from datetime import datetime, timezone
from web.scraper import process_region_keyword, scrape_job_page
from web.db import (
    db_init,
    upsert_listing,
    upsert_job_details,
    url_to_job_id,
    upsert_user_interaction,
    db_get_all_job_urls,
    db_delete_job,
    remove_job,
)

# Import utility functions
from web.utils import (
    make_request_with_retry,
    now_iso,
)
from web.db import get_all_regions, get_all_keywords, seed_regions_keywords_from_listings


def fetch_listings():
    """Fetch job listings from all regions and keywords."""
    # We'll collect URLs discovered in this run and then remove any DB listings
    # not present in this set (treat DB as reflecting current search results).
    existing_db_urls = set(db_get_all_job_urls())
    discovered_urls = set()
    new_rows = []

    # Ensure regions/keywords master lists exist
    try:
        seed_regions_keywords_from_listings()
    except Exception:
        pass

    yield "Initializing database and seeding regions/keywords...\n"

    # Fetch listings for each region/keyword from DB
    regions = get_all_regions()
    keywords = get_all_keywords()
    total_combinations = len(regions) * len(keywords)
    processed = 0

    yield f"Found {len(regions)} regions and {len(keywords)} keywords. Processing {total_combinations} combinations...\n"

    for region in regions:
        region_name = region.get("name")
        if not region_name:
            continue
        for keyword in keywords:
            keyword_name = keyword.get("name")
            if not keyword_name:
                continue
            processed += 1
            yield f"Processing {region_name} + {keyword_name} ({processed}/{total_combinations})...\n"
            for row in process_region_keyword(region_name, keyword_name, discovered_urls):
                timestamp, region, keyword, title, pay, location, url = row
                discovered_urls.add(url)
                if url not in existing_db_urls:
                    new_rows.append(row)
                # Upsert or update listing to reflect current search result
                upsert_listing(
                    url=url,
                    region=region,
                    keyword=keyword,
                    title=title,
                    pay=pay,
                    location=location,
                    timestamp=timestamp,
                )

    # Remove stale listings: those present in DB but not discovered now.
    stale_urls = existing_db_urls - discovered_urls
    if stale_urls:
        yield f"Removing {len(stale_urls)} stale listings...\n"
        for url in stale_urls:
            try:
                jid = url_to_job_id(url)
                db_delete_job(jid)
            except Exception:
                pass

    yield f"Listing fetch complete: {len(discovered_urls)} discovered, {len(new_rows)} new, {len(stale_urls)} stale\n"
    return {"discovered": len(discovered_urls), "new": len(new_rows), "stale": len(stale_urls)}


def process_job_url(job_url: str):
    try:
        job_id = url_to_job_id(job_url)
        yield f"Fetching job page: {job_url}\n"
        content = make_request_with_retry(job_url, 1)

        if content is None:
            yield f"Failed to fetch content for {job_url}, removing from database\n"
            remove_job(job_url)
            return None

        yield f"Scraping job data from {job_url}\n"
        job_data = scrape_job_page(content, job_url)
        if job_data:
            yield f"Upserting job details for {job_id}\n"
            upsert_job_details(job_data)
            upsert_user_interaction(
                job_id, seen_at=datetime.now(timezone.utc).isoformat())
            yield f"Successfully processed job {job_id}: {job_data.get('title', 'Unknown')}\n"
            return job_data
        else:
            yield f"Failed to scrape job data from {job_url}\n"
        return None
    except Exception as e:
        yield f"Error processing {job_url}: {str(e)}\n"
        return None


def scraper():
    """Main function to run the scraper."""
    yield "Starting scraper...\n"
    db_init()
    yield "Database initialized\n"

    # First, fetch current listings from search pages and make DB reflect them.
    yield "Fetching listings...\n"
    for message in fetch_listings():
        yield message

    # Finally, fetch and refresh individual job pages for current listings
    job_urls = db_get_all_job_urls()
    yield f"Processing {len(job_urls)} job pages...\n"

    for i, url in enumerate(job_urls, 1):
        yield f"\n--- Processing job {i}/{len(job_urls)} ---\n"
        for message in process_job_url(url):
            yield message

    yield "\nScraping completed successfully!\n"


if __name__ == "__main__":
    scraper()