"""Webpage content fetching with caching, PDF extraction, and summarization helpers."""

import copy
import io
import ipaddress
import json
import os
import re
import logging
import socket
from datetime import datetime, timedelta
from typing import List
from urllib.parse import urljoin, urlparse

import httpx
from bs4 import BeautifulSoup

from .analytics import RateLimitError, error_logger
from .cache import (
    CONTENT_CACHE_DIR,
    content_cache_index,
    generate_cache_key,
    cleanup_cache,
)

logger = logging.getLogger(__name__)

_PRIVATE_NETWORKS = (
    ipaddress.ip_network("0.0.0.0/8"),
    ipaddress.ip_network("10.0.0.0/8"),
    ipaddress.ip_network("127.0.0.0/8"),
    ipaddress.ip_network("169.254.0.0/16"),
    ipaddress.ip_network("172.16.0.0/12"),
    ipaddress.ip_network("192.168.0.0/16"),
    ipaddress.ip_network("::1/128"),
    ipaddress.ip_network("fc00::/7"),
    ipaddress.ip_network("fe80::/10"),
)


def _is_private_address(addr: ipaddress._BaseAddress) -> bool:
    return addr.is_private or addr.is_loopback or addr.is_link_local or any(addr in net for net in _PRIVATE_NETWORKS)


def _resolve_hostname_ips(hostname: str) -> list[ipaddress._BaseAddress]:
    try:
        infos = socket.getaddrinfo(hostname, None)
    except Exception:
        return []
    out = []
    for info in infos:
        try:
            out.append(ipaddress.ip_address(info[4][0]))
        except Exception:
            continue
    return out


def _public_http_url(url: str) -> bool:
    try:
        parsed = urlparse(url)
        if parsed.scheme not in ("http", "https"):
            return False
        host = (parsed.hostname or "").strip()
        if not host:
            return False
        lower = host.lower()
        if lower in ("localhost", "metadata", "metadata.google.internal"):
            return False
        if lower.endswith((".local", ".localhost", ".internal", ".lan", ".intranet")):
            return False
        try:
            return not _is_private_address(ipaddress.ip_address(host))
        except ValueError:
            pass
        addrs = _resolve_hostname_ips(host)
        return bool(addrs) and not any(_is_private_address(a) for a in addrs)
    except Exception:
        return False


def _get_public_url(url: str, headers: dict, timeout: int, max_redirects: int = 5) -> httpx.Response:
    current = url
    for _ in range(max_redirects + 1):
        if not _public_http_url(current):
            raise httpx.RequestError("Blocked private/internal URL", request=httpx.Request("GET", current))
        response = httpx.get(current, headers=headers, timeout=timeout, follow_redirects=False)
        if response.status_code not in (301, 302, 303, 307, 308):
            return response
        location = response.headers.get("location")
        if not location:
            return response
        current = urljoin(str(response.url), location)
    raise httpx.RequestError("Too many redirects", request=httpx.Request("GET", current))

# PDF extraction (optional dependency)
try:
    from pdfminer.high_level import extract_text as pdf_extract_text
except ImportError:
    pdf_extract_text = None  # type: ignore


# ----------------------------------------------------------------------
# HTML extraction helpers
# ----------------------------------------------------------------------
def _extract_meta(soup: BeautifulSoup) -> dict:
    """Pull meta description and keywords if present."""
    description = ""
    keywords = ""
    desc_tag = soup.find("meta", attrs={"name": re.compile("description", re.I)})
    if desc_tag and desc_tag.get("content"):
        description = desc_tag["content"].strip()
    kw_tag = soup.find("meta", attrs={"name": re.compile("keywords", re.I)})
    if kw_tag and kw_tag.get("content"):
        keywords = kw_tag["content"].strip()
    return {"description": description, "keywords": keywords}


def _extract_og_image(soup: BeautifulSoup) -> str:
    """Extract the best representative image URL from meta tags.

    Only returns absolute http(s) URLs -- skips relative paths and data URIs.
    """
    candidates = []
    for prop in ("og:image", "og:image:url", "og:image:secure_url"):
        tag = soup.find("meta", attrs={"property": prop})
        if tag and tag.get("content", "").strip():
            candidates.append(tag["content"].strip())
    tag = soup.find("meta", attrs={"name": "twitter:image"})
    if tag and tag.get("content", "").strip():
        candidates.append(tag["content"].strip())
    tag = soup.find("meta", attrs={"name": "thumbnail"})
    if tag and tag.get("content", "").strip():
        candidates.append(tag["content"].strip())
    for url in candidates:
        if url.startswith(("https://", "http://")) and not url.endswith((".svg", ".ico")):
            return url
    return ""


