This article presents thirty concise Python code snippets that demonstrate common programming tasks such as checking duplicates, counting vowels, merging dictionaries, measuring execution time, and performing list manipulations, each explained with clear examples for quick learning.
This tutorial explains how to use Scrapy's Request objects to feed article detail URLs into the crawler, configure callbacks for parsing, handle relative URLs with urljoin, and yield requests so Scrapy can download pages, completing the core data extraction workflow.
This article demonstrates how to scrape the Hurun Rich List from 2015 to 2020 using Python, clean the data, and create interactive visualizations of the top 20 wealth holders, wealth trends over six years, and industry shifts with Pyecharts.
This tutorial shows how to configure Scrapy to start from a list page, extract every article link, follow pagination automatically, and parse each article using XPath/CSS selectors, with practical shell commands and visual examples.
This article explains how to scrape detailed job description and address information from online job portals, use Python libraries such as requests, BeautifulSoup4, and pymongo for crawling, and then clean and normalize the collected data including publish dates, salaries, and work‑experience levels before storing it in MongoDB.
This guide shows how to install the Python Kubernetes client, initialize it, and perform comprehensive Job operations—including creation via SDK objects, YAML or dict definitions, monitoring with Watch, listing, reading, updating, and deleting Jobs—while providing concrete code snippets and best‑practice advice.
This guide explains what a message queue is, why it’s used in asynchronous architectures, walks through installing RabbitMQ on Linux and macOS, and demonstrates core patterns such as simple queues, work queues, publish/subscribe, routing, topics, and RPC with complete Python code examples.
This article recounts the author's three‑year journey building a Python‑based HR SaaS backend, detailing the architectural evolution from an initial Django MVC prototype through service splitting and microservices with Kong and custom RPC, to a domain‑driven design approach, and shares lessons learned and optimizations.
After two decades of Java and C dominating the TIOBE rankings, Python has surged to the second spot, prompting a discussion on why programming skills are becoming a universal necessity and how the latest index can guide developers in choosing the right language for future projects.
This article demonstrates how to locate and extract cover‑image URLs from a web page using Scrapy, explains handling absolute and relative URLs, shows the necessary XPath and meta‑passing code, and provides debugging tips to verify that the image URL is correctly transferred through the spider.
This article explains how to use Python's list index method to locate an element, details its full signature, performance considerations for large lists, ways to retrieve multiple matches, handling missing elements with exceptions, and useful tips like using the help function.
This tutorial explains how to retrieve an article’s cover image URL by starting from the list page, extracting the first image, and passing its URL through Scrapy’s Request meta dictionary to subsequent parsing callbacks, highlighting why list‑page extraction is more reliable than detail‑page scraping.
The newest TIOBE ranking shows Java's popularity slipping while Python climbs to the second spot, marking a historic shift in programming language trends and prompting developers to reassess language choices based on search‑engine‑driven popularity metrics.
This guide introduces NumPy, the core Python package for numerical computing, covering its ndarray structure, creation methods, attributes, reshaping, indexing, arithmetic and statistical functions, random number generation, and practical code examples to help you efficiently manipulate large data arrays.
This tutorial walks through checking the default Python version on a Linux system, locating its binaries, downloading Python 3.6.5 source, installing required build dependencies, compiling and installing Python, creating symlinks, and configuring environment variables, while also addressing common network and repository issues.
The article explains how automated testing—using Python‑based UI and API frameworks, configurable test‑data generation, Linux headless execution, and Jenkins continuous integration—addresses the growing complexity of software releases by reducing manual regression effort and improving defect detection speed.
This article walks through five common data‑cleaning scenarios—dropping/renaming columns, handling duplicates and nulls, string manipulation, merging tables, and window‑function ranking—showing practical SQL and Python code that can be applied to large‑scale data warehouses.
Discover 15 practical Pythonic techniques—from swapping variables and list comprehensions to context managers and chain comparisons—illustrated with clear code examples, while also learning how to claim free Python e-books through a simple WeChat interaction.
