Node.js vs Python: What are the differences?
Node.js and Python are primarily classified as "Frameworks (Full Stack)" and "Languages" tools respectively.
Node.js and Python are both open source tools. Node.js with 35.5K GitHub stars and 7.78K forks on GitHub appears to be more popular than Python with 25K GitHub stars and 10.3K GitHub forks.
According to the StackShare community, Node.js has a broader approval, being mentioned in 4054 company stacks & 3897 developers stacks; compared to Python, which is listed in 2789 company stacks and 3500 developer stacks.
What will be better Laravel or Node.js to handle a logistics portal which displays thousands (20-50k) of delivery data information in an interactive table (searchable, filterable), live delivery tracking, basic user management, and report creation?
Data comes usually in CSV (manually uploaded or via API from courier companies). Live tracking uses checks tracking numbers on the courier page using API.
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!
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!
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?
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.
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
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.
We choose Next.js for our React framework because it's very minimal and has a very organized file structure. Also, it offers key features like zero setups, automatic server rendering and code splitting, typescript support. Our app requires some loading time to process the video, server-side rendering will allow our website to display faster than client-side rending.
Python has become the most popular language for machine learning right now since almost all machine learning tools provide service for this language, and it is really to use since it has many build-in objects like Hashtable. In C, you need to implement everything by yourself.
C++ is one of the most popular programming languages in graphics. It has many fancy libraries like eigen to help us process matrix. I have many previous projects about graphics based on C++ and this time, we also need to deal with graphics since we need to analyze movements of the human body. C++ has much more advantages than Java. C++ uses only compiler, whereas Java uses compiler and interpreter in both. C++ supports both operator overloading and method overloading whereas Java only supports method overloading. C++ supports manual object management with the help of new and delete keywords whereas Java has built-in automatic garbage collection.
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.
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I have benchmarked Node.js and other popular frameworks using a real life application example. You can find the results here: https://firstname.lastname@example.org/web-rest-api-benchmark-on-a-real-life-application-ebb743a5d7a3
We decided to move the provisioning process to an API-driven process, and had to decide among a few implementation languages:
- Go, the server-side language from Google
We built prototypes in both languages, and decided on NodeJS:
- NodeJS is asynchronous-by-default, which suited the problem domain. Provisioning is more like “start the job, let me know when you’re done” than a traditional C-style program that’s CPU-bound and needs low-level efficiency.
- NodeJS acts as an HTTP-based service, so exposing the API was trivial
Getting into the headspace and internalizing the assumptions of a tool helps pick the right one. NodeJS assumes services will be non-blocking/event-driven and HTTP-accessible, which snapped into our scenario perfectly. The new NodeJS architecture resulted in a staggering 95% reduction in processing time: requests went from 7.5 seconds to under a second.
Beautiful is better than ugly.
Explicit is better than implicit.
Simple is better than complex.
Complex is better than complicated.
Flat is better than nested.
Sparse is better than dense.
Special cases aren't special enough to break the rules.
Although practicality beats purity.
Errors should never pass silently.
Unless explicitly silenced.
In the face of ambiguity, refuse the temptation to guess.
There should be one-- and preferably only one --obvious way to do it.
Although that way may not be obvious at first unless you're Dutch.
Now is better than never.
Although never is often better than right now.
If the implementation is hard to explain, it's a bad idea.
If the implementation is easy to explain, it may be a good idea.
Namespaces are one honking great idea -- let's do more of those!
The server side of Trello is built in Node.js. We knew we wanted instant propagation of updates, which meant that we needed to be able to hold a lot of open connections, so an event-driven, non-blocking server seemed like a good choice. Node also turned out to be an amazing prototyping tool for a single-page app. The prototype version of the Trello server was really just a library of functions that operated on arrays of Models in the memory of a single Node.js process, and the client simply invoked those functions through a very thin wrapper over a WebSocket. This was a very fast way for us to get started trying things out with Trello and making sure that the design was headed in the right direction. We used the prototype version to manage the development of Trello and other internal projects at Fog Creek.
All backend code is done in node.js
We have a SOA for our systems. It isn't quite Microservices jsut yet, but it does provide domain encapsulation for our systems allowing the leaderboards to fail without affecting the login or education content.
We've written a few internal modules including a very simple api framework.
I don't know how well this will scale if/when I have hundreds of people connected simultaneously, but I suspect that when that time comes, it may be just a matter of increasing the hardware.
Used node.js server as backend. Interacts with MongoDB using MongoSkin package which is a wrapper for the MongoDB node.js driver. It uses express for routing and cors package for enabling cors and eyes package for enhancing readability of logs. Also I use nodemon which takes away the effort to restart the server after making changes.
To me, this is by far the best programming language. Why? Because it’s the only language that really got me going after trying to get into programming with Java for a while. Python is powerful, easy to learn, and gets you to unsderstand other languages more once you understand it. Did I state I love the python language? Well, I do..
Backend server for analysis of image samples from iPhone microscope lens. Chose this because of familiarity. The number one thing that I've learned at hackathons is that work exclusively with what you're 100% comfortable with. I use Python extensively at my day job at Wit.ai, so it was the obvious choice for the bulk of my coding.
been a pythoner for around 7 years, maybe longer. quite adept at it, and love using the higher constructs like decorators. was my goto scripting language until i fell in love with clojure. python's also the goto for most vfx studios and great for the machine learning. numpy and pyqt for the win.