如何在云服务器使用docker快速部署jupyter web服务器(Nginx+docker+jupyter+tensorflow)

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简介: 如何在云服务器使用docker快速部署jupyter web服务器(Nginx+docker+jupyter+tensorflow)

如何在云服务器部署jupyter web服务器



导读:如果你用过百度人工只能的在线提交代码项目,是不是觉得AI Stdio很酷。或者阿里云天池,这些在线编程与NoteBook项目,它们往往后台集成了jupyter lab/notebook与相关的其它库,再进行自己的云技术相关配置。再这篇文章中,我将带你们在网络服务器上搭建一个基于tensorflow镜像的jupyter环境。阅读完本文后,你将掌握该类环境搭建的最基础的步骤。对于有兴趣者,你也可以尝试再搭建完成后对jupyter的web UI进行修改,建立一个自己风格的AI STDIO网络开发环境。

图:阿里天池 Notebook

图:百度 AI STDIO 。可以进入Notebook也可以进入终端,还有很多其它功能。


好的,现在我们自己试试开始吧!

如果你不能长期使用XShell,那么推荐使用一款免费好用的SSH工具链接你的Linux服务器:PuTTY

该工具安装简单、使用方便。可以自己在网上取查找相关教程,这里不做介绍了。 -

  • 注:文本内容以下以ubuntu系统为例,如果使用centos等其它Linux系统,再以下内容中基本就是包管理工具名不一样,替换即可

先要部署docker:

如果你的Linux服务器没有配置国内源的话,可能接下来的下载速度会很慢,建议配置一个国内源。这里以阿里云为例。

配置前,需要安装vim工具:

如有必要,也先更新apt源:

apt update
apt upgrade -y

安装vim:

apt - get install vim

然后使用vim编辑apt的源配置文件:

vim /etc/apt/sources.list

先使用"#"号注释掉或者删掉原先的地址,而后添加以下内容(阿里云镜像):

deb http://mirrors.aliyun.com/ubuntu/ bionic main restricted universe multiverse
deb http://mirrors.aliyun.com/ubuntu/ bionic-security main restricted universe multiverse
deb http://mirrors.aliyun.com/ubuntu/ bionic-updates main restricted universe multiverse
deb http://mirrors.aliyun.com/ubuntu/ bionic-proposed main restricted universe multiverse
deb http://mirrors.aliyun.com/ubuntu/ bionic-backports main restricted universe multiverse
deb-src http://mirrors.aliyun.com/ubuntu/ bionic main restricted universe multiverse
deb-src http://mirrors.aliyun.com/ubuntu/ bionic-security main restricted universe multiverse
deb-src http://mirrors.aliyun.com/ubuntu/ bionic-updates main restricted universe multiverse
deb-src http://mirrors.aliyun.com/ubuntu/ bionic-proposed main restricted universe multiverse
deb-src http://mirrors.aliyun.com/ubuntu/ bionic-backports main restricted universe multiverse

保存,退出。

再次更新和升级:

apt-get update
apt-get install upgrade

安装docker

apt-get install docker

既然向快速部署,我连jupyter都懒得自己安装。直接拉一个部署了jupyter的docker镜像:

docker pull tensorflow/tensorflow:latest

这个镜像的下载过程需要一点时间。

然后将镜像运行为docker容器,同时映射端口一步到位:

docker run -it -p 80:8000 tensorflow/tensorflow:latest-jupyter

我的思路是用Nginx做反向代理,进一步隐藏真实端口,这样更加安全。所以先映射到8000端口,而不是直接使用jupyter使用的8888(当然jupyter默认使用的端口也可以修改,这里不做介绍)。

第一次进入时,会直接在外部看到jupyter输出的信息并且已经启动了jupyter,直接Ctrl-C几次退出jupyter就好了,这不是我们需要的方式。

现在查看刚刚我们所有的docker容器:

docker ps -a

可以看到打印出了当前创建的docker容器

CONTAINER ID        IMAGE                                  COMMAND                  CREATED             STATUS                         PORTS                            NAMES
c229f9b659fb        tensorflow/tensorflow:latest-jupyter   "bash -c 'source /et…"   2 minutes ago      Up 1 minutes                  8888/tcp, 0.0.0.0:80->8000/tcp   fervent_mclean

启动它(需要根据你自己创建的容器的ID):

docker start c229f9b659fb

进入容器

docker exec -it c229f9b659fb /bin/bash

进入容器后相当于进入了一个新的系统,对宿主机系统而言,容器里面相当于与外隔绝的虚拟隔离环境。只不过这个容器是直接拉了一个由tensorflow配好一些东西了,其它的也就相当于一个新的系统。并且在容器内,你直接拥有root权限,所有命令不需要sudo。进入之后,你也可以为容器内的系统配置为国内源。

图:由宿主机进入tensorflow官方docker run的系统容器后画面

这里,你能就按到tensorflow的LOGO。因为它们配置这个容器的时候顺便就配了一下商标。当然自己配置也不难,你完全可以自己尝试配置一个镜像然后添加自己的头像上床到docker hub供大家pull哈。

以下为进入后在docker容器内的操作。为了之后可以编辑配置文件,我们在容器内也是需要安装vim工具的,同样的方法:

apt update
apt install vim

安装lsof工具,因为之后我们需要查看网络端口情况:

apt install lsof

安装Nginx部署Web服务器,之后以其作为反向代理:

apt install nginx

接下来,通过vim工具打开nginx配置文件:

vim /etc/nginx/nginx.conf

将该文件编辑为以下内容:

user www-data;
worker_processes auto;
pid /run/nginx.pid;
include /etc/nginx/modules-enabled/*.conf;
events {
        worker_connections 768;
        # multi_accept on;
}
http {
        ##
        # Basic Settings
        ##
        sendfile on;
        tcp_nopush on;
        tcp_nodelay on;
        keepalive_timeout 65;
        types_hash_max_size 2048;
        # server_tokens off;
        # server_names_hash_bucket_size 64;
        # server_name_in_redirect off;
        include /etc/nginx/mime.types;
        default_type application/octet-stream;
        ##
        # SSL Settings
        ##
        ssl_protocols TLSv1 TLSv1.1 TLSv1.2; # Dropping SSLv3, ref: POODLE
        ssl_prefer_server_ciphers on;
        ##
        # Logging Settings
        ##
        access_log /var/log/nginx/access.log;
        error_log /var/log/nginx/error.log;
        ##
        # Gzip Settings
        ##
        gzip on;
        # gzip_vary on;
        # gzip_proxied any;
        # gzip_comp_level 6;
        # gzip_buffers 16 8k;
        # gzip_http_version 1.1;
        # gzip_types text/plain text/css application/json application/javascript text/xml application/xml application/xml+rss text/javascript;
        ##
        # Virtual Host Configs
        ##
        include /etc/nginx/conf.d/*.conf;
        include /etc/nginx/sites-enabled/*;
        server {
            listen 8000;
            server_name 这里替换为你的域名或者服务器的IP地址;
            location / {
                proxy_set_header Host $host:$server_port;
                proxy_set_header X-Real-IP $remote_addr;
                proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
                proxy_pass http://127.0.0.1:8888;
            }
        }
}

编辑完成后保存,退出vim。

配置完成之后,还有一个Nginxm默认配置需要稍做修改:

cd /etc/nginx
ls

可以看到由以下文件和文件夹:

conf.d          koi-win            nginx.conf       sites-enabled
fastcgi.conf    mime.types         proxy_params     snippets
fastcgi_params  modules-available  scgi_params      uwsgi_params
koi-utf         modules-enabled    sites-available  win-utf

有个sites-available文件夹,可以用tab补齐的方法快熟输入:

cd sites-available/

里面只有一个`default文件:

ls
default

使用vim打开它:

vim default

你看到的大概是这样的:

##
# You should look at the following URL's in order to grasp a solid understanding
# of Nginx configuration files in order to fully unleash the power of Nginx.
# https://www.nginx.com/resources/wiki/start/
# https://www.nginx.com/resources/wiki/start/topics/tutorials/config_pitfalls/
# https://wiki.debian.org/Nginx/DirectoryStructure
#
# In most cases, administrators will remove this file from sites-enabled/ and
# leave it as reference inside of sites-available where it will continue to be
# updated by the nginx packaging team.
#
# This file will automatically load configuration files provided by other
# applications, such as Drupal or Wordpress. These applications will be made
# available underneath a path with that package name, such as /drupal8.
#
# Please see /usr/share/doc/nginx-doc/examples/ for more detailed examples.
##
# Default server configuration
#
server {
        listen 80 default_server;
        listen [::]:80 default_server;
        # SSL configuration
        #
        # listen 443 ssl default_server;
        # listen [::]:443 ssl default_server;
        #
        # Note: You should disable gzip for SSL traffic.
        # See: https://bugs.debian.org/773332
        #
        # Read up on ssl_ciphers to ensure a secure configuration.
        # See: https://bugs.debian.org/765782
        #
        # Self signed certs generated by the ssl-cert package
        # Don't use them in a production server!
        #
        # include snippets/snakeoil.conf;
        root /var/www/html;
        # Add index.php to the list if you are using PHP
        index index.html index.htm index.nginx-debian.html;
        server_name _;
        location / {
                # First attempt to serve request as file, then
                # as directory, then fall back to displaying a 404.
                try_files $uri $uri/ = 404;
        }
...

(文件后面已省略)

server下的第二行,即

listen [::]:80 default_server;

添加"#"符以注释掉:

保存,再退出。这样Nginx的配置就完成了。

为了作为服务器部署使用,jupyter是一定要配置密码的。接下来,我们先在docker容器中进入python编程环境。这个python就是部署jupyter的python,我们可以在里面计算哈希密码值:

python

进入之后在交互式环境中输入以下两行python代码:

>>>from notebook.auth import passwd
>>>passwd()

这时系统将提示你输入密码,需要输入两次(第二次是密码的确认):

Enter password: ········
Verify password: ········

输入完成后,你将获取一个如下格式的字符串,这个就是加密后的密码(以我获取的为例):

'sha1:c018cb5b13a0:7b945869a95654d657655c9bb909d7a90112e843'

复制或者记录这个字符串,接下来我们需要用这个字符串来配置jupyter。

这里,先在交互式编程环境中使用python退出函数退回该环境:

exit()

现在我们回到了docker容器级"系统"下,先使用如下指令生成一个jupyter配置文件:

jupyter notebook --generate-config

可以见到返回一行文字,它包含了生成的配置文件绝对路径:

Writing default config to: /root/.jupyter/jupyter_notebook_config.py

我们现在使用vim打开它:

vim /root/.jupyter/jupyter_notebook_config.py

以下是打开的配置文件,为了方便大家了解和学习jupyter配置,这里我们展示了整个配置文件的内容:

# Configuration file for jupyter-notebook.
#------------------------------------------------------------------------------
# Application(SingletonConfigurable) configuration
#------------------------------------------------------------------------------
## This is an application.
## The date format used by logging formatters for %(asctime)s
#c.Application.log_datefmt = '%Y-%m-%d %H:%M:%S'
## The Logging format template
#c.Application.log_format = '[%(name)s]%(highlevel)s %(message)s'
## Set the log level by value or name.
#c.Application.log_level = 30
#------------------------------------------------------------------------------
# JupyterApp(Application) configuration
#------------------------------------------------------------------------------
## Base class for Jupyter applications
## Answer yes to any prompts.
#c.JupyterApp.answer_yes = False
## Full path of a config file.
#c.JupyterApp.config_file = ''
## Specify a config file to load.
#c.JupyterApp.config_file_name = ''
## Generate default config file.
#c.JupyterApp.generate_config = False
#------------------------------------------------------------------------------
# NotebookApp(JupyterApp) configuration
#------------------------------------------------------------------------------
## Set the Access-Control-Allow-Credentials: true header
#c.NotebookApp.allow_credentials = False
## Set the Access-Control-Allow-Origin header
#
#  Use '*' to allow any origin to access your server.
#
#  Takes precedence over allow_origin_pat.
#c.NotebookApp.allow_origin = ''
## Use a regular expression for the Access-Control-Allow-Origin header
#
#  Requests from an origin matching the expression will get replies with:
#
#      Access-Control-Allow-Origin: origin
#
#  where `origin` is the origin of the request.
#
#  Ignored if allow_origin is set.
#c.NotebookApp.allow_origin_pat = ''
## Allow password to be changed at login for the notebook server.
#
#  While loggin in with a token, the notebook server UI will give the opportunity
#  to the user to enter a new password at the same time that will replace the
#  token login mechanism.
#
#  This can be set to false to prevent changing password from the UI/API.
#c.NotebookApp.allow_password_change = True
## Allow requests where the Host header doesn't point to a local server
#
#  By default, requests get a 403 forbidden response if the 'Host' header shows
#  that the browser thinks it's on a non-local domain. Setting this option to
#  True disables this check.
#
#  This protects against 'DNS rebinding' attacks, where a remote web server
#  serves you a page and then changes its DNS to send later requests to a local
#  IP, bypassing same-origin checks.
#
#  Local IP addresses (such as 127.0.0.1 and ::1) are allowed as local, along
#  with hostnames configured in local_hostnames.
#c.NotebookApp.allow_remote_access = False
## Whether to allow the user to run the notebook as root.
#c.NotebookApp.allow_root = False
## Reload the webapp when changes are made to any Python src files.
#c.NotebookApp.autoreload = False
## DEPRECATED use base_url
#c.NotebookApp.base_project_url = '/'
## The base URL for the notebook server.
#
#  Leading and trailing slashes can be omitted, and will automatically be added.
#c.NotebookApp.base_url = '/'
## Specify what command to use to invoke a web browser when opening the notebook.
#  If not specified, the default browser will be determined by the `webbrowser`
#  standard library module, which allows setting of the BROWSER environment
#  variable to override it.
#c.NotebookApp.browser = ''
## The full path to an SSL/TLS certificate file.
#c.NotebookApp.certfile = ''
## The full path to a certificate authority certificate for SSL/TLS client
#  authentication.
#c.NotebookApp.client_ca = ''
## The config manager class to use
#c.NotebookApp.config_manager_class = 'notebook.services.config.manager.ConfigManager'
## The notebook manager class to use.
#c.NotebookApp.contents_manager_class = 'notebook.services.contents.largefilemanager.LargeFileManager'
## Extra keyword arguments to pass to `set_secure_cookie`. See tornado's
#  set_secure_cookie docs for details.
#c.NotebookApp.cookie_options = {}
## The random bytes used to secure cookies. By default this is a new random
#  number every time you start the Notebook. Set it to a value in a config file
#  to enable logins to persist across server sessions.
#
#  Note: Cookie secrets should be kept private, do not share config files with
#  cookie_secret stored in plaintext (you can read the value from a file).
#c.NotebookApp.cookie_secret = b''
## The file where the cookie secret is stored.
#c.NotebookApp.cookie_secret_file = ''
## Override URL shown to users.
#
#  Replace actual URL, including protocol, address, port and base URL, with the
#  given value when displaying URL to the users. Do not change the actual
#  connection URL. If authentication token is enabled, the token is added to the
#  custom URL automatically.
#
#  This option is intended to be used when the URL to display to the user cannot
#  be determined reliably by the Jupyter notebook server (proxified or
#  containerized setups for example).
#c.NotebookApp.custom_display_url = ''
## The default URL to redirect to from `/`
#c.NotebookApp.default_url = '/tree'
## Disable cross-site-request-forgery protection
#
#  Jupyter notebook 4.3.1 introduces protection from cross-site request
#  forgeries, requiring API requests to either:
#
#  - originate from pages served by this server (validated with XSRF cookie and
#  token), or - authenticate with a token
#
#  Some anonymous compute resources still desire the ability to run code,
#  completely without authentication. These services can disable all
#  authentication and security checks, with the full knowledge of what that
#  implies.
#c.NotebookApp.disable_check_xsrf = False
## Whether to enable MathJax for typesetting math/TeX
#
#  MathJax is the javascript library Jupyter uses to render math/LaTeX. It is
#  very large, so you may want to disable it if you have a slow internet
#  connection, or for offline use of the notebook.
#
#  When disabled, equations etc. will appear as their untransformed TeX source.
#c.NotebookApp.enable_mathjax = True
## extra paths to look for Javascript notebook extensions
#c.NotebookApp.extra_nbextensions_path = []
## handlers that should be loaded at higher priority than the default services
#c.NotebookApp.extra_services = []
## Extra paths to search for serving static files.
#
#  This allows adding javascript/css to be available from the notebook server
#  machine, or overriding individual files in the IPython
#c.NotebookApp.extra_static_paths = []
## Extra paths to search for serving jinja templates.
#
#  Can be used to override templates from notebook.templates.
#c.NotebookApp.extra_template_paths = []
##
#c.NotebookApp.file_to_run = ''
## Extra keyword arguments to pass to `get_secure_cookie`. See tornado's
#  get_secure_cookie docs for details.
#c.NotebookApp.get_secure_cookie_kwargs = {}
