import hashlib
import json
import re
from urllib.parse import urljoin

from bs4 import BeautifulSoup, NavigableString, Tag
from requests import Session

from app.parser.profile_url import normalize_profile_url, parse_profile_identity
from app.version import BACKEND_VERSION

_YEAR_PATTERN = re.compile(r"Начал[аи]?\s+работать.*?ВШЭ.*?(\d{4})", re.IGNORECASE)
_EMAIL_PATTERN = re.compile(r"([A-Za-z0-9._%+-]+@[A-Za-z0-9.-]+\.[A-Za-z]{2,})")
_PHONE_PATTERN = re.compile(r"(?:Телефон|Phone)\s*:\s*([+()\d\-\s]{8,})", re.IGNORECASE)


def normalize_ws(value: str | None) -> str:
    return re.sub(r"\s+", " ", value or "").strip()


def extract_person_tabs(soup: BeautifulSoup, source_url: str) -> list[dict[str, str | None]]:
    selectors = (
        "div.person-menu.is-desktop.small.person-menu-addition",
        ".person-menu",
    )
    for selector in selectors:
        menu = soup.select_one(selector)
        if not menu:
            continue
        tabs = []
        for anchor in menu.select("a[href]"):
            title = normalize_ws(anchor.get_text(" ", strip=True))
            href = anchor.get("href", "").strip()
            if title and href:
                tabs.append(
                    {
                        "data_index": anchor.get("data-index"),
                        "title": title,
                        "href": urljoin(source_url, href),
                    }
                )
        if tabs:
            return _dedupe_tabs(tabs)
    return []


def extract_person_header(soup: BeautifulSoup, source_url: str) -> dict:
    name_node = soup.select_one("h1.person-caption") or soup.find("h1")
    text = normalize_ws(soup.get_text(" ", strip=True))
    year_match = _YEAR_PATTERN.search(text)
    contacts = {"phones": [], "emails": [], "address": None, "items": []}

    for email in _EMAIL_PATTERN.findall(text):
        if email not in contacts["emails"]:
            contacts["emails"].append(email)
    for phone in _PHONE_PATTERN.findall(text):
        normalized_phone = normalize_ws(phone)
        if normalized_phone and normalized_phone not in contacts["phones"]:
            contacts["phones"].append(normalized_phone)

    address_match = re.search(
        r"(Адрес[:\s].{0,220}?)(?:\s+Время|\s+Расписание|\s+SPIN|\s+ORCID|$)",
        text,
        flags=re.IGNORECASE,
    )
    if address_match:
        contacts["address"] = normalize_ws(address_match.group(1)).rstrip(",")

    positions = []
    for li in soup.select("ul.g-ul.g-list.small.employment-add li, ul.employment-add li"):
        value = normalize_ws(li.get_text(" ", strip=True))
        if value:
            positions.append(value)

    external_ids = []
    id_domains = (
        ("ORCID", "orcid.org"),
        ("Scopus AuthorID", "scopus.com"),
        ("ResearcherID", "webofscience.com"),
        ("Google Scholar", "scholar.google."),
        ("SPIN РИНЦ", "elibrary.ru"),
    )
    for anchor in soup.select("a[href]"):
        href = anchor.get("href", "").strip()
        label = normalize_ws(anchor.get_text(" ", strip=True))
        for system, marker in id_domains:
            if marker in href:
                external_ids.append({"system": system, "value": label or system, "url": href})
                break

    return {
        "source_url": source_url,
        "full_name": normalize_ws(name_node.get_text(" ", strip=True)) if name_node else None,
        "positions": positions,
        "hse_start_year": int(year_match.group(1)) if year_match else None,
        "contacts": contacts,
        "external_ids": _dedupe_dicts(external_ids),
    }


