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5000 articles · Page 7 of 50
Subtle Storm
Subtle Storm
Jan 17, 2026 · Backend Development

Deep Dive into Python Concurrency: Asyncio Event Loop, Scheduling, and High‑Performance Web Apps

This article dissects Python's asyncio event loop and coroutine scheduling, compares synchronous threading with asynchronous execution through benchmark tests, examines memory usage across models, presents a full async web service implementation with database and cache pools, and offers a decision matrix for choosing the right concurrency model.

Pythonasync webasyncio
0 likes · 15 min read
Deep Dive into Python Concurrency: Asyncio Event Loop, Scheduling, and High‑Performance Web Apps
Go Development Architecture Practice
Go Development Architecture Practice
Jan 17, 2026 · Backend Development

A Rapid Tour of 30+ Popular Web Frameworks Across Languages

This article provides concise, language‑by‑language overviews of more than thirty widely used web frameworks—including Ruby on Rails, ASP.NET, Vapor, Django, Flask, Phoenix, Laravel, Next.js, Astro, Spring Boot, Express.js, Gin, and Go‑specific frameworks—highlighting their core concepts, typical use cases, and notable projects built with them.

GoJavaScriptPython
0 likes · 16 min read
A Rapid Tour of 30+ Popular Web Frameworks Across Languages
Subtle Storm
Subtle Storm
Jan 15, 2026 · Backend Development

Deep Dive into Python Concurrency: Threads, Processes, and Coroutines (Part 1)

This article examines Python's three concurrency models—threading, multiprocessing, and asyncio coroutines—detailing their underlying mechanisms, performance traits, suitable use‑cases, and the impact of the Global Interpreter Lock, followed by a hybrid web‑server implementation example.

GILPythonWeb Development
0 likes · 9 min read
Deep Dive into Python Concurrency: Threads, Processes, and Coroutines (Part 1)
Aikesheng Open Source Community
Aikesheng Open Source Community
Jan 15, 2026 · Operations

Why Adding a Server with OAT Breaks yum and How to Fix It

This guide explains why using OAT to add a server can render yum unusable due to a broken Python interpreter, analyzes the underlying script logic that causes the failure, and provides two practical remediation methods—including fixing the Python symlink and adjusting the installation script—along with the full script for reference.

OATPythonShell script
0 likes · 12 min read
Why Adding a Server with OAT Breaks yum and How to Fix It
Sohu Tech Products
Sohu Tech Products
Jan 14, 2026 · Artificial Intelligence

Build a Zero‑Cost Open‑Source RAG Smart Document Q&A System from Scratch

This guide walks through building an open‑source Retrieval‑Augmented Generation (RAG) system that indexes local files with Everything, uses hybrid BM25‑vector search via Elasticsearch, and answers questions with a local LLM, covering architecture, core techniques, deployment steps, performance tweaks, and common pitfalls.

Document RetrievalElasticsearchLLM
0 likes · 11 min read
Build a Zero‑Cost Open‑Source RAG Smart Document Q&A System from Scratch
Data STUDIO
Data STUDIO
Jan 14, 2026 · Backend Development

Why FastAPI Is the Ideal Choice for High‑Performance Python Microservices – A Hands‑On Guide

This article explains how FastAPI’s async support, type‑hint integration, automatic OpenAPI docs, and rich ecosystem enable Python developers to build scalable, secure microservices with layered architecture, JWT authentication, performance optimizations, comprehensive testing, Docker/Kubernetes deployment, and structured logging.

DockerFastAPIJWT
0 likes · 22 min read
Why FastAPI Is the Ideal Choice for High‑Performance Python Microservices – A Hands‑On Guide
Fun with Large Models
Fun with Large Models
Jan 14, 2026 · Artificial Intelligence

Understanding Large Language Model Files: Structure, Tokens, and Inference with Qwen3

This article walks through the complete workflow of loading and running the open‑source Qwen3‑8B model, explaining each core file (weights, config, generation config, tokenizer), how the model tokenizes input, applies chat templates, generates responses, and decodes output, all illustrated with code and diagrams.

ModelScopePythonQwen3
0 likes · 16 min read
Understanding Large Language Model Files: Structure, Tokens, and Inference with Qwen3
360 Zhihui Cloud Developer
360 Zhihui Cloud Developer
Jan 13, 2026 · Databases

Turn PostgreSQL into a Graph Database with Apache AGE

This guide explains how Apache AGE extends PostgreSQL with OpenCypher‑compatible graph capabilities, covering architecture, installation, storage schema, Cypher‑SQL integration, common graph operations, and a LangChain example that turns natural‑language questions into executable graph queries.

Apache AGECypherGraph Database
0 likes · 11 min read
Turn PostgreSQL into a Graph Database with Apache AGE
Old Meng AI Explorer
Old Meng AI Explorer
Jan 13, 2026 · Artificial Intelligence

How an Open‑Source AI Tool Turns Xiaohongshu Posts into Viral Hits

The open‑source Xiaohongshu MCP (Multi‑Channel Publisher) leverages AI to predict hot topics, auto‑generate copy, titles and tags, monitor performance, analyze competitors, and manage multiple accounts, enabling creators to boost followers from a few hundred to thousands without costly subscriptions, with step‑by‑step deployment instructions and a free GitHub repository.

AIPythonSocial Media Automation
0 likes · 11 min read
How an Open‑Source AI Tool Turns Xiaohongshu Posts into Viral Hits
Architect's Tech Stack
Architect's Tech Stack
Jan 12, 2026 · Artificial Intelligence

How TuriX-CUA Lets AI Control Your Windows and macOS Desktop

TuriX-CUA is an open‑source Python framework that lets AI agents understand screen content and perform mouse‑keyboard actions on Windows and macOS, offering high success rates, model hot‑swapping, MCP integration, and step‑by‑step installation for desktop automation tasks.

