So we’re looking at updating one of our apps here for iOS 11 and joining the move to subscriptions which it appears is the only reasonable path to sustaining a productivity app on the horizon, so we’re seeing what’s new in receipt validation to support that, as last time we checked into it was four years ago and all and RMStore we picked then has languished since.

Let’s look around a bit … hmmm … hmmm … oh, what’s this? A comprehensive series walking through the whole process, updated for Swift 3? Well, bit late to the party, but looks like it’s all still relevant, and receipt validation code is something we really ought to write ourselves:

Preparing to Test Receipt Validation for iOS

After having to piece together each step along the path of preparing to test receipt validation for iOS apps, I’ve decided to combine everything into the following guide. Whether you’re working to implement receipt validation for a new iOS app, or for an existing one, this walk-through should provide guidance to get you ready to work with receipts in your iOS application…

Loading a Receipt for Validation with Swift

There are at least 5 steps to validate a receipt, as the Receipt Validation Programming Guide outlines…

Extracting a PKCS7 Container for Receipt Validation with Swift

Before attempting to work with OpenSSL’s PKCS7 functions, you’ve got to do a little prep work to get the functions to play nicely with Swift. Unfortunately, Swift doesn’t work well with C union types. It simply can’t see things defined with a C union…

Receipt Validation – Verifying a Receipt Signature in Swift

The aim of this guide is to help you take a look inside the PKCS #7 container, and verify the presence and authenticity of the signature on the receipt…

Receipt Validation – Parse and Decode a Receipt with Swift

The aim of this guide is to help you parse a receipt and decode it so that you have readable pieces of metadata to inspect and finalize all of the receipt validation steps…

Finalizing Receipt Validation in Swift – Computing a GUID Hash

After finishing this guide, you’ll simply need to use the parsed receipt data to perform any app-specific enabling/disabling of features based on the data within a valid receipt. If the receipt is invalid, you’ll need to handle that as well. But all of the relatively difficult work of working with the Open SSL crypto library will be DONE after this guide….

… The bottom line is that from this point on, you no longer need Open SSL or any additional cryptic, low-level, unsafe pointer-type stuff to finish things out. I hope this series has been helpful in setting you up to validate receipts locally on a user’s device!

That … is a veritably monumental guide to the validation process. And conveniently finished up right when we need it too, thanks ever so much @andrewcbancroft!

UPDATE:

We just beat by a day Messr. Bancroft pulling together his own collection guide, now that you’ve read ours go to the real thing!

Local Receipt Validation for iOS in Swift From Start to Finish

and code at SwiftyLocalReceiptValidator!

The choice of database technology for our apps has been something of a question for us the last while, where by “last while” we mean since iCloud Core Data was deprecated, which miffed us no end since we’d rather like our apps’ initial releases to Just Work™ across devices for iOS users without jumping through any great hoops or introducing any dependencies on non-Apple services.

So let’s see what’s new in Core Data this year in the iOS 11 release notes! Errr… nothing?

Hmmm. Let’s check out the What’s New In Core Data WWDC 2017 session…

… kinda thin, don’t you think?

Hmmm, hmmm. Sorta looking like it’s time to seriously evaluate other alternatives, it is.

We liked the looks of RocketData, very Swifty and all, but it … appears to be languishing.

Soooooo, what to do? Well, here is an article that presents an alternative of interest:

Ditching Core Data

I have been using Core Data since iOS 3.0. With few exceptions, it has served entirely as a network cache. Take data from a network response, turn it into a set of objects, save those objects, and update the user interface. Rinse and repeat.

The stack is pretty simple. A set of nested contexts to keep object building off of the main thread, a couple of models that have init(dictionary: NSDictionary), and some find-or-create helpers can get you a long way. The problem is that the apparent simplicity comes with an incredible amount of baggage. Instability, buggy classes, and outdated APIs make building modern apps difficult.

As a community, we have tried to solve these problems by building wrappers around Core Data. These wrappers add their own issues and none of them hide the fact that Core Data was simply not meant to be used like this…

Nodding along here? Yep, us too.

