def fetch_gsc_data(property_uri, start_date, end_date, creds):
    service = build('searchconsole', 'v1', credentials=creds)
    body = {
        'startDate': start_date,
        'endDate': end_date,
        'dimensions': ['date'],
        'rowLimit': 10000
    }
    response = service.searchanalytics().query(siteUrl=property_uri, body=body).execute()
    rows = response.get('rows', [])
    data = []
    for r in rows:
        d = r['keys'][0]
        data.append({
            'date': d,
            'clicks': r.get('clicks', 0),
            'impressions': r.get('impressions', 0),
            'position': r.get('position', 0)
        })
    df = pd.DataFrame(data)
    df['date'] = pd.to_datetime(df['date'])
    return df

def load_all_data(
    start_date=START_DATE, 
    end_date=END_DATE, 
    sites=SITES, 
    creds_file="Название вашего JSON-файла"
):
    creds = service_account.Credentials.from_service_account_file(
        creds_file,
        scopes=["https://www.googleapis.com/auth/webmasters.readonly"]
    )
    all_df = []
    for s in sites:
        df_s = fetch_gsc_data(s, start_date, end_date, creds)
        df_s['domain'] = s
        all_df.append(df_s)
    big_df = pd.concat(all_df, ignore_index=True)
    return big_df

app = dash.Dash(__name__)
GLOBAL_DF = None  # кешируем загруженные данные

app.layout = html.Div([
    html.H1("GSC Дашборд - Клики, Показы, Позиция"),

    html.Div([
        html.Label("Выберите сайт(-ы):"),
        dcc.Checklist(
            id='site-selector',
            options=[{'label': site, 'value': site} for site in SITES],
            value=SITES,  
            inline=True
        ),
    ]),

    html.Div([
        html.Label("Метрики:"),
        dcc.Checklist(
            id='metric-selector',
            options=[
                {'label': 'Клики', 'value': 'clicks'},
                {'label': 'Показы', 'value': 'impressions'},
                {'label': 'Позиция', 'value': 'position'},
            ],
            # Если тут пусто, у нас нет рядов данных => ось X может стать [0..1]
            value=[],  
            inline=True
        ),
    ]),

    html.Div([
        html.Label("Показать Google Updates:"),
        dcc.Checklist(
            id='updates-toggle',
            options=[{'label': u['name'], 'value': u['name']} for u in GOOGLE_UPDATES],
            value=[],  
            inline=True
        ),
    ]),

    html.Div([
        html.Label("Показать события:"),
        dcc.Checklist(
            id='events-toggle',
            options=[{'label': e['name'], 'value': e['name']} for e in EVENTS],
            value=[],  
            inline=True
        ),
    ]),

    dcc.Graph(id='gsc-graph')
])

@app.callback(
    Output('gsc-graph', 'figure'),
    [
        Input('site-selector', 'value'),
        Input('metric-selector', 'value'),
        Input('updates-toggle', 'value'),
        Input('events-toggle', 'value'),
        Input('gsc-graph', 'relayoutData')
    ]
)
def update_graph(selected_sites, selected_metrics, selected_updates, selected_events, relayoutData):
    global GLOBAL_DF
    if GLOBAL_DF is None:
        GLOBAL_DF = load_all_data()

    print("=== CALLBACK ===")
    print("Selected events: ", selected_events)  # Проверяем в консоли, что выбрано

    fig = go.Figure()

    # Фильтруем общий DF по выбранным доменам
    filtered_df = GLOBAL_DF[GLOBAL_DF['domain'].isin(selected_sites)]

    # Если выбраны метрики, строим линии
    if selected_metrics:
        for site in selected_sites:
            df_site = filtered_df[filtered_df['domain'] == site].sort_values('date')
            for metric in selected_metrics:
                fig.add_trace(go.Scatter(
                    x=df_site['date'],
                    y=df_site[metric],
                    mode='lines',
                    name=f"{site} - {metric}"
                ))