This article explains how to build a text‑to‑image search system by first extracting text with OCR, then storing image paths and textual embeddings in a SQLite or Milvus vector database, and finally improving retrieval with Transformer‑based sentence embeddings and image‑captioning models.
This article introduces the major enhancements of Python 3.11—including structural pattern matching, improved type hints, faster execution via PEP 659, richer error messages, the new | dictionary‑merge operator, built‑in breakpoint debugging, and other standard‑library additions—illustrated with concise code examples.
This article walks through a Python string fundamentals question raised in a community group, presents a concise code solution provided by an instructor, demonstrates the successful output, and offers practical tips for asking clear programming questions.
Based on an analysis of over 14 million developer job postings from January 2022 to May 2023, the report identifies JavaScript/TypeScript, Python, Java, C#, PHP, C/C++, Ruby and Go as the eight most in‑demand programming languages, detailing their job share percentages and market trends.
This article presents thirteen practical Python scripts covering speed testing, Google searching, web automation, lyric retrieval, EXIF extraction, OCR, image cartoonization, recycle bin cleaning, image enhancement, Windows version detection, PDF-to-image conversion, hex‑to‑RGB conversion, and website status checking, each with clear explanations and ready‑to‑run code examples.
This guide explains how to programmatically download arithmetic captcha images, use OCR to extract and compute the expression, and automatically click the correct image on a website by combining Python requests, pytesseract, and Selenium for web automation.
Meta is backing PEP 703, which proposes adding a --disable-gil build option to CPython so that Python code can run without the Global Interpreter Lock, improving multithreaded performance on multi‑core CPUs, with Meta promising engineering resources to help implement it by 2025.
This article presents a collection of seven practical Python scripts—including a Zhihu image scraper, two interacting chatbots, a Naive Bayes poetry author classifier, a 35‑choose‑7 lottery generator, an automatic apology writer, a screen‑capture tool, and a GIF maker—each demonstrated with complete, runnable code.
This article reviews the most useful additions to the Python standard library—Pathlib, Secrets, Zoneinfo, Dataclasses, proper logging, f‑strings, Tomllib and Setuptools—explaining why they replace older modules, showing concise code examples, and offering guidance on adopting them in everyday projects.
This article explains how to leverage computer‑vision techniques and deep‑learning frameworks such as Transformers and TensorFlow to build a complete image‑classification pipeline, covering the underlying RGB and CNN principles, model architecture, data preparation, training, and inference with runnable Python code.
This article examines Python's widespread popularity, highlighting its rich ecosystem and rapid prototyping advantages while also critiquing its numerous formatting quirks, strict indentation, ambiguous special methods, verbose regex handling, limited immutable structures, community elitism, and the debate over whether the language is over‑hyped.
In this article, we explore a common NumPy issue where filling an array after casting still yields integers, explain why the original variable’s type persists, and show how reassigning the variable enables proper float filling, complete with code examples and practical tips.
Cython 3.0, announced by co‑developer Dr. Stefan Behnel after nearly five years, drops Python 2 support, aligns fully with Python 3 semantics, improves exception handling and C/C++ interoperability, and resolves compatibility issues that affected tools like the AWS CLI.
This article explores how large AI models can act as autonomous agents equipped with tools, demonstrates practical LangChain examples for remote server queries and RSS parsing, explains the ReAct reasoning‑acting loop, and shows how decorators and object‑oriented patterns enable seamless AI‑driven programming.
This step‑by‑step tutorial shows how to set up a GPU environment, prepare custom text data, train a tokenizer, configure and train a GPT‑2‑based large language model, test its generation, and run the entire pipeline using only 61 lines of Python code.
This article introduces LangChain, explains its modular architecture—including models, prompts, memory, chains, and agents—shows how to handle tokens and model selection, and provides complete Python code examples for building a conversational retrieval chatbot with OpenAI models.
This article explains how to build the input processing stage of a Transformer—including tokenization with Hugging Face tokenizers, token‑to‑embedding conversion using BERT models, custom BPE tokenizers, and positional encoding—providing complete Python code examples and test results.
This article provides Python code examples for using Redis as a database—including connection, basic CRUD, list and sorted set operations, key expiration, publishing/subscribing, distributed locking, and caching—followed by a detailed comparison of Redis and MySQL across data model, persistence, query capabilities, performance, scalability, and transaction support.
This article presents a collection of practical Python tricks—including handling multiple inputs, using all/any for condition checks, determining odd/even numbers, swapping variables, palindrome detection, inline if statements, removing duplicates, finding the most frequent element, list comprehensions, *args, enumerate, joining strings, merging dictionaries, creating dictionaries with zip, sorting dictionaries, reversing lists efficiently, and pretty‑printing data—each illustrated with clear code examples.
