#!/usr/bin/env python3
"""
arXiv RSS Aggregator — Phase 1 Proof-of-Concept
Parent: the-nexus#830
Created: 2026-04-05 by Ezra

This is a ZERO-DEPENDENCY proof-of-concept for the Deep Dive source aggregation layer.
It fetches arXiv RSS feeds for cs.AI, cs.CL, cs.LG and stores items as JSON lines.

Can run TODAY with no API keys, no GPU, no TTS decisions.
"""

import json
import xml.etree.ElementTree as ET
import urllib.request
import urllib.error
from datetime import datetime, timezone
from pathlib import Path
from typing import List, Dict, Any

# arXiv RSS feeds for target categories
FEEDS = {
    "cs.AI": "http://export.arxiv.org/rss/cs.AI",
    "cs.CL": "http://export.arxiv.org/rss/cs.CL",
    "cs.LG": "http://export.arxiv.org/rss/cs.LG",
}

# Storage paths (relative to project root)
RAW_DIR = Path("data/deepdive/raw")


def fetch_feed(category: str, url: str) -> str:
    """Fetch RSS feed with rate limit respect (1 req per 3 sec min)."""
    req = urllib.request.Request(
        url,
        headers={
            "User-Agent": "DeepDiveBot/0.1 (research aggregator; ezra@timmy.local)"
        }
    )
    try:
        with urllib.request.urlopen(req, timeout=30) as resp:
            return resp.read().decode("utf-8")
    except urllib.error.HTTPError as e:
        if e.code == 403:
            print(f"RATE LIMITED on {category}: arXiv is blocking. Wait 1 hour.")
        raise


def parse_arxiv_rss(xml_content: str, category: str) -> List[Dict[str, Any]]:
    """Parse arXiv RSS into structured items."""
    root = ET.fromstring(xml_content)
    
    # Handle RSS namespace
    ns = {"": "http://www.w3.org/2005/Atom"}  # arXiv uses Atom namespace
    
    items = []
    for entry in root.findall(".//{http://www.w3.org/2005/Atom}entry"):
        item = {
            "id": entry.findtext("{http://www.w3.org/2005/Atom}id", ""),
            "title": entry.findtext("{http://www.w3.org/2005/Atom}title", "").strip(),
            "summary": entry.findtext("{http://www.w3.org/2005/Atom}summary", "").strip(),
            "published": entry.findtext("{http://www.w3.org/2005/Atom}published", ""),
            "updated": entry.findtext("{http://www.w3.org/2005/Atom}updated", ""),
            "category": category,
            "authors": [],
            "links": [],
            "fetched_at": datetime.now(timezone.utc).isoformat(),
        }
        
        # Extract authors
        for author in entry.findall("{http://www.w3.org/2005/Atom}author"):
            name = author.findtext("{http://www.w3.org/2005/Atom}name", "")
            if name:
                item["authors"].append(name)
        
        # Extract links (PDF, abstract)
        for link in entry.findall("{http://www.w3.org/2005/Atom}link"):
            href = link.get("href", "")
            rel = link.get("rel", "")
            title = link.get("title", "")
            item["links"].append({"href": href, "rel": rel, "title": title})
        
        items.append(item)
    
    return items


def dedupe_items(items: List[Dict[str, Any]]) -> List[Dict[str, Any]]:
    """Remove duplicate papers across categories."""
    seen = set()
    unique = []
    for item in items:
        paper_id = item["id"].split("/")[-1].split("v")[0]  # Extract arXiv ID
        if paper_id not in seen:
            seen.add(paper_id)
            item["arxiv_id"] = paper_id
            unique.append(item)
    return unique


def save_items(items: List[Dict[str, Any]], output_dir: Path) -> Path:
    """Save items as JSON lines file."""
    output_dir.mkdir(parents=True, exist_ok=True)
    
    today = datetime.now(timezone.utc).strftime("%Y-%m-%d")
    output_file = output_dir / f"arxiv-{today}.jsonl"
    
    with open(output_file, "w") as f:
        for item in items:
            f.write(json.dumps(item, ensure_ascii=False) + "\n")
    
    return output_file


def load_existing_ids(output_dir: Path) -> set:
    """Load existing arXiv IDs to prevent re-fetching."""
    existing = set()
    if not output_dir.exists():
        return existing
    
    for f in output_dir.glob("arxiv-*.jsonl"):
        with open(f) as fp:
            for line in fp:
                try:
                    item = json.loads(line)
                    existing.add(item.get("arxiv_id", ""))
                except json.JSONDecodeError:
                    continue
    return existing


def main():
    """Run daily aggregation."""
    print("Deep Dive — Phase 1: arXiv Aggregation")
    print("=" * 50)
    
    RAW_DIR.mkdir(parents=True, exist_ok=True)
    existing_ids = load_existing_ids(RAW_DIR)
    
    all_items = []
    
    for category, url in FEEDS.items():
        print(f"\nFetching {category}...")
        try:
            # Respect arXiv rate limits (be polite)
            import time
            time.sleep(3)  # 1 req per 3 seconds minimum
            
            xml = fetch_feed(category, url)
            items = parse_arxiv_rss(xml, category)
            
            # Filter existing
            new_items = [i for i in items if i.get("arxiv_id") not in existing_ids]
            
            print(f"  Found {len(items)} items, {len(new_items)} new")
            all_items.extend(new_items)
            
        except Exception as e:
            print(f"  ERROR: {e}")
    
    # Deduplicate across categories
    unique_items = dedupe_items(all_items)
    
    # Save
    if unique_items:
        output_file = save_items(unique_items, RAW_DIR)
        print(f"\n✅ Saved {len(unique_items)} items to {output_file}")
    else:
        print("\n⚠️ No new items found")
    
    return len(unique_items)


if __name__ == "__main__":
    count = main()
    exit(0 if count >= 0 else 1)