


In-depth exploration of Python's underlying technology: how to implement file permission management
Deeply explore the underlying technology of Python: how to implement file permission management
- Introduction
In the operating system, file permission management It is an important safety mechanism. It allows users to control access to files, ensuring that only authorized users can read, write, and execute files. As a popular programming language, Python also provides a wealth of libraries and modules to implement file permission management.
This article will delve into the underlying technology of Python, focusing on how to use the os module and the stat module to implement file permission management. For better understanding, we will provide specific code examples.
- Representation and setting of file permissions
In UNIX and UNIX-like operating systems, file permissions can be divided into three categories: user permissions, group permissions and other permissions. Each type of permission can be divided into three operations: read, write and execute. In Python, file permissions are represented by a 12-bit binary number. Among them, every three digits represent a type of permission, from high to low, user permissions, group permissions and other permissions.
The following are some common functions for expressing and setting file permissions:
- chmod(path, mode): Set the permissions of files or directories
- stat(path ): Get the status information of the file or directory
- S_IRUSR: The user has read permission
- S_IWUSR: The user has write permission
- S_IXUSR: The user has execution permission
- S_IRGRP: The group has read permissions
- S_IWGRP: The group has write permissions
- S_IXGRP: The group has execute permissions
- S_IROTH: Others have read permissions
- S_IWOTH: Others have write permissions
- S_IXOTH: Others have execute permissions
Here is a sample code to set file permissions:
import os import stat def set_file_permission(file_path, mode): # 获取文件或目录的状态信息 file_stat = os.stat(file_path) # 修改权限 os.chmod(file_path, file_stat.st_mode | mode) # 设置文件的用户权限为可读、可写、可执行 set_file_permission("test.txt", stat.S_IRUSR | stat.S_IWUSR | stat.S_IXUSR)
- File Permission query and judgment
In addition to setting file permissions, we also need to be able to query and judge file permissions. The os module provides related functions to implement these functions.
The following are some commonly used functions for querying and judging file permissions:
- access(path, mode): Check whether the file or directory in the specified path has certain permissions
- getuid(): Get the user ID of the current user
- getgid(): Get the group ID of the current user
- S_IRUSR: The user has read permission
- S_IWUSR: User Has write permission
- S_IXUSR: User has execute permission
Here is a sample code to query file permissions:
import os import stat def check_file_permission(file_path, mode): # 检查文件是否具有某种权限 has_permission = os.access(file_path, mode) if has_permission: print("当前用户具有权限!") else: print("当前用户不具有权限!") # 查询文件是否可写 check_file_permission("test.txt", os.W_OK)
- Conclusion
This article deeply explores the underlying technology of Python, focusing on how to use the os module and the stat module to implement file permission management. We learned the functions for representing and setting file permissions, as well as the functions for querying and judging file permissions. Through studying this article, I believe readers can better understand the underlying technology of Python and be able to use it flexibly in actual development. I hope readers can further strengthen their mastery of Python's underlying technology through their own practice.
The above is the detailed content of In-depth exploration of Python's underlying technology: how to implement file permission management. For more information, please follow other related articles on the PHP Chinese website!

ThedifferencebetweenaforloopandawhileloopinPythonisthataforloopisusedwhenthenumberofiterationsisknowninadvance,whileawhileloopisusedwhenaconditionneedstobecheckedrepeatedlywithoutknowingthenumberofiterations.1)Forloopsareidealforiteratingoversequence

In Python, for loops are suitable for cases where the number of iterations is known, while loops are suitable for cases where the number of iterations is unknown and more control is required. 1) For loops are suitable for traversing sequences, such as lists, strings, etc., with concise and Pythonic code. 2) While loops are more appropriate when you need to control the loop according to conditions or wait for user input, but you need to pay attention to avoid infinite loops. 3) In terms of performance, the for loop is slightly faster, but the difference is usually not large. Choosing the right loop type can improve the efficiency and readability of your code.

In Python, lists can be merged through five methods: 1) Use operators, which are simple and intuitive, suitable for small lists; 2) Use extend() method to directly modify the original list, suitable for lists that need to be updated frequently; 3) Use list analytical formulas, concise and operational on elements; 4) Use itertools.chain() function to efficient memory and suitable for large data sets; 5) Use * operators and zip() function to be suitable for scenes where elements need to be paired. Each method has its specific uses and advantages and disadvantages, and the project requirements and performance should be taken into account when choosing.

Forloopsareusedwhenthenumberofiterationsisknown,whilewhileloopsareuseduntilaconditionismet.1)Forloopsareidealforsequenceslikelists,usingsyntaxlike'forfruitinfruits:print(fruit)'.2)Whileloopsaresuitableforunknowniterationcounts,e.g.,'whilecountdown>

ToconcatenatealistoflistsinPython,useextend,listcomprehensions,itertools.chain,orrecursivefunctions.1)Extendmethodisstraightforwardbutverbose.2)Listcomprehensionsareconciseandefficientforlargerdatasets.3)Itertools.chainismemory-efficientforlargedatas

TomergelistsinPython,youcanusethe operator,extendmethod,listcomprehension,oritertools.chain,eachwithspecificadvantages:1)The operatorissimplebutlessefficientforlargelists;2)extendismemory-efficientbutmodifiestheoriginallist;3)listcomprehensionoffersf

In Python 3, two lists can be connected through a variety of methods: 1) Use operator, which is suitable for small lists, but is inefficient for large lists; 2) Use extend method, which is suitable for large lists, with high memory efficiency, but will modify the original list; 3) Use * operator, which is suitable for merging multiple lists, without modifying the original list; 4) Use itertools.chain, which is suitable for large data sets, with high memory efficiency.

Using the join() method is the most efficient way to connect strings from lists in Python. 1) Use the join() method to be efficient and easy to read. 2) The cycle uses operators inefficiently for large lists. 3) The combination of list comprehension and join() is suitable for scenarios that require conversion. 4) The reduce() method is suitable for other types of reductions, but is inefficient for string concatenation. The complete sentence ends.


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

PhpStorm Mac version
The latest (2018.2.1) professional PHP integrated development tool

SecLists
SecLists is the ultimate security tester's companion. It is a collection of various types of lists that are frequently used during security assessments, all in one place. SecLists helps make security testing more efficient and productive by conveniently providing all the lists a security tester might need. List types include usernames, passwords, URLs, fuzzing payloads, sensitive data patterns, web shells, and more. The tester can simply pull this repository onto a new test machine and he will have access to every type of list he needs.

SublimeText3 English version
Recommended: Win version, supports code prompts!

SublimeText3 Chinese version
Chinese version, very easy to use

Safe Exam Browser
Safe Exam Browser is a secure browser environment for taking online exams securely. This software turns any computer into a secure workstation. It controls access to any utility and prevents students from using unauthorized resources.
