Python词云词频统计函数未达预期要求，求定位遗漏问题

原代码核心问题 #

• 标点处理逻辑完全错误：split() 拆分得到的单词很多会携带附着的标点（比如example,、hello!），原代码直接判断整个单词是否在标点列表中无法过滤这类附着标点，且对列表类型的words调用字符串replace()方法会直接触发语法报错。同时未清理标点就判断isalpha()，会把携带标点的有效单词直接过滤掉。
• 词频统计逻辑错误：首次出现的单词被赋值为0，仅第二次及之后出现才累加计数，所有单词的统计频率都会比实际值少1，首次出现的单词频率直接为0不会被词云渲染。
• 函数返回值不符合要求：需求明确要求calculate_frequencies返回词频字典，原代码最终返回的是词云图片数组，不符合后续模块调用要求。

修正后的完整代码 #

import wordcloud

def calculate_frequencies(file_contents):
    # 标点符号与停用词列表
    punctuations = '''!()-[]{};:'"\,<>./?@#$%^&*_~'''
    uninteresting_words = ["the", "a", "to", "if", "is", "it", "of", "and", "or", "an", "as", "i", "me", "my",
    "we", "our", "ours", "you", "your", "yours", "he", "she", "him", "his", "her", "hers", "its", "they", "them",
    "their", "what", "which", "who", "whom", "this", "that", "am", "are", "was", "were", "be", "been", "being",
    "have", "has", "had", "do", "does", "did", "but", "at", "by", "with", "from", "here", "when", "where", "how",
    "all", "any", "both", "each", "few", "more", "some", "such", "no", "nor", "too", "very", "can", "will", "just",
    "in", "for", "so" ,"on", "says", "not", "into", "because", "could", "out", "up", "back", "about"]
    
    frequencies = {}
    words = file_contents.split()
    
    for item in words:
        # 统一转小写
        item = item.lower()
        # 移除单词中所有标点符号
        cleaned_item = ''.join([char for char in item if char not in punctuations])
        # 过滤非全字母单词、停用词
        if cleaned_item.isalpha() and cleaned_item not in uninteresting_words:
            # 累加词频
            frequencies[cleaned_item] = frequencies.get(cleaned_item, 0) + 1
    
    # 若需要直接生成词云可保留以下代码，否则直接返回frequencies即可符合输出字典的要求
    # cloud = wordcloud.WordCloud()
    # cloud.generate_from_frequencies(frequencies)
    # return cloud.to_array()

    # 符合需求的返回值：词频字典
    return frequencies

内容的提问来源于stack exchange，提问作者madmulchr