417 lines
15 KiB
Python
417 lines
15 KiB
Python
# -*- coding: utf-8 -*-
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import asyncio
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import csv
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import os
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import random
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import aiohttp
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import time
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import sys
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from bs4 import BeautifulSoup
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import re
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import aiofiles
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import urllib.parse
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import argparse
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from colorama import init, Fore
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from search import Bing,Baidu
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import openpyxl
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import ssl
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from tool.bing_search import BingSearcher
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from tool.csv_tool import CSVTool
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from tool.read_csv import CSVReader
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start = time.time()
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def printascii():
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# 初始化
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init()
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# 设置颜色
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print(Fore.GREEN + r'''
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____ _
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/ ___| ___ __ _ _ __ ___| |__ ___ _ __
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\___ \ / _ \/ _` | '__/ __| '_ \ / _ \ '__|
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___) | __/ (_| | | | (__| | | | __/ |
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|____/ \___|\__,_|_| \___|_| |_|\___|_|
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''' + Fore.RESET)
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# 天欣安全实验室
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def writeExcel(titles, links,ws):
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infos = list(zip(titles, links))
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for row in infos:
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ws.append(row)
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def create_sheet_and_write(wb, engine, keywords, num, title):
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ws = wb.create_sheet(title=title)
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result = engine(keywords, num)
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writeExcel(result[0], result[1], ws)
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def excel_text2url(link_url): #如果函数内部没有进行异步操作，使用 async 并不会对性能或功能产生实际影响。
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'''把一个网址字符串转换为 Excel公式，使其可以点击直接转跳'''
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return f'=HYPERLINK("{link_url}","{link_url}")'
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# 遍历所有工作表，并将第二列的所有数据传递给 excel_text2url 函数重新赋值
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def update_hyperlinks(wb):
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for sheet in wb.worksheets: # 遍历每一个工作表
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for row in sheet.iter_rows(min_row=1, max_row=sheet.max_row, min_col=2, max_col=2): # 遍历第二列
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for cell in row:
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if cell.value: # 检查单元格是否有内容
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cell.value = excel_text2url(cell.value) # 将网址转换为超链接公式
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else:
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break
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def commend():
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parser = argparse.ArgumentParser(prog="Searcher", description='此工具用于对百度、必应和谷歌搜索的协程爬取--天欣安全实验室', usage='please read -h')
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parser.add_argument("-k", type=str, help="搜索的关键词", nargs='+')
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# 添加一个positional arguments，叫a,读取类型为int（默认是字符串）
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parser.add_argument("-p", type=str, help="需要搜索页数,默认为5,支持范围搜索，例如搜索从第2页到第五页的参数为 2:5", default='5')
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parser.add_argument("-m", type=str, help="使用的搜索引擎:百度:bd,必应:bin,谷歌:goo 不填写默认使用全部", default='all',nargs='+')
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# parser.add_argument("-t", '--task', type=int, help="设置的线程,默认为8", default=8)
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parser.exit_on_error = False
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args = parser.parse_args()
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if len(sys.argv) == 1:
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printascii()
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parser.print_help()
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sys.exit()
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return args
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def search_company_info(company_name_key, addon_args, num):
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search_key = company_name_key.strip() + " " + addon_args
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search_key = search_key.strip()
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result = Bing.bing_main(search_key, num)
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# for 循环 遍历 result[0] 和 result[1]
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return result
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# for i in range(len(result[0])):
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# title= result[0][i]
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# url = result[1][i]
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# print(f"必应搜索爬取结果为,title:{title}, url:{url}")
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# if re.match(r"^https://aiqicha.baidu.com/company_detail_.*|https://www.qcc.com/firm/.*|https://www.tianyancha.com/company/.*", url):
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# data_list.append({"title":title, "url":url})
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# return data_list
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def filter_company_sites(urls):
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# urls https://www.tianyancha.com/company/5226478758
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# url:https://aiqicha.baidu.com/company_detail_26602790857925
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# url:https://www.qcc.com/firm/05b449eb5cc417d0f97c14104051f5c0.html
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# 匹配 前缀https://aiqicha.baidu.com/company_detail_*,https://www.qcc.com/firm/*.html,https://www.tianyancha.com/company/5226478758*
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filtered_urls = [url for url in urls if re.match(r"^https://aiqicha.baidu.com/company_detail_.*|https://www.qcc.com/firm/.*|https://www.tianyancha.com/company/.*", url)]
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return filtered_urls
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def filter_aiqicha_qcc(search_result, company_name_, with_not_match = False):
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datas = []
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for i in range(len(search_result)):
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data_node = search_result[i]
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title = data_node['title']
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url = data_node['url']
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print(f"必应搜索爬取结果为,title:{title}, url:{url}")
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# 判断title是否包含 company_name_
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# if re.match(
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# r"^https://aiqicha.baidu.com/company_detail_.*|https://www.qcc.com/firm/.*|https://www.tianyancha.com/company/.*",
