What is AutoIt and what are its top alternatives?
AutoIt is a scripting language designed for automating the windows GUI and general scripting. It is commonly used for automating tasks, creating macros, and creating GUI applications. Key features include a simple syntax, built-in functions for automation, and a vibrant community support. However, some limitations include a lack of cross-platform support, limited advanced functionality compared to other scripting languages, and a learning curve for beginners.
- AutoHotkey: AutoHotkey is a powerful and easy-to-learn scripting language for Windows. It offers similar automation capabilities as AutoIt, with features like hotkeys, remapping keys, and creating custom GUIs. Pros include extensive documentation and an active community, while cons include a steeper learning curve compared to AutoIt.
- SikuliX: SikuliX is a scripting/automation technology that relies on pattern matching, allowing users to automate GUI interaction by taking screenshots. Key features include cross-platform support and easy integration with Java, but a potential downside is the need for image recognition capabilities.
- AutoKey: AutoKey is a lightweight automation tool for Linux, with features such as text expansion, window management, and desktop automation. Pros include support for advanced scripting with Python, while cons may include a limited user base compared to other tools.
- Robot Framework: Robot Framework is a generic test automation framework for acceptance testing and robotic process automation. It offers keyword-driven testing approach and supports various libraries for different automation needs. Pros include extensibility with custom libraries, while cons include a learning curve for beginners.
- Pulover's Macro Creator: Pulover's Macro Creator is a free automation tool for Windows that allows users to create macros and automate repetitive tasks. Key features include a simple interface and easy macro recording, but the tool may lack advanced functionality compared to AutoIt.
- Keyboard Maestro: Keyboard Maestro is a powerful automation tool for Mac OS X that allows users to create macros, trigger actions, and automate tasks with ease. Pros include a user-friendly interface and extensive feature set, while cons may include limited cross-platform support.
- WinAutomation: WinAutomation is a Windows automation software that provides a visual designer for creating automation workflows. Key features include web automation, task scheduling, and integration with various technologies, but the software may come at a cost compared to free alternatives like AutoIt.
- Ifttt: Ifttt (If This Then That) is a free web-based automation service that allows users to create chains of simple conditional statements called applets. Pros include ease of use and wide integration with various services, but cons may include limited customization compared to scripting languages like AutoIt.
- AppleScript: AppleScript is a scripting language for Mac OS that allows users to automate tasks and control applications on their Mac. Pros include integration with Mac OS services and applications, while cons may include limited automation capabilities compared to AutoIt.
- Tasker: Tasker is an Android automation app that allows users to automate their device by creating rules and triggers based on various conditions. Key features include extensive customization options and integration with Android system functions, but some users may find the interface complex compared to simpler scripting tools like AutoIt.
Top Alternatives to AutoIt
- PowerShell
A command-line shell and scripting language built on .NET. Helps system administrators and power-users rapidly automate tasks that manage operating systems (Linux, macOS, and Windows) and processes. ...
- Selenium
Selenium automates browsers. That's it! What you do with that power is entirely up to you. Primarily, it is for automating web applications for testing purposes, but is certainly not limited to just that. Boring web-based administration tasks can (and should!) also be automated as well. ...
- 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. ...
- 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. ...
- Node.js
Node.js uses an event-driven, non-blocking I/O model that makes it lightweight and efficient, perfect for data-intensive real-time applications that run across distributed devices. ...
- HTML5
HTML5 is a core technology markup language of the Internet used for structuring and presenting content for the World Wide Web. As of October 2014 this is the final and complete fifth revision of the HTML standard of the World Wide Web Consortium (W3C). The previous version, HTML 4, was standardised in 1997. ...
- PHP
Fast, flexible and pragmatic, PHP powers everything from your blog to the most popular websites in the world. ...
- Java
Java is a programming language and computing platform first released by Sun Microsystems in 1995. There are lots of applications and websites that will not work unless you have Java installed, and more are created every day. Java is fast, secure, and reliable. From laptops to datacenters, game consoles to scientific supercomputers, cell phones to the Internet, Java is everywhere! ...
