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Go vs Python vs Rust: What are the differences?
Key Differences between Go, Python, and Rust
Go, Python, and Rust are all popular programming languages with their own unique features and use cases. Here are the key differences between these three languages:
Performance and Execution Speed: Go is known for its high performance and fast execution speed, making it suitable for building robust and efficient applications. Python, on the other hand, is an interpreted language, which tends to be slower compared to compiled languages like Go. Rust, being a systems programming language, prioritizes performance and memory safety through its strict borrowing and ownership system.
Concurrency and Parallelism: Go has built-in support for concurrency with goroutines and channels, making it easy to write concurrent programs. Python also offers concurrency with libraries like asyncio, but it is not as explicit or idiomatic as in Go. Rust, being a low-level language, provides fine-grained control over concurrency and parallelism but requires careful management of memory and thread synchronization.
Ease of Use and Developer Productivity: Python has a clean and readable syntax, making it easy to understand and write code quickly. It has a rich set of libraries and frameworks, making it a popular choice for web development, data analysis, and scripting. Go focuses on simplicity and readability, with a strict and straightforward syntax, but it lacks some of the advanced features and libraries found in Python. Rust, although powerful, has a steeper learning curve due to its complex ownership system and emphasis on memory safety.
Scalability and Concurrency Handling: Go is designed for building scalable systems, with built-in support for concurrent programming patterns and lightweight goroutines. Python, while capable of scaling, may struggle with highly concurrent or CPU-intensive tasks due to the Global Interpreter Lock (GIL), which limits true parallelism. Rust, with its focus on low-level systems programming, allows for fine-grained control over memory and concurrency but requires manual memory management and careful consideration of thread safety.
Community and Ecosystem: Python has a large and active community, with a vast selection of libraries and frameworks for various domains and use cases. It is well-established and has extensive documentation and resources. Go has a growing community and a standard library that covers many common tasks, but its ecosystem may not be as extensive and mature as Python's. Rust, while gaining popularity, has a smaller but passionate community and a growing ecosystem of libraries and frameworks.
Use Cases and Domains: Go is often used for building scalable web services, networking tools, and distributed systems due to its performance and built-in concurrency support. Python is widely used in web development, data analysis, scientific computing, machine learning, and automation. Rust is commonly used for systems programming, embedded systems, game development, and other scenarios where low-level control and performance are critical.
In summary, Go excels in terms of performance, concurrency, and scalability, Python emphasizes simplicity, ease of use, and a vast ecosystem, while Rust offers fine-grained control over memory and performance but with a steeper learning curve. The choice of language depends on the specific requirements, priorities, and trade-offs of the project at hand.
Generally speaking, what are the most important things you expect a junior developer to know and be able to do from day 1 in your respective tech stack? Firm grasp of OOP? SQL? MVC? ORM? Algorithms and Datastructures? Understanding CRUD & the request response cycle? Database design? framework familiarity? Postman? Deployment? TDD? Git? Language-specific knowledge? Other things?
Start with building a solid understanding of computer science fundamentals. Understand the basics of building blocks - memory, processing, storage, networking. Understand what CPU bound, memory bound, I/O bound, network bound processes are. Understand the cost of accessing data from Memory vs. Disk vs Network. Understand how multiple CPU threads help in optimizing the performance of a single machine.
Build expertise on a programming language. You may pick any language of your choice. I would recommend starting with Java / Python. Make sure you know one language really well. Build a strong understanding of Data Structures and Algorithms. You should be able to develop an intuition on when to use what. You may practice DS and Algorithm problems, using the language of your choice, on a competitive coding platform (e.g. Leetcode) or by building your own App!
Next, get familiar with basic cloud computing and distributed system concepts. Here is a good resource for that - https://www.youtube.com/watch?v=p7NkTUyEE1o&ab_channel=JeffreyRichter If you understand the computer science fundamentals well, you will be able to apply those concepts here as well.
Hope it helps!
Ability to read code and willingness to try to reason flow of operations and information. Tools and technologies change, one doesn't need to have them in toolbelt from day one. All things you name are relevant in some contexts, so it's not bad to understand them.
Just learn to learn. Learn to search and develop your logical thinking, that's all you need. No books, no deep study of how computers work, just logic and willingness to learn
For me, it is less of a specific technology you know (although I would prefer you have some knowledge of some of my team stack). It is more the way you get into a problem, the eagerness to learn more, the true sincerity to say "I don't know", the open mind to find solutions in different ways and the "Yes we can" mentality no matter how hard it is.
