What is Django REST framework and what are its top alternatives?
Top Alternatives to Django REST framework
Django is a high-level Python Web framework that encourages rapid development and clean, pragmatic design. ...
Flask is intended for getting started very quickly and was developed with best intentions in mind. ...
Tastypie is a webservice API framework for Django. It provides a convenient, yet powerful and highly customizable abstraction for creating REST-style interfaces. ...
- Swagger UI
Graphene is a Python library for building GraphQL schemas/types fast and easily. ...
- Spring Boot
Spring Boot makes it easy to create stand-alone, production-grade Spring based Applications that you can "just run". We take an opinionated view of the Spring platform and third-party libraries so you can get started with minimum fuss. Most Spring Boot applications need very little Spring configuration. ...
It is a web application framework with expressive, elegant syntax. It attempts to take the pain out of development by easing common tasks used in the majority of web projects, such as authentication, routing, sessions, and caching. ...
Firebase is a cloud service designed to power real-time, collaborative applications. Simply add the Firebase library to your application to gain access to a shared data structure; any changes you make to that data are automatically synchronized with the Firebase cloud and with other clients within milliseconds. ...
Django REST framework alternatives & related posts
- Rapid development648
- Open source477
- Great community410
- Easy to learn363
- Beautiful code220
- Great packages195
- Great libraries183
- Comes with auth and crud admin panel70
- Great documentation66
- Great for web62
- Great orm38
- Great for api36
- All included28
- Web Apps23
- Used by top startups20
- Easy setup18
- Convention over configuration14
- Allows for very rapid development with great libraries12
- The Django community11
- King of backend world9
- Great MVC and templating engine8
- Its elegant and practical7
- Batteries included7
- Full stack7
- Fast prototyping6
- Have not found anything that it can't do6
- Easy to develop end to end AI Models5
- Easy Structure , useful inbuilt library5
- Very quick to get something up and running5
- Great peformance4
- Many libraries4
- Python community4
- Easy to change database manager4
- Zero code burden to change databases4
- Easy to use4
- Full-Text Search3
- Just the right level of abstraction3
- Node js1
- Underpowered templating25
- Autoreload restarts whole server22
- Underpowered ORM21
- URL dispatcher ignores HTTP method15
- Internal subcomponents coupling10
- Not nodejs8
- Configuration hell7
- Not as clean and nice documentation like Laravel5
- Bloated admin panel included3
- Not typed3
- InEffective Multithreading2
- Overwhelming folder structure2
related Django posts
Simple controls over complex technologies, as we put it, wouldn't be possible without neat UIs for our user areas including start page, dashboard, settings, and docs.
Initially, there was Django. Back in 2011, considering our Python-centric approach, that was the best choice. Later, we realized we needed to iterate on our website more quickly. And this led us to detaching Django from our front end. That was when we decided to build an SPA.
For building user interfaces, we're currently using React as it provided the fastest rendering back when we were building our toolkit. It’s worth mentioning Uploadcare is not a front-end-focused SPA: we aren’t running at high levels of complexity. If it were, we’d go with Ember.js.
However, there's a chance we will shift to the faster Preact, with its motto of using as little code as possible, and because it makes more use of browser APIs. One of our future tasks for our front end is to configure our Webpack bundler to split up the code for different site sections. For styles, we use PostCSS along with its plugins such as cssnano which minifies all the code.
All that allows us to provide a great user experience and quickly implement changes where they are needed with as little code as possible.
- Open source148
- Easy to use68
- Easy to setup and get it going55
- Well designed54
- Easy to develop and maintain applications50
- Easy to get started47
- Beautiful code21
- Rapid development19
- Simple to use13
- Love it12
- Get started quickly12
- Easy to integrate11
- Perfect for small to large projects with superb docs.10
- For it flexibility10
- Flexibilty and easy to use9
- User friendly7
- Not JS7
- Not JS10
- 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.
- Good in Django2
- Fast development1
related Tastypie posts
- Open Source47
- Can execute api calls from the documentation34
- Free to use29
- Easy to implement in .Net14
- Mature, clean spec13
- API Visualization11
- Easy to use6
- Vibrant and active community5
- Adopted by tm forum api3
- Clear for React2
- Can deploy API to AWS API Gateway and AWS Lambda1
- Need to learn YAML and RAML3
- Documentation doesn't look that good2
- Doesn't generate code snippets in different languages1
- You don’t actually get in-line error highlighting1
- Does not support hypermedia1
related Swagger UI posts
We just launched the Segment Config API (try it out for yourself here) — a set of public REST APIs that enable you to manage your Segment configuration. A public API is only as good as its #documentation. For the API reference doc we are using Postman.
Postman is an “API development environment”. You download the desktop app, and build API requests by URL and payload. Over time you can build up a set of requests and organize them into a “Postman Collection”. You can generalize a collection with “collection variables”. This allows you to parameterize things like
workspace_name so a user can fill their own values in before making an API call. This makes it possible to use Postman for one-off API tasks instead of writing code.
