131 lines
3.8 KiB
Python
131 lines
3.8 KiB
Python
import datetime
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from Requests_Except import *
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import pandas as pd
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base_url = 'www.qj050.com'
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protocol = 'https'
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headers = {
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'accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,image/avif,image/webp,image/apng,*/*;q=0.8,application/signed-exchange;v=b3;q=0.7',
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'accept-language': 'zh-CN,zh;q=0.9,en;q=0.8',
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'cache-control': 'no-cache',
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'content-type': 'application/x-www-form-urlencoded',
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'origin': 'https://www.qj050.com',
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'pragma': 'no-cache',
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'priority': 'u=0, i',
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'referer': 'https://www.qj050.com/account/quick?login_type=1&ref=/?from=h5',
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'sec-ch-ua': '"Google Chrome";v="135", "Not-A.Brand";v="8", "Chromium";v="135"',
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'sec-ch-ua-mobile': '?0',
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'sec-ch-ua-platform': '"Windows"',
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'sec-fetch-dest': 'iframe',
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'sec-fetch-mode': 'navigate',
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'sec-fetch-site': 'same-origin',
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'sec-fetch-user': '?1',
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'upgrade-insecure-requests': '1',
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'user-agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/135.0.0.0 Safari/537.36',
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}
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Requests = MR(base_url, protocol, headers)
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_keyword = ""
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pd_data = {
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'resume_id': [],
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'姓名': [],
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'年龄': [],
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'生日': [],
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'工作经验': [],
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'最高学历': [],
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'婚姻状态': [],
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'电话': [],
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'意向岗位': [],
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'期望薪资': [],
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'工作性质': [],
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'求职状态': [],
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'工作地点': [],
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'工作经历1': [],
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'工作经历2': [],
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'工作经历3': [],
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'工作经历4': [],
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}
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def login():
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url = '/account/login'
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params = {
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'ref': '/?from=h5',
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}
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data = {
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'_type': '1',
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'_from': 'quick',
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'account': '真贤8888',
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'password': 'zhenxian8888',
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}
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response = Requests.post(url, params=params, data=data, autosave=True)
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response.cookies_dict()
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def get_page_for_keyword(keyword):
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global _keyword
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_keyword = keyword
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url = '/api/v1/resumes'
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params = {
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'_': str(int(time.time() * 1000 - 10000)),
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'tab': 'resume',
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'keyword': keyword,
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't': str(int(time.time() * 1000)),
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'pageSize': '100',
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'pageIndex': '1',
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'showStatus': 'true',
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}
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response = Requests.get(url, params=params)
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return response.to_Dict()
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def get_resumes_info(resumes_id):
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url = '/api/v1/resume/{}'.format(resumes_id)
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params = {
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'_': str(int(time.time() * 1000)),
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'view_type': 'resumeLibrary',
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'privacy_description': '1',
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}
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response = Requests.get(url, params=params)
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info = response.to_Dict().data
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data = {
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'resume_id': resumes_id,
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'姓名': info.name,
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'年龄': info.age,
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'生日': info.birthday,
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'工作经验': info.work_exp_value,
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'最高学历': info.edu_value,
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'婚姻状态': info.marriage_value,
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'电话': info.phone,
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'意向岗位': ','.join([item.name for item in info.infoCateforyArrObj]),
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'期望薪资': info.salaryDesc,
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'工作性质': info.work_type_value,
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'求职状态': info.job_instant_value,
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'工作地点': info.job_region_value,
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}
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for i in range(4): # 0, 1, 2, 3
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if i < len(info.works):
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work = info.works[i]
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data[f'工作经历{i + 1}'] = f"{work.company}:{work.content}"
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else:
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data[f'工作经历{i + 1}'] = ''
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return data
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def integration(keyword):
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global _keyword
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_keyword = keyword
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page = get_page_for_keyword(_keyword)
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for item in page.data.items:
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resumes_info = get_resumes_info(item.id)
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for key, value in resumes_info.items():
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pd_data[key].append(value)
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df = pd.DataFrame(pd_data)
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df.to_excel(f'{datetime.datetime.now().strftime("%Y%m%d_%H%M%S")}_{_keyword}.xlsx', index=False)
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if __name__ == '__main__':
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integration("财务")
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# get_resumes_info('36859')
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