The article explains how PyPy’s just‑in‑time compilation can make Python code run faster than even native C implementations, demonstrates benchmark results comparing default Python, PyPy, and C, and outlines the differences between ahead‑of‑time compilation, interpretation, and JIT.
The article reviews the most important additions in scikit‑learn 0.24, including faster hyper‑parameter search methods, ICE plots, histogram‑based boosting improvements, new feature‑selection tools, polynomial‑feature approximations, a semi‑supervised classifier, MAPE metric, enhanced OneHotEncoder and OrdinalEncoder handling, and a more flexible RFE interface.
This article examines why dynamic‑typed languages such as Perl, PHP, Ruby, and Python are generally slower than compiled or statically‑typed languages, discusses static versus dynamic typing, and emphasizes that performance issues often stem from implementation choices rather than the languages themselves.
Learn step-by-step how to use Python's Selenium library to automate login, scroll through QQ Space, extract historical posts and download album photos, including driver setup, code snippets for login, shuoshuo retrieval, and photo downloading, enabling you to preserve nostalgic content.
This guide walks you through installing AutoKey on Linux, configuring its UI, creating typo‑fix phrases, setting window filters, assigning hotkeys, and writing Python scripts to automate repetitive typing tasks, helping you streamline your workflow and reduce keystroke effort.
This article shares seven practical Python scripts—from web‑scraping Zhihu images and chatting bots to AI poem analysis, lottery generation, automatic apology letters, screen recording, and GIF creation—demonstrating how to avoid reinventing the wheel while learning useful automation techniques.
This article walks you through automating daily loan reporting for a bank using Python and pandas, covering data loading, date filtering, table splitting, column renaming, concatenation, missing‑value handling, calculated fields, and pivot‑table generation to replace repetitive Excel tasks.
This article explains what PEP8 is, outlines key Python coding conventions such as indentation, line length, spacing, comments, imports, and naming, and shows how to automatically apply these standards in Jupyter Notebook using the Autopep8 formatter.
This guide reviews the most frequent TCP/IP attacks—including IP spoofing, SYN flooding, UDP flooding, TCP reset hijacking, man‑in‑the‑middle, and DDoS—explains their underlying protocols, demonstrates practical exploitation with Python/Scapy and Netcat, and outlines mitigation techniques and cryptographic fundamentals.
This tutorial walks you through installing pyglet, creating windows, adding text and images, handling keyboard and mouse events, processing input, and playing audio and video, providing a comprehensive guide to building lightweight Python games and multimedia applications.
This article introduces the GoPUP library, which provides over a hundred free data interfaces—including social media indexes, macro‑economic figures, company information, and epidemic statistics—accessible with simple Python code, making data analysis faster and easier.
This article introduces Locust, an open‑source Python load‑testing framework, explains how to install it (including optional pyzmq for distributed mode), describes its core components, walks through a sample test script with database integration, and shows how to run and interpret results via the web UI or command line.
Although Python is slower than C or Java for CPU‑intensive tasks, several projects such as PyPy, Pyston, Nuitka, Cython, and Numba offer practical ways to boost its performance, each with its own trade‑offs and compatibility considerations.
This article shares seven practical PyCharm shortcuts—including changing the background, opening recent files, viewing source, inserting new lines, quick navigation, searching classes/files, and removing unused imports—to help Python developers work faster and more efficiently.
This tutorial introduces Python's pydub library for audio manipulation, covering installation, AudioSegment basics, slicing, merging, fading, speed adjustment, playback, gain control, cross‑fade, multichannel creation, and exporting, with a practical example for short‑video post‑production.
This tutorial explains how to download files, webpages, and Amazon S3 objects using Python, covering the requests and wget modules, handling redirects, chunked and parallel downloads, progress bars, proxy support, urllib/urllib3 usage, and asynchronous downloading with asyncio.
This article examines Python's notorious performance lag, explains why its dynamic typing and object overhead make simple loops sluggish, and demonstrates how NumPy's universal functions can accelerate reciprocal calculations by over a thousand times, outperforming even compiled languages.
This tutorial introduces Python fundamentals, covering why to learn the language, variable assignment, conditional statements, loops, lists, dictionaries, iteration techniques, and core object‑oriented concepts such as classes, getters/setters, encapsulation, and inheritance, all illustrated with clear code examples.
This article compares traditional Python web frameworks with modern asynchronous alternatives, presents benchmark data showing Sanic’s superior speed, explains the benefits of async I/O, and discusses Sanic’s ecosystem, production readiness, documentation, and community support for developers seeking high‑performance backend solutions.