After some research and planning, I landed on a set of features that I wanted in a persistence framework. The list is pretty short:

• My objects must be plain objects. Requiring model objects to extend a certain base class is painful; especially when you cannot see the source for those classes. I want to know that I can create objects however I like, use them wherever I like, and build my own functionality around them without worrying about what sandbox they belong to.
• I should not have to worry about concurrency. Tools like closures, Grand Central Dispatch, and NSOperationQueue make it easy to write code that spans many threads. Unpacking objects on background threads that are later used to update interface elements is a common operation that should be simple and easy to reason about.
• I should not have to write migration code. Frameworks and libraries can and should be smarter than this. Let me describe how I want the database to look. You take care of the rest.
• I should be able to track and respond to atomic changes. Elements in my application should be able to reload themselves if a single object, or a collection of objects changes. Otherwise it may spend too much time updating things that may not need to be updated, which could have a negative impact on the user experience.

Sounds good. Only thing we’d add as a base requirement is “CloudKit sync” to make the cross-device experience seamless.

And the winner was:

I decided to use YapDatabase. It came highly recommended and it offers support for all of my requirements. YapDatabase is, at its core, a key-value store build on top of SQLite. It has a simple API and is incredibly flexible…

You will notice a few things about my model objects right away: they are completely immutable, they have no knowledge of the persistent store, and no magic superclass. These objects can be passed around the application (and across thread boundaries) without requiring knowledge of the database or how these objects are to be handled…

All database operations in YapDatabase are handled through database connections. YapDatabaseConnection has functions for reading from, writing to, and responding to individual changes in the database. It does all of this in a thread safe manner. One less thing to worry about!

OK, flipping down the feature list there, looks like a solid solution to entry level needs, got a track record and is being easily maintained, just that one little extra base requirement…

• Sync. Support for syncing with Apple’s CloudKit is available out of the box. There’s even a fully functioning example project that demonstrates writing a syncing Todo app.

… well, there we go then. Unless some dramatically superior alternative comes to our attention, next data-storing app we ship will use YapDatabase too, farewell Core Data!

Been enough of a while since WWDC ’17 for people to sort out what they find interesting about iOS 11 and all now, so let’s take a look shall we?

The canonical references up at the mothership are

• macOS 10.13 and iOS 11 Release Notes Cocoa Foundation Framework
• iOS 10.3 to 11.0 API Differences
• What’s New in iOS 11.0
• What’s New in macOS 10.13 and AppKit
• What’s New in watchOS 4.0
• What’s New in tvOS 11.0
• What’s New in Safari 11.0

A good TL;DR while you bookmark this for later is What’s new in iOS 11 for developers

iOS 11 By Examples has, surprise, examples of using new iOS 11 APIs:

• Core ML: Image classification demo using Core ML framework
• Vision: Face detection, landmarks, and object tracking
• ARKit: Augmented reality experiences in your app or game
• Core NFC: Reading of NFC tag payloads.
• IdentityLookup: SMS and MMS filtering using IdentityLookup framework
• DeviceCheck: Identifying devices that have used a promo, flagging fraudsters
• Blogs/Newsletter: Other places that mentioned this list — probably mention more good stuff too!

Personally we’d already been planning to try out iPad-only travel soon, and iOS 11 + new iPad Pro looks like MASSIVE WIN on both fronts — seriously, did anybody at all predict the super duper ProMotion screen? — and the mutitasking stuff is a good bit better than we’d expected, and easy to use, see:

• Implementing Apple’s Drag and Drop
• SplitViewDragAndDrop: “Easily add drag and drop to pass data between your apps in split view mode”

CoreNFC is one of those what took you so long things, but hey better late than never: CoreNFC tutorial

Now that Metal is even more metal to support 120 fps displays and all, they’re Introducing Metal 2

If you do anything with file names in iOS or macOS, make sure you read APFS Native Normalization

One thing worthy of noting as removing what we’d found the major annoyance with UIStackView and likely you too: Stack View Custom Spacing

Also top and layout guides are simplified to Safe Area Layout Guide

Some more little bites, to coin a phrase, at #309: UIFontMetrics and #310: Screen Edges in iOS 11 and #311: Round Corner Improvements

Now, to step back from the API level, some people are very excited about this Business Chat thing:

… I believe that Apple Pay Cash, and the ability to send low transaction amounts with no cost to the sender or the receiver (the business) will be one of the most transformative elements to the impact of Business Chat. This can bring rise to a number of new businesses and applications that may be similar to the “gig economy” of Fivver and other systems…

Business Chat can not only spell the end of the POS system and payment systems as we know it in retail sales, it may also spell the end of the shopping carts and payment systems in online sales. Some may argue this is bombastic…

Yes, maybe a touch. Doesn’t mean it’s wrong though; read the whole thing, and the Business Chat info at the mothership, and see what you think —or read this one that figures it’s not just shopping carts in the crosshairs: Apple Bank here we come

Last one we’ll call out here — some good thoughts on the new evolutions of the interface design language: Think Bigger: Design Changes in iOS 11

Need more? Check out your veritably canonical reference to everything new over at New stuff from WWDC 2017!

