

    connection.close()

    plt.show()