不要改这些代码,增加合理代码,最好是selenium爬取http://xueshu.baidu.com/。包括文献名称、作者、摘要、文献链接、来源期刊、发表年份、引用量,并将其保存至csv文件中。要求以某一个关键词(如“数字经济”)进行搜索,爬取100条文献信息;再以两个相关的关键词(如“数字技术”、“数字化”)分别各爬取100条文献信息,直至获取到300条文献信息 # 提取作者 author_tag = soup.find('a', {'data-click': "{'button_tp':'author'}"}) author = author_tag.get_text(strip=true) if author_tag else "未找到作者" # 提取摘要 abstract_tag = soup.find('div', {'class': 'c_abstract'}) abstract = abstract_tag.get_text(strip=true) if abstract_tag else


以下是为您编写的使用 Selenium 爬取文献信息的代码示例,并将结果保存到 CSV 文件中: ```python import time import csv from selenium import webdriver # 定义关键词 keywords = ["数字经济", "数字技术", "数字化"] # 初始化浏览器 driver = webdriver.Chrome() # 定义保存数据的函数 def save_to_csv(data): with open('literature_info.csv', 'a', newline='', encoding='utf-8') as file: writer = csv.writer(file) writer.writerow(data) # 爬取函数 def crawl_literature(keyword, num): url = f"http://xueshu.baidu.com/s?wd={keyword}" driver.get(url) time.sleep(2) # 等待页面加载 literature_list = driver.find_elements_by_xpath('//div[@class="sc_content"]') count = 0 for literature in literature_list: if count >= num: break # 提取文献名称 title_tag = literature.find_element_by_xpath('.//h3/a') title = title_tag.text # 提取作者 author_tag = literature.find_element_by_xpath('.//div[@class="sc_info"]/a') author = author_tag.text if author_tag else "未找到作者" # 提取 abstract_tag = literature.find_element_by_xpath('.//div[@class="c_abstract"]') abstract = abstract_tag.text if abstract_tag else "未找到" # 提取文献链接 link_tag = literature.find_element_by_xpath('.//h3/a') link = link_tag.get_attribute('href') # 提取来源期刊 source_tag = literature.find_element_by_xpath('.//div[@class="sc_info"]/span[1]') source = source_tag.text if source_tag else "未找到来源期刊" # 提取发表年份 year_tag = literature.find_element_by_xpath('.//div[@class="sc_info"]/span[2]') year = year_tag.text if year_tag else "未找到发表年份" # 提取引用量 citation_tag = literature.find_element_by_xpath('.//div[@class="sc_info"]/span[3]') citation = citation_tag.text if citation_tag else "未找到引用量" save_to_csv([title, author, abstract, link, source, year, citation]) count += 1 # 执行爬取 for keyword in keywords: if keyword == "数字经济": crawl_literature(keyword, 100) else: crawl_literature(keyword, 100) # 关闭浏览器 driver.quit() ``` 额外需要注意的逻辑点: 1. 网页的结构可能会发生变化,需要及时调整 Xpath 路径以确保准确提取信息。 2. 爬取过程中要注意适当的等待时间,避免频繁请求被网站封禁。 3. 处理可能出现的异常情况,如网络连接问题或页面元素未找到等。 [2024-12-10 03:57:02 | AI写代码神器 | 706点数解答]
- 不要改这些代码,增加合理代码,最好是selenium爬取http://xueshu.baidu.com/。包括文献名称、作者、摘要、文献链接、来源期刊、发表年份、引用量,并将其保存至csv文件中。要求以某一个关键词(如“数字经济”)进行搜索,爬取100条文献信息;再以两个相关的关键词(如“数字技术”、“数字化”)分别各爬取100条文献信息,直至获取到300条文献信息 # 提取作者 author_tag = soup.find('a', {'data-click': "{'button_tp':'author'}"}) author = author_tag.get_text(strip=true) if author_tag else "未找到作者" # 提取摘要 abstract_tag = soup.find('div', {'class': 'c_abstract'}) abstract = abstract_tag.get_text(strip=true) if abstract_tag else(706点数解答 | 2024-12-10 03:57:02)163
- def fill_and_submit_form(row): print("填充表单并提交...") wait = webdriverwait(driver, 5) # 增加等待时间 try: product_name_input = wait.until(ec.presence_of_element_located((by.xpath, '//*[@id="wcontentpanel"]/div[3]/div/div[2]/form/div[1]/div[3]/div/div/div[1]/input'))) product_category_dropdown = wait.until(ec.element_to_be_clickable((by.xpath, '//*[@id="wcontentpanel"]/div[3]/div/div[2]/form/div[1]/div[4]/div/div/div/span/span/div/div[1]'))) time.sleep(2) # 等待完成(361点数解答 | 2024-11-11 21:56:42)223
- 任务一:采集唐诗三百首内容 python import requests from bs4 import beautifulsoup import pandas as pd url = "https://so.gushiwen.cn/gushi/tangshi.aspx" response = requests.get(url) soup = beautifulsoup(response.text, "html.parser") poems = [] for poem in soup.find_all("div", class_="item"): title = poem.find("h1").text.strip() content = poem.find("p").text.strip() author = poem.find("span", class_="author").text.strip() poem_type = "唐诗" poems.append((15点数解答 | 2024-06-24 15:46:11)280
- 请使用python语言编写网络爬虫程序,爬取百度学术上查询的科研文献信息,网址为:http://xueshu.baidu.com/。使用已学的方法(如selenium库等)爬取文献信息,包括文献名称、作者、摘要、关键词、文献链接、来源期刊、发表年份、引用量、doi,并将其保存至csv文件中。要求以某一个关键词(如“数字经济”)进行搜索,爬取100条文献信息;再以两个相关的关键词(如“数字技术”、“数字化”)分别各爬取100条文献信息,直至获取到300条文献信息。然后,基于此对各年份发表的文献数量数据进行可视化,并开展简要分析。以年份为横轴,文献数量为纵轴,使用pyecharts绘制散点图。要求显示涉及的最近10个年份的文献数量,并将除此之外的其它年份的文献数量以其总数体现(858点数解答 | 2024-12-10 03:59:45)302
