Question

我的目标是在Khan Academy上抓取尽可能多的个人资料链接。然后在每个配置文件上抓取一些特定数据，以将其写入CSV文件。

我的问题很简单：脚本很慢。

这是脚本：

from selenium import webdriver
from selenium.webdriver.common.by import By
from selenium.webdriver.support.ui import WebDriverWait
from selenium.webdriver.support import expected_conditions as EC
from selenium.common.exceptions import TimeoutException,StaleElementReferenceException,NoSuchElementException
from bs4 import BeautifulSoup
import re
from requests_html import HTMLSession

session = HTMLSession()
r = session.get('https://www.khanacademy.org/computing/computer-programming/programming#intro-to-programming')
r.html.render(sleep=5)
soup=BeautifulSoup(r.html.html,'html.parser')

# first step: find all courses links and put them in a list
courses_links = soup.find_all(class_='link_1uvuyao-o_O-nodeStyle_cu2reh-o_O-nodeStyleIcon_4udnki')
list_courses={}

for links in courses_links:
    courses = links.extract()
    link_course = courses['href']
    title_course= links.find(class_='nodeTitle_145jbuf')
    span_title_course=title_course.span
    text_span=span_title_course.text.strip()
    final_link_course ='https://www.khanacademy.org'+link_course
    list_courses[text_span]=final_link_course


# second step: loop the script down below with each course link in our list

for courses_step in list_courses.values():
    # part 1: make selenium infinite click "schow more" button so we can then scrape as much profile links as possible
    driver = webdriver.Chrome()
    driver.get(courses_step)
    while True: # might want to change that to do some testing
        try:
            showmore=WebDriverWait(driver, 15).until(EC.presence_of_element_located((By.CLASS_NAME,'button_1eqj1ga-o_O-shared_1t8r4tr-o_O-default_9fm203')))
            showmore.click()
        except TimeoutException:
            break
        except StaleElementReferenceException:
            break

    # part2: once the page fully loaded scrape all profile links and put them in a list

    soup=BeautifulSoup(driver.page_source,'html.parser')
    #find the profile links
    driver.quit()
    profiles = soup.find_all(href=re.compile("/profile/kaid"))
    profile_list=[]
    for links in profiles:
        links_no_list = links.extract()
        text_link = links_no_list['href']
        text_link_nodiscussion = text_link[:-10]
        final_profile_link ='https://www.khanacademy.org'+text_link_nodiscussion
        profile_list.append(final_profile_link)

    #remove profile link duplicates
    profile_list=list(set(profile_list))

    #print number of profiles we got in the course link
    print('in this link:')
    print(courses_step)
    print('we have this number of profiles:')
    print(len(profile_list))

    #create the csv file
    filename = "khan_withprojectandvotes.csv"
    f = open(filename, "w")
    headers = "link, date_joined, points, videos, questions, votes, answers, flags, project_request, project_replies, comments, tips_thx, last_date, number_project, projet_votes, projets_spins, topq_votes, topa_votes, sum_badges, badge_lvl1, badge_lvl2, badge_lvl3, badge_lvl4, badge_lvl5, badge_challenge\n"
    f.write(headers)

    #part 3: for each profile link, scrape the specific data and store them into the csv
    for link in profile_list:
        #print each profile link we are about to scrap
        print("Scrapping ",link)

        session = HTMLSession()
        r = session.get(link)
        r.html.render(sleep=5)

        soup=BeautifulSoup(r.html.html,'html.parser')

        badge_list=soup.find_all(class_='badge-category-count')
        badgelist=[]
        if len(badge_list) != 0:
            for number in badge_list:
                text_num=number.text.strip()
                badgelist.append(text_num)
            number_badges=sum(list(map(int, badgelist)))
            number_badges=str(number_badges)
            badge_challenge=str(badgelist[0])
            badge_lvl5=str(badgelist[1])
            badge_lvl4=str(badgelist[2])
            badge_lvl3=str(badgelist[3])
            badge_lvl2=str(badgelist[4])
            badge_lvl1=str(badgelist[5])

        else:
            number_badges='NA'
            badge_challenge='NA'
            badge_lvl5='NA'
            badge_lvl4='NA'
            badge_lvl3='NA'
            badge_lvl2='NA'
            badge_lvl1='NA'


        user_info_table=soup.find('table', class_='user-statistics-table')
        if user_info_table is not None:
            dates,points,videos=[tr.find_all('td')[1].text for tr in user_info_table.find_all('tr')]
        else:
            dates=points=videos='NA'

        user_socio_table=soup.find_all('div', class_='discussion-stat')
        data = {}
        for gettext in user_socio_table:
            category = gettext.find('span')
            category_text = category.text.strip()
            number = category.previousSibling.strip()
            data[category_text] = number

        full_data_keys=['questions','votes','answers','flags raised','project help requests','project help replies','comments','tips and thanks'] #might change answers to answer because when it's 1 it's putting NA instead
        for header_value in full_data_keys:
            if header_value not in data.keys():
                data[header_value]='NA'

        user_calendar = soup.find('div',class_='streak-calendar-scroll-container')
        if user_calendar is not None:
            last_activity = user_calendar.find('span',class_='streak-cell filled')
            try:
                last_activity_date = last_activity['title']
            except TypeError:
                last_activity_date='NA'
        else:
            last_activity_date='NA'