def extract_sections(soup: BeautifulSoup, source_url: str) -> list[dict]:
    sections = []
    for h2 in soup.select("h2"):
        title = normalize_ws(h2.get_text(" ", strip=True))
        if not title or "расписание занятий" in title.lower():
            continue
        nodes = _collect_between_h2(h2)
        raw_text = _nodes_raw_text(nodes)
        paragraphs = _nodes_paragraphs(nodes)
        items = _nodes_list_items(nodes)
        links = []
        for node in nodes:
            if isinstance(node, Tag):
                links.extend(_extract_links(node, source_url))

        section_type = _infer_section_type(title, nodes)
        section = {
            "title": title,
            "slug": _slugify(title),
            "type": section_type,
            "raw_text": raw_text,
            "paragraphs": paragraphs,
            "items": items,
            "links": links,
        }

        if section_type == "publications":
            section["publications_count"], section["publications"] = _parse_publications(title, nodes, source_url)
            section["items"] = [item["text"] for item in section["publications"] if item.get("text")]
        elif section_type == "courses_by_year":
            section["academic_year"], section["courses"] = _parse_courses(title, nodes, source_url)
            section.pop("items", None)
            section.pop("links", None)
        elif section_type == "table":
            section["table"] = _parse_table(nodes, source_url)
        elif "выпускные квалификационные работы студентов ниу вшэ" in title.lower():
            section["items"] = _parse_vkr_items(nodes)

        year_entries = _parse_year_entries(nodes, source_url)
        if year_entries:
            section["year_entries"] = year_entries
            if section_type in {"generic", "paragraphs"}:
                section["type"] = "year_blocks"
        sections.append(section)
    return sections


def parse_person_profile(
    session: Session,
    source_url: str,
    headers: dict[str, str],
    timeout: int,
    use_playwright: bool = False,
    resource_cache=None,
) -> dict | None:
    normalized_url = normalize_profile_url(source_url)
    if not normalized_url:
        return None
    profile_type, profile_id = parse_profile_identity(normalized_url)
    cache_profile_key = f"{profile_type}:{profile_id}"
    resource_manifest = []
    html = _fetch_text(
        session,
        normalized_url,
        headers,
        timeout,
        resource_cache=resource_cache,
        profile_key=cache_profile_key,
        resource_key="main-html",
        resource_manifest=resource_manifest,
    )
    if use_playwright:
        html = _render_with_playwright(normalized_url, html)

    soup = BeautifulSoup(html, "html.parser")
    header = extract_person_header(soup, normalized_url)
    tabs = extract_person_tabs(soup, normalized_url)
    sections = extract_sections(soup, normalized_url)
    sections = enrich_sections_from_hse_widgets(
        session,
        soup,
        normalized_url,
        headers,
        timeout,
        sections,
        resource_cache=resource_cache,
        profile_key=cache_profile_key,
        resource_manifest=resource_manifest,
    )
    internal_links = [tab["href"] for tab in tabs if tab.get("href")]

    return {
        "source_url": normalized_url,
        "profile_type": profile_type,
        "profile_id": profile_id,
        "full_name": header.get("full_name"),
        "positions": header.get("positions") or [],
        "hse_start_year": header.get("hse_start_year"),
        "contacts": header.get("contacts") or {},
        "external_ids": header.get("external_ids") or [],
        "tabs": tabs,
        "sections": sections,
        "employee_internal_links": internal_links,
        "parser_version": BACKEND_VERSION,
        "_html": html,
        "_resource_manifest": resource_manifest,
    }


def enrich_sections_from_hse_widgets(
    session: Session,
    soup: BeautifulSoup,
    source_url: str,
    headers: dict[str, str],
    timeout: int,
    sections: list[dict],
    resource_cache=None,
    profile_key: str | None = None,
    resource_manifest: list[dict] | None = None,
) -> list[dict]:
    enriched = list(sections)
    publications = _load_widget_publications(
        session,
        soup,
        headers,
        timeout,
        resource_cache=resource_cache,
        profile_key=profile_key,
        resource_manifest=resource_manifest,
    )
    if publications:
        enriched = _upsert_publications_section(enriched, publications)

