课程作业——获取全部校园新闻

作业要求：

1. 取出一个新闻列表页的全部新闻 包装成函数。
2. 获取总的新闻篇数，算出新闻总页数。
3. 获取全部新闻列表页的全部新闻详情。
4. 找一个自己感兴趣的主题，进行数据爬取，并进行分词分析。不能与其它同学雷同。

前三个要求代码如下：

import requests
from bs4 import BeautifulSoup
from datetime import datetime
import re

# 设置local是处理包含中文格式时间（%Y年%m月%d日）时报错：
# UnicodeEncodeError: 'locale' codec can't encode character '\u5e74'
# import locale
# locale.setlocale(locale.LC_CTYPE, 'chinese')


def crawlOnePageSchoolNews(page_url):
    res = requests.get(page_url)
    res.encoding = 'UTF-8'
    soup = BeautifulSoup(res.text, 'html.parser')
    news = soup.select('.news-list > li')
    for n in news:
        # print(n)
        print('**' * 5 + '列表页信息' + '**' * 10)
        print('新闻链接：' + n.a.attrs['href'])
        print('新闻标题：' + n.select('.news-list-title')[0].text)
        print('新闻描述：' + n.a.select('.news-list-description')[0].text)
        print('新闻时间：' + n.a.select('.news-list-info > span')[0].text)
        print('新闻来源：' + n.a.select('.news-list-info > span')[1].text)
        getNewDetail(n.a.attrs['href'])

def getNewDetail(href):
    print('**' * 5 + '详情页信息' + '**' * 10)
    res1 = requests.get(href)
    res1.encoding = 'UTF-8'
    soup1 = BeautifulSoup(res1.text, 'html.parser')
    if soup1.select('.show-info'): # 防止之前网页没有show_info
        news_info = soup1.select('.show-info')[0].text
    else:return
    info_list = ['来源', '发布时间', '点击', '作者', '审核', '摄影']  # 需要解析的字段
    news_info_set = set(news_info.split('\xa0')) - {' ', ''}  # 网页中的 获取后会解析成\xa0，所以可以使用\xa0作为分隔符
    # 循环打印文章信息
    for n_i in news_info_set:
        for info_flag in info_list:
            if n_i.find(info_flag) != -1:  # 因为时间的冒号采用了英文符所以要进行判断
                if info_flag == '发布时间':
                    # 将发布时间字符串转为datetime格式,方便日后存储到数据库
                    release_time = datetime.strptime(n_i[n_i.index(':') + 1:], '%Y-%m-%d %H:%M:%S ')
                    print(info_flag + ':', release_time)
                elif info_flag == '点击':  # 点击次数是通过文章id访问php后使用js写入，所以这里单独处理
                    getClickCount(href)
                else:
                    print(info_flag + ':' + n_i[n_i.index('：') + 1:])
    news_content = soup1.select('#content')[0].text
    print(news_content)  # 文章内容
    print('————' * 40)


def getClickCount(news_url):
    # http://oa.gzcc.cn/api.php?op=count&id={}&modelid=80
    # 上面链接为文章页得出访问次数的URL
    click_num_url = 'http://oa.gzcc.cn/api.php?op=count&id={}&modelid=80'
    # 通过正则表达式得出文章id
    click_num_url = click_num_url.format(re.search('_(.*)/(.*).html', news_url).group(2))
    res2 = requests.get(click_num_url)
    res2.encoding = 'UTF-8'
    # $('#todaydowns').html('5');$('#weekdowns').html('106');$('#monthdowns').html('129');$('#hits').html('399');
    # 上面为response的内容

    # 使用正则表达式的方法获取点击次数
    # res2.text[res2.text.rindex("('") + 2:res2.text.rindex("')")],不使用正则的方式
    print('点击:' + re.search("\$\('#hits'\).html\('(\d*)'\)", res2.text).group(1))


crawlOnePageSchoolNews('http://news.gzcc.cn/html/xiaoyuanxinwen/')

pageURL = 'http://news.gzcc.cn/html/xiaoyuanxinwen/{}.html'
res = requests.get('http://news.gzcc.cn/html/xiaoyuanxinwen/')
res.encoding = 'UTF-8'
soup = BeautifulSoup(res.text, 'html.parser')
newsSum = int(re.search('(\d*)条', soup.select('a.a1')[0].text).group(1))
if newsSum % 10:
    pageSum = int(newsSum/10) + 1
else:
    pageSum = int(newsSum/10)

for i in range(2, pageSum+1):
    crawlOnePageSchoolNews(pageURL.format(i))

结果截图：

第四个要求中，我爬取了校园所有的新闻描述，分析大概学校这些年干了些什么，在哪干，强调些什么，统计出词云。
主要代码如下：

import requests
from bs4 import BeautifulSoup
import re
import jieba

editors = []
descriptions = ''


def crawlOnePageSchoolNews(page_url):
    global descriptions
    res0 = requests.get(page_url)
    res0.encoding = 'UTF-8'
    soup0 = BeautifulSoup(res0.text, 'html.parser')
    news = soup0.select('.news-list > li')
    for n in news:
        print('新闻描述：' + n.a.select('.news-list-description')[0].text)
        print('新闻来源：' + n.a.select('.news-list-info > span')[1].text)
        descriptions = descriptions + ' ' + n.a.select('.news-list-description')[0].text
        editors.append(n.a.select('.news-list-info > span')[1].text.split(' ')[0])


crawlOnePageSchoolNews('http://news.gzcc.cn/html/xiaoyuanxinwen/')

pageURL = 'http://news.gzcc.cn/html/xiaoyuanxinwen/{}.html'
res = requests.get('http://news.gzcc.cn/html/xiaoyuanxinwen/')
res.encoding = 'UTF-8'
soup = BeautifulSoup(res.text, 'html.parser')
newsSum = int(re.search('(\d*)条', soup.select('a.a1')[0].text).group(1))
if newsSum % 10:
    pageSum = int(newsSum / 10) + 1
else:
    pageSum = int(newsSum / 10)

for i in range(2, pageSum+1):
    crawlOnePageSchoolNews(pageURL.format(i))

with open('punctuation.txt', 'r', encoding='UTF-8') as punctuationFile:
    for punctuation in punctuationFile.readlines():
        descriptions = descriptions.replace(punctuation[0], ' ')

with open('meaningless.txt', 'r', encoding='UTF-8') as meaninglessFile:
    mLessSet = set(meaninglessFile.read().split('\n'))
mLessSet.add(' ')

# 加载保留字
with open('reservedWord.txt', 'r', encoding='UTF-8') as reservedWordFile:
    reservedWordSet = set(reservedWordFile.read().split('\n'))
    for reservedWord in reservedWordSet:
        jieba.add_word(reservedWord)


keywordList = list(jieba.cut(descriptions))
keywordSet = set(keywordList) - mLessSet  # 将无意义词从词语集合中删除

keywordDict = {}
# 统计出词频字典
for word in keywordSet:
    keywordDict[word] = keywordList.count(word)

# 对词频进行排序
keywordListSorted = list(keywordDict.items())
keywordListSorted.sort(key=lambda e: e[1], reverse=True)
# 将所有词频写出到txt做词云分析
for topWordTup in keywordListSorted:
    print(topWordTup)
    with open('word.txt', 'a+', encoding='UTF-8') as wordFile:
        for i in range(0, topWordTup[1]):
            wordFile.write(topWordTup[0]+'\n')

经过以上处理之后将结果通过 https://wordsift.org/ 生成词云如下：

有些保留字没有处理好，所以有些事无意义词就选择性忽略
在上面中的文件已上传这里