Python method to traverse all files in a directory
os.walk generator
os.walk(PATH), PATH is a folder path, of course you can use it. Or.../this way.
What is returned is a list of triplet elements, each element represents the content of a folder. The first one is the content of the current folder.
The returned triple represents (the working folder, the list of folders under this folder, the list of files under this folder).
So,
Get all subfolders, that is (d represents this triplet):
os.path.join(d[0],d[1]);
Get all sub-files, that is:
os.path.join(d[0],d[2]);
The following example uses two sets of loops. After traversing, a list of all file names is obtained and then all files are looped:
result = [os.path.join(dp, f) for dp, dn, fs in os.walk("_pages") for f in fs if os.path.splitext(f)[1] == '.html'] for fname in result: #do something
actually equals
result=[] for dp, dn, fs in os.walk("_pages"): for f in fs: if (os.path.splitext(f)[1] == '.html'): result.append(os.path.join(dp, f)) for fname in result: #do something
Finally determine whether the html suffix is used to obtain the file name. You can also use glob:
result = [y for x in os.walk(PATH) for y in glob.glob(os.path.join(x[0], '*.txt'))]
You can also use iterator methods:
from itertools import chain import glob result = (chain.from_iterable(glob.iglob(os.path.join(x[0], '*.txt')) for x in os.walk('.')))
Advanced
The standard file number traversal generator os.walk is both powerful and flexible. However, os.walk still lacks some detailed processing capabilities required by applications, such as selecting files according to a certain pattern and performing operations on all files (or directories). Sorting, or only traversing the current directory without entering its subdirectories, so the interface needs to be encapsulated.
import os, fnmatch def filter_files(dirname, patterns='*', single_level=False, yield_folders=False): patterns = patterns.split(';') allfiles = [] for rootdir, subdirname, files in os.walk(dirname): print subdirname allfiles.extend(files) if yield_folders: allfiles.extend(dubdirname) if single_level: break allfiles.sort() for eachpattern in patterns: for eachfile in fnmatch.filter(allfiles, eachpattern): print os.path.normpath(eachfile)
Description:
1.The difference between extend and append
Lists are implemented as classes. "Creating" a list actually instantiates a class. Therefore, lists can be manipulated in multiple ways. Lists can contain elements of any data type, and the elements in a single list do not need to be all of the same type. The append() method adds a new element to the end of the list. Accepting only one parameter, the extend() method only accepts a list as a parameter and adds each element of the parameter to the original list.
2. fnmatch module
The fnmatch module uses patterns to match file names. The pattern syntax is the same as that used in Unix shells. An asterisk (*) matches zero or more characters, and a question mark (?) matches a single character. You can also use square brackets to specify a character range, for example [0-9] represents a number, and all other characters match themselves.
1) fnmatch.fnmatch(name, pattern) method: tests whether name matches pattern and returns true/false
2) fnmatch.filter(names, pat) implements filtering or filtering of special characters in the list and returns a list of characters that match the matching pattern. Of course, names represents the list

Hot AI Tools

Undresser.AI Undress
AI-powered app for creating realistic nude photos

AI Clothes Remover
Online AI tool for removing clothes from photos.

Undress AI Tool
Undress images for free

Clothoff.io
AI clothes remover

Video Face Swap
Swap faces in any video effortlessly with our completely free AI face swap tool!

Hot Article

Hot Tools

Notepad++7.3.1
Easy-to-use and free code editor

SublimeText3 Chinese version
Chinese version, very easy to use

Zend Studio 13.0.1
Powerful PHP integrated development environment

Dreamweaver CS6
Visual web development tools

SublimeText3 Mac version
God-level code editing software (SublimeText3)

Hot Topics

PHP is mainly procedural programming, but also supports object-oriented programming (OOP); Python supports a variety of paradigms, including OOP, functional and procedural programming. PHP is suitable for web development, and Python is suitable for a variety of applications such as data analysis and machine learning.

PHP is suitable for web development and rapid prototyping, and Python is suitable for data science and machine learning. 1.PHP is used for dynamic web development, with simple syntax and suitable for rapid development. 2. Python has concise syntax, is suitable for multiple fields, and has a strong library ecosystem.

Python is more suitable for beginners, with a smooth learning curve and concise syntax; JavaScript is suitable for front-end development, with a steep learning curve and flexible syntax. 1. Python syntax is intuitive and suitable for data science and back-end development. 2. JavaScript is flexible and widely used in front-end and server-side programming.

PHP originated in 1994 and was developed by RasmusLerdorf. It was originally used to track website visitors and gradually evolved into a server-side scripting language and was widely used in web development. Python was developed by Guidovan Rossum in the late 1980s and was first released in 1991. It emphasizes code readability and simplicity, and is suitable for scientific computing, data analysis and other fields.

VS Code can run on Windows 8, but the experience may not be great. First make sure the system has been updated to the latest patch, then download the VS Code installation package that matches the system architecture and install it as prompted. After installation, be aware that some extensions may be incompatible with Windows 8 and need to look for alternative extensions or use newer Windows systems in a virtual machine. Install the necessary extensions to check whether they work properly. Although VS Code is feasible on Windows 8, it is recommended to upgrade to a newer Windows system for a better development experience and security.

VS Code can be used to write Python and provides many features that make it an ideal tool for developing Python applications. It allows users to: install Python extensions to get functions such as code completion, syntax highlighting, and debugging. Use the debugger to track code step by step, find and fix errors. Integrate Git for version control. Use code formatting tools to maintain code consistency. Use the Linting tool to spot potential problems ahead of time.

Running Python code in Notepad requires the Python executable and NppExec plug-in to be installed. After installing Python and adding PATH to it, configure the command "python" and the parameter "{CURRENT_DIRECTORY}{FILE_NAME}" in the NppExec plug-in to run Python code in Notepad through the shortcut key "F6".

VS Code extensions pose malicious risks, such as hiding malicious code, exploiting vulnerabilities, and masturbating as legitimate extensions. Methods to identify malicious extensions include: checking publishers, reading comments, checking code, and installing with caution. Security measures also include: security awareness, good habits, regular updates and antivirus software.
