【详解Anaconda 、多环境安装多个不同python版本以及根据需要切换python版本】

前言

本文旨在详细介绍Anaconda 以及 如何在Anaconda上更换python版本。

备注： 根据读者建议，这里明确如下：
标题中的“在Anaconda上更换python版本”实际上是指：通过创建新的环境，得到自己想要的Python版本环境，而非在现有的环境中修改Python版本（这个应该也比较简单，参考我另外一篇博客：在当前conda env（conda环境）内修改Python的版本（升级或者降级），当然，仅供参考）。

1 Anaconda具体是用来干什么的

根据其主页介绍：https://www.anaconda.com/what-is-anaconda/

Anaconda - The Most Popular Python Data Science Platform
Anaconda Distribution - With over 6 million users, the open source Anaconda Distribution is the fastest and easiest way to do Python and R data science and machine learning on Linux, Windows, and Mac OS X. It’s the industry standard for developing, testing, and training on a single machine.

Anaconda是最流行的数据科学平台。但这个还不能解释性质上的问题。

根据wiki百科，https://en.wikipedia.org/wiki/Anaconda_(Python_distribution)

Anaconda is a free and open source[5] distribution of the Python and R programming languages for data science and machine learning related applications (large-scale data processing, predictive analytics, scientific computing), that aims to simplify package management and deployment. Package versions are managed by the package management system conda.[6] The Anaconda distribution is used by over 6 million users, and it includes more than 250 popular data science packages suitable for Windows, Linux, and MacOS.[5]

这下就更清楚了，Anaconda是一个免费，开源的针对数据科学处理和机器学习相关应用的Python和R语言的发行版。Anaconda发行版被6百万人使用，而且它包括了超过250个流行的数据科学处理包（适用于各个平台）。

Anaconda distribution comes with more than 1,000 data packages as well as the Conda package and virtual environment manager, called Anaconda Navigator [7], so it eliminates the need to learn to install each library independently.

Anaconda = 超过1000个数据包 + Conda package + virtual envir