Wix Blogberichten Exporteren naar Markdown met OpenAI
Waarom Blogberichten Exporteren vanuit Wix?
Samenvatting: Deze gids laat zien hoe u Wix blogberichten exporteert naar Markdown met drie Python-scripts: een setup-runner, een op Selenium gebaseerde scraper en een OpenAI-aangedreven HTML-naar-Markdown converter. Het resultaat zijn schone, draagbare Markdown-bestanden klaar voor Hugo, Jekyll of elke andere statische sitegenerator.
Wix biedt geen native blogexport naar Markdown. Als u migreert naar een statische sitegenerator zoals Hugo of Jekyll, moet u de gerenderde pagina’s scrapen, de inhoud extraheren en converteren. Deze tutorial automatiseert het hele proces met Python, Selenium, BeautifulSoup en OpenAI’s GPT API.
De pipeline gebruikt drie scripts:
fetch_blog_posts.sh— stelt de omgeving in en voert de pipeline uitparse_blog_sitemap.py— rendert pagina’s met Selenium, extraheert inhoud, downloadt afbeeldingengenerate_md.py— converteert HTML naar Markdown via OpenAI
Stap 1: De Omgeving Opzetten
Maak fetch_blog_posts.sh aan om Python-controles, virtuele omgeving setup, afhankelijkheden installatie en pipeline-uitvoering af te handelen.
#!/bin/bash
# setup_blog_scraper.sh
# Usage: bash setup_blog_scraper.sh
echo "🔍 Checking Python installation..."
if ! command -v python3 &> /dev/null; then
echo "❌ Python 3 is not installed. Please install Python 3 and try again."
exit 1
fi
echo "✅ Python 3 found: $(python3 --version)"
VENV_DIR=".venv"
if [ ! -d "$VENV_DIR" ]; then
echo "📁 Creating virtual environment in $VENV_DIR..."
python3 -m venv "$VENV_DIR"
else
echo "✅ Virtual environment already exists."
fi
echo "⚙️ Activating virtual environment..."
source "$VENV_DIR/bin/activate"
echo "📦 Installing dependencies..."
pip install --upgrade pip
pip install beautifulsoup4 lxml selenium webdriver-manager
echo "🚀 Running blog sitemap parser..."
python3 parse_blog_sitemap.py
deactivateStap 2: Bloginhoud Scrapen en Extraheren
parse_blog_sitemap.py doet het zware werk:
- Haalt de sitemap XML op om alle blogpost-URL’s te ontdekken
- Rendert elke pagina met Selenium (nodig omdat Wix-inhoud dynamisch geladen wordt)
- Extraheert de
<div id="content-wrapper">om artikelinhoud te isoleren - Downloadt alle afbeeldingen lokaal en werkt
src-attributen bij - Slaat de opgeschoonde HTML op als
_index.html - Roept de Markdown-converter aan
Waarom Selenium in plaats van requests? Wix rendert inhoud met JavaScript. Een eenvoudige HTTP-aanvraag geeft een lege paginahuls terug. Selenium draait een headless Chrome-browser om de volledig gerenderde HTML te krijgen.
#!/usr/bin/env python3
import os
import re
import time
import xml.etree.ElementTree as ET
from urllib.parse import urlparse
from bs4 import BeautifulSoup
import urllib.request
from selenium import webdriver
from selenium.webdriver.chrome.options import Options
from selenium.webdriver.chrome.service import Service as ChromeService
from webdriver_manager.chrome import ChromeDriverManager
# === CONFIG ===
SITEMAP_URL = "https://www.everappz.com/blog-posts-sitemap.xml"
BASE_OUTPUT_DIR = "downloads"
GPT_CONVERTER_SCRIPT = "generate_md.py"
# === UTILITIES ===
def fetch_rendered_html(url):
options = Options()
options.add_argument("--headless")
options.add_argument("--disable-gpu")
options.add_argument("--no-sandbox")
options.add_argument("--disable-dev-shm-usage")
options.add_argument("--window-size=1920,1080")
driver = webdriver.Chrome(service=ChromeService(ChromeDriverManager().install()), options=options)
try:
driver.get(url)
time.sleep(3)
return driver.page_source
finally:
driver.quit()
def sanitize_filename(filename):
return re.sub(r'[<>:"/\\\\|?*]', '_', filename)
def get_last_path_components(url, levels=2):
parts = urlparse(url).path.strip("/").split("/")
return os.path.join(*parts[-levels:])
def download_image(img_url, dest_folder):
try:
parsed = urlparse(img_url)
filename = os.path.basename(parsed.path)
dest_path = os.path.join(dest_folder, filename)
print(f"📥 Downloading image: {img_url}")
urllib.request.urlretrieve(img_url, dest_path)
return filename
except Exception as e:
print(f"⚠️ Failed to download image: {img_url} - {e}")
return None
def extract_content_wrapper(html):
soup = BeautifulSoup(html, "html.parser")
wrapper = soup.find("div", id="content-wrapper")
return str(wrapper) if wrapper else ""
def update_image_sources(content_html, folder):
from urllib.parse import urlparse
soup = BeautifulSoup(content_html, "html.parser")
for img in soup.find_all("img"):
src = img.get("data-pin-media") or img.get("src")
if src:
try:
parsed = urlparse(src)
filename = os.path.basename(parsed.path)
dest_path = os.path.join(folder, filename)
print(f"📥 Downloading image: {src}")
urllib.request.urlretrieve(src, dest_path)
img["src"] = filename # Update src to local path
except Exception as e:
print(f"⚠️ Failed to download image: {src} - {e}")
return str(soup)
def parse_sitemap_and_process():
os.makedirs(BASE_OUTPUT_DIR, exist_ok=True)
sitemap_xml = urllib.request.urlopen(SITEMAP_URL).read()
root = ET.fromstring(sitemap_xml)
url_elems = root.findall("{http://www.sitemaps.org/schemas/sitemap/0.9}url")
print(f"🔎 Total URLs found: {len(url_elems)}")
for url_elem in url_elems:
loc_elem = url_elem.find("{http://www.sitemaps.org/schemas/sitemap/0.9}loc")
if loc_elem is not None:
page_url = loc_elem.text.strip()
print(f"\n🔗 Processing: {page_url}")
try:
subpath = get_last_path_components(page_url)
folder_path = os.path.join(BASE_OUTPUT_DIR, subpath)
os.makedirs(folder_path, exist_ok=True)
html = fetch_rendered_html(page_url)
wrapper_html = extract_content_wrapper(html)
if not wrapper_html:
print(f"❌ No <div id='content-wrapper'> found in {page_url}")
continue
updated_html = update_image_sources(wrapper_html, folder_path)
index_html_path = os.path.join(folder_path, "_index.html")
with open(index_html_path, "w", encoding="utf-8") as f:
f.write(updated_html)
print(f"✅ Saved: {index_html_path}")
# Optional: call markdown converter
os.system(f"python3 {GPT_CONVERTER_SCRIPT} \"{index_html_path}\"")
except Exception as e:
print(f"❌ Failed to process {page_url}: {e}")
if __name__ == "__main__":
parse_sitemap_and_process()Stap 3: HTML naar Markdown Converteren met OpenAI
generate_md.py leest elk _index.html-bestand, stuurt de inhoud naar OpenAI’s Chat API en schrijft de resulterende Markdown.
