#!/usr/bin/env python3 """ Convert captured STATdx document JSON files (containing HTML) into Markdown files. Usage: python scrapers/document_to_markdown.py --input-dir xhr_captured_async --output-dir docs_md The script looks for .json files in the input directory. For each file it tries to extract HTML from common keys like `documentHtml`, `html`, or `content` and converts that HTML to Markdown using BeautifulSoup-based rules. Output: a .md file next to the JSON (or in --output-dir) with the same base name. """ from __future__ import annotations import argparse import glob import json import os import re from datetime import datetime import shutil from typing import Iterable from bs4 import BeautifulSoup, NavigableString, Tag import html import hashlib import urllib.parse from pprint import pformat from loguru import logger import sys IMAGE_GROUPS = {} CAPTURE_INPUT_DIR = None DOCUMENT_SUMMARYS = {} def text_of(node) -> str: """Return the text content of a node, stripping extra whitespace.""" if node is None: return "" s = node.get_text(separator=" ", strip=True) if hasattr(node, "get_text") else str(node).strip() # collapse multiple spaces return re.sub(r"\s+", " ", s) def node_to_md(node, indent=0) -> str: """Recursively convert a BeautifulSoup node to Markdown.""" if node is None: return "" if isinstance(node, NavigableString): return str(node) if isinstance(node, Tag): name = node.name.lower() # headings if name in ("h1", "h2", "h3", "h4", "h5", "h6"): level = int(name[1]) return "\n" + ("#" * level) + " " + text_of(node) + "\n\n" if name == "p": return "\n" + text_of(node) + "\n\n" if name in ("strong", "b"): return "**" + text_of(node) + "**" if name in ("em", "i"): return "*" + text_of(node) + "*" if name == "a": href = node.get("href") or "" text = text_of(node) or href return f"[{text}]({href})" if name == "img": src = node.get("src") or node.get("data-src") or "" alt = node.get("alt") or "" return f"![{alt}]({src})" if name in ("code",) and node.parent and node.parent.name == "pre": # handled in pre return str(node) if name == "pre": # code block code_text = node.get_text() or "" # try to detect language from class like language-python classes = " ".join(node.get("class") or []) lang_match = re.search(r"language-([a-zA-Z0-9_+-]+)", classes) lang = lang_match.group(1) if lang_match else "" fence = "```" + (lang or "") return "\n" + fence + "\n" + code_text.rstrip() + "\n" + "```\n\n" if name in ("ul", "ol"): out = "\n" for li in node.find_all("li", recursive=False): prefix = "- " if name == "ul" else "1. " # indent nested lists content = node_to_md(li, indent=indent + 2).strip() content = content.replace("\n", "\n" + " " * (indent + 2)) out += " " * indent + prefix + content + "\n" out += "\n" return out if name == "li": parts = [] for child in node.children: parts.append(node_to_md(child, indent=indent)) return "".join(parts) if name == "blockquote": content = text_of(node) lines = content.splitlines() return "\n" + "\n".join( "> " + line for line in lines if line.strip() ) + "\n\n" if name == "table": # simple table conversion: try header row then body rows rows = [] for tr in node.find_all("tr"): cells = [text_of(td) for td in tr.find_all(["th", "td"])] rows.append(cells) if not rows: return "" # header is first row header = rows[0] sep = ["---"] * len(header) out = "| " + " | ".join(header) + " |\n" out += "| " + " | ".join(sep) + " |\n" for r in rows[1:]: out += "| " + " | ".join(r) + " |\n" out += "\n" return out # block-level elements we want to preserve newlines for if name in ("div", "section", "article", "main", "header", "footer"): parts = [node_to_md(child, indent=indent) for child in node.children] return "".join(parts) # fallback: inline rendering of children parts = [] for child in node.children: parts.append(node_to_md(child, indent=indent)) return "".join(parts) # should never get here, but ensure a string is returned return "" def html_to_markdown(html: str) -> str: """Convert HTML fragment/string to markdown text.""" soup = BeautifulSoup(html, "html.parser") # If there's an