After three years of evolving a Python‑based HR SaaS backend from a simple MVC prototype to a microservices architecture with domain‑driven design, the author shares the architectural stages, challenges faced, and practical optimizations such as uWSGI‑gevent, Redis pooling, Kong API gateway, and custom RPC framework.
This guide walks you through extracting likes, comments, and article content from web pages using Scrapy’s CSS selectors, showing how to locate elements like bookmark buttons, parse numeric data with regular expressions, and integrate the resulting code into your Python spider for reliable data collection.
This guide walks through Python file operations—including opening, closing, reading, writing, path handling, file copying, CSV handling, in‑memory streams, sys.stdin/stdout/stderr redirection, and JSON vs. pickle serialization—providing code examples and practical tips for each topic.
This article demonstrates how to build a basic Tornado server, measures its performance under blocking operations, and then progressively applies multithreading, thread‑pool executors, and finally asyncio to achieve dramatically higher QPS and lower response times.
This guide walks you through using the Python httpx library to perform various HTTP methods—including GET, POST, PUT, DELETE, HEAD, and OPTIONS—handle query parameters, decode responses, work with JSON, custom headers, form data, file uploads, streaming, cookies, redirects, and authentication, all with clear code examples.
The author recounts a three‑year journey of scaling a Python‑based HR SaaS backend from a simple Django MVC prototype to a microservice architecture with domain‑driven design, detailing each architectural stage, the challenges faced, and the concrete optimizations applied.
This article introduces eight widely used Python web scraping tools—Scrapy, PySpider, Crawley, Portia, Newspaper, Beautiful Soup, Grab, and Cola—detailing their main features, typical use cases, and project links, helping developers choose the appropriate framework for data extraction tasks.
This article introduces the fundamentals of CSS selectors, compares them with XPath, and demonstrates step‑by‑step how to use CSS selectors in Scrapy to extract titles, dates, tags, likes, and other article data from web pages.
This article showcases a collection of practical Python snippets covering function chaining, mutable default argument traps, CSV reading and writing, number base conversion, JSON formatting, list flattening and merging, most‑common character counting, safe eval usage, matrix transposition, list comprehensions, permutations/combinations, defaultdict usage, and dictionary reversal techniques.
The author recounts a four‑stage evolution of a Python‑based SaaS backend—from a simple Django MVC prototype through service splitting, microservice adoption with Kong and custom RPC, to an exploratory domain‑driven design—highlighting practical problems, optimizations, and architectural trade‑offs.
This guide walks you through installing Scrapy-Distributed, setting up RabbitMQ and RedisBloom containers, creating a sitemap spider, configuring the distributed scheduler and dupefilter, and running the spider, while explaining why this non‑intrusive solution improves over existing Scrapy‑Redis and scrapy‑rabbitmq approaches.
This article presents a collection of practical Python snippets covering string reversal, title‑casing, set‑based deduplication, list multiplication, list comprehensions, variable swapping, splitting, joining, palindrome checking, Counter usage, dictionary merging, timing, flattening, random sampling, digit extraction, uniqueness testing and more, each illustrated with clear code examples.
This article details how Instagram migrated its massive Python 2/Django codebase to Python 3, describing the motivations, technical obstacles such as Unicode, pickling, iterator changes, the tools and strategies used, and the resulting CPU, memory, and latency improvements across billions of users.
This article explains the structure of MySQL ROW‑mode binlogs, demonstrates how to modify binlog events with Python to recover deleted rows, locate oversized transactions, and split large transactions into smaller ones, providing practical scripts and examples for advanced database manipulation.
This guide demonstrates how to use Python's redis module to manipulate all major Redis data structures—strings, lists, sets, sorted sets, and hashes—detailing each command, providing clear code examples, and showing expected output for practical learning.
The article outlines eight major software development trends expected to dominate the next ten years, including the continued rise of artificial intelligence, Python’s growth with AI/ML, 5G’s impact, edge and cloud computing expansion, emerging languages like Rust, Kubernetes dominance, React’s persistence, and the lowering barrier for self‑taught programmers.
