This article explains how Python determines whether an object is iterable by using the built‑in iter function, detailing the roles of __iter__, __getitem__, iterator protocols, and showing concise implementations with generators and generator expressions.
In a fiercely competitive internet era, technical professionals must continuously learn across fields such as information security, Python, cloud computing, big data, AI, software testing, IoT, and internet marketing to become the highly sought‑after talent that companies urgently need.
The author recounts eight interview experiences across companies like Afanti, XueTang Online, Guokr, Veeva, Zhihu, Spring Rain Doctor, 360, and Toutiao, sharing detailed insights on Python fundamentals, network protocols, system design, database concepts, and personal lessons that helped secure a final offer.
This tutorial walks you through Python functions—definition, calling, parameters, return values, nested calls, debugging with PyCharm, documentation strings, and how to organize and reuse code with modules and compiled bytecode—providing hands‑on examples and best‑practice tips for every step.
This tutorial covers Python's comprehensive file I/O capabilities, including pathlib and os.path directory operations, tempfile usage, fnmatch pattern matching, open() modes and buffering, reading and writing techniques, fileinput streams, linecache random access, and practical code examples.
This article explains Python decorators, showing how the @ syntax transforms functions into objects, how to build simple and parameterized decorators, and how to apply them for routing in frameworks like Flask, complete with clear code examples.
This guide introduces Scrapy, a powerful Python web‑scraping framework, explains its architecture and components, walks through installation, project creation, spider development, query syntax, recursive crawling, and item pipelines, providing practical code examples for building robust crawlers.
This guide walks you through installing Flask, structuring a project with webapp, templates, and static files, writing core code and routes, using Blueprint for modularization, rendering Jinja2 templates, and running the app, providing complete code snippets and configuration tips for rapid backend development.
This article explains why Python 2.7 reached end‑of‑life in 2020, outlines the benefits and incompatibilities of moving to Python 3, and offers practical guidance for a smooth migration, including using official porting tools and managing dual environments with conda.
This guide explains what XML is, compares it with HTML, and provides step‑by‑step Python code using xml.dom.minidom to read XML files, access nodes, attributes, and extract inner data, helping beginners grasp XML parsing techniques.
The Python Software Foundation secured $407,000 from Mozilla and the Chan Zuckerberg Initiative to fund pip’s 2020 development, outlining a three‑phase plan that includes core improvements, resolver work, and sustainability efforts to strengthen the Python packaging ecosystem.
This guide introduces the Scrapy framework, explains its architecture—including engine, scheduler, downloader, spiders, pipelines, and middlewares—covers installation, project setup, item definition, spider coding, pipeline handling, pagination, and provides practical code examples for extracting data from Douban books.
This guide explains practical techniques to avoid IP bans and 403 errors when web‑scraping, covering explicit and implicit waiting, User‑Agent spoofing, proxy usage, IP pools, and distributed crawling architectures.
This article walks you through four hands‑on Python projects—instant tagging, PDF drawing, XML‑driven website generation, and a Usenet news aggregator—explaining the underlying modules, key code structures, and how to extend each example for deeper learning.
When the Chinese railway ticketing system 12306 crashes under heavy load, developers turn to open‑source Python bots that simulate user behavior, query seat availability, and automate order submission, with detailed feature lists, repository links, and real‑world log examples.
This article introduces the ASCII encoding standard defined in RFC20, explains its binary mapping and character ranges, demonstrates Python's built‑in ord/chr functions, and provides a custom Rust crate implementing equivalent ASCII conversion utilities with testing examples.
This guide explains the fundamentals of web crawling, covering crawler types, the Robots.txt protocol, Python's urllib and urllib3 modules, the requests library, handling HTTP methods, user‑agents, HTTPS certificates, and practical code examples for extracting data from websites.
This article explains how to scrape all of your Zhihu saved collections using a Python crawler, store the data in JSON files, and then serve it through a Flask backend API and a Vue.js single‑page front‑end, complete with screenshots and full source code.
This article shares 35 practical PyCharm shortcuts and features—including clipboard history, JSON formatting, Linux command integration, quick code refactoring, and Git version control—to help Python developers work faster and more efficiently, with step‑by‑step instructions and visual examples.
This tutorial walks you through planning, extracting, and saving classic Chinese novel content from shicimingju.com using Python, regular expressions, and file storage, providing clear code examples and practical tips for successful web scraping.
