Learn how to create a Python logging wrapper that reduces repetitive code, ensures log entries show the correct filename and line number using the inspect module, and loads configuration once for global use, improving readability and maintainability in large applications.
This article explains the concept of deep copy in Python, demonstrating how it recursively copies all nested objects using the copy module's deepcopy function, with practical examples including basic data types, lists, dictionaries, and custom objects.
This article outlines six practical habits—following PEP 8, using the latest Python version, commenting code, employing linters, leveraging built‑in functions and libraries, and promptly fixing issues—to help new Python developers write clean, maintainable, and error‑free code throughout their careers.
This article explains how to create a panoramic image by detecting SIFT keypoints, matching features with KNN, estimating a homography using RANSAC, and warping the images with OpenCV, providing full Python code and step‑by‑step instructions.
This article explains why third‑party payment is needed, outlines Alipay’s workflow, guides through obtaining APPID and generating public/private keys, and provides a complete Python implementation—including key handling, request signing, and API usage—to integrate Alipay payments into backend applications.
This guide provides ready‑to‑run Python scripts for creating 3D scatter, line, surface, bar, and contour charts with Matplotlib, plus interactive 3D visualizations using Plotly, and includes pip installation commands for all required libraries.
This article explains Python's built‑in map() function, covering its syntax, basic usage with lambda and regular functions, and advanced scenarios such as handling multiple iterables, dictionaries, strings, conditional filtering, zip, nested lists, and compares it with list comprehensions, providing clear code examples throughout.
This article demonstrates ten practical techniques for iterating over rows, columns, and values of a pandas DataFrame and applying common transformations such as apply, vectorized operations, map, mask, groupby, cumulative sum, and rolling calculations, each illustrated with concise Python code examples.
This article explains Python's set type, covering its definition, creation (including empty sets), key properties such as unordered uniqueness, conversion using set(), the eight basic and four augmented set operators, common set methods, and practical applications like data deduplication.
This article walks through a Python web‑scraping project that fetches skin images, names, and prices from Honor of Kings, covering project background, required tools, site analysis, code implementation, data processing, and legal considerations.
The article explains Python's dict resizing mechanism, detailing when the hash table grows (when used entries reach two‑thirds of capacity), how the new size is chosen as the smallest power‑of‑two ≥ ma_used × 3, and the exact steps the interpreter takes to reallocate and rebuild the underlying key and entry arrays.
This article demonstrates how to use Python to fetch Amap traffic iso‑chrones via API calls, process city and district IDs, and visualize the 30‑minute travel range on an interactive map with Folium, providing complete code snippets for data acquisition, parsing, and map rendering.
This article explains how to build a Python script that searches a comic website, extracts chapter links and image URLs using requests and BeautifulSoup, and downloads the images into organized folders with multithreaded support, while outlining required modules and potential improvements.
This guide demonstrates how to install pandas and openpyxl, create DataFrames, write them to Excel worksheets, merge cells, combine multiple DataFrames into separate sheets, merge multiple Excel files, apply styles and conditional formatting, and remove duplicate rows using Python.
This guide explains how Python’s built‑in zip() and dict() functions can be combined to pair elements from two separate lists and create a dictionary, covering function basics, step‑by‑step examples, practical use cases such as user credentials and student scores, and a concise summary of the technique.
This article explains how the open‑source PySnooper library replaces manual print statements by automatically logging line execution, variable values, and timing through a simple decorator, offering a lightweight yet powerful way to debug Python code across various projects.
This article explains how pandas loc and iloc work, demonstrates their slow performance when used inside loops, and shows that using the at and iat accessors provides a dramatically faster alternative for scalar assignments in DataFrames.
This article introduces Python's functools module, explaining key utilities such as partial functions, lru_cache, update_wrapper, wraps, cmp_to_key, singledispatch, FunctionTool, cache, and partialmethod, and provides practical code examples demonstrating how to create preset request functions, cache results, update signatures, and implement polymorphic behavior.
This article explores the free GLM-4-Flash API from Zhipu AI, detailing its lightweight architecture, performance specs, a logic‑puzzle demonstration, and provides a comprehensive step‑by‑step tutorial—including data upload, model fine‑tuning, deployment commands and example code for building a LangChain‑based knowledge‑base retrieval system.
This article introduces Python's higher-order functions—including map, filter, reduce, partial, lambda, and related modules such as itertools, functools, contextlib, concurrent.futures, and decorator—explaining their concepts and demonstrating practical code examples for simplifying API testing and automation.
This article outlines six practical Python coding habits—including following PEP 8, using the latest version, commenting effectively, employing linters, leveraging built‑in functions and libraries, and fixing issues promptly—to help developers write clean, maintainable, and error‑free code.