This article explains why Python itself is not slow, demonstrates how to identify bottlenecks with timing and cProfile, and provides a collection of practical tips—such as using built‑in types, lru_cache, local variables, and efficient string formatting—to improve Python program performance by up to 30 percent.
This article introduces Numba, a Python just‑in‑time compiler, explains why it’s advantageous over alternatives, and provides detailed guidance on using its decorators such as @jit, @njit, @vectorize, and @cuda.jit, including code examples for CPU and GPU acceleration.
This article curates 23 open‑source game projects hosted on GitHub—ranging from Vim plugins and JavaScript Tetris clones to Python, Go, and web‑based multiplayer titles—providing installation steps, feature highlights, code snippets, and live demo links so developers can learn, experiment, and have fun during breaks.
This article explains Python regular expressions, covering basic and special characters, non‑print escapes, quantifier types, the re module’s compile function with flags, and the most frequently used pattern‑object methods such as match, search, findall, finditer, split, sub and subn, plus practical usage notes.
This article explains Python's static, class, and instance methods, detailing their definitions, usage with @staticmethod and @classmethod decorators, code examples, expected outputs, and common pitfalls such as TypeError when calling non‑static methods via instances.
This article explains the three core class relationships in object‑oriented programming—dependency, composition, and inheritance—illustrates each with clear Python code, discusses inheritance advantages, single‑ and multiple‑inheritance types, and introduces the method‑resolution‑order (MRO) algorithm.
This article describes how a mobile UI test framework was extended with Python scripts, configuration files, and an Enterprise WeChat robot to automate AB‑test validation across Android and iOS, reducing manual effort and improving efficiency by more than 50 percent.
This article explains Python higher‑order functions, showing how variables can reference functions, how function names act as variables, and how to pass functions as arguments, with step‑by‑step code examples and output screenshots to illustrate each concept.
The article explains how Python 3.10 beta introduces structural pattern matching with the match‑case statement, adds a switch‑case syntax, improves context manager syntax and error messages, and provides code examples comparing match‑case to traditional if‑elif‑else constructs.
This guide outlines essential Python best‑practice techniques—including memory management, choosing Python 2 vs 3, adhering to style guides, using static analysis tools, optimizing performance, profiling, testing, and continuous integration—to help developers write clean, fast, and reliable code.
This article introduces the Airtest mobile automation IDE, explains its cross‑platform and platform‑specific APIs, and provides detailed code examples for device initialization, control, app management, screen actions, and assertions, enabling developers to automate mobile testing efficiently.
The article presents a comprehensive guide to Python's built‑in functions, standard libraries, and third‑party packages across file I/O, web scraping, databases, data cleaning, statistical analysis, machine learning, visualization, and more, rating each with stars and offering a free e‑book collection for readers.
Python has become the go‑to language for AI and machine learning across startups and enterprises because of its rapid prototyping, flexible syntax, readability, extensive libraries like NumPy, SciPy, scikit‑learn, Pandas, Keras, and powerful visualization tools, making development faster, scalable, and easier to maintain.
The article presents DuLab, a distributed UI‑automation platform for mobile apps that leverages Airtest, Python/Tornado, Celery, and Redis to schedule and run bulk test cases on remote devices, detailing its layered case management, package database, mock services, and the resulting scalable, efficient regression testing across diverse devices.
Learn how to send emails using Python by exploring three approaches—smtplib, zmail, and yagmail—including setup, authentication, constructing MIME messages, attaching files, and sending, with complete code examples and step‑by‑step instructions for each method.
This article introduces latexify_py, an open‑source Python tool that automatically converts Python functions into LaTeX math expressions, dramatically simplifying the creation of complex formulas for research papers and eliminating the tedious manual editing in Word.
This article introduces Python’s built‑in string class and explains ten commonly used string methods—including center, count, find, swapcase, startswith/endswith, split, case conversions, justification, strip, and zfill—detailing their syntax, parameters, and example usages while emphasizing that they return new strings without altering the original.
This guide presents six practical Python best‑practice techniques—including memory management, version compatibility, code style, performance tuning, profiling, and testing with CI—to help developers write faster, more maintainable, and well‑documented code for open‑source and personal projects.
This article explains how Python implements function argument passing, distinguishing value passing—where a copy of the argument is used—from reference passing for mutable objects, illustrating both mechanisms with swap examples, memory diagrams, and concluding with best practices for modifying data inside functions.
This article explains Python function definitions, covering required, default, keyword, positional, variable-length (*args, **kwargs), and positional-only/keyword-only parameters, illustrating each type with syntax, usage rules, and example code snippets, and common pitfalls such as mutable default values and argument ordering errors.