This article introduces eight high‑performance Python web‑scraping frameworks—including Scrapy, PySpider, Crawley, Portia, Newspaper, Beautiful Soup, Grab, and Cola—detailing their main features, typical use cases, and providing direct project URLs for developers seeking efficient data extraction solutions.
This article explains PySpark's multi‑process architecture, how the Python driver uses Py4J to call Java/Scala APIs, the implementation of RDD and DataFrame interfaces, executor‑side process communication and serialization with Arrow, and the design of Pandas UDFs, while also discussing current limitations and future directions.
The article introduces Wenyan, an esoteric programming language that lets developers write code in Classical Chinese characters, demonstrates "Hello World" and a prime‑number sieve example compiled to JavaScript, and provides installation, usage, and feature details for this open‑source, Turing‑complete language.
This guide explains the principles of stack (LIFO) and queue (FIFO) data structures, demonstrates how to implement them in Python using classes with methods for push, pop, enqueue, dequeue, and provides complete example code for both stack.py and queue implementations.
This article presents a concise set of Python coding conventions and practical performance‑enhancing techniques, covering naming, data structures, variable scope, idiomatic expressions, loop optimizations, and recommendations for CPU‑intensive tasks to write faster, cleaner code.
This guide explains how to extract an item ID from Zabbix alerts, capture the corresponding chart image, upload it to a public server, format the alert as markdown, and deliver it through a DingTalk robot webhook using a Python script.
This article explains Python coroutine fundamentals, async/await syntax, and demonstrates how to use aiohttp with an event loop and semaphore to dramatically speed up I/O‑bound network requests, providing practical code and performance results.
Lingdong is a novel programming language based on Classical Chinese, created by a CMU senior, that can compile to JavaScript or Python, features an online IDE, showcases examples like Hello World and prime sieves, and has gained rapid popularity on GitHub with thousands of stars and forks.
A comprehensive collection of 70 NumPy exercises with detailed problem statements, code snippets, and expected outputs that cover array creation, manipulation, statistical analysis, handling missing data, encoding, sorting, and advanced mathematical operations for Python developers.
This tutorial shows how to reverse an existing GIF and create new GIF animations in Python using Pillow and imageio, including step‑by‑step code examples, frame extraction, reversal, and saving, plus a quick method for assembling multiple images into a GIF.
This article compares Java and Python on Armv8 platforms, explaining why both compile to machine code and rely on virtual machines, detailing JVM feature support across architectures, and offering configuration tips to prevent CodeCache overflow and improve performance, while also noting Python's compatibility on Kunpeng servers.
This article introduces a complete vehicle license‑plate detection and recognition pipeline—covering image preprocessing, ROI extraction, character segmentation, SVM‑based classification, and a PyQt5 GUI—while also discussing code structure, demo results, and future improvements.
This article introduces HttpRunner for API automation, covering environment setup, project structure, core commands, execution methods, workflow, and a collection of practical problems and solutions encountered during real‑world usage.
This article presents a collection of classic interview questions and answers on interface automation testing, covering topics such as Python coding, testing methodologies, and tools like Jenkins.
This article walks through downloading World Bank GDP and growth‑rate datasets, explores income‑group classifications, visualizes top‑ranking economies, maps worldwide GDP distribution, and compares growth trends across countries using Python and data‑visualisation techniques.
This article explains how to use Python to analyze Android APK packages, extract basic statistics, identify optimizable resources such as oversized images, duplicate files, and unused assets, and provide data‑driven guidance for reducing APK size and improving distribution efficiency.
This tutorial walks you through using Python to crawl Tmall lingerie product and comment data, store it in MySQL, clean and analyze cup‑size distribution and popular colors, and finally visualize the results with pyecharts.
This article explains how to create a Python‑based WeChat robot that forwards messages from a main lecture group to up to 24 large groups in real time, covering background, design, configuration, core code, testing steps, encountered issues, and practical deployment tips.
This guide walks you through opening, reading, writing, and closing files in Python, detecting file existence, using file dialogs, fetching web data, handling exceptions, raising custom errors, and performing binary I/O with pickle, complete with code examples and practical tips.
This tutorial explains the structure of Chinese citizen ID numbers, details the ISO 7064 checksum calculation, and provides Python code to generate random valid IDs and verify existing ones, covering area codes, birth dates, sequence and gender digits.
This article compares three popular Python test automation frameworks—Robot Framework, pytest, and unittest—detailing their prerequisites, key advantages, drawbacks, and ideal use cases to help developers choose the most suitable tool for their testing needs.
