from __future__ import annotations

import xml.etree.ElementTree as ET
from typing import Any, Dict, List

import requests

from intel.http_client import request
from intel.models import Candidate


def _text(node: ET.Element, name: str) -> str:
    child = node.find(name)
    return child.text.strip() if child is not None and child.text else ""


def fetch(system: Dict[str, Any], source: Dict[str, Any]) -> List[Candidate]:
    response = request("GET", source["url"])
    response.raise_for_status()
    root = ET.fromstring(response.content)

    keywords = {kw.lower() for kw in source.get("keywords", [])}
    items = root.findall(".//item")
    candidates: List[Candidate] = []
    for item in items[: source.get("max_items", 50)]:
        title = _text(item, "title")
        link = _text(item, "link") or source["url"]
        description = _text(item, "description")
        if keywords:
            haystack = " ".join([title, description]).lower()
            if not any(keyword in haystack for keyword in keywords):
                continue
        candidates.append(
            Candidate(
                system_id=system["system_id"],
                display_name=system["display_name"],
                category=system["category"],
                advisory_mode=source.get("advisory_mode", "core"),
                source_kind=source["kind"],
                source_name=source["name"],
                source_confidence=source["confidence"],
                source_url=link,
                title=title or f"RSS entry for {system['display_name']}",
                published_at=_text(item, "pubDate"),
                updated_at=_text(item, "pubDate"),
                summary=description,
                severity="unknown",
                references=[link],
                raw={"title": title, "link": link},
            )
        )
    return candidates