This article explains the motivation behind circuit breakers, illustrates how cascading failures occur in distributed microservices, describes the three circuit breaker states (closed, open, half‑open), and provides Python and Envoy configuration examples to implement fault‑tolerant service communication.
This article continues a Scrapy tutorial by showing how to extract like counts, comment counts, and full article content using XPath selectors, regular expressions, and debugging techniques, providing step‑by‑step code examples and screenshots to help Python developers automate web data collection.
This tutorial walks through building a Flask‑based search engine powered by Elasticsearch, covering configuration files, logging setup, blueprint routing with pagination, application initialization, and deployment options using Flask‑Script and Gunicorn, with complete code examples and a GitHub repository link.
A Keepthescore founder accidentally ran a local‑only database reset function on production, causing thousands of scores to vanish, but daily DigitalOcean backups enabled a rapid restore, illustrating the perils of unsafe code and the vital role of reliable backups.
This article introduces MySQL 8.0.21's built‑in multi‑threaded logical backup utility, compares it with legacy tools like mysqldump and mysqlpump, demonstrates usage of dump_instance, dump_schemas and load_dump with Python‑style code snippets, and summarizes performance results and recovery steps.
This article details Instagram's journey from Python 2 to Python 3, explaining why Python and Django were chosen, the engineering challenges faced during the migration, the performance improvements achieved, and the key takeaways for building and scaling high‑traffic backend services.
This article provides a comprehensive overview of the most common Selenium WebDriver exceptions, categorizes them into checked and unchecked types, details language‑specific variants for Java, C# and Python, and offers practical guidance on diagnosing and handling each exception during automated browser testing.
This tutorial shows how to apply XPath expressions within the Scrapy framework to extract titles, publication dates, tags, content, likes, favorites, and comments from a sample website, providing practical code snippets and tips for reliable web data collection.
This article reviews popular Python editors—including Sublime Text, IDLE, Vim, PyCharm, Emacs, WingIDE, LiClipse, and Spyder—highlighting their features, platform support, and suitability for beginners, and recommends starting with IDLE or Sublime Text before advancing to more powerful tools like Vim.
This article provides a concise overview of Python’s built‑in standard library modules, covering text handling, data structures, mathematics, functional programming, file and directory utilities, persistence, compression, encryption, OS tools, concurrency, inter‑process communication, and internet protocols, helping developers quickly locate the right tool for their tasks.
This article explains Python's class (static) variables versus instance variables, demonstrates how they are accessed and overridden, and details the differences between class methods, instance methods, and static methods, including naming conventions for private and protected attributes, supplemented with clear code examples and expected outputs.
This article walks through using FastAPI middleware for request timing, redirection, host whitelisting, and CORS, demonstrates background tasks and custom response codes, and explains various deployment options including Uvicorn, Gunicorn, Docker, and Nginx, providing complete code examples.
Jenkinsclient is an open‑source, Python‑based, cross‑platform command‑line client that offers Docker‑style commands to manage multiple Jenkins instances, covering configuration, nodes, plugins, credentials, jobs, queues, executors, and builds, with simple installation via pip.
This tutorial walks you through Python's dictionary and set data structures, covering creation, key uniqueness, updating, deleting, copying, and built‑in methods like keys(), while contrasting them with lists and tuples for clear, practical understanding.
This article introduces SQLAlchemy as a Python ORM, shows how to install and configure it in a Flask project, defines Article and Article_Detail models, demonstrates CRUD routes, explains database migration with Flask‑Migrate, and covers comment handling and rollback procedures.
This article walks you through creating a fully functional Gobang (Five‑in‑a‑Row) game using Python's Tkinter library, covering GUI setup, board rendering, game logic, win detection, undo and reset features, and provides the complete source code ready to run.
This guide walks you through installing the MariaDB Python connector, establishing a secure connection, executing SELECT and INSERT statements, handling transactions and errors, and properly closing the connection, providing a complete workflow for Python developers working with MariaDB databases.