Python 3.10 beta introduces a native switch‑case style construct called structural pattern matching, simplifying multi‑branch logic, while also adding enhancements like parenthesized context managers and smarter NameError suggestions, marking a major evolution for Python developers.
This article explains Python's built‑in magic (dunder) methods—functions that start and end with double underscores—showing how they enable custom class behavior such as indexing, iteration, string representation, callable objects, context management, object creation, and attribute handling with clear code examples.
This article walks through creating a Python script that parses web pages, extracts video URLs, and downloads multiple videos efficiently with progress tracking and buffering, providing complete code examples and implementation steps.
This tutorial explains how pandas handles missing values, introduces key functions like dropna, fillna, isnull, and notnull, and provides practical code examples for filtering and imputing missing data in Series and DataFrames.
Discover seven powerful Python tools—including Pandas, Selenium, Flask, Scrapy, Requests, Faker, and Pillow—that streamline data analysis, web testing, API calls, web development, web scraping, mock data generation, and image processing, complete with installation steps and code examples to boost your development efficiency.
This article explains Python's comprehension syntax for lists, tuples, dictionaries, and sets, detailing their structures, execution order, and practical examples—including filtering, nested loops, and conditional logic—while showing how to convert generator objects and highlighting common use cases.
This article introduces tidevice, an open‑source tool that enables iOS automation on Windows, Linux, and macOS by providing device information, app management, WebDriverAgent control, performance data collection, and various command‑line and Python APIs, along with detailed installation steps and integration advice.
This tutorial walks data analysts through transitioning from Excel and SQL to Python, covering environment setup, data import with pandas, web scraping, cleaning, renaming, type conversion, filtering, grouping, merging, and visualization using Jupyter Notebook and popular libraries.
This article presents a method that replaces traditional manual video frame quality checks with an automated YOLOv5‑based object detection pipeline, detailing data labeling, model training, loss computation, inference code, and experimental results that show higher accuracy than ResNet for classifying black, color‑screen, and normal frames.
The article examines Python web framework performance, highlights the advantages of asynchronous frameworks like Sanic, and provides benchmark code and practical considerations for choosing a fast, production‑ready backend solution; it also discusses ecosystem support, documentation quality, and community resources.
This article recounts the author's three‑year journey evolving a Python‑based SaaS backend from a simple MVC setup through service splitting and microservices, detailing architectural choices, performance challenges, optimization tactics, and the move toward domain‑driven design, while sharing practical lessons and resources.
This article presents a method that replaces manual visual inspection with an automated YOLOv5‑based object detection pipeline to classify video frames as normal, colorful, or black screens, detailing data annotation, training, loss calculation, inference code, and showing a 97% accuracy improvement over ResNet.
This article explains Python operator overloading, introduces special methods like __init__, __str__, __add__, and __lt__, provides step‑by‑step code examples for overloading the + operator and comparison operators, and demonstrates the results with clear output images.
This article compares popular Python web frameworks, presents benchmark results showing that traditional frameworks like Flask, Django, and Tornado lag behind modern async options, and explains why Sanic is the preferred choice for high‑performance, production‑ready asynchronous web applications.
This tutorial guides readers through analyzing web pages, using Python to write network programs, applying regular expressions, and operating Excel to scrape all listed company stock data for a specified date range, save it by stock code, and optionally store results in databases.
This article introduces Python’s hashlib module, explains the principles and characteristics of common hash algorithms such as MD5, SHA‑1, SHA‑224, SHA‑256, SHA‑384, and SHA‑512, demonstrates how to compute their digests with code examples, and shows simple key‑based encryption techniques.
This guide explains how to configure a robust Python development environment by installing pyenv for version management, using Poetry for dependency handling, applying Black for code formatting, integrating mypy for static type checking, and automating checks with pre-commit, all illustrated with concrete command examples.
This article introduces Ryven, a Python visual scripting tool created by a university student, explains how to set up the environment, run the editor, and describes its data‑flow and execution‑flow modes along with future feature ideas, highlighting that visual programming complements rather than replaces text coding.
This tutorial explains the First Order Motion Model for animating static images, covering the algorithm's keypoint‑based motion estimation, required datasets, environment setup with Python, OpenCV and ffmpeg, and provides complete code snippets to generate animated videos with audio.
Discover ten essential, free Python libraries for image processing—from scikit-image and NumPy to OpenCV-Python and Pycairo—each with resources, usage examples, and visual demonstrations, enabling you to manipulate, analyze, and transform images efficiently for computer vision and data science projects.
This article provides a comprehensive Python web‑scraping guide covering basic GET/POST requests with urllib2, proxy handling, cookie management, header manipulation to mimic browsers, gzip compression handling, regular‑expression and library parsing, simple captcha strategies, and a multithreaded thread‑pool example.
