import streamlit as st
import requests
import pandas as pd

def fetch_data(keyword, location, lang):
    url = f"https://google-keyword-insight1.p.rapidapi.com/keysuggest?keyword={keyword}&location={location}&lang={lang}"
    headers = {
        'X-RapidAPI-Key': '63e53aa879mshac0f7ff04cc8922p1a89dbjsn96a2ea051ea7',
        'X-RapidAPI-Host': 'google-keyword-insight1.p.rapidapi.com'
    }
    response = requests.get(url, headers=headers)
    if response.status_code == 200:
        return response.json()
    else:
        return []

def round_to_nearest_five_cents(value):
    if value == 0:
        return '0'
    rounded_value = round(value * 20) / 20
    return '0.10' if rounded_value < 0.1 else f'{rounded_value:.2f}'

def round_trend_to_percentage(value):
    return f'{round(value)} %'

st.title('Búsqueda de Palabras Clave')

keyword = st.text_input('Palabra clave:', placeholder='Ingrese la búsqueda', key='keyword')
location = st.text_input('Ubicación:', value='ES', key='location')
lang = st.text_input('Idioma:', value='es', key='lang')

# Initialize session state variables
if 'show_all' not in st.session_state:
    st.session_state.show_all = False

if 'results' not in st.session_state:
    st.session_state.results = None

if st.button('Buscar'):
    results = fetch_data(keyword, location, lang)
    if results:
        df = pd.DataFrame(results)
        df['Nivel de Competencia'] = df['competition_level'].map({
            'LOW': 'Baja',
            'MEDIUM': 'Media',
            'HIGH': 'Alta'
        }).fillna('-')
        df['Oferta Baja'] = df['low_bid'].apply(round_to_nearest_five_cents)
        df['Oferta Alta'] = df['high_bid'].apply(round_to_nearest_five_cents)
        df['Tendencia'] = df['trend'].apply(round_trend_to_percentage)
        df['Ads'] = df['low_bid'].apply(lambda x: 'Sí' if x > 0 else 'No')
        df = df[['text', 'volume', 'Nivel de Competencia', 'competition_index', 'Oferta Baja', 'Oferta Alta', 'Tendencia', 'Ads']]
        df.columns = ['Texto', 'Volumen', 'Nivel de Competencia', 'Índice de Competencia', 'Oferta Baja', 'Oferta Alta', 'Tendencia', 'Ads']
        df.sort_values(by='Volumen', ascending=False, inplace=True)
        st.session_state.results = df
        st.session_state.show_all = False  # Reset the view to default when new search is performed

# Display results if available
if st.session_state.results is not None:
    df = st.session_state.results
    rows_to_display = 20 if not st.session_state.show_all else len(df)
    st.table(df.head(rows_to_display))
    
    col1, col2 = st.columns([1, 1])
    
    with col1:
        if len(df) > 20:
            if st.button('Ver más'):
                st.session_state.show_all = not st.session_state.show_all
                # Reset button text after showing all
                if st.session_state.show_all:
                    st.button('Ver menos')

    with col2:
        csv = df.to_csv(index=False)
        st.download_button(
            label="Descargar resultados como CSV",
            data=csv,
            file_name='resultados.csv',
            mime='text/csv',
        )

# Run the app using the command: streamlit run app.py