def get_name(input_data):
count = 0
while count < len(input_data):
all_person_data_list = []
try:
for i in range(count, len(input_data)):
print('当前进度：%s / %s' % (i + 1, len(input_data)))
url = base_url % input_data[i][1]
author_info = requests.get(url=url,
proxies=proxies,
headers=headers).json()
author_name = author_info['search-results']['entry'][0]['preferred-name']['surname'] + ' ' + \
author_info['search-results']['entry'][0]['preferred-name'].get('initials', '')
all_person_data_list.append(
[input_data[i][0], input_data[i][1],
author_name.strip()])
count = len(input_data)
# 出现错误时，从错误处中断，再从该处开始
except Exception as err:
print('ERROR:%s' % err)
count = i
if all_person_data_list:
result_df = pd.DataFrame(
data=all_person_data_list,
columns=['person_id', 'scopus_id', 'name'])
write2sql([['scopus_author_name', result_df]])
def get_cite_data(input_data):
count = 0
while count < len(input_data):
result_df_list = []
# 启动浏览器并获取cookies
driver = start_driver()
cookies = get_cookies(driver)
driver.close()
try:
for i in range(count, len(input_data)):
print('当前进度：%s / %s' % (i + 1, len(input_data)))
cite_journal_list = []
cite_journal_id_list = []
get_page_url = base_url % (input_data[i][0], str(1))
page_info = requests.get(get_page_url,
proxies=proxies,
headers=headers,
timeout=300,
cookies=cookies).json()
cite_journal_list += [k['srctitle'] for k in page_info['docs']]
cite_journal_id_list += [k['srcid'] for k in page_info['docs']]
for j in range(2, int(page_info['Pages']) + 1):
url = base_url % (input_data[i][0], str(j))
cite_info = requests.get(url,
proxies=proxies,
headers=headers,
timeout=300,
cookies=cookies)
cite_info_dict = cite_info.json()
cite_journal_list += [
k['srctitle'] for k in cite_info_dict['docs']
]
cite_journal_id_list += [
k['srcid'] for k in cite_info_dict['docs']
]
cite_df_temp = pd.DataFrame(
data={
'cite_journal': cite_journal_list,
'cite_journal_id': cite_journal_id_list
})
cite_df_temp['cite_num'] = 1
cite_journal_data = cite_df_temp.groupby(
by=['cite_journal',
'cite_journal_id'], as_index=False).sum()
cite_journal_data['scopus_journal_id'] = input_data[i][0]
result_df_list.append(cite_journal_data)
count = len(input_data)
# 出现错误时，从错误处中断，再从该处开始
except Exception as err:
print('ERROR:%s' % err)
count = i
if result_df_list:
all_data = pd.concat(result_df_list)
write2sql([['scopus_cite_data0810', all_data]])
def get_doc_data(input_data, school, value):
headers['content-type'] = 'application/json'
post_url = post_url_base % value[1]
if school == 'Chinese Academy of Medical Sciences - Peking Union Medical College':
del post_data['filters']['orgtype']
count = 0
while count < len(input_data):
result_df_list = []
try:
session = requests.session()
session.post(url=login_url,
data=login_data,
headers=headers_login,
timeout=300)
for i in range(count, len(input_data)):
print('当前进度：%s / %s' % (i + 1, len(input_data)))
for year in range(2015, 2020):
post_data['filters']['sbjname']['is'] = input_data[i]
post_data['filters']['period']['is'] = [year, year]
doc_data = session.post(url=post_url,
data=json.dumps(post_data),
headers=headers,
timeout=300).json()
if doc_data['items']:
for item in doc_data['items']:
item['doc_num'] = item['jifdocsq1']['value']
del item['jifdocsq1']
del item['wosDocuments']
data_df = pd.DataFrame(data=doc_data['items'])