This article explains how to extract song information from KuGou by inspecting network requests, simplifying URLs, generating required MD5 signatures, constructing authenticated API calls, and using Python to download the resulting audio files to a local directory.
This tutorial walks you through Python's built‑in JSON handling, covering reading JSON files, converting between JSON strings and Python objects, using pandas for JSON parsing, and applying serialization, deserialization, and pretty‑printing techniques with complete code examples.
This tutorial introduces Pillow, the dominant Python imaging library, and walks through its six core modules—Image, ImageDraw, ImageEnhance, ImageFont, ImageGrab, and ImageFilter—showing how to load, edit, draw, enhance, capture, and filter images with practical code examples.
This tutorial walks through using Python's urllib and BeautifulSoup libraries to fetch, parse, clean, and export the Fast Track 100 company table into a CSV file, covering installation, page inspection, element extraction, data cleaning, link handling, and file writing.
This article presents a practical collection of Python regular‑expression techniques for extracting HTML elements such as table rows, links, titles, images, and scripts, showing how to filter tags and handle URL parameters during web crawling.
This tutorial explains Python dictionaries, covering their definition, key‑value storage, common operations such as adding, deleting, modifying, and clearing elements, as well as traversal methods including keys, values, items, and enumerate, with clear code examples and output screenshots.
This article explains how Python’s @property decorator transforms class methods into attribute-like accessors, covering basic usage, setter/getter patterns, error handling, and practical examples such as score validation and temperature conversion, helping developers write cleaner, more encapsulated code.
This article presents a collection of practical techniques—including Pandas Profiling, Cufflinks/Plotly visualizations, IPython magic commands, Jupyter formatting, keyboard shortcuts, multiple-output cells, and RISE slide creation—to streamline and speed up everyday data analysis workflows in Jupyter notebooks.
This tutorial shows how to generate eye‑catching dynamic bar‑chart‑race visualisations in Python using the bar_chart_race library, covering installation challenges, basic usage, GIF/MP4 output, and a wide range of customisation options such as orientation, sorting, colour maps, labels and Chinese text support.
WSGI (Web Server Gateway Interface) defines how Python web frameworks like Django and Flask interact with web servers, acting as a mediator that enables flexible, scalable deployment across servers such as Apache, NGINX, and containers like Gunicorn, uWSGI, and mod_wsgi.
This tutorial explains how to use Python on Windows to crawl any Eleme restaurant's comments—including user IDs, ratings, dates, text, and images—by analyzing network requests, constructing request URLs, retrieving JSON data, and storing the results in Excel or databases.
This article explains how to represent Android UI view trees as lists, generate unique page signatures, and filter actionable events such as scrolls and touches to improve model‑based testing coverage and traceability, providing Python code examples for each step.
This article provides a comprehensive overview of Python's regular expression features, covering special characters, character classes, quantifiers, grouping, backreferences, assertions, conditional matching, flags, and the most commonly used methods of the re module with illustrative code examples.
Learn how to install and use the Python stylecloud package to generate visually appealing word clouds with custom shapes, palettes, and masks, including examples using Trump’s speech and Tencent comments, plus tips on font paths, icon selection, and advanced parameters for fine‑tuned results.
This guide demonstrates how to use Python's Selenium library to log into a GPS web system, locate elements via name and XPath, handle iframes, click list items, and extract dynamic data, including detailed installation steps for Selenium and ChromeDriver.
This tutorial demonstrates how to use Python's requests library to simulate Zhihu login by handling dynamic _xsrf tokens, optional captcha verification, saving cookies, and then crawling the main page to extract questions and answer abstracts.
This tutorial shows how to use UiAutomator2 and WEditor to create a Python script that automatically clears unread notifications in the WeChat Android app by connecting to the device, locating UI elements, and performing fast double‑click actions until no messages remain.
Learn how Python’s flexible function parameters—default, variable (*args), and keyword (**kwargs) arguments—enable you to create versatile functions, with clear examples showing how to define, call, and simplify code using lists, tuples, and dictionaries for more powerful and concise programming.
This article presents thirty concise Python exercises, each with a short description and ready‑to‑run code illustrating common tasks such as duplicate detection, anagram checking, memory and byte size measurement, string repetition, title‑casing, list chunking, filtering, dictionary merging, enumeration, timing, exception handling, frequency analysis, palindrome testing, operator‑based calculations, shuffling, and more.
This article introduces the BeautifulSoup library, explains how to install it, demonstrates core parsing methods such as find, find_all, select, and relationship navigation, and provides a complete example of scraping novel titles from Qidian using Python requests.