## Deprecated: Use minified JS file or not, mainly use during dev to avoid JS
#  recompilation
#c.NotebookApp.ignore_minified_js = False
## (bytes/sec) Maximum rate at which stream output can be sent on iopub before
#  they are limited.
#c.NotebookApp.iopub_data_rate_limit = 1000000
## (msgs/sec) Maximum rate at which messages can be sent on iopub before they are
#  limited.
#c.NotebookApp.iopub_msg_rate_limit = 1000
## The IP address the notebook server will listen on.
#c.NotebookApp.ip = 'localhost'
## Supply extra arguments that will be passed to Jinja environment.
#c.NotebookApp.jinja_environment_options = {}
## Extra variables to supply to jinja templates when rendering.
#c.NotebookApp.jinja_template_vars = {}
## The kernel manager class to use.
#c.NotebookApp.kernel_manager_class = 'notebook.services.kernels.kernelmanager.MappingKernelManager'
## The kernel spec manager class to use. Should be a subclass of
#  `jupyter_client.kernelspec.KernelSpecManager`.
#
#  The Api of KernelSpecManager is provisional and might change without warning
#  between this version of Jupyter and the next stable one.
#c.NotebookApp.kernel_spec_manager_class = 'jupyter_client.kernelspec.KernelSpecManager'
## The full path to a private key file for usage with SSL/TLS.
#c.NotebookApp.keyfile = ''
## Hostnames to allow as local when allow_remote_access is False.
#
#  Local IP addresses (such as 127.0.0.1 and ::1) are automatically accepted as
#  local as well.
#c.NotebookApp.local_hostnames = ['localhost']
## The login handler class to use.
#c.NotebookApp.login_handler_class = 'notebook.auth.login.LoginHandler'
## The logout handler class to use.
#c.NotebookApp.logout_handler_class = 'notebook.auth.logout.LogoutHandler'
## The MathJax.js configuration file that is to be used.
#c.NotebookApp.mathjax_config = 'TeX-AMS-MML_HTMLorMML-full,Safe'
## A custom url for MathJax.js. Should be in the form of a case-sensitive url to
#  MathJax, for example:  /static/components/MathJax/MathJax.js
#c.NotebookApp.mathjax_url = ''
## Sets the maximum allowed size of the client request body, specified in the
#  Content-Length request header field. If the size in a request exceeds the
#  configured value, a malformed HTTP message is returned to the client.
#
#  Note: max_body_size is applied even in streaming mode.
#c.NotebookApp.max_body_size = 536870912
## Gets or sets the maximum amount of memory, in bytes, that is allocated for use
#  by the buffer manager.
#c.NotebookApp.max_buffer_size = 536870912
## Gets or sets a lower bound on the open file handles process resource limit.
#  This may need to be increased if you run into an OSError: [Errno 24] Too many
#  open files. This is not applicable when running on Windows.
#c.NotebookApp.min_open_files_limit = 0
## Dict of Python modules to load as notebook server extensions.Entry values can
#  be used to enable and disable the loading ofthe extensions. The extensions
#  will be loaded in alphabetical order.
#c.NotebookApp.nbserver_extensions = {}
## The directory to use for notebooks and kernels.
#c.NotebookApp.notebook_dir = ''
## Whether to open in a browser after starting. The specific browser used is
#  platform dependent and determined by the python standard library `webbrowser`
#  module, unless it is overridden using the --browser (NotebookApp.browser)
#  configuration option.
#c.NotebookApp.open_browser = True
## Hashed password to use for web authentication.
#
#  To generate, type in a python/IPython shell:
#
#    from notebook.auth import passwd; passwd()
#
#  The string should be of the form type:salt:hashed-password.
#c.NotebookApp.password = ''
## Forces users to use a password for the Notebook server. This is useful in a
#  multi user environment, for instance when everybody in the LAN can access each
#  other's machine through ssh.
#
#  In such a case, serving the notebook server on localhost is not secure since
#  any user can connect to the notebook server via ssh.
#c.NotebookApp.password_required = False
## The port the notebook server will listen on (env: JUPYTER_PORT).
#c.NotebookApp.port = 8888
## The number of additional ports to try if the specified port is not available
#  (env: JUPYTER_PORT_RETRIES).
#c.NotebookApp.port_retries = 50
## DISABLED: use %pylab or %matplotlib in the notebook to enable matplotlib.
#c.NotebookApp.pylab = 'disabled'
## If True, display a button in the dashboard to quit (shutdown the notebook
#  server).
#c.NotebookApp.quit_button = True
## (sec) Time window used to check the message and data rate limits.
#c.NotebookApp.rate_limit_window = 3
## Reraise exceptions encountered loading server extensions?
#c.NotebookApp.reraise_server_extension_failures = False
## DEPRECATED use the nbserver_extensions dict instead
#c.NotebookApp.server_extensions = []
## The session manager class to use.
#c.NotebookApp.session_manager_class = 'notebook.services.sessions.sessionmanager.SessionManager'
## Shut down the server after N seconds with no kernels or terminals running and
#  no activity. This can be used together with culling idle kernels
#  (MappingKernelManager.cull_idle_timeout) to shutdown the notebook server when
#  it's not in use. This is not precisely timed: it may shut down up to a minute
#  later. 0 (the default) disables this automatic shutdown.
#c.NotebookApp.shutdown_no_activity_timeout = 0
## The UNIX socket the notebook server will listen on.
#c.NotebookApp.sock = ''
## The permissions mode for UNIX socket creation (default: 0600).
#c.NotebookApp.sock_mode = '0600'
## Supply SSL options for the tornado HTTPServer. See the tornado docs for
#  details.
#c.NotebookApp.ssl_options = {}
## Supply overrides for terminado. Currently only supports "shell_command". On
#  Unix, if "shell_command" is not provided, a non-login shell is launched by
#  default when the notebook server is connected to a terminal, a login shell
#  otherwise.
#c.NotebookApp.terminado_settings = {}
## Set to False to disable terminals.
#
#  This does *not* make the notebook server more secure by itself. Anything the
#  user can in a terminal, they can also do in a notebook.
#
#  Terminals may also be automatically disabled if the terminado package is not
#  available.
#c.NotebookApp.terminals_enabled = True
## Token used for authenticating first-time connections to the server.
#
#  The token can be read from the file referenced by JUPYTER_TOKEN_FILE or set
#  directly with the JUPYTER_TOKEN environment variable.
#
#  When no password is enabled, the default is to generate a new, random token.
#
#  Setting to an empty string disables authentication altogether, which is NOT
#  RECOMMENDED.
#c.NotebookApp.token = '<generated>'
## Supply overrides for the tornado.web.Application that the Jupyter notebook
#  uses.
#c.NotebookApp.tornado_settings = {}
## Whether to trust or not X-Scheme/X-Forwarded-Proto and X-Real-Ip/X-Forwarded-
#  For headerssent by the upstream reverse proxy. Necessary if the proxy handles
#  SSL
#c.NotebookApp.trust_xheaders = False