Most employers don't expect from you to know how to implement CI/CD or any other funcy stuff. As junior developer you should focus on building a good toolset of good software practices & principles. Your soft skills are important as well. Learn about soft skills. Be eager to learn, be humble and show you talent and your creativity through your work. If you want to become a good developer ( at first) and a star engineer (at a later stage) then computer programming (coding) is your number one priority . Coding is like painting. Putting aside your talent, you have to practice a lot and improve your outcome each time. As junior developer you can learn how to write good code by studying existing code found in public git repositories (i e , github). As junior developer you should study some good software principles (i.e., DRY, KISS, YAGNI) and always recall them each time you write software code. As junior developer you should learn about coding standards and conventions. You will have to follow to your company's coding conventions (soon or later) as well as you will realize that you have to write code cosistent to the existing code base. At the end of the day, code consistency matters a lot. You have to improve your code day by day. If you manage to follow some good software practices you will find out that you will need an ORM to work with your database. Then you will realize that you need the X web framework to build your REST API etc. To sum up, you will start building a toolset with a single programming language and some good software practices & principles and then you will put new tools in it day-by-day.
Hey there, we are looking to develop our own layer 1 blockchain. We're splitting the responsibilities for origination, clearing, and settlement across three independent but cooperating node networks. We've gotten our Proof of Concept up using Ruby on Rails for the nodes, you can see it as the attached link. So far, so good. Now we are looking to convert it into a distributable and are trying to figure out which language is the best for this.
Essentially our needs from the language are: solid networking tools and speed, very fast execution of basic actions, some parallel execution, and able to compile the end product into an easy to distribute and use package for end users.
I was learning Rust, but I have a healthy amount of experience with Swift and right now, it's only me coding. I've only done iOS coding, but have built a fintech app from scratch that's now in the app store so I'm pretty familiar with the language and its benefits. Haven't experimented with Vapor or any of the application development tools, and I wanted to know if it is a crazy idea to develop a blockchain node in Swift instead.
Pick Rust. Rust can provide all what you need and has been a major language in blockchain/cryptocurrency industry. Swift is slower than Rust and does not have such support in the networking and domain field. Swift tooling is great only on macOS, therefore you are likely to have troubles on other platforms.
You can use swift of course. It’s more of a question of being performant.
You really want to try some basic operations and find what’s most performant for you.
Rust is wonderful for cloud applications requiring heavy concurrency, it has compile time checking for such things.
Go and C++ could be more performant in your case. Swift is really quite an obtuse language, with a lot of features, some which may complicate your implementation.
Also, you want to consider the market of developers who could help build it. If you use Go or C++ there is a larger collection of people who know the languages than there is with swift.
Hi! I'm currently studying Flutter for mobile apps, but I also have a demand to automate some tasks on the web and create backends' for my apps, so thinking about which one of those could be better? Considering the performance and how easy it's to learn and create stuff? (I'm already familiar with .NET stack but want something more "simple" to write)
Definitely Python. Lots of libraries, dead simple syntax. Lots of code examples and reference projects. Elixir is pure functional and takes time to grasp the concepts. Go is great, with simple syntax and performant runtime, but more strict as it is statically typed. For quick coding, nothing beats Python. As you come from .net I’d consider similar approach and be considering Java with SpringBoot as it makes Java faster and much more fun to code web servers
Elixir really has a good performance for the web (and in general). Its framework Phoenix for the web is a great tool, easy to install and to use, with features for websockets (and Pub/Sub) or LiveView to write reactive and real time app with only HTML (and Elixir) so basically everything is in one place
It can take some time to learn a few things in Elixir but I really think it's worth it, and it's very easy to go distributed and concurrent with Elixir. Also it's easier to code quickly with some features like the pattern matching or some operators like the pipe or the capture one
And in the case you need it you can still connect and interface Python and Elixir pretty quickly, and now Elixir has a lot of different frameworks : web, embedded or even neural networks now
Never went far with Go but I have some trouble with its syntax, I find it a bit messy
I don't have a lot of experience with the web with Python but I don't have a good experience with the little I did
Judging your previous experience we will benefit from Golang in terms of portability and speed. If you want to go simplier use Python. If it's only scripts use Python.
Hey Vitor, You can use Node and Express JS to create a backend for your app. You can create REST APIS to connect your front end with the backend. It is a very simple and scalable solution for building backend web apps.
I'm making my university community web service with a team. (6 members myself included)
And we decided to use JavaScript, HTML, CSS (for sure, it's the basic of websites) but couldn't decide for the back end part.
