This article introduces NumPy, the essential Python library for array and matrix operations, covering creation, arithmetic, slicing, aggregation, reshaping, and real‑world examples such as machine‑learning data preparation, image handling, audio processing, and text tokenization.
This article explains Python's file handling basics, covering what files are, how to open them with the open() function, various access modes, common file object methods such as read, readline, readlines, write, tell, seek, and the use of the with statement for safe resource management, plus code examples.
In a one‑hour interview, Python’s creator Guido van Rossum shares candid opinions on Rust, Go, Julia, and TypeScript, explaining why he finds Rust powerful, Go the most Pythonic, Julia a niche but interesting language, and how Python is learning from TypeScript.
This tutorial walks beginners through the complete process of building a Python web scraper to collect internship listings from Shixi.com, covering page analysis, static vs dynamic detection, data location with XPath, pagination handling, and storing results in a CSV file using pandas.
This guide explains how to use Scapy for host discovery (TCP SYN/ACK, UDP, ARP, ICMP pings), various port‑scanning techniques (SYN, FIN, NULL, Xmas, UDP) and traceroute methods (ICMP, TCP, DNS), providing complete code examples and practical insights.
This article compares popular Python web frameworks, highlights the speed advantages of async frameworks—especially Sanic—through benchmark data, explains why asynchronous I/O matters, and discusses Sanic's ecosystem, production readiness, documentation, and community support.
A wave of malicious PyPI packages named after popular movies and TV shows, many containing spam keywords and stolen code, exposed supply‑chain risks and prompted urgent cleanup by maintainers, highlighting the need for developers to verify packages before use.
This tutorial walks through the complete process of turning a local Python project into an open‑source package, covering licensing, project structure, setup.py creation, testing, coverage, documentation, continuous integration, and finally publishing to PyPI or Conda, with practical code examples and configuration files.
This article explains how Python persistence works by serializing objects with pickle and cPickle, compares file‑based and database storage, demonstrates basic and advanced usage—including handling circular references, custom classes, and versioning—and offers practical tips for maintaining pickled data across code changes.
This tutorial walks through installing Plotly Express in a Python 3.7 Jupyter environment and demonstrates how to create a wide range of visualizations—including line, scatter, area, geographic, violin, and polar charts—using concise one‑line commands and built‑in datasets.
This guide introduces parallel-ssh, a Python-based asynchronous SSH library for small‑scale automation, covering its history, Python‑3 support, installation methods across platforms, command‑line utilities (pssh, pscp, prsync, pslurp, pnuke), usage examples, and resource considerations.
This article explains why processes are preferred over threads for stability and multi‑machine distribution, introduces Python's multiprocessing.managers for networked task queues, and provides step‑by‑step code examples to create a distributed crawler that fetches image URLs and downloads them across several machines.
This article explains why Python’s Django framework is a top choice for backend development, outlining its popularity, benefits, essential system‑planning and web‑script skills, rapid prototyping, scientific computing, and the specific Python and Django expertise needed to become a proficient developer.
This article explains Python inheritance and polymorphism, covering single, multi‑level and multiple inheritance, method overriding, and duck‑type polymorphism with clear code examples and visual illustrations to help beginners grasp OOP fundamentals effectively.
Guido van Rossum revealed that the new “Shannon Plan” backed by Microsoft will target a 2× speed boost for CPython 3.11 through a specialized bytecode interpreter, stack optimizations, and other enhancements, while preserving ABI compatibility and open‑source principles.
An enthusiastic overview walks through the fundamentals of linear and multivariate regression, explains loss functions and least‑squares optimization, shows Python implementations of fit and predict, and applies the model to the classic Boston housing dataset to illustrate feature impact and prediction.
This article introduces and explains the most useful Visual Studio Code extensions for Python developers in 2021, covering essential tools such as the Python language support, Python Snippets, Docstring Generator, Test Explorer, Preview, Type Hint, and Jupyter integration to boost productivity and code quality.
In this interview, Python’s creator discusses how the language was born, its unexpected rise in AI, its role in web and mobile development, thoughts on newer languages like Rust and TypeScript, version transitions, package management, quantum computing prospects, and his personal life and hobbies.
Guido van Rossum’s recent “Making CPython Faster” talk reveals the Shannon Plan—a four‑year effort, backed by Microsoft, to boost Python’s performance up to five times, with the first milestone targeting a 2× speedup in the upcoming Python 3.11 release through adaptive bytecode interpreters and other optimizations.
This article explains the differences between local and global variables in Python, how to modify globals with the global keyword, the behavior of mutable and immutable objects, demonstrates variable scope with code examples, and also covers references, lambda anonymous functions, and recursive implementations such as factorial calculations.
This article compares Python's built‑in urllib library with the third‑party requests library, demonstrating their usage through code examples, highlighting differences in request construction, response handling, and practical considerations for web scraping, and concludes with recommendations for choosing the more convenient tool.
This article explains Python object persistence, covering the concepts of serialization with pickle and cPickle, various storage mechanisms, handling of complex objects, reference cycles, class instance pickling, versioning strategies, and advanced techniques such as custom state methods and Pickler/Unpickler usage.