AI automationDesktop AgentMCP
0 likes · 7 min read
How TuriX-CUA Lets AI Control Your Windows and macOS Desktop
IT Services Circle
IT Services Circle
Jan 11, 2026 · Artificial Intelligence

Can AI Really Control Your Computer? Inside TuriX‑CUA Open‑Source Agent

TuriX‑CUA is an open‑source Python‑based AI agent that equips artificial intelligence with visual perception and mouse‑keyboard control, enabling it to see the screen, reason with multimodal models, and act autonomously across macOS and Windows, with a multi‑model architecture, MCP support, and step‑by‑step setup instructions.

AIAutomationCrossPlatform
0 likes · 7 min read
Can AI Really Control Your Computer? Inside TuriX‑CUA Open‑Source Agent
Architect's Alchemy Furnace
Architect's Alchemy Furnace
Jan 10, 2026 · Artificial Intelligence

Build and Test a Multi‑Agent AI System with MetaGPT

This guide walks through the MetaGPT framework—explaining its multi‑agent architecture, core concepts, predefined roles, team setup, environment preparation, installation, configuration, and troubleshooting steps—so you can quickly build, run, and validate a collaborative AI software‑company simulation.

AI AgentsLLMMetaGPT
0 likes · 14 min read
Build and Test a Multi‑Agent AI System with MetaGPT
Old Meng AI Explorer
Old Meng AI Explorer
Jan 10, 2026 · Artificial Intelligence

Run Large Language Models on a Laptop: How ktransformers Breaks the GPU Barrier

ktransformers is an open‑source AI model optimization framework that uses dynamic quantization, layer fusion and memory reuse to cut memory usage by up to 50%, double loading speed and reduce inference cost, enabling 7B‑13B models to run smoothly on ordinary CPUs or low‑end GPUs.

KTransformersLarge Language ModelsModel Optimization
0 likes · 11 min read
Run Large Language Models on a Laptop: How ktransformers Breaks the GPU Barrier
Fun with Large Models
Fun with Large Models
Jan 10, 2026 · Artificial Intelligence

Designing Decentralized Multi‑Agent Networks with LangGraph: The Swarm Architecture

This article explains LangGraph's network (decentralized) architecture for multi‑agent systems, compares it with supervisor and hierarchical designs, and provides a step‑by‑step Python example using the langgraph‑swarm library to build agents that can dynamically hand off control and preserve conversation continuity.

LangGraphMulti-agentNetwork Architecture
0 likes · 13 min read
Designing Decentralized Multi‑Agent Networks with LangGraph: The Swarm Architecture
IT Services Circle
IT Services Circle
Jan 9, 2026 · Interview Experience

How to Find the Longest Balanced Substring in a Binary String (LeetCode 2609)

The article presents LeetCode problem 2609, defining a balanced substring as a consecutive segment of zeros followed by an equal number of ones, and provides a linear‑time solution using a two‑pointer scan that counts consecutive zeros and ones, with implementations in Java, C++, Python, and TypeScript, along with complexity analysis.

Balanced SubstringC++Java
0 likes · 7 min read
How to Find the Longest Balanced Substring in a Binary String (LeetCode 2609)
Data STUDIO
Data STUDIO
Jan 9, 2026 · Fundamentals

6 Hidden Python Features That Can Double Your Coding Efficiency

This article showcases six powerful yet often overlooked Python standard‑library features—pathlib, contextlib, __slots__, functools.lru_cache, generator pipelines, and dataclasses—demonstrating how they simplify code, boost performance, reduce memory usage, and make scripts more maintainable.

LRU cachePerformancePython
0 likes · 11 min read
6 Hidden Python Features That Can Double Your Coding Efficiency
Data STUDIO
Data STUDIO
Jan 8, 2026 · Backend Development

From “Magic Building Blocks” to “Clear Contracts”: 7 Pydantic v2 Features for Rock‑Solid API Design

The article examines seven new Pydantic v2 capabilities—TypeAdapter, Annotated + Field, deterministic validators, precise serialization hooks, computed_field, RootModel, and ConfigDict—showing how each resolves common API‑validation pain points, improves contract clarity, and boosts performance with concrete code examples and a FastAPI integration.

API designComputed FieldFastAPI
0 likes · 26 min read
From “Magic Building Blocks” to “Clear Contracts”: 7 Pydantic v2 Features for Rock‑Solid API Design
IT Services Circle
IT Services Circle
Jan 5, 2026 · Frontend Development

Which Python GUI Library Fits Your Project? A Hands‑On Comparison of PyQt6, Dear PyGui, Flet, Textual & CustomTkinter

This article compares five modern Python GUI frameworks—PyQt6, Dear PyGui, Flet, Textual, and CustomTkinter—detailing their core features, quick‑start code samples, strengths, learning curves, and ideal use cases to help developers choose the most suitable toolkit for desktop, web, or terminal‑based interfaces.

ComparisonCustomTkinterFlet
0 likes · 21 min read
Which Python GUI Library Fits Your Project? A Hands‑On Comparison of PyQt6, Dear PyGui, Flet, Textual & CustomTkinter
Data STUDIO
Data STUDIO
Jan 4, 2026 · Industry Insights

Is Python Still the #1 Programming Language in 2026?

The article argues that Python remains the top programming choice in 2026 because its concise syntax, massive ecosystem, and modern tooling deliver unmatched development speed, lower total cost, and a balanced blend of rapid prototyping with long‑term stability for a wide range of applications.

2026AutomationDevelopment Speed
0 likes · 11 min read
Is Python Still the #1 Programming Language in 2026?
37 Interactive Technology Team
37 Interactive Technology Team
Dec 31, 2025 · Backend Development

How AI‑Powered Cursor + Playwright Can Turbo‑Charge Your Web Automation Testing

This article details a practical workflow that combines Cursor's AI prompting with Playwright to quickly generate, debug, and launch a lightweight Python‑based web automation framework, covering requirement planning, prompt design, architecture, core modules, usage instructions, and future enhancement ideas.

