What is GraphiQL and what are its top alternatives?
GraphiQL is a powerful in-browser IDE for exploring GraphQL APIs. It provides an interactive interface for executing queries, viewing documentation, and exploring the schema. However, GraphiQL has limitations such as lack of advanced features like code autocompletion and doesn't support multiple query executions simultaneously.
- Insomnia: Insomnia is a popular alternative to GraphiQL that supports not only GraphQL but also other API types. It offers features like code autocompletion, multiple tabs, and the ability to save and share requests. Pros include versatility and a user-friendly interface, while cons may include a learning curve for beginners to API testing.
- Altair: Altair is an open-source GraphQL client that provides a clean and intuitive interface for executing queries and mutations. Features include query history, response visualization, and customizable themes. Pros of Altair include its simplicity and flexibility, but some users may miss advanced features offered by other tools.
- GraphQL Playground: GraphQL Playground is an interactive GraphQL IDE that offers features like automatic schema introspection, query history, and real-time error highlighting. Pros include robust debugging capabilities and customizable settings, while cons may include a cluttered interface for some users.
- Postman: Postman is a versatile API client that supports various protocols including GraphQL. It offers features like test automation, collections for organizing requests, and real-time collaboration. Pros include a wide range of features for API testing, while cons may include a steeper learning curve compared to specialized GraphQL clients.
- Paw: Paw is a powerful API client for macOS that supports GraphQL along with other API types. It offers features like dynamic values, code generation, and request chaining. Pros include advanced functionalities for API testing and customization options, but some users may find it overwhelming due to its complexity.
- GraphCMS: GraphCMS is a headless CMS and GraphQL API that provides a built-in GraphiQL interface for querying and exploring the schema. It offers features like content modeling, role-based permissions, and webhooks. Pros include seamless integration with a CMS platform, while cons may include limited customization options compared to standalone clients.
- Postwoman: Postwoman is an open-source API request builder that supports GraphQL along with other protocols. It offers features like environment variables, scriptable requests, and response visualization. Pros include a lightweight and customizable interface, while cons may include fewer advanced features compared to specialized GraphQL clients.
- Hoppscotch: Hoppscotch is an open-source API client that supports GraphQL and other protocols. It offers features like batch execution, request templating, and response validation. Pros include a user-friendly interface and robust documentation, while cons may include limited integrations and functionalities compared to specialized GraphQL clients.
- GraphQL Editor: GraphQL Editor is a visual tool for designing GraphQL schemas and generating code. It offers features like drag-and-drop schema building, syntax highlighting, and collaborative editing. Pros include a visual approach to GraphQL development, while cons may include limited support for executing queries directly within the tool.
- GraphiQL.app: GraphiQL.app is a standalone desktop application for using GraphiQL without the need for a browser. It offers features similar to the in-browser version, such as syntax highlighting, autocomplete, and schema exploration. Pros include a dedicated application for interacting with GraphQL APIs, while cons may include potential limitations compared to more feature-rich alternatives.
Top Alternatives to GraphiQL
- GraphQL
GraphQL is a data query language and runtime designed and used at Facebook to request and deliver data to mobile and web apps since 2012. ...
- Apollo
Build a universal GraphQL API on top of your existing REST APIs, so you can ship new application features fast without waiting on backend changes. ...
- Postman
It is the only complete API development environment, used by nearly five million developers and more than 100,000 companies worldwide. ...
- REST
An architectural style for developing web services. A distributed system framework that uses Web protocols and technologies. ...
- JavaScript
JavaScript is most known as the scripting language for Web pages, but used in many non-browser environments as well such as node.js or Apache CouchDB. It is a prototype-based, multi-paradigm scripting language that is dynamic,and supports object-oriented, imperative, and functional programming styles. ...
- Git
Git is a free and open source distributed version control system designed to handle everything from small to very large projects with speed and efficiency. ...
- GitHub
GitHub is the best place to share code with friends, co-workers, classmates, and complete strangers. Over three million people use GitHub to build amazing things together. ...
