使用Python解析文本文件

Question

我正在尝试使用Mike Robins发布的代码，但它在3.7版中失败了。

请让我知道如何解决此问题？谢谢。

How to parse complex text files using Python?

import re
import pandas as pd

parse_re = {
    'school': re.compile(r'School = (?P<school>.*)$'),
    'grade': re.compile(r'Grade = (?P<grade>\d+)'),
    'student': re.compile(r'Student number, (?P<info>\w+)'),
    'data': re.compile(r'(?P<number>\d+), (?P<value>.*)$'),
}

def parse(line):
    '''parse the line by regex search against possible line formats
       returning the id and match result of first matching regex,
       or None if no match is found'''
    return reduce(lambda (i,m),(id,rx): (i,m) if m else (id, rx.search(line)), 
                  parse_re.items(), (None,None))

    results = []
with open('sample.txt') as f:
    record = {}
    for line in f:
        id, match = parse(line)

        if match is None:
            continue

        if id == 'school':
            record['School'] = match.group('school')
        elif id == 'grade':
            record['Grade'] = int(match.group('grade'))
            names = {}  # names is a number indexed dictionary of student names
        elif id == 'student':
            info = match.group('info')
        elif id == 'data':
            number = int(match.group('number'))
            value = match.group('value')
            if info == 'Name':
                names[number] = value
            elif info == 'Score':
                record['Student number'] = number
                record['Name'] = names[number]
                record['Score'] = int(value)
                results.append(record.copy())
df = pd.DataFrame(results, columns=['School', 'Grade', 'Student number', 'Name', 'Score'])
print df