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WAGMI
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WAGMI
59 followers · 128 following

Achievements

Achievement: Pair ExtraordinaireAchievement: Pull Sharkx2Achievement: YOLOAchievement: Quickdraw

Achievements

Achievement: Pair ExtraordinaireAchievement: Pull Sharkx2Achievement: YOLOAchievement: Quickdraw

Highlights

Organizations

@ucsal @fesflabs @Codee-Hub

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yan-pi/README.md

AHOY! :D

About me

I'm a Full Stack Developer passionate about studying various languages and technologies.

I'm particularly enthusiastic about BTC and WEB3. You can see a more detailed overview of my career path here.

For updates on what I'm currently working on, check out my Twitter.

My WakaTime Stats:

From: 29 February 2024 - To: 12 July 2025

Total Time: 2,267 hrs 25 mins

TypeScript                 1,318 hrs 25 mins⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣤⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀   57.04 %
Markdown                   253 hrs 13 mins ⣿⣿⣶⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀   10.96 %
Bash                       82 hrs 23 mins  ⣷⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀   03.56 %
JavaScript                 79 hrs 40 mins  ⣷⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀   03.45 %
Lua                        53 hrs 43 mins  ⣦⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀   02.32 %
Other                      44 hrs 8 mins   ⣦⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀   01.91 %

Pinned Loading

  1. nvim nvim Public

    my nvim config

    Lua 2

  2. zmk-config-lilytyper zmk-config-lilytyper Public

    my lily58 firmware

  3. go-opportunities-api go-opportunities-api Public

    This project provides a Go API to manage job openings, using the Gin framework for routing and GORM for database interaction.

    Go 1

  4. zettelkasten zettelkasten Public archive

    My Public Zettelkasten :D

    MDX 1

  5. parking-nest-microservices parking-nest-microservices Public

    This project demonstrates a microservices architecture using NestJS, Prisma, RabbitMQ, and SQLite. The application consists of several independent services that communicate through a message bus (R…

    TypeScript 1

  6. flower-species-classifier flower-species-classifier Public

    This project demonstrates a basic MLOps pipeline using Docker, Kubernetes, and Pyenv to manage Python environments. It includes a classification model trained with the Iris dataset.

    Python 4