use that, otherwise body, otherwise whole doc candidate = soup.find("article") or soup.find("body") or soup md = node_to_md(candidate) # cleanup: collapse 3+ newlines to 2 md = re.sub(r"\n{3,}", "\n\n", md) # strip leading/trailing whitespace return md.strip() + "\n" def find_html_in_json(obj) -> str | None: """Heuristics to find an HTML payload in a JSON object.""" if not isinstance(obj, dict): return None # common keys for key in ("documentHtml", "html", "content", "document_html", "bodyHtml"): if key in obj and isinstance(obj[key], str) and ("<" in obj[key] and ">" in obj[key]): return obj[key] # search nested for v in obj.values(): if isinstance(v, str) and "<" in v and ">" in v: return v return None def slugify(s: str, max_len: int = 80) -> str: """Create a filesystem-friendly slug from a string.""" if not s: return "" s = s.lower() # replace spaces and slashes with hyphens s = re.sub(r"[\s/]+", "-", s) # remove characters that are not alnum, dash, or underscore s = re.sub(r"[^a-z0-9\-_]+", "", s) # collapse multiple hyphens s = re.sub(r"-+", "-", s) s = s.strip("-_") if max_len and len(s) > max_len: s = s[:max_len].rstrip("-_") return s #def find_article_name_in_json(obj) -> str | None: # """Look for an article name in known keys or nested values. # # Common keys include: aname, articleName, name, title, documentTitle # """ # if not isinstance(obj, dict): # return None # # candidates = [ # "aname", # "articleName", # "article_name", # "name", # "title", # "documentTitle", # "document_title", # ] # for key in candidates: # if key in obj: # v = obj.get(key) # if isinstance(v, str) and v.strip(): # return v.strip() # # # try shallow nested search for non-empty strings # for v in obj.values(): # if isinstance(v, str) and v.strip(): # # skip values that look like html (we prefer explicit name keys) # if "<" in v or ">" in v: # continue # # short string looks promising # if len(v.strip()) <= 200: # return v.strip() # # return None def extract_title_from_html(html: str) -> str | None: """Try to extract a human-friendly title from HTML content. Checks in order:

, , , , then first <h2>. """ if not html: return None soup = BeautifulSoup(html, "html.parser") # h1 first h1 = soup.find("h1") if h1 and text_of(h1).strip(): return text_of(h1).strip() # OpenGraph title og = soup.find("meta", property="og:title") if og and og.get("content"): return og.get("content").strip() # meta name=title m = soup.find("meta", attrs={"name": "title"}) if m and m.get("content"): return m.get("content").strip() # document <title> t = soup.find("title") if t and t.string: return t.string.strip() # fallback to first h2 h2 = soup.find("h2") if h2 and text_of(h2).strip(): return text_of(h2).strip() return None def recursive_search_for_key(obj, key: str): """Recursively search for the first occurrence of key in a nested JSON-like object.""" if isinstance(obj, dict): if key in obj and isinstance(obj[key], str) and obj[key].strip(): return obj[key].strip() for v in obj.values(): res = recursive_search_for_key(v, key) if res: return res elif isinstance(obj, list): for item in obj: res = recursive_search_for_key(item, key) if res: return res return None def recursive_search_for_value(obj, value: str) -> bool: """Return True if `value` appears as a substring in any string value inside obj.""" if value is None: return False if isinstance(obj, str): return value in obj if isinstance(obj, dict): for v in obj.values(): if recursive_search_for_value(v, value): return True elif isinstance(obj, list): for it in obj: if recursive_search_for_value(it, value): return True return False def find_breadcrumbs_for_docid(docid: str, search_dir: str) -> list: """Return a list of breadcrumb strings associated with docid by scanning captured JSONs. Preserves discovery order and HTML-unescapes values. """ if not docid: return [] def collect_names_from_breadcrumbs(bc_list): names = [] if isinstance(bc_list, list): for item in bc_list: if isinstance(item, dict) and item.get("name"): names.append(html.unescape(item.get("name"))) return names # First, prefer files whose filename contains the docid. These often # include a structured `breadcrumbs` list (ordered parents) and may # include a leaf node entry for the document. candidates = [] doc_paths = sorted(glob.glob(os.path.join(search_dir, f"*{docid}*.json"))) for path in doc_paths: try: with open(path, "r", encoding="utf-8") as f: data = json.load(f) except Exception: continue # look for a breadcrumbs list anywhere in this JSON # and prefer the first full list we find def recurse_find_breadcrumb_lists(obj): out = [] if isinstance(obj, dict): for k, v in obj.items(): if k == "breadcrumbs" and isinstance(v, list): names = collect_names_from_breadcrumbs(v) if names: out.append(names) out.extend(recurse_find_breadcrumb_lists(v)) elif isinstance(obj, list): for item in obj: out.extend(recurse_find_breadcrumb_lists(item)) return out bc_lists = recurse_find_breadcrumb_lists(data) if bc_lists: # take the first breadcrumbs list as base path base = bc_lists[0].copy() # try to find a leaf name for this doc within the JSON leaf = None def recurse_find_leaf(obj): nonlocal leaf if leaf: return if isinstance(obj, dict): # node that references the document directly if obj.get("documentId") == docid and obj.get("name"): leaf = html.unescape(obj.get("name")) return # some files use enhancedDocumentName/documentName for k in ("enhancedDocumentName", "documentName", "name", "title"): if k in obj and isinstance(obj[k], str) and obj.get("documentId") == docid: leaf = html.unescape(obj.get(k)) return for v in obj.values(): recurse_find_leaf(v) elif isinstance(obj, list): for item in obj: recurse_find_leaf(item) recurse_find_leaf(data) if leaf and (not base or base[-1] != leaf): base.append(leaf) if base and base not in candidates: candidates.append(base) # If we found candidate breadcrumb paths from docid-matching files, return the first if candidates: return candidates[0] # Otherwise, scan all JSONs for entries that explicitly list the docid and # attempt to reconstruct a breadcrumb path by combining any nearby breadcrumbs all_paths = sorted(glob.glob(os.path.join(search_dir, "*.json"))) for path in all_paths: try: with open(path, "r", encoding="utf-8") as f: data = json.load(f) except Exception: continue # list-of-dicts captures where an item references the documentId if isinstance(data, list): for item in data: if isinstance(item, dict) and item.get("documentId") == docid: # if this file also contains a breadcrumbs list elsewhere, use it bc_lists = [] if isinstance(data, dict): bc_lists = [] # try to locate breadcrumbs within same file by re-loading def find_bcs(obj): if isinstance(obj, dict): if obj.get("breadcrumbs") and isinstance(obj.get("breadcrumbs"), list): return collect_names_from_breadcrumbs(obj.get("breadcrumbs")) for v in obj.values(): res = find_bcs(v) if res: return res elif isinstance(obj, list): for it in obj: res = find_bcs(it) if res: return res return None bcs = find_bcs(data) path_names = bcs or [] # append the item's own enhancedDocumentName/name if present leaf = item.get("enhancedDocumentName") or item.get("name") if isinstance(leaf, str) and leaf.strip(): leaf = html.unescape(leaf.strip()) if not path_names or path_names[-1] != leaf: path_names = path_names + [leaf] if path_names: return path_names return [] def find_title_in_capture_index(docid: str, base_dir: str) -> str | None: """Look for a title for docid inside a capture_index.jsonl file in base_dir. capture_index.jsonl contains many JSON lines with search results; prefer titles found there. """ idx_path = os.path.join(base_dir, "capture_index.jsonl") if not os.path.exists(idx_path): # try parent idx_path = os.path.join(os.path.dirname(base_dir), "capture_index.jsonl") if not os.path.exists(idx_path): return None try: with open(idx_path, "r", encoding="utf-8") as f: for line in f: line = line.strip() if not line: continue try: j = json.loads(line) except Exception: continue # top-level id if j.get("id") == docid and j.get("title"): return j.get("title") # inside searchResults.results sr = j.get("searchResults") if isinstance(sr, dict): results = sr.get("results") if isinstance(results, list): for r in results: if isinstance(r, dict) and r.get("id") == docid and r.get("title"): return r.get("title") except Exception: return None return None def process_file(path: str, out_dir: str, overwrite: bool = False) -> tuple[bool, str]: """Process one JSON file. Returns (success, output_path_or_error).""" base = os.path.basename(path) name, _ = os.path.splitext(base) logger.debug(f"Processing file: {path}") # attempt to extract article name for nicer filenames try: with open(path, "r", encoding="utf-8") as f: data_peek = json.load(f) except Exception: data_peek = None # deterministic doc id (if present in filename) docid = None docid = base.split("_document_content_")[1].split("_")[0] logger.debug(f"Extracted