    theses = _load_widget_graduation_theses(
        session,
        soup,
        source_url,
        headers,
        timeout,
        resource_cache=resource_cache,
        profile_key=profile_key,
        resource_manifest=resource_manifest,
    )
    if theses:
        enriched = _upsert_graduation_theses_section(enriched, theses)
    return enriched


def _render_with_playwright(source_url: str, fallback_html: str) -> str:
    try:
        from playwright.sync_api import sync_playwright
    except Exception:
        return fallback_html
    try:
        with sync_playwright() as playwright:
            browser = playwright.chromium.launch(headless=True)
            page = browser.new_page()
            page.goto(source_url, wait_until="domcontentloaded", timeout=45000)
            for index in range(page.locator(".person-menu a").count()):
                try:
                    page.locator(".person-menu a").nth(index).click(timeout=2500, force=True)
                    page.wait_for_timeout(450)
                except Exception:
                    continue
            html = page.content()
            browser.close()
            return html
    except Exception:
        return fallback_html


def _load_widget_publications(
    session: Session,
    soup: BeautifulSoup,
    headers: dict[str, str],
    timeout: int,
    *,
    resource_cache=None,
    profile_key: str | None = None,
    resource_manifest: list[dict] | None = None,
) -> list[dict]:
    script = soup.select_one('script[data-widget-name="AuthorSearch"][data-author]')
    if not script:
        return []
    author_id = normalize_ws(script.get("data-author"))
    if not author_id:
        return []

    publications = []
    page_id = 1
    per_page = 100
    while page_id <= 20:
        payload = {
            "type": "ANY",
            "filterParams": (
                f'"acceptLanguage":"ru"|"fullTextPublicEnabled": 1|'
                f'"pubsAuthor": {author_id}|"widgetName": "AuthorSearch"'
            ),
            "paginationParams": {
                "publsSort": ["TITLE_ASC"],
                "publsCount": per_page,
                "pageId": page_id,
            },
        }
        try:
            if resource_cache and profile_key:
                text = _fetch_text(
                    session,
                    "https://publications.hse.ru/api/searchPubs",
                    headers,
                    timeout,
                    resource_cache=resource_cache,
                    profile_key=profile_key,
                    resource_key=f"publications-page-{page_id}",
                    resource_manifest=resource_manifest,
                    method="POST",
                    json_payload=payload,
                )
                data = json.loads(text)
            else:
                response = session.post(
                    "https://publications.hse.ru/api/searchPubs",
                    json=payload,
                    headers=headers,
                    timeout=timeout,
                )
                response.raise_for_status()
                data = response.json()
        except Exception:
            return publications

        result = data.get("result") if isinstance(data, dict) else {}
        items = _extract_publication_items(result)
        if not items:
            break
        publications.extend(_normalize_publication_item(item, author_id) for item in items)

        total = int(result.get("total") or 0)
        if not result.get("more") and len(publications) >= total:
            break
        page_id += 1
    return _dedupe_publications(publications)


def _extract_publication_items(result: object) -> list[dict]:
    if not isinstance(result, dict):
        return []
    return _flatten_publication_items(result.get("items"))


def _flatten_publication_items(value: object) -> list[dict]:
    if isinstance(value, list):
        return [item for item in value if _is_publication_item(item)]
    if not isinstance(value, dict):
        return []

    nested_items = value.get("items")
    if isinstance(nested_items, list):
        return [item for item in nested_items if _is_publication_item(item)]
    if isinstance(nested_items, dict):
        return _flatten_publication_items(nested_items)

    publications = []
    for child in value.values():
        publications.extend(_flatten_publication_items(child))
    return publications


def _is_publication_item(value: object) -> bool:
    return isinstance(value, dict) and ("id" in value or "title" in value)


def _load_widget_graduation_theses(
    session: Session,
    soup: BeautifulSoup,
    source_url: str,
    headers: dict[str, str],
    timeout: int,
    *,
    resource_cache=None,
    profile_key: str | None = None,
    resource_manifest: list[dict] | None = None,
) -> list[dict]:
    script = soup.select_one('script[src*="/n/stat/vkr/app.js"][data-person-id]')
    if not script:
        return []
    person_id = normalize_ws(script.get("data-person-id"))
    api_url = normalize_ws(script.get("data-api-url")) or "/n/vkr/api/"
    if not person_id:
        return []