This article compares three popular Python OCR libraries—pyocr, pytesseract, and python‑tesseract—explaining their installation, basic usage, and how they can be applied in interface automation tasks to extract text from images, with code examples for each.
Learn how to use Redis with Python for basic CRUD, list and sorted‑set manipulation, key expiration, Pub/Sub messaging, distributed locks, and caching, and understand when Redis is a suitable complement or alternative to MySQL based on data model, performance, and transaction needs.
This article introduces the open‑source Airtest framework for mobile UI automation, outlines its cross‑platform features, and provides a complete Python script that automates an end‑to‑end e‑commerce purchase, payment, return, and refund process with test data cleanup.
This article explains the most common Python file extensions—including .py, .ipynb, .pyi, .pyc, .pyd, .pyw, and .pyx—describes their purposes, shows example code for each, and demonstrates how Cython can dramatically improve performance for computation‑intensive tasks.
This article provides a comprehensive reference for Airtest's automation APIs, covering script initialization functions, device connection methods, application lifecycle commands, and frequently used interaction utilities such as screenshot, touch, swipe, text input, and key events, each illustrated with Python code examples.
This tutorial demonstrates how to use Python's pygame library to build a dynamic fireworks simulation, covering module imports, window setup, color configuration, class definition for fireworks particles, and the main loop that renders the animated display.
Meta is promoting PEP 703, which proposes adding a --disable-gil build option to CPython so Python can run without the Global Interpreter Lock, and has pledged three engineer‑years by 2025 to help implement the change, while also noting its Threads product already runs on a heavily modified CPython backend.
This article shows how to divide a Python list into equally sized sub‑lists using a custom function and NumPy reshape, includes a complete code example, and offers practical tips for asking programming questions in community groups.
This comprehensive guide walks you through using Python to read, write, and modify Excel files with popular libraries such as xlrd, xlwt, xlutils, xlwings, openpyxl, XlsxWriter, win32com, and pandas, providing installation steps, code examples, and tips for each tool.
This article introduces Python's urllib module, explains its main submodules—urllib.request, urllib.parse, urllib.error, and urllib.robotparser—and provides practical code examples demonstrating URL opening, parsing, error handling, and robots.txt processing for interface automation tasks in Python.
The article dissects Meta's Threads app, detailing its explosive user growth, the mobile engineering choices for Android and iOS—including universal APKs, Jetpack Compose UI, and large share extensions—while also revealing the Python‑based Cinder backend, performance optimizations, startup profiling, and the extensive code sharing with Instagram.
This guide explains how to quickly capture network traffic from a mobile app using the Stream proxy, export the data as a HAR file, and then decode and parse the compressed responses with a short Python script to extract the desired JSON information.
This article introduces 68 commonly used Python built‑in functions across numeric, string, list, dictionary, tuple, set, and file operations, providing clear explanations and code examples to help programmers efficiently manipulate data types and improve coding productivity.
This article introduces ten widely used Python libraries—NumPy, Pandas, Matplotlib, Scikit‑learn, Requests, Beautiful Soup, Selenium, Pygame, Flask, and PyTorch—each accompanied by a concise real‑world project and complete code examples to help readers understand and apply them effectively.
This article explains how the Python libraries requests and xlwt can be combined to build a flexible API automation testing framework that reads test cases from Excel, executes HTTP requests, validates responses, and writes test results back to Excel files.
This article demonstrates how to automate testing of WeChat mini‑program interfaces by obtaining an access token, writing test cases with the Python requests library, and generating detailed, visually appealing test reports using the Beautiful Report library.
This article provides a collection of Python examples that demonstrate how to convert lists and strings to JSON, format dates and timestamps, read files, generate QR codes and barcodes, compare lists and JSON data, retrieve class methods via reflection, and automatically delete large files based on size and time.
This article provides a comprehensive guide on building a network port scanner using Python, covering implementation principles, code examples, and practical usage instructions.
OpenAI’s newly released Code Interpreter plugin lets ChatGPT write, run, and test code, offering file handling, a built‑in Python environment with popular libraries, and a secure sandbox, while showcasing ten impressive tricks—from converting GIFs to MP4s to turning data into interactive webpages.
This article introduces Python's ConfigObj library for parsing INI files, demonstrating how to read configuration values, write new settings, update existing entries, handle multiple files, and dynamically generate sections and options, with five practical code examples for API automation tasks.
