This article explains how circular references cause memory leaks in Python, describes the role of reference counting and the cyclic garbage collector, and provides practical examples using the weakref and gc modules to create weak references, detect, and manually manage cyclic garbage.
This article walks through a Python pandas solution that groups a dataset by multiple fields, orders rows by end time, and retains only the first record when successive end times are within a 20‑second window, complete with optimized code snippets and explanations.
This guide demonstrates how to build a Python API automation testing suite using requests, pytest, and pytest‑html, covering environment setup, project structure, common utilities, test case implementation, advanced assertions, error handling, test data management, and HTML report generation.
This article explains how to group a dataset by multiple columns, sort each group by an end‑time column, and keep only the first record when consecutive timestamps differ by less than 20 seconds, using a concise Pandas solution.
This article presents ten practical Python tips and tricks, covering list comprehensions, efficient list traversal, element swapping, list initialization, string construction, tuple returns, dictionary access, library usage, slicing and stepping, and indentation best practices, each illustrated with clear code examples.
This article introduces key Python libraries for data analysis, visualization, statistical modeling, and machine learning—including NumPy, Pandas, Matplotlib, Seaborn, SciPy, Statsmodels, Scikit-learn, BeautifulSoup, TensorFlow, and Plotly—each accompanied by concise code examples demonstrating their core functionality.
This article explains how to list all file names in a specified folder with os.listdir and os.path.isfile, shows a concise list‑comprehension version, and demonstrates how to retain only the largest ZIP file by sorting and deleting others using Python's os and glob modules.
This article provides a comprehensive overview of Python's object‑oriented programming features, covering classes, class and instance variables, methods, inheritance, method overriding, built‑in class attributes, and garbage collection, supplemented with clear code examples and explanations.
This article walks through a Python regular‑expression solution for matching semi‑finished product identifiers like “半成品（广州）1#” or “半成品（北京）2#”, explaining the pattern, its components, and how to apply it in practice.
The article explains how Python’s speed limitations can be overcome with PyPy’s just‑in‑time compilation, presenting a performance test that shows PyPy outpacing both the standard interpreter and even compiled C code, and details the underlying differences between JIT, AOT, and interpreted execution.
This article introduces MonkeyRunner, an Android automation tool, and demonstrates its use in basic operation testing, app installation and removal, UI interaction, and performance measurement with clear Python‑style code examples for each scenario.
This tutorial walks you through the complete process of configuring the Mirai ecosystem, installing mirai-console-loader, handling login verification with Selenium, setting up mirai-api-http, configuring OpenJDK, and finally writing and running a Python bot using graia-application-mirai, providing detailed screenshots and code snippets.
This article explains how to install pycryptodome (or pycryptodomex) to perform SM2 signing and verification in Python, provides complete code examples, and offers guidance for ensuring compatibility with Java's Bouncy Castle SM2 implementation.
This article explains how to write a Python crawler that uses the WeChat public platform's open API to obtain an access token, retrieve the list of articles from a specified public account, and extract each article's title, summary, and link for further analysis.
This tutorial walks you through installing Pygame, setting up the game window, loading assets, defining tank and bullet sprites, implementing the main loop, and running a complete Python‑based 2D tank battle game with full source code.
The article explains why Python’s 0.1 + 0.2 does not equal 0.3 due to binary representation limits, discusses the impact of tiny rounding errors on equality checks, and recommends using tolerance thresholds or the Decimal module (initialized with strings) for accurate numeric computations, especially in finance.
This article provides Python implementations and usage examples for a range of encryption and decryption techniques—including AES, RSA, Caesar cipher, Base64, SHA‑256/HMAC, Blowfish, DES, ChaCha20‑Poly1305, and XOR—along with notes on required libraries and security considerations.
This article introduces a collection of lesser‑known Python tricks—including ternary operators, enumerate, zip, list comprehensions, lambda functions, any/all, itertools, generators, decorators, argument unpacking, dynamic imports, dictionary comprehensions, and mutable data structures—providing concise explanations and runnable code examples to boost coding efficiency.
This article presents ten practical Python automation scripts—including HTML parsing, QR code scanning, screenshot capture, audiobook creation, PDF editing, StackOverflow querying, mobile phone control, CPU/GPU temperature monitoring, Instagram uploading, and video watermarking—to help automate repetitive tasks and boost productivity.
This article introduces Requestium, a Python library that merges Selenium and Requests, and provides step‑by‑step examples covering basic session setup, installation, dynamic content handling, user interaction simulation, cookie and header management, asynchronous fetching, iframe switching, alert handling, and screenshot or video recording.