    request_headers = {**headers, "x-portal-language": "ru"}
    try:
        url = urljoin(source_url, api_url)
        params = {"supervisorId": person_id}
        if resource_cache and profile_key:
            text = _fetch_text(
                session,
                url,
                request_headers,
                timeout,
                resource_cache=resource_cache,
                profile_key=profile_key,
                resource_key="graduation-theses",
                resource_manifest=resource_manifest,
                params=params,
            )
            data = json.loads(text)
        else:
            response = session.get(
                url,
                params=params,
                headers=request_headers,
                timeout=timeout,
            )
            response.raise_for_status()
            data = response.json()
    except Exception:
        return []

    items = data.get("data") if isinstance(data, dict) else []
    if not isinstance(items, list):
        return []
    return [_normalize_vkr_item(item, source_url) for item in items if isinstance(item, dict)]


def _collect_between_h2(start_h2: Tag) -> list[Tag | NavigableString | str]:
    nodes = []
    for sibling in start_h2.next_siblings:
        if isinstance(sibling, Tag) and sibling.name == "h2":
            break
        if isinstance(sibling, NavigableString) and not normalize_ws(str(sibling)):
            continue
        nodes.append(sibling)
    return nodes


def _extract_links(node: Tag, source_url: str) -> list[dict[str, str]]:
    links = []
    for anchor in node.select("a[href]"):
        text = normalize_ws(anchor.get_text(" ", strip=True))
        href = anchor.get("href", "").strip()
        if text and href and "timetable" not in href.lower() and "расписание" not in text.lower():
            links.append({"text": text, "url": urljoin(source_url, href)})
    return links


def _nodes_raw_text(nodes: list) -> str:
    chunks = []
    for node in nodes:
        text = normalize_ws(node.get_text(" ", strip=True) if isinstance(node, Tag) else str(node))
        if text:
            chunks.append(text)
    return "\n".join(chunks)


def _nodes_paragraphs(nodes: list) -> list[str]:
    paragraphs = []
    for node in nodes:
        if isinstance(node, Tag):
            paragraphs.extend(normalize_ws(p.get_text(" ", strip=True)) for p in node.select("p"))
    return [p for p in paragraphs if p]


def _nodes_list_items(nodes: list) -> list[str]:
    items = []
    for node in nodes:
        if isinstance(node, Tag):
            items.extend(normalize_ws(li.get_text(" ", strip=True)) for li in node.select("li"))
    return [item for item in items if item and "расписание" not in item.lower()]


def _infer_section_type(title: str, nodes: list) -> str:
    lowered = title.lower()
    if _has_table(nodes):
        return "table"
    if _is_publications_title(lowered):
        return "publications"
    if "учебные курсы" in lowered:
        return "courses_by_year"
    if _nodes_list_items(nodes):
        return "list"
    if _nodes_paragraphs(nodes):
        return "paragraphs"
    return "generic"


def _is_publications_title(lowered_title: str) -> bool:
    return lowered_title.startswith("публикац")


def _has_table(nodes: list) -> bool:
    return any(isinstance(node, Tag) and (node.name == "table" or node.find("table")) for node in nodes)


def _parse_table(nodes: list, source_url: str) -> dict:
    for node in nodes:
        if not isinstance(node, Tag):
            continue
        table = node if node.name == "table" else node.find("table")
        if not table:
            continue
        headers = [normalize_ws(th.get_text(" ", strip=True)) for th in table.select("th")]
        rows = []
        for tr in table.select("tr"):
            cells = [normalize_ws(td.get_text(" ", strip=True)) for td in tr.select("td")]
            if cells:
                link = tr.find("a", href=True)
                rows.append({"cells": cells, "link_url": urljoin(source_url, link["href"]) if link else None})
        return {"headers": headers, "rows": rows}
    return {"headers": [], "rows": []}


