I’m still quite fond of my current Hexo theme. From using its predecessor material-x in 2021 to upgrading to Volantis 5.x in 2023, the theme’s functionality has completely met my personal needs, to the point where I haven’t upgraded to the author’s subsequent versions 6 and 7. However, after using AI to batch-translate my blog content into English earlier this year, there have been persistent issues with some interface elements remaining in Chinese. This year, instead of undertaking major renovations, I decided to fix these minor bugs myself under AI guidance.

DevPod is an open-source development environment management tool that allows you to create development environments similar to GitHub Codespaces on any Kubernetes cluster or Docker host. This article will introduce how to use the DevPod CLI to create workspaces and provide a detailed explanation of writing DevContainer configuration files.

As my classmate said, I’m currently experiencing a situation of “being forced to code”… The several websites I maintain each have their own frontend, backend databases, and some even have test code and migration code, involving languages ranging from Python commonly used in bioinformatics to JS, TS, HTML, C#, which I rarely used before. In actual work, there isn’t much time to systematically learn each language from scratch, so mastering the most basic debugging methods is crucial. Among them, I find the debugging methods for JavaScript and TypeScript particularly worth recording, as they do have some unique aspects compared to other languages.

Uptime Kuma is an extremely user-friendly open-source monitoring tool that makes monitoring various network services simple and efficient. It supports multiple protocol monitoring including HTTP(s), TCP, Ping, DNS queries, and even simulates real user access through Chrome engine mode to more accurately monitor service stability. Additionally, it supports dozens of notification methods for alerts and can integrate with various applications we use daily. It also offers a unique Push monitoring method, allowing users to extend monitoring functionality through custom code (such as monitoring SSH service availability).

There are really many modules for rapidly developing data or AI-related applications in Python. I’ve already used Dash, Streamlit, Gradio, NiceGUI, and recently I discovered two more. Just when I needed to develop a simple data dashboard to display company data, I once again recklessly decided to use a new framework - Taipy.

Picking up from where we left off, after successfully compiling the code in the libapp project, the next steps are: modifying the libapp code and applying the changes to the image.

I’ve been using FydeOS/ChromeOS for about two years now. While the system provides a usable terminal app, it’s honestly not that great. For example, during development, I often need to forward multiple ports. Although I can achieve this by entering SSH commands for port forwarding, this requires manually inputting quite a few parameters. Additionally, during port forwarding, I need to keep the SSH login window open. For someone like me who’s particularly obsessive about minimizing the number of open windows, keeping three or four windows open that won’t be used in the foreground is really uncomfortable… So I thought, can I do it myself, with the help of AI, modify the system’s default terminal client, and add quick forwarding functionality like VSCode has?

This year, DeepSeek has made LLMs popular again. Although after ChatGPT, Copilot and Cursor have been advertising everywhere, I never actually tried them… So this year, I… tried Cline, which is indeed good, but also matches my preconception - not that convenient. Especially since I need something that can be used directly in the command line and quickly integrated into scripts to batch complete some simple coding initialization tasks. That’s how I found aider…

Object-oriented programming is a common paradigm in programming. In my actual work, using object-oriented programming mainly serves two purposes: reducing duplicate code through inheritance features, and encapsulating frequently used data into objects to avoid excessive, repetitive, and nested parameter passing.

After getting used to Python, developing scripts in R can feel quite painful. Putting aside the often-discussed issues with unclear error tracing, when scripts become slightly more complex and need to be split into multiple files, I realized R’s import mechanism is also quite frustrating… Fortunately, there’s the box package that allows module imports similar to Python’s logic.