import os
import logging
import sys
from datetime import datetime
from pathlib import Path
from dotenv import load_dotenv
from huggingface_hub import HfApi
from zoneinfo import ZoneInfo

# Import modules
from ingestion.jobstreet.jobstreet_scraper import js_scraper, get_total_pages
from ingestion.linkedin.linkedin_scraper import ld_scraper

SEARCH_TERMS = [
    "Data Engineer",
    "Data Analyst",
    "Data Scientist",
    "Machine Learning Engineer",
]

js_date_range = {
    "daily": 1,
    "weekly": 7,
    "montly": 31,
    "None": None
}

ld_date_range = {
    "daily": "r86400",
    "weekly": "r604800",
    "montly": "r2592000",
    "None": None
}

app_logger = logging.getLogger(__name__)

def upload_to_hf():
    """Sends local JSONL data and active log files to permanent HF Dataset storage"""

    token = os.environ.get("HF_TOKEN")

    if not token:
        app_logger.warning("⚠️ HF_TOKEN not found in environment variables. Skipping cloud sync.")
        return

    api = HfApi(token=token)
    repo_target = "Amin1600/Web_Scraper_Data" 
    
    app_logger.info("📦 Commencing synchronization with Hugging Face Dataset vault...")
    
    try:
        # 1. Upload your data folder contents (.jsonl files)
        if os.path.exists("data") and os.listdir("data"):
            api.upload_folder(
                folder_path="data",
                path_in_repo="job_data", # Folder name inside your dataset repo
                repo_id=repo_target,
                repo_type="dataset"
            )
            app_logger.info("🎉 Scraping data (.jsonl) successfully backed up to HF Datasets!")

        # 2. Upload your logs folder contents (.log files)
        if os.path.exists("logs") and os.listdir("logs"):
            api.upload_folder(
                folder_path="logs",
                path_in_repo="logs", # Folder name inside your dataset repo
                repo_id=repo_target,
                repo_type="dataset"
            )
            app_logger.info("🎉 System execution logs successfully backed up to HF Datasets!")

    except Exception as e:
        app_logger.error(f"❌ Failed to sync files to Hugging Face Dataset: {e}")


def job_scraper(job_title="Data Analyst", target_location="Kuala Lumpur", date_range="None", run_type="scheduled"):

    kl_timezone = ZoneInfo("Asia/Kuala_Lumpur")
    timestamp = datetime.now(kl_timezone).strftime('%d-%m-%Y, %H:%M:%S')

    if date_range == "all" or date_range is None:
        date_range = "None"

    
    if run_type == 'scheduled':
        
        app_logger.info("🚀 Scheduler successfully armed for midnight Malaysia Time.")

        app_logger.info(f"⏰ Starting Scheduled web scraper run for {job_title} job listings. {timestamp}")

        app_logger.info("🚀 Scraping jobs from Jobstreet")
        js_scraper(job_type = job_title, location = target_location, date_range = js_date_range[date_range])

        app_logger.info("🚀 Scraping jobs from Linkedin")
        ld_scraper(job_type = job_title, location = target_location, date_range = ld_date_range[date_range])

        app_logger.info("🏁 All scraping tasks completed successfully.")
        upload_to_hf()
    
    elif run_type == 'manual':
        
        app_logger.info(f"Manual run, searching for {date_range or "all"} listings.")

        app_logger.info(f"Starting web scraper run for {job_title} job listings. {timestamp}")
        app_logger.info("🚀 Scraping jobs from Jobstreet")
        js_scraper(job_type = job_title, location = target_location, date_range = js_date_range[date_range])

        app_logger.info("🚀 Scraping jobs from Linkedin")
        ld_scraper(job_type = job_title, location = target_location, date_range = ld_date_range[date_range])

        app_logger.info("🏁 All scraping tasks completed successfully.")
        upload_to_hf()

    else:
        app_logger.warning('🛑 Undetermined run type task is unable to start!')