def _parse_publications(title: str, nodes: list, source_url: str) -> tuple[int | None, list[dict]]:
    count_match = re.search(r"(\d+)\s*$", title)
    publications = []
    for node in nodes:
        if not isinstance(node, Tag):
            continue
        for li in node.select("li"):
            text = normalize_ws(li.get_text(" ", strip=True))
            anchor = li.find("a", href=True)
            if text:
                publications.append(
                    {
                        "title": normalize_ws(anchor.get_text(" ", strip=True)) if anchor else text,
                        "url": urljoin(source_url, anchor["href"]) if anchor else None,
                        "text": text,
                    }
                )
        if publications:
            break
    if not publications:
        publications = [{"title": line, "url": None, "text": line} for line in _nodes_raw_text(nodes).split("\n") if line]
    return int(count_match.group(1)) if count_match else None, publications


def _parse_courses(title: str, nodes: list, source_url: str) -> tuple[str | None, list[dict]]:
    year_match = re.search(r"(\d{4}/\d{4})", title)
    courses = []
    for node in nodes:
        if isinstance(node, Tag):
            for li in node.select("li"):
                anchor = li.find("a", href=True)
                course_title = normalize_ws(anchor.get_text(" ", strip=True) if anchor else li.get_text(" ", strip=True))
                if course_title:
                    courses.append({"title": course_title, "url": urljoin(source_url, anchor["href"]) if anchor else None})
    return year_match.group(1) if year_match else None, _dedupe_dicts(courses)


def _parse_year_entries(nodes: list, source_url: str) -> list[dict]:
    entries = []
    for node in nodes:
        if not isinstance(node, Tag):
            continue
        for year_node in node.select(".person-list-hangover"):
            year_match = re.search(r"(19\d{2}|20\d{2})", year_node.get_text(" ", strip=True))
            parent = year_node.parent
            if parent:
                entries.append(
                    {
                        "year": int(year_match.group(1)) if year_match else None,
                        "text": normalize_ws(parent.get_text(" ", strip=True)),
                        "links": _extract_links(parent, source_url),
                    }
                )
    return entries


def _parse_vkr_items(nodes: list) -> list[str]:
    items = []
    for node in nodes:
        if isinstance(node, Tag):
            items.extend(normalize_ws(li.get_text(" ", strip=True)) for li in node.select("li"))
    return [item for item in dict.fromkeys(items) if item]


def _normalize_publication_item(item: dict, current_author_id: str | None = None) -> dict:
    publication_id = str(item.get("id") or "").strip()
    title = _html_to_text(item.get("title"))
    year = _int_or_none(item.get("year"))
    publication_type = str(item.get("type") or "").strip() or None
    description = item.get("description") if isinstance(item.get("description"), dict) else {}
    short_description = _localized_value(description.get("short")) or _localized_value(description.get("shortLeft"))
    documents = item.get("documents") if isinstance(item.get("documents"), dict) else {}
    language = item.get("language") if isinstance(item.get("language"), dict) else {}
    annotation = _localized_text_map(item.get("annotation"))
    authors = _normalize_publication_authors(item.get("authorsByType"), current_author_id)
    citation_text = normalize_ws(str(description.get("main") or "")) or _build_publication_citation(title, authors, year)
    text = normalize_ws(" ".join(part for part in [title, str(year or ""), short_description] if part))
    return {
        "id": publication_id or None,
        "publication_id": publication_id or None,
        "title": title or publication_id,
        "year": year,
        "type": publication_type,
        "publication_type": publication_type,
        "language": normalize_ws(language.get("name")) or None,
        "status": _int_or_none(item.get("status")),
        "url": f"https://publications.hse.ru/view/{publication_id}" if publication_id else None,
        "doi_url": _document_href(documents, "DOI"),
        "other_url": _document_href(documents, "OTHER_URL"),
        "document_url": _document_href(documents, "DOCUMENT"),
        "citation_text": citation_text or None,
        "annotation": annotation,
        "description": description or None,
        "authors": authors,
        "raw_data": item,
        "text": text or title or publication_id,
    }