UPDATES:

Changes to location tracking in iOS 11; Location Permissions in iOS 11 and avoiding the Blue Bar of Shame

iOS 11, Privacy and Single Sign On

What’s New In UIKit Animations In Swift 4

The other obviously transformational technology introduced at WWDC this year was Apple’s sudden leap from

One thing is clear: Apple needs to get moving soon.

to, a mere 5 days later — how’s that for “soon?” —

If Apple gets this right, they will own the hardware market for years to come.

and what we’re sure must be by far the quickest ever adoption of an Apple-only technology outside the computer industry,

Ikea’s plans for ARKit revealed, virtual shopping tool will launch in fall with iOS 11

so let’s start collecting links on that shall we?

Introducing ARKit

With ARKit, iPhone and iPad can analyze the scene presented by the camera view and find horizontal planes in the room. ARKit can detect horizontal planes like tables and floors, and can track and place objects on smaller feature points as well. ARKit also makes use of the camera sensor to estimate the total amount of light available in a scene and applies the correct amount of lighting to virtual objects…

… yeah ok that’s pretty cool.

There’s already signup open for ARKit Weekly to keep abreast of news here, and the same obviously extra-keen folk have also started

Made With ARKit: Hand-picked curation of the coolest stuff made with #ARKit

That’s some pretty darn nifty videos there for, like two weeks at this!

To grab some source code examples and interesting commentary, check out

Apple ARKit by Example

1. Getting setup, draw a cube in virtual reality
2. Plane Detection and Visualization
3.  Adding geometry and physics fun
4. Physically Based Rendering

ARShooter – An Example Shooter Created Using iOS 11’s ARKit

ViewAR does first tests with ARKit

3 Things To Know About Apple’s ARKit

Apple’s new augmented reality platform may be its next game-changer

Pretty cool huh? It’s like the future’s so bright we have to wear shades … except the whole point of Apple AR (so far…) is that we don’t!

UPDATES:

ARBrush: “Quick demo of 3d drawing in ARKit using metal + SceneKit.”

ARKit Tutorial in Swift 4 for Xcode 9 using SceneKit

Watch a Tesla Model 3 come to life

ARTetris: “Augmented Reality Tetris made with ARKit and SceneKit”

Getting Started with ARKit: Waypoints

ARKit introduction

Wenderlich Introduction to ARKit:

1. Getting Started
2. Adding 3D Models
3. Measuring Distances

I’m presenting the ARKit workshop at RWDevCon 2018!

ARKit-CoreLocation: “Combines the high accuracy of AR with the scale of GPS data.”

Inside iOS 11: The coolest Apple ARKit demos created so far

Using ARKit with Metal

ARKit-CoreLocation: “Combines the high accuracy of AR with the scale of GPS data.”

ARKit and Autism: New Futures

Adventures in ARKit (with magic)

ARPaint: “Draw with bare fingers in the air using ARKit.”

ARKit for iOS Developers

Why Apple’s glasses won’t include ARKit

Checked out the WW17 Roundup yet? OK then, let’s start digging into this new stuff a little deeper. And we’ll start with the one with the most buzz around the web,

Introducing Core ML

Machine learning opens up opportunities for creating new and engaging experiences. Core ML is a new framework which you can use to easily integrate machine learning models into your app. See how Xcode and Core ML can help you make your app more intelligent with just a few lines of code.

Vision Framework: Building on Core ML

Vision is a new, powerful, and easy-to-use framework that provides solutions to computer vision challenges through a consistent interface. Understand how to use the Vision API to detect faces, compute facial landmarks, track objects, and more. Learn how to take things even further by providing custom machine learning models for Vision tasks using CoreML.

By “more intelligent” what do we mean exactly here? Why, check out

iOS 11: Machine Learning for everyone

The API is pretty simple. The only things you can do are:

1. loading a trained model
2. making predictions
3. profit!!!

This may sound limited but in practice loading a model and making predictions is usually all you’d want to do in your app anyway…

Yep, probably. Some people are very excited about that approach:

Apple Introduces Core ML

When was the last time you opened up a PDF file and edited the design of the document directly?

