FastAPI on Jaehyeon Kim

Guide to Building Integrated Web Applications with FastAPI and NiceGUI

Wed, 19 Nov 2025 00:00:00 +0000

The standard architecture for modern web applications involves a decoupled frontend, typically built with a JavaScript framework, and a backend API. This pattern is powerful but introduces complexity in managing two separate codebases, development environments, and the API contract between them.

This article explores an alternative approach: an integrated architecture where the backend API and the frontend UI are served from a single, cohesive Python application.

Realtime Dashboard with FastAPI, Streamlit and Next.js - Part 1 Data Producer

Tue, 18 Feb 2025 00:00:00 +0000

In this series, we develop real-time monitoring dashboard applications. A data generating app is created with Python, and it ingests the theLook eCommerce data continuously into a PostgreSQL database. A WebSocket server, built by FastAPI, periodically queries the data to serve its clients. The monitoring dashboards will be developed using Streamlit and Next.js, with Apache ECharts for visualization. In this post, we walk through the data generation app and backend API, while the monitoring dashboards will be discussed in later posts.

Dynamic Routing and Centralized Auth with Traefik, Python and R Example

Fri, 29 Nov 2019 00:00:00 +0000

Ingress in Kubernetes exposes HTTP and HTTPS routes from outside the cluster to services within the cluster. By setting rules, it routes requests to appropriate services (precisely requests are sent to individual Pods by Ingress Controller). Rules can be set up dynamically and I find it’s more efficient compared to traditional reverse proxy. Traefik is a modern HTTP reverse proxy and load balancer and it can be used as a Kubernetes Ingress Controller.

Distributed Task Queue with Python and R Example

Fri, 15 Nov 2019 00:00:00 +0000

While I’m looking into Apache Airflow, a workflow management tool, I thought it would be beneficial to get some understanding of how Celery works. To do so, I built a simple web service that sends tasks to Celery workers and collects the results from them. FastAPI is used for developing the web service and Redis is used for the message broker and result backend. During the development, I thought it would be possible to implement similar functionality in R with Rserve.