gunicorn

Gunicorn worker timeout error

杀马特。学长 韩版系。学妹 提交于 2019-11-27 04:10:41
问题 I have setup gunicorn with 3 workers 30 worker connections and using eventlet worker class. It is setup behind Nginx. After every few requests, I see this in the logs. [ERROR] gunicorn.error: WORKER TIMEOUT (pid:23475) None [INFO] gunicorn.error: Booting worker with pid: 23514 Why is this happening? How can I figure out whats going wrong? thanks 回答1: We had the same problem using Django+nginx+gunicorn. From Gunicorn documentation we have configured the graceful-timeout that made almost no

gunicorn autoreload on source change

北城以北 提交于 2019-11-27 03:24:49
Finally I migrated my development env from runserver to gunicorn/nginx. It'd be convenient to replicate the autoreload feature of runserver to gunicorn, so the server automatically restarts when source changes. Otherwise I have to restart the server manually with kill -HUP . Any way to avoid the manual restart? Dmitry Ziolkovskiy While this is old question, just for consistency - since version 19.0 gunicorn has --reload option. So no third party tools needed more. One option would be to use the --max-requests to limit each spawned process to serving only one request by adding --max-requests 1

How to use environment variables with supervisor, gunicorn and django (1.6)

我们两清 提交于 2019-11-27 00:52:36
问题 I want to configure supervisor to control gunicorn in my django 1.6 project using an environment variable for SECRET_KEY. I set my secret key in .bashrc as export SECRET_KEY=[my_secret_key] And I have a shell script to start gunicorn: NAME="myproject" LOGFILE=/home/django/myproject/log/gunicorn.log LOGDIR=$(dirname $LOGFILE) NUM_WORKERS=3 DJANGO_WSGI_MODULE=myproject.wsgi USER=django GROUP=django IP=0.0.0.0 PORT=8001 echo "Starting $NAME" cd /home/django/myproject/myproject source /home

Gunicorn Nginx timeout problem

强颜欢笑 提交于 2019-11-27 00:08:42
I'm running django on gunicorn+nginx. I'm facing a problem with file uploads. Actually uploads are working fine but gunicorn times out thus causing this in nginx: 2011/07/25 12:13:47 [error] 15169#0: *2317 upstream timed out (110: Connection timed out) while reading response header from upstream, client: IP-ADDRESS, server: SERVER, request: "GET /photos/events/event/25 HTTP/1.1", upstream: "http://127.0.0.1:29000/photos/events/event/25", host: "HOST", referrer: "REFERER_ADDRESS" If I refresh the page, I can see all the photos are uploaded just fine. The problem is that it causes a timeout thus

部署flask

我的梦境 提交于 2019-11-26 22:51:08
python web 部署 web开发中,各种语言争奇斗艳,web的部署方面,却没有太多的方式。简单而已,大概都是 nginx 做前端代理,中间 webservice 调用程序脚本。大概方式: nginx + webservice + script nginx 不用多说,一个高性能的web服务器。通常用来在前端做反向代理服务器。所谓正向与反向(reverse),只是英文说法翻译。代理服务,简而言之,一个请求经过代理服务器从局域网发出,然后到达互联网上服务器,这个过程的代理为正向代理。如果一个请求,从互联网过来,先进入代理服务器,再由代理服务器转发给局域网的目标服务器,这个时候,代理服务器为反向代理(相对正向而言)。 正向代理:{ 客户端 ---》 代理服务器 } ---》 服务器 反向代理:客户端 ---》 { 代理服务器 ---》 服务器 } {} 表示局域网 nginx既可以做正向,也可以做反向。 webservice 的方式同样也有很多方式。常见的有 FastCGI , WSGI 等。我们采用 gunicorn 为 wsgi容器。python为服务器script,采用 flask 框架。同时采用supervisor管理服务器进程。也就是最终的部署方式为: nginx + gunicorn + flask ++ supervisor 创建一个项目 mkdir myproject

How many concurrent requests does a single Flask process receive?

你离开我真会死。 提交于 2019-11-26 21:26:28
I'm building an app with Flask, but I don't know much about WSGI and it's HTTP base, Werkzeug. When I start serving a Flask application with gunicorn and 4 worker processes, does this mean that I can handle 4 concurrent requests? I do mean concurrent requests, and not requests per second or anything else. When running the development server you get running app.run() , you get a single synchronous process, which means at most 1 requests being processed at a time. By sticking Gunicorn in front of it in its default configuration and simply increasing the number of --workers , what you get is

How to run Flask with Gunicorn in multithreaded mode

白昼怎懂夜的黑 提交于 2019-11-26 19:09:33
问题 I have web application written in Flask. As suggested by everyone, I can't use Flask in production. So I thought of Gunicorn with Flask . In Flask application I am loading some Machine Learning models. These are of size 8GB collectively. Concurrency of my web application can go upto 1000 requests . And the RAM of machine is 15GB. So what is the best way to run this application? 回答1: You can start your app with multiple workers or async workers with Gunicorn. Flask server.py from flask import

How can I modify Procfile to run Gunicorn process in a non-standard folder on Heroku?

南楼画角 提交于 2019-11-26 17:58:12
问题 I'm new to heroku and gunicorn so I'm not sure how this works. But I've done some searching and I think I'm close to deploying my Django app (1.5.1). So I know I need a Procfile which has web: gunicorn app.wsgi Because my directories are a bit different. I can't run gunicorn in the root directory app_project requirements/ contributors/ app/ app/ settings/ wsgi.py # Normally Procfile goes here Procfile Normally app/ would be the root directory, but I decided to structure my folders this way to

How to use Flask-Script and Gunicorn

北城以北 提交于 2019-11-26 15:33:24
问题 I'm working on on a Flask app using Flask's built in dev server. I start it using Flask-Script. I want to switch to using Gunicorn as the web server. To do so, do I need to write some sort of integration code between Flask-Script and Gunicorn? Or is Flask-Script irrelevant to running the app using Gunicorn? Thanks in advance! Props to @sean-lynch. The following is working, tested code based on his answer. The changes I made were: Options that aren't recognized by Gunicorn are removed from sys

Debugging a Flask app running in Gunicorn

℡╲_俬逩灬. 提交于 2019-11-26 12:53:56
问题 I\'ve been working on a new dev platform using nginx/gunicorn and Flask for my application. Ops-wise, everything works fine - the issue I\'m having is with debugging the Flask layer. When there\'s an error in my code, I just get a straight 500 error returned to the browser and nothing shows up on the console or in my logs. I\'ve tried many different configs/options.. I guess I must be missing something obvious. My gunicorn.conf: import os bind = \'127.0.0.1:8002\' workers = 3 backlog = 2048