## Disable launching browser by redirect file
#
#  For versions of notebook > 5.7.2, a security feature measure was added that
#  prevented the authentication token used to launch the browser from being
#  visible. This feature makes it difficult for other users on a multi-user
#  system from running code in your Jupyter session as you.
#
#  However, some environments (like Windows Subsystem for Linux (WSL) and
#  Chromebooks), launching a browser using a redirect file can lead the browser
#  failing to load. This is because of the difference in file structures/paths
#  between the runtime and the browser.
#
#  Disabling this setting to False will disable this behavior, allowing the
#  browser to launch by using a URL and visible token (as before).
#c.NotebookApp.use_redirect_file = True
## DEPRECATED, use tornado_settings
#c.NotebookApp.webapp_settings = {}
## Specify Where to open the notebook on startup. This is the `new` argument
#  passed to the standard library method `webbrowser.open`. The behaviour is not
#  guaranteed, but depends on browser support. Valid values are:
#
#   - 2 opens a new tab,
#   - 1 opens a new window,
#   - 0 opens in an existing window.
#
#  See the `webbrowser.open` documentation for details.
#c.NotebookApp.webbrowser_open_new = 2
## Set the tornado compression options for websocket connections.
#
#  This value will be returned from
#  :meth:`WebSocketHandler.get_compression_options`. None (default) will disable
#  compression. A dict (even an empty one) will enable compression.
#
#  See the tornado docs for WebSocketHandler.get_compression_options for details.
#c.NotebookApp.websocket_compression_options = None
## The base URL for websockets, if it differs from the HTTP server (hint: it
#  almost certainly doesn't).
#
#  Should be in the form of an HTTP origin: ws[s]://hostname[:port]
#c.NotebookApp.websocket_url = ''
#------------------------------------------------------------------------------
# ConnectionFileMixin(LoggingConfigurable) configuration
#------------------------------------------------------------------------------
## Mixin for configurable classes that work with connection files
## JSON file in which to store connection info [default: kernel-<pid>.json]
#
#  This file will contain the IP, ports, and authentication key needed to connect
#  clients to this kernel. By default, this file will be created in the security
#  dir of the current profile, but can be specified by absolute path.
#c.ConnectionFileMixin.connection_file = ''
## set the control (ROUTER) port [default: random]
#c.ConnectionFileMixin.control_port = 0
## set the heartbeat port [default: random]
#c.ConnectionFileMixin.hb_port = 0
## set the iopub (PUB) port [default: random]
#c.ConnectionFileMixin.iopub_port = 0
## Set the kernel's IP address [default localhost]. If the IP address is
#  something other than localhost, then Consoles on other machines will be able
#  to connect to the Kernel, so be careful!
#c.ConnectionFileMixin.ip = ''
## set the shell (ROUTER) port [default: random]
#c.ConnectionFileMixin.shell_port = 0
## set the stdin (ROUTER) port [default: random]
#c.ConnectionFileMixin.stdin_port = 0
##
#c.ConnectionFileMixin.transport = 'tcp'
#------------------------------------------------------------------------------
# KernelManager(ConnectionFileMixin) configuration
#------------------------------------------------------------------------------
## Manages a single kernel in a subprocess on this host.
#
#  This version starts kernels with Popen.
## Should we autorestart the kernel if it dies.
#c.KernelManager.autorestart = True
## DEPRECATED: Use kernel_name instead.
#
#  The Popen Command to launch the kernel. Override this if you have a custom
#  kernel. If kernel_cmd is specified in a configuration file, Jupyter does not
#  pass any arguments to the kernel, because it cannot make any assumptions about
#  the arguments that the kernel understands. In particular, this means that the
#  kernel does not receive the option --debug if it given on the Jupyter command
#  line.
#c.KernelManager.kernel_cmd = []
## Time to wait for a kernel to terminate before killing it, in seconds.
#c.KernelManager.shutdown_wait_time = 5.0
#------------------------------------------------------------------------------
# Session(Configurable) configuration
#------------------------------------------------------------------------------
## Object for handling serialization and sending of messages.
#
#  The Session object handles building messages and sending them with ZMQ sockets
#  or ZMQStream objects.  Objects can communicate with each other over the
#  network via Session objects, and only need to work with the dict-based IPython
#  message spec. The Session will handle serialization/deserialization, security,
#  and metadata.
#
#  Sessions support configurable serialization via packer/unpacker traits, and
#  signing with HMAC digests via the key/keyfile traits.
#
#  Parameters ----------
#
#  debug : bool
#      whether to trigger extra debugging statements
#  packer/unpacker : str : 'json', 'pickle' or import_string
#      importstrings for methods to serialize message parts.  If just
#      'json' or 'pickle', predefined JSON and pickle packers will be used.
#      Otherwise, the entire importstring must be used.
#
#      The functions must accept at least valid JSON input, and output *bytes*.
#
#      For example, to use msgpack:
#      packer = 'msgpack.packb', unpacker='msgpack.unpackb'
#  pack/unpack : callables
#      You can also set the pack/unpack callables for serialization directly.
#  session : bytes
#      the ID of this Session object.  The default is to generate a new UUID.
#  username : unicode
#      username added to message headers.  The default is to ask the OS.
#  key : bytes
#      The key used to initialize an HMAC signature.  If unset, messages
#      will not be signed or checked.
#  keyfile : filepath
#      The file containing a key.  If this is set, `key` will be initialized
#      to the contents of the file.
## Threshold (in bytes) beyond which an object's buffer should be extracted to
#  avoid pickling.
#c.Session.buffer_threshold = 1024
## Whether to check PID to protect against calls after fork.
#
#  This check can be disabled if fork-safety is handled elsewhere.
#c.Session.check_pid = True
## Threshold (in bytes) beyond which a buffer should be sent without copying.
#c.Session.copy_threshold = 65536
## Debug output in the Session
#c.Session.debug = False
## The maximum number of digests to remember.
#
#  The digest history will be culled when it exceeds this value.
#c.Session.digest_history_size = 65536
## The maximum number of items for a container to be introspected for custom
#  serialization. Containers larger than this are pickled outright.
#c.Session.item_threshold = 64
## execution key, for signing messages.
#c.Session.key = b''
## path to file containing execution key.
#c.Session.keyfile = ''
## Metadata dictionary, which serves as the default top-level metadata dict for
#  each message.
#c.Session.metadata = {}
## The name of the packer for serializing messages. Should be one of 'json',
#  'pickle', or an import name for a custom callable serializer.
#c.Session.packer = 'json'