This article explains how to utilize Python's config module for managing logging levels in interface automation, providing five practical code examples to demonstrate configuration of log levels, output paths, dynamic updates, format settings, and file backups.
This article introduces Python's built-in ConfigParser library, demonstrating how to read, write, update, handle multiple, and dynamically generate sections and options in INI configuration files through five practical code examples for interface automation tasks.
This article introduces the Python FuzzyWuzzy library, explains its Levenshtein‑based fuzzy string matching functions such as Ratio, Partial Ratio, Token Sort Ratio and Token Set Ratio, demonstrates how to use the process module for extracting best matches, and provides practical code examples for matching company and province names.
The article examines Meta’s Threads app, comparing its features and user experience with Twitter, and dives deep into the backend technologies—including Python 3.10, a custom Cinder JIT, Django customizations, and supporting services—that power the rapidly growing platform.
This article reviews the ten most popular backend frameworks for 2023—including Spring Boot, Django, Express.js, ASP.NET Core, Laravel, Ruby on Rails, Fiber, CakePHP, Flask, and Play—explaining their key features, language ecosystems, and recommended learning resources for developers of all levels.
This article introduces LangChain—a modular framework for constructing large‑language‑model applications—covering its core components, asynchronous support, prompt engineering, memory handling, chain and agent workflows, token considerations, embedding techniques, and a step‑by‑step Python example that culminates in a Gradio‑based conversational chatbot.
The article introduces the Command design pattern, explains its key roles such as Command, ConcreteCommand, Receiver, Invoker, and Client, outlines its advantages, and provides multiple Python code examples demonstrating light control, undo operations, file handling, shopping cart management, and menu actions.
This article explains the Object Factory design pattern, its benefits such as decoupling, extensibility, and centralized instance management, and demonstrates five practical Python examples covering basic product creation, configuration‑driven factories, logger factories, singleton factories, and object caching factories.
This article lists and briefly describes fifteen widely used design patterns in Python, including Singleton, Factory, Abstract Factory, Builder, Prototype, Adapter, Decorator, Proxy, Observer, Strategy, Template Method, Iterator, Chain of Responsibility, Command, and State patterns.
LangChain is an innovative framework that simplifies building language‑model‑driven applications by providing modular components such as models, prompts, memory, chains, and agents, with examples of asynchronous LLM calls, custom prompt templates, vector stores, token handling, and a simple Gradio chatbot implementation.
This article surveys a wide range of Python optimization tools—including NumPy, SciPy, Pandas, JIT compilers like PyPy and Pyston, GPU libraries, Cython, Numba, and interfacing utilities—explaining how they can accelerate code execution, reduce memory usage, and improve overall performance for single‑ and multi‑processor environments.
The article introduces LangChain, a framework that unifies language models, prompts, memory, retrieval, and tool‑driven agents into composable chains, illustrating its core components, code examples, end‑to‑end applications such as retrieval‑augmented QA and image generation, and outlining future uses in customer service, recommendation, and automated code review.
Scrapy is a powerful Python-based web scraping framework designed for large-scale and complex website data extraction. It offers high-level abstractions, built-in data extraction tools using XPath and CSS selectors, asynchronous processing for parallel requests, and flexible pipelines for data storage, making it ideal for efficient and scalable web scraping projects.
This article demonstrates how to use Python's requests library to call the YY live video API, parse the returned JSON for video URLs, download each video file, and store them locally, while also providing a complete reusable script for repeated batch downloads.
This guide explains how to combine ByteHouse's cloud‑native data warehouse with Apache Airflow to build scalable, automated, and easy‑to‑manage data pipelines, covering business scenarios, data flow, and step‑by‑step installation and DAG creation.
This article shows a step‑by‑step Python solution for finding the third last working day of any month, explaining the logic behind handling month‑end dates and weekend adjustments, and provides ready‑to‑run code for immediate use.
This article introduces several powerful Python libraries—Albumentations for image augmentation, MonkeyType for type inference, Bleach for HTML sanitization, Plotnine for data visualization, Returns for exception handling, ipdb for interactive debugging, and Virtualenv for environment isolation—detailing their use cases and providing example code for interface automation.
This guide explains how to use the argcomplete library to add Bash/Zsh auto‑completion for Python, pip, and other argparse‑based command‑line tools, including installation steps, activation commands, code integration for custom packages, and important usage cautions.
This article explains how to install and configure Redis, connect to it using Python's redis library, and demonstrates storing and retrieving various data structures—including strings, hashes, lists, sets, and sorted sets—followed by proper disconnection, providing a practical guide for Python developers.
