#!/usr/bin/env python3
"""UNIRI akademski repozitorij + znanstveni radovi."""
import sys, json, time
sys.path.insert(0, "/opt/pgz-sport/scrapers/harvesters")
from _common import (fetch, extract_text, extract_title, chunk_text,
                      upsert_facts, find_internal_links, DSN)
from urllib.parse import urlparse
import psycopg2

ACADEMIC = {
    "uniri_repozitorij":   ["https://repozitorij.uniri.hr/"],
    "portal_znanstveni":   ["https://portal.uniri.hr/"],
    "hrčak_uniri":        ["https://hrcak.srce.hr/"],
    "pfri_radovi":        ["https://repository.pfri.uniri.hr/"],
    "medri_radovi":       ["https://medri.uniri.hr/znanstveni-radovi/"],
    "tfr_radovi":         ["https://www.riteh.uniri.hr/"],
    "ffri_radovi":        ["https://www.ffri.uniri.hr/znanstveni-radovi/"],
}


def crawl(name, urls, max_pages=15):
    conn = psycopg2.connect(DSN); conn.autocommit = True
    visited = set(); queue = list(urls); facts = 0
    while queue and len(visited) < max_pages:
        url = queue.pop(0)
        if url in visited: continue
        visited.add(url)
        html, status = fetch(url, timeout=20)
        if not html or status != 200: continue
        title = extract_title(html); text = extract_text(html)
        if not text or len(text) < 300: continue
        ff = []
        if title and len(title) > 15:
            ff.append({"fact": f"[Academic] {name} - {title}", "url": url, "title": title})
        for c in chunk_text(text, 900):
            if len(c) > 150:
                ff.append({"fact": c, "url": url, "title": title})
        facts += upsert_facts(conn, ff, source_name=name,
                               category="akademski_pgz", confidence=0.90)
        base = urlparse(url).hostname
        for link in find_internal_links(html, url):
            if link not in visited and (urlparse(link).hostname or "") == base and len(queue) < 40:
                queue.append(link)
        time.sleep(0.7)
    conn.close()
    return {"name": name, "visited": len(visited), "facts": facts}


def main():
    results = []
    for name, urls in ACADEMIC.items():
        try:
            r = crawl(name, urls, max_pages=12)
            print(f"  {name:25} {r['visited']:>3}p  {r['facts']:>5}f")
            results.append(r)
        except Exception as e:
            print(f"  {name:25} FAIL: {str(e)[:60]}")
    total = sum(r.get("facts", 0) for r in results)
    print(f"=== TOTAL: {total} ===")
    print(json.dumps({"academic_count": len(results), "total_facts": total}))


if __name__ == "__main__":
    main()