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）
将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/
