Anaconda3 镜像，插件，虚拟环境，内核

1
2
conda config --remove-key channels

1
2
3
4
5
6
conda install -c conda-forge jupyter_contrib_nbextensions
conda install -c conda-forge  jupyter_nbextensions_configurator

jupyter contrib nbextension install --user
jupyter nbextensions_configurator enable --user

1
2
3
4
5
pip install jupyter_nbextensions_configurator jupyter_contrib_nbextensions

jupyter contrib nbextension install --user
jupyter nbextensions_configurator enable --user

1
2
3
4
5
6
7
8
9
pip install qgrid
jupyter nbextension enable --py --sys-prefix widgetsnbextension

#要想使用 Qgrid 渲染数据帧，开发者只需导入 Qgrid，然后将数据帧输入到 show_grid 函数：
import qgrid
qgrid_widget = qgrid.show_grid(df, show_toolbar=True)
qgrid_widget

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
pip install ipywidgets
jupyter nbextension enable --py widgetsnbextension

jupyter labextension install @jupyter-widgets/jupyterlab-manager


import ipywidgets as widgets
from ipywidgets import interact, interact_manual



pip install qgrid  #Installing with pip
conda install qgrid  #Installing with conda


pip install itables

from itables import init_notebook_mode
init_notebook_mode(all_interactive=True)import world_bank_data as wb
df = wb.get_countries()
df


pip install jupyter-datatables

from jupyter_datatables import init_datatables_mode
init_datatables_mode()



pip install ipyvolume #通过pip安装
conda install -c conda-forge ipyvolume  #通过conda进行安装


pip install bqplot 
conda install -c conda-forge bqplot 


pip install livelossplot

from livelossplot import PlotLossesKeras
model.fit(X_train, Y_train,
          epochs=10,
          validation_data=(X_test, Y_test),
          callbacks=[PlotLossesKeras()],
          verbose=0)


pip install tensorwatch

pip install -U polyaxon

pip install handcalcs

pip install jupyternotify

import numpy as np
%timeit np.random.normal(size=1000)

1
2
conda list

1
2
3
conda env list 
conda info -e

1
2
conda update conda

1
2
conda create -n your_env_name python=x.x

1
2
source activate your_env_nam

1
2
activate your_env_name

1
2
source deactivate your_env_nam

1
2
deactivate your_env_name

1
2
conda remove -n your_env_name --all

1
2
3
4
5
6
7
8
# 新建一个新的环境，克隆原环境
conda create --name NewName --clone OldName
# 删除原环境
conda remove --name OldName --all 
# 激活新环境
conda activate NewName 

1
2
python -m ipykernel --version

1
2
jupyter kernelspec list

1
2
python -m pip install ipykernel

1
2
python -m ipykernel install --user --name=your_kernelname  --display-name your_showname

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69

## pip 安装
pip install jupyter


## 安装jupyterlab
pip install jupyterlab

## 安装依赖关系(npm, nodejs)
pip install npm
conda install -c conda-forge nodejs


生成配置文件 默认保存：~/.jupyter/jupyter_notebook_config.py
jupyter notebook --generate-config
或
jupyter lab --generate-config


2. 配置密码

现在最近版本的jupyter可以直接用以下命令：

$ jupyter notebook password



 配置一下 jupyter_notebook_config.py 文件

c.NotebookApp.ip = '*'
c.NotebookApp.allow_root = True
c.NotebookApp.port = 8888



## 启动notebook
jupyter notebook --no-browser --port=8889
## 启动lab
jupyter lab --no-browser --port=8889



Jupyter notebook 更换kernel
由于jupyter notebook访问的时候，默认使用了anaconda的base环境，这里就需要更换环境

安装ipykernel
conda install nb_conda_kernels

将环境写入notebook的kernel中
python -m ipykernel install --user --name 环境名称 --display-name "显示的名称"



查看安装的内核和位置
jupyter kernelspec list

删除 kernel
jupyter kernelspec remove tensorflow


然后 需要在你需要切换的虚拟环境下安装 内核，命令如下
我是在 TensorFlow2的环境下安装的

conda install ipykernel

1
2
3
4
5
6
7
8
9
10
软件包"anaconda clean"(可从Anaconda平台获得)，需要安全卸载。

复制代码
conda install anaconda-clean   # install the package anaconda clean
anaconda-clean --yes           # clean all anaconda related files and directories 
rm -rf ~/anaconda3             # removes the entire anaconda directory

rm -rf ~/.anaconda_backup       # anaconda clean creates a back_up of files/dirs, remove it 
                                # (conda list; cmd shouldn't respond after the clean up)