Anaconda更新最新版本、下载慢问题及更新conda版本

一、下载最新Anaconda版本两种方法

1.Anaconda官网

官网
之前一篇有介绍怎么下载点击。

2.清华大学开源软件镜像站
https://mirrors.tuna.tsinghua.edu.cn/anaconda/archive/?C=M&O=D
清华镜像源网站
Anaconda更新最新版本、下载慢问题及更新conda版本_第1张图片

二、Anaconda环境里下载速度都比较慢

输入conda info查看一些信息

(base) C:\Users\Administrator>conda info
     active environment : base
    active env location : D:\Anaconda
            shell level : 1
       user config file : C:\Users\Administrator\.condarc
 populated config files : C:\Users\Administrator\.condarc
          conda version : 4.5.11
    conda-build version : 3.15.1
         python version : 3.7.0.final.0
       base environment : D:\Anaconda  (writable)
           channel URLs : https://repo.anaconda.com/pkgs/main/win-64
                          https://repo.anaconda.com/pkgs/main/noarch
                          https://repo.anaconda.com/pkgs/free/win-64
                          https://repo.anaconda.com/pkgs/free/noarch
                          https://repo.anaconda.com/pkgs/r/win-64
                          https://repo.anaconda.com/pkgs/r/noarch
                          https://repo.anaconda.com/pkgs/pro/win-64
                          https://repo.anaconda.com/pkgs/pro/noarch
                          https://repo.anaconda.com/pkgs/msys2/win-64
                          https://repo.anaconda.com/pkgs/msys2/noarch
          package cache : D:\Anaconda\pkgs
                          C:\Users\Administrator\AppData\Local\conda\conda\pkgs
       envs directories : D:\Anaconda\envs
                          C:\Users\Administrator\AppData\Local\conda\conda\envs
                          C:\Users\Administrator\.conda\envs
               platform : win-64
             user-agent : conda/4.5.11 requests/2.19.1 CPython/3.7.0 Windows/10 Windows/10.0.19041
          administrator : True
             netrc file : None
           offline mode : False

解决办法:

1.添加国内镜像源
下面解释什么是镜像源
运行Anaconda Prompt

conda config --add channels https://mirrors.ustc.edu.cn/anaconda/pkgs/free/

conda config --add channels https://mirrors.ustc.edu.cn/anaconda/pkgs/main/

2.设置启动设置好的国内镜像源
conda config --set show_channel_urls yes

3.查看是否添加上了源
conda config --show

4.如果镜像源失效了,或者想换成其他的源,怎么删除呢?
conda config --remove channels https://mirrors.ustc.edu.cn/anaconda/pkgs/free/
conda config --remove channels https://mirrors.ustc.edu.cn/anaconda/pkgs/main/

(pytorch36) C:\Users\Administrator>conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free/

(pytorch36) C:\Users\Administrator>conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main/

(pytorch36) C:\Users\Administrator>conda config --set show_channel_urls yes

(pytorch36) C:\Users\Administrator>conda info

     active environment : pytorch36
    active env location : D:\Anaconda\envs\pytorch36
            shell level : 2
       user config file : C:\Users\Administrator\.condarc
 populated config files : C:\Users\Administrator\.condarc
          conda version : 4.5.11
    conda-build version : 3.15.1
         python version : 3.7.0.final.0
       base environment : D:\Anaconda  (writable)
           channel URLs : https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main/win-64
                          https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main/noarch
                          https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free/win-64
                          https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free/noarch
                          https://repo.anaconda.com/pkgs/main/win-64
                          https://repo.anaconda.com/pkgs/main/noarch
                          https://repo.anaconda.com/pkgs/free/win-64
                          https://repo.anaconda.com/pkgs/free/noarch
                          https://repo.anaconda.com/pkgs/r/win-64
                          https://repo.anaconda.com/pkgs/r/noarch
                          https://repo.anaconda.com/pkgs/pro/win-64
                          https://repo.anaconda.com/pkgs/pro/noarch
                          https://repo.anaconda.com/pkgs/msys2/win-64
                          https://repo.anaconda.com/pkgs/msys2/noarch
          package cache : D:\Anaconda\pkgs
                          C:\Users\Administrator\AppData\Local\conda\conda\pkgs
       envs directories : D:\Anaconda\envs
                          C:\Users\Administrator\AppData\Local\conda\conda\envs
                          C:\Users\Administrator\.conda\envs
               platform : win-64
             user-agent : conda/4.5.11 requests/2.19.1 CPython/3.7.0 Windows/10 Windows/10.0.19041
          administrator : True
             netrc file : None
           offline mode : False

