初步实现服务器和终端能连接，并且终端向服务端发起请求并取得响应,基础

.gitignore

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+!/dcs/tests/zhiwang.py

dcs/tests/zhiwang.py

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+'''
+    知网论文数据爬取
+'''
+
+from bs4 import BeautifulSoup
+from selenium import webdriver
+from selenium.webdriver.chrome.service import Service
+import time
+import requests
+import csv
+
+
+# 定义论文类
+from selenium.webdriver.common.by import By
+
+
+class Paper:
+    def __init__(self, title, authors):
+        self.title = title
+        self.authors = authors
+
+
+# 定义作者类
+class Author:
+    def __init__(self, name, college, major):
+        self.name = name
+        self.college = college
+        self.major = major
+
+
+# 进入知网首页并搜索关键词
+def driver_open(driver, key_word):
+    url = "https://www.cnki.net/"
+    driver.get(url)
+    time.sleep(2)
+    driver.find_element(by=By.CSS_SELECTOR, value='#txt_SearchText').send_keys(key_word)
+    time.sleep(2)
+    # 点击搜索按钮
+    driver.find_element(by=By.CSS_SELECTOR, value=
+        'body > div.wrapper.section1 > div.searchmain > div > div.input-box > input.search-btn').click()
+    time.sleep(5)
+    content = driver.page_source.encode('utf-8')
+    # driver.close()
+    soup = BeautifulSoup(content, 'lxml')
+    return soup
+
+
+def spider(driver, soup, papers):
+    tbody = soup.find_all('tbody')
+    tbody = BeautifulSoup(str(tbody[0]), 'lxml')
+    tr = tbody.find_all('tr')
+    for item in tr:
+        tr_bf = BeautifulSoup(str(item), 'lxml')
+
+        td_name = tr_bf.find_all('td', class_='name')
+        td_name_bf = BeautifulSoup(str(td_name[0]), 'lxml')
+        a_name = td_name_bf.find_all('a')
+        # get_text()是获取标签中的所有文本，包含其子标签中的文本
+        title = a_name[0].get_text().strip()
+        print("title : " + title)
+
+        td_author = tr_bf.find_all('td', class_='author')
+        td_author_bf = BeautifulSoup(str(td_author), 'lxml')
+        a_author = td_author_bf.find_all('a')
+        authors = []
+        # 拿到每一个a标签里的作者名
+        for author in a_author:
+            skey, code = get_skey_code(author)  # 获取作者详情页url的skey和code
+            name = author.get_text().strip()  # 获取学者的名字
+            print('name : ' + name)
+            college, major = get_author_info(skey, code)  # 在作者详情页获取大学和专业, major是一个数组
+            au = Author(name, college, major)  # 创建一个学者对象
+            authors.append(au)
+
+        print('\n')
+        paper = Paper(title, authors)
+        papers.append(paper)
+        time.sleep(1)  # 每调一次spider休息1s
+
+
+# pn表示当前要爬的页数
+def change_page(driver, pn):
+    driver.find_element(by=By.CSS_SELECTOR, value='#page' + str(pn)).click()
+    time.sleep(5)
+    content = driver.page_source.encode('utf-8')
+    soup = BeautifulSoup(content, 'lxml')
+    return soup
+
+
+# 获取作者详情页url的skey和code, 传入参数是一个a标签
+def get_skey_code(a):
+    skey = a.get_text().strip()
+    href = str(a.get('href'))  # 拿到a标签href的值
+    code = href[href.find('acode') + 6:]  # 拿到code的值
+    return skey, code
+
+
+# 获取作者的详细信息
+def get_author_info(skey, code):
+    url = 'https://kns.cnki.net/kcms/detail/knetsearch.aspx?dbcode=CAPJ&sfield=au&skey=' + skey + '&code=' + code + '&v=3lODiQyLcHhoPt6DbD%25mmd2FCU9dfuB5GXx8ZJ7nSrKZfD6N9B5gKP9Ftj%25mmd2B1IWA1HQuWP'
+    header = {
+        'user-agent': 'Mozilla/5.0 (Windows NT 6.3; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/63.0.3239.133 Safari/569.36',
+        'Connection': 'close'
+    }
+    requests.packages.urllib3.disable_warnings()
+    rsp = requests.get(url, headers=header, verify=False)
+    rsp_bf = BeautifulSoup(rsp.text, 'lxml')
+    div = rsp_bf.find_all('div', class_='wrapper')
+    # 有的学者查不到详细信息
+    if div:
+        div_bf = BeautifulSoup(str(div[0]), 'lxml')
+        h3 = div_bf.find_all('h3')
+        college = h3[0].get_text().strip()
+        major = h3[1].get_text().strip()
+        # major = major.split(';')[0: -1]
+        print('college:' + college)
+        print('major: ' + major)
+        return college, major
+    print("无详细信息")
+    return None, None
+
+
+if __name__ == '__main__':
+    browser = Service('../../bin/msedgedriver.exe')
+    driver = webdriver.Edge(service=browser)
+    soup = driver_open(driver, '知识图谱')  # 搜索知识图谱
+    papers = []  # 用于保存爬取到的论文
+    # 将爬取到的论文数据放入papers中
+    spider(driver, soup, papers)
+    for pn in range(2, 3):
+        content = change_page(driver, pn)
+        spider(driver, content, papers)
+    driver.close()
+
+    # 写入文件
+    f_papers_authors = open('./paper_author.csv', 'w', encoding='utf-8', newline='')
+    writer_p_a = csv.writer(f_papers_authors)  # 基于文件对象构建 csv写入对象
+    writer_p_a.writerow(["name", "college", "major", "paper"])  # csv文件的表头
+
+    # 读取每一篇论文
+    for paper in papers:
+        # 写入paper_author.csv文件
+        for author in paper.authors:
+            if author.name:
+                # print(author + "  ")
+                writer_p_a.writerow([author.name, author.college, author.major, paper.title])
+
+    # 关闭文件
+    f_papers_authors.close()