An in‑depth Python tutorial walks through the fundamentals of classes, covering creation, instance and class methods, protected and private members, core OOP features such as encapsulation, inheritance and polymorphism, as well as dynamic attribute handling with __slots__ and property decorators, illustrated with clear examples.
This guide introduces Scapy, a powerful interactive Python packet manipulation tool, covering installation, basic usage, packet creation, sending and receiving functions, layer inspection, packet export formats, sniffing, and advanced features such as sprintf and custom packet handlers, enabling network testing, analysis, and security tasks.
This article explains how to define Android UI pages as view trees, convert them to list structures, generate unique page signatures, and filter actionable events such as scrollable and clickable views using Python, enabling more effective model‑based testing of mobile applications.
This article explores the differences between Python interpreters, explains why PyPy often runs faster than CPython through JIT compilation, compares performance across several languages, and offers practical optimization techniques for Python code, all backed by code examples and benchmark results.
This tutorial walks you through creating a variety of Python visualizations—line plots, bar charts, histograms, density plots, scatter matrices, and faceted grids—using pandas, matplotlib, and seaborn, with complete code examples and tips for customizing appearance.
Guido van Rossum, now a Microsoft Distinguished Engineer, promises to boost CPython performance by up to five times without breaking existing code, detailing the team, funding, and security efforts behind the ambitious speed upgrades slated for Python 3.11 and beyond.
This article explains Python's memory management, covering reference counting, its limitations with cyclic references, and how the interpreter supplements it with mark‑sweep and generational garbage‑collection algorithms, complete with code examples and detailed diagrams of the underlying mechanisms.
This article explains Python's multiprocessing module, covering process concepts, creation of single and multiple processes, process pools, locks, inter‑process communication methods such as Event, Pipe, Queue, semaphores, and data sharing techniques, with code examples and visual illustrations.
This guide explains why manual regression testing of a WeChat mini‑program becomes a bottleneck, compares Jest‑based SDK and Minium frameworks, shows how to set up the environment, write page‑object scripts, configure and run tests, generate reports, and troubleshoot common issues.
This article explains the limitations of traditional RESTful APIs, introduces GraphQL as a flexible query language, details its core concepts such as operation types, object and scalar types, and schema definition, and provides a complete Python Flask example with code analysis, execution steps, and a discussion of its advantages and drawbacks.
This article explains the limitations of traditional RESTful APIs, introduces GraphQL's core concepts and operation types, provides a step‑by‑step Flask and Graphene implementation for querying and mutating book data, and discusses the practical pros and cons of adopting GraphQL in real‑world projects.
This article provides a comprehensive guide to Python threading, covering core concepts such as thread creation, synchronization primitives like locks, RLocks, conditions, semaphores, events, local storage, and timers, complete with practical code examples and explanations of their usage and pitfalls.
This article explains what NoSQL means, contrasts it with SQL and relational databases, walks through schema design, primary keys, indexing, and then demonstrates how to implement a lightweight key‑value NoSQL store in pure Python with full command parsing and handling.
This article provides a comprehensive guide to Python threading, covering core concepts such as threads, locks, RLock, conditions, semaphores, events, local storage, and timers, along with practical code examples for creating, managing, and synchronizing threads to improve concurrent program performance.
This article introduces the fundamentals of automatic speech recognition (ASR) for food‑sound classification, explains key audio representations and modeling approaches, and provides a fully runnable Python implementation using librosa, TensorFlow/Keras, and classic machine‑learning tools to train and predict on the Tianchi competition dataset.
This article shares a curated collection of ready‑to‑run Python and Shell scripts—including Enterprise WeChat alerts, FTP and SSH clients, SaltStack and vCenter utilities, SSL certificate checks, weather notifications, SVN backups, Zabbix password monitoring, local YUM mirroring, and high‑load detection—complete with full source code and usage notes to help engineers automate routine tasks and boost operational efficiency.
This article documents a Python web service performance optimization case, detailing the initial bottlenecks, architectural redesign with caching and message queues, load‑testing methodology, Linux TCP time‑wait tuning, and the final results achieving 50k QPS with sub‑70 ms latency.
This tutorial walks you through using Airtest to automate mobile apps—showing how to launch apps via image recognition or package name, perform likes and comments, capture screenshots, enable real‑time coordinates, and create endless swipe loops with Python code.
This article explains what NoSQL means, contrasts it with relational databases, and guides readers through building a simple Python key‑value NoSQL database, covering schema basics, querying, indexing, command parsing, and the trade‑offs between flexibility and query performance.
This article explains how the PyPy interpreter dramatically speeds up Python code through just‑in‑time (JIT) compilation, compares its performance to CPython and C, and provides a practical example demonstrating the runtime gains.
This article introduces Python functions, demonstrates how to define and call them, and explores essential time-related modules such as time, datetime, calendar, and random, providing clear code examples and output screenshots to help beginners grasp practical usage.
This article explains how to use Python's NumPy library to translate common mathematical formulas—such as powers, roots, absolute values, vector and matrix operations—into concise, executable code, covering setup, basic operations, and practical examples for data analysis and machine learning.
This tutorial shares three handy tools—a Sublime Text build system for running Python scripts, an iTerm2 imgcat setup for displaying images directly in the terminal, and a concise guide to Python's typing module for better type safety and code readability.
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.
