Python爬虫案例五：将获取到的文本生成词云图

基础知识：

# 词云图 wordcloud
# 1、导包 jieba  wordcloud
import jieba
from wordcloud import WordCloud
data = '全年经济社会发展主要目标任务圆满完成'
data_list = list(jieba.cut(data))
# print(data_list)  # generator数据类型# 2、构造词云图样式  ===》虚拟的词云图
wb = WordCloud(width=500,height=500,background_color='white',font_path='C:\Windows\Fonts\msyh.ttc'  //window中找到此路径，字体为微软雅黑
)
# 3、添加数据
wb.generate(' '.join(data_list))  # 这里的字符串是否已经进行了切割
# 4、虚拟词云图保存到本地，注意：名字必须要用png,png属于无损压缩，jpg属于有损压缩
wb.to_file('xxx.png')  

案例实战：

源码：
# 抓取政府工作报告的文本
import requests, os, jieba, numpy
from lxml import etree
from wordcloud import WordCloud
from PIL import Image  # 装库：pip install pillow
class OneSpider(object):def __init__(self):passdef  request_start_url(self):# 爬虫部分start_url = 'https://www.ynbdm.cn/news.php'cookies = {'PHPSESSID': 'rpkr2o2rots8pe0mr9dp0kn0d1',}headers = {'accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,image/avif,image/webp,image/apng,*/*;q=0.8,application/signed-exchange;v=b3;q=0.7','accept-language': 'zh-CN,zh;q=0.9','cache-control': 'max-age=0',# 'cookie': 'PHPSESSID=rpkr2o2rots8pe0mr9dp0kn0d1','priority': 'u=0, i','sec-ch-ua': '"Not/A)Brand";v="8", "Chromium";v="126", "Google Chrome";v="126"','sec-ch-ua-mobile': '?0','sec-ch-ua-platform': '"Windows"','sec-fetch-dest': 'document','sec-fetch-mode': 'navigate','sec-fetch-site': 'none','sec-fetch-user': '?1','upgrade-insecure-requests': '1','user-agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/126.0.0.0 Safari/537.36',}params = {'id': '31039',}response = requests.get(start_url, params=params, cookies=cookies, headers=headers).textself.parse_response(response)def parse_response(self, response):# 解析响应A = etree.HTML(response)# bt = A.xpath('//title/text()')[0].replace('！', '')nr = A.xpath('//div[@class="content_show"]//text()')nr = ''.join(nr)with open('政府工作报告.txt', 'w', encoding='utf-8') as f:f.write(nr)print('ok -- 政府工作报告.txt')def show_image(self):# 词云图部分# --------1、读文本-------------data = open('政府工作报告.txt', 'r', encoding='utf-8').read()# --------2、jieba切割-----------data_list = list(jieba.cut(data))# --------3、粗略处理文本---------data_list = [i for i in data_list if len(i) != 1]# --------4、精确处理文本（过滤敏感信息，称为停用词）----------tyc = open('../stop_words.txt', 'r', encoding='utf-8').read()tyc = tyc.split('\n')data_list = [i for i in data_list if i not in tyc]# print(data_list)# ------------------5、文本变字符串-------------TEXT = ' '.join(data_list)# --------6、添加一个背景图片------------------img = Image.open('../Y.jpg')  # 此处的image为一个数据类型mask = numpy.array(img)  # 得到矩阵形式的图片，[255 255 255 ... 255 255 255]代表RGB的含量# --------7、建立词云图样式------------------------wb = WordCloud(width=500,height=500,background_color='white',mask=mask,font_path='C:\Windows\Fonts\msyh.ttc',)# -------8、添加数据---------------wb.generate(TEXT)#--------9、生成本地效果-------------wb.to_file('第二个.png')print('------词云图生成完毕-----------')def main(self):if not os.path.exists('政府工作报告.txt'):self.request_start_url()else:self.show_image()if __name__ == '__main__':on = OneSpider()on.main()

运行效果：

# 样式