Last year, when I joined my current company, I was tasked with preparing a teaching analysis environment for bioinformatics training. This opportunity introduced me to Pixi. Later, as my responsibilities shifted, I not only continued with bioinformatics analysis but also took on full‑stack maintenance work. The projects I handled spanned front‑end and back‑end, involving languages and frameworks beyond the data‑science staples R and Python. Pixi has still been able to serve as a cross‑language/stack development environment management tool (Conda offers an extremely rich resource pool, covering mainstream programming languages and common frameworks). Therefore, I’d like to summarize the practical Pixi features that have proven useful in my daily work.

I have experience with several rapid application development frameworks in python, all of which uniformly bind element actions to Python functions to trigger updates or changes. So I should be fairly experienced in this area. However, Taipy genuinely puzzles me———it occasionally throws errors for no apparent reason…

I’ve been wondering: Taipy seems to be actively maintained, and it appears to have quite a few users (judging by the number of issues raised). Yet its component library isn’t particularly rich, and even some basic features come with minor bugs (like the light/dark toggle button bug I discovered earlier). Then I accidentally came across the official tutorial on embedding third‑party content, and it suddenly clicked: even though its built‑in components are limited, you can always “stitch” in whatever you need!

As the number of projects I need to maintain keeps growing (3 official websites, 2 systems, and 1 mini‑program, all with separate front‑end/back‑end and independent databases), I’ve encountered many tasks that are trivial to do once but become chaotic when repeated many times across different contexts. I had already experimented with CI on GitHub, and this time I learned and practiced CD (Continuous Deployment).

In CI/CD workflows, dependency management is often a key factor determining build efficiency and reliability. Recently, I tried the setup-pixi GitHub Action in a static website deployment pipeline.

Ah, I didn’t expect that after so many years, Plotly still hits its limits with just a little use. Previously it couldn’t draw timeline charts, and this time I found that the customization of map markers is insufficient…

After using devpod for a short while, I realized that I still needed a tool that could automatically install VS Code on a remote host via SSH without relying on containers, and then forward the port back to my local machine. So I started using Copilot to help me understand devpod’s code…

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.