        session = HTMLSession()
        linkq=link+'discussion/questions'
        r = session.get(linkq)
        r.html.render(sleep=5)
        soup=BeautifulSoup(r.html.html,'html.parser')

        topq_votes=soup.find(class_='text_12zg6rl-o_O-LabelXSmall_mbug0d-o_O-votesSum_19las6u')
        if topq_votes is not None:
            topq_votes=topq_votes.text.strip()
            topq_votes=re.findall('\d+', topq_votes)
            topq_votes=topq_votes[0]
            #print(topq_votes)
        else:
            topq_votes='0'


        session = HTMLSession()
        linka=link+'discussion/answers'
        r = session.get(linka)
        r.html.render(sleep=5)
        soup=BeautifulSoup(r.html.html,'html.parser')

        topa_votes=soup.find(class_='text_12zg6rl-o_O-LabelXSmall_mbug0d-o_O-votesSum_19las6u')
        if topa_votes is not None:
            topa_votes=topa_votes.text.strip()
            topa_votes=re.findall('\d+', topa_votes)
            topa_votes=topa_votes[0]
        else:
            topa_votes='0'

# infinite click on show more button for each profile link project section and then scrape data
        with webdriver.Chrome() as driver:
            wait = WebDriverWait(driver,10)
            driver.get(link+'projects')

            while True:
                try:
                    showmore = wait.until(EC.presence_of_element_located((By.CSS_SELECTOR,'[class^="showMore"] > a')))
                    driver.execute_script("arguments[0].click();",showmore)
                except Exception:
                    break

            soup = BeautifulSoup(driver.page_source,'html.parser')
            driver.quit()
            project = soup.find_all(class_='title_1usue9n')
            prjct_number = str(len(project))
            votes_spins=soup.find_all(class_='stats_35behe')
            list_votes=[]
            for votes in votes_spins:
                numbvotes=votes.text.strip()
                numbvotes=re.split(r'\s',numbvotes)
                list_votes.append(numbvotes[0])
                prjct_votes=str(sum(list(map(int, list_votes))))
            list_spins=[]
            for spins in votes_spins:
                numspins=spins.text.strip()
                numspins=re.split(r'\s',numspins)
                list_spins.append(numspins[3])
                number_spins=list(map(int, list_spins))
            number_spins = [0 if i < 0 else i for i in number_spins]
            prjct_spins=str(sum(number_spins))

        f.write(link + "," + dates + "," + points.replace("," , "") + "," + videos + "," + data['questions'] + "," + data['votes'] + "," + data['answers'] + "," + data['flags raised'] + "," + data['project help requests'] + "," + data['project help replies'] + "," + data['comments'] + "," + data['tips and thanks'] + "," + last_activity_date + "," + prjct_number + "," + prjct_votes + "," + prjct_spins + "," + topq_votes + "," + topa_votes + "," + number_badges + "," + badge_lvl1 + ',' + badge_lvl2 + ',' + badge_lvl3 + ',' + badge_lvl4 + ',' + badge_lvl5 + ',' + badge_challenge + ',' + "\n")

我尝试过的事情：

无头模式：不是很有用，因为它不会使脚本运行得更快
使用Scrapy：问题是khanacademy网站上有很多JavaScript。据我所知，Scrapy并不打算与Javascript繁重的网站一起使用。我需要无限次点击以加载更多数据（以收集最多的配置文件链接并进行项目零件抓取）。我需要Selenium来做，但是Selenium真的很慢。
创建线程：我不知道该怎么做，我发现chromedriver / selenium不是线程安全的。

您有什么建议吗？（一些代码可以帮助我理解）

所需的输出应如下所示（但有更多行）：

Answer 1

此脚本花费大量时间的一个原因是由于它发送的请求数量很高，它消耗更少时间的一种方法是限制请求数量。这可以通过使用其内部API获取配置文件数据来实现。例如：向此链接https://www.khanacademy.org/api/internal/user/discussion/summary?username=user_name&lang=en发送get请求（并将user_name更改为实际的用户名）将以JSON格式返回您需要（以及更多）的配置文件数据，而不必抓取许多资源。然后，您可以从JSON输出中提取数据，并将其转换为CSV。您将需要使用硒仅获取讨论数据并找到用户名列表。这样可以大大减少脚本的运行时间。

侧面说明：甚至模块链接也可以使用在抓取主URL时解析的JS变量来提取。该变量包含用于存储课程数据（包括链接）的JSON。

这是执行此操作的代码：

import requests
import bs4
import json

URL = "https://www.khanacademy.org/computing/computer-programming/programming#intro-to-programming"
BASE_URL = "https://www.khanacademy.org"

response = requests.get(URL)
soup = bs4.BeautifulSoup(response.content, 'lxml')

script = soup.find_all('script')[18]
script = script.text.encode('utf-8')
script = unicode(script, errors='ignore').encode('utf-8').strip()
script = script.split('{window["./javascript/app-shell-package/app-entry.js"] = ')[1]
script = script[:-2]
json_content = json.loads(script)

您可以从该JSON中提取模块链接，然后查询它们。

有没有办法让硒异步工作？

1 个答案: