Z's Blog

During the New Year’s holiday, my iPhone 12 dropped and caused some malfunctions, making it barely usable. However, recently the battery also swelled and it easily shut down automatically, rendering it completely unusable. After switching to a backup phone, it was set aside for a while.

I recently thought of it again, as it could still power on normally and most of its main functions could still operate, so I speculated that it was only partially faulty and not completely damaged. It would be a pity to completely scrap it, and it seems I can only swap it for a stainless steel basin.

I took it apart to analyze the cause of the faults and attempted to buy parts for repair. This article documents the disassembly and resolution process.

This year, I plan to celebrate the Spring Festival in Shenzhen and the next stop for my Greater Bay Area trip is Macau. Traveling from Shenzhen to Macau is relatively convenient, so I am making arrangements for the trip. I’ve done some research and itinerary planning that can serve as a reference for those visiting Macau for the first time.

In the previous article Design and Implementation of Resource Self-Correction in UE, I introduced the implementation plan of filtering using the asset inspection of ResScannerUE, followed by automated processing.

Normally, if you want to check a certain property within a resource, you need to load the asset and retrieve the object:

However, if you want to check the properties of many resources in bulk, loading resources one by one in this way takes a long time, especially in the absence of DDC, where loading resources triggers the construction of DDC cache, which is time-consuming and has a high performance overhead.

As the size of the assets increases, scanning all resources in a project completely can be extraordinarily time-consuming. Therefore, I wonder if it’s possible to implement a method that does not require loading resources but can still retrieve properties within resources.

After research, I found a clever way to achieve this by combining reflection, asset serialization, and the features of AssetRegistry. Moreover, this is a non-intrusive approach that does not require modifying any existing resource type code.

This article will introduce the implementation principles and analyze the related logic in the engine, as well as present the practical application of this mechanism in the project.

In a previous article, I introduced the implementation and efficiency optimization of multi-stage and automated resource checks using ResScannerUE in UE.

• Multistage Automated Resource Check Solutions in UE
• Automated Resource Check Practices Based on ResScannerUE
• Resource Compliance Check Tool ResScannerUE in UE

This already allows for very flexible configuration of resource checks and timely alerts, with very powerful rule expression capabilities. However, they are still limited to the stage of discovering problems for reminders; although there are constraints to prevent submission, manual processing is still required. Especially in cases with a large amount of existing resources, the manpower involved in manual processing is very time-consuming.

Based on this situation, I designed a mechanism for automating resource corrections that can automatically fix resources after rules are established, ensuring that all scanned resources are set to the correct state.

This completes the final piece of the puzzle in my resource check solution and can be applied throughout the scanning process as needed. This article will introduce its design concept and implementation mechanism, as well as some practical application scenarios in projects.

If I had to choose one recent experience in working with UE that felt the most meaningless and torturous, it would definitely be trying to find a resource in the ContentBrowser based on a long string path.

The inability to quickly jump directly to a directory or resource makes me feel like I’m wasting my life every time I have to navigate deeply nested folders one step at a time.

To address this pain point, I wrote a small tool that significantly alleviates this manual anxiety. I named it j2 (jump to), which is a minimalist ContentBrowser jump tool, open-source on GitHub: hxhb/JumpTo.

This article will introduce the usage of this project, the thought process behind conceptualizing the solution, and the step-by-step code implementation. Although the functionality itself is a very simple plugin, the discovery, analysis, and solution process for the actual pain points is worth documenting.

In 2020, I wrote an article How to Build Your Own Knowledge System?, which mainly reflects on the daily accumulation of technology, leaning towards methodology.

This article will explore the possibilities of personal knowledge management from the perspective of tools and practical use, based on Obsidian, and attempt to integrate it with the Hexo blog. Of course, this preference for tools and practices has a strong subjectivity; this article is entirely based on my personal practice and experience; there is no best tool, only the one that suits you best.

Shenzhen and Hong Kong are separated by just a river. Although I had long planned to visit Hong Kong, I was unable to do so for the past two to three years due to the pandemic. Now that the pandemic restrictions have eased this year, passing between Hong Kong and the mainland has also become relatively convenient, so I’ve included a trip to Hong Kong in my schedule.

I went to Hong Kong for a weekend trip with my wife. Before we went, I made some travel plans and arrangements that can serve as a reference for first-time travelers to Hong Kong.

Remote building is a very convenient way to package iOS in UE, allowing code compilation only on a Mac without COOKing resources, which greatly reduces the hardware requirements for Mac.

Moreover, Macs are quite expensive. In a traditional setup, if multiple independent iOS package build processes are needed, it usually requires purchasing several separate Mac machines for deployment, leading to high hardware costs.

Additionally, the iOS development environment often needs to be updated with iOS system iterations. Every year at WWDC, a new version of iOS is released, requiring support from the latest XCode, which in turn depends on the latest MacOS—a nested chain of dependencies. If the number of Mac build environments increases, updating the build environments of these machines also becomes a cumbersome repetitive task.

Remote building for iOS can effectively solve this issue. A single independent Mac can simultaneously support multiple iOS build processes, and if an update is needed, it only needs to be handled on one machine. Furthermore, the time it takes to compile code is relatively fixed, and incremental compilation can be performed. In theory, as long as not all machines execute a full compilation at the same time, the performance pressure on the Mac won’t be that great.

There are also articles on enabling remote building for iOS in the blog: UE Development Notes: Mac/iOS Edition, which can be referred to for basic configuration.

However, the default implementation of iOS remote building in UE also presents several issues in actual use, failing to achieve a fully automated process from deployment to building. This article aims to optimize the pain points of remote building in real project applications.

To do a good job, one must first sharpen their tools! AIGC tools represented by ChatGPT and Stable Diffusion have emerged, and the AI wave is sweeping across various industries. As developers, how to leverage AI capabilities to improve efficiency in tasks is a question worth studying.

It is crucial to note that the content generated by GPT may not be entirely accurate and can contain inaccuracies. However, its potential lies in the possibility of achieving a general-purpose AI assistant. No one can possess expert-level knowledge in all fields, but effectively utilizing GPT in unfamiliar domains can significantly lower the entry costs.

In this article, I will introduce some cases of using GPT to assist in work, life, and learning, as well as explore application scenarios for secondary development using the GPT API. At the end of the article, I will share some Prompts I use and recommend some useful GPT tools, as well as a solution for encapsulating Azure OpenAI services using Cloudflare Worker.

DevOps is a philosophy based on automation for Continuous Integration (CI) and Continuous Deployment (CD), optimizing all aspects of development, testing, and operations. It emphasizes the integration of software development, testing, and operations, reducing communication costs between departments or processes to achieve rapid and high-quality releases and iterations.

Although the development situation in the gaming field differs significantly from traditional internet development, leveraging the concept of DevOps to integrate all production elements of a project into automation can greatly enhance efficiency.

This article will introduce the basic concepts of automation in UE and share some of my attempts and actual engineering practices regarding automation builds in Unreal Engine.