Streamlit is a free, open‑source Python framework that lets machine‑learning engineers quickly turn scripts into interactive web apps, featuring top‑to‑bottom script execution, widget‑as‑variable handling, caching, GPU support, and seamless integration with tools like Git.
This article presents a comprehensive guide to advanced Python topics—including exception handling, the collections and itertools modules, lambda functions, decorators, generators, process/thread basics, dunder methods, logging, and context managers—providing code examples and explanations to help developers deepen their expertise.
This article explains why recording and replaying HTTP interactions with Betamax is essential for automated testing, outlines its benefits such as consistency, efficiency, error reduction, regression support, and provides multiple advanced code examples for custom recording modes, request filtering, cassette control, context‑manager usage, and handling dynamic content.
This article introduces essential Python built‑in functions such as map, filter, reduce, sorted, any, all, zip, enumerate, reversed, chr, max, min, sum, join, list, tuple, set, frozenset, type and dir, explaining their purpose and providing concise example code for each.
This article walks through a common Matplotlib title garbling issue caused by encoding settings, explains why the 'encoding' argument triggers an AttributeError, and provides a concise code fix using font configuration to display Chinese characters correctly.
This article introduces the Python profig library for converting configuration files between YAML, JSON, and INI formats, providing five practical code examples for interface automation work.
This article explains Python's dynamic class creation and modification techniques—including the type function, metaclasses, and class decorators—through ten practical code examples that demonstrate how to build flexible, maintainable, and powerful object‑oriented designs.
This tutorial explains how to install the gym and highway‑env packages, configure the highway‑v0 environment, explore its observation types, and implement a DQN agent in Python to train and evaluate autonomous driving policies, complete with code snippets and performance visualizations.
This article explains how to automatically rotate Matplotlib X‑axis labels based on their length, using the rotation property, and provides a concise implementation along with tips for asking clear programming questions in community groups.
This article introduces ten popular Python visualization and GUI libraries—Matplotlib, Seaborn, Plotly, Bokeh, Altair, Plotnine, VisPy, Pygame, Kivy, and PyQt/PySide—providing concise code examples and brief explanations of their typical use cases and strengths.
The article introduces the second version of phpy, a PHP extension that embeds a Python interpreter, explains its dual‑VM runtime architecture, shows how to use it under PHP‑FPM, presents detailed performance benchmarks, covers exception handling, IDE auto‑completion, compilation options, dynamic‑library troubleshooting, and provides numerous code examples for testing and scientific computing.
Real‑time monitoring of CPU, memory, disk I/O and network bandwidth during performance testing helps identify bottlenecks, prevent crashes, collect actionable data, ensure accurate results, and meet SLA requirements, and a Python script can automate data collection and storage in MySQL.
This article walks through a common Matplotlib pie‑chart issue—displaying color legends below the chart and showing percentages outside—by presenting the problem, solution screenshots, and concise explanations to help Python users implement the fix.
This step‑by‑step guide shows how to install and configure a single‑node Hadoop 3.2.0 environment on CentOS 7, set up Python 3.7, write MapReduce mapper and reducer scripts in Python, and run a word‑count job using Hadoop streaming, illustrating core Hadoop concepts and their relevance today.
This article introduces regular expressions, explains Python's re module and its core functions such as match, search, and sub, and demonstrates their usage with clear code examples and visual illustrations of special syntax, character classes, and grouping constructs.
This tutorial walks you through Hadoop’s core components, sets up a single‑node Hadoop cluster on CentOS 7, installs Python 3, writes mapper and reducer scripts in Python, and runs a Hadoop‑Streaming word‑count job to demonstrate classic big‑data processing techniques.
This article explains Python's magic (special) methods such as __init__, __str__, __getitem__, __setitem__, __len__, __eq__, __iter__, __next__, __enter__, __exit__, __call__, and __del__, providing clear descriptions and runnable code examples for each in Python programming.
Python automatically manages memory through garbage collection, and this article explains how the garbage collector works and presents ten practical techniques—including manual gc calls, generators, sys.getsizeof, slice copying, del statements, sys.intern, NumPy, pandas, reference counting, and __slots__—to reduce memory usage and improve performance.
This article introduces ten Python visualization libraries—ranging from the classic Matplotlib to newer tools like Plotly and Leather—detailing their features, typical use cases, developer backgrounds, and how they complement each other for creating static, interactive, and geographic visualizations across various fields.
