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Python vs Swift: What are the differences?

Key Differences between Python and Swift

Introduction

In this article, we will explore the key differences between Python and Swift programming languages. Both Python and Swift are popular and widely used languages in different domains, and understanding their differences can help developers choose the most appropriate language for their projects.

  1. Syntax: One of the primary differences between Python and Swift is their syntax. Python uses an indentation-based syntax, where the indentation level determines the block structure. On the other hand, Swift uses braces to define blocks of code, similar to C-based languages like C++, Java, and JavaScript.

  2. Typing: Another significant difference is the typing system. Python is dynamically typed, meaning that variable types are determined at runtime. In contrast, Swift is statically typed, requiring explicit declaration of variable types during compile-time. This makes Swift more type-safe and allows for better performance optimizations.

  3. Memory Management: Python utilizes automatic memory management through garbage collection. The programmer doesn't need to explicitly manage memory allocation and deallocation. In Swift, memory management is done using Automatic Reference Counting (ARC), which automatically tracks and deallocates unused objects. However, Swift also provides control over memory management through manual memory management techniques if needed.

  4. Platform Support: Python is versatile and can run on multiple platforms, including Windows, macOS, and Linux. Swift, initially developed by Apple, is primarily used for iOS, macOS, watchOS, and tvOS app development. While efforts are being made to expand Swift's availability on other platforms, it still lags behind Python in terms of cross-platform support.

  5. Libraries and Ecosystem: Python has a vast ecosystem and a rich collection of libraries and frameworks built by the community, making it a popular choice for data science, web development, and automation tasks. Swift, being relatively new, has a smaller ecosystem, with a focus on iOS and macOS development. However, Swift is supported by Apple and has a growing number of libraries and frameworks specifically designed for iOS and macOS development.

  6. Concurrent Programming: Python relies on Global Interpreter Lock (GIL), which allows only one thread to execute Python byte code at a time, limiting true parallelism in multi-threaded applications. Swift, on the other hand, does not have a GIL and supports true parallelism, making it more suitable for concurrent programming and performance-critical applications.

In summary, Python and Swift differ in their syntax, typing system, memory management techniques, platform support, ecosystem, and concurrent programming capabilities. Understanding these differences allows developers to choose the most suitable language for their specific requirements.

Advice on Python and Swift
Caue Carvalho
Needs advice
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GolangGolangPythonPython
and
RubyRuby

Hello!

I'm a developer for over 9 years, and most of this time I've been working with C# and it is paying my bills until nowadays. But I'm seeking to learn other languages and expand the possibilities for the next years.

Now the question... I know Ruby is far from dead but is it still worth investing time in learning it? Or would be better to take Python, Golang, or even Rust? Or maybe another language.

Thanks in advance.

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Replies (8)
Angel Ramirez
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Hi Caue, I don't think any language is dead in 2022, and we still see a lot of Cobol and Fortran out there, so Ruby is not going to die for sure. However, based on the market, you'll be better off learning Goland and Python. For example, for data science, machine learning, and similar areas, Python is the default language while backend API, services, and other general purpose Goland is becoming the preferred.

I hope this helps.

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GolangGolangPythonPython

I feel most productive using go. It has all the features I need and doesn't throw road blocks in your way as you learn. Rust is the most difficult to learn as borrow checking and other features can puzzle a newcomer for days. Python is a logical next step as it has a huge following, many great libraries, and one can find a gig using python in a heartbeat. Ruby isn't awful, it's just not that popular as the others.

Another reason to use python is that it is not compiled. You can muck around in the interpreter until you figure things out. OTOH, that makes it less performant. You really need to think about your use cases, your interest in lower-lever versus high-level coding, and so on.

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Roman Glushko
Machine Learning, Software Engineering and Life · | 4 upvotes · 70K views
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GolangGolangPythonPythonRustRust

I enjoy coding in Python. I think it's minimalistic and readable syntax and lang features are just unparalleled. They are perfect for prototyping and for the software engineering in general. If I'm not wrong Gitlab marked Python as #2 popular language after JavaScript. Beyond that, Python ecosystem and areas of usage are enormous. In areas like ML/DL, it's important to know Python to leverage variety of existing tools and frameworks.