data_df['year'] = year
data_df['category_id'] = input_data[i][:4]
data_df['category_name'] = input_data[i][5:]
result_df_list.append(data_df)
count = len(input_data)
session.close()
# 出现错误时，从错误处中断，再从该处开始
except Exception as err:
print('ERROR:%s' % err)
session.close()
count = i
if result_df_list:
all_data_df = pd.concat(result_df_list)
all_data_df = all_data_df.loc[all_data_df['orgName'] == value[0]]
all_data_df['orgName'] = school
write2sql([['wos_doc_data_copy', all_data_df]])
def get_article(input_data):
count = 0
while count < len(input_data):
all_person_data_list = []
try:
for i in range(count, len(input_data)):
print('当前进度：%s / %s' % (i + 1, len(input_data)))
for j in range(1000):
url = base_url.format(input_data[i][1], input_data[i][2],
str(j * 25))
author_article_info = requests.get(url=url,
proxies=proxies,
headers=headers).json()
if 'service-error' in author_article_info:
print(input_data[i][2])
break
if 'entry' not in author_article_info['search-results']:
break
if 'error' in author_article_info['search-results'][
'entry'][0]:
break
for article_dict in author_article_info['search-results'][
'entry']:
doi = article_dict.get('prism:doi', '')
eid = article_dict.get('eid', '')
scopus_article_id = article_dict['dc:identifier'][10:]
publish_year = article_dict.get('prism:coverDate', '')
all_person_data_list.append([
input_data[i][0], input_data[i][1], doi,
publish_year, eid, scopus_article_id
])
count = len(input_data)
# 出现错误时，从错误处中断，再从该处开始
except Exception as err:
print('ERROR:%s' % err)
count = i
if all_person_data_list:
result_df = pd.DataFrame(data=all_person_data_list,
columns=[
'person_id', 'scopus_id', 'doi',
'publish_year', 'eid',
'scopus_article_id'
])
write2sql([['scopus_author_article', result_df]])
def get_doc_data(input_data):
headers['content-type'] = 'application/json'
count = 0
while count < len(input_data):
result_df_list = []
try:
session = requests.session()
session.post(url=login_url,
data=login_data,
headers=headers_login,
timeout=300)
for i in range(count, len(input_data)):
print('当前进度：%s / %s' % (i + 1, len(input_data)))
post_url = post_url_base.format(input_data[i][1])
post_data_detail['filters']['sbjname'][
'is'] = input_data[i][3] + ' ' + input_data[i][4]
doc_data = session.post(url=post_url,
data=json.dumps(post_data_detail),
headers=headers,
timeout=300).json()
if doc_data['items']:
for item in doc_data['items']:
item['title'] = item['a']['title']
del item['a']
data_df = pd.DataFrame(data=doc_data['items'])
data_df['category_id'] = input_data[i][3]
data_df['category_name'] = input_data[i][4]
data_df['orgName'] = input_data[i][0]
result_df_list.append(data_df)
count = len(input_data)
session.close()
# 出现错误时，从错误处中断，再从该处开始
except Exception as err:
print('ERROR:%s' % err)
session.close()
count = i
if result_df_list:
all_data_df = pd.concat(result_df_list)
write2sql([['wos_doc_data_detail', all_data_df]])
def main_prog(driver, subject_code, type_code):
driver.get(basic_url)
time.sleep(0.5)
# 选择资助类别
driver.find_element_by_id('f_grantCode').click()
time.sleep(0.5)
driver.find_element_by_xpath(
'/html/body/div[4]/div[1]/div[2]/div/table/tbody/tr[1]/td/table/tbody/tr[6]/td[2]/select/option[%s]'
% type_code).click()
time.sleep(0.5)