This article introduces twenty commonly used Python magic (dunder) methods, explains their purpose such as object initialization, representation, iteration, arithmetic, and context management, and provides clear code examples for each to help developers apply them in real‑world automation tasks.
June 2023’s TIOBE Index reveals Python’s share slipping to 13% amid rising competition from C, Java, and C++, while AI-driven demand still fuels its popularity, and introduces two newcomers—Microsoft’s X++ and the versatile Raku—highlighting shifting trends in programming language usage.
This tutorial walks through building a Python command‑line movie ticket reservation system, covering data structures for film information, seat‑booking class design, user interaction for selecting seats or the front‑most available seat, and a controller that ties the film selector and seat booking together.
This article demonstrates how to use Redis as a database with Python code examples for basic operations, advanced features like pub/sub and distributed locks, and compares Redis to MySQL across data model, persistence, query capabilities, performance, scalability, and transaction support.
This article presents a collection of lesser‑known Python tricks—including string normalization, iterator slicing, keyword‑only functions, custom context managers, memory‑saving __slots__, CPU/memory limits, import control with __all__, and simplified ordering with total_ordering—to help developers write cleaner and more efficient code.
This guide explains how to use the open‑source binlog_parse_sql tool to parse MySQL 8.0 binary logs, generate SQL statements, and seamlessly migrate data to MariaDB or ClickHouse, covering installation, execution modes, troubleshooting, and practical ETL scenarios.
This article presents a concise, categorized guide to frequently used Python 3 standard library modules—including text processing, file handling, networking, data manipulation, concurrency, time/date, mathematics, and system utilities—each accompanied by clear explanations and runnable code snippets.
The article explains how Python now exists as both a typed and an untyped language, discusses the distinction between infrastructure and business‑logic code, and argues that embracing both approaches—using type hints for business logic while keeping infrastructure code flexible—benefits developers and the community.
This article provides a comprehensive overview of Python package management tools—including PyPI, setuptools, pip, virtualenv, and conda—explaining their purposes, core features, and basic usage commands for creating, sharing, and managing Python packages and environments.
This guide shows how to install, import, and use the JMESPath and JsonPath Python modules to perform basic and advanced queries on JSON data, including example scripts that filter, sort, and extract specific fields.
DeepKE-LLM is an open‑source, extensible knowledge‑graph extraction framework that leverages large language models for entity, relation, and attribute extraction, supports multiple LLMs, provides installation scripts, various usage modes, fine‑tuning pipelines, and integrates with the KnowLM project for advanced instruction‑following capabilities.
This tutorial walks through creating a Chrome extension that captures images from web pages, sends them to a Python‑backed Tesseract OCR engine, and displays the recognized text, covering the plugin's file structure, manifest configuration, JavaScript code, HTML UI, CSS styling, and installation steps.
Python's lambda (anonymous) functions, despite being limited to a single expression, can be employed in a variety of practical scenarios such as mapping, filtering, sorting, reducing, zipping, decorating, and implementing strategy patterns, as illustrated by ten concise code examples.
This article walks through solving Python web‑scraping captcha challenges by using Selenium to capture the image, applying OCR for recognition, and offering alternative request‑based methods, while also addressing common driver version mismatches.
This tutorial explains how to scrape a news article with Python, segment Chinese text, count word frequencies, and visualize the top ten words using a word cloud and a pie chart, providing complete code and sample results.
This article introduces how to build a Chrome extension using Python to convert JSON data to FormData format and vice versa, improving development efficiency through browser-based data format conversion.
This tutorial explains how to develop a Chrome extension that assists developers in locating web page elements and generating XPath expressions by outlining the plugin's structure, providing complete configuration files, JavaScript code, HTML/CSS UI, and step‑by‑step instructions for loading and testing the extension.
The TIOBE June 2023 ranking shows Python's share dropping to 13% amid rising competition from C, Java and C++, while AI-driven growth and new entrants like X++ and Raku highlight shifting trends in programming language popularity.
This article demonstrates how to use Python's concurrent.futures module to parallelize image resizing, turning a single‑process script into a multi‑core solution with just three additional lines of code, achieving up to a six‑fold speed‑up on typical CPUs.
This article walks through converting a high‑precision timestamp like "2022-03-25 08:00:00.000000000" into a readable Chinese date format using Python's datetime module, offering simpler alternatives to cumbersome string‑splitting tricks.
This article provides a step‑by‑step guide to creating a Google Chrome extension using Python and Flask that validates JSON data on the current page, covering prerequisite setup, project structure, manifest configuration, content and background scripts, backend server implementation, and testing procedures.