Python Software Foundation announced $407,000 in funding from Mozilla’s Open Source Support program and the Chan Zuckerberg Initiative to support pip’s 2020 development, outlining a three‑phase plan covering core work, resolver redesign, and long‑term maintenance, while detailing allocation of resources and future funding goals.
This tutorial walks you through using Python's requests library to fetch a web page and BeautifulSoup4 to parse HTML, covering object creation, common attributes, tag properties, and the find() / find_all() methods for extracting specific content.
This article walks through several Python optimization techniques—including the bisection, three‑point division, Fibonacci, golden‑section, quadratic interpolation, and Newton methods—providing clear code examples, explanations of return statements, variable type handling, and debugging tips.
This article presents practical Python scripts that automate repetitive workplace tasks such as system data entry, Excel file merging and chart creation, Word resume parsing, operational KPI monitoring, and email dispatch, enabling professionals to boost efficiency and focus on higher‑value work.
This tutorial demonstrates how to perform face swapping on static images using Python, dlib, and OpenCV, guiding readers through landmark detection, Procrustes alignment, color correction, and seamless blending to achieve realistic results.
This guide introduces Python’s Requests library, covering installation, GET and POST requests, handling headers, response codes, cookies, redirects, timeouts, and proxy settings, with practical code examples to help developers perform reliable HTTP operations and avoid common pitfalls in web scraping.
This article explains the purpose and behavior of Python's yield keyword, how generators work, their difference from regular functions, and demonstrates practical examples including iterator concepts, itertools utilities, and memory‑efficient looping techniques.
A comprehensive guide that explains Python concurrency concepts—including processes, threads, synchronization primitives, thread pools, asyncio, greenlet, and gevent—while showing how to choose the right model for CPU‑bound or I/O‑bound tasks.
This guide demonstrates how to use Zabbix's API with Python to retrieve host information, item IDs, historical and trend data, process the metrics, and automatically write them into an Excel/CSV file, enabling scheduled monitoring reports.
This article demonstrates how compiling OpenCV 3.2 with CUDA 8.0 enables GPU‑accelerated template matching in Python, reducing average processing time from 0.299 seconds on CPU to 0.181 seconds on GPU—a 39.4% performance gain for automated testing image‑recognition APIs.
This article explains how to prepare the Docker environment, install TensorFlow Serving (CPU and GPU versions), convert a YOLO V3 checkpoint to SavedModel, deploy the model as a service, warm‑up and manage versions, invoke it via gRPC and HTTP, and compare CPU versus GPU inference performance.
This article explains how to compile OpenCV‑Python with CUDA support to speed up image template matching, compares CPU and GPU execution times, and shows a practical Python example demonstrating a 39.4% performance improvement using OpenCV 3.2.0 and CUDA 8.0.
This tutorial introduces Python lists, explaining their characteristics, how to create them, and covering the most common operations such as indexing, slicing, concatenation, repetition, membership testing, built‑in functions, and list methods with clear code examples.
This article demonstrates how to automate e‑commerce test data creation by retrieving schema information with SQLAlchemy ORM, defining mapping classes, generating realistic data using Faker, and submitting it via HTTP requests with the Requests library, covering database interactions, data assembly, and API communication.
This page provides a comprehensive catalog of resources covering API testing, unit testing, performance testing, language-specific tutorials (Java, Groovy, Python), case studies, testing tools, UI automation, and related technical articles, offering developers and testers a centralized reference for improving software quality and efficiency.
This guide shows how to instantly create a lightweight HTTP server using a single Python command, enabling fast LAN file downloads and uploads, with step‑by‑step instructions, command examples, IP discovery, and screenshots for both Python 3 and Python 2 environments.
This tutorial demonstrates how to create a full‑stack server‑monitoring web app by setting up a Vue‑based frontend with Element and ECharts, and a Python Flask backend that collects load and disk usage data via Paramiko, stores it in SQLite, and serves it through a JSON API.
This guide shows how to use Baidu's AI speech synthesis service with Python, covering SDK installation, app creation, obtaining credentials, and sample code to convert text—including daily quotes from an external API—into audio files, even customizing voice styles.
This article introduces Python’s built‑in unittest framework, outlining its lightweight advantages, core components such as TestCase, TestSuite, TestRunner and TestLoader, and demonstrates a complete automation workflow from Excel‑based test data preparation to generating HTML test reports with HTMLTestRunnerNew.
