why google search api results is NoneType object

[Amol Shivnath]

output:

  result = self.fn(*self.args, **self.kwargs)
  File "app-1.py", line 103, in run
    results.append(self.find_keyword(keyword, country))
  File "app-1.py", line 75, in find_keyword
    for i, search_item in enumerate(search_items, start=1):
TypeError: 'NoneType' object is not iterable

my code:

import undetected_chromedriver as uc
uc.install()
import sys, os
import traceback
import requests
import urllib.parse as p
import pandas as pd
import datetime
from bs4 import BeautifulSoup
import random
from selenium import webdriver
from selenium.webdriver.common.by import By
from selenium.webdriver.common.keys import Keys
from selenium.webdriver.chrome.options import Options
from time import sleep
import time
import re
import threading
import concurrent.futures
import csv
from config import *
import math
import code




date = datetime.datetime.now()
date_format = date.strftime("%d-%m-%Y, %H:%M:%S")
date_only = date.strftime("%d-%m-%Y-%H%M%S")

import logging
import sys

logger = logging.getLogger()
logger.setLevel(logging.INFO)
formatter = logging.Formatter('%(asctime)s | %(levelname)s | %(message)s',
                              '%m-%d-%Y %H:%M:%S')
file_handler = logging.FileHandler(f'logs/{date_only}.log', encoding="utf8")
file_handler.setLevel(logging.DEBUG)
file_handler.setFormatter(formatter)

logger.addHandler(file_handler)

class Process:
    def __init__(self, keywords, url):
        self.keywords = keywords
        #self.no_of_pages = no_of_pages
        self.count = 1
        self.url = url
        self.driver = None
    
        
    def find_keyword(self, keyword,country):
        
        
        for page in range(1, 11):

            print("[*] Going for page:", page)
            # calculating start
            start = (page - 1) * 10 + 1
            # make API request
            url = f"https://www.googleapis.com/customsearch/v1?key={API_KEY}&cx={SEARCH_ENGINE_ID}&q={keyword}&gl={country}&start={start}"
            
            data = requests.get(url).json()
            
            search_items = data.get("items")

            # a boolean that indicates whether `target_domain` is found
            found = False
            for i, search_item in enumerate(search_items, start=1):
                # get the page title
                title = search_item.get("title")
                # page snippet
                snippet = search_item.get("snippet")
                # alternatively, you can get the HTML snippet (bolded keywords)
                html_snippet = search_item.get("htmlSnippet")
                # extract the page url
                link = search_item.get("link")
                # extract the domain name from the URL
                domain_name = p.urlparse(link).netloc
                if domain_name.endswith(self.url):
                    # get the page rank
                    rank = i + start - 1
                    print(f"[+] {self.url} is found on rank #{rank} for keyword: '{keyword}'")
                    print("[+] Title:", title)
                    print("[+] Snippet:", snippet)
                    print("[+] URL:", link)
                    logging.info(f"link -- {link}")
                    return {'keyword': keyword, 'rank' : rank}
                    # target domain is found, exit out of the program
                else:
                    return {'keyword': keyword, 'rank' : 0}
            
    def run(self):
        results = []
        
        for keyword, country in self.keywords:
            results.append(self.find_keyword(keyword, country))
                
        return results

if __name__=="__main__":
    result = []
    df = pd.read_csv('Input/Keywords - Sheet2.csv')
    keywords = list(df['keyword'].values)
    countries = list(df['country'].values)
    kc = list(zip(keywords,countries))
    url = "vpnbrains.com"
    row = len(keywords)
    arr = []
    batch = BATCH
    batchsize = math.ceil(row/batch)
    
    for i in range(batch):
        arr.append(kc[i*batchsize:(i+1)*batchsize])
    

    with concurrent.futures.ThreadPoolExecutor() as executor:
        futures = []
        for af in arr :
            if (i+1)*batchsize > row:
                obj = Process(kc,url)
                futures.append(
                    executor.submit(
                    obj.run
                    )
                )
            else:
                obj = Process(af,url)
                futures.append(

                    executor.submit(
                    obj.run
                    )
                )
        for j in futures:
            res = j.result()
            result.extend(res)
    
    out_df = pd.DataFrame(result)
    out_df.to_csv(f'Export/{date_only}.csv', index=False)
    code.interact(local=locals())

[Shawn Wu]

what is the python version ? Generally,  It means the value of data is None. You can simply print "enumerate(search_items, start=1)" to confirm the value type.