fatbobman

This article will explore how to apply SwiftData’s way of thinking within Core Data, focusing on data modeling and concurrent programming.

Fatbobman's Swift Weekly #053 | Breaking the Annual Release Cycle: A New Dawn for Tech Innovation?

• UserDefaults + Observation
• SwiftUI Animation
• Using Binaries as Libraries
• Why I Stopped Building for visionOS
• Arrays vs Sets
• Dependency Injection in Swift
• AI-Generated Unit Tests

This article will explore how to efficiently and conveniently manage data in UserDefaults under the Observation framework and propose a complete and practical solution.

ObservableDefaults responds to changes in UserDefaults from any source, offering the precision of Observation while maintaining the flexibility of AppStorage in handling modifications.

Fatbobman's Swift Weekly #052 | Reflecting on the Original Aspiration: On the First Anniversary of the Weekly's Inception

• Dev Conversations
• VoiceOver and Voice Control
• Shared With You
• UIKit or SwiftUI
• SwiftUI Environment

Fatbobman's Swift Weekly #051 | Xcode Is Not Alone

• NSManagedObjectID and PersistentIdentifier
• Container in SwiftUI
• Reduce Local AI Model Size
• Blend modes
• Tips of NSFetchedResultsController
• Communication Patterns in SwiftUI
• Mesh Gradients

Core Data and SwiftData are powerful data management frameworks designed by Apple for developers, capable of efficiently handling complex object relationships, hence known as object graph management frameworks. In these two frameworks, NSManagedObjectID and PersistentIdentifier serve similar functions and are both extremely important. This article will delve into their features, usage methods, and important considerations.

Fatbobman's Swift Weekly #050 | Has Your App Been Defeated by the New System?

• Data Binning
• Style Text in Terminal
• Pass Binding in NavigationDestination
• SPM Snippets
• Realm Deprecation
• ContentMargins in SwiftUI
• NSAttributedString Changes

Data binning is a commonly used data processing technique that typically divides continuous numerical or temporal data into multiple intervals (which are mostly adjacent and non-overlapping). This method not only covers the entire data range but also provides clear demarcation for data points within each interval. By performing data binning, we can analyze, visualize, and statistically process complex datasets more effectively. This article will explore how to use the advanced APIs provided by Swift Charts to achieve precise and efficient data binning.

Fatbobman's Swift Weekly #049 | Innovation Comes in Many Forms

• Core Data Issue
• Observable vs ObservableObject
• SwiftData Expressions
• Obj-c to SwiftUI
• Swift Testing
• Memory Leak
• visionOS 2 PortalComponent

Fatbobman's Swift Weekly #048 | Apple Watch, The Sturdy Linchpin of the Apple Ecosystem

• Hover Effects
• AirDrop Conundrum
• LockedCameraCapture Framework
• iOS Performance
• visionOS in Medical
• Github Contribution Graph with Swift Charts

Fatbobman's Swift Weekly #047 | Societal Progress Through the Lens of Driver's License Medical Examinations

• TipKit
• Gucci App on VisionPro
• App Size
• Darwin Notifications
• Custom Symbols in Control Center Widgets
• init of View
• UDP in SwiftNIO

Fatbobman's Swift Weekly #046 | Warning-Free Compilation is Not the Ultimate Goal of Swift 6

• EditorConfig in Xcode
• SwiftUI for Mac 2024
• Guide to Xcode Cloud
• Swift and WebAssembly
• From Highlighting to AI
• _ConditionalContent in List SubView