AIAutomationPlaywright
0 likes · 8 min read
How AI‑Powered Cursor + Playwright Can Turbo‑Charge Your Web Automation Testing
21CTO
21CTO
Dec 31, 2025 · Frontend Development

Run Full Python in the Browser with Pyodide: A Hands‑On Guide

This article explains how Pyodide compiles CPython to WebAssembly, allowing developers to run complete Python—including libraries like Pandas, NumPy, and Matplotlib—directly in the browser without any server, installation, or build system, and demonstrates a practical CSV‑viewer example.

BrowserPandasPyodide
0 likes · 8 min read
Run Full Python in the Browser with Pyodide: A Hands‑On Guide
AI Architecture Hub
AI Architecture Hub
Dec 31, 2025 · Artificial Intelligence

Why LangGraph Is the Next‑Generation Framework for LLM Agent Orchestration

This article explains the motivation behind LangGraph, walks through a quick start, details its core syntax and state management, demonstrates conditional branching, parallel execution, tool integration, multi‑agent orchestration, and real‑time monitoring, and finally discusses future directions for the framework.

LLMLangGraphPython
0 likes · 32 min read
Why LangGraph Is the Next‑Generation Framework for LLM Agent Orchestration
AI Insight Log
AI Insight Log
Dec 30, 2025 · Artificial Intelligence

What Connecting Claude Code to LSP Reveals About Its Previous Limitations

The article explains how Claude Code’s new native support for the Language Server Protocol transforms its code‑understanding from a heuristic, file‑reading approach to real‑time, type‑aware diagnostics and precise navigation, and provides step‑by‑step guidance for enabling and configuring LSP plugins.

Claude CodeGoIDE integration
0 likes · 6 min read
What Connecting Claude Code to LSP Reveals About Its Previous Limitations
Woodpecker Software Testing
Woodpecker Software Testing
Dec 30, 2025 · Information Security

Master Automated Security Testing with ZAP: From Zero to Enterprise‑Ready

This article walks readers through ZAP’s architecture, dual passive/active scanning engines, headless operation, Python automation, CI/CD integration with Jenkins and Docker, advanced scripting with Zest and custom plugins, and best‑practice recommendations for building an enterprise‑grade automated security testing pipeline.

Automated Security TestingCI/CDDAST
0 likes · 10 min read
Master Automated Security Testing with ZAP: From Zero to Enterprise‑Ready
Subtle Storm
Subtle Storm
Dec 29, 2025 · Fundamentals

Understanding HTTP: From 1.1 to HTTP/3 and Beyond

The article traces the evolution of HTTP from the persistent‑connection design of HTTP/1.1 through the multiplexed, binary framing of HTTP/2 to the QUIC‑based HTTP/3, while also explaining status codes, cookies, caching directives, RESTful principles, WebSocket upgrades, and practical Python examples.

HTTP/2HTTP/3Python
0 likes · 8 min read
Understanding HTTP: From 1.1 to HTTP/3 and Beyond
Data STUDIO
Data STUDIO
Dec 29, 2025 · Fundamentals

Why Python’s Context Manager Prevents Resource Leaks

The article explains how Python’s context manager (the with statement) provides an elegant, exception‑safe way to acquire and release resources such as files, database connections, locks, and even asynchronous handles, showing concrete code examples, custom implementations, and best‑practice guidelines.

Pythonasyncbest practices
0 likes · 12 min read
Why Python’s Context Manager Prevents Resource Leaks
Mingyi World Elasticsearch
Mingyi World Elasticsearch
Dec 28, 2025 · Artificial Intelligence

Building an Elasticsearch‑Powered RAG Q&A System: Theory and Full Code Walkthrough

This article walks through the principles of Retrieval‑Augmented Generation (RAG) and provides a complete Python implementation using Elasticsearch, covering document chunking, semantic embedding, bulk indexing, hybrid BM25‑vector search, RRF result fusion, prompt design, LLM invocation, and a practical demo.

ElasticsearchHybrid SearchPrompt Engineering
0 likes · 9 min read
Building an Elasticsearch‑Powered RAG Q&A System: Theory and Full Code Walkthrough
Frontend AI Walk
Frontend AI Walk
Dec 27, 2025 · Artificial Intelligence

From Prompt to Production: Engineering Hard‑Core AI Skills with wechat‑publisher

The article defines AI Skill “hard‑core” capabilities versus soft prompt‑based logic, outlines a three‑layer architecture (scripts, metadata, security), and walks through concrete wechat‑publisher implementations—including inline style injection, multi‑template rendering, exit‑code handling, and a step‑by‑step development checklist—to show how to turn AI from a mere text generator into an autonomous executor.

AI SkillsAutomationCLI
0 likes · 17 min read
From Prompt to Production: Engineering Hard‑Core AI Skills with wechat‑publisher
Java One
Java One
Dec 26, 2025 · Fundamentals

How C/C++, Java, and Python Run: A Deep Dive into Compilation and Execution

This article compares the execution models of C/C++, Java, and Python, explaining how compiled machine code, bytecode with JVM, and interpreted bytecode with the Python virtual machine operate, and illustrates each process with example file structures and compilation steps.

C++CompilationJava
0 likes · 6 min read
How C/C++, Java, and Python Run: A Deep Dive into Compilation and Execution
Mingyi World Elasticsearch
Mingyi World Elasticsearch
Dec 26, 2025 · Databases

How to Enable Accurate Code Search in Elasticsearch with an NGram Analyzer

This article analyzes the shortcomings of standard Elasticsearch analyzers for code search, presents a custom NGram analyzer combined with match_phrase queries, shows configuration and query examples, compares performance of different query types, and offers best‑practice guidelines and pitfalls to avoid when building a reliable code‑search system.

Code searchElasticsearchNGram
0 likes · 13 min read
How to Enable Accurate Code Search in Elasticsearch with an NGram Analyzer
MaGe Linux Operations
MaGe Linux Operations
Dec 26, 2025 · Operations

Taming vLLM OOM: Real‑World Causes and Proven Fixes for Production

This article examines why vLLM experiences out‑of‑memory errors in production, explains memory fragmentation caused by PagedAttention, outlines four typical OOM scenarios with concrete command‑line solutions, and provides deep analysis, configuration scripts, dynamic tuning, troubleshooting flowcharts, monitoring alerts, and best‑practice recommendations.