# 选择年份
# driver.find_element_by_id('f_year').click()
# time.sleep(0.5)
# driver.find_element_by_xpath('/html/body/div[4]/div[1]/div[2]/div/table/tbody/tr[1]/td/table/tbody/tr[10]/td[2]/select/option[1]').click()
# 选择申请代码
driver.find_element_by_name('subjectCode').send_keys(subject_code)
time.sleep(2)
driver.find_element_by_xpath('/html/body/div[6]/ul/li[1]').click()
time.sleep(0.5)
# 输入验证码，识别错误时重新输入
while '递减' not in driver.page_source:
# 识别验证码
check_code = check_code_ocr(driver)
# 填入验证码
driver.find_element_by_id('f_checkcode').clear()
driver.find_element_by_id('f_checkcode').send_keys(check_code)
time.sleep(0.5)
# 查询
driver.find_element_by_id('searchBt').click()
time.sleep(0.5)
result_list = get_data(driver)
if result_list:
result_df = pd.DataFrame(data=result_list,
columns=[
'id', '项目批准号', '申请代码', '项目名称', '项目负责人',
'依托单位', '批准金额', '项目起止年月'
])
write2sql([['nsfc_data', result_df]])
def crawl_h_index(input_data):
count = 0
while count < len(input_data):
# 启动浏览器并获取cookies
driver = start_driver()
cookies = get_cookies(driver)
driver.close()
result_list = []
try:
# 开始对每位学者再scopus上进行匹配和信息获取
for i in range(count, len(input_data)):
print('当前进度：%s / %s' % (i + 1, len(input_data)))
url = 'https://www.scopus.com/authid/detail.uri?authorId=%s' % input_data[
i][1]
detail_page = requests.get(url,
proxies=proxies,
headers=headers,
timeout=300,
cookies=cookies)
soup = bs(detail_page.text, 'lxml')
h_index = soup.find(id='authorDetailsHindex')
element = h_index.find(class_='fontLarge')
if element:
result_list.append(
[input_data[i][0], input_data[i][1], element.text])
# 结束循环
count = len(input_data)
# 出现错误时，从错误处中断，再从该处开始
except Exception as err:
print('ERROR:%s' % err)
count = i
# 将已完成的部分进行数据写入
result_df = pd.DataFrame(data=result_list,
columns=['person_id', 'scopus_id', 'h_index'])
write2sql([['h_index', result_df]])
def get_detail_data(input_data):
data_no = datetime.datetime.now().strftime('%Y%m%d%H%M%S') + str(random.randint(10, 99))
count = 0
t_index = 4
while count < len(input_data):
# 启动浏览器并获取cookies
driver = start_driver()
cookies = get_cookies(driver)
driver.close()
ins_data_list = []
hindex_data_list = []
article_data_list = []
try:
for i in range(count, len(input_data)):
print('当前进度：%s / %s' % (i + 1, len(input_data)))
# 获取学者文献及引证数据
article_data_df = catch_info(input_data[i][t_index], cookies)
article_data_df['name_zh'] = input_data[i][2]
article_data_df['person_id'] = input_data[i][0]
article_data_list.append(article_data_df)
# 获取学者h_index数据
detail_url = detail_base_url % input_data[i][t_index]
detail_page = requests.get(detail_url, proxies=proxies, headers=headers, timeout=300, cookies=cookies)
detail_soup = bs(detail_page.text, 'lxml')
h_index = detail_soup.find(id='authorDetailsHindex')
h_index_element = h_index.find(class_='fontLarge')
if h_index_element:
hindex_data_list.append([input_data[i][0], input_data[i][t_index], h_index_element.text])
# 获取学者机构数据
ins_url = ins_base_url % input_data[i][t_index]
ins_page = requests.get(ins_url, proxies=proxies, headers=headers, timeout=300, cookies=cookies)
ins_data = eval(ins_page.text)
for ins in ins_data:
# print(len(ins['affiliationName']), ins['affiliationName'])
ins['start_year'] = ins['dateRange'][0]
ins['end_year'] = ins['dateRange'][1]
ins.pop('dateRange')
ins_data_df = pd.DataFrame(ins_data)
rename_dict = {'affiliationCity': 'aff_city',
'affiliationName': 'aff_name',
'affiliationCountry': 'aff_country',
'affiliationId': 'aff_id',
