To list all files in a directory, Python provides multiple methods, mainly three ways: 1. Use os.listdir() to quickly list files and subdirectories in directories; 2. Use os.walk() to recursively list all files in directories and their subdirectories; 3. Use pathlib.Path to be more modern and clearer syntax. 1. os.listdir() is simple and straightforward, returning a list of strings, but does not distinguish between files and directories, nor does it recurse subdirectories. Files can be filtered through os.path.isfile(); 2. os.walk() recursively finds all hierarchical files through traversal, suitable for batch processing or searching for specific types of files; 3. pathlib.Path handles paths in an object-oriented manner, with more readable syntax, supports chain calls and wildcard matching, and its iterdir() method can list the current directory file, and rglob() can recursively find all files. If you need to filter a specific type of file, you can do it through the endswith() or glob() method. Different methods return different data types, so pay attention to the processing method.
To list all files in a directory, Python provides a variety of methods, most commonly using the os
or pathlib
modules. These two methods have their own advantages, and the specific choice depends on your project style and needs.

Using os.listdir() is simple and straightforward
If you only need to obtain all the files and subdirectory names in a certain directory, os.listdir()
is the most basic and direct method.
import os files = os.listdir('.') print(files)
This code lists all file and folder names in the current directory, and returns a list of strings. Note that it does not distinguish between files and directories, nor does it recurse subdirectories.

Tips:
- The parameter
'.'
represents the current directory, and can also be replaced with other paths such as'my_folder'
- If you only want to see the files, you can use
os.path.isfile()
for filtering
Use os.walk() to get all files in the directory (including subdirectories)
If you need to recursively list all files in a directory and its subdirectories, os.walk()
is a good choice.

import os for root, dirs, files in os.walk('.'): for file in files: print(os.path.join(root, file))
This will traverse all levels of files in the current directory and print the full path. This method is especially suitable for handling the entire folder structure.
Common uses:
- Batch processing of files (such as renaming, copying)
- Find files of a specific type (such as all
.txt
files)
Use pathlib.Path is more modern and easier to read
Starting from Python 3.4, it is recommended to use the pathlib
module, which handles paths in an object-oriented manner and has clearer syntax.
from pathlib import Path files = [f for f in Path('.').iterdir() if f.is_file()] print(files)
This code lists all files in the current directory (excluding files in subdirectories). If you want to recursively search, you can use rglob()
:
files = list(Path('.').rglob('*')) print(files)
This lists all files and folders in the current directory and subdirectories.
Advantages:
- More modern syntax and more readable
- Supports chain calls and wildcard matching (such as
**/*.txt
)
Tips: List only specific types of files
Regardless of the way you use, if you want to list only some type of files, such as all .py
files, you can handle it like this:
- Check with
os.listdir()
suffix:
py_files = [f for f in os.listdir('.') if f.endswith('.py')]
- Using
pathlib
'sglob()
:
py_files = list(Path('.').glob('*.py'))
Or recursive search:
py_files = list(Path('.').rglob('*.py'))
Basically these methods are all, just select the appropriate function according to your specific needs. It is not complicated but easy to ignore that the data types returned by different methods are slightly different, such as os.listdir()
returns a string, while Pathlib
's method returns a Path
object. Pay attention to conversion or use the corresponding method when processing.
The above is the detailed content of How to list all files in a directory in Python. For more information, please follow other related articles on the PHP Chinese website!

Hot AI Tools

Undress AI Tool
Undress images for free

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

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

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)

Polymorphism is a core concept in Python object-oriented programming, referring to "one interface, multiple implementations", allowing for unified processing of different types of objects. 1. Polymorphism is implemented through method rewriting. Subclasses can redefine parent class methods. For example, the spoke() method of Animal class has different implementations in Dog and Cat subclasses. 2. The practical uses of polymorphism include simplifying the code structure and enhancing scalability, such as calling the draw() method uniformly in the graphical drawing program, or handling the common behavior of different characters in game development. 3. Python implementation polymorphism needs to satisfy: the parent class defines a method, and the child class overrides the method, but does not require inheritance of the same parent class. As long as the object implements the same method, this is called the "duck type". 4. Things to note include the maintenance

Iterators are objects that implement __iter__() and __next__() methods. The generator is a simplified version of iterators, which automatically implement these methods through the yield keyword. 1. The iterator returns an element every time he calls next() and throws a StopIteration exception when there are no more elements. 2. The generator uses function definition to generate data on demand, saving memory and supporting infinite sequences. 3. Use iterators when processing existing sets, use a generator when dynamically generating big data or lazy evaluation, such as loading line by line when reading large files. Note: Iterable objects such as lists are not iterators. They need to be recreated after the iterator reaches its end, and the generator can only traverse it once.

The key to dealing with API authentication is to understand and use the authentication method correctly. 1. APIKey is the simplest authentication method, usually placed in the request header or URL parameters; 2. BasicAuth uses username and password for Base64 encoding transmission, which is suitable for internal systems; 3. OAuth2 needs to obtain the token first through client_id and client_secret, and then bring the BearerToken in the request header; 4. In order to deal with the token expiration, the token management class can be encapsulated and automatically refreshed the token; in short, selecting the appropriate method according to the document and safely storing the key information is the key.

A common method to traverse two lists simultaneously in Python is to use the zip() function, which will pair multiple lists in order and be the shortest; if the list length is inconsistent, you can use itertools.zip_longest() to be the longest and fill in the missing values; combined with enumerate(), you can get the index at the same time. 1.zip() is concise and practical, suitable for paired data iteration; 2.zip_longest() can fill in the default value when dealing with inconsistent lengths; 3.enumerate(zip()) can obtain indexes during traversal, meeting the needs of a variety of complex scenarios.

InPython,iteratorsareobjectsthatallowloopingthroughcollectionsbyimplementing__iter__()and__next__().1)Iteratorsworkviatheiteratorprotocol,using__iter__()toreturntheiteratorand__next__()toretrievethenextitemuntilStopIterationisraised.2)Aniterable(like

Assert is an assertion tool used in Python for debugging, and throws an AssertionError when the condition is not met. Its syntax is assert condition plus optional error information, which is suitable for internal logic verification such as parameter checking, status confirmation, etc., but cannot be used for security or user input checking, and should be used in conjunction with clear prompt information. It is only available for auxiliary debugging in the development stage rather than substituting exception handling.

TypehintsinPythonsolvetheproblemofambiguityandpotentialbugsindynamicallytypedcodebyallowingdeveloperstospecifyexpectedtypes.Theyenhancereadability,enableearlybugdetection,andimprovetoolingsupport.Typehintsareaddedusingacolon(:)forvariablesandparamete

To create modern and efficient APIs using Python, FastAPI is recommended; it is based on standard Python type prompts and can automatically generate documents, with excellent performance. After installing FastAPI and ASGI server uvicorn, you can write interface code. By defining routes, writing processing functions, and returning data, APIs can be quickly built. FastAPI supports a variety of HTTP methods and provides automatically generated SwaggerUI and ReDoc documentation systems. URL parameters can be captured through path definition, while query parameters can be implemented by setting default values ??for function parameters. The rational use of Pydantic models can help improve development efficiency and accuracy.