GPUOOMPython
0 likes · 24 min read
Taming vLLM OOM: Real‑World Causes and Proven Fixes for Production
Fun with Large Models
Fun with Large Models
Dec 26, 2025 · Artificial Intelligence

LangGraph Agent Design Patterns Part 1: Prompt‑Chain, Router, and Parallel Modes

This article introduces three core LangGraph workflow patterns—Prompt‑Chain, Router, and Parallel—explaining their concepts, advantages, and concrete Python code examples that demonstrate how to decompose tasks, route requests, and run sub‑tasks concurrently for more reliable and efficient AI agents.

AI AgentsLangGraphParallel mode
0 likes · 19 min read
LangGraph Agent Design Patterns Part 1: Prompt‑Chain, Router, and Parallel Modes
Alibaba Cloud Developer
Alibaba Cloud Developer
Dec 26, 2025 · Artificial Intelligence

How to Build a Fully Automated Knowledge‑Extraction Pipeline for AI Agents with Python

This article presents a complete end‑to‑end pipeline that automatically extracts, generalizes, incrementally updates, and vector‑syncs knowledge from diverse sources such as tickets, documents, and SQL code, turning the traditionally labor‑intensive knowledge‑base construction for agents into a low‑effort, continuously maintainable Python‑driven solution.

Knowledge ExtractionLLMPython
0 likes · 15 min read
How to Build a Fully Automated Knowledge‑Extraction Pipeline for AI Agents with Python
Architect
Architect
Dec 25, 2025 · Artificial Intelligence

How GraphRAG Boosts Retrieval Accuracy with Knowledge Graphs – A Complete Guide

This article explains why traditional RAG suffers from hallucinations, introduces GraphRAG’s knowledge‑graph‑based approach, walks through its indexing and query pipelines—including text splitting, entity‑relation extraction, graph construction, community detection, and local vs. global retrieval—provides practical setup commands, Neo4j visualization steps, and compares its performance with classic RAG.

GraphRAGKnowledge GraphLLM
0 likes · 27 min read
How GraphRAG Boosts Retrieval Accuracy with Knowledge Graphs – A Complete Guide
360 Tech Engineering
360 Tech Engineering
Dec 25, 2025 · Artificial Intelligence

Why LangChain 1.0 Makes AI Agent Development Faster, Safer, and More Scalable

LangChain 1.0 replaces fragmented agent code with a production‑ready framework that unifies model outputs, simplifies tool integration, introduces content_blocks for consistent response handling, and adds a middleware system for privacy, summarization, and human‑in‑the‑loop safety, dramatically improving developer efficiency and reliability.

LLMLangChainMiddleware
0 likes · 13 min read
Why LangChain 1.0 Makes AI Agent Development Faster, Safer, and More Scalable
Architecture Digest
Architecture Digest
Dec 25, 2025 · Artificial Intelligence

MCP Explained: The Universal ‘Connector’ Turning AI Models into Extensible Agents

This article introduces the Model Context Protocol (MCP), a universal standard that lets large language models seamlessly connect to databases, APIs, local files, and third‑party services, explains its architecture, core primitives, practical Python implementation, trade‑offs, security considerations, and how it compares with other integration approaches.

AIModel Context ProtocolPython
0 likes · 13 min read
MCP Explained: The Universal ‘Connector’ Turning AI Models into Extensible Agents
Data STUDIO
Data STUDIO
Dec 25, 2025 · Fundamentals

Boost Python Automation Efficiency with toolz: A Practical Refactoring Guide

This article explains how the pure‑Python functional library toolz can transform tangled automation scripts into clear, composable data pipelines, reducing code size, improving testability, and eliminating hidden technical debt through concrete examples and step‑by‑step refactoring.

AutomationData pipelinesFunctional Programming
0 likes · 15 min read
Boost Python Automation Efficiency with toolz: A Practical Refactoring Guide
Tencent Technical Engineering
Tencent Technical Engineering
Dec 24, 2025 · Artificial Intelligence

Build a Mini LLM from Scratch: Step‑by‑Step Guide to Tokenizer, Attention, and Transformer

This article walks through constructing a small large‑language model from the ground up, covering model architecture, tokenization methods, BPE vocabulary building, embedding, positional encoding, attention mechanisms, multi‑head attention, transformer blocks, training pipelines, inference, and sampling strategies, all with runnable Python code.

Deep LearningLLMPython
0 likes · 34 min read
Build a Mini LLM from Scratch: Step‑by‑Step Guide to Tokenizer, Attention, and Transformer
Data STUDIO
Data STUDIO
Dec 24, 2025 · Fundamentals

Understanding Kalman Filter: A Simple, Step‑by‑Step Guide

The article explains how the Kalman filter fuses noisy sensor measurements with model predictions using Bayesian updates, demonstrates the process with intuitive 1‑D and 2‑D Python examples, and shows its real‑world applications such as navigation, autonomous driving, and signal processing.

Bayesian EstimationKalman filterPython
0 likes · 17 min read
Understanding Kalman Filter: A Simple, Step‑by‑Step Guide
Java One
Java One
Dec 23, 2025 · Fundamentals

Master Python Numbers & Strings: Tips, Pitfalls, and Best Practices

This guide covers Python's core numeric and string types—including ints, floats, complex numbers, booleans, and bytes—explains common pitfalls like floating‑point precision, demonstrates formatting options, shows how to use enums and SQLAlchemy for cleaner code, and offers practical advice for readable and efficient scripting.