You don’t.

PDF is not about making a document. PDF is about being able to easily view a document.

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…

Well, speaking as that Average Developer here, yep this sure sounds like a great way to dip a toe into $CURRENT_BUZZWORD without, y’know, having to actually work at it. Great stuff!

Here’s some more reactions worth reading:

• Welcoming Core ML
• Machine Learning in iOS Using Core ML
• Apple’s CoreML a Big Step for Machine Learning
• Apple just leveled up the iPhone’s machine learning chops
• Apple’s Core ML: The pros and cons
• Swift World: What’s new in iOS 11 — CoreML and  Vision
• Apple just offered a ‘dead giveaway’ that it’s building an AI chip for iPhones, expert says

Here’s some models to try it out with, or you can convert your own built with XGBoost, Caffe, LibSVM, scikit-learn, and Keras :

• Places205-GoogLeNet CoreML (Detects the scene of an image from 205 categories such as an airport terminal, bedroom, forest, coast, and more.)
• ResNet50 CoreML (Detects the dominant objects present in an image from a set of 1000 categories such as trees, animals, food, vehicles, people, and more.)
• Inception v3 CoreML (Detects the dominant objects present in an image from a set of 1000 categories such as trees, animals, food, vehicles, people, and more.)
• VGG16 CoreML (Detects the dominant objects present in an image from a set of 1000 categories such as trees, animals, food, vehicles, people, and more.)

And some samples and tutorials:

• Core ML and Vision: Machine Learning in iOS 11 Tutorial
• Introduction to Core ML: Building a Simple Image Recognition App
• Tutorial: Using iOS 11’s Vision Framework For Object Detection On A Live Video Feed
• MobileNet-CoreML: “The MobileNet neural network using Apple’s new CoreML framework”
• CoreMLExample: “An example of CoreML using a pre-trained VGG16 model”
• UnsplashExplorer-CoreML: “Core ML demo app with Unsplash API”
• Bender: “Easily craft fast Neural Networks on iOS! Use TensorFlow models. Metal under the hood.”

Also note NSLinguisticTagger that’s part of the new ML family here too.

For further updates we miss, check out awesome-core-ml and Machine Learning for iOS !

UPDATES:

YOLO: Core ML versus MPSNNGraph

Why Core ML will not work for your app (most likely)

Blog: Getting Started with Vision

MLCamera – Vision & Core ML with AVCaptureSession Inceptionv3 model

Can Core ML in iOS Really Do Hot Dog Detection Without Server-side Processing?

Bringing Machine Learning to your iOS Apps 🤖📲

Creating A Simple Game With CoreML In Swift 4

Custom classifiers in iOS11 using CoreML and Vision

Using Vision Framework for Text Detection in iOS 11

That was a particularly good WWDC this year wasn’t it? Lots of possibly transformational technologies introduced it’s going to be very interesting indeed to see how they play out!

We’ll explore those in more depth later on, but for now let’s sort out some resource links and initial reactions.

First up, you want to go download The Unofficial WWDC app for macOS:

Isn’t that pretty? Definitely your WWDC video viewing app of choice, we say!

Next, address this problem

with the WWDC-Downloader script over at Github.

(And while that’s all downloading for your next transcontinental plane flight or whatever, have your heart warmed with

WWDC17 Scholarship winner Kenny Batista shared his experiences at Apple’s big week for developers !)

If you want to prioritize a bit, here’s a WWDC 2017 Viewing Guide that looks solid.

There’s enough interesting new technologies that they deserve roundup posts each as there’s going to be a lot of figuring out there to keep track of, so for now we’ll just link a couple overviews hitting the highest points:

The 2017 Apple Design Award Winners

WWDC 2017 Initial Impressions from the Wenderlich team

Another take from the Big Nerd Ranch crew at WWDC 2017: Helping You Get Things Done

Also check out their article New HEVC & HEIF Media Formats: What You Need to Know and Begun, The Codec War Has for background on the fur that’s no doubt going to be flying all over about that soon.

Oh, and we’ll put An In Depth Look At the New App Store and New rules following WWDC 2017 here too — there’s some interesting changes there you want to be aware of. Most notably to us, that finally The new iOS App Store lets devs choose whether or not to reset ratings when updating!! Woo-woo-woohoo!

And as always, over at mjtsai.com you can find a near-canonical list of WWDC 2017 Links for deeper diving!

UPDATES:

HEIF: A First Nail in JPEG’s Coffin?