What is Waitress and what are its top alternatives?
Top Alternatives to Waitress
- Gunicorn
Gunicorn is a pre-fork worker model ported from Ruby's Unicorn project. The Gunicorn server is broadly compatible with various web frameworks, simply implemented, light on server resources, and fairly speedy. ...
- uWSGI
The uWSGI project aims at developing a full stack for building hosting services. ...
- Flask
Flask is intended for getting started very quickly and was developed with best intentions in mind. ...
- NGINX
nginx [engine x] is an HTTP and reverse proxy server, as well as a mail proxy server, written by Igor Sysoev. According to Netcraft nginx served or proxied 30.46% of the top million busiest sites in Jan 2018. ...
- Owin
It is a standard for an interface between .NET Web applications and Web servers. It is a community-owned open-source project. ...
- Xen Orchestra
It provides a web based UI for the management of XenServer installations without requiring any agent or extra software on your hosts nor VMs. ...
- Werbot
It is basically a platform for storing, sharing, and managing server access. But the most valuable part of it concerns the possibility to do an audit and to control the work performed on the server. Our platform can be integrated as an independent service in company infrastructure. It doesn’t change the way developers are used to working on the server, it changes the way they connect on it. All connections to servers are made through a single sign-on and private user access. All the actions performed on servers and in Werbot web interface are logged and recorded (screencasts). The server administrator can not only see what was done on the server by each user and when it was done but also can replay the whole working session in our player. The server audit is made much easier with Werbot. ...
Waitress alternatives & related posts
- Python34
- Easy setup30
- Reliable8
- Light3
- Fast3
related Gunicorn posts
Unlike our frontend, we chose Flask, a microframework, for our backend. We use it with Python 3 and Gunicorn.
One of the reasons was that I have significant experience with this framework. However, it also was a rather straightforward choice given that our backend almost only serves REST APIs, and that most of the work is talking to the database with SQLAlchemy .
We could have gone with something like Hug but it is kind of early. We might revisit that decision for new services later on.
I use Gunicorn because does one thing - it’s a WSGI HTTP server - and it does it well. Deploy it quickly and easily, and let the rest of your stack do what the rest of your stack does well, wherever that may be.
uWSGI “aims at developing a full stack for building hosting services” - if that’s a thing you need then ok, but I like the principle of doing one thing well, and I deploy to platforms like Heroku and AWS Elastic Beanstalk where the rest of the “hosting service” is provided and managed for me.
- Faster6
- Simple4
- Powerful2
related uWSGI posts
I find I really like using GitHub because its issue tracker integrates really well into my project flow and the projects feature allows me to organize different efforts into boards. The automation features allow my issues to automatically progress through some states on the boards when I merge pull requests.
My Python / Django app is deployed on Heroku with PostgreSQL database and uWSGI webserver.
I use Gunicorn because does one thing - it’s a WSGI HTTP server - and it does it well. Deploy it quickly and easily, and let the rest of your stack do what the rest of your stack does well, wherever that may be.
uWSGI “aims at developing a full stack for building hosting services” - if that’s a thing you need then ok, but I like the principle of doing one thing well, and I deploy to platforms like Heroku and AWS Elastic Beanstalk where the rest of the “hosting service” is provided and managed for me.
Flask
- Lightweight314
- Python272
- Minimal214
- Open source146
- Documentation98
- Easy to use66
- Easy to setup and get it going54
- Well designed53
- Easy to develop and maintain applications48
- Easy to get started45
- Beautiful code18
- Rapid development17
- Powerful14
- Expressive13
- Awesome12
- Flexibilty12
- Speed11
- Get started quickly11
- Love it11
- Simple to use11
- Easy to integrate10
- Customizable10
- Perfect for small to large projects with superb docs.9
- For it flexibility9
- Flexibilty and easy to use8
- Productive8
- Flask7
- User friendly6
- Not JS6
- Secured5
- Unopinionated4
- Orm1
- Secure1
- Not JS10
- Context7
- Not fast5
- Don't has many module as in spring1
related Flask posts
One of our top priorities at Pinterest is fostering a safe and trustworthy experience for all Pinners. As Pinterest’s user base and ads business grow, the review volume has been increasing exponentially, and more content types require moderation support. To solve greater engineering and operational challenges at scale, we needed a highly-reliable and performant system to detect, report, evaluate, and act on abusive content and users and so we created Pinqueue.
