然后运行四个 python 程序，端口为咱们配置好的端口
WSGI framework 就是我们经常提到的 Django 这种框架。不过需要注意的是, 很少有单纯的 WSGI framework , 基于 WSGI 的框架往往都自带 WSGI server。比如 Django、CherryPy 都自带 WSGI server 主要是测试用途, 发布时则使用生产环境的 WSGI server。而有些 WSGI 下的框架比如 pylons、bfg 等, 自己不实现 WSGI server。使用 paste 作为 WSGI server。Paste 是流行的 WSGI server, 带有很多中间件。还有 flup 也是一个提供中间件的库。搞清除 WSGI server 和 application, 中间件自然就清楚了。除了 session、cache 之类的应用, 前段时间看到一个 bfg 下的中间件专门用于给网站换肤的 (skin) 。中间件可以想到的用法还很多。这里再补充一下, 像 django 这样的框架如何以 fastcgi 的方式跑在 apache 上的。这要用到 flup.fcgi 或者 fastcgi.py (eurasia 中也设计了一个 fastcgi.py 的实现) 这些工具, 它们就是把 fastcgi 协议转换成 WSGI 接口 (把 fastcgi 变成一个 WSGI server) 供框架接入。整个架构是这样的: django -> fcgi2wsgiserver -> mod_fcgi -> apache 。虽然我不是 WSGI 的粉丝, 但是不可否认 WSGI 对 python web 的意义重大。有意自己设计 web 框架, 又不想做 socket 层和 http 报文解析的同学, 可以从 WSGI 开始设计自己的框架。在 python 圈子里有个共识, 自己随手搞个 web 框架跟喝口水一样自然, 非常方便。或许每个 python 玩家都会经历一个倒腾框架的
启动一个 fastcgi 的进程
uwsgi 的官方文档：
为了让多个站点共享一个 uwsgi 服务，必须把 uwsgi 运行成虚拟站点：去掉“-w myapp”加上”–vhost”：
再来搞下 fastcgi 的方式
uwsgi 的参数以上是单个 project 的最简单化部署，uwsgi 还是有很多令人称赞的功能的，例如：并发 4 个线程： uwsgi -s :9090 -w myapp -p 4主控制线程 +4 个线程： uwsgi -s :9090 -w myapp -M -p 4执行超过 30 秒的 client 直接放弃： uwsgi -s :9090 -w myapp -M -p 4 -t 30限制内存空间 128M： uwsgi -s :9090 -w myapp -M -p 4 -t 30 --limit-as 128服务超过 10000 个 req 自动 respawn： uwsgi -s :9090 -w myapp -M -p 4 -t 30 --limit-as 128 -R 10000后台运行等： uwsgi -s :9090 -w myapp -M -p 4 -t 30 --limit-as 128 -R 10000 -d uwsgi.log
uWSGI 的主要特点如下：
upstream backend {server 127.0.0.1:8888;server 127.0.0.1:8887;server 127.0.0.1:8886;server 127.0.0.1:8885;} server{listen 80;server_name message.test.com;keepalive_timeout 65; #proxy_read_timeout 2000; #sendfile on;tcp_nopush on;tcp_nodelay on; location / {proxy_pass_header Server;proxy_set_header Host $http_host;proxy_redirect off;proxy_set_header X-Real-IP $remote_addr;proxy_set_header X-Scheme $scheme;proxy_pass http://backend;}} fcgi ：用 spawn-fcgi 或者框架自带的工具对各个 project 分别生成监听进程，然后和 http 服务互动wsgi ：利用 http 服务的 mod_wsgi 模块来跑各个 project(Web 应用程序或框架简单而通用的 Web 服务器 之间的接口)。uWSGI 是一款像 php-cgi 一样监听同一端口，进行统一管理和负载平衡的工具，uWSGI，既不用 wsgi 协议也不用 fcgi 协议，而是自创了一个 uwsgi 的协议，据说该协议大约是 fcgi 协议的 10 倍那么快。
uwsgi 的调优参数~
spawn-fcgi -d /path/to/www -f /path/to/www/index.py -a 127.0.0.1 -p 9002
大家可以先用 uwsgi，要还是有压力和堵塞的话，可以用用 nginx 做负载。
uwsgi -s :9090 -w myapp
uwsgi -s :9090 -M -p 4 -t 30 --limit-as 128 -R 10000 -d uwsgi.log --vhost
图片 2.1 pic
import subprocessimport tornado.ioloopimport timeimport fcntlimport functoolsimport osclass GenericSubprocess (object): def __init__ ( self, timeout=-1, **popen_args ):self.args = dictself.args["stdout"] = subprocess.PIPEself.args["stderr"] = subprocess.PIPEself.args["close_fds"] = Trueself.args.update(popen_args)self.ioloop = Noneself.expiration = Noneself.pipe = Noneself.timeout = timeoutself.streams = self.has_timed_out = False def start(self):"""Spawn the task.Throws RuntimeError if the task was already started."""if not self.pipe is None: raise RuntimeError("Cannot start task twice")self.ioloop = tornado.ioloop.IOLoop.instanceif self.timeout > 0: self.expiration = self.ioloop.add_timeout( time.time + self.timeout, self.on_timeout )self.pipe = subprocess.Popen(**self.args)self.streams = [ (self.pipe.stdout.fileno, ), (self.pipe.stderr.fileno, ) ]for fd, d in self.streams: flags = fcntl.fcntl(fd, fcntl.F_GETFL)| os.O_NDELAY fcntl.fcntl( fd, fcntl.F_SETFL, flags) self.ioloop.add_handler( fd, self.stat, self.ioloop.READ|self.ioloop.ERROR) def on_timeout(self):self.has_timed_out = Trueself.cancel def cancel (self ) :"""Cancel task executionSends SIGKILL to the child process."""try: self.pipe.killexcept: pass def stat( self, *args ):\'\'\'Check process completion and consume pending I/O data\'\'\'self.pipe.pollif not self.pipe.returncode is None: \'\'\'cleanup handlers and timeouts\'\'\' if not self.expiration is None:self.ioloop.remove_timeout(self.expiration) for fd, dest in self.streams:self.ioloop.remove_handler(fd) \'\'\'schedulle callback (first try to read all pending data)\'\'\' self.ioloop.add_callback(self.on_finish)for fd, dest in self.streams: while True:try: data = os.read(fd, 4096) if len(data) == 0:break dest.extend([data])except: break @property def stdout(self):return self.get_output(0) @property def stderr(self):return self.get_output(1) @property def status(self):return self.pipe.returncode def get_output(self, index ):return "".join(self.streams[index][1]) def on_finish(self):raise NotImplementedclass Subprocess (GenericSubprocess): """Create new instance Arguments:callback: method to be called after completion. This method should take 3 arguments: statuscode(int), stdout(str), stderr(str), has_timed_out(boolean)timeout: wall time allocated for the process to complete. After this expires Task.cancel is called. A negative timeout value means no limit is set The task is not started until start is called. The process will then be spawned using subprocess.Popen(**popen_args). The stdout and stderr are always set to subprocess.PIPE. """ def __init__ ( self, callback, *args, **kwargs):"""Create new instanceArguments: callback: method to be called after completion. This method should take 3 arguments: statuscode(int), stdout(str), stderr(str), has_timed_out(boolean) timeout: wall time allocated for the process to complete. After this expires Task.cancel is called. A negative timeout value means no limit is setThe task is not started until start is called. The process will then be spawned using subprocess.Popen(**popen_args). The stdout and stderr are always set to subprocess.PIPE."""self.callback = callbackself.done_callback = FalseGenericSubprocess.__init__(self, *args, **kwargs) def on_finish(self):if not self.done_callback: self.done_callback = True \'\'\'prevent calling callback twice\'\'\' self.ioloop.add_callback(functools.partial(self.callback, self.status, self.stdout, self.stderr, self.has_timed_out))if __name__ == "__main__": ioloop = tornado.ioloop.IOLoop.instance def print_timeout( status, stdout, stderr, has_timed_out) :assert(status!