- Python
Python is a general purpose programming language created by Guido Van Rossum. Python is most praised for its elegant syntax and readable code, if you are just beginning your programming career python suits you best. ...
GraphiQL alternatives & related posts
- Schemas defined by the requests made by the user75
- Will replace RESTful interfaces63
- The future of API's62
- The future of databases49
- Self-documenting13
- Get many resources in a single request12
- Query Language6
- Ask for what you need, get exactly that6
- Fetch different resources in one request3
- Type system3
- Evolve your API without versions3
- Ease of client creation2
- GraphiQL2
- Easy setup2
- "Open" document1
- Fast prototyping1
- Supports subscription1
- Standard1
- Good for apps that query at build time. (SSR/Gatsby)1
- 1. Describe your data1
- Better versioning1
- Backed by Facebook1
- Easy to learn1
- Hard to migrate from GraphQL to another technology4
- More code to type.4
- Takes longer to build compared to schemaless.2
- No support for caching1
- All the pros sound like NFT pitches1
- No support for streaming1
- Works just like any other API at runtime1
- N+1 fetch problem1
- No built in security1
related GraphQL posts
I just finished the very first version of my new hobby project: #MovieGeeks. It is a minimalist online movie catalog for you to save the movies you want to see and for rating the movies you already saw. This is just the beginning as I am planning to add more features on the lines of sharing and discovery
For the #BackEnd I decided to use Node.js , GraphQL and MongoDB:
Node.js has a huge community so it will always be a safe choice in terms of libraries and finding solutions to problems you may have
GraphQL because I needed to improve my skills with it and because I was never comfortable with the usual REST approach. I believe GraphQL is a better option as it feels more natural to write apis, it improves the development velocity, by definition it fixes the over-fetching and under-fetching problem that is so common on REST apis, and on top of that, the community is getting bigger and bigger.
MongoDB was my choice for the database as I already have a lot of experience working on it and because, despite of some bad reputation it has acquired in the last months, I still believe it is a powerful database for at least a very long list of use cases such as the one I needed for my website
When I joined NYT there was already broad dissatisfaction with the LAMP (Linux Apache HTTP Server MySQL PHP) Stack and the front end framework, in particular. So, I wasn't passing judgment on it. I mean, LAMP's fine, you can do good work in LAMP. It's a little dated at this point, but it's not ... I didn't want to rip it out for its own sake, but everyone else was like, "We don't like this, it's really inflexible." And I remember from being outside the company when that was called MIT FIVE when it had launched. And been observing it from the outside, and I was like, you guys took so long to do that and you did it so carefully, and yet you're not happy with your decisions. Why is that? That was more the impetus. If we're going to do this again, how are we going to do it in a way that we're gonna get a better result?
So we're moving quickly away from LAMP, I would say. So, right now, the new front end is React based and using Apollo. And we've been in a long, protracted, gradual rollout of the core experiences.
React is now talking to GraphQL as a primary API. There's a Node.js back end, to the front end, which is mainly for server-side rendering, as well.
Behind there, the main repository for the GraphQL server is a big table repository, that we call Bodega because it's a convenience store. And that reads off of a Kafka pipeline.
- From the creators of Meteor12
- Great documentation8
- Open source3
- Real time if use subscription2
- File upload is not supported1
- Increase in complexity of implementing (subscription)1
related Apollo posts
Oof. I have truly hated JavaScript for a long time. Like, for over twenty years now. Like, since the Clinton administration. It's always been a nightmare to deal with all of the aspects of that silly language.
But wowza, things have changed. Tooling is just way, way better. I'm primarily web-oriented, and using React and Apollo together the past few years really opened my eyes to building rich apps. And I deeply apologize for using the phrase rich apps; I don't think I've ever said such Enterprisey words before.
But yeah, things are different now. I still love Rails, and still use it for a lot of apps I build. But it's that silly rich apps phrase that's the problem. Users have way more comprehensive expectations than they did even five years ago, and the JS community does a good job at building tools and tech that tackle the problems of making heavy, complicated UI and frontend work.