There are tons of languages, tools, etc., but I'm really new to programming, so I'd like to get some help to figure out what tools we need.
So my question is this: are there any good examples of web community services we can mimic the tools or get an insight from them?
Since you're following Python, I would recomend using Django as your main back-end language. If you know Python it would be a great experience. Django is well documented on their official website: https://www.djangoproject.com/ I would also use React for front-end as well. Also this article is worth reading, I think progressive web app is something worth learning these days: https://web.dev/progressive-web-apps/ Hope that helps :)
Since your team is already using JavaScript, there's a great number of examples for backend services written with NodeJS. I'd recommend using Firebase, or any backend as a service (you can use that term to find alternatives), for setting up your backend as it is much easier for newer people to understand and lets you focus on your core application logic, and not provisioning servers, databases, etc.
Since you're team is already using JavaScript, there are alot of examples and open source projects written with NodeJs, so I preffer this language in your backend application and also I am recommended using Mongo DB with It for saving data in it, and also for your frontend application I am recommanded using VueJs.
Since you are already using JavaScript on the front end it would be easy to adopt the MERN (MongoDB, Express, React, NodeJS) stack which s all javascript based making it easy to transfer knowledge with the backend and front end
Kindly I don't find any help that solve this mystery I need more help if it will happen
Make it simple, most of projects doesnt need a AI, ML or big algorithms. If your project just serving end users take it to the web ready compatible. (Javascript, .Net, PHP Laravel)
Hello, I am interested in learning how to program. I am a beginner, and many articles saying I should go with Python if I am new to programming. I considered Lua a long time ago, but for my career, I believe major programming languages should be better for me. I'm considering Python at this moment, but if you have other tools I should use, let me know.
Although Lua is a very simple,efficient, elegant and welcoming language, Python is extremely versatile. Therefore, if you want to get into programming without a defined direction, Python is the way to go. It has a lot of libraries, the ability to do anything and it is closer to other languages than Lua is (yeah I know about Lua and C, but from a learner's point of view, it makes sense). Additionally, Python will be a marketable skill, but I for one have not yet seen job offers for Lua devs.
The language you choose is also dependant on the type of career / area of programming you wish to focus on: Web Based and mobile applicaitons I would lean towards Java, PC Applications I tend to like C#, Embedded industry C, C++
my advice , you should answer me for this question, what do you like to work: web base or mobile native or cross platform. if you like web base you should choose PHP or ASP.net or Node.js or if you like mobile native you should decide Android or IOS platform and else if you like cross platfrom you should learn Flutter with dart language. thanks
Hey, 👋
My name is Brayden. I’m currently a Frontend React Developer, striving to move into Fullstack so I can expand my knowledge.
For my main backend language, I am deciding between Python, Rust, and Go. I’ve tried each of them out for about an hour and currently, I like Python and Rust the most. However, I’m not sure if I’m missing out on something!
If anyone has advice on these technologies, I’d love to hear it!
Thanks.
Rust is still in low demand. It's a great language but you'll have a hard time finding jobs. Go is the mix of both Rust and Python. Great language with modern features, fast, scalable, fun to write, and at the same time it has high demand (not as much as python).
Python on the other hand is a language that you can't go wrong with. Look around you and see what your job market prefers. If there isn't much difference to you personally, pick the one with more demand.
All of these are solid options, however considering your expertise currently, I would probably suggest Node.JS considering your past experience with JS. However Python offers a similar development environment to JS in my opinion, and Go is a good sort of intermediate between Rust and Node.JS and Python. It's fast, but not as fast as Rust, and offers a development experience that combines C-styled languages (like Rust), and Python-y languages... So: Rust for the fastest, Node for familiarity, Python for ease of development, and Go for a good middle ground. I have used all in personal projects... If you use Go, I suggest a easy to use web server framework like Fiber.
Rust is a challenging choice, but worth to be chosen. It has strong memory-safety and type-safety, this gives you no bother about those errors. However, static typing languages often slow our developing speed down in early stage. In that case, it's effective to write prototype in an easy language like Python, and rewrite it in a hard language. It's important not to be afraid to throw away first code you write.
The other answers are excellent, but I want to be a bit of a contrarian and say you should learn Rust. While the number of jobs for it are (relatively) low(er), it is certainly expanding and you'd be surprised at which companies do use Rust (Discord, for example, is starting to move away from Golang to Rust!).