This article presents several advanced Python debugging and performance optimization techniques—including using assert statements, interactive pdb debugging, cProfile profiling, generator expressions, dictionary/set lookups, appropriate data structures, and functools.lru_cache caching—to help developers write more efficient and reliable code.
This article walks through how to combine twelve distinct pandas DataFrames into a single Excel worksheet, inserting two blank rows between each table, by determining the current sheet’s last occupied row and appending data accordingly, complete with code snippets and visual guidance.
This article presents ten practical Python examples illustrating lazy evaluation using generators and iterators, covering infinite sequences, large data processing, file streaming, and on-demand computation, highlighting memory efficiency and performance benefits for handling big data and infinite streams.
This article walks through a practical solution for combining twelve distinct pandas DataFrames into a single Excel worksheet, inserting two blank rows between each table, and offers alternative approaches using CSV intermediate files, complete with code snippets and visual examples.
This article explains how to implement online traffic replay for Python automated testing by parsing logs, storing request data in a local MySQL database, analyzing user information with data‑analysis libraries, and locally persisting URL, method, headers, and body details using JSON files, complete with sample code.
This article explains Python generator expressions and list comprehensions, highlighting their role in functional programming, providing syntax details, and presenting ten practical code samples that demonstrate how they simplify code and improve readability.
This article walks through a step‑by‑step Python solution for scraping Shanghai Gold Exchange transaction data, using requests_html to collect URLs, pandas to parse HTML tables, and finally exporting the aggregated results to Excel, while also offering practical tips for sharing code and debugging.
This tutorial demonstrates a complete workflow for building credit‑card user profiles by first extracting and transforming the KDD99 dataset with SQL, then applying Python libraries such as pandas, matplotlib, and seaborn to perform descriptive statistics and produce visualizations of demographic, transaction, and financial characteristics.
This article presents a comprehensive overview of Python's 68 built-in functions up to version 3.6.2, categorizing them into twelve groups such as numeric operations, data structures, scope, iterators, I/O, memory, file handling, modules, and more, with clear code examples.
This article walks through a real‑world Pandas tutorial where a single‑column Excel file is reshaped into 13 columns, duplicate rows are removed, column headers are set, and timestamps from a second workbook are merged, highlighting the challenges of aligning data without a unique key.
Using Tencent's Hunyuan model, the tutorial walks through a Python workflow that scrapes a student‑score table from a web page, saves it as CSV and Excel, cleans missing values, computes total and average scores, and visualizes their distributions with matplotlib, illustrating how LLMs can accelerate data‑analysis coding while still needing human verification.
This article introduces Python's multiprocessing module and the Celery task queue, explains their core concepts, and provides practical code examples for multi‑process parallel computation, inter‑process communication, asynchronous execution, scheduled jobs, result callbacks, retries, and distributed task orchestration.
This guide walks you through installing PHPY on Ubuntu, covering the required environment setup, building PHP 8.3 from source, installing Anaconda and a Python 3.10 environment, compiling the PHPY extension, configuring php.ini, verifying the installation, and running a sample script that accesses Python's os module from PHP.
This guide demonstrates how to use the TestProject Python SDK to automate a complete e‑commerce workflow—including user registration, login, profile setup, product browsing, purchase, payment, and order verification—through a detailed Python script with Selenium‑style commands and handling of common automation challenges.
Released on December 4, Django 5.0 brings full support for Python 3.10‑3.12, introduces field groups for streamlined form rendering, adds facet filters in the admin, offers new database defaults and generated fields, enhances choice declarations, and includes numerous minor improvements while noting backward‑incompatible changes.
phpy is an open‑source Swoole project that lets PHP import and use Python packages—including popular AI and scientific libraries—by providing a PHP extension or a Python C module, with detailed installation steps, usage examples, and support for callbacks and named parameters.
This article introduces phpy, a PHP‑Python bridge library from Swoole, explains its purpose of filling gaps in the PHP ecosystem, provides step‑by‑step compilation and installation instructions, and demonstrates how to call Python packages, handle callbacks, and build GUI or AI applications from PHP code.
This article demonstrates how to apply the SLSA (Supply chain Levels for Software Artifacts) framework to the Python ecosystem by building clean packages, generating provenance statements, uploading them to PyPI, and verifying the package origin using GitHub Actions and the slsa‑verifier tool.
This guide explains how to use Python's config module to load log levels, set output paths per environment, dynamically update logging settings, control log formats, and configure file backup, providing five practical code examples for robust API automation logging.
This article shows a quick Python tip for reading a key from the user and safely fetching its value from a dictionary using the get method, while warning about variable naming pitfalls and providing a ready-to‑run code example.
