import json
import re

import httpx
from bs4 import BeautifulSoup

from app.config import settings
from app.models import Job
from app.ral import detect_subject, detect_work_type, extract_salary, hide_salary


def _text(el) -> str:
    return el.get_text(" ", strip=True) if el else ""


def _from_ld_json(data: dict) -> dict:
    title = data.get("title") or ""
    description = BeautifulSoup(data.get("description") or "", "lxml").get_text(" ", strip=True)
    org = data.get("hiringOrganization") or {}
    company = org.get("name") if isinstance(org, dict) else ""
    loc = data.get("jobLocation") or {}
    if isinstance(loc, list) and loc:
        loc = loc[0]
    location = ""
    if isinstance(loc, dict):
        address = loc.get("address") or {}
        if isinstance(address, dict):
            location = address.get("addressLocality") or address.get("addressRegion") or ""
    extracted = {"ral_min": None, "ral_max": None, "ral_exact": None}
    salary = data.get("baseSalary") or {}
    value = salary.get("value") if isinstance(salary, dict) else {}
    if isinstance(value, dict):
        try:
            if value.get("value"):
                extracted["ral_exact"] = int(float(str(value["value"]).replace(",", "")))
            if value.get("minValue"):
                extracted["ral_min"] = int(float(str(value["minValue"]).replace(",", "")))
            if value.get("maxValue"):
                extracted["ral_max"] = int(float(str(value["maxValue"]).replace(",", "")))
        except (TypeError, ValueError):
            pass
    return {
        "title": title,
        "description": description,
        "company": company or "",
        "location": location or "",
        **extracted,
    }


def parse_job_html(html: str, url: str) -> dict:
    soup = BeautifulSoup(html, "lxml")
    title = _text(soup.select_one("h1")) or _text(soup.select_one(".top-card-layout__title"))
    company = _text(soup.select_one(".topcard__org-name-link")) or _text(
        soup.select_one(".top-card-layout__card .topcard__flavor")
    )
    location = _text(soup.select_one(".topcard__flavor--bullet"))
    description = _text(soup.select_one(".show-more-less-html__markup")) or _text(
        soup.select_one(".description__text")
    )
    extracted = {"ral_min": None, "ral_max": None, "ral_exact": None}

    for script in soup.select('script[type="application/ld+json"]'):
        try:
            data = json.loads(script.text)
        except json.JSONDecodeError:
            continue
        if isinstance(data, list):
            data = next(
                (item for item in data if isinstance(item, dict) and item.get("@type") == "JobPosting"),
                {},
            )
        if isinstance(data, dict) and data.get("@type") == "JobPosting":
            parsed = _from_ld_json(data)
            title = title or parsed["title"]
            description = description or parsed["description"]
            company = company or parsed["company"]
            location = location or parsed["location"]
            extracted = {k: parsed[k] for k in ("ral_min", "ral_max", "ral_exact")}
            break

    if not title:
        og = soup.select_one('meta[property="og:title"]')
        title = og["content"] if og and og.get("content") else "LinkedIn job"

    blob = f"{title} {company} {description}"
    if not any(extracted.values()):
        extracted = extract_salary(blob)

    extra_bits = []
    if location:
        extra_bits.append(f"Location: {location}")
    extra_bits.extend(_text(el) for el in soup.select(".description__job-criteria-item") if _text(el))

    has_salary = bool(extracted.get("ral_exact") or extracted.get("ral_min"))
    spread = 0
    if extracted.get("ral_max") and extracted.get("ral_min"):
        spread = extracted["ral_max"] - extracted["ral_min"]

    fields = {c.name for c in Job.__table__.columns}
    payload = {
        "linkedin_url": url,
        "title": (title or "LinkedIn job")[:300],
        "company": (company or "Unknown company")[:200],
        "location": (location or "")[:200],
        "description": description or "",
        "description_clean": hide_salary(description or ""),
        "extra_info": " | ".join(extra_bits)[:500],
        "subject": detect_subject(title or "", description or ""),
        "work_type": detect_work_type(blob),
        "difficulty": 2 if spread > 15000 else 1,
        "source": "linkedin",
        "status": "ready" if has_salary else "needs_salary",
        "fetch_error": "" if has_salary else "Salary not found; edit in admin",
        **extracted,
    }
    return {k: v for k, v in payload.items() if k in fields}


async def fetch_linkedin_job(url: str) -> dict:
    if "linkedin.com" not in url:
        raise ValueError("Only LinkedIn job URLs are supported")
    headers = {
        "User-Agent": settings.linkedin_user_agent,
        "Accept-Language": "en-US,en;q=0.9,it;q=0.8",
        "Accept": "text/html,application/xhtml+xml",
    }
    async with httpx.AsyncClient(follow_redirects=True, timeout=25.0, headers=headers) as client:
        response = await client.get(url)
        response.raise_for_status()
        if "authwall" in str(response.url):
            raise RuntimeError("LinkedIn showed a login wall for this URL")
        html = response.text
        if "/jobs/view/" in url and "JobPosting" not in html:
            guest = url.split("?")[0]
            response = await client.get(guest)
            html = response.text
    parsed = parse_job_html(html, url)
    if not parsed.get("description") and not parsed.get("title"):
        raise RuntimeError("Could not parse job posting from LinkedIn page")
    return parsed