'affiliationUrl': 'aff_url'}
ins_data_df.rename(columns=rename_dict, inplace=True)
ins_data_df['scopus_id'] = input_data[i][t_index]
ins_data_df['person_id'] = input_data[i][0]
ins_data_df['name_zh'] = input_data[i][2]
ins_data_list.append(ins_data_df)
count = len(input_data)
# 出现错误时，从错误处中断，再从该处开始
except Exception as err:
print('ERROR:%s' % err)
count = i
all_ins_data = pd.DataFrame() if not ins_data_list else pd.concat(ins_data_list)
all_hindex_data = pd.DataFrame() if not ins_data_list else pd.DataFrame(data=hindex_data_list, columns=['person_id', 'scopus_id', 'h_index'])
all_article_data = pd.DataFrame() if not ins_data_list else pd.concat(article_data_list)
for _df in [all_ins_data, all_article_data]:
if len(_df) > 0:
_df['data_no'] = data_no
_df['flag'] = 2
all_hindex_data['flag'] = 2
write2sql([['author_info_new', all_article_data], ['author_exp', all_ins_data],
['h_index', all_hindex_data]])
try:
for i in range(count, len(data_list)):
print(i)
data = data_list[i]
url = data[1]
# page = requests.get(url=url, headers=headers, proxies=proxies, cookies=cookies_dict)
page = requests.get(url=url, headers=headers, cookies=cookies_dict)
source = re.findall(r'''<div class="i-list_baokan t1_12">[\s\S]*?</div>''', page.text)
if source:
link_list = re.findall(r'''<li style=".*?"><a title=".*?" href="(.*?)">''', source[0])
title_list = re.findall(r'''<li style=".*?"><a title="(.*?)" href=".*?''', source[0])
domain_url = 'http://www.apabi.com/sjtu/'
link_list = [domain_url + i for i in link_list]
df = pd.DataFrame(data={'title': title_list, 'text_link': link_list})
df['text_date'] = data[2]
df['page_link'] = data[1]
df['page_name'] = data[0]
result_list.append(df)
# 结束循环
count = len(data_list)
# 出现错误时，从错误处中断，再从该处开始
except Exception as err:
print('ERROR:%s' % err)
print('当前进度：%s / %s' % (i + 1, len(data_list)))
count = i
if result_list:
all_data_df = pd.concat(result_list)
write2sql([['rmrb_copy', all_data_df]])
def get_detail_data(input_data):
data_no = datetime.datetime.now().strftime('%Y%m%d%H%M%S') + str(
random.randint(10, 99))
count = 0
while count < len(input_data):
all_person_data_list = []
driver = start_driver()
try:
for i in range(count, len(input_data)):
print('当前进度：%s / %s' % (i + 1, len(input_data)))
url = detail_base_url % input_data[i][1]
driver.get(url)
try:
driver.find_element_by_id('authViewCitOver').click()
except Exception as err:
print('ERROR:%s' % err)
continue
time.sleep(10)
cto_id1 = re.findall(r'CTOF_([0-9]+)', driver.current_url)
cto_id2 = re.findall(r'var ctoId = "CTODS_([0-9]+)"',
driver.page_source)
one_person_data_list = []
# 页数循环
for j in range(5):
url2 = article_url % (cto_id2[0], cto_id1[0], 200 * j)
driver.get(url2)
if 'Error 500' in driver.page_source:
break
soup = bs(driver.page_source.replace(' ', '0'),
'lxml')
publish_year = re.findall(r'<span>([0-9]{4})</span>',
driver.page_source)
previous_cell_count = [
int(k.text)
for k in soup.find_all(class_='previousCellCount')
]
previous_years = [
int(k.text)
for k in soup.find_all(class_='previousYears')
]
sub_total = [
int(k.text) for k in soup.find_all(class_='subTotal')
]
all_total = [
int(k.text) for k in soup.find_all(class_='subtotal')
]
prev_latest = [
int(k.text)
for k in soup.find_all(class_='prevLatestYears')
]
one_page_data = pd.DataFrame({
'publish_year': publish_year,