DecimalEnumsFormatting
0 likes · 21 min read
Master Python Numbers & Strings: Tips, Pitfalls, and Best Practices
Data STUDIO
Data STUDIO
Dec 22, 2025 · Operations

12 Essential Python Automation Libraries for 2026 Every Developer Should Know

The article reviews twelve Python automation libraries—Kedro, Prefect, Pywinauto, Swifter, DagFactory, Schedule, Tenacity, Beanie, Helium, PyFilesystem2, Ruff, and Zappa—detailing their core features, code examples, use‑case scenarios, and why they will become indispensable tools for developers in 2026.

AutomationData ProcessingPython
0 likes · 29 min read
12 Essential Python Automation Libraries for 2026 Every Developer Should Know
Woodpecker Software Testing
Woodpecker Software Testing
Dec 21, 2025 · Fundamentals

Using ChatGPT to Generate Password‑Recovery Test Cases and Scripts

The article demonstrates how to prompt ChatGPT to produce comprehensive password‑recovery test cases and corresponding automation scripts—both API‑based with Python unittest and GUI‑based with Playwright‑pytest—covering normal flows, error conditions, security checks, and XSS vulnerabilities.

API testingChatGPTPassword Recovery
0 likes · 22 min read
Using ChatGPT to Generate Password‑Recovery Test Cases and Scripts
Architect's Alchemy Furnace
Architect's Alchemy Furnace
Dec 21, 2025 · Artificial Intelligence

Deploy and Explore Open WebUI: A Feature‑Rich Self‑Hosted AI Platform

Open WebUI is a self‑hosted, extensible AI platform that runs fully offline, supports multiple LLM back‑ends such as Ollama and OpenAI‑compatible APIs, offers built‑in RAG, role‑based access, multi‑model chat, markdown/LaTeX, image generation, and provides detailed Docker, pip, and Kubernetes installation guides with ready‑to‑run commands.

AI platformDockerLLM
0 likes · 11 min read
Deploy and Explore Open WebUI: A Feature‑Rich Self‑Hosted AI Platform
Advanced AI Application Practice
Advanced AI Application Practice
Dec 20, 2025 · Artificial Intelligence

Master System, User, Assistant Roles to Get Precise AI Testing Answers from LLMs

This article explains how the System, User, and Assistant roles in large-language-model chat APIs shape response quality, demonstrates their impact with concrete Python code examples, compares outcomes with and without System prompts, and offers practical tips for crafting effective prompts to achieve concise, relevant AI testing guidance.

AI testingAssistant RoleLLM
0 likes · 14 min read
Master System, User, Assistant Roles to Get Precise AI Testing Answers from LLMs
Mingyi World Elasticsearch
Mingyi World Elasticsearch
Dec 20, 2025 · Artificial Intelligence

How to Build an Enterprise‑Grade Intelligent Document QA System with Everything plus RAG

This article walks through the need for fast, accurate answers from massive document collections, compares plain keyword search and pure LLM chat, and presents a hybrid Retrieval‑Augmented Generation solution built with open‑source components, detailing architecture, hybrid retrieval, prompt engineering, deployment, performance tuning, and common pitfalls.

ElasticsearchHybrid RetrievalPrompt Engineering
0 likes · 12 min read
How to Build an Enterprise‑Grade Intelligent Document QA System with Everything plus RAG
IT Services Circle
IT Services Circle
Dec 20, 2025 · Fundamentals

10 Common Python String Pitfalls Every Developer Should Avoid

This article enumerates ten classic mistakes when handling Python strings—covering immutability, identity vs equality, truthiness of empty values, misuse of strip and split, Unicode length, performance of concatenation, encoding issues, and trailing backslashes—to help developers write safer, more efficient code.

ComparisonImmutablePerformance
0 likes · 7 min read
10 Common Python String Pitfalls Every Developer Should Avoid
MaGe Linux Operations
MaGe Linux Operations
Dec 19, 2025 · Artificial Intelligence

Boost vLLM Inference Throughput by 40% with Three Simple Config Tweaks

After discovering that only a few vLLM settings truly impact performance, this guide details how adjusting gpu_memory_utilization, max_num_batched_tokens, and enabling chunked prefill can raise Qwen2.5‑72B‑Instruct throughput from ~1800 to over 2500 tokens/s, improve latency, and provides comprehensive deployment, monitoring, and troubleshooting instructions.

DockerGPUKubernetes
0 likes · 30 min read
Boost vLLM Inference Throughput by 40% with Three Simple Config Tweaks
Data STUDIO
Data STUDIO
Dec 19, 2025 · Frontend Development

5 Python GUI Libraries That Make UI Development Fun (Beyond Tkinter)

Tired of Tkinter’s dated look, this article evaluates five modern Python GUI toolkits—PyQt6, Dear PyGui, Flet, Textual, and CustomTkinter—by outlining their core features, code snippets, ideal use‑cases, and a decision matrix to help you choose the most suitable framework for desktop, web, or terminal interfaces.

CustomTkinterDear PyGuiFlet
0 likes · 18 min read
5 Python GUI Libraries That Make UI Development Fun (Beyond Tkinter)
Data STUDIO
Data STUDIO
Dec 18, 2025 · Fundamentals

10 Essential Python Standard Library Modules You Should Use Today

After a senior engineer pointed out that a custom task scheduler could be replaced by Python’s built‑in graphlib, the author explored the standard library and discovered ten modules—dis, singledispatch, ast, atexit, sys.settrace, tomllib, graphlib, heapq, secrets, and shutil—that simplify debugging, code organization, security, and cross‑platform file handling.

HeapqPythondis
0 likes · 16 min read
10 Essential Python Standard Library Modules You Should Use Today
Fun with Large Models
Fun with Large Models
Dec 17, 2025 · Artificial Intelligence

Quick Guide to LangGraph 1.0: Core Concepts, Nodes, and Edges

This article introduces LangGraph 1.0 as a programming‑language‑style framework for AI agents, explains its core abstractions—State, Node, Edge, Reducer, and Human‑in‑the‑Loop—shows how to define state and node functions, builds simple and parallel graphs with static, conditional, and MapReduce edges, and demonstrates conflict‑resolution using built‑in and custom reducers.