Obviously there's a lot of things happening here, so just saying "JavaScript isn't terrible" might encompass a huge amount of libraries and frameworks. But if you're like me, yeah, give things another shot- I'm somehow not hating on JavaScript anymore and... gulp... I kinda love it.
When I joined NYT there was already broad dissatisfaction with the LAMP (Linux Apache HTTP Server MySQL PHP) Stack and the front end framework, in particular. So, I wasn't passing judgment on it. I mean, LAMP's fine, you can do good work in LAMP. It's a little dated at this point, but it's not ... I didn't want to rip it out for its own sake, but everyone else was like, "We don't like this, it's really inflexible." And I remember from being outside the company when that was called MIT FIVE when it had launched. And been observing it from the outside, and I was like, you guys took so long to do that and you did it so carefully, and yet you're not happy with your decisions. Why is that? That was more the impetus. If we're going to do this again, how are we going to do it in a way that we're gonna get a better result?
So we're moving quickly away from LAMP, I would say. So, right now, the new front end is React based and using Apollo. And we've been in a long, protracted, gradual rollout of the core experiences.
React is now talking to GraphQL as a primary API. There's a Node.js back end, to the front end, which is mainly for server-side rendering, as well.
Behind there, the main repository for the GraphQL server is a big table repository, that we call Bodega because it's a convenience store. And that reads off of a Kafka pipeline.
- Easy to use490
- Great tool369
- Makes developing rest api's easy peasy276
- Easy setup, looks good156
- The best api workflow out there144
- It's the best53
- History feature53
- Adds real value to my workflow44
- Great interface that magically predicts your needs43
- The best in class app35
- Can save and share script12
- Fully featured without looking cluttered10
- Collections8
- Option to run scrips8
- Global/Environment Variables8
- Shareable Collections7
- Dead simple and useful. Excellent7
- Dark theme easy on the eyes7
- Awesome customer support6
- Great integration with newman6
- Documentation5
- Simple5
- The test script is useful5
- Saves responses4
- This has simplified my testing significantly4
- Makes testing API's as easy as 1,2,34
- Easy as pie4
- API-network3
- I'd recommend it to everyone who works with apis3
- Mocking API calls with predefined response3
- Now supports GraphQL2
- Postman Runner CI Integration2
- Easy to setup, test and provides test storage2
- Continuous integration using newman2
- Pre-request Script and Test attributes are invaluable2
- Runner2
- Graph2
- <a href="http://fixbit.com/">useful tool</a>1
- Stores credentials in HTTP10
- Bloated features and UI9
- Cumbersome to switch authentication tokens8
- Poor GraphQL support7
- Expensive5
- Not free after 5 users3
- Can't prompt for per-request variables3
- Import swagger1
- Support websocket1
- Import curl1
related Postman posts
I am starting to become a full-stack developer, by choosing and learning .NET Core for API Development, Angular CLI / React for UI Development, MongoDB for database, as it a NoSQL DB and Flutter / React Native for Mobile App Development. Using Postman, Markdown and Visual Studio Code for development.
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 username
, password
and 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.
