Rainux

Flask - Common Application Deployment Solutions

Sat, 14 Feb 2026 12:40:31 +0800

This article introduces several common deployment solutions for Flask applications in production environments

Executing Asynchronous Scheduled Tasks with Database-Based Distributed Locking in FastAPI

Sun, 08 Feb 2026 23:56:57 +0800

This article provides a comprehensive guide on implementing an asynchronous task scheduler in FastAPI, using database-based distributed locks to prevent duplicate task execution in multi-process environments.

Using UPSERT in SQLAlchemy

Sun, 08 Feb 2026 16:20:18 +0800

This article explains how to use UPSERT operations in SQLAlchemy with PostgreSQL and SQLite

Exploring the Official MCP Go SDK

Sat, 07 Feb 2026 15:05:31 +0800

Hands-on experience with the official MCP Go SDK: Building an MCP Server and an MCP Client that enables LLMs to autonomously select tools

Deploying a Single-Node Kubernetes Cluster on Debian 13 with kubeadm and Cilium

Thu, 05 Feb 2026 00:44:06 +0800

This article provides a comprehensive guide on deploying a single-node Kubernetes cluster in a local virtual machine environment using Cilium as the network plugin.

Flask - Design and Implementation of tracking_id

Sat, 17 Jan 2026 17:36:52 +0800

This article details how to implement request tracking ID (tracking_id) functionality in Flask applications, including middleware design, logging, response formatting, and a complete solution to help developers achieve request tracing and enhance system observability.

FastAPI - Calling Synchronous Methods in FastAPI Asynchronous Methods

Tue, 06 Jan 2026 16:19:44 +0800

Introduction

Directly calling synchronous methods within asynchronous methods blocks the entire event loop, preventing the application from handling any other concurrent requests while executing the synchronous method. This severely impacts the overall performance and responsiveness of the service.

To address this issue, the core approach is to delegate synchronous methods to external thread pools or process pools for execution, thereby avoiding blocking the main event loop.

Method 1: Using asyncio.to_thread

Python 3.9 and later versions provide the asyncio.to_thread method, which runs synchronous functions in a separate thread and returns a coroutine object that can be awaited.

MCP-01: Introduction and Core Concepts

Thu, 25 Dec 2025 00:14:28 +0800

Introduction to MCP (Model Context Protocol)

About

Wed, 24 Dec 2025 23:47:24 +0800

Rainux He <–> 花酒锄作田, a normal developer, mainly develop Golang and Python program, familiar with cloud native development based on Kubernetes, have a little experience with web development (Vue).

FastAPI - Design of tracking_id

Thu, 11 Dec 2025 00:40:44 +0800

Introduction

In real business scenarios, tracing a request’s complete processing path in logs based on a tracking_id is a common requirement. However, FastAPI does not provide this functionality out of the box, so developers need to implement it themselves. This article introduces how to add a tracking_id to the entire request lifecycle based on contextvars and automatically record it in logs.

What is contextvars

Python 3.7 added a module contextvars to the standard library, which stands for “Context Variables”. It is typically used to implicitly pass some environmental information variables, similar to threading.local(). However, threading.local() is thread-specific, isolating data states between threads, while contextvars can be used in asynchronous coroutines within the asyncio ecosystem. PS: contextvars can not only be used in asynchronous coroutines but can also replace threading.local() in multi-threaded functions.