But the main reason is that learning Rust itself will teach you a lot about systems design (/backend) because of its borrow checker. You can try out a lot of ideas and make a lot mistakes and the borrow checker will always be there guide you to a better solution (thereby teaching you in the process).
Also, I wouldn't underestimated how important managing memory (and memory safety) is. While Golang is great in some ways, it doesn't protect you from pushing memory leaks into production. And eventually you'll come upon a scenario where you'll have to make your Python code run faster and the optimizations you'd have to do won't look pretty (or be very Pythontic).
And Rust is freakin fast! If you have Rust, you wouldn't need any other language for the backend (or any other systems level code). Check this blog post: https://blog.discord.com/why-discord-is-switching-from-go-to-rust-a190bbca2b1f?gi=dd8bc5d669d. Discord found that even after spending months optimizing Golang code it still wasn't fast enough. But unoptimized, first-draft Rust code was (is) faster by an order of magnitude!
Hi
I want to build a tool to check asset availability (video, images, etc.) from third-party vendors. These vendors have APIs. However, this process should run daily basis and update the database with the status. This is a kind of separate process. I need to know what will be the good approach and technology for this?
hi - I think this depends on how you want to provide the information to the user. If you want to build a Wordpress-plugin: PHP If you want to build your own website: Python+Django / PHP / JavaScript+Node.js As Desktop application?
for what technologies you should use, this is depend on what technology do you prefer? your should think best structuing for your code because each API vendor has different to a nother one so it's better no merege code vendores together. your code must be using SOLID principle pattern and some design pattern such as Factory Pattern
The major advantage of Go is that you can run queries in parallel. Fire off a Go thread for each vendor and each thread can check the availability of assets from a specific vendor and update the database. Go supports hundreds of threads with ease.
your decision depend on what language do you know. if you know php you can use laravel framework
Hi, I would recommend Go because of strongly-typed nature which makes a developer more productive as it is less error prone compared to the other dynamic-typed language. Go also has cron-job library(powered by goroutines) that can help with your automated tasks.
I am a beginner, and I am totally confused, which of these 3 languages to learn first. Go, Rust, or Python. As my studies are going which of them will be easy to learn with studies that is, I can learn and do my studies also. Which one of them will be easily handled with my studies, and will be much much useful in future?
Python is a great language to learn as a beginner. However, Go is really easy to learn as well and has a much more powerful standard library that will allow you to build very complex and powerful applications in the future. Go is becoming a standard in Cloud computing and concurrency. Both of which are very advanced but important.
I have experience in all three languages, and you should learn python first. These are three different languages (read: tools) to solve different problems you may have. Python is a high level language you can use for writing cross-platform scripts, web servers, AI, websites (e.g. Django) and the list goes on. Python can be used for most programming tasks while being the easiest to learn of the three and probably the most productive as well.
A lot of tech companies start out with Python for their web services, but due to Pythons slow speed and the pain that comes with dynamically typed languages when the code base grows, switch to Go later on when they need to scale. Go is a systems language that thrives when used for high performance cloud/web or networking services. Go is used in performance critical networking situations such as Twitch's streaming services and Uber's geofence services. It's also very clean and simple syntax that makes it very easy to quickly understand what code does.
Python is an interpreted language and Go is a garbage collected language, but Rust is a highly performant and reliable compiled programming language without the extra baggage of runtime memory management. Rust forces you to follow coding patterns that assure memory safety. This makes Rust a perfect fit for high performance algorithms, game engines or safety-critical systems, but would be overkill for web servers or scripts on modern hardware.
I'd definitely start with Go. I know Python, Go and quite a few other languages.
Rust is not easy to learn as a beginner.
Python has way too many features to be called "easy" to learn. While it is very forgiving to beginner mistakes it feels like playing in a puddle of mud. It does not teach you clean programming at all. Unless of course you like messy.
Go on the other hand is very easy to learn. As a professional you can learn the entire language in under 2 hours. I have already given the tour of Go (https://tour.golang.org/) to complete beginners and they went through it very thoroughly and thereby knew the entire Go language in less than 5 days. While it is very easy to learn and very easy to read, it is quite strict on other things, guiding you to write clean code. For one it is a typed language and it is good to learn very early about types.
Knowing the entire language is of course not all there is to know. There is the standard library and a lot of other libraries to get to know in every language. Also one has to learn patterns in every language, get experience on how to structure code, dig deeper into the language itself to understand its inner workings, etc. That takes years in every language.