related REST posts
JavaScript
- Can be used on frontend/backend1.7K
- It's everywhere1.5K
- Lots of great frameworks1.2K
- Fast896
- Light weight745
- Flexible425
- You can't get a device today that doesn't run js392
- Non-blocking i/o286
- Ubiquitousness236
- Expressive191
- Extended functionality to web pages55
- Relatively easy language49
- Executed on the client side46
- Relatively fast to the end user30
- Pure Javascript25
- Functional programming21
- Async15
- Full-stack13
- Setup is easy12
- Its everywhere12
- JavaScript is the New PHP11
- Because I love functions11
- Like it or not, JS is part of the web standard10
- Can be used in backend, frontend and DB9
- Expansive community9
- Future Language of The Web9
- Easy9
- No need to use PHP8
- For the good parts8
- Can be used both as frontend and backend as well8
- Everyone use it8
- Most Popular Language in the World8
- Easy to hire developers8
- Love-hate relationship7
- Powerful7
- Photoshop has 3 JS runtimes built in7
- Evolution of C7
- Popularized Class-Less Architecture & Lambdas7
- Agile, packages simple to use7
- Supports lambdas and closures7
- 1.6K Can be used on frontend/backend6
- It's fun6
- Hard not to use6
- Nice6
- Client side JS uses the visitors CPU to save Server Res6
- Versitile6
- It let's me use Babel & Typescript6
- Easy to make something6
- Its fun and fast6
- Can be used on frontend/backend/Mobile/create PRO Ui6
- Function expressions are useful for callbacks5
- What to add5
- Client processing5
- Everywhere5
- Scope manipulation5
- Stockholm Syndrome5
- Promise relationship5
- Clojurescript5
- Because it is so simple and lightweight4
- Only Programming language on browser4
- Hard to learn1
- Test1
- Test21
- Easy to understand1
- Not the best1
- Easy to learn1
- Subskill #41
- Hard 彤0
- A constant moving target, too much churn22
- Horribly inconsistent20
- Javascript is the New PHP15
- No ability to monitor memory utilitization9
- Shows Zero output in case of ANY error8
- Thinks strange results are better than errors7
- Can be ugly6
- No GitHub3
- Slow2
related JavaScript posts
Oof. I have truly hated JavaScript for a long time. Like, for over twenty years now. Like, since the Clinton administration. It's always been a nightmare to deal with all of the aspects of that silly language.
But wowza, things have changed. Tooling is just way, way better. I'm primarily web-oriented, and using React and Apollo together the past few years really opened my eyes to building rich apps. And I deeply apologize for using the phrase rich apps; I don't think I've ever said such Enterprisey words before.
But yeah, things are different now. I still love Rails, and still use it for a lot of apps I build. But it's that silly rich apps phrase that's the problem. Users have way more comprehensive expectations than they did even five years ago, and the JS community does a good job at building tools and tech that tackle the problems of making heavy, complicated UI and frontend work.
Obviously there's a lot of things happening here, so just saying "JavaScript isn't terrible" might encompass a huge amount of libraries and frameworks. But if you're like me, yeah, give things another shot- I'm somehow not hating on JavaScript anymore and... gulp... I kinda love it.
How Uber developed the open source, end-to-end distributed tracing Jaeger , now a CNCF project:
Distributed tracing is quickly becoming a must-have component in the tools that organizations use to monitor their complex, microservice-based architectures. At Uber, our open source distributed tracing system Jaeger saw large-scale internal adoption throughout 2016, integrated into hundreds of microservices and now recording thousands of traces every second.
Here is the story of how we got here, from investigating off-the-shelf solutions like Zipkin, to why we switched from pull to push architecture, and how distributed tracing will continue to evolve:
https://eng.uber.com/distributed-tracing/
(GitHub Pages : https://www.jaegertracing.io/, GitHub: https://github.com/jaegertracing/jaeger)
Bindings/Operator: Python Java Node.js Go C++ Kubernetes JavaScript OpenShift C# Apache Spark
- Distributed version control system1.4K
- Efficient branching and merging1.1K
- Fast959
- Open source845
- Better than svn726
- Great command-line application368
- Simple306
- Free291
- Easy to use232
- Does not require server222
- Distributed27
- Small & Fast22
- Feature based workflow18
- Staging Area15
- Most wide-spread VSC13
- Role-based codelines11
- Disposable Experimentation11
- Frictionless Context Switching7
- Data Assurance6
- Efficient5
- Just awesome4
- Github integration3
- Easy branching and merging3
- Compatible2
- Flexible2
- Possible to lose history and commits2
- Rebase supported natively; reflog; access to plumbing1
- Light1
- Team Integration1
- Fast, scalable, distributed revision control system1
- Easy1
- Flexible, easy, Safe, and fast1
- CLI is great, but the GUI tools are awesome1