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# url) and title.find(company_name_) != -1:
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if title.find(company_name_) != -1 or with_not_match:
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web_site_type = None
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if re.match(r"^https://aiqicha.baidu.com/company_detail_.*", url):
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web_site_type = "aiqicha"
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elif re.match(r"^https://www.tianyancha.com/company/.*", url):
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web_site_type = "tianyancha"
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elif re.match(r"^https://www.qcc.com/firm/.*", url):
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web_site_type = "qcc"
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if web_site_type is not None:
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data_node['web_site_type'] = web_site_type
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data_node['company_name'] = company_name_
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datas.append(data_node)
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return datas
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def search_one_company(company_name_arg, num):
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keywords = company_name_arg
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# for key in keyword:
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# keywords = keywords + key + " "
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keywords = keywords.strip()
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print(f"---==您搜索的关键词为:{keywords}")
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wb = openpyxl.Workbook()
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# 删除默认创建的工作表（现在名为 "数据表1"）
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wb.remove(wb['Sheet'])
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printascii()
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pattern = r"[\\/:\*\?\"<>|]"
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keyword = re.sub(pattern, "", keywords)
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create_sheet_and_write(wb, Bing.bing_main, keywords, num, "必应爬取结果")
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create_sheet_and_write(wb, Baidu.baidu_main, keywords, num, "百度爬取结果")
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# 将所有url变为超链接,点击即可打开转跳
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update_hyperlinks(wb)
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wb.save(f'./{keyword}-{company_name_arg}.xlsx')
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print(Fore.GREEN + '总任务结束!' + Fore.RESET)
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end = time.time()
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print(Fore.RED + f'脚本总时间: {end - start:.2f}')
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def save_to_csv(filter_list):
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if filter_list is None or len(filter_list) == 0:
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print('filter_list is None or len(filter_list) == 0, 没有数据可写入')
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return False
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"""
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将结果追加写入csv文件中
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Args:
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filter_list: 需要写入的数据列表
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"""
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csv_file = 'company_search_result_data.csv'
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headers = ['title', 'url', 'web_site_type', 'request_url', 'company_name', 'create_time']
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# 判断文件是否存在，不存在则创建并写入列头
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file_exists = os.path.exists(csv_file)
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# 读取现有数据，用于判断重复项
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existing_data = set()
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if file_exists:
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with open(csv_file, 'r', encoding='utf-8') as f:
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reader_ins = csv.reader(f)
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header_skipped = False
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for row in reader_ins:
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if not header_skipped:
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header_skipped = True
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continue
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if len(row) >= 5: # 确保行数据完整
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company_name = row[4] # company_name在第5列(索引4)
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web_site_type = row[2] if len(row) > 2 else "" # web_site_type在第3列(索引2)
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existing_data.add((company_name, web_site_type))
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# 写入数据
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with open(csv_file, 'a', encoding='utf-8', newline='') as f:
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writer = csv.writer(f)
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# 如果文件不存在，写入列头
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if not file_exists:
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writer.writerow(headers)
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# 追加写入数据，去重处理
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for data_node in filter_list:
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company_name = data_node.get('company_name', '')
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web_site_type = data_node.get('web_site_type', '')
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# 判断是否已存在相同的company_name和web_site_type组合
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if (company_name, web_site_type) not in existing_data:
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# 创建时间格式化
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create_time = time.strftime("%Y-%m-%d %H:%M:%S", time.localtime())
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# 写入数据行
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row_data = [
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data_node.get('title', ''),
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data_node.get('url', ''),
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web_site_type,
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data_node.get('request_url', ''),
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company_name,
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create_time
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]
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writer.writerow(row_data)
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# 添加到已存在数据集合中，避免本次写入中的重复
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existing_data.add((company_name, web_site_type))
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print(f"写入数据成功,title:{data_node.get('title', '')}, "
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f"url:{data_node.get('url', '')}, "
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f"web_site_type:{web_site_type}, "
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f"request_url:{data_node.get('request_url', '')}, "
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f"company_name:{company_name}, "
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f"create_time:{create_time}")
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def check_company_exists(company_names, type_list):
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"""
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读取 company_search_result_data.csv 数据，检查指定的公司名称和类型是否存在
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Args:
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company_names (list): 公司名称列表
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type_list (list): 类型列表
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Returns:
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list: 包含公司名称和存在状态的字典列表
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格式: [{"company_name": "公司名", "exists": True/False}, ...]
