csv download is not including all the results in a django application

Hi,

im trying to build a web app with python and django, in this application a user can enter a list of websites, the results will show the website status, the website title, the website summary, the email, the phone number, facebook and instagram links if present. At the end the user can download the results as csv, btw the csv is showing only 1 result, and even incomplete (the website, the phone, the email, fb and instagram are missing). What am i doing wrong? attached the base.html and result.html files and here is my views.py file
any idea how i can solve this?

thanks!

# website_checker/checker/views.py

from django.shortcuts import render
from django.http import HttpResponseRedirect
from django.shortcuts import render, HttpResponse
from django.urls import reverse
import requests
from bs4 import BeautifulSoup
from .utils import get_business_summary, extract_emails, extract_phones, extract_social_media_links
import spacy
import re
import csv
import io

# Function to get a business summary from the text
def get_business_summary(text):
    nlp = spacy.load('en_core_web_sm')
    doc = nlp(text)
    sentences = [sent.text.strip() for sent in doc.sents]
    business_summary = ''
    for sent in sentences:
        # You can add more conditions to extract business-specific information from the text
        if 'business' in sent.lower() or 'company' in sent.lower():
            business_summary = sent
            break
    return business_summary



# Function to extract emails from the text
def extract_emails(text):
    # Use regex pattern for email extraction
    email_pattern = r'[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}'
    emails = set(re.findall(email_pattern, text))  # Use set to eliminate duplicates
    return list(emails)

# Function to extract phone numbers from the text
def extract_phones(text):
    phone_pattern = re.compile(r'(\+?\d{1,3}[-.\s]?)?(\()?\d{3}(\))?[-.\s]?\d{3}[-.\s]?\d{4}')

    phones = set()
    for match in phone_pattern.finditer(text):
        phone = match.group(0).replace('(', '').replace(')', '').replace('-', '').replace(' ', '').replace('.', '')
        phones.add(phone)

    return list(phones) if phones else ['No phones found']

# Function to extract Facebook and Instagram links from the website
def extract_social_media_links(soup):
    facebook_links = []
    instagram_links = []

    # Find all anchor tags with href attributes
    anchor_tags = soup.find_all('a', href=True)

    for tag in anchor_tags:
        href = tag['href']
        if 'facebook.com' in href:
            facebook_links.append(href)
        elif 'instagram.com' in href:
            instagram_links.append(href)

    # Return the links as lists
    return facebook_links, instagram_links

# Actual implementation of generate_csv function to convert websites_data into CSV format
def generate_csv(websites_data):
    # Prepare CSV data
    csv_data = io.StringIO()  # Create a StringIO object to hold CSV data
    fieldnames = ['Website', 'Status', 'Title', 'Description', 'Business Summary', 'Emails', 'Phones', 'Facebook', 'Instagram']

    # Use DictWriter to write the CSV data
    writer = csv.DictWriter(csv_data, fieldnames=fieldnames)
    writer.writeheader()  # Write the header row

    for data in websites_data:
        # Create a new dictionary with the required fieldnames to avoid extra fields in the CSV
        row_data = {
            'Website': data['url'],
            'Status': data['is_down'],
            'Title': data['title'],
            'Description': data['description'],
            'Business Summary': data['business_summary'],
            'Emails': ', '.join(data['emails']),
            'Phones': ', '.join(data['phones']),
            'Facebook': ', '.join(data['facebook_links']),
            'Instagram': ', '.join(data['instagram_links']),
        }

        # Write the data row
        writer.writerow(row_data)

    return csv_data.getvalue()



def download_csv(request):
    if request.method == 'POST':
        websites_data = request.session.get('websites_data')
        if websites_data:
            # Prepare CSV data
            csv_data = generate_csv(websites_data)

            # Create and return the CSV response
            response = HttpResponse(csv_data, content_type='text/csv')
            response['Content-Disposition'] = 'attachment; filename="websites_data.csv"'
            return response
        else:
            return HttpResponse("No data to download.")
    else:
        return HttpResponse("Invalid request method for CSV download.")




# Combine the check_websites logic with the home view function
def home(request):
    if request.method == 'POST':
        website_urls = request.POST.get('website_urls', '').strip()
        urls_list = website_urls.splitlines()
        # Remove empty strings from the list
        urls_list = list(filter(None, urls_list))

        print("Request Method:", request.method)  # Debugging line
        print("Website URLs:", urls_list)  # Debugging line

        websites_data = []
        for url in urls_list:
            try:
                response = requests.get(url)
                is_down = response.status_code != 200
                soup = BeautifulSoup(response.content, 'html.parser')

                if soup:
                    # Check if the title tag exists
                    title = soup.title
                    if title:
                        title = title.string.strip() if title.string else 'No title available'
                    else:
                        title = 'No title available'

                    # Check if the description meta tag exists
                    description_tag = soup.find('meta', attrs={'name': 'description'})
                    description = description_tag['content'].strip() if description_tag else 'No description available'

                    # Get the website content for NLP processing
                    website_text = soup.get_text()

                    # Get a brief business summary
                    business_summary = get_business_summary(website_text)

                    # Extract emails using regex pattern
                    emails = extract_emails(website_text)

                    # Extract phone numbers using regex pattern
                    phones = extract_phones(website_text)

                    # Extract Facebook and Instagram links from the website
                    facebook_links, instagram_links = extract_social_media_links(soup)
                    # Remove duplicates from Facebook and Instagram links
                    facebook_links = list(set(facebook_links))
                    instagram_links = list(set(instagram_links))
                else:
                    is_down = True
                    title = 'No title available'
                    description = 'No description available'
                    business_summary = 'Unable to retrieve website content.'
                    emails = []
                    phones = []
                    facebook_links = []
                    instagram_links = []

            except requests.exceptions.RequestException:
                is_down = True
                title = 'No title available'
                description = 'No description available'
                business_summary = 'Unable to retrieve website content.'
                emails = []
                phones = []
                facebook_links = []
                instagram_links = []
                pass

            # Check the status and set 'UP' or 'Down' accordingly
            status = 'UP' if not is_down else 'Down'
            websites_data.append({
                'url': url,
                'is_down': is_down,
                'title': title,
                'description': description,
                'business_summary': business_summary,
                'emails': emails,
                'phones': phones,
                'facebook_links': facebook_links,
                'instagram_links': instagram_links,
                'status': status,
            })

        # Check if the request is for CSV download
        if request.POST.get('download_csv'):
            # Save websites_data in the session
            request.session['websites_data'] = websites_data
            # Generate the URL for the download view using reverse
            download_url = reverse('download_csv')
            # Redirect to the download view
            return HttpResponseRedirect(download_url)

        # For normal POST request, render the result table
        print("Websites Data:", websites_data)  # Debugging line
        return render(request, 'checker/home.html', {'websites_data': websites_data, 'status': status})

    # For GET request, display the form to enter website URLs
    return render(request, 'checker/home.html')