- It's what you do1
- Phinx0
- Hard to learn16
- Inconsistent command line interface11
- Easy to lose uncommitted work9
- Worst documentation ever possibly made7
- Awful merge handling5
- Unexistent preventive security flows3
- Rebase hell3
- When --force is disabled, cannot rebase2
- Ironically even die-hard supporters screw up badly2
- Doesn't scale for big data1
related Git posts
Our whole DevOps stack consists of the following tools:
- GitHub (incl. GitHub Pages/Markdown for Documentation, GettingStarted and HowTo's) for collaborative review and code management tool
- Respectively Git as revision control system
- SourceTree as Git GUI
- Visual Studio Code as IDE
- CircleCI for continuous integration (automatize development process)
- Prettier / TSLint / ESLint as code linter
- SonarQube as quality gate
- Docker as container management (incl. Docker Compose for multi-container application management)
- VirtualBox for operating system simulation tests
- Kubernetes as cluster management for docker containers
- Heroku for deploying in test environments
- nginx as web server (preferably used as facade server in production environment)
- SSLMate (using OpenSSL) for certificate management
- Amazon EC2 (incl. Amazon S3) for deploying in stage (production-like) and production environments
- PostgreSQL as preferred database system
- Redis as preferred in-memory database/store (great for caching)
The main reason we have chosen Kubernetes over Docker Swarm is related to the following artifacts:
- Key features: Easy and flexible installation, Clear dashboard, Great scaling operations, Monitoring is an integral part, Great load balancing concepts, Monitors the condition and ensures compensation in the event of failure.
- Applications: An application can be deployed using a combination of pods, deployments, and services (or micro-services).
- Functionality: Kubernetes as a complex installation and setup process, but it not as limited as Docker Swarm.
- Monitoring: It supports multiple versions of logging and monitoring when the services are deployed within the cluster (Elasticsearch/Kibana (ELK), Heapster/Grafana, Sysdig cloud integration).
- Scalability: All-in-one framework for distributed systems.
- Other Benefits: Kubernetes is backed by the Cloud Native Computing Foundation (CNCF), huge community among container orchestration tools, it is an open source and modular tool that works with any OS.
Often enough I have to explain my way of going about setting up a CI/CD pipeline with multiple deployment platforms. Since I am a bit tired of yapping the same every single time, I've decided to write it up and share with the world this way, and send people to read it instead ;). I will explain it on "live-example" of how the Rome got built, basing that current methodology exists only of readme.md and wishes of good luck (as it usually is ;)).
It always starts with an app, whatever it may be and reading the readmes available while Vagrant and VirtualBox is installing and updating. Following that is the first hurdle to go over - convert all the instruction/scripts into Ansible playbook(s), and only stopping when doing a clear vagrant up
or vagrant reload
we will have a fully working environment. As our Vagrant environment is now functional, it's time to break it! This is the moment to look for how things can be done better (too rigid/too lose versioning? Sloppy environment setup?) and replace them with the right way to do stuff, one that won't bite us in the backside. This is the point, and the best opportunity, to upcycle the existing way of doing dev environment to produce a proper, production-grade product.
I should probably digress here for a moment and explain why. I firmly believe that the way you deploy production is the same way you should deploy develop, shy of few debugging-friendly setting. This way you avoid the discrepancy between how production work vs how development works, which almost always causes major pains in the back of the neck, and with use of proper tools should mean no more work for the developers. That's why we start with Vagrant as developer boxes should be as easy as vagrant up
, but the meat of our product lies in Ansible which will do meat of the work and can be applied to almost anything: AWS, bare metal, docker, LXC, in open net, behind vpn - you name it.
We must also give proper consideration to monitoring and logging hoovering at this point. My generic answer here is to grab Elasticsearch, Kibana, and Logstash. While for different use cases there may be better solutions, this one is well battle-tested, performs reasonably and is very easy to scale both vertically (within some limits) and horizontally. Logstash rules are easy to write and are well supported in maintenance through Ansible, which as I've mentioned earlier, are at the very core of things, and creating triggers/reports and alerts based on Elastic and Kibana is generally a breeze, including some quite complex aggregations.
