extract_bio_old.py

import os
import json
from bs4 import BeautifulSoup
from concurrent.futures import ProcessPoolExecutor, as_completed

def extract_biography_from_html(soup):
    header = soup.find("h2", class_="normal_header")
    if not header:
        return None, ""

    name = header.get_text(strip=True)

    # Extract bio content after the header
    bio_parts = []
    current = header.next_sibling
    while current:
        if str(current).strip() == "":
            current = current.next_sibling
            continue
        if getattr(current, 'name', None) == "div":
            break
        if getattr(current, 'name', None) == "br":
            bio_parts.append("\n")
        else:
            bio_parts.append(current.get_text(strip=True) if hasattr(current, "get_text") else str(current).strip())
        current = current.next_sibling

    biography = " ".join(bio_parts).replace("\n\n", "\n").strip()

    # If it's a placeholder, return an empty string
    if "no biography written" in biography.lower():
        biography = ""

    return name, biography

def extract_animeography_from_html(soup):
    anime_list = []
    anime_section = soup.find("div", class_="normal_header", string="Animeography")
    if not anime_section:
        return anime_list

    table = anime_section.find_next("table")
    if not table:
        return anime_list

    rows = table.find_all("tr")
    for row in rows:
        cells = row.find_all("td")
        if len(cells) < 2:
            continue

        anime_link_tag = cells[1].find("a", href=True)
        role_tag = cells[1].find("small")

        if anime_link_tag:
            anime_title = anime_link_tag.text.strip()
            anime_url = anime_link_tag['href']
            role = role_tag.text.strip() if role_tag else "Unknown"
            anime_list.append({
                "title": anime_title,
                "url": anime_url,
                "role": role
            })

    return anime_list

def process_single_file(args):
    input_path, output_path = args
    try:
        with open(input_path, "r", encoding="utf-8") as file:
            html_content = file.read()
            soup = BeautifulSoup(html_content, "html.parser")

            name, bio = extract_biography_from_html(soup)
            animeography = extract_animeography_from_html(soup)

            if name:
                data = {
                    "name": name,
                    "biography": bio,
                    "animeography": animeography
                }
                with open(output_path, "w", encoding="utf-8") as json_file:
                    json.dump(data, json_file, indent=2, ensure_ascii=False)
                return f"✅ Saved: {os.path.basename(output_path)}"
            else:
                return f"⚠️ Skipped (no name found): {os.path.basename(input_path)}"
    except Exception as e:
        return f"❌ Error processing {os.path.basename(input_path)}: {e}"

def process_all_html_files_parallel(input_dir, output_dir, max_workers=None):
    os.makedirs(output_dir, exist_ok=True)

    tasks = []
    for filename in os.listdir(input_dir):
        if filename.endswith(".html"):
            input_path = os.path.join(input_dir, filename)
            output_filename = os.path.splitext(filename)[0] + ".json"
            output_path = os.path.join(output_dir, output_filename)
            tasks.append((input_path, output_path))

    with ProcessPoolExecutor(max_workers=max_workers) as executor:
        futures = [executor.submit(process_single_file, task) for task in tasks]
        for future in as_completed(futures):
            print(future.result())

# Update these paths as needed
input_folder = "output/mal_char_ind_pages"
output_folder = "output/char_bio_json"

# Run with default CPU core count (or specify max_workers=4, etc.)
process_all_html_files_parallel(input_folder, output_folder, max_workers=4)