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 details an open‑source Binance trading bot that uses machine‑learning models and extensive feature‑engineering pipelines to generate and broadcast automated cryptocurrency buy‑sell signals via a Telegram channel, covering data acquisition, offline training, hyper‑parameter tuning, and live service deployment.
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.
This article introduces the importance of image watermarking for copyright protection and provides a step‑by‑step Python tutorial using the Pillow library, covering installation, basic usage, a script for batch watermarking, and advanced techniques such as dynamic watermarks and automated folder monitoring.
This article explains Python tuples as immutable list subsets, details their C‑level struct layout, creation and deallocation processes, the internal freelist cache for lengths up to 20, performance advantages over lists, and the special handling of the empty tuple singleton.
This article provides a thorough overview of Python file handling, covering opening and closing files, absolute and relative paths, various file modes, reading and writing techniques, pointer manipulation, file copying, CSV I/O, in‑memory streams with StringIO/BytesIO, and serialization/deserialization using JSON and pickle modules.
An in-depth guide to Python's queue module, covering thread-safe queue classes, their usage in multithreaded programming, common methods like put, get, task_done, join, and practical code examples demonstrating producer-consumer patterns and bounded queues.
This tutorial introduces Python's built‑in Turtle graphics library, explaining how to configure the drawing canvas, use pen functions, draw shapes, apply fill colors, write text, and create animated balloon objects with movement and rendering loops for a festive visual program.
This article demonstrates a simple Python method for identifying and removing duplicate files by leveraging the built‑in os module, explaining how to list directory contents, construct file paths, and use os.remove() to delete unwanted copies, complete with example code and usage notes.
This article explains Python's four variable scope types—local, enclosing, global, and built‑in—through clear descriptions and runnable code examples that illustrate how each scope affects variable accessibility and program behavior.
This tutorial presents a detailed overview of over fifty core NumPy functions, covering array creation, reshaping, arithmetic, statistical analysis, set operations, splitting, stacking, printing, and data persistence, with clear explanations and complete code examples for each operation.
This article walks through the CPython source code that defines list’s built‑in methods—append, insert, pop, index, count, remove, reverse, clear, and copy—explaining how each method is wired into the type object, the underlying C logic, time‑complexity characteristics, and common pitfalls such as reference‑count handling and shallow versus deep copying.
This article compiles 19 practical Linux, security, networking, and Python interview questions covering command‑line techniques, system monitoring, load‑balancing, HTTP protocols, common vulnerabilities, TCP handshakes, TIME_WAIT optimization, and code snippets to help candidates prepare for sysadmin roles.
This article explains how to generate the iconic green falling‑character “code rain” effect from The Matrix in a terminal using Python, detailing the required script, ASCII character set, matrix update logic, and optional ANSI color enhancements.
This article introduces fifteen of the most useful Python libraries—including Dash, Pygame, Pillow, Requests, and BeautifulSoup—explaining their core features and typical use cases, making it a concise guide for developers seeking to expand their Python toolkit.
This article explains how Python's dataclasses module, combined with the typing library, can automatically generate boilerplate methods, provide rich type annotations, support optional and union types, enable dictionary serialization, perform runtime checks, and be extended with field metadata for robust, maintainable code.
This guide introduces the open‑source Realtime Voice Cloning project, explains its key features, and provides detailed installation and usage instructions—including environment setup, dependency installation, cloning the repository, and running the demo tool—to enable real‑time voice transformation with Python.
This tutorial demonstrates how to use Python's Matplotlib library to create five essential data‑visualization charts—simple bar, pie, donut, stacked bar, and Pareto—by installing the library, explaining each chart’s purpose, and providing ready‑to‑run code examples.
This guide explains why random User-Agent headers improve API automation testing, introduces the Python fake_useragent library, shows how to install it, and provides comprehensive example code for generating, validating, and persisting random User-Agent strings.
The Numpy‑ML project, created by UC Berkeley’s David Bourgin, provides a comprehensive pure‑NumPy implementation of over 30 machine‑learning algorithms—including probabilistic models, neural‑network layers, optimizers, and reinforcement‑learning agents—along with extensive data‑preprocessing utilities, all in a single open‑source repository.
This article explains how to use Python to build a Zha Jin Hua card‑game simulator, covering the game rules, hand‑type definitions, scoring logic, player management, statistical analysis of 100 000 rounds, and provides the complete source code with detailed comments.
This guide explains how to set up httprunner 4.x, write YAML/JSON test cases, run them, use parameterization and environment variables, and generate HTML reports for efficient Python API automation testing.
This article reviews the lack of a standard Python project layout and compares four popular tools—CookieCutter, PyScaffold, PyBuilder, and Poetry—by showing their installation commands, generated directory structures, and typical build/test workflows.
This article explains how to implement human skin color detection in Python with OpenCV, covering library installation, basic image operations, and three algorithms based on YCrCb and HSV color spaces, including code examples, parameter choices, and visual results.
