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import gradio as gr
import requests
from bs4 import BeautifulSoup
from urllib.parse import urljoin
from gradio_client import Client
import json
import csv
import pandas
client = Client("mgokg/PerplexicaApi")
def parse_links_and_content(ort):
base_url = "https://vereine-in-deutschland.net"
all_links = []
# Konstruiere die vollständige URL
initial_url = f"{base_url}/vereine/Bayern/{ort}/"
try:
# Senden der Anfrage an die initiale URL
response = requests.get(initial_url)
response.raise_for_status() # Überprüfen, ob die Anfrage erfolgreich war
# Parse the HTML content using BeautifulSoup
soup = BeautifulSoup(response.content, 'html.parser')
# Ermittle die letzte Seite
link_element = soup.select_one('li.page-item:nth-child(8) > a:nth-child(1)')
if link_element and 'href' in link_element.attrs:
href = link_element['href']
# Extrahiere die letzten beiden Zeichen der URL
last_two_chars = href[-2:]
# Konvertiere die letzten beiden Zeichen in einen Integer
last_two_chars_int = int(last_two_chars)
else:
last_two_chars_int = 1 # Falls die letzte Seite nicht gefunden wird, nimm an, dass es nur eine Seite gibt
# Schleife durch alle Seiten und sammle Links
for page_number in range(1, last_two_chars_int + 1):
page_url = f"{base_url}/vereine/Bayern/{ort}/p/{page_number}"
response = requests.get(page_url)
response.raise_for_status()
soup = BeautifulSoup(response.content, 'html.parser')
target_div = soup.select_one('div.row-cols-1:nth-child(4)')
if target_div:
#links = [urljoin(base_url, a['href']) for a in target_div.find_all('a', href=True)]
texts = [a.text for a in target_div.find_all('a', href=True)]
print(texts)
all_links.extend(texts)
else:
print(f"Target div not found on page {page_number}")
except Exception as e:
return str(e), []
all_links = all_links[0::2]
return all_links
def scrape_links(links):
links=links
contact_details= []
for verein in links:
result = client.predict(
prompt=f"{verein}",
api_name="/parse_links"
)
#print(result)
contact_details.append(result)
return contact_details
# Speichere die JSON-Daten in eine CSV-Datei
def save_to_csv(data, filename):
keys = data[0].keys()
with open(filename, 'w', newline='', encoding='utf-8') as output_file:
dict_writer = csv.DictWriter(output_file, fieldnames=keys)
dict_writer.writeheader()
dict_writer.writerows(data)
# Erstelle die Gradio-Schnittstelle
with gr.Blocks() as demo:
gr.Markdown("# ")
with gr.Row():
ort_input = gr.Textbox(label="Ort", placeholder="Gib den Namen des Ortes ein")
links_output = gr.Textbox(label="")
#links_output = gr.Markdown(label="Ergebnisse")
json_output = gr.JSON(label="Ergebnisse")
def process_ort(ort):
links = parse_links_and_content(ort)
contact= scrape_links(links)
json_data = [json.loads(item) for item in contact]
save_to_csv(json_data, './contact_details.csv')
return f"[Download CSV](contact_details.csv)", json_data
return links, json_data
#return contact
#return pd.DataFrame(json_data)
#return json_data
# Button zum Starten der Parsung
button = gr.Button("senden")
# Verbinde den Button mit der Funktion
button.click(fn=process_ort, inputs=ort_input, outputs=[links_output,json_output])
# Starte die Gradio-Anwendung
demo.launch()
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