Then, I have learned and worked with Golang. I use it where I think I would need a slightly better performance than in Python. Plus, relatively small and self-contained executable is a great thing to have. If you plan to write distributed systems, extend Kubernetes or do similar things I think Golang is a great choice. It's also simple and straightforward, especially when you want to do effective multithreading. Although I don't like that Golang is more low-level than Python. Sometimes I feel like I need to implement myself too much things.

Now, about Rust. It's my second try to learn Rust. First time I decided to learn Golang as I understood it in 30mins or so while I was struggling to compile/do anything meaningful there for quite a bit. So I personally don't think Rust is super easy. I have got back to learning Rust as it's going to fill one of gaps in my problem solving toolkit - let me write low-level system programs (e.g. linux kernel modules). I don't want to learn "obsolete" C/C++ (my reasons are similar to why Google has recently introduced Carbon - a replacement for C/C++ codebases). If you are not going to tight your life with system-like programming, Rust may be an overkill for you.

Finally, I have never coded in Ruby, so are not going to comment it.

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Recommends
on
PythonPython

Because it opens endless possibilities you can do anything and everything you want to. from ai to app development to web development.

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at

Since you are very experienced, picking up a language will not take you more than a week. Rust is a very new language. Many startups are still experimenting with it. Golang is very popular nowadays. You can see a lot of golang jobs in the market. The best part is, compiled code is single binary and has a minimal footprint. Rails is a compelling framework; believe me, many websites like Shopify, GitHub, GitLab, etc., are powered by the rails framework. You can also leverage the power of metaprogramming in Ruby. Python is memory and CPU intensive. It is not as performant as the other three. If you want to go into Data Science, Python is the language. Good luck, buddy. Feel free to connect with me: https://twitter.com/avirajkhare00

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I'm almost same position as you. 8 years same company with c#. I tried both Python and Golang. I like working with Golang. Check this litte go doc. After reading this document and following its examples, I decided to work with "go" https://www.openmymind.net/assets/go/go.pdf

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it is highly recommended to take a look at that survey

https://survey.stackoverflow.co/2022/

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A Nielsen
Fullstack Dev at ADTELA · | 1 upvotes · 66.6K views
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on
GolangGolangPythonPython

Either Python or Golang, for all the enlightened reasons already mentionned in all advices/comments :) Enjoy!

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Nikhilesh Swaminathan
Needs advice
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JavaJavaJavaScriptJavaScript
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PythonPython
Please Help in creating a test framework

Hello Devs,

I am planning to implement a ETL test system for checking data quality and business use cases. I am confused on what stack to use. Any advice on the below will be very helpful.

  1. Any existing frameworks and its source code for help
  2. Any other stack apart from the mentioned stack (that might be suitable)
  3. Any ideas for features are welcomed.
  4. The usage of multiple BE stacks.
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Replies (1)

If you want to create using Python language, Robot Framework is one very helpful tool to improve your test scripting and we have a lot of methods created by the community. If you want to use Javascript, Cypress in terms of benefits is the better option to create and maintain tests, and run and generate reports in many browsers is really easy with them.

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Sachin K
Cloud Engineer and Developer · | 6 upvotes · 102.4K views
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GolangGolangJavaJava
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PythonPython

Hello Folks, my first time here, and for requesting advice. I am trying to create some automation from my cloud stack on AWS to something more cloud native. I have containerised the services, however, I am stuck at DB, my Data warehouse, and messaging. Would love some recommendations on how can I automate this for some future work too.

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Replies (1)
Simon Banks
Principal Software Engineer at AtCore Tech · | 3 upvotes · 98.8K views
Recommends

I recommend cloud-init for base setup of machines and configuring them.. Its simple (YAML file) and is industry standard. Even works on bare metal as well as cloud.

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Paul Morgan
Researcher at Working on it · | 25 upvotes · 258.7K views
Needs advice
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JavaScriptJavaScriptPythonPython
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ReactReact

Hey everyone, I have a matrix chart drawn in HTML5/CSS 3 dominantly using CSS grid. I would like to add interactive features and am unsure about the best tool. My programming knowledge is limited to 2 semesters of Java in college, so I'd have to learn the language as I go. I am open to anything, but the selected languages would be useful in future projects.

