如何同时用python处理多个文本生成词云图，这篇文章就够了_python词云可以合并文本吗

# -*- coding: utf-8 -*-
"""
Created on Wed Apr 22 21:22:42 2020

@author: Administrator
"""

# -*- coding: utf-8 -*-
"""
Created on Wed Apr 22 18:08:04 2020

@author: Administrator
"""
import os
import jieba  
from collections import Counter
from wordcloud import WordCloud
import numpy as np
from PIL import Image
import string



#去除标点符号

#打开文件，读取文字内容
class Wordcloud():
    def __init__(self,
            path, 
            back_coloring_path,
            save_path,            
            width,
            height,
            max_words,
            min_length,
            stop_words,
            background_color = 'white',
            font_path = "simhei.ttf",
            cut_all = True,
            ):
        self.path = path
        self.save_path = save_path
        self.back_coloring_path = np.array(Image.open(back_coloring_path))
        self.width = width
        self.height = height
        self.stop_words = stop_words
        self.cut_all = cut_all
        self.max_words = max_words
        self.font_path = font_path
        self.background_color = background_color
        self.min_length = min_length
        
    #去除标点符号
    def replace_punctutation(self,word):
        #定义中文标点符号
        punctutations = ['【','】','《','》','：','，','（','）','、','！','？','“','”',"。",".","/","%","；"]
        #去除中文标点符号
        for i in punctutations:
            word.replace(i, "")
        #去除英文标点符号
        for j in string.punctuation:
            word.replace(i, "")
        return word
    
    #打开文件，读取文字内容
    def __open_split_file(self, path):        
        #合并所有txt文件内容
        file_path = self.join_txt(path)
        file_words = self.open_file(file_path)
        return self.__seg_words(file_words)#调用__seg_words方法
    
    #打开文件
    def open_file(self,path):
        file_words = []
        with open(path,'r', encoding='gbk') as f:
            for i in f.readlines():#逐行读入到file_words中
                i = ''.join(i.split())
                file_words.append(i)
        return file_words
    
    #进行分词       
    def __seg_words(self,file_words):
        seg_lists = []
        for i in file_words:
            seg_list = jieba.cut(i,cut_all = self.cut_all)#进行分词，cut_all=True的话分词更精细一些
            seg_lists.extend(seg_list) 
        #遍历每一行
        results = []
        for result in seg_lists:
            result = self.replace_punctutation(result)#去除标点符号
            if self.stop_words:
                result = self.delet_words(result)  #删除指定词
            results.append(result)      
        if "" in results:
            results.remove('')#去除空值

        return results
    def delet_words(self,word):
        for i in self.stop_words:  #停用词语
            if i in word:
                word = ""
        return word
        
    #统计词频
    def __count_words(self,results):
        counter = Counter()#初始化一个计数器 
        for word in results:
            if len(word) >= self.min_length and word != '\n':
                counter[word] += 1
        return counter

    def word_cloud_and_count_words(self):
        """
        生成词云图片
        统计词频
        """
        words = self.__open_split_file(self.path)#调用open_split_file方法，进行分词
        #统计词频
        counter = self.__count_words(words)#调用count_words方法
        text = ' '.join(words)
        wordcloud = WordCloud(          #初始化词云对象
                background_color = self.background_color,
                width = self.width,
                height= self.height,
                margin = 2,
                max_words = self.max_words,
                mask = self.back_coloring_path,
                font_path = self.font_path,
                random_state= 100)  #设置随机生成多少种配色方案
        #调用生成词云图方法
        word_cloud = wordcloud.generate(text)
        #转换成图片
        image = word_cloud.to_image()
        #保存图片
        image.save(self.save_path)      
        return counter,image
    
    def join_txt(self,path):
        '''
        合并所有的txt文件并写入到一个文件中
        '''
        #找出当前目录下所有的文件
        file_names = os.listdir(path)
        file = open(os.path.join(path,'results.txt'), 'w')
        for file_name in file_names:
            if ".txt" not in file_name: #如果后缀不是.txt,直接结束当前迭代，进入下一次迭代
                continue
            else:
                file_path = os.path.join(path,file_name)
                #遍历单个文件，读取每行内容
                for line in open(file_path, encoding='utf-8'):
                    file.writelines(line)
                file.write('\n') #每个txt文件的内容用回车键隔开
        file.close()
        #results文件的绝对路径
        path = os.path.join(path,'results.txt')
        return path

if __name__ == "__main__":
    #参数
    args = {
    "path" : "D:\\cloud_words\\",  # 文本所在的文件夹相对路径
    "back_coloring_path" : "D:\\cloud_words\\爱心.png", #背景图路径
    "save_path": "D:\\cloud_words\\词云图.png", #词云图文件保存路径
    "background_color" : "white", #词云背景图颜色，默认是白色
    "font_path" : "simhei.ttf", #字体，默认是黑体
    "cut_all" : False, #是否全分，默认是True 
    "width" : 300,      #词云图的宽度
    "height" : 400,     #词云图的高度
    "max_words" : 100,#最多显示多少词
    "min_length":2,#词语最短长度
    "stop_words":None #停用词语，直接往里添加list
    }
    word_cloud = Wordcloud(**args)
    counter, image = word_cloud.word_cloud_and_count_words()
    print(counter)
    image.show()
    
    


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文本内容
假如你不够快乐
作者：汪国真

也不要把眉头深锁
人生本来短暂
为什么 还要栽培苦涩

打开尘封的门窗
让阳光雨露洒遍每个角落
走向生命的原野
让风儿熨平前额

博大可以稀释忧愁
深色能够覆盖浅色
背景图

最终效果如下

Counter({'假如': 1, '不够': 1, '快乐': 1, '作者': 1, '汪国真': 1, '不要': 1, '眉头': 1, '深锁': 1, '人生': 1, '本来': 1, '短暂': 1, '为什么': 1, '还要': 1, '栽培': 1, '苦涩': 1, '打开': 1, '尘封': 1, '门窗': 1, '阳光雨露': 1, '洒遍': 1, '每个': 1, '角落': 1, '走向': 1, '生命': 1, '原野': 1, '风儿': 1, '熨平': 1, '前额': 1, '博大': 1, '可以': 1, '稀释': 1, '忧愁': 1, '深色': 1, '能够': 1, '覆盖': 1, '浅色': 1})
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