Guaword Download Work File

word,definition,audio apple, fruit, [sound:apple.mp3] Then import into Anki. guaword_downloader/ ├── downloader.py ├── checkpoint.json ├── output/ │ ├── data.json │ ├── audio/ │ └── images/ ├── requirements.txt └── config.py requirements.txt

Use with low concurrency and respect server load. B. JavaScript-heavy site (Selenium example) from selenium import webdriver from selenium.webdriver.common.by import By driver = webdriver.Chrome() driver.get("https://example.com/guaword") words = driver.find_elements(By.CSS_SELECTOR, ".word-item") data = ["word": w.text for w in words] driver.quit() C. Export to Anki (flashcard app) Generate a CSV compatible with Anki: guaword download

def parse_word(html): soup = BeautifulSoup(html, "html.parser") word = soup.select_one(".word-title").text.strip() definition = soup.select_one(".def").text.strip() return "word": word, "definition": definition def get_all_word_ids(base_url, max_pages=10): ids = [] for page in range(1, max_pages+1): page_url = f"base_url?page=page" # ... fetch and parse IDs from page links ids.extend(extract_ids_from_page(page_url)) time.sleep(1) # polite delay return ids Step 4: Download Media Files (Audio/Images) def download_file(url, output_path): response = requests.get(url, stream=True) total_size = int(response.headers.get('content-length', 0)) with open(output_path, 'wb') as f: with tqdm(total=total_size, unit='B', unit_scale=True) as pbar: for chunk in response.iter_content(chunk_size=8192): f.write(chunk) pbar.update(len(chunk)) Step 5: Save Structured Data import json, csv def save_as_json(data, filename="guaword_export.json"): with open(filename, "w", encoding="utf-8") as f: json.dump(data, f, ensure_ascii=False, indent=2) word,definition,audio apple, fruit, [sound:apple

def save_checkpoint(downloaded_set): with open(CHECKPOINT_FILE, "w") as f: json.dump(list(downloaded_set), f) A. Parallel Downloading (Faster but risky) from concurrent.futures import ThreadPoolExecutor with ThreadPoolExecutor(max_workers=3) as executor: results = executor.map(fetch_word_page, word_ids) Parallel Downloading (Faster but risky) from concurrent

requests beautifulsoup4 tqdm selenium # optional