Home Backend Development Python Tutorial The article you provided is about Python package building tools, and the evolution from Distutils to Distribute, Setuptools, and Distutils2. A fitting question-based title that focuses on the key tak

The article you provided is about Python package building tools, and the evolution from Distutils to Distribute, Setuptools, and Distutils2. A fitting question-based title that focuses on the key tak

Oct 28, 2024 pm 11:04 PM

The article you provided is about Python package building tools, and the evolution from Distutils to Distribute, Setuptools, and Distutils2.  A fitting question-based title that focuses on the key takeaway could be:

Which Python Package Building Tool Sho

Handling Package Building in Python: Distutils, Distribute, Setupextools, and Distutils2

Developers may encounter confusion when managing package building in Python due to the existence of multiple modules: distutils, distribute, setuptools, and distutils2. This article aims to clarify their differences and guide users towards the most modern solution.

Distutils: The Standard but Limited Tool

Distutils is the original package building module included in the Python standard library. It offers basic functionality for building and distributing Python packages. However, distutils has limitations, particularly in support for advanced features such as dependency management and data files packaging.

Distribute: A Fork Merged with Setuptools

Distribute emerged as a fork of setuptools, aiming to address some of distutils' shortcomings. It introduced features like dependency resolution and improved packaging options. However, distribute was later merged back into setuptools 0.7, rendering it redundant.

Setuptools: Feature-Rich and Widely Used

Setuptools was developed to overcome distutils' limitations. It enhances the distutils API, providing a more comprehensive set of features. Setuptools introduces easy_install, a command-line tool for installing packages, and pkg_resources, a module for locating data files installed with a distribution. It is widely used and plays well with pip, the preferred package manager for Python.

Distutils2: An Abandoned Project

Distutils2 was an attempt to consolidate the best features of distutils, setuptools, and distribute into a single, modern tool. However, the project is now abandoned, with its last release dating back to 2012.

Recommended Solution: Embracing Setuptools

For most users, setuptools is the recommended choice for package building. It offers a robust feature set, is well-supported, and works seamlessly with pip. Adopting setuptools simplifies package management and ensures compatibility with the latest Python versions.

Conclusion

Understanding the differences between distutils, distribute, setuptools, and distutils2 is crucial for package building in Python. While distutils is now considered deprecated, setuptools remains the industry standard. Embracing setuptools alongside pip offers a reliable and efficient solution for package building and distribution.

The above is the detailed content of The article you provided is about Python package building tools, and the evolution from Distutils to Distribute, Setuptools, and Distutils2. A fitting question-based title that focuses on the key tak. For more information, please follow other related articles on the PHP Chinese website!

Statement of this Website
The content of this article is voluntarily contributed by netizens, and the copyright belongs to the original author. This site does not assume corresponding legal responsibility. If you find any content suspected of plagiarism or infringement, please contact admin@php.cn

Hot AI Tools

Undresser.AI Undress

Undresser.AI Undress

AI-powered app for creating realistic nude photos

AI Clothes Remover

AI Clothes Remover

Online AI tool for removing clothes from photos.

Undress AI Tool

Undress AI Tool

Undress images for free

Clothoff.io

Clothoff.io

AI clothes remover

Video Face Swap

Video Face Swap

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

Hot Tools

Notepad++7.3.1

Notepad++7.3.1

Easy-to-use and free code editor

SublimeText3 Chinese version

SublimeText3 Chinese version

Chinese version, very easy to use

Zend Studio 13.0.1

Zend Studio 13.0.1

Powerful PHP integrated development environment

Dreamweaver CS6

Dreamweaver CS6

Visual web development tools

SublimeText3 Mac version

SublimeText3 Mac version

God-level code editing software (SublimeText3)

Hot Topics

Java Tutorial
1664
14
PHP Tutorial
1266
29
C# Tutorial
1239
24
Python vs. C  : Applications and Use Cases Compared Python vs. C : Applications and Use Cases Compared Apr 12, 2025 am 12:01 AM

Python is suitable for data science, web development and automation tasks, while C is suitable for system programming, game development and embedded systems. Python is known for its simplicity and powerful ecosystem, while C is known for its high performance and underlying control capabilities.

The 2-Hour Python Plan: A Realistic Approach The 2-Hour Python Plan: A Realistic Approach Apr 11, 2025 am 12:04 AM

You can learn basic programming concepts and skills of Python within 2 hours. 1. Learn variables and data types, 2. Master control flow (conditional statements and loops), 3. Understand the definition and use of functions, 4. Quickly get started with Python programming through simple examples and code snippets.

Python: Games, GUIs, and More Python: Games, GUIs, and More Apr 13, 2025 am 12:14 AM

Python excels in gaming and GUI development. 1) Game development uses Pygame, providing drawing, audio and other functions, which are suitable for creating 2D games. 2) GUI development can choose Tkinter or PyQt. Tkinter is simple and easy to use, PyQt has rich functions and is suitable for professional development.

How Much Python Can You Learn in 2 Hours? How Much Python Can You Learn in 2 Hours? Apr 09, 2025 pm 04:33 PM

You can learn the basics of Python within two hours. 1. Learn variables and data types, 2. Master control structures such as if statements and loops, 3. Understand the definition and use of functions. These will help you start writing simple Python programs.

Python vs. C  : Learning Curves and Ease of Use Python vs. C : Learning Curves and Ease of Use Apr 19, 2025 am 12:20 AM

Python is easier to learn and use, while C is more powerful but complex. 1. Python syntax is concise and suitable for beginners. Dynamic typing and automatic memory management make it easy to use, but may cause runtime errors. 2.C provides low-level control and advanced features, suitable for high-performance applications, but has a high learning threshold and requires manual memory and type safety management.

Python and Time: Making the Most of Your Study Time Python and Time: Making the Most of Your Study Time Apr 14, 2025 am 12:02 AM

To maximize the efficiency of learning Python in a limited time, you can use Python's datetime, time, and schedule modules. 1. The datetime module is used to record and plan learning time. 2. The time module helps to set study and rest time. 3. The schedule module automatically arranges weekly learning tasks.

Python: Exploring Its Primary Applications Python: Exploring Its Primary Applications Apr 10, 2025 am 09:41 AM

Python is widely used in the fields of web development, data science, machine learning, automation and scripting. 1) In web development, Django and Flask frameworks simplify the development process. 2) In the fields of data science and machine learning, NumPy, Pandas, Scikit-learn and TensorFlow libraries provide strong support. 3) In terms of automation and scripting, Python is suitable for tasks such as automated testing and system management.

Python vs. C  : Exploring Performance and Efficiency Python vs. C : Exploring Performance and Efficiency Apr 18, 2025 am 12:20 AM

Python is better than C in development efficiency, but C is higher in execution performance. 1. Python's concise syntax and rich libraries improve development efficiency. 2.C's compilation-type characteristics and hardware control improve execution performance. When making a choice, you need to weigh the development speed and execution efficiency based on project needs.

See all articles