This article introduces Python's Abstract Syntax Tree (AST), explains its purpose for code analysis and transformation, and provides ten detailed examples that demonstrate building, inspecting, modifying, and generating code using the ast module in a standard Python environment.
This article demonstrates ten practical Python list techniques—including sorting by ID, filtering by condition, locating elements, removing items, merging lists, finding intersections and differences, converting to dictionaries, using list comprehensions, and deduplicating—each illustrated with clear code examples and expected output.
This article introduces Python's built‑in shutil module, explains its key functions for copying, moving, deleting, archiving, and retrieving file information, and provides comprehensive code examples demonstrating how to prepare test files and perform common file‑system tasks such as copying files, moving directories, and creating archives.
This article explains how to create a Python script that automatically compensates weapon recoil in PUBG by capturing the screen, recognizing equipment with OpenCV and SSIM, and moving the mouse via pynput and pydirectinput without modifying the game memory.
This guide walks through ten practical Python examples for parsing, constructing, validating, updating, deleting, and iterating JSON data via HTTP requests, including custom date serialization and schema validation, each demonstrated with complete code and expected outcomes.
This article walks through a real‑world Python JSON parsing issue where extra quotes break the data, presents multiple regex‑based and parsing approaches from community members, and provides ready‑to‑run code snippets to clean and convert the malformed strings into valid JSON.
This article presents six hands‑on Python generative‑AI projects—ranging from a Llama 2 chatbot built with Streamlit and Replicate to natural‑language‑to‑SQL conversion using LlamaIndex and SQLAlchemy—complete with environment setup, required code snippets, deployment tips and resource links for further exploration.
This article provides a detailed overview of over a hundred essential Python libraries spanning environment management, packaging, file handling, date‑time utilities, text processing, office document formats, databases, networking, web frameworks, and concurrency, illustrating Python's vast ecosystem for diverse development needs.
This article demonstrates ten essential Python string manipulation techniques—including concatenation, splitting, searching, replacement, case conversion, slicing, formatting, whitespace trimming, list conversion, and URL encoding/decoding—each illustrated with clear code examples and expected output for practical API development.
This article presents a series of Python requests code snippets demonstrating how to upload and download files, compare contents, process CSV and JSON payloads, verify file size, name, MD5 checksum, MIME type, and handle multiple file uploads in typical backend API scenarios.
This article surveys the most suitable programming languages for artificial intelligence, detailing why Python, R, Java, LISP, Prolog, C++, Haskell, JavaScript, and Julia each excel in AI development, and provides practical FAQs for developers choosing the right language.
This article explains how to construct a multi‑agent AI research assistant using LangGraph and the open‑source GPT‑Researcher project, detailing the system architecture, agent roles, state design, workflow creation, parallel sub‑processes, and code examples for autonomous online research and report generation.
This article dissects CPython's dictionary implementation, explaining how a PyDictObject and its PyDictKeysObject are allocated, how method groups map to Python magic methods, and the detailed C logic for inserting, updating, and retrieving key‑value pairs, including __missing__ handling.
This tutorial demonstrates how to perform fundamental Redis operations—including setting, retrieving, and deleting keys, working with hashes, lists, and sorted sets—using Python's redis client and includes complete test code for each scenario.
This article explains why pandas loc/iloc operations inside Python loops are extremely slow, demonstrates the performance difference with concrete examples, and shows that using the scalar‑access methods at and iat can speed up the same task by dozens of times.
This article walks through using PaddlePaddle's linear algebra API to vectorize face images, load the ORL dataset, implement PCA for dimensionality reduction, and evaluate a simple face‑recognition classifier, providing full code, installation steps, and experimental results.
This article introduces the pytest-httpserver plugin for launching a simple HTTP server during tests, provides installation instructions, and walks through ten practical examples covering GET, POST, headers, query parameters, request counting, error codes, redirects, file uploads, timeouts, and client certificate verification.
This guide walks you through installing the PHPy extension on Ubuntu 22.04, configuring it, and running a simple PHP script that calls Python code, complete with required packages, configuration steps, and example code.
This tutorial walks you through building a fully functional Pong game in Python using the turtle library, featuring an AI paddle that automatically tracks the ball, complete with step‑by‑step code snippets and a complete source listing for easy copy‑paste implementation.
In this post a Python enthusiast shares a real‑world troubleshooting session where a pyecharts chart fails to display in Jupyter, discusses common causes such as missing git or offline resources, and provides a concrete fix by setting the online host URL via CurrentConfig, along with practical tips for future queries.
