docker-jupyterhub/README.md

# docker-jupyterhub

## Getting started

[main reference](https://github.com/jupyterhub/jupyterhub-deploy-docker)

构建自己的docker镜像

修改自己想要的python环境在文件`Dockerfile.jupyterhub`

基础镜像是：`jupyter/scipy-notebook` 里面含有conda

```shell
docker buildx build -t hotwa/jupyterhub:latest . -f Dockerfile.jupyterhub --load
```

修改docker-compose.yml文件环境变量：DOCKER_NOTEBOOK_IMAGE

```shell
DOCKER_NOTEBOOK_IMAGE: hotwa/jupyterhub:latest
```

也可以通过 docker-compose 构建镜像

```shell
docker compose build
```

启动docker-compose.yml

```shell
docker compose up -d
```

停止

```shell
docker compose down
```

[基本镜像](https://github.com/jupyter/docker-stacks/tree/main/images/base-notebook)

https://github.com/jupyter/docker-stacks/tree/main/images

[jupyter-gpu](https://github.com/iot-salzburg/gpu-jupyter)

构建自己的基础镜像：

```shell
git clone https://github.com/jupyter/docker-stacks
cd docker-stacks/images/base-notebook
# 修改这个目录下面的 Dockerfile文件, 在后面加就行，里面已经有了mamba、conda
docker buildx build -t hotwa/notebook:latest . -f Dockerfile
```

## 修改jupyterhub启动notebook的路径映射

修改jupyterhub_config.py文件，修改卷的路径：

```python
c.DockerSpawner.volumes = {
    "jupyterhub-user-{username}": notebook_dir,
    "/mnt/mydrive": "/home/jovyan/work/mydrive",
    "/mnt/mydrive/project/docker-jupyterhub/id_rsa": "/home/jovyan/.ssh/id_rsa",
}
```

## 启动notebook修改

启动notebook修改docker-compose.yml文件，修改notebook的基础镜像：

```yaml
      DOCKER_NOTEBOOK_IMAGE: hotwa/notebook:latest
```

## Alternatives

- [rocker/binder](https://rocker-project.org/images/versioned/binder.html) -
  From the R focused [rocker-project](https://rocker-project.org),
  lets you run both RStudio and Jupyter either standalone or in a JupyterHub
- [jupyter/repo2docker](https://github.com/jupyterhub/repo2docker) -
  Turn git repositories into Jupyter-enabled Docker Images
- [openshift/source-to-image](https://github.com/openshift/source-to-image) -
  A tool for building artifacts from source code and injecting them into docker images
- [jupyter-on-openshift/jupyter-notebooks](https://github.com/jupyter-on-openshift/jupyter-notebooks) -
  OpenShift compatible S2I builder for basic notebook images

## nvidia-container-toolkit add

参考了 llama [容器部署](https://hub.docker.com/r/ollama/ollama)

```shell
curl -fsSL https://nvidia.github.io/libnvidia-container/gpgkey \
    | sudo gpg --dearmor -o /usr/share/keyrings/nvidia-container-toolkit-keyring.gpg
curl -s -L https://nvidia.github.io/libnvidia-container/stable/deb/nvidia-container-toolkit.list \
    | sed 's#deb https://#deb [signed-by=/usr/share/keyrings/nvidia-container-toolkit-keyring.gpg] https://#g' \
    | sudo tee /etc/apt/sources.list.d/nvidia-container-toolkit.list
sudo apt-get update
sudo apt-get install -y nvidia-container-toolkit
sudo apt-get install nvidia-container-runtime -y
```

Configure Docker to use Nvidia driver

```shell
sudo nvidia-ctk runtime configure --runtime=docker
sudo systemctl restart docker
```