AutoIt alternatives & related posts
related PowerShell posts
I currently work helpdesk and have been for about 6 years. I am looking to become more valuable, and I can't decide what route to take? Python is of interest, and so is PowerShell. What are some recommendations? Maybe something that would benefit a helpdesk position or even get into a network administrator.
Objective: I am trying to build a custom service that will create VMs in Azure, based on inputs taken from a web interface. I want the backend code that interacts with Azure to be PowerShell.
Ask: Hoping to find help with deciding the simplest architecture of tools to achieve this.
What I have so far with my Limited Knowledge: I am new to Azure and Jenkins. I arrived at Jenkins coz it can run PowerShell and has API that can be called to trigger a job. Although integrating with it over the web seems problematic since its on-prem network. I hear it is possible using the VPN. For the Web, I hope to use Azure Web App with Python/Node.js that I can manage to make API calls to Jenkins.
Is there a better way? I just need help getting the right directions; I will walk the way.
- Automates browsers177
- Testing154
- Essential tool for running test automation101
- Record-Playback24
- Remote Control24
- Data crawling8
- Supports end to end testing7
- Easy set up6
- Functional testing6
- The Most flexible monitoring system4
- End to End Testing3
- Easy to integrate with build tools3
- Comparing the performance selenium is faster than jasm2
- Record and playback2
- Compatible with Python2
- Easy to scale2
- Integration Tests2
- Integrated into Selenium-Jupiter framework0
- Flaky tests8
- Slow as needs to make browser (even with no gui)4
- Update browser drivers2
related Selenium posts
When you think about test automation, it’s crucial to make it everyone’s responsibility (not just QA Engineers'). We started with Selenium and Java, but with our platform revolving around Ruby, Elixir and JavaScript, QA Engineers were left alone to automate tests. Cypress was the answer, as we could switch to JS and simply involve more people from day one. There's a downside too, as it meant testing on Chrome only, but that was "good enough" for us + if really needed we can always cover some specific cases in a different way.





In 2012 we made the very difficult decision to entirely re-engineer our existing monolithic LAMP application from the ground up in order to address some growing concerns about it's long term viability as a platform.
Full application re-write is almost always never the answer, because of the risks involved. However the situation warranted drastic action as it was clear that the existing product was going to face severe scaling issues. We felt it better address these sooner rather than later and also take the opportunity to improve the international architecture and also to refactor the database in. order that it better matched the changes in core functionality.
PostgreSQL was chosen for its reputation as being solid ACID compliant database backend, it was available as an offering AWS RDS service which reduced the management overhead of us having to configure it ourselves. In order to reduce read load on the primary database we implemented an Elasticsearch layer for fast and scalable search operations. Synchronisation of these indexes was to be achieved through the use of Sidekiq's Redis based background workers on Amazon ElastiCache. Again the AWS solution here looked to be an easy way to keep our involvement in managing this part of the platform at a minimum. Allowing us to focus on our core business.
Rails ls was chosen for its ability to quickly get core functionality up and running, its MVC architecture and also its focus on Test Driven Development using RSpec and Selenium with Travis CI providing continual integration. We also liked Ruby for its terse, clean and elegant syntax. Though YMMV on that one!
Unicorn was chosen for its continual deployment and reputation as a reliable application server, nginx for its reputation as a fast and stable reverse-proxy. We also took advantage of the Amazon CloudFront CDN here to further improve performance by caching static assets globally.
We tried to strike a balance between having control over management and configuration of our core application with the convenience of being able to leverage AWS hosted services for ancillary functions (Amazon SES , Amazon SQS Amazon Route 53 all hosted securely inside Amazon VPC of course!).