This article explains the WSGI/ASGI ecosystem, compares uWSGI, Nginx, and uvicorn, and then introduces Granian—a Rust‑written ASGI server that supports WSGI, ASGI, and RSGI, offering superior performance, HTTP/2‑3 support, and easy integration for Python web applications.
LangGraph Studio is a new visual IDE that simplifies the development, debugging, and interactive iteration of complex LLM‑based agent applications, offering features such as graph visualization, real‑time state inspection, code‑aware debugging, and seamless integration with LangSmith, with step‑by‑step guidance for desktop users.
This article introduces functional programming techniques in Python, covering first‑class functions, treating functions as objects, higher‑order functions, lambda expressions, and built‑in utilities like map, filter, and reduce, with clear code examples and explanations of their practical uses.
This article explains what large language models (LLMs) are, how they are trained, their diverse applications across industries, the challenges they face, and provides a practical Python example using Replicate to run Meta's Llama 3‑70b‑instruct model.
Mark Shannon’s “Shannon Plan” for Faster CPython outlines three parallel initiatives—Tier 2 optimizer, enabling sub‑interpreters via PEP 554, and memory‑management improvements—aimed at making Python up to five times faster by Python 3.13, with Microsoft joining the effort.
Learn how to create a lightweight calculator in Python using the PySimpleGUI library, complete with a functional UI, arithmetic operations, history tracking, and clear/delete features, accompanied by full source code and explanations for each component.
This guide explains how to query a Microsoft GraphRAG knowledge graph using the official CLI, API, and a custom Neo4j implementation, covering both local and global retrieval modes, vector index creation, Cypher query customization, and integration with LangChain for end‑to‑end RAG pipelines.
This tutorial introduces PyYAML, explains how to install it, and provides twelve practical Python examples covering reading, writing, and manipulating YAML files, strings, lists, nested structures, complex data types, tags, anchors, streams, and environment variables.
This article walks through a complete PCA‑based face‑recognition pipeline using the PaddlePaddle framework, covering dataset preparation, library installation, image vectorization, PCA dimensionality reduction, training, testing, and performance evaluation with detailed code examples.
This article provides comprehensive examples of APScheduler's advanced features including database storage, multi-threading/multi-processing, event listeners, dynamic task management, external event triggers, priority settings, logging, advanced triggers, and timezone support.
This article introduces the Python APScheduler library, covering installation, a basic interval example, various trigger types such as date and cron, parameterized and timezone-aware jobs, retry handling, dynamic job management, SQL job stores, multithreading, parallel execution, external event triggers, priority settings, and how to run the examples.
This tutorial explains how to merge multiple graphs into a single figure using the patchwork package in R and the patchworklib library in Python, providing installation steps, code examples for arranging plots side‑by‑side and in grids, and visual results.
This article reviews the most downloaded Python packages on PyPI over the last year, explaining each library's purpose, key features, usage examples, and why they are popular among developers, covering tools for HTTP, compatibility, AWS, data handling, security, and more.
This article presents LeetCode problem 112 "Path Sum", detailing the problem statement, example inputs and outputs, constraints, a recursive analysis, and complete reference implementations in Java, C++, and Python for determining whether a root‑to‑leaf path equals a given target sum.
This tutorial demonstrates how to install Paramiko, establish SSH connections, execute remote commands, upload and download files via SFTP, and close connections, while also covering advanced topics such as key‑based authentication, channel operations, interactive sessions, concurrent commands, jump hosts, proxy commands, and proxy servers.
This article introduces the Python Invoke library, explains how to install it, demonstrates basic task definitions with @task decorators, and provides practical code examples for automating testing, documentation building, dependency installation, cleaning, packaging, deployment, remote execution, database migration, log analysis, and virtual‑environment creation.
This article dissects Python's dictionary implementation, explaining the PyDictObject layout, the combined and split hash‑table designs, memory‑optimisation techniques, insertion and lookup processes, ordered iteration, and precise memory‑size calculations with concrete code examples.
This article introduces seven noteworthy open‑source Python repositories—including Pandas, Apache Airflow, G4F, Scrapy, Ultroid, Zulip, and Freqtrade—highlighting their key features, typical use cases, and where to find them, offering developers a curated guide to valuable tools for data analysis, workflow automation, web crawling, chat bots, team collaboration, and crypto trading.
This article lists the 22 most downloaded Python packages on PyPI over the past year, explains their functionality, interrelationships, and provides code examples, highlighting why they are popular and offering guidance on their usage and alternatives.