This tutorial walks you through installing Elasticsearch 8.x, generating sentence embeddings with Python, creating a dense_vector index, bulk‑loading documents, and performing both exact and approximate k‑nearest‑neighbor queries using script_score and the built‑in knn API.
This article provides a step-by-step guide to creating a Google Chrome extension that captures full-page screenshots, detailing the required project structure, manifest configuration, JavaScript background and content scripts, and a Python Selenium script for automated screenshot capture and saving.
This article demonstrates how to use Python to create an automated piano script that simulates keyboard presses, employs multithreading to play multiple hands simultaneously, and controls a web‑based piano interface, providing complete code examples and step‑by‑step instructions.
This tutorial explains how to create a web‑based tool that generates batch mock data of various types—including names, ages, genders, ID numbers, phone numbers, emails, and bank cards—by implementing a Flask backend API and a Vue.js frontend interface, complete with setup, code examples, and deployment steps.
This guide explains how to add, manage, and persist asynchronous scheduled jobs in a FastAPI application using APScheduler's AsyncIOScheduler with SQLite storage, covering task types, code examples, limitations, and alternative solutions such as arq, fastapi‑utils, and Celery.
This tutorial demonstrates how to build an efficient Excel data merging tool using Python Flask for the backend and Vue.js for the frontend, featuring template download, batch upload, progress tracking, and merged file path display.
This article introduces a variety of Python optimization tools—including NumPy, SciPy, Pandas, JIT compilers like PyPy, GPU libraries, Cython, Numba, and interfacing utilities—explaining how they can make code more concise, faster, and better suited for single‑processor or multi‑processor execution.
This guide introduces Scanless, a Python‑based tool that leverages third‑party online scanners to conduct anonymous port scans, explains how to install it via Git and pip, demonstrates command‑line usage and Docker support, and lists the supported scanning services.
The TIOBE June 2023 ranking reveals Python still leading but slipping to 13% share, while AI-driven popularity, emerging languages X++ and Raku, and the steady rise of C, C++, and Java reshape the top‑10 programming language landscape.
This tutorial walks through creating a web-based timestamp conversion utility that transforms second‑ and millisecond‑level timestamps to dates and vice versa, using a Flask backend API and a Vue.js frontend with styled HTML and CSS.
This article explains five common methods for storing authentication tokens during API automated testing—embedding in scripts, using environment variables, configuration files, databases, and secret management systems—and provides complete Python code samples for each approach.
This article provides a thorough walkthrough of advanced Pandas techniques—including complex logical queries, data‑type conversion, sorting, adding or modifying rows and columns, sophisticated filtering, iteration methods, and various function‑application utilities—complete with practical code examples for each operation.
The article reviews the newly released Python book “From 0 to 1”, exposing dozens of factual and conceptual errors ranging from variable naming rules and misuse of triple‑quoted strings to incorrect explanations of built‑in functions, and warns readers to avoid the book while offering free Python learning resources.
This article presents a detailed OTA (Over‑the‑Air) testing framework covering preparation, functional test points, upgrade strategies, data consistency, compatibility, performance load testing, and Python‑based automation for IoT devices, helping engineers avoid missed cases and ensure reliable firmware upgrades.
This tutorial explains how to install and use the Python Paramiko library to establish SSH connections to Linux servers from Windows and Mac terminals, enabling execution of Linux commands remotely and improve server management efficiency.
This article explains how Python decorators can abstract common functionalities such as logging, authentication, and performance monitoring in API automation testing, providing code examples, recommended use‑cases, and a complete demonstration that integrates logging and MySQL data storage to improve test efficiency and maintainability.
Robusta KRR is a local CLI tool that gathers pod metrics from Prometheus, recommends CPU and memory requests and limits, supports custom strategies, and can be installed via Homebrew or source, helping Kubernetes clusters cut up to 69% of cloud costs.
This article introduces ten essential Python libraries and frameworks, providing practical examples and code implementations for each to help readers understand and master their applications in various domains.
This tutorial walks developers through setting up an OpenAI account, obtaining an API key, configuring the Python environment, and writing a complete Python script that uses the ChatGPT API to create an interactive chatbot, complete with code examples and execution tips.
This article chronicles the life and career of Guido van Rossum, the creator of Python, detailing his early fascination with computers, the birth of Python in 1989, its evolution across various domains, his roles at Google and Dropbox, retirement, and recent return to Microsoft, while also offering a free Python learning resource.
This guide demonstrates how to set up a Flask backend service providing message APIs, install and configure Vue.js for the frontend, create components for displaying and submitting messages, and run both servers to produce a functional online message board.