This tutorial shows how to use a short Python socket program and the PIL library to capture the PC screen, serve it over HTTP, and view the continuously refreshed desktop on a mobile device by simply entering the server’s IP and port.
An analysis of Indeed's 2014‑2019 job‑posting data reveals that SQL, Java, and Python lead the demand rankings, while AWS, Azure, Docker, and machine‑learning skills show explosive growth, and traditional technologies like Oracle and .NET are rapidly declining.
This article introduces PyAndroidControl, a lightweight Android receiver that periodically uploads screenshots to a Python web server for image analysis and returns executable commands, enabling remote device control via cloud phones without needing Java/Kotlin or ADB on a PC.
This guide walks you through installing MoviePy, extracting audio from MP4 files, trimming video segments, and stitching them together—including advanced effects like mirroring—to automate video editing tasks in Python, with complete code examples and explanations of container formats.
This tutorial walks through creating a web‑based server monitoring tool that tracks CPU load and disk usage, using Vue.js with Element UI and Echarts for the frontend and a Python Flask backend with SQLite for data storage and API delivery.
This article reviews a wide range of Python IDEs, explaining what an IDE is, comparing code editors, and detailing the features, compatibility, advantages, and disadvantages of each tool—from popular choices like PyCharm and VS Code to niche options such as Vim and Emacs—so readers can select the environment that best fits their needs.
This tutorial walks you through building a lightweight web application that uses OpenAI's GPT‑2 model to generate text, covering environment setup, model loading, a custom prediction function, and an interactive Panel‑based UI with callbacks, all in less than fifty lines of code.
This article explains the design, core features, implementation details, and real‑world deployment of the Auto_ApiTest tool for automating API testing in a large‑scale search platform, covering data management, configuration, code examples, CI integration, monitoring, and measurable outcomes.
This tutorial walks through setting up the Python happybase library, installing JPype for Java integration, and demonstrates end‑to‑end code examples for connecting to an HBase Thrift server, generating row keys via Java utilities, querying data, and handling type conversions.
This guide details a Python‑based Scrapy spider that crawls Sina Weibo user profiles, posts, followers and followings from the WAP site, explains the required environment, configuration steps, and the MongoDB schema used to store the collected data.
This article presents seven practical Python scripts—from scraping Zhihu images and chatting bots to poetry author detection, lottery generation, auto‑drafting apologies, screen recording, and GIF creation—showcasing how to quickly automate diverse tasks without reinventing the wheel.
This article provides a thorough tutorial on Python decorators, covering simple decorators without parameters, decorators with optional arguments, class‑based decorators, and advanced techniques such as preserving function metadata with functools.wraps, illustrating each concept with clear code examples and explanations.
This tutorial demonstrates how to use Python's requests library to retrieve every hero image from the game King of Glory, organizing the downloads into separate directories per hero, providing a ready-made collection of high‑resolution wallpapers.
This guide shows how to use Python 2.7 to extend Zabbix 4.2 alerts by attaching the current graph image to email and WeChat notifications, covering environment setup, script details, Zabbix media type configuration, and testing the final result.
This tutorial explains how Python's built‑in enumerate and zip functions simplify list iteration, allowing you to retrieve both element indices and values or combine multiple sequences, with clear code examples and visual illustrations for everyday programming scenarios.
This article presents a comprehensive guide to building and applying a unified API automation testing tool, covering its background, framework design, core features, data and configuration management, public functions, test case handling, logging, execution workflow, CI integration, and monitoring in a search service environment.
This article explains how machine‑learning engineers can create fully functional, interactive apps using only Python and the open‑source Streamlit framework, covering its core principles, widget handling, caching, GPU support, deployment workflow, and real‑world examples with code snippets and diagrams.
This article introduces essential Pandas techniques for data import, cleaning, type conversion, and merging, providing clear code examples that demonstrate reading from MySQL, handling missing values, transforming columns, and combining multiple DataFrames for comprehensive data analysis.
This article explains why left‑recursive rules break recursive‑descent parsers, demonstrates how naïve grammar rewrites alter parse trees, and introduces an oracle‑based memoization technique with a custom @memoize_left_rec decorator to correctly handle left recursion in PEG parsers.
This article reviews the most popular Python IDEs, explains what an IDE is, compares each tool's features, compatibility, advantages and disadvantages, and helps developers choose the environment that best fits their experience level and project requirements.