Here are the features I am attempting to add to the site linked as my blog:

  • Assign over 120 attributes each to over 400 elements (probably in a DB)

  • Procedurally position elements in a matrix chart based on user-inputted filters (filtering and searching)

  • Procedurally position matrix elements based on attributes weighted by user-input

  • Change style of elements based on user input (highlighting)

  • Allow saving matrix chart states to be revisited or shared

  • Provide a user-friendly interface for users to submit the above input

  • Build several columns or matrices that are separate but related and seamless to the viewer

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Replies (5)

PyCharm + Python + Flask + Jinja2 is enough to build web server/ajax and JavaScript + JQuery (maybe React). You can write small easy application but also extreme high scalable application.

I know Java but it need 4x time more code and code is not clear (too much forced use of @decorators) - too complex and takes more memory :)

Remember if you code in Python it is easy to code in Java but if you code in Java you must understand that Python is much more flexible and powerful - also easier to learn.

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There are two main facets to interactivity - whether your frontend (Javacsript, HTML, CSS) is programmed to behave dynamically based on events and on any other preprogrammed behavior, and based on what information your server can send and receive and compute for the benefit of your frontend. For the former (a dynamic frontend) you'll need to use Javascript (or Typescript) in some form. For the latter (a server with custom behavior and data endpoints beyond just sending static HTML etc. files), any of the major languages can serve this purpose. However, if you are going to create a dynamic frontend with Javascript and don't know that language at all, then learning it will be a task in itself, and without knowing a backend language well either (probably the case with only two semesters of one language a while back), you ideally don't want to also have to learn a whole other backend language on top of that. That's where NodeJS comes in. It has essentially the same exact syntax as frontend Javascript (just different native libraries). Since you already need to learn Javascript to make the frontend behave dynamically, if you also want a custom backend, NodeJS will spare you a big learning curve on top of the existing learning curve of learning JS. NodeJS is also highly performant for low-compute high-volume requests, i.e. handling a large barrage of requests if each doesn't require a lot of complicated behavior on the backend. A lot of coding bootcamps teach this, commonly called "full stack JS", for this reason - it allows someone to learn a constellation of full stack web development skills from the mastery of one language syntax. NodeJS + ExpressJS is also one of the easiest backend languages + REST API library to use to build a backend. Look up "NodeJS Express Hello World", and you'll be shocked at how easy it is to build a basic server. As far as frontend frameworks go, if this project is very limited in scope, JQuery could be fine, but I'd highly recommend learning React for something more involved - it will be immensely easier to manage and maintain, and generally lends itself to much better and more intuitive code organization. Its use of components will also be somewhat familiar and intuitive from the object oriented programming you learned through Java. Create React App is great tool to use, especially when first learning React, to avoid all of the finicky nonsense in configuring transpilation etc.

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Recommends
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ReactReact

React is hands-down the tool I recommend to add interactivity to your matrix. Because it is Javascript, it will leverage a lot of the formatting from Java. Python would be very foreign to you. React shines in allowing you to use OOP principles within the JavaScript language and it is really powerful, fast and browser friendly.

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Recommends

Use Javascript alongwith HTML CSS and you have complete set of application ready (even for future for PWA or bundled applications).

You can use charts.js library https://www.chartjs.org/ or https://apexcharts.com/javascript-chart-demos/. You can find many examples, you can have a look at https://codepen.io/ksarpotdar/pen/NWyqqZM?editors=0010

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Recommends
on
JavaScriptJavaScript

Ok. Clearly you forgot the best tool to give for interactive features. JavaScript! In particular I recommend the freeCodeCamp JavaScript course. Here it is.