That being said, it depends very much on what you want to do with a language. If you want to go into ML and science you definitely need Python. If you want to go into cloud computing, distributed servers (which in my opinion any server should be nowadays), use Go. If you want to do systems level programming, e.g in hardware programming, use Rust.
Rust is probably a bad choice for starting out. It is a low level language where garbage collection is not done automatically, and has to get you thinking about all the technical aspects. It is statically typed and compiled, so it's very strict with how you code. I do love Rust though, it's a nice language. Golang is also compiled and statically typed, but it aims to be for quick development, which makes it a better choice for starting out.
Python though can be great for starting out and getting a hold on how to program. You don't need to worry about things such as types, garbage collection, or an overwhelming amount of data types. Since I'm a JavaScript fanboy I can't help but say another great popular choice to start is JavaScript 😁
If all you want is a gentle intro and have access to tools and libs that can help with your tasks, Python is the way to go. It's ecosystem is huge and the language is easy to pick up. However, if you are aiming to get into software industry, I'd highly recommend you also pick up another classic language like C++/C#/Java. It really helps you cement some CS & programming fundamentals and get more familiar with the concept of software design and software architecture. Not saying you cannot achieve good architecture in Python or Go, but traditionally you have more materials covering these classic OOP languages. And once you learn them, you can apply your knowledge to other languages and it helps you understand other languages faster.
Python has the broadest reach as it's been around the longest; rust is much more difficult for a beginner to learn; I work with Go every day and it's probably the most productive general use language.
If you start learning programming I'd suggest Python language. I have no experience with Go and Rust so I cannot give you advice for them.
Python is the easiest of the languages to learn, and while the slowest in production, it will teach many of the basic fundamental concepts of programming, especially if you're not going to be doing anything low level or at a system level.
Learn/start with C; don't rush after buzz words. Python is easy to learn but you would not get the underpinnings of memory and pointers, an important aspect of programming.
Python, because its the easiest to learn as a beginer. Its often called "English without grammar" because its terms and writing style is quite similar to English. Python also has a diverse range of applications like Web App, Desktop App, Data Science etc
Study, machine learning = Python | High performance computing, safety-oriented programming = Rust | Backend, feel productive with less runtime performance drawback = Go
Python is the best programming language for starting out as it is quite easy to learn, but it also is very powerful and you can do plenty with it. It will be useful for a long time. Python is my recommendation.
Go and Python are going to be much easier to learn than Rust. The memory management for Rust is pretty hard to wrap your head around when you are first learning how to do basic things with the language. Get familiar with programming first, then learn Rust.
Python is a great language to start programming with, there is an awesome python course on coursera by Dr. Charles Severance called Programming for everybody, check it out :)
I agree with most of the other answers here. Python is the best choice because it is super user-friendly, has an easy syntax, and can do many complex things in relatively fewer lines.
While Rust is a more recent and a great language nonetheless, it is slightly more complicated as it involves compiling and the syntax isn't so great.
And Go is the not a great choice either. While it has a decent syntax, keep in mind that Go won't be of much use unless you plan on working in Google. Even if you want to learn it, you can do so later.
I hope this helped you in making your decision, and welcome to the world of programming! I hope you enjoy.
I'd choose python because with a good knowledge of python and it's libraries, you could do literally anything. Also it has a relatively simple structure, so it won't be tough for a beginner.
Later on if you wish to learn Rust and Go, please do by all means.
So, I've been working with all 3 languages JavaScript, Python and Rust, I know that all of these languages are important in their own domain but, I haven't took any of it to the point where i could say I'm a pro at any of these languages. I learned JS and Python out of my own excitement, I learned rust for some IoT based projects. just confused which one i should invest my time in first... that does have Job and freelance potential in market as well...
I am an undergraduate in computer science. (3rd Year)
I would start focusing on Javascript because even working with Rust and Python, you're always going to encounter some Javascript for front-ends at least. It has: - more freelancing opportunities (starting to work short after a virus/crisis, that's gonna help) - can also do back-end if needed (I would personally avoid specializing in this since there's better languages for the back-end part) - hard to avoid. it's everywhere and not going away (well not yet)
Then, later, for back-end programming languages, Rust seems like your best bet. Its pros: - it's satisfying to work with (after the learning curve) - it's got potential to grow big in the next year (also with better paying jobs) - it's super versatile (you can do high-perf system stuff, graphics, ffi, as well as your classic api server) It comes with a few cons though: - it's harder to learn (expect to put in years) - the freelancing options are virtually non-existent (and I would expect them to stay limited, as rust is better for long-term software than prototypes)
I suggest you to go with JavaScript. From my perspective JavaScript is the language you should invest your time in. The community of javascript and lots of framework helps developer to build what they want to build in no time whether it a desktop, web, mobile based application or even you can use javascript as a backend as well. There are lot of frameworks you can start learning i suggest you to go with (react,vue) library both are easy to learn than angular which is a complete framework.