def _extract_lists(soup: BeautifulSoup) -> List[List[str]]:
    """Return a list of lists, each inner list representing a <ul>/<ol>."""
    all_lists = []
    for lst in soup.find_all(["ul", "ol"]):
        items = [li.get_text(separator=" ", strip=True) for li in lst.find_all("li")]
        if items:
            all_lists.append(items)
    return all_lists


def _extract_tables(soup: BeautifulSoup) -> List[List[List[str]]]:
    """Return a list of tables, each table is a list of rows, each row a list of cell texts."""
    tables_data = []
    for table in soup.find_all("table"):
        rows = []
        for tr in table.find_all("tr"):
            cells = [td.get_text(separator=" ", strip=True) for td in tr.find_all(["td", "th"])]
            if cells:
                rows.append(cells)
        if rows:
            tables_data.append(rows)
    return tables_data


def _extract_code_blocks(soup: BeautifulSoup) -> List[str]:
    """Collect text from <pre> and <code> blocks."""
    blocks = []
    for tag in soup.find_all(["pre", "code"]):
        txt = tag.get_text(separator=" ", strip=True)
        if txt:
            blocks.append(txt)
    return blocks


def _detect_js_frameworks(soup: BeautifulSoup) -> bool:
    """Very naive detection of common JS frameworks."""
    js_indicators = [
        "react", "angular", "vue", "svelte", "next", "nuxt",
        "ember", "backbone", "jquery", "polymer", "mithril",
    ]
    for script in soup.find_all("script"):
        src = script.get("src", "").lower()
        if any(fr in src for fr in js_indicators):
            return True
        if script.string:
            content = script.string.lower()
            if any(fr in content for fr in js_indicators):
                return True
    if soup.find(attrs={"data-reactroot": True}) or soup.find(attrs={"ng-app": True}):
        return True
    return False


def _empty_result(url: str, error: str = "") -> dict:
    """Build a standard failure result dict."""
    return {
        "url": url,
        "title": "",
        "content": "",
        "lists": [],
        "tables": [],
        "code_blocks": [],
        "meta_description": "",
        "meta_keywords": "",
        "js_rendered": False,
        "js_message": "",
        "success": False,
        "error": error,
    }


# ----------------------------------------------------------------------
# Main content fetcher
# ----------------------------------------------------------------------
def fetch_webpage_content(url: str, timeout: int = 5, retry_attempt: int = 0) -> dict:
    """Fetch and extract meaningful content from a webpage with caching."""
    cache_key = generate_cache_key(url)
    cache_file = CONTENT_CACHE_DIR / f"{cache_key}.cache"

    # Check cache
    if cache_file.exists():
        try:
            with open(cache_file, "r", encoding="utf-8") as f:
                cached_data = json.load(f)
            timestamp = datetime.fromisoformat(cached_data["timestamp"])
            if datetime.now() - timestamp < timedelta(hours=2):
                logger.debug(f"Content cache hit for URL: {url}")
                return cached_data["data"]
            else:
                cache_file.unlink(missing_ok=True)
                content_cache_index.pop(cache_key, None)
        except Exception as e:
            logger.warning(f"Failed to read content cache for {url}: {e}")
            cache_file.unlink(missing_ok=True)
            content_cache_index.pop(cache_key, None)

    # Fetch
    try:
        headers = {
            "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36",
            "Accept": "text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8",
            "Accept-Language": "en-US,en;q=0.5",
            "Accept-Encoding": "gzip, deflate",
            "Connection": "keep-alive",
        }
        response = _get_public_url(url, headers=headers, timeout=timeout)

        if response.status_code == 429:
            raise RateLimitError(f"Rate limit hit for {url} (attempt {retry_attempt})")

        response.raise_for_status()
    except httpx.RequestError as e:
        error_logger.error(f"NetworkError fetching {url} (attempt {retry_attempt}): {e}")
        return _empty_result(url, f"NetworkError: {e}")
    except RateLimitError as e:
        error_logger.error(str(e))
        return _empty_result(url, str(e))

    # PDF handling
    content_type = response.headers.get("Content-Type", "").lower()
    if "application/pdf" in content_type or url.lower().endswith(".pdf"):
        if pdf_extract_text is None:
            logger.error("pdfminer.six is not installed; cannot extract PDF text.")
            pdf_text = ""
        else:
            try:
                pdf_bytes = io.BytesIO(response.content)
                pdf_text = pdf_extract_text(pdf_bytes)
            except Exception as e:
                logger.warning(f"PDF extraction failed for {url}: {e}")
                pdf_text = ""
        result = {
            "url": url,
            "title": os.path.basename(url),
            "content": pdf_text,
            "lists": [],
            "tables": [],
            "code_blocks": [],
            "meta_description": "",
            "meta_keywords": "",
            "js_rendered": False,
            "js_message": "",
            "success": bool(pdf_text),
            "error": "" if pdf_text else "Failed to extract PDF text",
        }
        _cache_result(cache_file, cache_key, result, url)
        return result