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Needs advice
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JavaScriptJavaScript
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PythonPython

I am unhappy. When doing my research, I heard Python is useless. Data science is an unworthy field thanks to TensorFlow, and web scraping has also become pointless since the introduction of the PWA. Since PWAs are only frontend, I feel forced to learn JavaScript, and to ditch Python. I love Python with all my mind, it's simplicity, conciseness, and easiness as a tool. Here are a few questions:

  1. Should I forget Python and move on?
  2. Are there any PWA alternatives to JavaScript/TypeScript. I've been thinking of using Python for WASM and use HTML+CSS for the DOM to create the PWA. Is this possible?
  3. Why is JavaScript such a pain in the butt
  4. What's the point of me learning Python if it's not useful for web development?
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Replies (4)
Christophe Vermeulen
Engineer Counselor at IBPT · | 8 upvotes · 79.5K views
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on
PythonPython

You should not ditch or forget Python because of what you hear or because of one particular project. It's probably going to stay relevant and useful for the coming 20 years. If you're a programmer, you should however be prepared to use several tools, and programming languages are just part of the toolbox (like HTML or CSS, but also your IDE, powershell, linux commands, etc.) It's not for nothing that this site is called "stackshare".

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Adam Bouqdib
Software Engineer, Entrepreneur at ABE Media · | 6 upvotes · 78.4K views
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on
GolangGolang

Python is great for data science but it's not very performant and eats up loads of resources. I recommend that you give Go a go. It's easy to learn and very fast!

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Recommends

JavaScript is reduced Python. Python is powerful. If Python is not powerful you can mix it with C/C++ - this is not available in JavaScript in easy way. I am programmer and electrical engineer too - I think for research Python is the best thing. JavaScript is better for Web. I code in both very good.

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Recommends

Python is definitely not useless, It has a ton of usecases, with a huge community behind it, but not that performant and consumes lots of resources, I don't think you should abandon it, and PWA is kind a in its early stage, so I doubt that there will be any language better than js for developing it any time soon, so I guess there are no alternatives, but I guess you will like js/ts if you spend a little more time playing with it, and the same goes for wasm it is also in its early stage, and i guess web assembly and rust will be used a lot for that, and lets say you have built a frontend web app , now with the help of python + django or flask you can write server code, and learn a little bit about databases, then bravo you are a full stack dev.

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Needs advice
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PythonPython

Actually, I'll add, C++ and C# as well.

Well, I'm into Computer Science since 1996, so I understand a bit of everything plus a lot of different OSs, I study 10 hours per day every day. However back in the 90s we didn't have books or universities about programming, all were passed through if you knew somebody in that profession. Which I did and in that time, he showed me .NET and MySQL, and that offered a lot of jobs also Java. Today you have a lot of options but I'm already discarding new languages as I believe they will jot succeed.

My always dream was to create game, and software. I don't understand all programming concepts and I'm studying all languages at the same time, so I'm heavy loaded. But that keeps me more aware.

I made a choice: use Python for everything but if you want performance, apps, security, compatibility, Multiplatform. What should I choose? The real question here is: which language should I go 100% and that language will teach me all I need about programming BUT without getting lost in that language forever (I discard any Assembly possibility) and one that has full documentation, support and libraries.

In my experience: I found a lot of info for python and java. But hardly I have ever found anything for C lang, C++ and, what about C# (it's only for Windows, is it easy, I saw a lot of documentation). Thanks!!

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Replies (3)
Recommends
on
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I would go with Python, it is fast to code, readable and very powerful without giving you too much to think about (e.g. memory management). If you're looking for speed, Cython is a fairly good way to get there, since Python is a C-based language it can be compiled to C using Cython and will get you a very significant boost in speed! You can also make use of C libraries if you prefer. The only downside to Cython over Python is that it is compiled and not interpreted, which can make debugging a pain (but you might find yourself doing most of the debugging in Python before switching to Cython). C languages are a bit of a pain to read up on (API, libraries etc.), but Stack Overflow has you covered in most cases!

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Python can be linked with C++ both language are similar in many places (using same libraries or concepts to build libraries) - except memory and static types. C++ is more assembler and have different syntax (need 3x-4x coding more).

If you do engineering it is perfect stack - Java is to slow in coding (4x more code) and little faster than Python - whatever it is hard to mix Java/C++ what is easy Python/C++.

In the most program you do not need super performance but if you need C++ is the best and have rich Object Language much richer than Java and more poor than Python. Python is true object language - everything is object.

Whatever sometimes more important is framework than language for specific use.