And if you want to go with python as a secondary tool then i suggest you to learn a python framework (Flask,Django).
I've been juggling with an app idea and am clueless about how to build it.
A little about the app:
- Social network type app ,
- Users can create different directories, in those directories post images and/or text that'll be shared on a public dashboard .
Directory creation is the main point of this app. Besides there'll be rooms(groups),chatting system, search operations similar to instagram,push notifications
I have two options:
- React Native, Python, AWS stack or
- Flutter, Go ( I don't know what stack or tools to use)
Currently, I have decided to use Python and JavaScript (especially React and Node.js) for any of my projects. Well, I have used Python with Django for a lot of things, and I would certainly recommend Django to anyone, due to its high secure authentication and authorization inbuilt system, a ready to use admin platform, template tags, and many more. Well, I guess that you would like to use Python to create the backend of your application, an API, and React Native for the frontend. Python and JavaScript (React) are on the trend these days and have a huge community, so there are many resources, tutorials, great documentation. I have not really heard anyone using Flutter and Go for applications these days, so I would not recommend it to you, it would make your life much more difficult.
Hope that helps, and good luck with your project!
I'm typically agnostic when it comes to picking languages. Whatever gets the job done, but, in this case, to figure out what's involved with what you want to do, it's going to be much more than just picking programming languages for your client and backend interfaces.
So, I'm recommending you use Flutter+Firebase as a way to figure out what you need to get done. It supports both iOS and Android out of the box, introduces you to a bunch of components you will need to think about in the future (whether you stick with Firebase or not), and the key here, is that there are tons of articles, youtube videos, and other courses you can take to pick it up pretty quickly. You could even clone an Instagram knockoff from github. Guess what else, it's all free. You might not need to worry as much about the backend since there are client libraries for Flutter/Dart for Firebase.
Some might have different opinions, and like I said, I'm usually agnostic, but in this case, you have a lot to consider. Where are you going to store the data? Are people going to need to login? Will there but customized settings the will save even if I close the app? Yeah, that's just a few questions.
Those are just a few. Lots to consider, so if you want to get something in your hand as soon as possible, try a search for flutter + firebase + chat + Instagram or something like that and have a look.
The above listed tools will do the job, you just need to figure out your architecture(e.g models). How they will all connect. Then you can use a tool you are comfortable with to implement them.
If this is for learning about how to design the system, then pick the tools are you are confortable with.
Often times, I get stuck picking the tools (and trying to learn about them) vs actually trying to design the system itself.
If you are familiar with React (check out Expo) and Django then I would recommend going with that.
For deploying your backend, I would go with a provider like https://zeit.co/ that automates a whole bunch of deployment steps with their cli tools that you might have to do with AWS.
What you need to take a look at is Apache OpenMeetings. It already does what you want, it is open source and well documented and only requires that you design the UI and plumbing required to serve you application.
Let's select right tool you feel you are good at. And selecting tools are used by large community to solve your stuck if encounter
We chose Rust for our web API because the Warp crate makes it easy to compose high-performance and asynchronous APIs. Rust allows us to achieve high development velocity because it provides zero-cost abstractions and enforces strict type and memory-safety checks with high quality and actionable error messages.
Python will be used in order to train machine learning models from our data. We chose python for this task because it is the most common language for machine learning. It has very performant libraries like numpy and scikit-learn that provide functionality for manipulating data and creating models that you cannot get in other languages like JavaScript and Java. Additionally, it is the most familiar language for us to use for machine learning because almost every machine learning course teaches ml using python.
Javascript will be used for both our frontend and backend on the web service. JavaScript is ubiquitous as the language to use for the frontend. For the backend, we decided to create our server using JavaScript because of its easy setup; using Express we can create a server in just a few short lines of code. It is simple not only to run the server locally, but to host it as well because any major service will support the language. JavaScript is a simple language to code in and familiar among our team members, so using it will help speed up development. Using JavaScript allows us to use NodeJS and npm, so we can use packages to easily set up the server, connect to a database and other convenient utilities. We also considered Python for our server. It is also very simple to create a server in Python, especially using flask. However, the extra familiarity with the JavaScript language and the ease of using packages were enough for us to pick JavaScript as our language of choice.