If we are happy with the state of the Ansible it's time to move on and put all those roles and playbooks to work. Namely, we need something to manage our CI/CD pipelines. For me, the choice is obvious: TeamCity. It's modern, robust and unlike most of the light-weight alternatives, it's transparent. What I mean by that is that it doesn't tell you how to do things, doesn't limit your ways to deploy, or test, or package for that matter. Instead, it provides a developer-friendly and rich playground for your pipelines. You can do most the same with Jenkins, but it has a quite dated look and feel to it, while also missing some key functionality that must be brought in via plugins (like quality REST API which comes built-in with TeamCity). It also comes with all the common-handy plugins like Slack or Apache Maven integration.
The exact flow between CI and CD varies too greatly from one application to another to describe, so I will outline a few rules that guide me in it: 1. Make build steps as small as possible. This way when something breaks, we know exactly where, without needing to dig and root around. 2. All security credentials besides development environment must be sources from individual Vault instances. Keys to those containers should exist only on the CI/CD box and accessible by a few people (the less the better). This is pretty self-explanatory, as anything besides dev may contain sensitive data and, at times, be public-facing. Because of that appropriate security must be present. TeamCity shines in this department with excellent secrets-management. 3. Every part of the build chain shall consume and produce artifacts. If it creates nothing, it likely shouldn't be its own build. This way if any issue shows up with any environment or version, all developer has to do it is grab appropriate artifacts to reproduce the issue locally. 4. Deployment builds should be directly tied to specific Git branches/tags. This enables much easier tracking of what caused an issue, including automated identifying and tagging the author (nothing like automated regression testing!).
Speaking of deployments, I generally try to keep it simple but also with a close eye on the wallet. Because of that, I am more than happy with AWS or another cloud provider, but also constantly peeking at the loads and do we get the value of what we are paying for. Often enough the pattern of use is not constantly erratic, but rather has a firm baseline which could be migrated away from the cloud and into bare metal boxes. That is another part where this approach strongly triumphs over the common Docker and CircleCI setup, where you are very much tied in to use cloud providers and getting out is expensive. Here to embrace bare-metal hosting all you need is a help of some container-based self-hosting software, my personal preference is with Proxmox and LXC. Following that all you must write are ansible scripts to manage hardware of Proxmox, similar way as you do for Amazon EC2 (ansible supports both greatly) and you are good to go. One does not exclude another, quite the opposite, as they can live in great synergy and cut your costs dramatically (the heavier your base load, the bigger the savings) while providing production-grade resiliency.
GitHub
- Open source friendly1.8K
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- Nice UI1.3K
- Great for team collaboration1.1K
- Easy setup867
- Issue tracker504
- Great community486
- Remote team collaboration482
- Great way to share451
- Pull request and features planning442
- Just works147
- Integrated in many tools132
- Free Public Repos121
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- Easy to find repos83
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- Easy to find projects60
- Network effect56
- Extensive API49
- Organizations43
- Branching42
- Developer Profiles34
- Git Powered Wikis32
- Great for collaboration30
- It's fun24
- Clean interface and good integrations23
- Community SDK involvement22
- Learn from others source code20
- Because: Git16
- It integrates directly with Azure14
- Newsfeed10
- Standard in Open Source collab10
- Fast8
- It integrates directly with Hipchat8
- Beautiful user experience8
- Easy to discover new code libraries7
- Smooth integration6
- Cloud SCM6
- Nice API6
- Graphs6
- Integrations6
- It's awesome6
- Quick Onboarding5
- Remarkable uptime5
- CI Integration5
- Hands down best online Git service available5
- Reliable5
- Free HTML hosting4
- Version Control4
- Simple but powerful4
- Unlimited Public Repos at no cost4
- Security options4
- Loved by developers4
- Uses GIT4
- Easy to use and collaborate with others4
- IAM3
- Nice to use3
- Ci3
- Easy deployment via SSH3
- Good tools support2
- Leads the copycats2
- Free private repos2
- Free HTML hostings2
- Easy and efficient maintainance of the projects2
- Beautiful2
- Never dethroned2
- IAM integration2
- Very Easy to Use2
- Easy to use2
- All in one development service2
- Self Hosted2
- Issues tracker2
- Easy source control and everything is backed up2
- Profound1
- Owned by micrcosoft53
- Expensive for lone developers that want private repos37
- Relatively slow product/feature release cadence15
- API scoping could be better10
- Only 3 collaborators for private repos8
- Limited featureset for issue management3
- GitHub Packages does not support SNAPSHOT versions2
- Does not have a graph for showing history like git lens2
- No multilingual interface1
- Takes a long time to commit1
- Expensive1
related GitHub posts
I was building a personal project that I needed to store items in a real time database. I am more comfortable with my Frontend skills than my backend so I didn't want to spend time building out anything in Ruby or Go.
