import time
import pandas as pd
from typing import List, Dict, Any

def run_jobspy_scrapes() -> List[Dict[Any, Any]]:
    """
    Executes JobSpy searches across nationwide US hubs and remote roles
    covering major industries: Tech, Finance, Healthcare, Retail, Trades, etc.
    """
    collected_jobs = []

    try:
        from jobspy import scrape_jobs
    except ImportError:
        print("[JobSpy] python-jobspy is not installed. Skipping JobSpy runner.")
        return []

    # Target key employment hubs across US states
    us_regions = [
        ("New York, NY", ["Finance", "Software Engineer", "Marketing", "Data Analyst"]),
        ("Austin, TX", ["Software Engineer", "Project Manager", "Customer Support"]),
        ("San Francisco, CA", ["AI Engineer", "Product Manager", "DevOps"]),
        ("Chicago, IL", ["Operations", "Healthcare", "Logistics", "Accountant"]),
        ("Atlanta, GA", ["IT Support", "Sales", "Supply Chain", "Administrative"]),
        ("Seattle, WA", ["Cloud Architect", "Software Developer", "Data Scientist"]),
        ("Boston, MA", ["Biotech", "Software Engineer", "Healthcare"]),
        ("Denver, CO", ["Customer Success", "Cybersecurity", "Engineering"]),
        ("Connecticut", ["Healthcare", "Finance", "Insurance", "Software", "Engineering"])
    ]

    # Nationwide Remote queries
    remote_queries = [
        "Software Engineer", "Full Stack Developer", "Data Analyst", "Product Manager",
        "Customer Support", "Administrative Assistant", "IT Support Specialist",
        "DevOps Engineer", "Account Executive", "Marketing Manager", "UX Designer"
    ]

    print("[JobSpy] Starting Nationwide Regional Scrapes...")
    for loc, queries in us_regions:
        for query in queries:
            try:
                print(f"[JobSpy] Searching {loc}: '{query}'")
                jobs_df = scrape_jobs(
                    site_name=["indeed", "zip_recruiter"],
                    search_term=query,
                    location=loc,
                    results_wanted=35,
                    hours_old=72,
                    country_indeed="USA",
                    is_remote=False
                )

                if isinstance(jobs_df, pd.DataFrame) and not jobs_df.empty:
                    for idx, row in jobs_df.iterrows():
                        job_url = str(row.get("job_url", "") or row.get("job_url_direct", ""))
                        if not job_url or job_url == "nan":
                            continue
                        
                        loc_val = str(row.get("location", loc) or loc)
                        if loc_val == "nan":
                            loc_val = loc

                        collected_jobs.append({
                            "title": str(row.get("title", "Untitled")),
                            "company": str(row.get("company", "Unknown")),
                            "location": loc_val,
                            "is_remote": False,
                            "description": str(row.get("description", "") or "No description provided."),
                            "salary_min": float(row.get("min_amount")) if pd.notnull(row.get("min_amount")) else None,
                            "salary_max": float(row.get("max_amount")) if pd.notnull(row.get("max_amount")) else None,
                            "job_url": job_url,
                            "source": str(row.get("site", "jobspy")),
                            "date_posted": str(row.get("date_posted")) if pd.notnull(row.get("date_posted")) else None
                        })
                time.sleep(1.5)
            except Exception as e:
                print(f"[JobSpy Warning] Search '{query}' in '{loc}' failed: {e}")

    print("[JobSpy] Starting US Nationwide Remote Scrapes...")
    for query in remote_queries:
        try:
            print(f"[JobSpy] Searching US Remote: '{query}'")
            jobs_df = scrape_jobs(
                site_name=["indeed", "zip_recruiter"],
                search_term=query,
                results_wanted=35,
                hours_old=72,
                country_indeed="USA",
                is_remote=True
            )

            if isinstance(jobs_df, pd.DataFrame) and not jobs_df.empty:
                for idx, row in jobs_df.iterrows():
                    job_url = str(row.get("job_url", "") or row.get("job_url_direct", ""))
                    if not job_url or job_url == "nan":
                        continue

                    collected_jobs.append({
                        "title": str(row.get("title", "Untitled")),
                        "company": str(row.get("company", "Unknown")),
                        "location": "Remote, USA",
                        "is_remote": True,
                        "description": str(row.get("description", "") or "No description provided."),
                        "salary_min": float(row.get("min_amount")) if pd.notnull(row.get("min_amount")) else None,
                        "salary_max": float(row.get("max_amount")) if pd.notnull(row.get("max_amount")) else None,
                        "job_url": job_url,
                        "source": str(row.get("site", "jobspy")),
                        "date_posted": str(row.get("date_posted")) if pd.notnull(row.get("date_posted")) else None
                    })
            time.sleep(1.5)
        except Exception as e:
            print(f"[JobSpy Warning] Remote search '{query}' failed: {e}")

    print(f"[JobSpy] Finished. Total jobs parsed: {len(collected_jobs)}")
    return collected_jobs