docid: {docid}") #logger.debug(f"DOCUMENT_SUMMARYS keys: {DOCUMENT_SUMMARYS.get(docid)}") article_name = DOCUMENT_SUMMARYS.get(docid).get("title") # if still not found, try to extract from inline HTML #if not article_name and isinstance(data_peek, dict): # html_candidate = find_html_in_json(data_peek) # if html_candidate: # title_from_html = extract_title_from_html(html_candidate) # if title_from_html: # article_name = title_from_html logger.debug(f"Determined article name: {article_name}") if article_name: slug = slugify(article_name) # prefer deterministic filename based on docid when available to avoid duplicates if docid: out_base = f"{slug}_{docid}" if slug else docid else: out_base = f"{slug}_{name}" if slug else name # place titled articles into an articles/ subfolder target_dir = os.path.join(out_dir, "articles") if isinstance(article_name, str) and article_name.startswith("https"): return False, "external-url" target_dir = os.path.join(out_dir, "external") else: # per request: only save files that have titles logger.error(f"No article name found for {path}; skipping.") return False, "no-title" out_path = os.path.join(target_dir, out_base + ".md") if os.path.exists(out_path) and not overwrite: return False, f"exists: {out_path}" try: with open(path, "r", encoding="utf-8") as f: data = json.load(f) except Exception as e: return False, f"json load error: {e}" html = find_html_in_json(data) if not html: return False, "no-html-found" md = html_to_markdown(html) # If we have an article_name (extracted earlier for filename), prepend it as H1 try: if article_name: # avoid duplicating if the markdown already starts with the same header first_line = md.lstrip().splitlines()[0] if md.strip() else "" normalized_first = re.sub(r"[#\s]+", "", first_line).strip().lower() normalized_title = re.sub(r"[^a-z0-9]+", "", article_name.lower()) if not normalized_first or normalized_title not in normalized_first: # Build YAML frontmatter with title and breadcrumbs (and docid) front_lines = ["---"] # use JSON quoting to safely escape strings in YAML front_lines.append(f"title: {json.dumps(article_name.strip())}") if docid: front_lines.append(f"docid: {json.dumps(docid)}") # collect breadcrumbs and render as YAML list if present crumbs = [] if docid: crumbs = find_breadcrumbs_for_docid(docid, os.path.dirname(path) or ".") if crumbs: front_lines.append("breadcrumbs:") for c in crumbs: front_lines.append(f" - {json.dumps(c)}") front_lines.append("---\n") front = "\n".join(front_lines) # Avoid duplicating an H1 that matches the title in the body md_lines = md.lstrip().splitlines() if md_lines: first = md_lines[0].strip() normalized_first = re.sub(r"[#\s]+", "", first).strip().lower() normalized_title = re.sub(r"[^a-z0-9]+", "", article_name.lower()) if first.startswith("#") and normalized_title in normalized_first: # drop the first line (existing H1) md_lines = md_lines[1:] md = front + "\n".join(md_lines).lstrip() except Exception: # be conservative: if anything goes wrong, keep the original md pass # (channel/frontmatter injection removed - handled elsewhere) image_data_to_add = {} if isinstance(data_peek, dict) and "imageGroups" in data_peek: for img_group in data_peek.get("imageGroups", []): #logger.debug(f"Image group: {pformat(img_group)}") group_id = img_group.get("imageGroupId") try: image_data = IMAGE_GROUPS[group_id] image_data_to_add[image_data["name"]] = image_data["images"] except KeyError: logger.warning(f"Image group {group_id} not found in IMAGE_GROUPS.") #logger.debug(f"Extracted image data to add: {pformat(image_data_to_add)}") # If we have image groups to add, copy matching files and append a formatted # Images section to the markdown. We search the capture input directory # recursively for filenames containing the imageId and copy any matches. try: if image_data_to_add: images_dir = os.path.join(target_dir, "images") os.makedirs(images_dir, exist_ok=True) appended_images = [] images_md_lines = ["\n\n## Images\n"] # map imageId -> (rel_path, caption) for replacement in-md image_map: dict = {} search_root = CAPTURE_INPUT_DIR or os.path.dirname(path) or "." for group_name, images in image_data_to_add.items(): images_md_lines.append(f"\n### {group_name}\n") # render each image in the group for img in images: try: iid = img.get('imageId') or img.get('id') caption = img.get('caption') or img.get('imageTitle') or img.get('title') or "" thumb = img.get('thumbnailUrl') or "" # find matching files under the capture input dir recursively matches = [] if iid: matches = glob.glob(os.path.join(search_root, "**", f"*{iid}*"), recursive=True) # also consider thumbnail URL id in case different naming if not matches and isinstance(thumb, str) and thumb: m = re.search(r"/thumbnail/([0-9a-fA-F-\-]+)", thumb) if m: tid = m.group(1) matches = glob.glob(os.path.join(search_root, "**", f"*{tid}*"), recursive=True) rel_paths = [] for match in sorted(set(matches)): # skip JSON metadata files; prefer binary images b = os.path.basename(match) if b.endswith('.json') or b.endswith('.meta.json'): # still copy metadata alongside image when present # we'll copy meta files later if we also find an image continue try: dst = os.path.join(images_dir, os.path.basename(match)) if os.path.abspath(match) != os.path.abspath(dst): shutil.copy2(match, dst) rel = os.path.join('images', os.path.basename(match)) rel_paths.append(rel) appended_images.append(rel) # associate imageId -> rel + caption for later replacement if iid: # prefer explicit caption if available cval = caption or img.get('caption') or img.get('imageTitle') or img.get('title') or '' image_map[iid] = (rel, cval) except Exception: continue # If we found images, render them; otherwise, render the thumbnail URL if present if rel_paths: for rp in rel_paths: cap = caption or os.path.basename(rp) # render image and then visible caption on the next line images_md_lines.append(f"![{cap}]({rp})") # ensure caption is visible (italicized) images_md_lines.append(f"*{cap}*") images_md_lines.append("") else: # try to render a thumbnail path (as-is) if no local file if thumb: # normalize thumb path to a relative filename when possible thumb_name = os.path.basename(thumb.split('?')[0]) images_md_lines.append(f"![{caption}]({thumb_name})") images_md_lines.append(f"*{caption}*") images_md_lines.append("") else: # at minimum show caption text if caption: images_md_lines.append(f"*{caption}*") images_md_lines.append("") except Exception: continue # attach Images section to markdown # Before attaching, replace inline references to these images so # their alt text shows the caption (not original alt). try: for iid, (rel, cap) in image_map.items(): # replace markdown image links that include the imageId or filename bn = os.path.basename(rel) # 1) replace markdown image links where the URL contains the imageId md = re.sub(r'!\[[^\]]*\]\([^)]*' + re.escape(iid) + r'[^)]*\)', f'![{cap}]({rel})\n\n*{cap}*', md) # 2) replace markdown image links where URL contains the basename md = re.sub(r'!\[[^\]]*\]\([^)]*' + re.escape(bn) + r'[^)]*\)', f'![{cap}]({rel})\n\n*{cap}*', md) # 3) replace HTML <img ... src="...basename..."> with markdown image md = re.sub(r'<img[^>]+src=["\"][^"\']*' + re.escape(bn) + r'[^"\']*["\"][^>]*>', f'![{cap}]({rel})\n\n*{cap}*', md) # 4) replace full URLs ending with basename md = re.sub(r'https?://[^)\s]*' + re.escape(bn), rel, md) # 5) replace URL-encoded variants try: q = urllib.parse.quote(bn) md = md.replace(q, rel) except Exception: pass except Exception: pass md = md.rstrip() + "\n" + "\n".join(images_md_lines) + "\n" # update a top-level images index so we can see associations across runs try: images_index_path = os.path.join(out_dir, "_images_index.json") images_index = {} if os.path.exists(images_index_path): with open(images_index_path, 'r', encoding='utf-8') as ixf: try: images_index = json.load(ixf) except Exception: images_index = {} images_index[out_path] = appended_images with open(images_index_path, 'w', encoding='utf-8') as ixf: json.dump(images_index, ixf, indent=2, ensure_ascii=False) except Exception: pass except Exception: # non-fatal; continue without images pass # Before writing, compute a normalized content hash to detect duplicates def normalize_for_hash(s: str) -> str: # remove ISO8601-like timestamps and common date patterns, collapse whitespace s2 = re.sub(r"\d{4}-\d{2}-\d{2}T\d{2}:\d{2}:\d{2}(?:Z|[+-]\d{2}:?\d{2})?", "", s) s2 = re.sub(r"\b\d{1,2}/\d{1,2}/\d{2,4}\b", "", s2) # remove lines that are just timestamps or contain 'Last updated' s2 = "\n".join([ln for ln in s2.splitlines() if not re.match(r"^\s*(Last updated|LastVisited|LastVisitedAsDate|Updated).