Whilst there is some compromise here with potential vendor lock in, the tasks being performed by these ancillary services are no particularly specialised which should mitigate this risk. Furthermore we have already containerised the stack in our development using Docker environment, and looking to how best to bring this into production - potentially using Amazon EC2 Container Service
Python
- Great libraries1.2K
- Readable code965
- Beautiful code848
- Rapid development789
- Large community692
- Open source439
- Elegant394
- Great community283
- Object oriented274
- Dynamic typing222
- Great standard library78
- Very fast62
- Functional programming56
- Easy to learn52
- Scientific computing47
- Great documentation36
- Productivity30
- Matlab alternative29
- Easy to read29
- Simple is better than complex25
- It's the way I think21
- Imperative20
- Very programmer and non-programmer friendly19
- Free19
- 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
- Fast coding and good for competitions6
- There should be one-- and preferably only one --obvious6
- High Documented language6
- Readability counts6
- Rapid Prototyping6
- I love snakes6
- Now is better than never6
- Flat is better than nested6
- Great for tooling6
- Great for analytics5
- Web scraping5
- Lists, tuples, dictionaries5
- Complex is better than complicated4
- Socially engaged community4
- Plotting4
- Beautiful is better than ugly4
- Easy to learn and use4
- Easy to setup and run smooth4
- Simple and easy to learn4
- Multiple Inheritence4
- CG industry needs4
- List comprehensions3
- Powerful language for AI3
- Flexible and easy3
- 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
- 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
- No cruft3
- Generators3
- Import this3
- Can understand easily who are new to programming2
- Securit2
- Should START with this but not STICK with This2
- A-to-Z2
- Because of Netflix2
- Only one way to do it2
- Better outcome2
- Good for hacking2
- Batteries included2
- Procedural programming2
- Sexy af1
- Automation friendly1
- Slow1
- Best friend for NLP1
- Powerful0
- Keep it simple0
- Ni0
- 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
Hi, I have an LMS application, currently developed in Python-Django.
It works all very well, students can view their classes and submit exams, but I have noticed that some students are sharing exam answers with other students and let's say they already have a model of the exams.
I want with the help of artificial intelligence, the exams to have different questions and in a different order for each student, what technology should I learn to develop something like this? I am a Python-Django developer but my focus is on web development, I have never touched anything from A.I.
What do you think about TensorFlow?
Please, I would appreciate all your ideas and opinions, thank you very much in advance.
JavaScript
- Can be used on frontend/backend1.7K
- It's everywhere1.5K
- Lots of great frameworks1.2K
- Fast899
- Light weight746
- Flexible425
- You can't get a device today that doesn't run js392
- Non-blocking i/o286
- Ubiquitousness237
- 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
- Its everywhere12
- Future Language of The Web12
- Setup is easy12
- JavaScript is the New PHP11
- Because I love functions11
- Like it or not, JS is part of the web standard10
- Everyone use it9
- Can be used in backend, frontend and DB9
- Easy9
- Expansive community9
- For the good parts8
- Easy to hire developers8
- No need to use PHP8
- Most Popular Language in the World8
- Powerful8
- Can be used both as frontend and backend as well8
- It's fun7
- Its fun and fast7
- Popularized Class-Less Architecture & Lambdas7
- Agile, packages simple to use7
- Supports lambdas and closures7
- Love-hate relationship7
- Photoshop has 3 JS runtimes built in7
- Evolution of C7
- Hard not to use7
- Versitile7
- Nice7
- Easy to make something6
- Can be used on frontend/backend/Mobile/create PRO Ui6
- 1.6K Can be used on frontend/backend6
- Client side JS uses the visitors CPU to save Server Res6
- It let's me use Babel & Typescript6
- Clojurescript5
- Everywhere5
- Scope manipulation5
- Function expressions are useful for callbacks5
- Stockholm Syndrome5
- Promise relationship5
- Client processing5
- What to add5
- Because it is so simple and lightweight4
- Only Programming language on browser4