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All programming languages are cross platform except Java, but even that's not that bad. Performance: C(++), Go, Rust, Java, Ada, OCaml, Haskell, C# Apps: JS, TS, ReScript, Go, C(++), Java, Haskell, C#, Dart Security: Java, Go, Rust, COBOL, C(++), C# Compatibility: Java(due to it's VM), C(++), Go, C# Libraries: Java, Go, C(++), C# Documentation: Java, C(++) (since they are mature) What do you mean without getting lost in the language? I'd not advocate for C(or C++), considering it's hard to understand the memory, and it's for those into programming theory. You are looking for all you need. Go for Java, it has a library for everything, it has a reasonable learning curve, and pretty much you are going to encounter it everywhere- it's like a programming black hole you can't escape.

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Needs advice
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PythonPython

I want to create a mobile-first e-commerce platform app. I think Dart and Flutter is a way for me to build cross-platform apps from a single codebase but I might be wrong so what do you guys think?

I also don't know what to do about the back-end. I mean managing the database of products and users. handing orders and invoices. I think Firebase can be an answer to my problems but how far I can go with firebase and its user authentication and database tools? Just firebase is enough for all my back-end needs?

What suits my needs, a relational database or a non-relational database?

Do I need to learn another programming language for handling back-end, like Python or Go?

I would appreciate your opinion. Thanks

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Replies (1)
Mohamed Reda
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on
DartDartFirebaseFirebase

Hi, I have 3 years with Flutter and I can see that Flutter with Firebase will be a good choice for you, Just start with Firebase, it's a little bit expensive when you have a lot of users, but there you will have some money to build your own API using any other language, and here I recommend Elixir or Python.

And about what you need to learn: - Dart - Flutter - State management for Flutter - Firebase

Then you can publish your app finally, and I wish you a happy published app :)

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Hüseyin Acebet
Needs advice
on
FlutterFlutterPythonPython
and
SwiftSwift

Hello, I am still a student and would like to ask a question. Currently, I am developing in mobile development with Flutter in the frontend and Python in the backend part. Right now I have to make a choice about developing a mobile app or developing a backend to progress more professionally. My questions are as follows:

1) If I prefer the mobile application area, will I only work with the Ui/Ux developer with the front-end and code the designs in Swift Kotlin languages, am I responsible for the back-end software?

2) I have a product that generates new ideas so I like to control the development and work there because the backend is the brain, but are they independent from each other in the backend mobile application? Is the mobile app developer responsible for the backend software?

3) I don't like graphic design because I don't like it if it's not perfect and I get stressed. Am I responsible for the graphic design in the mobile app?

4) Is a mobile app developer also a backend developer?

I know these are very simple questions, but they are very important to me. Thanks for your answers.

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Replies (3)
Benjamín Cáceres
Software Developer at Empirica Consultores · | 5 upvotes · 120.9K views
Recommends

Hi Hüseyin! 1-2) In my experience If you are a Mobile Applications Developer you will have the following responsabilities: - Develop (not designing) both functionality and screens of the app you are working - Consume (not develop) third party or self company owned APIs or Backend services - Distribution tasks. - Mantainance tasks. Now, there will always be companies wishing you know the whole thing (ui/ux, backend, frontend, mobile, cd/ci, data science, etc.). And of course it will be helpful for you to know a little bit of the stuff around mobile development, but it's not very common since it's not part of the responsabilities of a mobile app dev.

3) No, you are not responsable for the designs of your application, that's why companies have Product designers, ux designers, ui designers for preparing the screens, logos, color palettes, etc for products. As a developer your job is to see and examine the designs and take them from Figma, InVision, Zeplin, etc to the Code editor.

4) This is the thing, if you are working as a Mobile Developer you might know about Mobile development, not backend, not frontend, not ui ux. BUT if you know a little about backend that might be helpful although backend should not be your responsability.

I hope this makes sense to you. Cheers!

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Jake Hawken
Senior iOS Developer at Grailed · | 4 upvotes · 116.8K views
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SwiftSwiftXcodeXcode

As a mobile developer, I'm usually a member of a larger team and it's usually another person's responsibility to develop the backend/API, and another person's to do the UX/design. Very very few teams use cross-platform tools like Flutter or React Native, because tools like those tend to make mediocre apps that scale poorly and are impossible to debug, so make sure to get familiar with Swift/iOS or Kotlin/Android (or both).