def _normalize_vkr_item(item: dict, source_url: str) -> dict:
    thesis_id = item.get("id")
    program = item.get("learnProgram") if isinstance(item.get("learnProgram"), dict) else {}
    org_unit = item.get("orgUnit") if isinstance(item.get("orgUnit"), dict) else {}
    supervisors = []
    for supervisor in item.get("supervisors") or []:
        if not isinstance(supervisor, dict):
            continue
        name = normalize_ws(supervisor.get("name"))
        url = normalize_ws(supervisor.get("url"))
        if name or url:
            supervisors.append({"name": name or url, "url": url or None})
    return {
        "id": thesis_id,
        "student": normalize_ws(item.get("student")),
        "title": normalize_ws(item.get("title")),
        "defense_year": item.get("year"),
        "level": normalize_ws(item.get("level")),
        "rating": item.get("rating"),
        "project_url": urljoin(source_url, f"/edu/vkr/{thesis_id}") if thesis_id else None,
        "program": normalize_ws(program.get("title")),
        "program_url": urljoin(source_url, program.get("url")) if program.get("url") else None,
        "org_unit": normalize_ws(org_unit.get("title")),
        "org_unit_url": urljoin(source_url, org_unit.get("url")) if org_unit.get("url") else None,
        "supervisors": supervisors,
        "text": normalize_ws(" ".join(str(part) for part in [item.get("student"), item.get("title"), item.get("year")] if part)),
    }


def _upsert_publications_section(sections: list[dict], publications: list[dict]) -> list[dict]:
    merged = []
    inserted = False
    for section in sections:
        if section.get("type") != "publications":
            merged.append(section)
            continue
        existing = section.get("publications") or []
        section = {
            **section,
            "publications_count": max(section.get("publications_count") or 0, len(publications)),
            "publications": _dedupe_publications([*existing, *publications]),
        }
        section["items"] = [item["text"] for item in section["publications"] if item.get("text")]
        merged.append(section)
        inserted = True
    if not inserted:
        merged.append(
            {
                "title": "Публикации и исследования",
                "slug": "publikacii_i_issledovaniya",
                "type": "publications",
                "raw_text": "",
                "paragraphs": [],
                "items": [item["text"] for item in publications if item.get("text")],
                "links": [],
                "publications_count": len(publications),
                "publications": publications,
            }
        )
    return merged


def _upsert_graduation_theses_section(sections: list[dict], theses: list[dict]) -> list[dict]:
    section = {
        "title": "Выпускные квалификационные работы студентов НИУ ВШЭ",
        "slug": "vypusknye_kvalifikacionnye_raboty_studentov_niu_vshe",
        "type": "graduation_theses",
        "raw_text": "",
        "paragraphs": [],
        "items": [item["text"] for item in theses if item.get("text")],
        "links": [{"text": item["title"], "url": item["project_url"]} for item in theses if item.get("title") and item.get("project_url")],
        "theses_count": len(theses),
        "theses": theses,
    }
    return [item for item in sections if item.get("type") != "graduation_theses"] + [section]


def _dedupe_publications(items: list[dict]) -> list[dict]:
    seen = set()
    unique = []
    for item in items:
        key = item.get("id") or item.get("url") or item.get("title")
        if key and key not in seen:
            seen.add(key)
            unique.append(item)
    return unique


def _html_to_text(value: object) -> str:
    return normalize_ws(BeautifulSoup(str(value or ""), "html.parser").get_text(" ", strip=True))


def _localized_text_map(value: object) -> dict[str, str]:
    if not isinstance(value, dict):
        return {}
    localized = {}
    for key in ("ru", "en", "publ"):
        text = _html_to_text(value.get(key))
        if text:
            localized[key] = text
    return localized


def _localized_value(value: object) -> str:
    if isinstance(value, dict):
        return normalize_ws(value.get("ru") or value.get("publ") or value.get("en"))
    return normalize_ws(str(value or ""))