The article reviews pandas 2.0’s major upgrades—including an Apache Arrow backend that speeds up CSV reads by over 30×, new Arrow dtypes, a nullable‑numpy dtype for missing values, a copy‑on‑write memory model, optional dependencies, and benchmark comparisons with ydata‑profiling—highlighting the library’s enhanced performance, flexibility, and interoperability for data‑intensive Python workflows.
The article reports the August 2024 TIOBE index, highlighting Python’s surge past Java to become the most popular language, analyzes the ranking data, explains why Python dominates, and provides historical context and a detailed list of the top programming languages.
This article explores the classic “Hello World” program across five popular programming languages—Python, C#, C++, JavaScript, and PHP—detailing each language’s syntax, key functions, and code snippets, while reflecting on the significance of this introductory example for beginners.
The article explains how Python maps a dict key to a hash‑table slot, the two classic collision‑resolution strategies (separate chaining and open addressing), why Python uses an iterative probing function, and walks through the core C functions that perform the lookup and slot‑finding logic.
This article explains what .nc (netCDF) files are, why they are useful for storing scientific time‑series data, and provides two clear Python solutions—standard reading and direct extraction—complete with installation tips, code examples, and practical guidance.
This guide walks through ten common Redis tasks—setting and getting keys, deleting keys, listing keys, hash, list, set, sorted‑set operations, publish/subscribe, pipeline, and transactions—each illustrated with clear Python redis‑py code examples.
This article introduces and compares ten widely used Python libraries for computer vision, including Pillow, OpenCV, Mahotas, Scikit‑Image, TensorFlow Image, PyTorch Vision, SimpleCV, Imageio, Albumentations, and timm, highlighting their features, typical use cases, and providing code examples for each.
This article presents a detailed overview of Python's unittest framework, covering test suites, decorators, parameterized tests, nested tests, dynamic test generation, loaders, exception assertions, subtests, setup/teardown, various assertion methods, test skipping, output capturing, asynchronous testing, and custom assertions, each illustrated with clear code examples.
Learn how to fetch real‑time COVID‑19 data from Baidu, then use Python’s pyecharts library to build province‑level maps and a dynamic timeline carousel, complete with code snippets and visual results for new, existing, cumulative, recovered, and death cases.
This tutorial explains how to read and write common file formats in Python—including text, JSON, Excel, XML, and INI files—covering append, overwrite, and read operations with clear code examples for each file type.
This article demonstrates how to build a colorful, music‑synchronized fireworks animation in Python using the Pygame library, covering module imports, window setup, color definitions, the Fireworks class implementation, and the main loop that renders and animates the fireworks effect.
This guide explains the difference between Python's shallow and deep copy mechanisms, shows the built‑in tools available, and provides ten concrete code examples covering lists, dictionaries, custom objects, tuples, sets and multi‑level nesting to help you choose the right copying strategy for reliable API test automation.
This article walks through a follower's Python question about filtering nested list titles for both "python" and "应用" keywords, presenting two clear solutions—regular list access and the operator module—complete with code snippets and result screenshots.
The latest TIOBE Index shows Python surpassing 18% for the first time, overtaking Java as the top language, while Java, C++, and emerging contenders like Rust and Kotlin shift positions, offering developers a strategic view of programming language popularity and future trends.
This article introduces LangGraph, a Python library for creating stateful, multi‑agent LLM workflows, explains its loop, persistence, and human‑in‑the‑loop features, shows how to install it, and provides a complete code example that builds, runs, and reuses a searchable AI agent with thread‑level state saving.
This article introduces cuDF, a Python GPU DataFrame library with a pandas‑like API, compares it to pandas, explains when to use cuDF versus Dask‑cuDF for single‑GPU or multi‑GPU workloads, and provides practical code examples for common data operations.
This article explains the fundamentals of Microsoft GraphRAG, details its indexing pipeline—including text chunking, entity‑relationship extraction, community detection, and description generation—shows how to set up the graphrag library, create adaptive prompts, build the index, and import the resulting graph into Neo4j for visualization and analysis.
The article presents a practical method for evaluating 1‑million‑token LLMs by inserting structured medal data into a classic Chinese novel, provides a full Python script for the test, shares results on GLM‑4‑long, and discusses training techniques and open‑source resources for long‑context models.
This tutorial demonstrates how to encode Python objects to JSON strings, decode JSON back to Python, read and write JSON files, pretty‑print and sort JSON output, handle special types with custom encoders, preserve key order, manage non‑ASCII characters, and process binary JSON data using the built‑in json module.
This tutorial demonstrates how to use Python's datetime and calendar modules to obtain the current date and time, convert dates to timestamps, perform date arithmetic, format and parse dates, generate date ranges, compare dates, and display monthly calendars, with clear code examples for each operation.