MACHINE LEARNING
Python is the default go-to for machine learning. It has a wide variety of useful packages such as pandas and numpy to aid with ML, as well as deep-learning frameworks. Furthermore, it is more production-friendly compared to other ML languages such as R.
Pytorch is a deep-learning framework that is both flexible and fast compared to Tensorflow + Keras. It is also well documented and has a large community to answer lingering questions.
Python: The top language in machine learning area because of the various open-source libraries. Our company will rely on open-source libraries for development as well.
Amazon EC2: Training machine learning model needs to be running on independent 3rd party computing resources. AWS EC2 can provide a variety of virtual computing resources based on what users need.
React+Javascript: React is popular and everyone in the team is familiar with it. React is an open-source JavaScript library that is used for building user interfaces specifically for single-page applications.
ExpressJS: Everyone in the team has used expressJS for development. It can create server-side web applications faster and smarter.
Amazon RDS: relational database service and free to use
Postman: Tool for the team to test API endpoint.
Circle CI: is lightweight and open. Therefore for faster deployment jobs, one can execute their codes on CircleCI as it deploys on scalable and robust cloud servers.
Docker: Easily pack, ship, and run any application as a lightweight, portable, self-sufficient container, which can run virtually anywhere
Github+Git: Julian is from Github so no other choice for us 😎
Slack: Everyone likes it and it's free
Python: Top one language in machine learning area because of the various open source libraries. Our company will rely on the open source libraries for development as well.
Amazon EC2: Training machine learning model needs to be ran on independent 3rd party computing resources. AWS EC2 can provide variety of virtual computing resources based on what users need.
React+Javascript: React is popular and everyone in the team is familiar with it. React is an open-source JavaScript library that is used for building user interfaces specifically for single-page applications.
ExpressJS: Everyone in the team has used expressJS for development. It can create server-side web applications faster and smarter.
Amazon RDS: relational database service and free to use
Postman: Tool for the team to test API end point.
Circle CI: is lightweight and open. Therefore for faster deployment jobs, one can execute their codes on CircleCI as it deploys on scalable and robust cloud servers.
Docker: Easily pack, ship, and run any application as a lightweight, portable, self-sufficient container, which can run virtually anywhere
Github+Git: Julian is from Github so no other choice for us 😎
Slack: Everyone likes it and it's free
2 major challenges for which JS comes as a handy tool, 1st its integration with AWS SDK was at par as Python and .net and the solution comes to hand with the reverse proxy solutions for the application to be running as an instance taking the situation of inside organization demography of resources expertise over the technology.
I had a goal to create the simplest accounting software for Mac and Windows to help small businesses in Canada.
This led me to a long 2 years of exploration of the best language that could provide these features:
- Great overall productivity
- International wide-spread usage for long-term sustainability and easy to find documentation
- Versatility for creating websites and desktop softwares
- Enjoyable developper experience
- Ability to create good looking modern UIs
- Job openings with this language
I tried Python, Java, C# and C++ without finding what I was looking for.
When I discovered Javascript, I really knew it was the right language to use. Thinking of this today makes me realize even more how great a decision this has been to learn, use and master Javascript. It has been a fun, challenging and productive road on which I am still satisfied.
Obviously, when I refer to Javascript, it is not without implying the vast ecosystem around it. For me, JS is a whole universe in which almost every imaginable tools exist. It's awesome - for real. Thanks to all the contributors which have made it possible.
To be even clearer about how intense I am with Javascript, let's just say that my first passion was music. Until, I find coding with Javascript! Yep, I know!
So in conclusion, I chose Javascript because it is versatile, enjoyable, widely used, productive for both desktop softwares and websites with ability to create modern great looking user interfaces (assuming HTML and CSS are involved) and finally there are job openings.
Go is a way faster than both Python and PHP, which is pretty understandable, but we were amazed at how good we adapted to use it. Go was a blessing for a team , since strict typing is making it very easy to develop and control everything inside team, so the quality was really good. We made huge leap forward in dev speed because of it.
Context: Writing an open source CLI tool.
Go and Rust over Python: Simple distribution.
With Go and Rust, just build statically compiled binaries and hand them out.
With Python, have people install with "pip install --user" and not finding the binaries :(.
Go and Rust over Python: Startup and runtime performance
Go and Rust over Python: No need to worry about which Python interpreter version is installed on the users' machines.
Go over Rust: Simplicity; Rust's memory management comes at a development / maintenance cost.