def _normalize_publication_authors(value: object, current_author_id: str | None) -> list[dict]:
    if not isinstance(value, dict):
        return []
    authors = []
    for author in value.get("author") or []:
        if not isinstance(author, dict):
            continue
        title = author.get("title") if isinstance(author.get("title"), dict) else {}
        reverse_title = author.get("reverseTitle") if isinstance(author.get("reverseTitle"), dict) else {}
        author_id = normalize_ws(author.get("id"))
        href = normalize_ws(author.get("href"))
        authors.append(
            {
                "id": author_id or None,
                "href": urljoin("https://www.hse.ru", href) if href else None,
                "title_ru": _html_to_text(title.get("ru")),
                "title_en": _html_to_text(title.get("en")),
                "reverse_title_ru": _html_to_text(reverse_title.get("ru")),
                "reverse_title_en": _html_to_text(reverse_title.get("en")),
                "alt_name": normalize_ws(author.get("altName")) or None,
                "other_name": normalize_ws(author.get("otherName")) or None,
                "is_current_employee": bool(current_author_id and author_id == current_author_id),
            }
        )
    return authors


def _document_href(documents: dict, key: str) -> str | None:
    document = documents.get(key)
    if not isinstance(document, dict):
        return None
    return normalize_ws(document.get("href")) or None


def _build_publication_citation(title: str, authors: list[dict], year: int | None) -> str:
    author_names = [author.get("title_ru") or author.get("title_en") or author.get("alt_name") for author in authors]
    return normalize_ws(". ".join(part for part in [", ".join(filter(None, author_names)), title, str(year or "")] if part))


def _int_or_none(value: object) -> int | None:
    try:
        return int(value)
    except (TypeError, ValueError):
        return None


def _slugify(value: str) -> str:
    cleaned = re.sub(r"[^\w\s-]", "", value.lower(), flags=re.UNICODE)
    return re.sub(r"[-\s]+", "_", cleaned).strip("_") or "section"


def _dedupe_tabs(items: list[dict]) -> list[dict]:
    seen = set()
    unique = []
    for item in items:
        key = (item.get("title"), item.get("href"))
        if key not in seen:
            seen.add(key)
            unique.append(item)
    return unique


def _dedupe_dicts(items: list[dict]) -> list[dict]:
    seen = set()
    unique = []
    for item in items:
        key = tuple(sorted(item.items()))
        if key not in seen:
            seen.add(key)
            unique.append(item)
    return unique


def _fetch_text(
    session: Session,
    url: str,
    headers: dict[str, str],
    timeout: int,
    *,
    resource_cache=None,
    profile_key: str | None = None,
    resource_key: str,
    resource_manifest: list[dict] | None,
    method: str = "GET",
    json_payload: object | None = None,
    params: dict | None = None,
) -> str:
    if resource_cache and profile_key:
        cached = resource_cache.fetch_text(
            session,
            profile_key=profile_key,
            resource_key=resource_key,
            method=method,
            url=url,
            headers=headers,
            timeout=timeout,
            json_payload=json_payload,
            params=params,
        )
        if resource_manifest is not None:
            resource_manifest.append(
                {
                    "resource_key": resource_key,
                    "method": method,
                    "url": url,
                    "body_hash": cached.body_hash,
                    "from_cache": cached.from_cache,
                    "status_code": cached.status_code,
                }
            )
        return cached.text

    if method.upper() == "POST":
        response = session.post(url, json=json_payload, headers=headers, timeout=timeout, params=params)
    else:
        response = session.get(url, headers=headers, timeout=timeout, params=params)
    response.raise_for_status()
    text = response.text
    if resource_manifest is not None:
        resource_manifest.append(
            {
                "resource_key": resource_key,
                "method": method,
                "url": url,
                "body_hash": hashlib.sha256(text.encode("utf-8")).hexdigest(),
                "from_cache": False,
                "status_code": response.status_code,
            }
        )
    return text