- Subskill #41
- Test21
- Easy to understand1
- Not the best1
- Easy to learn1
- Hard to learn1
- Easy to learn and test1
- Love it1
- Test1
- 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
- HORRIBLE DOCUMENTS, faulty code, repo has bugs0
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
Node.js
- Npm1.4K
- Javascript1.3K
- Great libraries1.1K
- High-performance1K
- Open source805
- Great for apis487
- Asynchronous477
- Great community425
- Great for realtime apps390
- Great for command line utilities296
- Websockets86
- Node Modules84
- Uber Simple69
- Great modularity59
- Allows us to reuse code in the frontend58
- Easy to start42
- Great for Data Streaming35
- Realtime32
- Awesome28
- Non blocking IO25
- Can be used as a proxy18
- High performance, open source, scalable17
- Non-blocking and modular16
- Easy and Fun15
- Easy and powerful14
- Future of BackEnd13
- Same lang as AngularJS13
- Fullstack12
- Fast11
- Scalability10
- Cross platform10
- Simple9
- Mean Stack8
- Great for webapps7
- Easy concurrency7
- Typescript6
- Fast, simple code and async6
- React6
- Friendly6
- Control everything5
- Its amazingly fast and scalable5
- Easy to use and fast and goes well with JSONdb's5
- Scalable5
- Great speed5
- Fast development5
- It's fast4
- Easy to use4
- Isomorphic coolness4
- Great community3
- Not Python3
- Sooper easy for the Backend connectivity3
- TypeScript Support3
- Blazing fast3
- Performant and fast prototyping3
- Easy to learn3
- Easy3
- Scales, fast, simple, great community, npm, express3
- One language, end-to-end3
- Less boilerplate code3
- Npm i ape-updating2
- Event Driven2
- Lovely2
- Creat for apis1
- Node0
- Bound to a single CPU46
- New framework every day45
- Lots of terrible examples on the internet40
- Asynchronous programming is the worst33
- Callback24
- Javascript19
- Dependency hell11
- Dependency based on GitHub11
- Low computational power10
- Very very Slow7
- Can block whole server easily7
- Callback functions may not fire on expected sequence7
- Breaking updates4
- Unstable4
- Unneeded over complication3
- No standard approach3
- Bad transitive dependency management1
- Can't read server session1
related Node.js posts
Needs advice on code coverage tool in Node.js/ExpressJS with External API Testing Framework
Hello community,
I have a web application with the backend developed using Node.js and Express.js. The backend server is in one directory, and I have a separate API testing framework, made using SuperTest, Mocha, and Chai, in another directory. The testing framework pings the API, retrieves responses, and performs validations.
I'm currently looking for a code coverage tool that can accurately measure the code coverage of my backend code when triggered by the API testing framework. I've tried using Istanbul and NYC with instrumented code, but the results are not as expected.
Could you please recommend a reliable code coverage tool or suggest an approach to effectively measure the code coverage of my Node.js/Express.js backend code in this setup?
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
- New doctype448
- Local storage389
- Canvas334
- Semantic header and footer285
- Video element240
- Geolocation121
- Form autofocus106
- Email inputs100
- Editable content85
- Application caches79
- Easy to use10
- Cleaner Code9
- Easy5
- Websockets4
- Semantical4
- Audio element3
- Content focused3
- Better3
- Modern3
- Compatible2
- Very easy to learning to HTML2
- Semantic Header and Footer, Geolocation, New Doctype2
- Portability2
- Easy to forget the tags when you're a begginner2
- Long and winding code1
related HTML5 posts
Hey guys, I need some advice on one thing. Currently, I am a fresher and know HTML5, CSS, JavaScript, PHP and, MySQL. Recently I got a client project through one of my friends and he wants me to build an E-learning Management System. Are these skills enough to build an LMS website?
Thanks in advance!! ;)
Few years ago we were building a Next.js site with a few simple forms. This required handling forms validation and submission, but instead of picking some forms library, we went with plain JavaScript and constraint validation API in HTML5. This shaved off a few KBs of dependencies and gave us full control over the validation behavior and look. I describe this approach, with its pros and cons, in a blog post.