AI AgentsGraph workflowLangChain
0 likes · 17 min read
Quick Guide to LangGraph 1.0: Core Concepts, Nodes, and Edges
Sohu Tech Products
Sohu Tech Products
Dec 17, 2025 · Artificial Intelligence

How We Cut Vision Transformer Inference Latency from 53 ms to 8 ms

Facing 53.64 ms per‑image latency in a Flask‑served Vision Transformer classifier, we iteratively optimized the pipeline—switching to ONNX Runtime, leveraging TensorRT, replacing Pillow with OpenCV, eliminating URL downloads, and finally batching requests—reducing average server‑side processing to 8.34 ms, a 6.4× speedup.

FlaskONNXPerformance Optimization
0 likes · 28 min read
How We Cut Vision Transformer Inference Latency from 53 ms to 8 ms
ShiZhen AI
ShiZhen AI
Dec 17, 2025 · Artificial Intelligence

Step-by-Step Guide: Train a Lerobot Robotic Arm from Scratch on GPUFree

This tutorial walks you through renting a GPUFree RTX 4090 cloud instance, uploading your Lerobot dataset, launching training via a lightweight Flask web UI, automatically shutting down the server, and downloading the trained model, all with detailed code snippets and practical tips.

AI trainingFlaskGPUFree
0 likes · 11 min read
Step-by-Step Guide: Train a Lerobot Robotic Arm from Scratch on GPUFree
Qborfy AI
Qborfy AI
Dec 17, 2025 · Artificial Intelligence

Unlocking AI Integration: A Hands‑On Guide to the Model Context Protocol (MCP)

The article introduces the Model Context Protocol (MCP), an open Anthropic standard that creates a secure, standardized, bidirectional bridge between large language models and external tools, then walks through its architecture, core components, Python server and client code, OpenAI integration, usage flow, ecosystem and future outlook.

AI integrationFastMCPJSON-RPC
0 likes · 8 min read
Unlocking AI Integration: A Hands‑On Guide to the Model Context Protocol (MCP)
Qborfy AI
Qborfy AI
Dec 16, 2025 · Artificial Intelligence

Mastering AI Function Calling: Turn LLMs into Actionable Assistants

Function Calling lets large language models invoke external tools or APIs during a conversation, transforming them from passive responders into proactive assistants; this guide explains the concept, workflow, and practical implementations with weather, parallel queries, and stock price examples using OpenAI’s Python SDK.

AI Function CallingLLMOpenAI SDK
0 likes · 9 min read
Mastering AI Function Calling: Turn LLMs into Actionable Assistants
Efficient Ops
Efficient Ops
Dec 15, 2025 · Operations

Mastering nvitop: Interactive NVIDIA GPU Monitoring and Management

This guide introduces nvitop, an interactive NVIDIA‑GPU process viewer and resource manager, explains its key features, shows how to install it via uvx/pipx, demonstrates basic device and process commands as well as the real‑time monitoring mode, and provides troubleshooting tips for common issues.

CLIGPU monitoringNVIDIA
0 likes · 5 min read
Mastering nvitop: Interactive NVIDIA GPU Monitoring and Management
Test Development Learning Exchange
Test Development Learning Exchange
Dec 15, 2025 · Backend Development

How to Build a Self‑Healing API Test Client with Automatic Token Refresh

Learn how to implement an automatic token‑refresh mechanism for API automation tests using Python’s requests and tenacity libraries, covering token refresh strategies, intercepting 401 responses, retry logic, client design, and production‑grade enhancements to ensure robust, unattended test execution.

API testingPythonToken Refresh
0 likes · 7 min read
How to Build a Self‑Healing API Test Client with Automatic Token Refresh
Tencent Technical Engineering
Tencent Technical Engineering
Dec 15, 2025 · Artificial Intelligence

How to Add Human‑in‑the‑Loop Interrupts to LangGraph Agents for Safe, Controllable AI Workflows

This guide explains the concept of human‑in‑the‑loop (HITL) interruptions in LangGraph, outlines the core mechanisms such as persistent state and dynamic/static interrupts, and provides detailed Python examples for four classic patterns—approval/rejection, state editing, tool‑call review, and input validation—plus advanced topics like parallel interrupts and MCP‑based tool integration.

AI AgentsLangGraphMCP
0 likes · 35 min read
How to Add Human‑in‑the‑Loop Interrupts to LangGraph Agents for Safe, Controllable AI Workflows
Data STUDIO
Data STUDIO
Dec 15, 2025 · Fundamentals

Stop reinventing the wheel: 9 Python libraries that can triple your efficiency

The article introduces nine powerful Python libraries—Boltons, Pydash, funcy, glom, furl, Cachier, Python‑Levenshtein, Plumbum, and Hydra—explaining why each is needed, highlighting core capabilities, showing concrete code examples, and recommending practical use‑cases to dramatically speed up everyday scripting and data‑processing tasks.

AutomationConfigurationData Processing
0 likes · 18 min read
Stop reinventing the wheel: 9 Python libraries that can triple your efficiency
Xiaolong Cloud Tech Team
Xiaolong Cloud Tech Team
Dec 9, 2025 · Artificial Intelligence

Introducing ValueCell: An Open‑Source Multi‑Agent AI Platform for A‑Shares, US Stocks and Crypto

ValueCell is an open‑source Python‑based multi‑agent AI platform that simulates a professional investment team, integrates various LLM providers, covers multiple markets (A‑shares, US stocks, crypto, Hong Kong), and offers one‑click deployment with detailed orchestration, enabling users to run AI‑driven portfolio management and replicate the Alpha Arena trading competition.

