I am a Taiwanese. Please call me Daniel. I am a person who desires to meet new things, challenges and new ideas. I have experience in front-end development in the industry and a self-taught full-stack developer (study back-end and dev-ops).

My goal is that I can build anything as I want and becoming a software architect in this industry. After I have been worked for two years, I realized that I have to work on my own project first so that I could have more time to cover more comprehensive knowledge. In order to achieve this goal, I quit my job and study online to enhance my knowledge by studying algorithm and system design. In practice level, I strongly believe to build an enterprise level product from scratch is the best way and the only way to go.

Building a US stock screener based on the financial statement from www.sec.gov. This project means a lot for me. I can boost my career through this work in terms of technical knowledge and project management. See "Project: Full-stack: Lazy-stock-screener-demo" section for more details.

Front End
➢ webpack/babel
➢ React Ecosystem: React Hooks/React Router/Redux/React SSR/dynamic import/React in Typescript
➢ API: Axios/Apollo-client/GraphQL
➢ CSS/SCSS/Style Component/Materical UI
➢ MVP pattern

Server
➢ Golang Ecosystem: Fasthttp
➢ Node.js Ecosystem: Express.js in Typescript/Chi+Mocha/Sequelize/Mongoose
➢ Python Ecosystem: Pandas
➢ System Design Pattern: DDD/Clean Architecture
➢ DB/Cache: PostgreSQL/MongoDB/Redis

Dev-Ops
➢ Container: Docker/Docker-Compose
➢ Reverse-Proxy: Traefik

A US stock screener based on the financial statement from www.sec.gov. Design a system from use-case/user story to CI/CD. It leverages all the ideas or principles listed in the following: highly decoupled components, event-driven design, and SOLID principles. A MVP pattern is in front-end with React Hooks; Using Clean Architecture and DDD best practices with Golang in the back-end; Data pipeline is built on top of Python with various design patterns. Everything is containerized with Docker and managed by Kubernetes, while Gitlab CI/CD helped me to deploy this project to the GKE. The main project is privated and on gitlab, therefore, only part of this project are demonstrated on github origanization.

An internal SPA for the purpose of setting and reading prices in terms of each product in the online shop. The tech stack is MERN (react-redux, node, express, mongoDB) with Docker/Kubernetes and system structure is based on microservice architecture. The details tech-stack are Webpack/SPA/Google OAuth2/Node/Mocha/Apollo Server/MongoDB/Redis/Nginx/Docker/K8S/TravisCI/Terraform.

• A python version financial report dumper with Pandas/Google Sheet API/
• I also implement various design pattern like:
  • TableAbstractFactory
  • ScoreTableStrategy
  • BuyDecisionStrategy
  • InputPipeLine
  • APIMediator
  • OutputObserver
  • Chain of Responsibility/Builder