import time
import requests
import pandas as pd
import gradio as gr
import os
from urllib.parse import urlparse

# =====================================================
# CONFIGURATION (HF SAFE)
# =====================================================
HASDATA_API_KEY = os.getenv("HASDATA_API_KEY")  # ✅ From Hugging Face Secrets
HASDATA_ENDPOINT = "https://api.hasdata.com/scrape/google/serp"

TARGET_DOMAIN = "rishabhsoft.com"
COUNTRY = "us"            # "us" or "in"
LANGUAGE = "en"
LOCATION = "United States" if COUNTRY == "us" else "India"

MAX_PAGES = 10            # Top 100
RESULTS_PER_PAGE = 10
SLEEP_TIME = 1

if not HASDATA_API_KEY:
    raise ValueError("HASDATA_API_KEY is missing. Add it in Hugging Face Secrets.")

# =====================================================
# HELPERS
# =====================================================
def normalize_domain(url: str) -> str:
    try:
        return urlparse(url).netloc.replace("www.", "").lower()
    except Exception:
        return ""

# =====================================================
# CORE RANK CHECK
# =====================================================
def check_domain_rank(keyword: str) -> pd.DataFrame:
    keyword = keyword.strip()
    results = []

    headers = {
        "x-api-key": HASDATA_API_KEY
    }

    for page in range(MAX_PAGES):
        start = page * RESULTS_PER_PAGE

        params = {
            "q": keyword,
            "gl": COUNTRY,
            "hl": LANGUAGE,
            "domain": "google.com",
            "location": LOCATION,
            "start": start,
            "num": RESULTS_PER_PAGE,
            "deviceType": "desktop"
        }

        response = requests.get(
            HASDATA_ENDPOINT,
            headers=headers,
            params=params,
            timeout=30
        )

        if response.status_code != 200:
            print(f"API Error [{response.status_code}]: {response.text}")
            break

        data = response.json()

        organic_results = (
            data.get("organic_results")
            or data.get("organicResults")
            or []
        )

        for idx, item in enumerate(organic_results, start=1):
            url = item.get("link") or item.get("url") or ""
            if not url:
                continue

            domain = normalize_domain(url)

            if domain.endswith(TARGET_DOMAIN):
                results.append({
                    "Keyword": keyword,
                    "Domain": f"https://www.{TARGET_DOMAIN}/",
                    "Page": page + 1,
                    "Position on Page": idx,
                    "Absolute Rank": start + idx,
                    "URL": url,
                    "Title": item.get("title")
                })

        if results:
            break

        time.sleep(SLEEP_TIME)

    if results:
        return pd.DataFrame(results)

    return pd.DataFrame([{
        "Keyword": keyword,
        "Domain": f"https://www.{TARGET_DOMAIN}/",
        "Page": "Not Found",
        "Position on Page": "Not Found",
        "Absolute Rank": "Not Found",
        "URL": None,
        "Title": "Not ranking in top 100"
    }])

# =====================================================
# BULK EXCEL HANDLER
# =====================================================
def run_bulk_excel(file):
    if file is None:
        return None, None

    df = pd.read_excel(file)

    if "keyword" not in df.columns:
        raise ValueError("Excel must contain a 'keyword' column")

    all_results = []

    for kw in df["keyword"].dropna().unique():
        all_results.append(check_domain_rank(str(kw)))

    final_df = pd.concat(all_results, ignore_index=True)

    output_file = "hasdata_keyword_ranking.xlsx"
    final_df.to_excel(output_file, index=False)

    return final_df, output_file

# =====================================================
# GRADIO UI
# =====================================================
with gr.Blocks(title="Hasdata Google Rank Checker") as demo:
    gr.Markdown("## 🔍 Google Keyword Rank Checker (Hasdata)")
    gr.Markdown(f"**Target Domain:** https://www.{TARGET_DOMAIN}/")
    gr.Markdown(f"**Country:** {COUNTRY.upper()} | **Device:** Desktop")

    excel_input = gr.File(
        label="Upload Excel (.xlsx) with 'keyword' column",
        file_types=[".xlsx"]
    )

    run_btn = gr.Button("Check Rankings")

    output_table = gr.Dataframe(
        headers=[
            "Keyword",
            "Domain",
            "Page",
            "Position on Page",
            "Absolute Rank",
            "URL",
            "Title"
        ],
        wrap=True
    )

    download_file = gr.File(label="Download Result Excel")

    run_btn.click(
        fn=run_bulk_excel,
        inputs=excel_input,
        outputs=[output_table, download_file]
    )

demo.queue()
demo.launch()