AIAutomated TradingFinance
0 likes · 6 min read
Introducing ValueCell: An Open‑Source Multi‑Agent AI Platform for A‑Shares, US Stocks and Crypto
Xiaolong Cloud Tech Team
Xiaolong Cloud Tech Team
Dec 8, 2025 · Artificial Intelligence

A Complete Guide to the Top 3 NLP Models (Llama, ChatGLM, T5) with Hands‑On Deployment for Beginners

This article breaks down the core principles, architectures, and formulas of Llama, ChatGLM, and T5, compares their strengths and weaknesses, and provides a zero‑data, no‑VPN beginner project that trains and evaluates all three models on sentiment analysis and summarization, visualizes the results, and offers practical deployment tips.

ChatGLMLlamaNLP
0 likes · 24 min read
A Complete Guide to the Top 3 NLP Models (Llama, ChatGLM, T5) with Hands‑On Deployment for Beginners
Tencent Technical Engineering
Tencent Technical Engineering
Dec 8, 2025 · Artificial Intelligence

Building Persistent Long‑Term Memory for LLM Agents with LangGraph – A Complete Guide

This article explains how to give large language model agents lasting memory by combining short‑term and long‑term storage in LangGraph, covering concepts, implementation details, database persistence, tool integration, semantic search, memory‑management strategies, checkpoint handling, and a multi‑agent supervisor example.

LLMLangGraphLong-Term Memory
0 likes · 43 min read
Building Persistent Long‑Term Memory for LLM Agents with LangGraph – A Complete Guide
Xiaolong Cloud Tech Team
Xiaolong Cloud Tech Team
Dec 5, 2025 · Artificial Intelligence

Recreate Claude Code’s Core Features with LangGraph – A Hands‑On Python Tutorial

This tutorial walks you through reproducing Claude Code’s core functionality using the LangGraph Python framework, covering ReAct agents, human‑in‑the‑loop control, sub‑agent orchestration, Todo task management, context compression, streaming output, and provides complete notebooks, installation steps, and example code for hands‑on learning.

AI AgentsAsync ProgrammingClaude Code
0 likes · 12 min read
Recreate Claude Code’s Core Features with LangGraph – A Hands‑On Python Tutorial
Data STUDIO
Data STUDIO
Dec 5, 2025 · Big Data

Why Parquet Is the Default Choice for Big Data Storage

The article explains how Apache Parquet’s columnar layout, multi‑level row‑group structure, projection and predicate push‑down, and advanced compression and encoding make it the high‑performance, space‑efficient storage format that powers modern big‑data ecosystems and tools like Spark, Python pandas, and ClickHouse.

Big DataClickHousePerformance Optimization
0 likes · 11 min read
Why Parquet Is the Default Choice for Big Data Storage
Ray's Galactic Tech
Ray's Galactic Tech
Dec 4, 2025 · Information Security

How to Secure Phone Numbers in Databases: Threat Modeling, Envelope Encryption, and High‑Performance Key Rotation

This guide presents a comprehensive, enterprise‑grade solution for encrypting phone numbers in databases, covering threat modeling, layered schema design, envelope encryption with KMS, Python service implementation, searchable indexes, key rotation, performance tuning, auditing, and common pitfalls.

AES-GCMEncryptionKMS
0 likes · 11 min read
How to Secure Phone Numbers in Databases: Threat Modeling, Envelope Encryption, and High‑Performance Key Rotation
IT Services Circle
IT Services Circle
Dec 4, 2025 · Backend Development

6 Python Libraries That Can Supercharge Your Development in 2025

This article introduces six cutting‑edge Python libraries—FakerX, Prefect 3.0, SQLModel, Litestar, Robocorp, and Typer—explaining the problems they solve, providing concise code examples, and offering practical steps for integrating them to dramatically improve development speed and code quality.

DevelopmentORMPython
0 likes · 12 min read
6 Python Libraries That Can Supercharge Your Development in 2025
Data STUDIO
Data STUDIO
Dec 4, 2025 · Backend Development

6 Python Libraries That Will Transform Your Development Workflow

This article introduces six Python libraries—FakerX, Prefect 3.0, SQLModel, Litestar, Robocorp, and Typer—explaining the problems they solve, providing concrete code examples, performance highlights, and practical advice for integrating them into modern Python projects.

FakerXLitestarPrefect
0 likes · 12 min read
6 Python Libraries That Will Transform Your Development Workflow
DevOps Engineer
DevOps Engineer
Dec 4, 2025 · Operations

Detect Python End‑of‑Life Versions Instantly with py‑eol

This article introduces py‑eol, a lightweight open‑source tool that checks whether a Python interpreter version is already or soon to be End‑of‑Life, offering module, CLI, and pre‑commit hook integrations for local development, CI/CD pipelines, and team collaboration.

CI/CDEOLPython
0 likes · 5 min read
Detect Python End‑of‑Life Versions Instantly with py‑eol
Data STUDIO
Data STUDIO
Dec 3, 2025 · Artificial Intelligence

Pixeltable: One Table to Power Multimodal AI with Declarative Python

Pixeltable introduces a unified table abstraction that treats images, text, embeddings and model outputs as columns, enabling declarative multimodal AI pipelines, eliminating glue code, supporting built‑in vector indexing, versioned experiments, extensible custom functions, and a concise 30‑line RAG implementation.

Multimodal AIPixeltablePython
0 likes · 15 min read
Pixeltable: One Table to Power Multimodal AI with Declarative Python
dbaplus Community
dbaplus Community
Dec 2, 2025 · Databases

Adapting goInception for OceanBase MySQL: Full Guide with Python Integration

This article walks through the challenges of using goInception with OceanBase‑MySQL tenants, details the code modifications required to parse OB's Query Plan, shows how to expose the enhanced engine via a Python wrapper, and presents validation results demonstrating accurate, low‑latency SQL auditing.

DatabaseOB-MySQLOceanBase
0 likes · 10 min read
Adapting goInception for OceanBase MySQL: Full Guide with Python Integration
Xiaolong Cloud Tech Team
Xiaolong Cloud Tech Team
Dec 2, 2025 · Industry Insights

Top GitHub Open‑Source Projects That Dominated November

This article surveys the most popular GitHub open‑source projects of November, highlighting their star counts, core functionalities, supported platforms, and providing direct repository links for tools ranging from AI agents and speech‑to‑text apps to Rust UI libraries and cloud‑native storage solutions.