'previous_cell_count': previous_cell_count,
'2006': previous_years[0::15],
'2007': previous_years[1::15],
'2008': previous_years[2::15],
'2009': previous_years[3::15],
'2010': previous_years[4::15],
'2011': previous_years[5::15],
'2012': previous_years[6::15],
'2013': previous_years[7::15],
'2014': previous_years[8::15],
'2015': previous_years[9::15],
'2016': previous_years[10::15],
'2017': previous_years[11::15],
'2018': previous_years[12::15],
'2019': previous_years[13::15],
'2020': previous_years[14::15],
'sub_total': sub_total,
'all_total': all_total,
'prev_latest': prev_latest
})
one_person_data_list.append(one_page_data)
if one_person_data_list:
one_person_data = pd.concat(one_person_data_list)
one_person_data['person_id'] = input_data[i][0]
one_person_data['scopus_id'] = input_data[i][1]
all_person_data_list.append(one_person_data)
count = len(input_data)
driver.close()
# 出现错误时，从错误处中断，再从该处开始
except Exception as err:
print('ERROR:%s' % err)
count = i
driver.close()
if all_person_data_list:
all_person_data = pd.concat(all_person_data_list)
all_person_data['article_num'] = 1
final_data = all_person_data.groupby(
by=['person_id', 'scopus_id',
'publish_year'], as_index=False).sum()
final_data['data_no'] = data_no
write2sql([['article_cite_data', final_data]])
def main_prog(input_data):
'''
:param input_data: [{'person_id':1234564, 'name':'liu bo', 'ins':['fudan university', 'xx university', 'xxx university'],
'ins_id':[111, 222, 333], 'name_zh':'刘博'}, {...}]
:return:
'''
data_no = datetime.datetime.now().strftime('%Y%m%d%H%M%S') + str(random.randint(10, 99))
logger.info('数据版本号: %s' % data_no)
count = 0
while count < len(input_data):
all_aff_df = pd.DataFrame(data=None, columns=None)
basic_info_df = pd.DataFrame(data=None, columns=None)
mult_result_df = pd.DataFrame(data=None, columns=None)
not_matched_df = pd.DataFrame(data=None, columns=None)
# 启动浏览器并获取cookies
driver = start_driver()
cookies = get_cookies(driver)
driver.close()
try:
# 开始对每位学者再scopus上进行匹配和信息获取
for i in range(count, len(input_data)):
person_id = input_data[i]['person_id']
author_name = input_data[i]['name']
author_name_zh = input_data[i]['name_zh']
author_ins = input_data[i]['ins']
author_ins_id = input_data[i]['ins_id']
logger.info('当前进度：软科id：%s, 姓名：%s,%s' % (person_id, author_name_zh, author_name[0]))
# 机构英文名称全部转为小写
author_ins = [i.lower() for i in author_ins]
# todo 0624临时修改
# authorID_list = get_id(person_id, author_name, author_name_zh, author_ins[0])
authorID_list = []
for _name in author_name:
for _ins in author_ins:
authorID_list.extend(get_id(person_id, _name, author_name_zh, _ins))
if authorID_list:
break
if authorID_list:
break
# 以机构对应的scopus_id匹配
aff_df, basic_info, mult_re, not_match = match(cookies, person_id, author_name, author_name_zh,
author_ins_id, authorID_list)
all_aff_df = all_aff_df.append(aff_df, ignore_index=True)
basic_info_df = basic_info_df.append(basic_info, ignore_index=True)
mult_result_df = mult_result_df.append(mult_re, ignore_index=True)
not_matched_df = not_matched_df.append(not_match, ignore_index=True)
# 结束循环
count = len(input_data)
# 出现错误时，从错误处中断，再从该处开始
except Exception as err:
logger.info('ERROR:%s' % err)
logger.info('当前进度：%s / %s' % (i+1, len(input_data)))
count = i
# 添加data_no字段
for df in [all_aff_df, basic_info_df, mult_result_df, not_matched_df]:
if len(df) > 0:
df['data_no'] = data_no
# 将已完成的部分进行数据写入
write2sql([['author_info_new', basic_info_df], ['author_exp', all_aff_df],
['mult_matched_author', mult_result_df], ['not_matched_author', not_matched_df]])
# df = pd.read_excel('C:/Users/Administrator/Desktop/校名映射表.xlsx')
# data = pd.merge(data, df, how='left', on='orgName')
#
# print('merge完成')
# print('开始写入数据库')
# write2sql([['wos_doc_data0930', data]])
# print('写入数据库完成')
dbutil = DBUtil(host, port, database, username, password)
sql = 'select * from wos_doc_data_detail'
data = dbutil.get_allresult(sql, 'df')
print('读取源数据完成')
df = pd.read_excel('C:/Users/Administrator/Desktop/校名映射表.xlsx')
data = pd.merge(data, df, how='left', on='orgName')
data1 = data.loc[0:499999]
data2 = data.loc[500000:999999]
data3 = data.loc[1000000:1499999]
data4 = data.loc[1500000:1999999]
data5 = data.loc[2000000:2499999]
data6 = data.loc[2500000:2999999]
data7 = data.loc[3000000:]
data_list = [data1, data2, data3, data4, data5, data6, data7]
i = 0
for data in data_list:
print(i)
write2sql([['wos_doc_data_detail0930', data]])
i += 1
try:
for i in range(count, len(data_list)):
print(i)
data = data_list[i]
url = data[1]
# page = requests.get(url=url, headers=headers, proxies=proxies, cookies=cookies_dict)
page = requests.get(url=url, headers=headers, cookies=cookies_dict)
source = re.findall(r'''<div class="i-list_baokan t1_12">[\s\S]*?</div>''', page.text)
if source:
link_list = re.findall(r'''<li style=".*?"><a title=".*?" href="(.*?)">''', source[0])
title_list = re.findall(r'''<li style=".*?"><a title="(.*?)" href=".*?''', source[0])
domain_url = 'http://www.apabi.com/sjtu/'
link_list = [domain_url + i for i in link_list]
df = pd.DataFrame(data={'title': title_list, 'text_link': link_list})
df['text_date'] = data[2]
df['page_link'] = data[1]
df['page_name'] = data[0]
result_list.append(df)
# 结束循环
count = len(data_list)
# 出现错误时，从错误处中断，再从该处开始
except Exception as err:
print('ERROR:%s' % err)
print('当前进度：%s / %s' % (i + 1, len(data_list)))
count = i
if result_list:
all_data_df = pd.concat(result_list)
write2sql([['rmrb', all_data_df]])
def get_doc_data(input_data, author_position, period):
if period == '近10年':
post_data['filters']['period']['is'] = [2010, 2019]
if period == '近5年' or period == '近5年Q1':
post_data['filters']['period']['is'] = [2015, 2019]
if 'authorposition' in post_data['filters']:
post_data['filters']['authorposition']['is'] = [author_position]
if author_position == 'First & Corresponding':
post_data['filters']['authorposition']['is'] = [
'First', 'Corresponding'
]
if author_position == 'All':
del post_data['filters']['authorposition']
if author_position == 'First & Corresponding':
post_data['filters']['authorposition'] = {
"is": ['First', 'Corresponding']
}
a = post_data
count = 0
no_result = []
while count < len(input_data):
result_df_list = []
try:
session = requests.session()
session.post(url=login_url,
data=login_data,
headers=headers_login,
timeout=300)
for i in range(count, len(input_data)):
print('当前进度：%s / %s' % (i + 1, len(input_data)))
post_data['filters']['personId']['is'] = input_data[i][2]
author_data = session.post(url=post_url,
data=json.dumps(post_data),
headers=headers,
timeout=300).json()
if author_data['items']:
for item in author_data['items']:
item['doc_num'] = item['wosDocuments']['value']
