如果您将每个输入文件读取为CSV（尽管文件扩展名为.txt，但问题似乎暗示了这一点），那么您只需要从每个输入文件创建一个dataframe，然后将它们连接起来以生成输出文件，如下所示：

from glob import glob
import os
import pandas

SRC_DIR = '/Volumes/G-Drive/Data'
OUTPUT_FILE = '/Volumes/G-Drive/output.txt'
DELIMITER = '/'

dflist = []

for file in glob(os.path.join(SRC_DIR, '*.txt')):
    dflist.append(pandas.read_csv(file, delimiter=DELIMITER))

df = pandas.concat(dflist, ignore_index=True)

df.to_csv(OUTPUT_FILE, sep=DELIMITER, index=False)

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如果你不想使用 pandas，那么就像这样简单：

with open(OUTPUT_FILE, 'w') as output:
    for file in glob(os.path.join(SRC_DIR, '*.txt')):
        with open(file) as data:
            header = next(data)
            if output.tell() == 0:
                output.write(header)
            for row in data:
                output.write(row)

型

如果所有.txt文件都具有相同的结构，则可以在第二个循环中添加一个条件，以便对于除第一个文件之外的每个文件，跳过第一行：

import pandas
import glob
file_names = glob.glob("./*.txt")
with open('output_file.txt', 'w') as out_file:
    for index, i in enumerate(file_names):
        if index == 0:  # First file
            with open(i) as in_file:
                for j in in_file:
                    out_file.write(j)
        else:  # The rest of the files
            with open(i) as in_file:
                for j in in_file:
                    if 'Sales' in j:
                        continue  # Skip the row containing 'Sales'
                    else:
                        out_file.write(j)
data = pandas.read_csv("output_file.txt", delimiter='/')

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