This article explains how to use Python scripts, the email and smtplib libraries, and MIME components to automatically send progress and completion notifications for long‑running tasks such as model training, data uploads, and financial simulations, including code examples and configuration details.
Learn the essential mobile app compatibility testing tools—including Appium, Calabash, Robot Framework, Selendroid, TestFlight, BrowserStack, and more—plus a practical Python unittest example that demonstrates how to verify element presence across devices and OS versions.
This tutorial shows how to create a Python script that crawls daily recipe pages, formats the content, and automatically sends it via email on a schedule, providing all necessary code and setup instructions.
This article explains how Python’s __new__, __init__, and __del__ magic methods work, shows when to use each, and provides step‑by‑step code examples—including singleton creation, inheritance initialization, resource cleanup, and metaclass usage—to help developers master object lifecycle control.
An extensive guide presents 17 practical Python scripts covering file management, web scraping, email handling, Excel processing, database interaction, system tasks, image editing, network automation, data cleaning, PDF manipulation, GUI automation, testing, cloud services, finance, and natural language processing, enabling readers to streamline workflows and boost productivity.
This article provides a comprehensive set of ten beginner-friendly Python string exercises covering indexing, slicing, step slicing, searching, replacing, concatenation, formatting, membership testing, length calculation, case conversion, and advanced topics like regular expressions, splitting, padding, stripping, digit checking, and practical text‑analysis examples.
Learn how to quickly launch a Stable Diffusion WebUI service in just five minutes using Volcengine’s cloud‑native continuous delivery platform, which abstracts Kubernetes complexities, provides pre‑configured AI templates, serverless VCI deployment, automatic scaling, API gateway access, and includes a Python client for image generation.
This article outlines the key benefits of automated testing frameworks, details a step‑by‑step design process, provides a practical Python‑Selenium example, and showcases real‑world applications in e‑commerce, mobile, and financial systems, illustrating how such frameworks accelerate development and improve software quality.
The latest TIOBE index shows Python surpassing 18% for the first time, overtaking Java's historic high, while PHP drops sharply, and the report explains the methodology, historical trends, and potential challengers like Rust and Kotlin.
This article walks through creating a Python‑based screen recorder on Windows 10 using Pillow for screenshots, OpenCV for video encoding, NumPy for frame processing, and pynput to control recording via hotkeys, including steps to install dependencies, calculate optimal FPS, and save MP4 files.
This article presents ten practical Python performance optimization techniques—including using generators, built‑in libraries, local variables, list comprehensions, efficient string joining, reducing loop work, multithreading/multiprocessing, JIT compilation, and profiling—to help developers write faster, more efficient code.
This tutorial explains how to build various colorful, popup-style progress bars for desktop applications using Python's Tkinter library together with tqdm or rich, covering installation, basic and styled examples, label integration, multithreading, and custom styling.
This guide walks you through extracting novel chapters from the Biquw.com website with Python, explaining how to obtain the book ID, retrieve the chapter list, download each chapter using requests and BeautifulSoup, handle common anti‑scraping measures, and organize the downloaded files.
This article walks through building a Python-based appointment elevator control system, covering platform setup, independent elevator design with detailed class implementations, a task‑oriented group‑control algorithm, and provides complete source code and diagrams for simulation and scheduling.
This article introduces Python's magic methods, explaining their roles in object-oriented programming, including __init__, __str__, __len__, and more, with practical code examples and outputs.
The article explains how Python's dict uses a hash table to provide constant‑time insertion, deletion, and lookup, demonstrates its speed advantage over lists with benchmarks, and details the handling of collisions, resizing, and the underlying array‑based implementation.
This article presents five beginner‑friendly Python projects— a number‑guessing game, a calculator, a word‑frequency counter, a simple ledger, and a chatroom—each with background, implementation steps, and complete source code to help new programmers practice core language concepts.
This article introduces Python's built-in os, os.path, and shutil modules, demonstrating how to create and delete directories, manipulate file paths, list directory contents, and perform advanced file operations such as copying, moving, and compressing files with clear code examples.
This tutorial demonstrates building a FastAPI‑powered “Moyu Office” page that dynamically shows today’s date, weekday, and the remaining days until the weekend and major Chinese holidays, using Jinja2 templates, the zhdate library for lunar‑solar conversion, and deployment behind Nginx.
This article explains the concepts of shallow copy and deep copy in Python, describes their differences, and provides numerous code examples—including lists, dictionaries, and custom classes—to demonstrate how to use the copy module’s copy and deepcopy functions effectively.