AIGitHubPython
0 likes · 11 min read
Top GitHub Open‑Source Projects That Dominated November
DevOps Engineer
DevOps Engineer
Dec 2, 2025 · Operations

How I Turned Gnuplot into a One‑Click Python Wheel for Seamless Installation

After struggling with manual gnuplot installations across Linux, macOS, and Windows, the author created a Python wheel that bundles the binary, enabling pip install without system dependencies, simplifying usage for developers, researchers, and DevOps scripts, and integrating it into the gitstats tool.

AutomationDevOpsGnuplot
0 likes · 6 min read
How I Turned Gnuplot into a One‑Click Python Wheel for Seamless Installation
AI Algorithm Path
AI Algorithm Path
Dec 1, 2025 · Artificial Intelligence

Getting Started with the Cutting‑Edge Vision‑Language Model Qwen3‑VL

This article introduces vision‑language models, explains why they outperform OCR‑plus‑LLM pipelines, and walks through practical OCR and information‑extraction tasks using Qwen3‑VL, complete with code snippets, example prompts, result analysis, and a discussion of the model's limitations and resource considerations.

Deep LearningOCRPython
0 likes · 13 min read
Getting Started with the Cutting‑Edge Vision‑Language Model Qwen3‑VL
Data Party THU
Data Party THU
Dec 1, 2025 · Backend Development

Simplify Python Logging with Loguru: From Boilerplate to Best Practices

This article explains why Python logging often feels cumbersome, demonstrates how Loguru provides a minimal‑configuration alternative with powerful features, offers a reusable wrapper for the standard logging module, and presents practical examples and best‑practice guidelines for effective logging in backend applications.

DebuggingLoggingLoguru
0 likes · 9 min read
Simplify Python Logging with Loguru: From Boilerplate to Best Practices
Java Tech Enthusiast
Java Tech Enthusiast
Nov 30, 2025 · Fundamentals

Is Python Losing Its Edge? How Rust Is Eating Its Lunch

A candid look at Python’s recent performance woes, the Python Software Foundation’s financial troubles, the rise of Rust in core libraries, stagnant growth, and why the language may be losing its appeal for high‑scale production systems.

AILanguage TrendsPython
0 likes · 7 min read
Is Python Losing Its Edge? How Rust Is Eating Its Lunch
IT Services Circle
IT Services Circle
Nov 29, 2025 · Backend Development

Simplify Python Logging with Loguru: One‑Line Configuration

This article explains why traditional Python logging is cumbersome, demonstrates the verbose boilerplate required, and then shows how the Loguru library can replace it with a minimal, powerful setup that includes automatic exception handling, colored output, log rotation, async support, and structured logging for both web and script applications.

ConfigurationDebuggingLogging
0 likes · 9 min read
Simplify Python Logging with Loguru: One‑Line Configuration
IT Services Circle
IT Services Circle
Nov 29, 2025 · Fundamentals

Is Python Heading for Obsolescence? Rust’s Rise and the Cracks in the Ecosystem

The article examines Python’s growing performance and sustainability challenges, highlighting the Python Software Foundation’s financial loss, the increasing reliance on Rust for core libraries, stagnant version adoption, chaotic dependency management, and the shift of large‑scale production to compiled languages, warning that Python may become a legacy glue layer.

AIDependency ManagementProgramming Languages
0 likes · 7 min read
Is Python Heading for Obsolescence? Rust’s Rise and the Cracks in the Ecosystem
Architecture and Beyond
Architecture and Beyond
Nov 29, 2025 · Backend Development

How ComfyUI Caches Work: CLASSIC vs LRU vs RAM_PRESSURE Explained

This article breaks down ComfyUI's two‑level cache system, explains the differences between the CLASSIC, LRU, and RAM_PRESSURE strategies for outputs and objects, and offers practical guidance on choosing the right cache mode when running multiple models, LoRAs, and workflows on a single machine.

AI WorkflowsCache strategiesComfyUI
0 likes · 19 min read
How ComfyUI Caches Work: CLASSIC vs LRU vs RAM_PRESSURE Explained
Data Party THU
Data Party THU
Nov 27, 2025 · Artificial Intelligence

Which Python Causal Inference Library Wins? A Hands‑On Comparison of Six Tools

This article compares six popular Python causal inference libraries—Bnlearn, Pgmpy, CausalNex, DoWhy, PyAgrum, and CausalImpact—using the U.S. Census Income dataset to answer whether a graduate degree raises the probability of earning over $50K, and provides detailed code, pros, cons, and results for each tool.

BnlearnCausalImpactDoWhy
0 likes · 21 min read
Which Python Causal Inference Library Wins? A Hands‑On Comparison of Six Tools
DevOps Engineer
DevOps Engineer
Nov 27, 2025 · Operations

Catch Jenkinsfile Errors Before Commit with jenkinsfilelint – A Python Linter

jenkinsfilelint is a Python‑based command‑line tool that validates Jenkinsfile syntax via the Jenkins API, integrates seamlessly with pre‑commit hooks, offers flexible configuration and smart filtering, and provides step‑by‑step installation and usage instructions to prevent build failures caused by pipeline errors.

CI/CDJenkinsLinter
0 likes · 6 min read
Catch Jenkinsfile Errors Before Commit with jenkinsfilelint – A Python Linter
Data STUDIO
Data STUDIO
Nov 26, 2025 · Fundamentals

Simplify Python Logging with Loguru: A One‑Line Solution to Debugging Hassles

The article explains why Python logging often feels cumbersome, demonstrates the verbose boilerplate of the standard logging module, and then shows how Loguru provides a minimal one‑line configuration, powerful features, and practical examples that turn logging into an efficient debugging tool.

DebuggingLoggingLoguru
0 likes · 9 min read
Simplify Python Logging with Loguru: A One‑Line Solution to Debugging Hassles