*$", ln, re.I)]) s2 = re.sub(r"\s+", " ", s2).strip() return s2 def content_hash(s: str) -> str: nh = normalize_for_hash(s) return hashlib.sha256(nh.encode("utf-8")).hexdigest() # index stored at top-level out_dir to dedupe across articles/external index_path = os.path.join(out_dir, "_content_index.json") index = {} try: if os.path.exists(index_path): with open(index_path, "r", encoding="utf-8") as ix: index = json.load(ix) except Exception: index = {} ch = content_hash(md) existing = index.get(ch) if existing and os.path.exists(existing) and not overwrite: # content already saved elsewhere — skip writing return False, f"duplicate: {existing}" try: os.makedirs(target_dir, exist_ok=True) with open(out_path, "w", encoding="utf-8") as f: f.write(md) # update index try: index[ch] = out_path with open(index_path, "w", encoding="utf-8") as ix: json.dump(index, ix, indent=2, ensure_ascii=False) except Exception: pass # log saved file path with timestamp try: log_path = os.path.join(target_dir, "_saved_files.log") from datetime import timezone with open(log_path, "a", encoding="utf-8") as lf: lf.write(f"{datetime.now(timezone.utc).isoformat()}\t{out_path}\n") except Exception: # non-fatal if logging fails pass except Exception as e: return False, f"write error: {e}" return True, out_path def main(argv: Iterable[str] | None = None) -> int: p = argparse.ArgumentParser(description="Convert captured JSON HTML to Markdown") p.add_argument("--input-dir", default="xhr_captured_async", help="Directory with captured .json files") p.add_argument("--output-dir", default="docs_md", help="Where to write .md files (defaults to input-dir) ") p.add_argument("--pattern", default="*.json", help="Glob pattern to find files in input dir") p.add_argument("--overwrite", action="store_true", help="Overwrite existing .md files") p.add_argument("--verbose", "-v", action="store_true", help="Print processing details") p.add_argument("--clear", "-c", action="store_true", default=False, help="Clear output directory before processing (default: false)") args = p.parse_args(list(argv) if argv is not None else None) input_dir = args.input_dir output_dir = args.output_dir or input_dir if args.clear and os.path.exists(output_dir): # remove all .md files in output_dir shutil.rmtree(output_dir, ignore_errors=True) files = sorted(glob.glob(os.path.join(input_dir, args.pattern))) if not files: print(f"No files found in {input_dir} matching {args.pattern}") return 1 # Start by caching image group metadata for path in files: base = os.path.basename(path) # only process files that match the desired prefix if not base.startswith("app.statdx.com_document_") or base.endswith("meta.json") or ("_media_" not in base): continue with open(path, "r", encoding="utf-8") as f: image_group_data = json.load(f) for group in image_group_data: group_id = group.get("groupId") group_name = group.get("name") images = group.get("images", []) IMAGE_GROUPS[group_id] = { "name": group_name, "images": images, } #logger.debug(f"Image group {n}: {pformat(group)}") # Then cache document summary data for path in files: base = os.path.basename(path) # only process files that match the desired prefix if "document_summary" not in base or "meta" in base: continue with open(path, "r", encoding="utf-8") as f: summary_data = json.load(f) doc_id = base.split("_document_summary_")[1].split("_")[0] DOCUMENT_SUMMARYS[doc_id] = summary_data #logger.debug(f"Document summary {n}: {pformat(doc)}") logger.debug(f"Cached {len(IMAGE_GROUPS)} image groups from media files.") logger.debug(f"Cached {len(DOCUMENT_SUMMARYS)} document summaries from summary files.") ok = 0 for path in files: base = os.path.basename(path) # only process files that match the desired prefix if not base.startswith("app.statdx.com_document_") or base.endswith("meta.json") or ("_media_" in base) or ("breadcrumbs" in base) or ("_summary_" in base) or ("_tables_" in base): #if args.verbose: # print(f"SKIP (not matching prefix): {path}") continue success, info = process_file(path, output_dir, overwrite=args.overwrite) if success: ok += 1 if args.verbose: print(f"WROTE: {info}") else: if args.verbose: print(f"SKIP: {path} -> {info}") continue print(f"Converted {ok}/{len(files)} files to Markdown in {output_dir}") return 0 if __name__ == "__main__": raise SystemExit(main())