File size: 4,831 Bytes
a60ecc7 10e43ba e80ddde a60ecc7 10e43ba e80ddde 10e43ba e80ddde 10e43ba a60ecc7 10e43ba e80ddde 10e43ba e80ddde 10e43ba e80ddde 10e43ba a60ecc7 f7f4da3 10e43ba f7f4da3 a60ecc7 10e43ba a60ecc7 10e43ba a60ecc7 a92c739 10e43ba a92c739 f7f4da3 10e43ba a60ecc7 f7f4da3 a60ecc7 10e43ba a60ecc7 10e43ba a60ecc7 10e43ba a60ecc7 10e43ba a60ecc7 10e43ba a60ecc7 10e43ba a60ecc7 10e43ba a60ecc7 10e43ba a60ecc7 10e43ba a60ecc7 10e43ba a60ecc7 10e43ba a60ecc7 10e43ba a60ecc7 10e43ba a60ecc7 10e43ba a60ecc7 10e43ba a60ecc7 10e43ba a60ecc7 10e43ba a60ecc7 10e43ba a60ecc7 10e43ba a60ecc7 10e43ba f7f4da3 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 | 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()
|