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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
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