    # HTML handling
    try:
        soup = BeautifulSoup(response.text, "html.parser")
    except Exception as e:
        error_logger.error(f"ParseError parsing HTML from {url} (attempt {retry_attempt}): {e}")
        result = _empty_result(url, f"ParseError: {e}")
        _cache_result(cache_file, cache_key, result, url)
        return result

    title_tag = soup.find("title")
    title_text = title_tag.get_text(strip=True) if title_tag else ""
    meta_info = _extract_meta(soup)
    og_image = _extract_og_image(soup)
    js_rendered = _detect_js_frameworks(soup)
    js_message = "Page appears to be rendered by a JavaScript framework; content may be incomplete." if js_rendered else ""

    # Main textual content (heuristic): prefer semantic / "content"-classed
    # containers to skip nav/footer/boilerplate; tuned for article pages.
    main_content = ""
    content_areas = soup.find_all(
        ["main", "article", "section", "div"],
        class_=re.compile("content|main|body|article|post|entry|text", re.I),
    )
    if content_areas:
        for area in content_areas[:3]:
            main_content += area.get_text(separator=" ", strip=True) + " "
    main_content = re.sub(r"\s+", " ", main_content).strip()

    # If the heuristic finds only a tiny wrapper, fall back to body text with
    # obvious boilerplate stripped so UI/deep-research search results do not
    # look empty for app/landing pages.
    THIN_CONTENT_CHARS = 600
    if len(main_content) < THIN_CONTENT_CHARS:
        body = soup.find("body")
        if body:
            body_copy = copy.copy(body)
            for noise in body_copy.find_all(
                ["script", "style", "noscript", "template", "nav", "header", "footer", "aside"]
            ):
                noise.extract()
            body_text = re.sub(r"\s+", " ", body_copy.get_text(separator=" ", strip=True)).strip()
            if len(body_text) > len(main_content):
                main_content = body_text

    result = {
        "url": url,
        "title": title_text,
        "content": main_content,
        "lists": _extract_lists(soup),
        "tables": _extract_tables(soup),
        "code_blocks": _extract_code_blocks(soup),
        "meta_description": meta_info.get("description", ""),
        "meta_keywords": meta_info.get("keywords", ""),
        "og_image": og_image,
        "js_rendered": js_rendered,
        "js_message": js_message,
        "success": True,
        "error": "",
    }
    _cache_result(cache_file, cache_key, result, url)
    return result


def _cache_result(cache_file, cache_key: str, result: dict, url: str):
    """Write a result to the content cache."""
    try:
        cache_data = {"timestamp": datetime.now().isoformat(), "data": result}
        with open(cache_file, "w", encoding="utf-8") as f:
            json.dump(cache_data, f)
        content_cache_index[cache_key] = datetime.now()
        cleanup_cache(CONTENT_CACHE_DIR, content_cache_index, timedelta(hours=2))
    except Exception as e:
        logger.warning(f"Failed to write content cache for {url}: {e}")


# ----------------------------------------------------------------------
# Content summarization helpers
# ----------------------------------------------------------------------
def extract_key_points(text: str) -> List[str]:
    """Pull out bullet-style key points from a block of text."""
    points: List[str] = []
    bullet_pat = re.compile(r"^\s*[-*•]\s+(.*)")
    numbered_pat = re.compile(r"^\s*\d+[\.\)]\s+(.*)")
    for line in text.splitlines():
        m = bullet_pat.match(line) or numbered_pat.match(line)
        if m:
            points.append(m.group(1).strip())
    return points


def get_tldr(text: str, max_sentences: int = 3) -> str:
    """Produce a very short TL;DR by taking the first few sentences."""
    sentences = re.split(r"(?<=[.!?])\s+", text)
    selected = [s.strip() for s in sentences if s][:max_sentences]
    return " ".join(selected)


def extract_quotes(text: str) -> List[str]:
    """Return quoted excerpts that are at least 15 characters long."""
    # Backreference the opening quote so the closing quote must match it —
    # otherwise `"text'` (open double, close single) is treated as a quote.
    return [m.group(2).strip() for m in re.finditer(r'(["\'])([^"\']{15,}?)\1', text)]


def extract_statistics(text: str) -> List[str]:
    """Find numbers, percentages, dates and simple measurements."""
    # Match a comma-grouped number (1,000,000) OR a plain digit run (50000) —
    # the old `\d{1,3}(?:,\d{3})*` matched only the first 3 digits of a
    # comma-less number, and the trailing `\b` dropped a closing `%`.
    pattern = re.compile(
        r"\b(?:\d{1,3}(?:,\d{3})+|\d+)(?:\.\d+)?\s*(%|percent|‰|per cent|[a-zA-Z]+)?",
        re.IGNORECASE,
    )
    return [m.group(0).strip() for m in pattern.finditer(text)]