实际上这个操作修改了/etc/docker/daemon.json文件：

```shell
{
    "registry-mirrors": [
        "https://0b27f0a81a00f3560fbdc00ddd2f99e0.mirror.swr.myhuaweicloud.com",
        "https://ypzju6vq.mirror.aliyuncs.com",
        "https://registry.docker-cn.com",
        "http://hub-mirror.c.163.com",
        "https://docker.mirrors.ustc.edu.cn"
    ],
    "runtimes": {
        "nvidia": {
            "args": [],
            "path": "nvidia-container-runtime"
        }
    }
}
```

配置完成之后：

```shell
docker-compose up -d
```

在jupyterhub_config.py中添加：这样jupyterhub的容器启动镜像就可以使用宿主机的显卡了

```python
# GPU 和网络配置
c.DockerSpawner.extra_host_config = {
    #'network_mode': 'host',
    'runtime': 'nvidia'
}
c.DockerSpawner.environment = {
    'NVIDIA_DRIVER_CAPABILITIES': 'compute,utility',
    'NVIDIA_VISIBLE_DEVICES': 'all'
}
```

## 清除卷


```shell
docker volume ls
docker-compose down
docker rm <container_name_or_id>
docker volume rm basic-example_jupyterhub-data
docker volume rm docker-jupyterhub_jupyterhub-data
docker volume rm jupyterhub-user-admin
```

## 修改绑定到notebook的卷

修改jupyterhub_config.py文件，修改卷的路径：

```python
c.DockerSpawner.volumes = {
    "jupyterhub-user-{username}": notebook_dir,
    "/mnt/mydrive": "/home/jovyan/work/mydrive",
    "/mnt/mydrive/project/docker-jupyterhub/id_rsa": "/home/jovyan/.ssh/id_rsa",
}
```

docker-compose.yml文件，修改notebook的基础镜像：

```yaml
DOCKER_NOTEBOOK_IMAGE: hotwa/notebook:latest
```


## 构建

构建基础notebook镜像

```shell
docker buildx build -t hotwa/notebook:latest -f Dockerfile.base-notebook . --load
```

构建jupyterhub镜像

```shell
docker compose build
```

## 推送镜像至阿里云私有仓库

```shell
docker login --username=ze.ga@qq.com registry.cn-hangzhou.aliyuncs.com
# 重命名
docker tag 2ad3860183ce registry.cn-hangzhou.aliyuncs.com/hotwa/jupyterhub:latest
docker tag ddf815cbaa9b registry.cn-hangzhou.aliyuncs.com/hotwa/notebook:latest
# 推送
docker login --username=ze.ga@qq.com registry.cn-hangzhou.aliyuncs.com
docker push registry.cn-hangzhou.aliyuncs.com/hotwa/jupyterhub:latest
docker push registry.cn-hangzhou.aliyuncs.com/hotwa/notebook:latest
# 拉取
docker pull registry.cn-hangzhou.aliyuncs.com/hotwa/jupyterhub:latest
docker pull registry.cn-hangzhou.aliyuncs.com/hotwa/notebook:latest
```

## add mojo

```shell
docker build --no-cache \
	--build-arg AUTH_KEY= mut_efe460b898e3482bb6208bfcd4a51d7e \
  -t mojosdk:latest \
  -f mojo/examples/docker/Dockerfile.mojosdk .
docker buildx build --build-arg AUTH_KEY=mut_efe460b898e3482bb6208bfcd4a51d7e -t hotwa/notebook:latest . -f Dockerfile.base-notebook --load
```


## 自建证书

openssl req -x509 -nodes -days 365 -newkey rsa:2048 -keyout nginx-selfsigned.key -out nginx-selfsigned.crt
openssl dhparam -out dhparam.pem 2048

这将会在当前目录生成私钥nginx-selfsigned.key，自签名证书nginx-selfsigned.crt，以及Diffie-Hellman参数dhparam.pem。

然后，在您的nginx.conf中，您需要使用这些文件：

```shell
ssl_certificate /path/to/nginx-selfsigned.crt;
ssl_certificate_key /path/to/nginx-selfsigned.key;
ssl_dhparam /path/to/dhparam.pem;
```