Then you can add Markdown content to the entire collection, a folder of related methods, and/or every API method to explain how the APIs work. You can publish a collection and easily share it with a URL.
This turns Postman from a personal #API utility to full-blown public interactive API documentation. The result is a great looking web page with all the API calls, docs and sample requests and responses in one place. Check out the results here.
Postman’s powers don’t end here. You can automate Postman with “test scripts” and have it periodically run a collection scripts as “monitors”. We now have #QA around all the APIs in public docs to make sure they are always correct
Along the way we tried other techniques for documenting APIs like ReadMe.io or Swagger UI. These required a lot of effort to customize.
Writing and maintaining a Postman collection takes some work, but the resulting documentation site, interactivity and API testing tools are well worth it.
Our whole Node.js backend stack consists of the following tools:
- Lerna as a tool for multi package and multi repository management
- npm as package manager
- NestJS as Node.js framework
- TypeScript as programming language
- ExpressJS as web server
- Swagger UI for visualizing and interacting with the API’s resources
- Postman as a tool for API development
- TypeORM as object relational mapping layer
- JSON Web Token for access token management
The main reason we have chosen Node.js over PHP is related to the following artifacts:
- Flexibility: Node.js sets very few strict dependencies, rules and guidelines and thus grants a high degree of flexibility in application development. There are no strict conventions so that the appropriate architecture, design structures, modules and features can be freely selected for the development.
- Will replace RESTful interfaces0
- The future of API's0
related Graphene posts
We recently switched from MongoDB and the Python library MongoEngine to PostgreSQL and Django in order to:
- Better leverage GraphQL (using the Graphene library)
- Allow us to use the autogenerated Django admin interface
- Allow better performance due to the way some of our pages present data
- Give us more a mature stack in the form of Django replacing MongoEngine, which we had some issues with in the past.
MongoDB was hosted on mlab, and we now host Postgres on Amazon RDS .
We recently implemented GraphQL because we needed to build dynamic reports based on the user preference and configuration, this was extremely complicated with our actual RESTful API, the code started to get harder to maintain but switching to GraphQL helped us to to build beautiful reports for our clients that truly help them make data-driven decisions.
Our goal is to implemented GraphQL in the whole platform eventually, we are using Graphene , a python library for Django .
- Powerful and handy140
- Easy setup132
- Lots of "off the shelf" functionalities37
- Cloud Solid32
- Caches well26
- Many receipes around for obscure features24
- Integrations with most other Java frameworks23
- Spring ecosystem is great22
- Fast Performance With Microservices21
- Easy setup, Community Support, Solid for ERP apps17
- One-stop shop15
- Easy to parallelize14
- Powerful 3rd party libraries and frameworks13
- Easy setup, good for build erp systems, well documented13
- Easy setup, Git Integration12
- It's so easier to start a project on spring5
- Heavy weight23
- Annotation ceremony17
- Many config files needed11
- Excellent tools for cloud hosting, since 5.x4
related Spring Boot posts
We are in the process of building a modern content platform to deliver our content through various channels. We decided to go with Microservices architecture as we wanted scale. Microservice architecture style is an approach to developing an application as a suite of small independently deployable services built around specific business capabilities. You can gain modularity, extensive parallelism and cost-effective scaling by deploying services across many distributed servers. Microservices modularity facilitates independent updates/deployments, and helps to avoid single point of failure, which can help prevent large-scale outages. We also decided to use Event Driven Architecture pattern which is a popular distributed asynchronous architecture pattern used to produce highly scalable applications. The event-driven architecture is made up of highly decoupled, single-purpose event processing components that asynchronously receive and process events.
To build our #Backend capabilities we decided to use the following: 1. #Microservices - Java with Spring Boot , Node.js with ExpressJS and Python with Flask 2. #Eventsourcingframework - Amazon Kinesis , Amazon Kinesis Firehose , Amazon SNS , Amazon SQS, AWS Lambda 3. #Data - Amazon RDS , Amazon DynamoDB , Amazon S3 , MongoDB Atlas
To build #Webapps we decided to use Angular 2 with RxJS
#Devops - GitHub , Travis CI , Terraform , Docker , Serverless
Is learning Spring and Spring Boot for web apps back-end development is still relevant in 2021? Feel free to share your views with comparison to Django/Node.js/ ExpressJS or other frameworks.
Please share some good beginner resources to start learning about spring/spring boot framework to build the web apps.