Pinqueue-3.0 serves as a generic platform for content moderation and human labeling. Under the hood, Pinqueue3.0 is a Flask + React app powered by Pinterest’s very own Gestalt UI framework. On the backend, Pinqueue3.0 heavily relies on PinLater, a Pinterest-built reliable asynchronous job execution system, to handle the requests for enqueueing and action-taking. Using PinLater has significantly strengthened Pinqueue3.0’s overall infra with its capability of processing a massive load of events with configurable retry policies.
Hundreds of millions of people around the world use Pinterest to discover and do what they love, and our job is to protect them from abusive and harmful content. We’re committed to providing an inspirational yet safe experience to all Pinners. Solving trust & safety problems is a joint effort requiring expertise across multiple domains. Pinqueue3.0 not only plays a critical role in responsively taking down unsafe content, it also has become an enabler for future ML/automation initiatives by providing high-quality human labels. Going forward, we will continue to improve the review experience, measure review quality and collaborate with our machine learning teams to solve content moderation beyond manual reviews at an even larger scale.
Hey, so I developed a basic application with Python. But to use it, you need a python interpreter. I want to add a GUI to make it more appealing. What should I choose to develop a GUI? I have very basic skills in front end development (CSS, JavaScript). I am fluent in python. I'm looking for a tool that is easy to use and doesn't require too much code knowledge. I have recently tried out Flask, but it is kinda complicated. Should I stick with it, move to Django, or is there another nice framework to use?
NGINX
- High-performance http server1.4K
- Performance893
- Easy to configure727
- Open source606
- Load balancer529
- Scalability287
- Free286
- Web server223
- Simplicity174
- Easy setup135
- Content caching29
- Web Accelerator20
- Capability14
- Fast13
- High-latency11
- Predictability11
- Reverse Proxy7
- Supports http/26
- The best of them5
- Great Community4
- Lots of Modules4
- Enterprise version4
- High perfomance proxy server3
- Embedded Lua scripting3
- Reversy Proxy3
- Streaming media delivery3
- Streaming media3
- Fast and easy to set up2
- Slim2
- Blash2
- Lightweight2
- saltstack2
- Virtual hosting1
- Along with Redis Cache its the Most superior1
- Ingress controller1
- Narrow focus. Easy to configure. Fast1
- GRPC-Web1
- Advanced features require subscription8
related NGINX posts

















Recently I have been working on an open source stack to help people consolidate their personal health data in a single database so that AI and analytics apps can be run against it to find personalized treatments. We chose to go with a #containerized approach leveraging Docker #containers with a local development environment setup with Docker Compose and nginx for container routing. For the production environment we chose to pull code from GitHub and build/push images using Jenkins and using Kubernetes to deploy to Amazon EC2.
We also implemented a dashboard app to handle user authentication/authorization, as well as a custom SSO server that runs on Heroku which allows experts to easily visit more than one instance without having to login repeatedly. The #Backend was implemented using my favorite #Stack which consists of FeathersJS on top of Node.js and ExpressJS with PostgreSQL as the main database. The #Frontend was implemented using React, Redux.js, Semantic UI React and the FeathersJS client. Though testing was light on this project, we chose to use AVA as well as ESLint to keep the codebase clean and consistent.
We switched to Traefik so we can use the REST API to dynamically configure subdomains and have the ability to redirect between multiple servers.
We still use nginx with a docker-compose to expose the traffic from our APIs and TCP microservices, but for managing routing to the internet Traefik does a much better job
The biggest win for naologic was the ability to set dynamic configurations without having to restart the server