[英]Reading multiple txt files from multiple folders
I have 20 folders, each containing 50 txt files, I need to read all of them in order to compare the word counts of each folder.我有 20 个文件夹,每个文件夹包含 50 个 txt 文件,我需要阅读所有文件夹以比较每个文件夹的字数。 I know how to read multiple files in one folder, but it is slow, is there a more efficient way instead of reading the folder one by one like below?
我知道如何读取一个文件夹中的多个文件,但是速度很慢,有没有更有效的方法,而不是像下面这样一个一个地读取文件夹?
import re
import pandas as pd
import seaborn as sns
from matplotlib import pyplot as plt
import os
import glob
1. folder1
folder_path = '/home/runner/Final-Project/folder1'
for filename in glob.glob(os.path.join(folder_path, '*.txt')):
with open(filename, 'r') as f:
text = f.read()
print (filename)
print (len(text))
2. folder2
folder_path = '/home/runner/Final-Project/folder2'
for filename in glob.glob(os.path.join(folder_path, '*.txt')):
with open(filename, 'r') as f:
text = f.read()
print (filename)
print (len(text))
You can do something similar using glob
like you have, but with the directory names.您可以像使用
glob
一样执行类似的操作,但使用目录名称。
folder_path = '/home/runner/Final-Project'
for filename in glob.glob(os.path.join(folder_path,'*','*.txt')):
# process your files
The first '*'
in the os.path.join()
represents directories of any name. os.path.join()
中的第一个'*'
代表任何名称的目录。 So calling glob.glob()
like this will go through and find any text file in any directory within folder_path
因此,像这样调用
glob.glob()
将通过 go 并在folder_path
内的任何目录中找到任何文本文件
Below function will return list of files in all the directories and sub-directories without using glob. function 下面将返回所有目录和子目录中的文件列表,而不使用 glob。 Read from the list of files and open to read.
从文件列表中读取并打开读取。
def list_of_files(dirName):
files_list = os.listdir(dirName)
all_files = list()
for entry in files_list:
# Create full path
full_path = os.path.join(dirName, entry)
if os.path.isdir(full_path):
all_files = all_files + list_of_files(full_path)
else:
all_files.append(full_path)
return all_files
print(list_of_files(<Dir Path>)) # <Dir Path> ==> your directory path
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