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Preeti Yuankrathok
Software Consultant at CODIUM · | 2 upvotes · 92.2K views
Recommends

Hi! I think most of your questions led to these answers:

  • Mobile software developers don't responsible for the back-end part, or even graphic design. Of course, the back-end part should be done by a back-end developer. The graphic design, I'd say that if you work on a start-up, you might be the one who does since there isn't much manpower there, but in the larger company, they would have a designer especially in UI/UX. You'll have a mockup for the application that you need to follow. As a developer, you're expected to code, not design.

  • I've said that the responsibility isn't yours, but of course, you'll have an advantage over others if you know UI/UX, or back-end as well. That would help you a lot to be a good mobile developer.

Good luck!

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Sadie Flick
Needs advice
on
JavaJavaJavaScriptJavaScript
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PythonPython

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?

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Replies (5)
Prashant Singh Ahluwalia
Head of Engineering - AIOps at Microsoft · | 13 upvotes · 287.8K views
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at

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!

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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.

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Luan Himmlisch
Recommends

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

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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.

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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.

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Adit Patel
Needs advice
on
RustRust
and
SwiftSwift

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.

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Replies (2)
Recommends
on
RustRust

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.

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Peter Suwara
Director at Realityworks · | 6 upvotes · 118.5K views
Recommends
on
C++C++GolangGolangSwiftSwift

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.

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Decisions about Python and Swift
Piotr Czarnas

We have chosen a mix of Java and Python for building an open source data observability tool. The application can work as a standalone command line tool with a rich shell interface (using even command completion). The Java ecosystem is more mature when it comes to connectivity to various databases using JDBC. Also picocli with jline3 let us make a very dynamic shell interface with command completion. The definitions of data quality checks that should be executed are defined in YAML files, backed by a YAML (in fact JSON) schema files. Our YAML files can be edited in Visual Studio Code (and other code editors) with support of the code completion. It is possible because all the data model is defined as pure Java classes for which we are generating a YAML/JSON schema. There is still place for Python because it is very popular in the database space. We are simply starting a Python interpreter in the background (from a Java code). Python is used to evaluate validation rules (defined as Python functions) and render SQL queries from Jinja2 templates.

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Mark Esser
Director People & Culture at i22 Digitalagentur GmbH · | 8 upvotes · 114.1K views

A developer and project manager from our team X says the following about our use of Rails at i22:

"We use Rails to build stable and flexible backend systems. Rails is extremely good for managing data structures and quickly setting up new systems. It is the perfect base for most use cases."

I asked the same Team X member why the team prefers to work with Ruby on Rails, rather than Python and Django:

"Because Python is a scripting language and from my point of view not suitable for building stable web services. Python is for me rather good for scripts and fast small tools. Not for stable business applications. And if I want it fast I prefer Go."

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Gonçalo Rodrigues
Chose
GolangGolang
over
PythonPython

As we're developing a critical piece of software, type safety is very important to minimize the errors we have. While Python supports type hints nowadays, Go makes it much more easy to work with and allows us to be confident in the software we ship.

Take look at our code in our github

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Migrated
from
PythonPython
to
GolangGolang

Ever since the introduction of the PWA, I felt forced to learn JS, React, and Angular. I encountered WASM, which compiles Go/Rust to JS. I decided to give go a shot and made a simple weather PWA that tells the weather of various Japanese cities. It was 40x faster than Transcrypt and 0.9x faster than regular JS. Go is even simpler than Python when coming to tools like list comprehension and Pandas.

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Olivier B Deland
Web Developer, Consultant at ConseilsWeb · | 13 upvotes · 135.8K views

Coming from a C/C++ background, I picked up PHP 20 years ago. Today, the language is still in constant evolution while still having a stable base. It powers all of my backend project. It is fast to prototype and get started, and is supported almost everywhere.

Python and Node.js do not provide anything that PHP cannot already offer, so there is no point for me to switch to those language. Mature framework like Laravel provides real ease and speed of development to kick-start any new web project, be it a simple API or a robust ERP running on server-less architecture. There are libraries available for machine learning, crypto, web3 and pretty much anything you can think of.