#!/usr/bin/env python3
import os
import sys
import json
import time
import random
import urllib.request
import urllib.error
from bs4 import BeautifulSoup
# === CONFIGURATION ===
API_MODEL = "gpt-4o"
API_KEY_FILE = "OPENAI_API_KEY.TXT"
DISABLE_API_REQUESTS = False
def read_openai_api_key():
with open(API_KEY_FILE, "r", encoding="utf-8") as f:
return f.read().strip()
def call_openai_to_convert_to_markdown(html_content, api_key=None):
if DISABLE_API_REQUESTS:
return html_content
if api_key is None:
api_key = read_openai_api_key()
time.sleep(round(random.uniform(1.0, 2.0), 2))
system_prompt = (
"You are a tool that converts HTML content from blog posts into well-structured Markdown (.md) format. "
"Convert all visible text content and replace all <img> tags with Markdown image syntax using their local filenames. "
"Retain the content hierarchy using proper markdown headers, and preserve paragraph structure. "
"Make sure image alt attributes (if any) are preserved as the alt text in the markdown image syntax."
)
data = {
"model": API_MODEL,
"temperature": 0.3,
"messages": [
{"role": "system", "content": system_prompt},
{"role": "user", "content": html_content}
]
}
request = urllib.request.Request(
"https://api.openai.com/v1/chat/completions",
data=json.dumps(data).encode("utf-8"),
headers={
"Authorization": f"Bearer {api_key}",
"Content-Type": "application/json"
}
)
try:
with urllib.request.urlopen(request) as response:
result = json.load(response)
markdown = result["choices"][0]["message"]["content"].strip()
return markdown
except Exception as e:
print(f"❌ OpenAI API request failed: {e}")
return ""
def extract_html_content(file_path):
with open(file_path, "r", encoding="utf-8") as f:
html = f.read()
soup = BeautifulSoup(html, "html.parser")
return soup.prettify()
def write_markdown_file(output_path, markdown_text):
with open(output_path, "w", encoding="utf-8") as f:
f.write(markdown_text)
print(f"✅ Markdown saved to {output_path}")
def main():
if len(sys.argv) != 2:
print("Usage: python3 generate_md.py path/to/_index.html")
return
html_file = sys.argv[1]
if not os.path.exists(html_file):
print(f"❌ File not found: {html_file}")
return
print(f"🔍 Converting HTML to Markdown: {html_file}")
html_content = extract_html_content(html_file)
markdown = call_openai_to_convert_to_markdown(html_content)
if markdown:
md_path = os.path.join(os.path.dirname(html_file), "_index.md")
write_markdown_file(md_path, markdown)
if __name__ == "__main__":
main()Uitvoermapstructuur
Na het uitvoeren van de pipeline krijgt elk blogbericht zijn eigen map:
downloads/
your-post-title/
_index.html # Geëxtraheerde en opgeschoonde HTML
_index.md # Geconverteerde Markdown
image1.png # Gedownloade afbeeldingen
image2.pngOpenAI API-sleutel Instellen
Sla uw API-sleutel op in een bestand genaamd OPENAI_API_KEY.TXT in de scriptmap:
sk-XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXDe Volledige Pipeline Uitvoeren
bash fetch_blog_posts.shDit enkele commando stelt de omgeving in, scrapt alle blogberichten van de sitemap, downloadt afbeeldingen en converteert alles naar Markdown.
Bijdragen aan het Project
Het project is open source. Bugrapporten, functiesuggesties en pull requests zijn welkom.
Veelgestelde Vragen
Waarom kan ik niet gewoon requests gebruiken om Wix blogberichten te scrapen?
Werkt dit met elke Wix blog?
SITEMAP_URL-variabele in parse_blog_sitemap.py bij te werken om naar de sitemap van uw site te verwijzen.
Welk OpenAI-model gebruikt dit?
API_MODEL-variabele in generate_md.py wijzigen om een ander model te gebruiken.
Kan ik dit gebruiken om van Wix naar Hugo te migreren?
_index.md-bestanden om de migratie te voltooien.