补充:镜像源
镜像:比如你照镜子,里面的成像,这里的镜像,是一种文件格式,是镜像文件的简称,举例,你租房时房东给你了一把钥匙A,你出于各种目的(怕丢,给女友,给小伙伴)又配了一把钥匙B,这两把钥匙从功能上都能开你家的门,钥匙B就是钥匙A的镜像。
源(来源):下载软件一般来源都是网站,网站存储在服务器上,有的服务器在国内,有的在国外。
镜像源:镜像的来源,一般指国内存放国外软件镜像的网站、服务器。为啥需要镜像源,在国内由于各种原因下载或更新国外的软件(比如python)网速特别慢甚至连不上。Ubuntu、Python、Nodejs、MySQL、Git、Chromium、Docker、Homebrew 等一系列的常用开源系统、软件都是国外开发的,下载地址位于国外,从国内访问、下载、更新。所以找个镜像网站就解决了。

目前有那些镜像源

清华源
https://mirrors.tuna.tsinghua.edu.cn/

腾讯源
https://mirrors.cloud.tencent.com/

阿里源
https://developer.aliyun.com/mirror/

华为源
https://mirrors.huaweicloud.com/home

网易源
http://mirrors.163.com/

淘宝 NPM 镜像
https://developer.aliyun.com/mirror/NPM

豆瓣 Python PyPI 镜像
http://pypi.doubanio.com/simple/

中国科技大学
https://pypi.mirrors.ustc.edu.cn/simple/

中国科学技术大学
http://pypi.mirrors.ustc.edu.cn/simple/

%%比如使用方法:以Python环境下pip安装keras为例

pip install keras==2.3.1 -i http://pypi.douban.com/simple/
//2.3.1为所需版本号,尾部url为对应镜像源地址

访问速度方面,大型商业公司、尤其是云服务商(没错,指的是腾讯源、阿里源和华为源)的镜像站会做得更好,毕竟钱多、基础设施广。

三、更新conda

代码和显示如下

(pytorch36) C:\Users\Administrator>conda update -n base -c defaults conda
%%输入以上代码,光标开始闪烁


Solving environment: done

## Package Plan ##

  environment location: D:\Anaconda

  added / updated specs:
    - conda


The following NEW packages will be INSTALLED:

    charset-normalizer:     2.0.4-pyhd3eb1b0_0
    conda-package-handling: 1.9.0-py37h8cc25b3_0
    libarchive:             3.3.3-h0643e63_5
    liblief:                0.11.5-hd77b12b_1
    lz4-c:                  1.8.1.2-h2fa13f4_0
    m2-msys2-runtime:       2.5.0.17080.65c939c-3
    m2-patch:               2.7.5-2
    py-lief:                0.11.5-py37hd77b12b_1
    python-libarchive-c:    2.9-pyhd3eb1b0_1
    toml:                   0.10.2-pyhd3eb1b0_0
    xz:                     5.2.6-h8cc25b3_0
    zstd:                   1.3.7-h508b16e_0

The following packages will be UPDATED:

    ca-certificates:        2018.03.07-0            --> 2022.07.19-haa95532_0
    certifi:                2018.8.24-py37_1        --> 2022.9.24-py37haa95532_0
    conda:                  4.5.11-py37_0           --> 22.9.0-py37haa95532_0
    conda-build:            3.15.1-py37_0           --> 3.22.0-py37haa95532_0
    cryptography:           2.3.1-py37h74b6da3_0    --> 3.3.2-py37hcd4344a_0
    curl:                   7.61.0-h7602738_0       --> 7.82.0-h2bbff1b_0
    libcurl:                7.61.0-h7602738_0       --> 7.82.0-h86230a5_0
    libpng:                 1.6.34-h79bbb47_0       --> 1.6.37-h2a8f88b_0
    libssh2:                1.8.0-hd619d38_4        --> 1.10.0-hcd4344a_0
    openssl:                1.0.2p-hfa6e2cd_0       --> 1.1.1q-h2bbff1b_0
    pycurl:                 7.43.0.2-py37h74b6da3_0 --> 7.45.1-py37hcd4344a_0
    qt:                     5.9.6-vc14h1e9a669_2    --> 5.9.7-vc14h73c81de_0
    requests:               2.19.1-py37_0           --> 2.28.1-py37haa95532_0
    sqlite:                 3.24.0-h7602738_0       --> 3.39.3-h2bbff1b_0
    vs2015_runtime:         14.15.26706-h3a45250_0  --> 14.27.29016-h5e58377_2

Proceed ([y]/n)? y

Preparing transaction: done
Verifying transaction: done
Executing transaction: done
%%到这里代表更新成功

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