Assignment 2

AI悦创原创大约 4 分钟...约 1139 字

1. 题目

Develop a Python program that reads a text file provided by the user (for example, any book in .TXT format from Project Gutenberg at https://www.gutenberg.orgopen in new window).
The program should then present the top ten keywords, their counts, and the percentage of these keywords in comparison to the total number of words in the text file. Please ensure that the program first excludes common words like a, the, and, to, from, where, what, was, when, I, you, we, us, me, and for from the total word count before proceeding to subsequent analyses and calculations.
In addition, your program should also be capable of providing the count of a specific keyword as requested by the user.

To better understand the term ‘keyword’, please refer to this website: https://www.semrush.com/blog/what-are-keywords-simple-keyword-definition/open in new window

Kindly share your Python program and the text file with my email at bernardlkb@ukm.edu.my. The deadline for Project 1 submission is 2024-01-31.

2. 解决

2.1 下载 TXT

https://www.gutenberg.orgopen in new window

# -*- coding: utf-8 -*-
# @Time    : 2024/1/28 22:09
# @Author  : AI悦创
# @FileName: a2.py
# @Software: PyCharm
# @Blog    ：https://bornforthis.cn/
# Created by Bornforthis.
import requests
from requests.exceptions import RequestException


def read_text(url: str):
    try:
        response = requests.get(url)
        if response.status_code == 200:
            return response.text
    except RequestException:
        return ''


def main():
    url = 'https://www.gutenberg.org/cache/epub/72796/pg72796.txt'
    text = read_text(url)
    print(text)


if __name__ == '__main__':
    main()

code1

# -*- coding: utf-8 -*-
# @Time    : 2024/1/28 22:09
# @Author  : AI悦创
# @FileName: a2.py
# @Software: PyCharm
# @Blog    ：https://bornforthis.cn/
# Created by Bornforthis.
import re
import collections
from typing import List, Dict, Tuple


def read_file(file_path: str) -> str:
    """读取文本文件并返回其内容"""
    with open(file_path, 'r', encoding='utf-8') as file:
        return file.read()


def preprocess_text(text: str) -> List[str]:
    """预处理文本：去除标点符号，转换为小写，并分割为单词列表"""
    text = re.sub(r'[^\w\s]', '', text)  # 移除标点符号
    text = text.lower()  # 转换为小写
    return text.split()


def filter_common_words(words: List[str], common_words: set) -> List[str]:
    """过滤掉常见单词"""
    return [word for word in words if word not in common_words]


def get_top_keywords(words: List[str], top_n: int = 10) -> List[Tuple[str, int]]:
    """获取前N个关键词及其出现次数"""
    word_count = collections.Counter(words)
    return word_count.most_common(top_n)


def get_keyword_percentage(word_counts: List[Tuple[str, int]], total_words: int) -> Dict[str, float]:
    """计算关键词占总词数的百分比"""
    return {word: (count / total_words) * 100 for word, count in word_counts}


# 常见单词列表
COMMON_WORDS = set([
    'a', 'the', 'and', 'to', 'from', 'where', 'what', 'was', 'when',
    'i', 'you', 'we', 'us', 'me', 'for'
])


# 主程序
def main(file_path: str):
    text = read_file(file_path)
    words = preprocess_text(text)
    filtered_words = filter_common_words(words, COMMON_WORDS)
    top_keywords = get_top_keywords(filtered_words)
    total_words = len(filtered_words)
    keyword_percentages = get_keyword_percentage(top_keywords, total_words)

    print("Top 10 Keywords, Counts, and Percentages:")
    for word, count in top_keywords:
        print(f"{word}: Count = {count}, Percentage = {keyword_percentages[word]:.2f}%")

    # 用户查询特定关键词
    query_word = input("Enter a keyword to find its count: ").lower()
    print(f"Count of '{query_word}': {filtered_words.count(query_word)}")


if __name__ == "__main__":
    file_path = 'pg72796.txt'
    # file_path = input("Enter the path to your text file: ")
    main(file_path)

code2

# -*- coding: utf-8 -*-
# @Time    : 2024/1/28 22:09
# @Author  : AI悦创
# @FileName: a2.py
# @Software: PyCharm
# @Blog    ：https://bornforthis.cn/
# Created by Bornforthis.
import requests
from requests.exceptions import RequestException
import re
import collections


def read_text(url: str):
    try:
        response = requests.get(url)
        if response.status_code == 200:
            return response.text
    except RequestException:
        return ''


def preprocess_text(text):
    """预处理文本：去除标点符号，转换为小写，并分割为单词列表"""
    # 方法一
    text = re.sub('[^\w\s]', '', text)  # 移除标点符号 replace

    # 方法二
    # text = text.replace(',', '')
    # text = text.replace('.', '')
    # text = text.replace('!', '')
    # text = text.replace('?', '')
    # text = text.replace(':', '')
    # text = text.replace('\\', '')
    # text = text.replace('-', '')
    # text = text.replace('“', '')
    # text = text.replace('·', '')
    # text = text.replace('‒', '')
    # text = text.replace('_', '')
    # text = text.replace('"', '')
    # text = text.replace('*', '')

    # 下面两行不动
    text = text.lower()  # 转换为小写
    return text.split()


def filter_common_words(words, common_words):
    filter_words = []
    for word in words:
        if word not in common_words:
            filter_words.append(word)
    return filter_words


def get_top_keywords(words, top_n=10):
    """获取前 N 个关键词及其出现次数"""
    word_count = collections.Counter(words)
    return word_count.most_common(top_n)


def get_keyword_percentage(word_counts, total_words):
    """计算关键词占总词数的百分比"""
    # return {word: (count / total_words) * 100 for word, count in word_counts}
    keyword_percentages = {}
    for word, count in word_counts:
        keyword_percentages[word] = (count / total_words) * 100
    return keyword_percentages


# 常见的单词列表
COMMON_WORDS = {'a', 'the', 'and', 'to', 'from', 'where', 'what', 'was', 'when', 'i', 'you', 'we', 'us', 'me', 'for'}


def main():
    url = 'https://www.gutenberg.org/cache/epub/72796/pg72796.txt'
    text = read_text(url)
    # print(text)
    words = preprocess_text(text)
    # print(words)
    # print(len(words))
    filtered_words = filter_common_words(words, COMMON_WORDS)
    # print(filtered_words)
    top_keywords = get_top_keywords(filtered_words)
    # print(top_keywords)
    total_words = len(filtered_words)
    keyword_percentages = get_keyword_percentage(top_keywords, total_words)
    # print(keyword_percentages)
    print("Top 10 Keywords, Counts, and Percentages:")
    for word, count in top_keywords:
        print(f"{word}: Count = {count}, Percentage = {keyword_percentages[word]:.2f}%")

    # 用户查询特定关键词
    query_word = input("Enter a keyword to find its count: ").lower()
    print(f"Count of '{query_word}': {filtered_words.count(query_word)}")


if __name__ == '__main__':
    main()

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