Using Python to scrape 150,000 NetEase Cloud Music folk lyrics, the author applies jieba segmentation, word‑frequency analysis, word‑cloud visualization, seasonal and geographic preferences, and SnowNLP sentiment scoring to reveal the themes, hopes, and city loves of Chinese folk singers.
This article showcases thirty concise Python code snippets—each explainable in half a minute—that help you quickly solve everyday tasks such as checking list uniqueness, detecting anagrams, measuring memory usage, handling strings, manipulating collections, and more.
This article introduces Python's ConfigParser module, explains its configuration file format, and demonstrates common operations such as creating parser objects, listing sections, adding sections, setting key‑value pairs, retrieving items, and applying these techniques in continuous integration parameterized builds.
This article provides a concise tutorial on Python's core fundamentals, covering program structure, syntax rules, variable naming, reserved keywords, primary data types, string indexing, boolean logic, statement forms, and basic input/output functions for beginners.
This guide shows how to extract average API response times from a MySQL database using Java, process the data with a Python script, and generate an interactive time-series chart with Plotly, providing a practical method for long-term performance monitoring.
This article explains the concepts of processes and threads in Python, compares multi‑process, multi‑thread, and combined approaches, shows how to use fork, the multiprocessing module, process pools, subprocesses, and inter‑process communication with queues, and provides complete code examples with results.
This tutorial explains Python's multithreading model, its advantages and limitations—including the Global Interpreter Lock—demonstrates thread creation with the threading module, shows race conditions and lock usage, compares processes and threads, and discusses when to choose threads, processes, or asynchronous I/O for different workloads.
This article explores a collection of useful yet often overlooked Python features—including functions with arbitrary arguments, file searching with glob, debugging with inspect, generating unique IDs, serialization, compression, and registering shutdown hooks—providing clear code examples and practical explanations for each.
This article explains how to dramatically speed up Python programs by improving algorithms, choosing the right data structures, optimizing loops, leveraging lazy evaluation, using efficient string operations, list comprehensions, profiling tools, and advanced accelerators such as PyPy and Cython.
This article demonstrates how to generate a 100×100 interference dataset in Java, compress it with a transparent layer, and visualize the double‑source interference pattern as a 3D surface plot using Plotly in Python, including full source code and rendered images.
This tutorial shows how to use Matplotlib's animation module to create a Game of Life visualisation in Python, covering the rules, grid setup, code implementation, and how to generate and display the animated plot for data‑science applications.
Python’s ecosystem—Jupyter notebooks, Pandas for data manipulation, scikit-learn for machine learning, and matplotlib/Basemap for powerful visualizations—offers a streamlined, scriptable environment that outperforms traditional Java or PHP workflows, enabling researchers to write, run, and document code seamlessly in a single web interface.
Learn how to create wave interference simulations by generating data with Java, processing it in Python, and visualizing the results using Plotly's contour plot and heatmap features, including step‑by‑step code snippets and configuration details for producing clear interference patterns.
This article walks through the complete process of designing, implementing, and visualizing a Python web crawler that extracts tourism hotspot data from ticketing sites for China's 2019 National Day holiday, covering requirement analysis, URL and element inspection, data collection, cleaning, and geographic heat‑map presentation using Pyecharts.
This article explains why large numbers of active Python objects can cause memory problems and presents several techniques—including using dicts, class __slots__, namedtuple, recordclass, Cython, and NumPy—to shrink object size and dramatically lower memory consumption.
This guide shows how to use Python and Plotly to create a distplot—combining a histogram and density curve—to visualize API response time data read from a log file, complete with a ready‑to‑run script and sample output image.
This article explains how the Python library Camelot can quickly extract tables from PDF files, convert them into pandas DataFrames, and export the data to various formats, while also covering installation options and providing a concise code example.
Discover a curated selection of open‑source utilities spanning Go‑based alert visualizers, command‑line benchmarkers, Python image generators, C REPLs, TypeScript web linting, and strict Python style guides, each with brief descriptions and links, offering developers valuable resources for web, ops, and general programming tasks.
This guide walks through using Python's requests and BeautifulSoup libraries to simulate Zhihu login, extract user profiles, retrieve answer likers, download avatars, fetch all answers for a question, and store the collected data in a SQLite database.
This article presents six challenging Python quizzes covering list comprehensions, decorators, descriptors, inheritance, metaclasses, and special methods, each accompanied by code illustrations and detailed solutions to help developers uncover common pitfalls and deepen their understanding of the language.