## The UUID identifying this session.
#c.Session.session = ''
## The digest scheme used to construct the message signatures. Must have the form
#  'hmac-HASH'.
#c.Session.signature_scheme = 'hmac-sha256'
## The name of the unpacker for unserializing messages. Only used with custom
#  functions for `packer`.
#c.Session.unpacker = 'json'
## Username for the Session. Default is your system username.
#c.Session.username = 'username'
#------------------------------------------------------------------------------
# MultiKernelManager(LoggingConfigurable) configuration
#------------------------------------------------------------------------------
## A class for managing multiple kernels.
## The name of the default kernel to start
#c.MultiKernelManager.default_kernel_name = 'python3'
## The kernel manager class.  This is configurable to allow subclassing of the
#  KernelManager for customized behavior.
#c.MultiKernelManager.kernel_manager_class = 'jupyter_client.ioloop.IOLoopKernelManager'
## Share a single zmq.Context to talk to all my kernels
#c.MultiKernelManager.shared_context = True
#------------------------------------------------------------------------------
# MappingKernelManager(MultiKernelManager) configuration
#------------------------------------------------------------------------------
## A KernelManager that handles notebook mapping and HTTP error handling
## White list of allowed kernel message types. When the list is empty, all
#  message types are allowed.
#c.MappingKernelManager.allowed_message_types = []
## Whether messages from kernels whose frontends have disconnected should be
#  buffered in-memory. When True (default), messages are buffered and replayed on
#  reconnect, avoiding lost messages due to interrupted connectivity. Disable if
#  long-running kernels will produce too much output while no frontends are
#  connected.
#c.MappingKernelManager.buffer_offline_messages = True
## Whether to consider culling kernels which are busy. Only effective if
#  cull_idle_timeout > 0.
#c.MappingKernelManager.cull_busy = False
## Whether to consider culling kernels which have one or more connections. Only
#  effective if cull_idle_timeout > 0.
#c.MappingKernelManager.cull_connected = False
## Timeout (in seconds) after which a kernel is considered idle and ready to be
#  culled. Values of 0 or lower disable culling. Very short timeouts may result
#  in kernels being culled for users with poor network connections.
#c.MappingKernelManager.cull_idle_timeout = 0
## The interval (in seconds) on which to check for idle kernels exceeding the
#  cull timeout value.
#c.MappingKernelManager.cull_interval = 300
## Timeout for giving up on a kernel (in seconds). On starting and restarting
#  kernels, we check whether the kernel is running and responsive by sending
#  kernel_info_requests. This sets the timeout in seconds for how long the kernel
#  can take before being presumed dead. This affects the MappingKernelManager
#  (which handles kernel restarts) and the ZMQChannelsHandler (which handles the
#  startup).
#c.MappingKernelManager.kernel_info_timeout = 60
##
#c.MappingKernelManager.root_dir = ''
#------------------------------------------------------------------------------
# KernelSpecManager(LoggingConfigurable) configuration
#------------------------------------------------------------------------------
## If there is no Python kernelspec registered and the IPython kernel is
#  available, ensure it is added to the spec list.
#c.KernelSpecManager.ensure_native_kernel = True
## The kernel spec class.  This is configurable to allow subclassing of the
#  KernelSpecManager for customized behavior.
#c.KernelSpecManager.kernel_spec_class = 'jupyter_client.kernelspec.KernelSpec'
## Whitelist of allowed kernel names.
#
#  By default, all installed kernels are allowed.
#c.KernelSpecManager.whitelist = set()
#------------------------------------------------------------------------------
# ContentsManager(LoggingConfigurable) configuration
#------------------------------------------------------------------------------
## Base class for serving files and directories.
#
#  This serves any text or binary file, as well as directories, with special
#  handling for JSON notebook documents.
#
#  Most APIs take a path argument, which is always an API-style unicode path, and
#  always refers to a directory.
#
#  - unicode, not url-escaped
#  - '/'-separated
#  - leading and trailing '/' will be stripped
#  - if unspecified, path defaults to '',
#    indicating the root path.
## Allow access to hidden files
#c.ContentsManager.allow_hidden = False
##
#c.ContentsManager.checkpoints = None
##
#c.ContentsManager.checkpoints_class = 'notebook.services.contents.checkpoints.Checkpoints'
##
#c.ContentsManager.checkpoints_kwargs = {}
## handler class to use when serving raw file requests.
#
#  Default is a fallback that talks to the ContentsManager API, which may be
#  inefficient, especially for large files.
#
#  Local files-based ContentsManagers can use a StaticFileHandler subclass, which
#  will be much more efficient.
#
#  Access to these files should be Authenticated.
#c.ContentsManager.files_handler_class = 'notebook.files.handlers.FilesHandler'
## Extra parameters to pass to files_handler_class.
#
#  For example, StaticFileHandlers generally expect a `path` argument specifying
#  the root directory from which to serve files.
#c.ContentsManager.files_handler_params = {}
## Glob patterns to hide in file and directory listings.
#c.ContentsManager.hide_globs = ['__pycache__', '*.pyc', '*.pyo', '.DS_Store', '*.so', '*.dylib', '*~']
## Python callable or importstring thereof
#
#  To be called on a contents model prior to save.
#
#  This can be used to process the structure, such as removing notebook outputs
#  or other side effects that should not be saved.
#
#  It will be called as (all arguments passed by keyword)::
#
#      hook(path=path, model=model, contents_manager=self)
#
#  - model: the model to be saved. Includes file contents.
#    Modifying this dict will affect the file that is stored.
#  - path: the API path of the save destination
#  - contents_manager: this ContentsManager instance
#c.ContentsManager.pre_save_hook = None
##
#c.ContentsManager.root_dir = '/'
## The base name used when creating untitled directories.
#c.ContentsManager.untitled_directory = 'Untitled Folder'
## The base name used when creating untitled files.
#c.ContentsManager.untitled_file = 'untitled'
## The base name used when creating untitled notebooks.
#c.ContentsManager.untitled_notebook = 'Untitled'
#------------------------------------------------------------------------------
# FileManagerMixin(Configurable) configuration
#------------------------------------------------------------------------------
