当前位置:首页 > 数码 > 找出最适合你-vs.-Anaconda-pip-环境包管理器-Python (找出最适合你的歌)

找出最适合你-vs.-Anaconda-pip-环境包管理器-Python (找出最适合你的歌)

admin3周前 (04-29)数码10

Python environment package managers are tools that help developers install, update, uninstall, and manage packages in their Python environment. They make it easier to manage the various libraries and frameworks used in Python development.

Common Python Environment Package Managers

  • pip (Python Package Manager)

    pip is the official package manager for Python. It provides an easy-to-use command-line interface for installing, updating, and uninstalling Python packages. Using pip, you can easily install various third-party libraries from the Python Package Index (PyPI), such as NumPy, Pandas, etc.

    For example, to install the NumPy library, you can use the following command:

    pip install numpy
    

    To update an already installed library, you can use the following command:

    pip install --upgrade package_name
    
  • conda (Anaconda Distribution Package Manager)

    conda is a cross-platform, multi-language package and environment manager from the Anaconda Distribution. It is primarily used in the data science and machine learning space, but can be used for other purposes as well. conda allows you to create and manage multiple environments and can easily install, update, and uninstall packages.

    For example, to create a new conda environment, you can use the following command:

    conda create --name myenv python=3.8
    

    To install the NumPy library in that environment, you can use the following command:

    conda activate myenv
    pip install numpy
    
  • pipenv (Python Dependency Management Tool)

    pipenv is a dependency management tool for Python that combines the functionality of pip and virtualenv. It helps you manage your project's dependencies and create virtual environments. pipenv can easily resolve dependency conflicts and is easy to use.

    For example, to install the NumPy library using pipenv, you can use the following command:

    pipenv install numpy
    
  • Poetry (Python Dependency Management and Packaging Tool)

    Poetry is a dependency management and packaging tool for Python. It provides an easy way to manage your project's dependencies and can easily create, switch, and manage multiple Python environments. Poetry also provides other features such as virtual environments, dependency locking, etc.

    For example, to install the NumPy library using Poetry, you can use the following command:

    poetry add numpy
    
  • PyCharm (Python Integrated Development Environment)

    PyCharm is a powerful Python integrated development environment (IDE) that provides an easy way to manage and use Python packages and frameworks. PyCharm has a built-in package manager that helps you easily install, upgrade, and manage various libraries and frameworks. You can also use PyCharm to create virtual environments and install the required packages in them.

    For example, to install the NumPy library in PyCharm,you can open the PyCharm Preferences (Settings) dialog. In the left-hand navigation, select Project: [project_name] > Python Interpreter, and then search for and install NumPy using the + button on the right-hand side.

  • Anaconda
  • Anaconda Navigator (Anaconda Distribution Package and Environment Manager)

    Anaconda Navigator is the package and environment manager for the Anaconda Distribution. It provides an easy-to-use graphical user interface (GUI) that helps you manage and use various data science and machine learning libraries and frameworks. Anaconda Navigator allows you to create and manage multiple environments and can easily install, update, and uninstall various packages.

    For example, to install the NumPy library using Anaconda Navigator, you can open the Anaconda Navigator application. In the left-hand navigation, select Environments, and then create a new environment and install NumPy using the Add Environment button on the right-hand side.

免责声明:本文转载或采集自网络,版权归原作者所有。本网站刊发此文旨在传递更多信息,并不代表本网赞同其观点和对其真实性负责。如涉及版权、内容等问题,请联系本网,我们将在第一时间删除。同时,本网站不对所刊发内容的准确性、真实性、完整性、及时性、原创性等进行保证,请读者仅作参考,并请自行核实相关内容。对于因使用或依赖本文内容所产生的任何直接或间接损失,本网站不承担任何责任。

标签: Python

“找出最适合你-vs.-Anaconda-pip-环境包管理器-Python (找出最适合你的歌)” 的相关文章

Python中的LEGB规则 (python怎样打开)

Python中的LEGB规则 (python怎样打开)

Python 中的 LEGB 规则决定了变量和函数的作用域解析顺序。它代表了四个作用域层级: 局部作用域 闭包函数外的函数 全局作用域 内置作用域...

b-b-个入门建议!-Python-技术书籍推荐-附赠-11 (b+b+b等于什么)

b-b-个入门建议!-Python-技术书籍推荐-附赠-11 (b+b+b等于什么)

近年来,Python 持续火爆,越来越多的人开始入门学习 Python。RealPython 作为最受好评的 Python 学习网站,拥有超百万的浏览量,以下是 RealPython 的开发者给...

处置日常义务的终极工具!-Python-文件读写实战 (处置行为是什么意思)

处置日常义务的终极工具!-Python-文件读写实战 (处置行为是什么意思)

/target=_blankclass=infotextkey>Python文件的读写操作时,有很多须要思考的细节,这包含文件关上形式、读取和写入数据的方法、意外处置等。 在本文中,...

Python中的Random模块-摸索随机性的神奇环球 (python编程)

Python中的Random模块-摸索随机性的神奇环球 (python编程)

随机性在计算机编程和数据迷信中表演着至关关键的角色。/target=_blankclass=infotextkey>Python中的random模块提供了丰盛的工具和函数,协助咱们生成随机数...

惰性求值和lambda表达式的强大组合-Python高级技巧 (惰性求值和逻辑短路)

惰性求值和lambda表达式的强大组合-Python高级技巧 (惰性求值和逻辑短路)

Lambda 表达式 在 Python 中,Lambda 表达式是一个匿名函数,它可以在需要函数对象的地方使用。Lambda 表达式的语法如下: lambda arguments: exp...

掌握网络世界的无限可能-Python分布式爬虫助力搜索引擎打造 (掌握网络世界的好处)

掌握网络世界的无限可能-Python分布式爬虫助力搜索引擎打造 (掌握网络世界的好处)

主从模式 主从模式是一种简单的分布式爬虫架构,其中一台主机作为控制节点,负责管理所有运行爬虫的从机。 主节点负责向从机分配任务,并接收新生成的任务。从机只需要从主节点接收任务,并把新生...

轻松把握多线程和多进程-Python编程进阶 (多线是什么意思)

轻松把握多线程和多进程-Python编程进阶 (多线是什么意思)

1、简介 咱们将讨论如何应用/target=_blankclass=infotextkey>Python口头多线程和多进程义务。它们提供了在单个进程或多个进程之间口头并发操作的方法。并...

生成-UUID-操作-Python-齐全指南-格局和经常出现疑问 (生成uuid java)

生成-UUID-操作-Python-齐全指南-格局和经常出现疑问 (生成uuid java)

UUID(UniversallyUniqueIdentifier,通用惟一标识符)是一种全局惟一标识符生成形式,用于创立举世无双的标识符。/target=_blankclass=infotextk...