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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.

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James Bender
Lead Application Architect at TekPartners · | 5 upvotes · 57.3K views

I've yet to see a non-native application that I felt performed as well and/or provided the same user experience with Cordova/PhoneGap/Xamarin. Frankly, at best they all seemed like underpowered web applications deployed to a sandbox that ran on a phone. They didn't feel "slick" or "mobile-first" and in some cases the performance was unacceptable. At previous companies, we built a few of these apps at the client's insistence, and in every case, they re-engaged us about 18 months later to re-write the app(s) natively.

We are doing some research on React Native and Flutter, but I am not yet convinced that they can provide the same level of experience and performance as native, though I am trying to keep an open mind.

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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.

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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.

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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.

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Pros of Python
Pros of Swift
  • 1.2K
    Great libraries
  • 962
    Readable code
  • 847
    Beautiful code
  • 788
    Rapid development
  • 690
    Large community
  • 438
    Open source
  • 393
    Elegant
  • 282
    Great community
  • 272
    Object oriented
  • 220
    Dynamic typing
  • 77
    Great standard library
  • 60
    Very fast
  • 55
    Functional programming
  • 49
    Easy to learn
  • 45
    Scientific computing
  • 35
    Great documentation
  • 29
    Productivity
  • 28
    Easy to read
  • 28
    Matlab alternative
  • 24
    Simple is better than complex
  • 20
    It's the way I think
  • 19
    Imperative
  • 18
    Free
  • 18
    Very programmer and non-programmer friendly
  • 17
    Powerfull language
  • 17
    Machine learning support
  • 16
    Fast and simple
  • 14
    Scripting
  • 12
    Explicit is better than implicit
  • 11
    Ease of development
  • 10
    Clear and easy and powerfull
  • 9
    Unlimited power
  • 8
    It's lean and fun to code
  • 8
    Import antigravity
  • 7
    Print "life is short, use python"
  • 7
    Python has great libraries for data processing
  • 6
    Although practicality beats purity
  • 6
    Now is better than never
  • 6
    Great for tooling
  • 6
    Readability counts
  • 6
    Rapid Prototyping
  • 6
    I love snakes
  • 6
    Flat is better than nested
  • 6
    Fast coding and good for competitions
  • 6
    There should be one-- and preferably only one --obvious
  • 6
    High Documented language
  • 5
    Great for analytics
  • 5
    Lists, tuples, dictionaries
  • 4
    Easy to learn and use
  • 4
    Simple and easy to learn
  • 4
    Easy to setup and run smooth
  • 4
    Web scraping
  • 4
    CG industry needs
  • 4
    Socially engaged community
  • 4
    Complex is better than complicated
  • 4
    Multiple Inheritence
  • 4
    Beautiful is better than ugly
  • 4
    Plotting
  • 3
    Many types of collections
  • 3
    Flexible and easy
  • 3
    It is Very easy , simple and will you be love programmi
  • 3
    If the implementation is hard to explain, it's a bad id
  • 3
    Special cases aren't special enough to break the rules
  • 3
    Pip install everything
  • 3
    List comprehensions
  • 3
    No cruft
  • 3
    Generators
  • 3
    Import this
  • 3
    If the implementation is easy to explain, it may be a g
  • 2
    Can understand easily who are new to programming
  • 2
    Batteries included
  • 2
    Securit
  • 2
    Good for hacking
  • 2
    Better outcome
  • 2
    Only one way to do it
  • 2
    Because of Netflix
  • 2
    A-to-Z
  • 2
    Should START with this but not STICK with This
  • 2
    Powerful language for AI
  • 1
    Automation friendly
  • 1
    Sexy af
  • 1
    Slow
  • 1
    Procedural programming
  • 0
    Ni
  • 0
    Powerful
  • 0
    Keep it simple
  • 259
    Ios
  • 180
    Elegant
  • 126
    Not Objective-C
  • 107
    Backed by apple
  • 93
    Type inference
  • 61
    Generics
  • 54
    Playgrounds
  • 49
    Semicolon free
  • 38
    OSX
  • 36
    Tuples offer compound variables
  • 24
    Clean Syntax
  • 24
    Easy to learn
  • 22
    Open Source
  • 21
    Beautiful Code
  • 20
    Functional
  • 12
    Dynamic
  • 12
    Linux
  • 11
    Protocol-oriented programming
  • 10
    Promotes safe, readable code
  • 9
    No S-l-o-w JVM
  • 8
    Explicit optionals
  • 7
    Storyboard designer
  • 6
    Optionals
  • 6
    Type safety
  • 5
    Super addicting language, great people, open, elegant
  • 5
    Best UI concept
  • 4
    Its friendly
  • 4
    Highly Readable codes
  • 4
    Fail-safe
  • 4
    Powerful
  • 4
    Faster and looks better
  • 4
    Swift is faster than Objective-C
  • 4
    Feels like a better C++
  • 3
    Easy to learn and work
  • 3
    Much more fun
  • 3
    Protocol extensions
  • 3
    Native
  • 3
    Its fun and damn fast
  • 3
    Strong Type safety
  • 3
    Easy to Maintain
  • 2
    Protocol as type
  • 2
    All Cons C# and Java Swift Already has
  • 2
    Esay
  • 2
    MacOS
  • 2
    Type Safe
  • 2
    Protocol oriented programming
  • 1
    Can interface with C easily
  • 1
    Actually don't have to own a mac
  • 1
    Free from Memory Leak
  • 1
    Swift is easier to understand for non-iOS developers.
  • 1
    Numbers with underbar
  • 1
    Optional chain
  • 1
    Great for Multi-Threaded Programming
  • 1
    Runs Python 8 times faster
  • 1
    Objec