## Mixin for ContentsAPI classes that interact with the filesystem.
#
#  Provides facilities for reading, writing, and copying both notebooks and
#  generic files.
#
#  Shared by FileContentsManager and FileCheckpoints.
#
#  Note ---- Classes using this mixin must provide the following attributes:
#
#  root_dir : unicode
#      A directory against against which API-style paths are to be resolved.
#
#  log : logging.Logger
## By default notebooks are saved on disk on a temporary file and then if
#  successfully written, it replaces the old ones. This procedure, namely
#  'atomic_writing', causes some bugs on file system without operation order
#  enforcement (like some networked fs). If set to False, the new notebook is
#  written directly on the old one which could fail (eg: full filesystem or quota
#  )
#c.FileManagerMixin.use_atomic_writing = True
#------------------------------------------------------------------------------
# FileContentsManager(FileManagerMixin,ContentsManager) configuration
#------------------------------------------------------------------------------
## If True (default), deleting files will send them to the platform's
#  trash/recycle bin, where they can be recovered. If False, deleting files
#  really deletes them.
#c.FileContentsManager.delete_to_trash = True
## Python callable or importstring thereof
#
#  to be called on the path of a file just saved.
#
#  This can be used to process the file on disk, such as converting the notebook
#  to a script or HTML via nbconvert.
#
#  It will be called as (all arguments passed by keyword)::
#
#      hook(os_path=os_path, model=model, contents_manager=instance)
#
#  - path: the filesystem path to the file just written - model: the model
#  representing the file - contents_manager: this ContentsManager instance
#c.FileContentsManager.post_save_hook = None
##
#c.FileContentsManager.root_dir = ''
## DEPRECATED, use post_save_hook. Will be removed in Notebook 5.0
#c.FileContentsManager.save_script = False
#------------------------------------------------------------------------------
# NotebookNotary(LoggingConfigurable) configuration
#------------------------------------------------------------------------------
## A class for computing and verifying notebook signatures.
## The hashing algorithm used to sign notebooks.
#c.NotebookNotary.algorithm = 'sha256'
## The sqlite file in which to store notebook signatures. By default, this will
#  be in your Jupyter data directory. You can set it to ':memory:' to disable
#  sqlite writing to the filesystem.
#c.NotebookNotary.db_file = ''
## The secret key with which notebooks are signed.
#c.NotebookNotary.secret = b''
## The file where the secret key is stored.
#c.NotebookNotary.secret_file = ''
## A callable returning the storage backend for notebook signatures. The default
#  uses an SQLite database.
#c.NotebookNotary.store_factory = traitlets.Undefined
#------------------------------------------------------------------------------
# GatewayKernelManager(MappingKernelManager) configuration
#------------------------------------------------------------------------------
## Kernel manager that supports remote kernels hosted by Jupyter Kernel or
#  Enterprise Gateway.
#------------------------------------------------------------------------------
# GatewayKernelSpecManager(KernelSpecManager) configuration
#------------------------------------------------------------------------------
#------------------------------------------------------------------------------
# GatewayClient(SingletonConfigurable) configuration
#------------------------------------------------------------------------------
## This class manages the configuration.  It's its own singleton class so that we
#  can share these values across all objects.  It also contains some helper methods
#   to build request arguments out of the various config options.
## The authorization token used in the HTTP headers.  (JUPYTER_GATEWAY_AUTH_TOKEN
#  env var)
#c.GatewayClient.auth_token = None
## The filename of CA certificates or None to use defaults.
#  (JUPYTER_GATEWAY_CA_CERTS env var)
#c.GatewayClient.ca_certs = None
## The filename for client SSL certificate, if any.  (JUPYTER_GATEWAY_CLIENT_CERT
#  env var)
#c.GatewayClient.client_cert = None
## The filename for client SSL key, if any.  (JUPYTER_GATEWAY_CLIENT_KEY env var)
#c.GatewayClient.client_key = None
## The time allowed for HTTP connection establishment with the Gateway server.
#  (JUPYTER_GATEWAY_CONNECT_TIMEOUT env var)
#c.GatewayClient.connect_timeout = 40.0
## A comma-separated list of environment variable names that will be included,
#  along with their values, in the kernel startup request.  The corresponding
#  `env_whitelist` configuration value must also be set on the Gateway server -
#  since that configuration value indicates which environmental values to make
#  available to the kernel. (JUPYTER_GATEWAY_ENV_WHITELIST env var)
#c.GatewayClient.env_whitelist = ''
## Additional HTTP headers to pass on the request.  This value will be converted
#  to a dict. (JUPYTER_GATEWAY_HEADERS env var)
#c.GatewayClient.headers = '{}'
## The password for HTTP authentication.  (JUPYTER_GATEWAY_HTTP_PWD env var)
#c.GatewayClient.http_pwd = None
## The username for HTTP authentication. (JUPYTER_GATEWAY_HTTP_USER env var)
#c.GatewayClient.http_user = None
## The gateway API endpoint for accessing kernel resources
#  (JUPYTER_GATEWAY_KERNELS_ENDPOINT env var)
#c.GatewayClient.kernels_endpoint = '/api/kernels'
## The gateway API endpoint for accessing kernelspecs
#  (JUPYTER_GATEWAY_KERNELSPECS_ENDPOINT env var)
#c.GatewayClient.kernelspecs_endpoint = '/api/kernelspecs'
## The gateway endpoint for accessing kernelspecs resources
#  (JUPYTER_GATEWAY_KERNELSPECS_RESOURCE_ENDPOINT env var)
#c.GatewayClient.kernelspecs_resource_endpoint = '/kernelspecs'
## The time allowed for HTTP request completion. (JUPYTER_GATEWAY_REQUEST_TIMEOUT
#  env var)
#c.GatewayClient.request_timeout = 40.0
## The url of the Kernel or Enterprise Gateway server where kernel specifications
#  are defined and kernel management takes place. If defined, this Notebook
#  server acts as a proxy for all kernel management and kernel specification
#  retrieval.  (JUPYTER_GATEWAY_URL env var)
#c.GatewayClient.url = None
## For HTTPS requests, determines if server's certificate should be validated or
#  not. (JUPYTER_GATEWAY_VALIDATE_CERT env var)
#c.GatewayClient.validate_cert = True
## The websocket url of the Kernel or Enterprise Gateway server.  If not
#  provided, this value will correspond to the value of the Gateway url with 'ws'
#  in place of 'http'.  (JUPYTER_GATEWAY_WS_URL env var)
#c.GatewayClient.ws_url = None
#------------------------------------------------------------------------------
# TerminalManager(LoggingConfigurable,NamedTermManager) configuration
#------------------------------------------------------------------------------
##
## Timeout (in seconds) in which a terminal has been inactive and ready to be
#  culled. Values of 0 or lower disable culling.
#c.TerminalManager.cull_inactive_timeout = 0
## The interval (in seconds) on which to check for terminals exceeding the
#  inactive timeout value.
#c.TerminalManager.cull_interval = 300