This article explains the concept of monkey patching in Python, demonstrates how to replace the built‑in json module with the faster ujson library using a simple runtime patch, and shows performance improvements through code examples and timing tests.
This article walks through a Pandas date‑time issue where a user wants to extract the month from a date column and concatenate the Chinese character "月", providing a clear code solution and practical tips for similar data‑processing tasks.
This tutorial explains how to use Python with requests and BeautifulSoup to locate image URLs in a webpage's HTML, extract them via regular expressions, and programmatically download all images to a local folder in an automated batch process.
This article demonstrates how to scrape a news webpage with Python, extract and segment its Chinese text using jieba, count word frequencies, and visualize the top ten terms as a word cloud and a pie chart with pyecharts.
ULID (Universally Unique Lexicographically Sortable Identifier) offers a 128‑bit, time‑based and random identifier that is URL‑safe, sortable, and more collision‑resistant than UUID, with detailed specifications, binary layout, and Python usage examples including generation, conversion, and component extraction.
This article walks through a Python web‑crawler error reported in a community chat, shows the original code snippet, explains how downgrading the Python version resolved the issue, and offers practical tips for sharing reproducible examples when seeking help.
This article provides a comprehensive overview of PyMuPDF, covering its relationship to MuPDF, core features, installation methods, import conventions, and detailed usage examples for opening documents, handling pages, extracting text and images, and performing PDF-specific operations such as merging, splitting, and saving.
This article introduces ten popular Python libraries for computer vision, describing their main features, typical applications, and providing concise code examples to help beginners and practitioners quickly choose and use the right tools for image processing and deep learning tasks.
This article guides readers through designing and implementing a basic Python interpreter that can evaluate arithmetic expressions by defining tokens, writing a lexer and parser with PLY, specifying BNF grammar, handling precedence, and assembling a runnable program that processes user input.
This article introduces Ryven, a Python‑based visual programming environment that lets users see real‑time feedback while manipulating matrices, explains its data‑flow and execution‑flow modes, provides setup instructions, and shares background about its creator.
This article walks through a pandas data‑processing question where a one‑column DataFrame is grouped every five rows and reshaped into five columns, presenting two Python solutions—including list slicing and groupby aggregation—along with clear code examples and explanations.
This article explains how to build a Text‑to‑SQL application using LangChain, OpenAI LLMs, and SQLDatabaseChain, covering the fundamentals of Text2SQL, LangChain components, code examples, and a practical SQLite case that transforms natural‑language questions into executable SQL queries.
This article introduces Python coroutines and asynchronous programming using the asyncio module, explains key concepts such as event loops and non‑blocking I/O, and provides ten detailed code examples that demonstrate creating, managing, and synchronizing async tasks for improved performance.
This article presents fifteen practical Python techniques—including multi‑key sorting, data classes, list comprehensions, memory inspection, frequency analysis, dictionary merging, multiple return values, filter/map/zip usage, list reversal, element existence checks, flattening nested lists, and uniqueness verification—to help developers write cleaner, faster, and more readable code.
This article describes a Python script that monitors the local network for the boss's phone MAC address, using ARP scans to infer his proximity and automatically alerts the user to stop or resume non‑work activities, complete with step‑by‑step implementation and code examples.
This article explains the TOTP algorithm behind time‑based one‑time passwords, outlines its security benefits and common use cases such as online logins, VPNs, and hardware tokens, and provides a practical Python implementation with code examples using the pyotp library.
This article presents ten real‑world business scenarios illustrating data sampling methods such as random, stratified, time‑window, sliding‑window, keyword, group, interval, click‑based, and weight‑based sampling, each accompanied by clear Python pandas code examples.
This article introduces six useful Python techniques—including string manipulation, list comprehensions, lambda functions, the map and zip utilities, and one‑line conditional expressions—showing concise code examples and explaining how each feature can simplify everyday programming tasks.
This article demonstrates ten practical Python metaprogramming techniques—including dynamic attribute access with __getattr__, attribute assignment with __setattr__, descriptor-based validation, property decorators, dynamic class and method creation, and metaclass usage—providing complete code examples for each scenario.
This article introduces four Python packages—Pivottablejs, PyGWalker, Qgrid, and Itables—that transform Pandas DataFrames into interactive tables within Jupyter notebooks, providing code examples, visual demonstrations, and guidance on when to choose each tool for data analysis and visualization.
This article presents ten practical Python code examples demonstrating how to implement iteration and serialization magic methods, covering iterable objects, generators, indexed and sliced sequences, length, string and byte representations, as well as JSON, pickle, and XML serialization techniques.
