import pandas as pd
import requests
import gradio as gr
import time
import tempfile

def check_urls(url_list):
    urls = url_list.strip().split('\n')
    status_codes = []

    for url in urls:
        try:
            final_status_code = None
            current_url = url
            while True:
                response = requests.get(current_url, allow_redirects=False)
                status_code = response.status_code
                if status_code == 200 or status_code == 404:
                    final_status_code = status_code
                    break
                elif 300 <= status_code < 400:
                    current_url = response.headers.get('Location')
                    if not current_url:
                        final_status_code = status_code
                        break
                else:
                    final_status_code = status_code
                    break
                time.sleep(1)  # Wait for 1 second between requests
            status_codes.append(final_status_code)
        except requests.RequestException:
            status_codes.append(float('nan'))  # Handle connection errors

    df = pd.DataFrame({"URL": urls, "Status Code": status_codes})
    return df

def apply_style(code):
    if pd.isna(code):
        return "background-color: yellow"
    elif code == 200:
        return "background-color: green"
    elif code == 404:
        return "background-color: red"
    else:
        return "background-color: orange"

def style_df(df):
    return df.style.applymap(apply_style, subset=["Status Code"])

def to_csv(df):
    with tempfile.NamedTemporaryFile(delete=False, suffix=".csv") as tmp:
        df.to_csv(tmp.name, index=False)
        return tmp.name

with gr.Blocks() as demo:
    url_input = gr.Textbox(lines=10, placeholder="Enter URLs separated by new lines...")
    output_df = gr.DataFrame()
    download_button = gr.File(label="Download CSV")
    
    def process_and_return(url_list):
        df = check_urls(url_list)
        styled_df = style_df(df)
        csv_file = to_csv(df)
        return styled_df, csv_file

    url_input.change(process_and_return, inputs=url_input, outputs=[output_df, download_button])

    demo.launch()