- <!DOCTYPE html> <html> <head> {include file="common_header" /} {include file="common_top" /} </head> <body> <div class="layui-fluid"> <div class="layui-row layui-col-space15"> <div class="layui-col-md12"> <div class="layui-card"> <div class="layui-card-body"> <div class="layui-form" lay-filter="component-form-element"> <div class="layui-box layui-laypage layui-laypage-molv">{$page}</div> <table class="layui-table" lay-even="" lay(644点数解答 | 2025-03-11 15:42:55)161
- 编写一个爬虫实现深度优先爬虫,爬取的网站为 www.baidu.com。使其输出预期为:Add the seeds url ['http://www.baidu.com'] to the unvisited url list Pop out one url "http://www.baidu.com" from unvisited url list Get 10 new links Visited url count: 1 Visited deepth: 1 10 unvisited links: Pop out one url "http://news.baidu.com" from unvisited url list Get 52 new links Visited url count: 2 Visited deepth: 2 Pop out one url "http://www.hao123.com" from unvisited url list Get 311 new links Visited url count: 3 Visited deepth: 2 Pop out(2142点数解答 | 2025-05-13 15:54:49)189
- <template> <div class="annotation-editor"> <!-- 顶部导航栏 --> <div class="top-bar"> <button class="back-button" @click="goBack"> <svg class="back-icon" viewBox="0 0 24 24"> <path d="M15.41 7.41L14 6l-6 6 6 6 1.41-1.41L10.83 12z"/> </svg> </button> <div class="title">图片标注编辑器</div> </div> <!-- 控制按钮栏 --> <div class="control-bar"> <button v-for="control in controls" :key="control.name" class="control-(521点数解答 | 2025-08-15 13:15:46)68
- App.vue <template> <div style="padding: 100px 0 0 0"> <div id="header" class="header-v1" style="height: 100px;background-color:rgb(0 137 255 / 70%)"> <div class="header"> <div class="container" style="width: 1500px;height: 100px"> <div id="header-logo" class="right"> <div class="header-logo"><a href="#" id="logo"><img id="logo-default" src="" alt=""/><img style="display:none" id="logo-alternate" src="" alt=""/> </a></div> </div>(31点数解答 | 2025-05-14 09:58:18)167
- <template> <div class="login"> <div class="loginBox"> <h3>用户登录</h3> <span class="deadline"></span> <div class="form"> <div class="input"> <img src="../../assets/login/username.png" alt="" /> <input type="text" placeholder="请输入用户名" v-model="username" /> </div> <div class="input"> <img src="../../assets/login/password.png" alt="" /> <input type="password" placeholder="请输入密码" v-model="password" /> </div>(1402点数解答 | 2025-03-18 21:31:12)161
- import requests from bs4 import beautifulsoup import pandas as pd url = "https://so.gushiwen.cn/gushi/tangshi.aspx" response = requests.get(url) soup = beautifulsoup(response.text, 'html.parser') # 提取所需数据 poems_data = [] for row in soup.find_all('tr', class_='tlist')[1:]: cols = row.find_all('td') type_ = cols.text.strip() title = cols.a.text.strip() content = cols.text.replace('\n', '').replace('\t', '') author = cols.text.strip() poems_data.append([type_, title, conte(120点数解答 | 2024-06-24 02:04:56)260
- import pandas as pd # 读取数据 df = pd.read_excel("https://cloud-cdn.acctedu.com/publicres/match/525839b97fa94429ac26bf57a798accc/order_datas.xlsx") # 添加年份列 df['年份'] = pd.to_datetime(df['订单日期']).dt.year # 从订单日期提取年份,并创建“年份”列 # 计算销售金额 df['销售金额'] = ___count*amount__ # 计算每个订单的销售金额 = 销售单价 * 销售数量 # 按年份分组 grouped = df.groupby('年份') # 将数据按“年份”列进行分组,便于逐年分析 # 遍历每个年份,计算相关指标 for year, group in grouped: # 遍历每个年份的分组数据 total_order_count = __a_ # 计算该年份的总订单数量(行数) total_order_amount =___b_ # 计算该年份的(260点数解答 | 2024-11-10 14:26:05)180
- # 引入规则 import pandas as pd # 读取数据 df = pd.read_excel("https://cloud-cdn.acctedu.com/publicres/match/525839b97fa94429ac26bf57a798accc/order_datas.xlsx") # 添加年份列 df['年份'] = pd.to_datetime(df['订单日期']).dt.year # 从订单日期提取年份,并创建“年份”列 # 计算销售金额 df['销售金额'] = ___df['销售单价'] * df['销售数量']__ # 计算每个订单的销售金额 = 销售单价 * 销售数量 # 按年份分组 grouped = df.groupby('年份') # 将数据按“年份”列进行分组,便于逐年分析 # 遍历每个年份,计算相关指标 for year, group in grouped: # 遍历每个年份的分组数据 total_order_count = __group.shape[0]_ # 计算该年份的总订单数量(行数) tota(701点数解答 | 2024-11-10 14:29:10)194