Python 3.9.3 and 3.8.9 were released early with multiple security patches, OpenSSL CVE fixes, module hardening, FTP PASV safety, audit hooks, Unicode handling improvements, and various bug fixes for syntax errors, import cycles, recursion limits, SSL context, and SMTP authentication.
The Supreme Court ruled APIs uncopyrightable, letting Google use Java code in Android, while LG exits the smartphone market, a massive Facebook data leak surfaces, UK developer jobs surge amid skill shortages, and Python 3.9.4 patches critical security flaws.
This article provides a comprehensive tutorial on XPath concepts, node types, syntax, axes, predicates, and operators, followed by a detailed introduction to the fast Python lxml library, its installation, usage for both offline and online HTML parsing, and practical code examples for extracting elements and attributes.
An in‑depth walkthrough demonstrates how to identify, analyze, and attack a QQ phishing website—revealing its URL, POST parameters, using Python to flood it with fake credentials, performing WHOIS, ping, nmap, and w3af scans, uncovering backend details, and discussing mitigation strategies.
This article introduces the fundamentals of user profiling, explains tag types and their business value, and demonstrates a data‑driven e‑commerce case study that analyzes gender, age, region, marital status, education, profession, product preferences, purchase timing, and price sensitivity to guide targeted promotion strategies.
This article walks through installing pyecharts, explains its version differences, and demonstrates a series of bar‑chart techniques—including basic charts, axis labeling, multiple series, styling, horizontal orientation, mark lines/points, label rotation, and interactive zoom—complete with code snippets and visual examples.
This article walks through creating a Python‑based mobile app using the Kivy framework, covering environment setup on macOS, Linux, and CentOS, code examples, packaging with Buildozer, troubleshooting common errors, and deploying the resulting APK to Android devices.
This step‑by‑step guide shows how to log into Toutiao, locate the fan list via browser dev tools, capture the AJAX request URLs, decode Unicode nicknames, paginate through all pages, and save the results as JSON using Python.
This article explains the fundamentals of Python threading, covering thread definitions, the threading module, two ways to create threads, daemon thread behavior, common thread‑safety issues, and how to use mutex locks to synchronize access to shared resources.
This article provides a comprehensive guide to Python decorators, covering their core concepts, practical use‑cases, step‑by‑step creation of simple, parameterized, class‑based, and advanced decorators, complete with runnable code examples.
This article demonstrates how to use Python's data‑analysis ecosystem (NumPy, pandas, statsmodels, etc.) together with Flask, MySQL, and ECharts to create a web‑based sales forecasting tool that automates data extraction, modeling, prediction, and visualisation.
This tutorial walks through analyzing a Qidian novel page, extracting GET request parameters, constructing the catalog URL, and repeatedly fetching free chapters with Python, handling asynchronous loading and delays to reliably download the novel’s free content.
This article introduces the Python requests-html library, covering its installation, basic operations such as fetching pages, extracting links and elements with CSS and XPath selectors, advanced capabilities like JavaScript rendering, pagination handling, custom request options, and practical web‑scraping examples.
This tutorial explains the fundamentals of programming with Python, covering what code is, how to use conditional statements, loops, variables, function definitions, module imports, and the basics of classes and objects, illustrated with clear examples and code snippets.
This article presents a complete Django‑based basketball information management system that implements player data CRUD operations, pagination, and front‑end templates, providing full code examples for view functions, HTML tables, and edit forms to help developers build similar web applications.
This article introduces a free Python certification exam simulator, explains how to download, install, and crack the software, and shows how to use its diverse question sets to assess and improve your Python fundamentals, data‑structure knowledge, and overall coding confidence.
This tutorial explains how to install, launch, and use TensorBoard and Visdom with PyTorch, providing step‑by‑step commands, code examples for logging training metrics, and visualizing images and plots to monitor deep‑learning experiments.
This article explains Python's context manager mechanism, covering the basic with statement, custom __enter__/__exit__ classes, the contextlib.contextmanager decorator, nesting, combining multiple managers with ExitStack, and practical applications such as SQLAlchemy session handling, exception management, and persistent HTTP requests.
This article introduces Python functions, demonstrates how to define and call them, and explores essential time‑related utilities—including time, datetime, calendar, and random modules—through clear explanations and runnable code snippets, helping readers build a solid foundation for practical Python programming.
This article introduces the open‑source Plotly library for Python, showing how to install it, use the cufflinks wrapper with Pandas, and create a variety of interactive visualizations—from simple bar and box plots to scatter matrices, time‑series charts, heatmaps, and themed 3D figures—using just one or two lines of code.