I stumbled on Firebase by #Google, and it was really all I needed. It had realtime data, an area for storing file uploads and best of all for the amount of data I needed it was free!
I built out my application using tools I was familiar with, React for the framework, Redux.js to manage my state across components, and styled-components for the styling.
Now as this was a project I was just working on in my free time for fun I didn't really want to pay for hosting. I did some research and I found Netlify. I had actually seen them at #ReactRally the year before and deployed a Gatsby site to Netlify already.
Netlify was very easy to setup and link to my GitHub account you select a repo and pretty much with very little configuration you have a live site that will deploy every time you push to master.
With the selection of these tools I was able to build out my application, connect it to a realtime database, and deploy to a live environment all with $0 spent.
If you're looking to build out a small app I suggest giving these tools a go as you can get your idea out into the real world for absolutely no cost.
StackShare Feed is built entirely with React, Glamorous, and Apollo. One of our objectives with the public launch of the Feed was to enable a Server-side rendered (SSR) experience for our organic search traffic. When you visit the StackShare Feed, and you aren't logged in, you are delivered the Trending feed experience. We use an in-house Node.js rendering microservice to generate this HTML. This microservice needs to run and serve requests independent of our Rails web app. Up until recently, we had a mono-repo with our Rails and React code living happily together and all served from the same web process. In order to deploy our SSR app into a Heroku environment, we needed to split out our front-end application into a separate repo in GitHub. The driving factor in this decision was mostly due to limitations imposed by Heroku specifically with how processes can't communicate with each other. A new SSR app was created in Heroku and linked directly to the frontend repo so it stays in-sync with changes.
Related to this, we need a way to "deploy" our frontend changes to various server environments without building & releasing the entire Ruby application. We built a hybrid Amazon S3 Amazon CloudFront solution to host our Webpack bundles. A new CircleCI script builds the bundles and uploads them to S3. The final step in our rollout is to update some keys in Redis so our Rails app knows which bundles to serve. The result of these efforts were significant. Our frontend team now moves independently of our backend team, our build & release process takes only a few minutes, we are now using an edge CDN to serve JS assets, and we have pre-rendered React pages!