- Clean architecture532
- Growing community380
- Composer friendly359
- Open source329
- The only framework to consider for php310
- Quickly develop204
- Dependency injection162
- Application architecture151
- Embraces good community packages139
- Write less, do more68
- Orm (eloquent)63
- Restful routing61
- Database migrations & seeds51
- Artisan scaffolding and migrations50
- Great documentation36
- Awsome, Powerfull, Fast and Rapid27
- Build Apps faster, easier and better26
- Promotes elegant coding25
- JSON friendly22
- Modern PHP22
- Easy to learn, scalability22
- Eloquent ORM22
- Most easy for me21
- Blade Template21
- Based on SOLID14
- Easy to attach Middleware12
- Clean Documentation12
- Convention over Configuration11
- Easy Request Validatin10
- Easy to use9
- Its just wow8
- Laravel + Cassandra = Killer Framework8
- Get going quickly straight out of the box. BYOKDM8
- Friendly API8
- Simplistic , easy and faster7
- Super easy and powerful7
- Less dependencies7
- Its beautiful to code in6
- Great customer support6
- Minimum system requirements5
- Laravel Mix5
- The only "cons" is wrong! No static method just Facades5
- Fast and Clarify framework5
- Active Record5
- Easy views handling and great ORM4
- Laravel Nova3
- Intuitive usage3
- Ease of use3
- Cashier with Braintree and Stripe3
- Laravel Forge and Envoy3
- Laravel Horizon and Telescope3
- Laravel Passport3
- Laravel casher3
- Laravel Spark3
- Rapid development2
- Succint sintax1
- Too many dependency31
- Slower than the other two22
- A lot of static method calls for convenience17
- Too many include15
- Too underrated5
- Not fast with MongoDB3
- Difficult to learn1
- Not using SOLID principles1
related Laravel posts
I need to build a web application plus android and IOS apps for an enterprise, like an e-commerce portal. It will have intensive use of MySQL to display thousands (40-50k) of live product information in an interactive table (searchable, filterable), live delivery tracking. It has to be secure, as it will handle information on customers, sales, inventory. Here is the technology stack: Backend: Laravel 7 Frondend: Vue.js, React or AngularJS?
Need help deciding technology stack. Thanks.
Back at the start of 2017, we decided to create a web-based tool for the SEO OnPage analysis of our clients' websites. We had over 2.000 websites to analyze, so we had to perform thousands of requests to get every single page from those websites, process the information and save the big amounts of data somewhere.
Very soon we realized that the initial chosen script language and database, PHP, Laravel and MySQL, was not going to be able to cope efficiently with such a task.
By that time, we were doing some experiments for other projects with a language we had recently get to know, Go , so we decided to get a try and code the crawler using it. It was fantastic, we could process much more data with way less CPU power and in less time. By using the concurrency abilites that the language has to offers, we could also do more Http requests in less time.
Unfortunately, I have no comparison numbers to show about the performance differences between Go and PHP since the difference was so clear from the beginning and that we didn't feel the need to do further comparison tests nor document it. We just switched fully to Go.
There was still a problem: despite the big amount of Data we were generating, MySQL was performing very well, but as we were adding more and more features to the software and with those features more and more different type of data to save, it was a nightmare for the database architects to structure everything correctly on the database, so it was clear what we had to do next: switch to a NoSQL database. So we switched to MongoDB, and it was also fantastic: we were expending almost zero time in thinking how to structure the Database and the performance also seemed to be better, but again, I have no comparison numbers to show due to the lack of time.
As of now, we don't only use the tool intern but we also opened it for everyone to use for free: https://tool-seo.com
- Realtime backend made easy369
- Fast and responsive268
- Easy setup240
- Backed by google126
- Angular adaptor82
- Great customer support35
- Great documentation30
- Real-time synchronization25
- Mobile friendly21
- Rapid prototyping18
- Great security14
- Automatic scaling12
- Freakingly awesome11
- Angularfire is an amazing addition!8
- Super fast development8
- Firebase hosting6
- Awesome next-gen backend6
- Ios adaptor6
- Built in user auth/oauth6
- Speed of light4
- Very easy to use4
- Brilliant for startups3
- It's made development super fast3
- Push notification2
- Free hosting2
- Free authentication solution2
- Cloud functions2
- JS Offline and Sync suport2
- Low battery consumption2
- The concurrent updates create a great experience2
- I can quickly create static web apps with no backend2
- Great all-round functionality2
- Easy to use1
- Easy Reactjs integration1
- Free SSL1
- Faster workflow1
- Google's support1
- Simple and easy1
- CDN & cache out of the box1
- Good Free Limits1
- Can become expensive31
- Scalability is not infinite15
- No open source, you depend on external company15
- Not Flexible Enough9
- Cant filter queries7
- Very unstable server3
- No Relational Data3
- Too many errors2
- No offline sync2
related Firebase posts
This is my stack in Application & Data
My Utilities Tools
Google Analytics Postman Elasticsearch
My Devops Tools
Git GitHub GitLab npm Visual Studio Code Kibana Sentry BrowserStack
My Business Tools