Go over Rust: Easier cross compiles from macOS to Linux.
Pros of Golang
- High-performance551
- Simple, minimal syntax395
- Fun to write363
- Easy concurrency support via goroutines303
- Fast compilation times273
- Goroutines195
- Statically linked binaries that are simple to deploy181
- Simple compile build/run procedures151
- Great community137
- Backed by google137
- Garbage collection built-in53
- Built-in Testing47
- Excellent tools - gofmt, godoc etc44
- Elegant and concise like Python, fast like C40
- Awesome to Develop37
- Used for Docker26
- Flexible interface system26
- Great concurrency pattern25
- Deploy as executable24
- Open-source Integration21
- Easy to read19
- Fun to write and so many feature out of the box17
- Go is God17
- Powerful and simple14
- Easy to deploy14
- Its Simple and Heavy duty14
- Concurrency14
- Best language for concurrency13
- Safe GOTOs11
- Rich standard library11
- Clean code, high performance10
- Easy setup10
- High performance10
- Simplicity, Concurrency, Performance9
- Cross compiling8
- Single binary avoids library dependency issues8
- Hassle free deployment8
- Used by Giants of the industry7
- Simple, powerful, and great performance7
- Gofmt7
- Garbage Collection6
- WYSIWYG5
- Very sophisticated syntax5
- Excellent tooling5
- Keep it simple and stupid4
- Widely used4
- Kubernetes written on Go4
- No generics2
- Looks not fancy, but promoting pragmatic idioms1
- Operator goto1
Pros of Python
- Great libraries1.2K
- Readable code962
- Beautiful code847
- Rapid development788
- Large community690
- Open source438
- Elegant393
- Great community282
- Object oriented272
- Dynamic typing220
- Great standard library77
- Very fast60
- Functional programming55
- Easy to learn49
- Scientific computing45
- Great documentation35
- Productivity29
- Easy to read28
- Matlab alternative28
- Simple is better than complex24
- 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
- Now is better than never6
- Great for tooling6
- Readability counts6
- Rapid Prototyping6
- I love snakes6
- Flat is better than nested6
- Fast coding and good for competitions6
- There should be one-- and preferably only one --obvious6
- High Documented language6
- 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
- Many types of collections3
- Flexible and easy3
- It is Very easy , simple and will you be love programmi3
- 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
- If the implementation is easy to explain, it may be a g3
- Can understand easily who are new to programming2
- Batteries included2
- Securit2
- Good for hacking2
- Better outcome2
- Only one way to do it2
- Because of Netflix2
- A-to-Z2
- Should START with this but not STICK with This2
- Powerful language for AI2
- Automation friendly1
- Sexy af1
- Slow1
- Procedural programming1
- Ni0
- Powerful0
- Keep it simple0
Pros of Rust
- Guaranteed memory safety145
- Fast132
- Open source88
- Minimal runtime75
- Pattern matching71
- Type inference63
- Concurrent57
- Algebraic data types56
- Efficient C bindings47
- Practical43
- Best advances in languages in 20 years37
- Safe, fast, easy + friendly community32
- Fix for C/C++30
- Stablity25
- Zero-cost abstractions24
- Closures23
- Extensive compiler checks20
- Great community20
- Async/await18
- No NULL type18
- Completely cross platform: Windows, Linux, Android15
- No Garbage Collection15
- High-performance14
- Great documentations14
- Super fast12
- High performance12
- Generics12
- Guaranteed thread data race safety11
- Safety no runtime crashes11
- Macros11
- Fearless concurrency11
- Compiler can generate Webassembly10
- Helpful compiler10
- RLS provides great IDE support9
- Prevents data races9
- Easy Deployment9
- Painless dependency management8
- Real multithreading8
- Good package management7
- Support on Other Languages5
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Cons of Golang
- You waste time in plumbing code catching errors42
- Verbose25
- Packages and their path dependencies are braindead23
- Google's documentations aren't beginer friendly16
- Dependency management when working on multiple projects15
- Automatic garbage collection overheads10
- Uncommon syntax8
- Type system is lacking (no generics, etc)7
- Collection framework is lacking (list, set, map)5
- Best programming language3
- A failed experiment to combine c and python1
Cons of Python
- 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
Cons of Rust
- Hard to learn28
- Ownership learning curve24
- Unfriendly, verbose syntax12
- High size of builded executable4
- Many type operations make it difficult to follow4
- No jobs4
- Variable shadowing4
- Use it only for timeoass not in production1