item['highly_cited_paper'] = item['highlyCitedPapers'][
'value']
item['inter_colla'] = item['intCollaborations'][
'value']
del item['wosDocuments']
del item['highlyCitedPapers']
del item['intCollaborations']
data_df = pd.DataFrame(data=author_data['items'])
data_df['person_id'] = input_data[i][0]
data_df['name_zh'] = input_data[i][1]
result_df_list.append(data_df)
else:
no_result.append([
input_data[i][0], input_data[i][1], author_position, 0
])
count = len(input_data)
session.close()
# 出现错误时，从错误处中断，再从该处开始
except Exception as err:
print('ERROR:%s' % err)
session.close()
count = i
if result_df_list:
all_data_df = pd.concat(result_df_list)
all_data_df['author_position'] = author_position
all_data_df['period'] = period
write2sql([['incites_author_data1008', all_data_df]])
if no_result:
no_result_df = pd.DataFrame(data=no_result,
columns=['人才编号', '姓名', '作者类型', '文献数量'])
no_result_df.to_excel(
'C:/Users/Administrator/Desktop/no_result1008.xlsx', index=False)
def wos_article(input_data):
count = 0
page_count = 33
while count < len(input_data):
articel_data_all = []
try:
# 建立连接session
session = requests.session()
connection = session.get(url, headers=headers, proxies=proxies)
# 获取sid
sid = re.findall(r'SID=(\w+)&', connection.url)[0]
# 开始循环获取数据
for i in range(count, len(input_data)):
print('当前进度：%s / %s' % (i + 1, len(input_data)))
print(input_data[i])
name = input_data[i][0]
data = data_ini.format(sid, sid, name)
search_page = session.post(post_url,
data=data,
proxies=proxies,
headers=headers,
timeout=300)
qid = re.findall(r'qid=([0-9]+)&', search_page.text)[0]
search_result_num = re.findall(
r'FINAL_DISPLAY_RESULTS_COUNT = ([0-9]+);',
search_page.text)[0]
print(search_result_num)
page_num = math.ceil(int(search_result_num) / 500)
for k in range(page_count, page_num):
print(f'{k}/{page_num}')
data_dl = data_dl_ini.format(qid, sid, qid, sid,
k * 500 + 500, k * 500 + 1,
name, k * 500 + 1,
k * 500 + 500)
dl_page = session.post(dl_post_url,
data=data_dl,
proxies=proxies,
headers=headers,
timeout=300)
if ('PT' not in dl_page.text) and ('AU'
not in dl_page.text):
raise Exception('error')
data_list = dl_page.text.strip().split('\n')
articel_data_temp = [
j.strip().split('\t') for j in data_list[1:]
]
df_temp = pd.DataFrame(data=articel_data_temp,
columns=columns)
df_temp['name_zh'] = input_data[i][1]
articel_data_all.append(df_temp)
page_count = 0
# 结束循环
count = len(input_data)
session.close()
# 出现错误时，从错误处中断，再从该处开始
except Exception as err:
print('ERROR:%s' % err)
session.close()
count = i
page_count = k
if articel_data_all:
articel_data_df = pd.concat(articel_data_all)
write2sql([['wos_article_data', articel_data_df]])
find_df_list.append(temp_df)
else:
not_find.append(source_list[i][4])
else:
not_find.append(source_list[i][4])
# 结束循环
count = len(source_list)
# 出现错误时，从错误处中断，再从该处开始
except Exception as err:
print('ERROR:%s' % err)
print('当前进度：%s / %s' % (i + 1, len(source_list)))
count = i
if str(type(err)) == "<class 'UnicodeEncodeError'>":
count += 1
not_find.append(source_list[i][4])
if len(find_df_list) > 0:
all_find = pd.concat(find_df_list)
else:
all_find = pd.DataFrame()
if len(not_find) > 0:
all_not_find = pd.DataFrame(data=not_find, columns=['person_id'])
else:
all_not_find = pd.DataFrame()
write2sql([['find_result', all_find], ['not_find', all_not_find]])