=0)assert(has_timed_out)print "OK status:", repr(status), "stdout:", repr(stdout), "stderr:", repr(stderr), "timeout:", repr(has_timed_out) def print_ok( status, stdout, stderr, has_timed_out) :assert(status==0)assert(not has_timed_out)print "OK status:", repr(status), "stdout:", repr(stdout), "stderr:", repr(stderr), "timeout:", repr(has_timed_out) def print_error( status, stdout, stderr, has_timed_out):assert(status!=0)assert(not has_timed_out)print "OK status:", repr(status), "stdout:", repr(stdout), "stderr:", repr(stderr), "timeout:", repr(has_timed_out) def stop_test:ioloop.stop t1 = Subprocess( print_timeout, timeout=3, args=[ "sleep", "5" ] ) t2 = Subprocess( print_ok, timeout=3, args=[ "sleep", "1" ] ) t3 = Subprocess( print_ok, timeout=3, args=[ "sleepdsdasdas", "1" ] ) t4 = Subprocess( print_error, timeout=3, args=[ "cat", "/etc/sdfsdfsdfsdfsdfsdfsdf" ] ) t1.start t2.start try:t3.startassert(false) except:print "OK" t4.start ioloop.add_timeout(time.time + 10, stop_test) ioloop.start 启动 nginx
WSGI server 把服务器功能以 WSGI 接口暴露出来。比如 mod_wsgi 是一种 server, 把 apache 的功能以 WSGI 接口的形式提供出来。
这样，重启 nginx 服务，两个站点就可以共用一个 uwsgi 服务了。
用 web.py 写的一个小 demo 测试
部署的时候采用了单 IP 多端口方式，服务器有 4 个核心，决定开 4 个端口对应，分别是 8885~8888，修改
http://projects.unbit.it/uwsgi/wiki/Doc
我自己的经验来看还是这个靠谱~
nginx.conflocation / { include uwsgi_params uwsgi_pass 127.0.0.1:9090} 前端 nginx 用负责负载分发：
server { listen 80; server_name app1.mydomain.com; location / { include uwsgi_params; uwsgi_pass 127.0.0.1:9090; uwsgi_param UWSGI_PYHOME /var/www/myenv; uwsgi_param UWSGI_SCRIPT myapp1; uwsgi_param UWSGI_CHDIR /var/www/myappdir1; }}server { listen 80; server_name app2.mydomain.com; location / { include uwsgi_params; uwsgi_pass 127.0.0.1:9090; uwsgi_param UWSGI_PYHOME /var/www/myenv; uwsgi_param UWSGI_SCRIPT myapp2; uwsgi_param UWSGI_CHDIR /var/www/myappdir2; }} #!/usr/bin/env python # -*- coding: utf-8 -*-import weburls = ("/.*", "hello")app = web.application(urls, globals)class hello: def GET(self):return \'Hello, world!\'if __name__ == "__main__": web.wsgi.runwsgi = lambda func, addr=None: web.wsgi.runfcgi(func, addr) app.run 最后配置 nginx，注意每个站点必须单独占用一个 server，同一 server 不同 location 定向到不同的应用不知为何总是失败，估计也 算是一个 bug。
其实 WSGI 是分成 server 和 framework (即 application) 两部分 (当然还有 middleware)。严格说 WSGI 只是一个协议, 规范 server 和 framework 之间连接的接口。
启动 app
然后必须配置 virtualenv，virtualenv 是 Python 的一个很有用的虚拟环境工具，这样安装：
我这里用 tornado 写了一个执行系统程序的例子：
location / {fastcgi_param REQUEST_METHOD $request_method;fastcgi_param QUERY_STRING $query_string;fastcgi_param CONTENT_TYPE $content_type;fastcgi_param CONTENT_LENGTH $content_length;fastcgi_param GATEWAY_INTERFACE CGI/1.1;fastcgi_param SERVER_SOFTWARE nginx/$nginx_version;fastcgi_param REMOTE_ADDR $remote_addr;fastcgi_param REMOTE_PORT $remote_port;fastcgi_param SERVER_ADDR $server_addr;fastcgi_param SERVER_PORT $server_port;fastcgi_param SERVER_NAME $server_name;fastcgi_param SERVER_PROTOCOL $server_protocol;fastcgi_param SCRIPT_FILENAME $fastcgi_script_name;fastcgi_param PATH_INFO $fastcgi_script_name;fastcgi_pass 127.0.0.1:9002;} location /static/ {root /path/to/www;if (-f $request_filename) { rewrite ^/static/(.*)$ /static/$1 break;} } nginx
这样就 ok 了~