This article provides a comprehensive overview of Python multithreading, covering basic concepts, the _thread and threading modules, thread creation methods, synchronization primitives like Lock and RLock, thread-local storage, thread pools, and the differences between multithreading and multiprocessing for both CPU‑bound and I/O‑bound workloads.
Python 3.8 introduced the walrus operator (:=), a concise assignment expression that allows in-line variable assignment within expressions, and this article explains its purpose, benefits, and provides ten practical code examples illustrating its use in loops, comprehensions, conditionals, and function calls.
This article reviews a wide range of Python IDEs and code editors—including PyCharm, VS Code, Sublime Text, Vim, Emacs, IDLE, and many others—detailing their features, compatibility, advantages, disadvantages, and download links to help developers choose the most suitable environment for their needs.
This article provides 10 detailed Python code examples demonstrating how to connect to, query, insert, update, delete, and manage MySQL databases with proper error handling and resource management.
This article walks through a Python community member's question about configuring a Matplotlib contour plot's colorbar to display values from 0 to 17, presents two code attempts, and provides a working solution using a custom ScalarMappable with defined tick levels.
This article walks through the author’s experience creating a custom AI agent using LangChain and OpenAI APIs, explains the concepts of AI agents and the ReAct reasoning framework, provides step‑by‑step code, discusses required libraries and APIs, and shares practical tips and challenges encountered.
This article provides a series of Python code examples demonstrating how to perform API automation testing tasks—including GET and POST requests, authentication, file uploads, redirects, unit testing with unittest and pytest, response mocking with responses, and response schema validation with jsonschema—offering practical guidance for backend testing.
The article provides ten code examples demonstrating how to validate JSON data with Python's jsonschema library, covering basic validation, required fields, nested schemas, arrays, uniqueness, enums, ranges, pattern matching, conditional logic, and custom error messages.
This article introduces Python's re module and demonstrates ten practical regular‑expression examples—including basic matching, email extraction, finding multiple patterns, substitution, anchoring, wildcard matching, grouping, repetition, non‑greedy matching, and look‑behind—complete with code snippets and expected outputs.
This article introduces Python's essential keywords, explaining their purpose and demonstrating ten practical code examples that cover conditional statements, loops, functions, classes, exception handling, file management, module imports, return values, infinite loops with break, and extended conditional branches.
This tutorial walks through creating a Coze bot that fetches a Juejin author's information and articles via web scraping, processes the data to generate a concise author profile, identifies expertise domains, ranks hot articles, and finally publishes the bot for interactive use.
This article explains Python's reflection and metaprogramming features, demonstrating how to inspect objects, dynamically invoke methods, create classes, use metaclasses, decorators, exec, inspect signatures, and other advanced techniques through ten clear code examples.
Mem0 is an open‑source memory‑management middleware for large language models that provides dynamic, context‑aware, and adaptive memory, outperforming traditional Retrieval‑Augmented Generation (RAG) and enabling personalized AI assistants, travel planners, and support agents with concrete Python APIs and examples.
This article demonstrates ten practical methods for handling dynamic parameters in Python API automation testing, covering dictionaries, loops, pytest parametrization, fixtures, unittest, decorators, generators, class attributes, reflection, and external data sources like CSV.
This article explains how Bayesian Network models can be built and applied to forecast public opinion reversals, detailing the network structure, joint probability distribution, inference methods, and a Python implementation using pgmpy with sample data and analysis of key influencing factors.
This article introduces Python's functools.partial, explaining how fixing certain function arguments creates new callable functions, and demonstrates ten practical examples ranging from mathematical calculations and file handling to HTTP request wrapping, decorator parameterization, multiprocessing, GUI event binding, logging, data validation, and configuration parsing.
This article provides a comprehensive guide to Python's eval() function, covering its syntax, parameters, execution process, differences between globals and locals, dynamic versus static execution, common use cases, security risks, and alternatives such as ast.literal_eval() and exec().
This article explains the concept of higher‑order functions in Python, illustrating their flexibility and reusability through ten practical examples—including map, filter, reduce, decorators, partial, and itertools—while providing complete code snippets for each use case.
This article provides a comprehensive, step‑by‑step tutorial on Python's built‑in debugger Pdb, covering its purpose, how to start it, essential commands, practical debugging examples, advanced features like conditional breakpoints and stack inspection, and tips for improving debugging efficiency.
This article explains PaddlePaddle tensor indexing, covering basic slicing, integer and boolean advanced indexing, ellipsis and newaxis usage, assignment in dynamic and static graphs, automatic gradient propagation, and demonstrates practical applications such as semantic segmentation, object detection, and NLP sequence masking.
This article introduces seven powerful Python libraries—Pandas, Selenium, Flask, Scrapy, Requests, Faker, and Pillow—explaining their core features, typical use cases, and providing ready‑to‑run code snippets to help developers boost productivity and automate routine tasks.
This tutorial explains how to construct XML data in Python, set the appropriate Content-Type header, send it via a POST request using the requests library, and parse the XML response, providing complete example code for developers working with web APIs.
