python3.9anaconda增加清华源并在不同环境下运行jupyternotebook

 

增加清华源，提高conda install 的下载速度，这两篇帖子实践过，讲的很详细了：

1、第一篇，大致看一下 

https://blog.youkuaiyun.com/ffscript/article/details/78447197?ops_request_misc=%257B%2522request%255Fid%2522%253A%2522164896827816781685329268%2522%252C%2522scm%2522%253A%252220140713.130102334.pc%255Fall.%2522%257D&request_id=164896827816781685329268&biz_id=0&utm_medium=distribute.pc_search_result.none-task-blog-2~all~first_rank_ecpm_v1~rank_v31_ecpm-4-78447197.142^v5^article_score_rank,157^v4^new_style&utm_term=anaconda+conda+install+%E5%A4%AA%E6%85%A2&spm=1018.2226.3001.4187

2、这个博文直接拉到最后，最后那个命令是正确的

https://www.cnblogs.com/tianlang25/p/12433025.html 

 试图在不同虚拟环境下运行jupyternotebook，由于是安装最新版python3.9的anaconda，所以又要重新开始踩坑

1、这篇帖子提到新版anaconda中安装nb_conda报错

https://blog.youkuaiyun.com/qq_43678005/article/details/122509756?spm=1001.2101.3001.6650.6&utm_medium=distribute.pc_relevant.none-task-blog-2%7Edefault%7EBlogCommendFromBaidu%7ERate-6.pc_relevant_default&depth_1-utm_source=distribute.pc_relevant.none-task-blog-2%7Edefault%7EBlogCommendFromBaidu%7ERate-6.pc_relevant_default&utm_relevant_index=11

所以先没有安装nb_conda,直接开始安装ipykernel，这里参考了另一篇博文，

https://blog.youkuaiyun.com/ninpengyou/article/details/120508552?ops_request_misc=%257B%2522request%255Fid%2522%253A%2522164897004616782089399345%2522%252C%2522scm%2522%253A%252220140713.130102334.pc%255Fall.%2522%257D&request_id=164897004616782089399345&biz_id=0&utm_medium=distribute.pc_search_result.none-task-blog-2~all~first_rank_ecpm_v1~times_rank-6-120508552.142^v5^article_score_rank,157^v4^new_style&utm_term=%E4%B8%8D%E5%90%8C%E8%99%9A%E6%8B%9F%E7%8E%AF%E5%A2%83%E4%B8%AD%E4%BD%BF%E7%94%A8jupyternotebook&spm=1018.2226.3001.4187https://blog.youkuaiyun.com/ninpengyou/article/details/120508552?ops_request_misc=%257B%2522request%255Fid%2522%253A%2522164897004616782089399345%2522%252C%2522scm%2522%253A%252220140713.130102334.pc%255Fall.%2522%257D&request_id=164897004616782089399345&biz_id=0&utm_medium=distribute.pc_search_result.none-task-blog-2~all~first_rank_ecpm_v1~times_rank-6-120508552.142^v5^article_score_rank,157^v4^new_style&utm_term=%E4%B8%8D%E5%90%8C%E8%99%9A%E6%8B%9F%E7%8E%AF%E5%A2%83%E4%B8%AD%E4%BD%BF%E7%94%A8jupyternotebook&spm=1018.2226.3001.4187 同时写的好的还有另一篇：

https://blog.youkuaiyun.com/w55100/article/details/88925697?spm=1001.2101.3001.6650.5&utm_medium=distribute.pc_relevant.none-task-blog-2%7Edefault%7EBlogCommendFromBaidu%7ERate-5.pc_relevant_paycolumn_v3&depth_1-utm_source=distribute.pc_relevant.none-task-blog-2%7Edefault%7EBlogCommendFromBaidu%7ERate-5.pc_relevant_paycolumn_v3&utm_relevant_index=10https://blog.youkuaiyun.com/w55100/article/details/88925697?spm=1001.2101.3001.6650.5&utm_medium=distribute.pc_relevant.none-task-blog-2%7Edefault%7EBlogCommendFromBaidu%7ERate-5.pc_relevant_paycolumn_v3&depth_1-utm_source=distribute.pc_relevant.none-task-blog-2%7Edefault%7EBlogCommendFromBaidu%7ERate-5.pc_relevant_paycolumn_v3&utm_relevant_index=10目前进度：

接下来重启jupyter notebook：

我是在虚拟环境中启动的，命令如下：

 自动跳出jupyter notebook界面，可以看到已经建立了名为tf230的kernel：

 

 由于我在这个tf230的虚拟环境中创建的python3.6的环境，而anaconda的base环境是python3.9，可通过这个不同加以验证jupyter是否真的运行在不同的虚拟环境中，点击“tf230”切换成名为“tf230“的kernel:

 自动弹出界面：

 打印虚拟环境下python版本：

可以看到打印的版本是python3.6，jupyternotebook 切换kernel成功