This article explains how to use Celery together with Redis to manage and execute periodic and asynchronous tasks in Python, covering basic concepts, architecture, configuration steps, single‑worker and multi‑worker setups, distributed processing strategies, and practical considerations for reliable task execution.
The article demonstrates how Tencent's Hunyuan large model can generate Python scripts to automatically compare Excel‑based reports, highlight differences, and handle multiple files, turning a tedious manual regression test into a fast, reliable automated process.
This article explains Python's multithreading model, covering thread creation, synchronization, data sharing, and provides practical code examples for sending concurrent API requests, downloading files, running test cases, reading files, and inserting records into a SQLite database.
This article explains how to use pandas in Python to remove rows where a column contains a given keyword or multiple keywords, providing concise code examples and practical tips for handling such data‑cleaning tasks.
This tutorial shows how, with about 50 lines of Python using Playwright and pyperclip, you can automate a persistent Firefox session to log into ChatGPT Plus, navigate to your private GPT URL, send prompts and retrieve responses via the clipboard, all without incurring extra API fees.
This article explains several Python techniques for extracting browser cookies—including Selenium automation, direct HTTP requests, driver‑based retrieval, and HAR file parsing—providing clear code examples and guidance on when to use each method.
This article presents a comprehensive guide to building a classic Snake game in Python using the Pygame library, covering game rules, overall design, required libraries, detailed function explanations, and the complete source code for both normal and wall‑through modes.
This article explores how PHP and Python can be combined to build scalable, efficient, and user‑friendly mobile applications, highlighting PHP’s strengths in backend services, Python’s cross‑platform capabilities, and strategies for integrating both languages to maximize performance, scalability, and development speed.
This article explains why full‑link performance testing is essential for e‑commerce systems, provides step‑by‑step Python Locust scripts to simulate user actions such as login, product browsing and ordering, shows how to run the tests, and demonstrates multi‑domain testing with weighted tasks.
This article introduces ModelScope Agents, an open‑source LLM‑based agent framework that addresses limitations of GPT Store, outlines its features, provides installation and usage instructions, showcases a RPG game example, and invites the community to contribute to its roadmap.
This tutorial explains how to install the Spire.XLS library, import its modules, and use Python code examples to convert entire Excel workbooks, individual worksheets, or specific sheets with custom page settings into PDF files for consistent document sharing.
This article explains the core concepts of higher-order functions and function composition in functional programming, defines them, and provides ten practical Python code examples illustrating usage as parameters, return values, composition, and common utilities such as map, filter, reduce, list comprehensions, and functools.partial.
This article presents a detailed 28‑chapter curriculum for mastering Python full‑stack development, covering Linux basics, Python fundamentals, web front‑end design with Vue, RESTful API creation with Flask, Django and Django REST Framework, big‑data processing with Hadoop, Spark and MapReduce, feature engineering, recommendation systems, and live streaming system implementation.
This article explains how software test engineers can combine ChatGPT and the HttpRunner framework to address DevOps testing pain points, record web operations, batch‑modify scripts, run and debug tests, and automatically generate API test cases and scripts for faster, more efficient regression testing.
This article explains the benefits of using short‑link services for marketing, sharing, and SMS optimization, and provides step‑by‑step Flask and Django tutorials—including installation commands, MySQL integration, URL generation, routing, and database models—to create a functional short URL platform.
OpenAI's new ChatGPT Code Interpreter, which can generate and run Python code in a sandbox, has been shown to allow malicious actors to exploit spreadsheet handling and command execution features, raising serious information‑security concerns among experts.
This guide demonstrates how to create a custom image editing tool in Python by leveraging the Pillow, OpenCV, and NumPy libraries, providing step‑by‑step code examples for opening, resizing, filtering, converting to grayscale, edge detection, rotation, channel manipulation, blurring, contour extraction, and color adjustment.
The third part of the series shows how Python scripts can automatically refactor Objective‑C code by encapsulating each data item’s read/write operations in static wrapper classes and rewriting over 600 call sites to use generated XXXSettingReader and XXXSettingWriter methods, achieving zero bugs.
This comprehensive guide walks you through Pytest fundamentals, basic usage, fixture mechanisms, conftest configuration, and advanced features such as Allure report beautification, parameterized data‑driven testing, and YAML integration, providing practical code examples for Python test automation.
This article introduces LangChain—a Python framework for building LLM‑driven applications—explains its core components such as models, indexes, chains, memory, and agents, and provides practical code examples for document summarization, retrieval‑augmented QA, and future development directions.