#StackDecisionsLaunch #SSR #Microservices #FrontEndRepoSplit
Python
- Great libraries1.2K
- Readable code960
- Beautiful code845
- Rapid development786
- Large community689
- Open source435
- Elegant392
- Great community281
- Object oriented272
- Dynamic typing219
- Great standard library77
- Very fast59
- Functional programming55
- Easy to learn48
- Scientific computing45
- Great documentation35
- Productivity29
- Easy to read28
- Matlab alternative28
- Simple is better than complex23
- It's the way I think20
- Imperative19
- Free18
- Very programmer and non-programmer friendly18
- Powerfull language17
- Machine learning support17
- Fast and simple16
- Scripting14
- Explicit is better than implicit12
- Ease of development11
- Clear and easy and powerfull10
- Unlimited power9
- It's lean and fun to code8
- Import antigravity8
- Print "life is short, use python"7
- Python has great libraries for data processing7
- Although practicality beats purity6
- Flat is better than nested6
- Great for tooling6
- Rapid Prototyping6
- Readability counts6
- High Documented language6
- I love snakes6
- Fast coding and good for competitions6
- There should be one-- and preferably only one --obvious6
- Now is better than never6
- Great for analytics5
- Lists, tuples, dictionaries5
- Easy to learn and use4
- Simple and easy to learn4
- Easy to setup and run smooth4
- Web scraping4
- CG industry needs4
- Socially engaged community4
- Complex is better than complicated4
- Multiple Inheritence4
- Beautiful is better than ugly4
- Plotting4
- If the implementation is hard to explain, it's a bad id3
- Special cases aren't special enough to break the rules3
- Pip install everything3
- List comprehensions3
- No cruft3
- Generators3
- Import this3
- It is Very easy , simple and will you be love programmi3
- Many types of collections3
- If the implementation is easy to explain, it may be a g3
- Batteries included2
- Should START with this but not STICK with This2
- Powerful language for AI2
- Can understand easily who are new to programming2
- Flexible and easy2
- Good for hacking2
- A-to-Z2
- Because of Netflix2
- Only one way to do it2
- Better outcome2
- Sexy af1
- Slow1
- Securit1
- Ni0
- Powerful0
- Still divided between python 2 and python 353
- Performance impact28
- Poor syntax for anonymous functions26
- GIL22
- Package management is a mess19
- Too imperative-oriented14
- Hard to understand12
- Dynamic typing12
- Very slow12
- Indentations matter a lot8
- Not everything is expression8
- Incredibly slow7
- Explicit self parameter in methods7
- Requires C functions for dynamic modules6
- Poor DSL capabilities6
- No anonymous functions6
- Fake object-oriented programming5
- Threading5
- The "lisp style" whitespaces5
- Official documentation is unclear.5
- Hard to obfuscate5
- Circular import5
- Lack of Syntax Sugar leads to "the pyramid of doom"4
- The benevolent-dictator-for-life quit4
- Not suitable for autocomplete4
- Meta classes2
- Training wheels (forced indentation)1
related Python posts
How Uber developed the open source, end-to-end distributed tracing Jaeger , now a CNCF project:
Distributed tracing is quickly becoming a must-have component in the tools that organizations use to monitor their complex, microservice-based architectures. At Uber, our open source distributed tracing system Jaeger saw large-scale internal adoption throughout 2016, integrated into hundreds of microservices and now recording thousands of traces every second.
Here is the story of how we got here, from investigating off-the-shelf solutions like Zipkin, to why we switched from pull to push architecture, and how distributed tracing will continue to evolve:
https://eng.uber.com/distributed-tracing/
(GitHub Pages : https://www.jaegertracing.io/, GitHub: https://github.com/jaegertracing/jaeger)
Bindings/Operator: Python Java Node.js Go C++ Kubernetes JavaScript OpenShift C# Apache Spark
Winds 2.0 is an open source Podcast/RSS reader developed by Stream with a core goal to enable a wide range of developers to contribute.
We chose JavaScript because nearly every developer knows or can, at the very least, read JavaScript. With ES6 and Node.js v10.x.x, it’s become a very capable language. Async/Await is powerful and easy to use (Async/Await vs Promises). Babel allows us to experiment with next-generation JavaScript (features that are not in the official JavaScript spec yet). Yarn allows us to consistently install packages quickly (and is filled with tons of new tricks)
We’re using JavaScript for everything – both front and backend. Most of our team is experienced with Go and Python, so Node was not an obvious choice for this app.
Sure... there will be haters who refuse to acknowledge that there is anything remotely positive about JavaScript (there are even rants on Hacker News about Node.js); however, without writing completely in JavaScript, we would not have seen the results we did.
#FrameworksFullStack #Languages