Python实现TXT文件行枚举及指定列值求和问题求助

我是Python新手，尝试读取Windows/Mac系统下的Your_Wordle_Results.txt文件，想要对1pt列的4、1、4三个数值求和，但当前代码未正确遍历目标行，导致结果为4×3。请求添加枚举类功能以实现正确求和。

原代码 #

import os
import platform

pathwindows = os.environ['USERPROFILE'] + r"\Documents\Your_Wordle_Results.txt"
pathmac = r'/Mac/Users/%USEPROFILE%/Documents/Your_Wordle_Results.txt'
isFileWindows = os.path.exists(pathwindows)
isFileMac = os.path.isfile(pathmac)

if isFileWindows == True:
    outfile = open(pathwindows, 'r')

if isFileMac == True:
    outfile = open(pathmac, 'r')

totalpoints1 = 0
totalpoints2 = 0
totalpoints3 = 0
totalpoints4 = 0
totalpoints5 = 0

with open(pathwindows, 'r') as fp:
    lineofinterest = fp.readlines()[2:100]
    stringlineofinterest = str(lineofinterest)
    print(*lineofinterest)
    for line in lineofinterest:
        print(line.strip())

    startline = 22
    separation = 4
    value1 = (stringlineofinterest[startline + separation * 0])
    value2 = (stringlineofinterest[startline + separation * 1])
    value3 = (stringlineofinterest[startline + separation * 2])
    value4 = (stringlineofinterest[startline + separation * 3])
    value5 = (stringlineofinterest[startline + separation * 4])

outfile.close   

print(value1)

print(totalpoints1)

TXT文件内容 #

Ben        Jackson    
                    1pt 2pt 3pt 4pt 5pt                    Total Results Will Be Shown Below
                    4   3   0   1   0   LOSS for audio in 7.28s
                    1   2   0   2   0   LOSS for audit in 6.18s
                    4   5   0   1   0   LOSS for audio in 7.28s

修复后的代码 #

import os
from enum import Enum

# 用枚举类定义各分数列的索引，提升代码可读性和可维护性
class PointsColumn(Enum):
    PT1 = 0  # 1pt列对应的索引
    PT2 = 1
    PT3 = 2
    PT4 = 3
    PT5 = 4

# 处理跨平台文件路径
def get_file_path():
    if os.name == 'nt':  # Windows系统
        return os.path.join(os.environ['USERPROFILE'], 'Documents', 'Your_Wordle_Results.txt')
    else:  # Mac/Linux系统
        return os.path.join(os.environ['HOME'], 'Documents', 'Your_Wordle_Results.txt')

file_path = get_file_path()

total_points = {col: 0 for col in PointsColumn}

# 读取文件并计算各列总和
with open(file_path, 'r') as fp:
    lines = fp.readlines()
    # 从第3行开始读取有效数据行（索引从0开始，跳过前两行）
    data_lines = lines[2:]
    for line in data_lines:
        # 分割行内容，过滤空字符串，提取数值部分
        parts = list(filter(None, line.strip().split()))
        if len(parts) >= 5:  # 确保有足够的数值列
            # 累加1pt列的数值
            total_points[PointsColumn.PT1] += int(parts[PointsColumn.PT1.value])
            # 其他列如果需要也可以累加
            total_points[PointsColumn.PT2] += int(parts[PointsColumn.PT2.value])
            total_points[PointsColumn.PT3] += int(parts[PointsColumn.PT3.value])
            total_points[PointsColumn.PT4] += int(parts[PointsColumn.PT4.value])
            total_points[PointsColumn.PT5] += int(parts[PointsColumn.PT5.value])

# 输出1pt列的总和
print(f"1pt列总和: {total_points[PointsColumn.PT1]}")
# 其他列总和也可以按需输出
# print(f"2pt列总和: {total_points[PointsColumn.PT2]}")

关键改进说明 #

1. 枚举类的使用：通过PointsColumn枚举定义各分数列的索引，避免硬编码数字，后续修改列顺序时只需调整枚举值即可，大幅提升代码可维护性。
2. 跨平台路径处理：用os.name判断系统类型，结合os.path.join生成标准路径，同时修正了原Mac路径的错误（原代码错误使用%USEPROFILE%，改为os.environ['HOME']获取用户目录）。
3. 正确的行遍历与数值提取：放弃原代码中硬索引取字符的错误方式，通过分割每行内容提取有效数值，遍历所有数据行累加对应列的数值，确保求和结果正确。
4. 文件资源管理：统一使用with语句处理文件，自动关闭文件，避免资源泄漏问题。

内容的提问来源于stack exchange，提问作者Ben Jackson