其中第284行为:

#c.NotebookApp.password = ''

将之前生成好的加密密码复制过来,即改成如下形式

c.NotebookApp.password = 'sha1:c018cb5b13a0:7b945869a95654d657655c9bb909d7a90112e843'

保存该配置文件并退出到docker容器中。这里需要指出,由于jupyter版本的不一致等因素,你的配置文件不一定和我的一样在284行,但是你应该找到的是#c.NotebookApp.password = ''这一段,将这个模板前的注释符取消既可以了。

然后,继续更改以下配置:

允许所有域名:

c.NotebookApp.allow_origin='*'

允许远程:

c.NotebookApp.allow_remote_access = True

指定默认启动目录(根据你的需求填写目录):

c.NotebookApp.notebook_dir = '/home/jupyterstart'

启动后不打开浏览器

c.NotebookApp.open_browser = False

接下来,就到了启动Nginx的时候了:

输入exeit命令退出容器(系统),即:

exit

好了,现在你要做的就是重新启动这个docker容器(注意替换成你自己系统上刚刚做的容器ID号):

docker stopc229f9b659fb
docker start c229f9b659fb

再次进入该容器

docker exec -it c229f9b659fb /bin/bash

在这个容器中,由于tensorflow官方已经帮我们配置过,jupyter服务将自动启动。因此紧接着,我们只需要启动作为反向代理的Nginxf服务器:

nginx -c /etc/nginx/nginx.conf

退出容器:

exit

这样,在云服务器中就假设好了一台juyter服务器,现在我们变可以打开浏览器,输入我们的域名地址或者服务器的ip地址,如我的域名(域名需要购买并在注册局等级注册,同时在域名供应商设置解析到自己服务器的ip地址才可以使用。域名只是相当于ip地址的助记符,没有的话直接在浏览器输入公网服务器ip也是一样的):

jcstdio.cn

第一次打开后的页面,由于没有登录过,浏览器cookie也不会由历史的密码信息,肯定是需要输入密码的。你看到的juputer登陆页面大概是这个样子的:

输入你设置的密码。注意不是经过编码加密后的密码,而是之前你设置时输入了两次才确认的原始密码。输入完成后将进入到jupyetr web的主页:

与你自己取安装jupyetr不同,这里已经配置好了tensorflow开发所需要的所有依赖包以及tensorflow本身。同时你可以注意到,这里有一个tensorflow-tutorials文件夹。打开它:

如你所见,里面的是tensorflow官方入门的经典案例。

另外,在python界混的人早早晚晚需要自己去添加一些库,每次远程登录Linux宿主机再进入docker的容器中的Linux系统以使用命令进行包管理难免不方便。这里也给大家介绍两种我常用的方法。

  • 方法一:需要时,直接在代码中安装。
    比如假装我想安装一个sklearn。先打开一个jupyter notebook,输入以下代码即可:
import os
os.sys("pip3 install sklearn")
  • 方法二:在jupyter中打开终端。
    这个看起来很向开头的 BAIDU AISTDIO。步骤如下:
    (1)打开终端:
    (2)在这里,你可以直接对docker中的系统运行bash命令。比如使用pip工具进行安装。

    还是以安装sklearn为例:
    输入pip3 install sklearn

    可以看到,由于没有给docker里ubuntu系统的python配置国内源,下载速度还是有点慢的。

最后作为补充,再教大家如何在Linux系统中将python源设置为国内源吧,这次我们以豆瓣源为例:

依次执行以下命令:

mkdir ~/.pip
cd ~/.pip
vim pip.conf

编辑pip.conf文件内容如下:

★豆瓣源(推荐):

[global]
timeout = 6000
index-url = http://pypi.douban.com/simple
trusted-host = pypi.douban.com

保存并退出,你将拥有更快的速度。

另外,还有一些比较常用的源。如:

★阿里源(推荐):

[global] 
timeout = 6000
index-url = http://mirrors.aliyun.com/pypi/simple/ 
trusted-host=mirrors.aliyun.com

国内源首选阿里源或者豆瓣源。虽然有些高校也架设了服务器同步了Pypi镜像,但作为开发者一般不推荐使用高校源。不过以下也为想试试同学精选列了一些。

中科大源(不推荐)

[global]
timeout = 6000
index-url = http://pypi.mirrors.ustc.edu.cn/simple/
trusted-host = https://pypi.tuna.tsinghua.edu.cn

清华源(不推荐):

[global]
timeout = 6000
index-url = https://pypi.tuna.tsinghua.edu.cn/simple
trusted-host = https://pypi.tuna.tsinghua.edu.cn

还有其它的国内源,只要按照上面的格式将统一资源定位符(url)进行相应的修改即可。

搜狐源

http://mirrors.sohu.com/Python/

V2EX

pypi.v2ex.com/simple

北京外果语大学源

http://pypi.mirrors.ustc.edu.cn/

华中理工大学

http://pypi.hustunique.com/

山东理工大学

http://pypi.sdutlinux.org/
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