PHP
- Large community954
- Open source820
- Easy deployment767
- Great frameworks487
- The best glue on the web387
- Continual improvements235
- Good old web185
- Web foundation145
- Community packages135
- Tool support125
- Used by wordpress35
- Excellent documentation34
- Used by Facebook29
- Because of Symfony23
- Dynamic Language21
- Easy to learn17
- Cheap hosting17
- Very powerful web language15
- Awesome Language and easy to implement14
- Fast development14
- Because of Laravel14
- Composer13
- Flexibility, syntax, extensibility12
- Easiest deployment9
- Readable Code8
- Fast8
- Most of the web uses it7
- Short development lead times7
- Worst popularity quality ratio7
- Fastestest Time to Version 1.0 Deployments7
- Faster then ever6
- Simple, flexible yet Scalable6
- Open source and large community5
- Easy to use and learn4
- Great developer experience4
- Has the best ecommerce(Magento,Prestashop,Opencart,etc)4
- Is like one zip of air4
- Open source and great framework4
- Large community, easy setup, easy deployment, framework4
- Cheap to own4
- Easy to learn, a big community, lot of frameworks4
- I have no choice :(4
- Hard not to use2
- Great flexibility. From fast prototyping to large apps2
- Interpreted at the run time2
- Walk away2
- FFI2
- Safe the planet2
- Used by STOMT2
- Fault tolerance2
- Simplesaml1
- Secure1
- It can get you a lamborghini1
- Bando1
- Secure0
- Largr community0
- So easy to learn, good practices are hard to find21
- Inconsistent API16
- Fragmented community8
- Not secure6
- No routing system3
- Hard to debug3
- Old2
related PHP posts
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.
Hello, I am building a website for a school that's used by students to find Zoom meeting links, view their marks, and check course materials. It is also used by the teachers to put the meeting links, students' marks, and course materials.
I created a similar website using HTML, CSS, PHP, and MySQL. Now I want to implement this project using some frameworks: Next.js, ExpressJS and use PostgreSQL instead of MYSQL
I want to have some advice on whether these are enough to implement my project.
Java
- Great libraries607
- Widely used446
- Excellent tooling401
- Huge amount of documentation available396
- Large pool of developers available334
- Open source209
- Excellent performance203
- Great development158
- Used for android150
- Vast array of 3rd party libraries148
- Compiled Language61
- Used for Web53
- High Performance47
- Managed memory46
- Native threads45
- Statically typed43
- Easy to read35
- Great Community33
- Reliable platform29
- JVM compatibility24
- Sturdy garbage collection24
- Cross Platform Enterprise Integration22
- Good amount of APIs20
- Universal platform20
- Great Support18
- Great ecosystem14
- Lots of boilerplate11
- Backward compatible11
- Everywhere10
- Excellent SDK - JDK9
- It's Java8
- Static typing7
- Cross-platform7
- Mature language thus stable systems6
- Better than Ruby6
- Long term language6
- Portability6
- Vast Collections Library5
- Clojure5
- Used for Android development5
- Most developers favorite4
- Old tech4
- Best martial for design4
- Javadoc3
- History3
- Testable3
- Great Structure3
- Stable platform, which many new languages depend on3
- Type Safe2
- Faster than python2
- Makes code organized1
- Job0
- Verbosity33
- NullpointerException27
- Nightmare to Write17
- Overcomplexity is praised in community culture16
- Boiler plate code12
- Classpath hell prior to Java 98
- No REPL6
- No property4
- Code are too long3
- Non-intuitive generic implementation2
- There is not optional parameter2
- Floating-point errors2
- Java's too statically, stronglly, and strictly typed1
- Returning Wildcard Types1
- Terrbible compared to Python/Batch Perormence1
related Java 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
When you think about test automation, it’s crucial to make it everyone’s responsibility (not just QA Engineers'). We started with Selenium and Java, but with our platform revolving around Ruby, Elixir and JavaScript, QA Engineers were left alone to automate tests. Cypress was the answer, as we could switch to JS and simply involve more people from day one. There's a downside too, as it meant testing on Chrome only, but that was "good enough" for us + if really needed we can always cover some specific cases in a different way.