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"""
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csv_file = 'company_search_result_data.csv'
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result = []
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# 初始化所有公司为不存在状态
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for company_name_item in company_names:
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result.append({
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"company_name": company_name_item,
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"exists": False
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})
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# 如果文件不存在，直接返回初始化结果
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if not os.path.exists(csv_file):
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return result
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# 读取CSV文件中的现有数据
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existing_combinations = set() # 存储(公司名, 类型)组合
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try:
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with open(csv_file, 'r', encoding='utf-8') as f:
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reader = csv.reader(f)
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header_skipped = False
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for row in reader:
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if not header_skipped:
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header_skipped = True
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continue
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# 确保行数据完整
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if len(row) >= 5:
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company_name_item = row[4] # company_name在第5列(索引4)
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web_site_type = row[2] if len(row) > 2 else "" # web_site_type在第3列(索引2)
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# 添加到现有组合集合中
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existing_combinations.add((company_name_item, web_site_type))
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except Exception as e:
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print(f"读取CSV文件时出错: {e}")
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return result
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# 检查每个公司是否存在于指定的类型中
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for item in result:
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company_name_item = item["company_name"]
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exists = False
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# 如果type_list为空，检查公司是否存在任何类型中
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if not type_list:
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for existing_company, _ in existing_combinations:
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if existing_company == company_name_item:
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exists = True
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break
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else:
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# 检查公司是否存在于指定的类型中
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for web_site_type in type_list:
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if (company_name_item, web_site_type) in existing_combinations:
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exists = True
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break
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item["exists"] = exists
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return result
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if __name__ == '__main__':
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reader = CSVReader('data.csv')
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company_names = reader.read_column(0, has_header=False)
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print("所有数据:", company_names)
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# 检查已存在的公司
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type_list = ["aiqicha", "qcc", "tianyancha"]
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check_result = check_company_exists(company_names, type_list)
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print("检查结果:", check_result)
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i = 1
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# 方法2: 使用上下文管理器
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with BingSearcher() as searcher:
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# 创建CSV工具实例
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csv_tool = CSVTool(
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csv_file_name='company_search_bing_data.csv',
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headers=['title', 'url', 'web_site_type', 'request_url', 'company_name', 'create_time']
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)
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# 查询所有数据
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all_data = csv_tool.get_all_data()
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print("所有数据:", all_data)
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# 查询所有数据
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all_data = csv_tool.get_all_data()
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print("所有数据:", all_data)
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# 初始化所有公司为不存在状态
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company_names_saved_set = set()
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for company_name_item in all_data:
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company_names_saved_set.add(company_name_item["company_name"])
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for company_name in company_names:
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# 如果公司已存在，跳过处理
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if company_name in company_names_saved_set:
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print(f"公司 {company_name} 已存在，跳过处理")
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continue
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# if company_exists:
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# print(f"公司 {company_name} 已存在，跳过处理")
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# continue
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print(f"正在处理第 {i} 个公司: {company_name}")
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addon_args = " 爱企查|企查查"
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data_list = searcher.search(company_name+" "+addon_args, 1)
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filter_list = filter_aiqicha_qcc(data_list, company_name)
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print(company_name, "filter_list:", filter_list)
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if len(filter_list) <= 0:
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print("没有数据 filter_list is empty. " + company_name)
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filter_list_with_not_match = filter_aiqicha_qcc(data_list, company_name, with_not_match=True)
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# 创建CSV工具实例
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csv_tool = CSVTool(
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csv_file_name='company_search_filter_is_none_data.csv',
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headers=['company_name','title', 'web_site_type','url', 'request_url', 'create_time']
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)
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# 保存数据，指定去重字段
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csv_tool.save_data(filter_list_with_not_match, unique_titles=['company_name', 'title','url','web_site_type'])
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continue
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else:
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# 创建CSV工具实例
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csv_tool = CSVTool(
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csv_file_name='company_search_bing_data.csv',
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headers=['company_name','title', 'web_site_type','url', 'request_url', 'create_time']
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)
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# 保存数据，指定去重字段
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csv_tool.save_data(filter_list,
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unique_titles=['company_name', 'web_site_type'])
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# save_to_csv(filter_list)
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# i = i + 1
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# if i > 3:
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# print("结束循环")
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# break
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# results2 = searcher.search("腾讯", 1)
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# results3 = searcher.search("百度", 1)
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sleep_time = 5
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sleep_time += random.randint(3, 10)
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time.sleep(sleep_time)
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pass
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pass
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if True:
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print("exit")
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exit(0)
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i = 1
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for company_name_ele in check_result:
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company_name = company_name_ele["company_name"]
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company_exists = company_name_ele["exists"]
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# 如果公司已存在，跳过处理
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if company_exists:
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print(f"公司 {company_name} 已存在，跳过处理")
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continue
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sleep_time = 5
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sleep_time += random.randint(3, 10)
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time.sleep(sleep_time)
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addon_args = " 爱企查|企查查"
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data_list = search_company_info(company_name, addon_args, '1')
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filter_list = filter_aiqicha_qcc(data_list, company_name)
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print("filter_list:",filter_list)
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save_to_csv(filter_list)
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if len(filter_list)<= 0:
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print("没有数据 filter_list is empty. "+company_name)
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continue
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i=i+1
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if i > 100:
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break
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