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Tutorial: Introduction to MVVM in Swift 3 With Code!

In recent times the MVC (model-view-controller) design pattern has lost its place as a de facto pattern ever since better architectural patterns have come to light.  MVC is now infamously called a Massive(or Messy)-View-Controller pattern, the reason for that is it’s very easy to pile up 1000+ lines of code inside a View controller. Even Apple is famous for shying away from following the MVC pattern in their sample code. MVVM (model-view-viewModel) is an architecture pattern that is an alternative to MVC which makes it easier to further isolate the UI specific responsibility of a ViewController to a View Model.

If you are new to MVVM and want to know more about how to implement one, then check out this great in-depth article by Erica Millado linked below.

Source: Dabbling with MVVM in Swift 3

How to open Deep Links, Notifications, and Shortcuts!

Deep Linking is becoming quite prevalent in apps these days and it’s important for developers to have an understanding of it. Deep linking consists of using a hyperlink that links to a specific piece of content within an app. The specific content could be a page, view, or a certain tab. You can deep link from another app or even from a website to your app. Check out this excellent article by Stan Ostrovskiy who explains the concept with some easy to understand sample code:

Source: iOS: How to open Deep Links, Notifications and Shortcuts

Developers Who Use Spaces: Make More Money Than Those Who Use Tabs!

It’s amusing to see someone take so much time & effort to conduct a survey of this kind; but what a conclusion! Interestingly, more people use spaces than tabs, which is hard to believe.

There were 28,657 survey respondents who provided an answer to tabs versus spaces and who considered themselves a professional developer (as opposed to a student or former programmer). Within this group, 40.7% use tabs and 41.8% use spaces (with 17.5% using both). Of them, 12,426 also provided their salary.

Analyzing the data leads us to an interesting conclusion. Coders who use spaces for indentation make more money than ones who use tabs, even if they have the same amount of experience.

Source: Developers Who Use Spaces Make More Money Than Those Who Use Tabs

Phased Releases: in iTunes Connect!

A nice new feature announced at WWDC this year was phased releases. This is the new ability to be able to gradually release your app update to users over a period of 7 days. This has long been the envy of iOS developers looking over at their Android developer colleagues. Phased releases don’t quite have the same flexibility as the Android staged-rollouts but it is certainly much better than releases to potentially millions of users simultaneously.

Source: Phased Releases in iTunes Connect

Easily lookup App Store trending keywords –! is an online tool that can help you quickly look up App Store search results just by typing a few letters of the keyboard. It’s an excellent tool to do research on the keywords like what keywords are trending in a particular country. You can also select your favorites from the list and copy them to your clipboard as a comma separated list or download them as a csv file. The website also provides great advice on how to pick the best app keywords.


Port: Your iOS App to macOS!

If you are an iOS developer and are thinking about developing apps for macOS but felt daunted, then its time to think again. Your iOS development skills will come to great use when you are developing apps for macOS and the best part is that you can reuse a significant amount of the code between the 2 platforms and only having to rewrite the portions that are platform-specific.

Check out the article linked below that takes you through the process in detail:

Source: Porting Your iOS App to macOS

Tutorial: Core Machine Learning for iOS Developers!

Machine learning is a technology that’s been there since 1950’s but it’s all the rage today. It’s being increasing adopted in many industries, not just at tech companies. Many people have heard about it, but only a few know what it is. Apple has made available a ton of great resources covering Cover ML including their in-depth documentation along with 2 WWDC sessions – Introducing Core MLCore ML in depth.

If you are looking for a starter tutorial to get you going with Core ML, then check out this article linked below.

Source: Core Machine Learning For iOS Developers – Towards Data Science – Medium

Xcode: Demystifying iOS Provisioning & Certificates!

If you have recently started developing apps for iOS then you must have found the topic of provisioning profiles & certificates the most confusing. It’s essential as a iOS developer, to know about these 2 important topics and understand why they are needed in development. If you don’t have the patience or time to read through the Apple Docs, then this article linked below is for you.

Source: Demystifying iOS Provisioning – Cary Bohon@Martian Craft

ARKit: Getting Started Building an AR App!

It’s been just a week since Apple introduced augmented reality with iOS 11 and developers around the world are pretty stoked with the possibilities. You can find a collection of great demos that developers have already created at this link. If you are also psyched with the creative possibilities of ARKit but don’t know how to begin, then check out the link below to learn how to create a simple ARKit application.

Source: ARKit 101: Get Started Building AR Apps

Quote: Core ML is the PDF equivalent for Machine Learning!

With Core ML, Apple has managed to achieve an equivalent of PDF for machine learning. With their .mlmodel format, the company is not venturing into the business of training models (at least not yet). Instead, they have rolled out a meticulously crafted red carpet for models that are already trained. It’s a carpet that deploys across their entire lineup of hardware.

As a business strategy, it’s shrewd. As a technical achievement, it’s stunning. It moves complex machine learning technology within reach of the average developer.

Source: Apple Introduces Core ML | Deep Dojo