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Cons of Python
Cons of Swift
  • 53
    Still divided between python 2 and python 3
  • 28
    Performance impact
  • 26
    Poor syntax for anonymous functions
  • 22
    GIL
  • 19
    Package management is a mess
  • 14
    Too imperative-oriented
  • 12
    Hard to understand
  • 12
    Dynamic typing
  • 12
    Very slow
  • 8
    Indentations matter a lot
  • 8
    Not everything is expression
  • 7
    Incredibly slow
  • 7
    Explicit self parameter in methods
  • 6
    Requires C functions for dynamic modules
  • 6
    Poor DSL capabilities
  • 6
    No anonymous functions
  • 5
    Fake object-oriented programming
  • 5
    Threading
  • 5
    The "lisp style" whitespaces
  • 5
    Official documentation is unclear.
  • 5
    Hard to obfuscate
  • 5
    Circular import
  • 4
    Lack of Syntax Sugar leads to "the pyramid of doom"
  • 4
    The benevolent-dictator-for-life quit
  • 4
    Not suitable for autocomplete
  • 2
    Meta classes
  • 1
    Training wheels (forced indentation)
  • 6
    Must own a mac
  • 2
    Memory leaks are not uncommon
  • 1
    Very irritatingly picky about things that’s
  • 1
    Complicated process for exporting modules
  • 1
    Its classes compile to roughly 300 lines of assembly
  • 1
    Is a lot more effort than lua to make simple functions
  • 0
    Overly complex options makes it easy to create bad code

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What is 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.

What is Swift?

Writing code is interactive and fun, the syntax is concise yet expressive, and apps run lightning-fast. Swift is ready for your next iOS and OS X project — or for addition into your current app — because Swift code works side-by-side with Objective-C.

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What are some alternatives to Python and Swift?
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!
R Language
R provides a wide variety of statistical (linear and nonlinear modelling, classical statistical tests, time-series analysis, classification, clustering, ...) and graphical techniques, and is highly extensible.
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.
Scala
Scala is an acronym for “Scalable Language”. This means that Scala grows with you. You can play with it by typing one-line expressions and observing the results. But you can also rely on it for large mission critical systems, as many companies, including Twitter, LinkedIn, or Intel do. To some, Scala feels like a scripting language. Its syntax is concise and low ceremony; its types get out of the way because the compiler can infer them.
Anaconda
A free and open-source distribution of the Python and R programming languages for scientific computing, that aims to simplify package management and deployment. Package versions are managed by the package management system conda.
See all alternatives