Please, press ENTER to continue
# 按enter 出现用户协议 一直按enter
Please answer 'yes' or 'no':'
# 输入 yes 按 enter
[/root/anaconda3] >>> /root/Anaconda
# 设置安装目录(必须未存在的文件夹)，直接enter就是默认的目录，显示在左边中括号那个
Unpacking payload ...  
#出现就是就是在安装了
by running conda init? [yes|no] 
# 是否初始化conda，这里一定要输入yes 不要直接按enter，因为默认是no 然后就安装完成了

# >>> conda initialize >>>
# !! Contents within this block are managed by 'conda init' !!
__conda_setup="$('/root/Anaconda/bin/conda' 'shell.bash' 'hook' 2> /dev/null)"
if [ $? -eq 0 ]; then
    eval "$__conda_setup"
else
    if [ -f "/root/Anaconda/etc/profile.d/conda.sh" ]; then
        . "/root/Anaconda/etc/profile.d/conda.sh"
    else
        export PATH="/root/Anaconda/bin:$PATH"
    fi
fi
unset __conda_setup
# <<< conda initialize <<<

source ~/.bashrc
# 检查是否安装成功
conda -V
conda 4.10.1 # 出来这个就说明安装成功了

conda config --set auto_activate_base false
conda deactivate

# 开启下载时通道显示
conda config --set show_channel_urls yes
# ./condarc 中追加镜像信息
channels:
  - defaults
default_channels:
  - https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
  - https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/r
  - https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/msys2
custom_channels:
  conda-forge: https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud
  msys2: https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud
  bioconda: https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud
  menpo: https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud
  pytorch: https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud
  pytorch-lts: https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud
  simpleitk: https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud

conda create -n nlp python=3.6.8

conda install jupyterlab

# 生成配置文件
jupyter notebook --generate-config 
# 在配置文件中追加
c.ServerApp.open_browser = False  # 禁止自动打开浏览器
c.ServerApp.ip='*'  # 就是设置所有ip皆可访问
c.ServerApp.allow_remote_access = True  # 允许远程访问
c.ServerApp.allow_root = True  # 以root身份运行
c.ServerApp.port = 8888  # 指定端口，默认8888
c.ServerApp.root_dir = '/jupyter/xuxingchen'  # 工作目录
c.ServerApp.password = ''

# 进入python命令行
from jupyter_server.auth import passwd; passwd()
# 输入密码、验证密码后会输出'sha1:*****'结果，复制粘贴到配置文件中的c.ServerApp.password值中

# 安装依赖
conda install nb_conda_kernels
# 定位到anaconda/etc/jupyter/jupyter_config.json，修正配置为以下：
{
  "CondaKernelSpecManager": {
    "kernelspec_path": "--user",
    "name_format": "{kernel} ({environment})"
  }
}
# base下直接指定环境安装ipykernel
conda install -n 环境名称 ipykernel
# 切换到对应环境中 写入jupyter notebook 的kernel
python -m ipykernel install --user --name 环境名称

# 复制多份.jupyter/jupyter_lab_config.py，修改其中端口号与密码，以脚本形式后台执行
# 启动脚本
#!/bin/bash

source /root/Anaconda/etc/profile.d/conda.sh
# 切换环境
conda activate base

# 执行jupyter
root_dir="/jupyter/"
log_dir="/root/.jupyter/logs/"
declare -A dic
dic=([zl]=8888 [xj]=8889 [zgp]=8890 [xxc]=8891)
if [ $1 == "all" ]
then
	for dirname in ${!dic[*]}
	do
		(jupyter-lab --port=${dic[$dirname]} --notebook-dir=$root_dir$dirname) > $log_dir$dirname.log 2>&1 &
		sleep 2
		cat $log_dir$dirname.log
		echo "jupyter lab $dirname are running successfully"
	done
else
	(jupyter-lab --port=${dic[$1]} --notebook-dir=$root_dir$1) > $log_dir$1.log 2>&1 &
	sleep 3
	cat $log_dir$1.log
	echo "jupyter lab $1 is running successfully"
fi

# 关闭脚本
#!/bin/bash

if [ $1 == "all" ]
then
	list=("zl" "xj" "zgp" "xxc")
	for dirname in ${!list[@]}
		do
			# 获取进程pid
			PID=$(pgrep -f dir=/jupyter/${list[$dirname]})
			if [ $PID ]
			then 
				kill -n 15 $PID
				echo "已终止${list[$dirname]} $PID"
			else
				echo "未找到${list[$dirname]}相关进程"
			fi
		done
else
	# 获取进程pid
	PID=$(pgrep -f dir=/jupyter/$1)
	if [ $PID ]
	then 
		kill -n 15 $PID
		echo "已终止$1 $PID"
	else
		echo "未找到$1相关进程"
	fi
fi

sudo mkdir -p /usr/local/lib/nodejs
sudo tar -xJvf node-xxx.tar.xz -C /usr/local/lib/nodejs
vim ~/.profile

# 追加环境变量
export PATH=/usr/local/lib/nodejs/node-$VERSION-$DISTRO/bin:$PATH
# 刷新bash环境
source ~/.profile
# 验证安装
node -v

conda activate
pip install jupyterlab-lsp
pip install python-lsp-server[all]
pip install nbclassic==0.2.8