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WAGBI
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WAGBI
68 followers · 139 following

Achievements

Achievement: Pair ExtraordinaireAchievement: Pull Sharkx2Achievement: YOLOAchievement: Quickdraw

Achievements

Achievement: Pair ExtraordinaireAchievement: Pull Sharkx2Achievement: YOLOAchievement: Quickdraw

Highlights

Organizations

@ucsal @Codee-Hub

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yan-pi/README.md

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: 04 October 2025

Total Time: 2,686 hrs 11 mins

TypeScript                 1,520 hrs 26 mins⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣷⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀   55.56 %
Markdown                   303 hrs 28 mins ⣿⣿⣷⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀   11.09 %
Bash                       121 hrs 16 mins ⣿⣄⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀   04.43 %
JavaScript                 87 hrs 54 mins  ⣷⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀   03.21 %
Lua                        73 hrs 19 mins  ⣶⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀   02.68 %
Other                      50 hrs 19 mins  ⣦⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀   01.84 %

Pinned Loading

  1. zmk-config-lilytyper zmk-config-lilytyper Public

    my lily58 firmware

  2. nvim nvim Public

    my nvim config

    Lua 4

  3. portifolio portifolio Public

    TypeScript

  4. 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

  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 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