This article explains how Python's dynamic objects consume hidden memory, demonstrates measuring object sizes with sys.getsizeof and a recursive get_size function, and shows how using __slots__ can dramatically reduce memory footprints while discussing trade‑offs and practical code examples.
This guide explains how to set up, configure, and run the Ceph s3-tests compatibility suite—including installation, virtualenv setup, config.yaml creation, HTML reporting with nose-html-reporting, and custom test extensions—to reliably validate S3 API behavior in object‑storage environments.
This article explains Python's object‑oriented fundamentals, covering class and instance attributes, instance, class and static methods, inheritance techniques, the super() function, and the @property decorator, each illustrated with clear code examples.
This tutorial explains how to use Python to scrape Wallhaven for 4K wallpapers, automatically iterate through pages, download images in bulk, and handle request headers and delays to avoid blocking, providing complete code and result screenshots.
The article examines the September 2020 TIOBE programming language index, highlighting C’s rise to the top spot, Java’s decline, the rapid growth of C++ and Python, and discusses how these trends can guide developers in choosing which language to learn.
Learn how to efficiently build Python web scrapers by mastering basic GET and POST requests, configuring proxy IPs, handling cookies, spoofing browser headers, enabling gzip compression, and leveraging multithreaded concurrency to accelerate data extraction.
This tutorial walks you through setting up a Python environment, installing required dependencies, and using AssemblyAI’s high‑accuracy speech‑to‑text Web API to upload audio files, start transcription, and retrieve the transcribed text, including tips for handling API keys and checking transcription status.
This article introduces Python’s sys standard library, explains its purpose, and provides clear, code‑driven walkthroughs of seven key sys functions—including exc_info, getprofile, getrecursionlimit, gettrace, setprofile, setrecursionlimit, and settrace—complete with illustrative screenshots.
This tutorial walks through Python fundamentals, covering primitive data types, operators, variables, collections, control structures, functions, classes, modules, and advanced features such as generators and decorators, all illustrated with clear code examples and explanations.
This article introduces Python’s sys module, a core standard‑library component closely tied to the interpreter, and walks through twelve of its most useful attributes—such as argv, path, modules, executable, and version—providing concise explanations, code snippets, and visual illustrations to help readers understand and apply each variable effectively.
Learn to uncover concealed Wi‑Fi networks by capturing router signals with a wireless adapter, using Ubuntu’s airodump-ng and Python’s Scapy library to monitor packets, identify hidden SSIDs, and display them when a client connects, complete with step‑by‑step setup and screenshots.
This article explains why configuration files are essential, compares popular formats such as INI, JSON, TOML, and YAML, and provides Python code examples for reading each type while highlighting their advantages, limitations, and security considerations.
This article explains why Python objects consume more memory than expected, demonstrates how to measure the true size of objects with a recursive get_size function, and shows that adding __slots__ to a class can dramatically reduce memory consumption while slightly improving performance.
This guide explains how to install PyInstaller, package Python scripts into standalone executables, extract and decompile those executables to retrieve source code, and finally protect the packaged program by using PyInstaller's encryption option, while also covering common pitfalls and solutions.
This article explores Python's preference for snake_case naming, comparing it with other conventions, outlining readability and typing advantages, and tracing its historical roots and the language's unique affinity for the underscore character.
This article introduces the cutecharts Python library that generates hand‑drawn style visualizations, explains how to install it, describes common chart parameters, and provides detailed API references and code demos for Bar, Line, Pie, Radar, and Scatter charts, complete with example images.
This tutorial walks through using Selenium to handle pop‑ups and simple numeric captchas on a web portal, captures the captcha image, applies binary thresholding, recognizes the text with Tesseract OCR, and then submits the login credentials, including retry logic for failed recognitions.
This guide explains five key PyTorch tensor functions—expand, permute, tolist, narrow, and where—detailing their purpose, usage, and code examples so you can manipulate tensors efficiently on CPU or GPU.
This tutorial walks you through using Python's requests, lxml, and JSON parsing to automatically crawl the King of Glory website, extract hero skin URLs, and download the images into organized folders while displaying progress in the console.
This article demonstrates how to configure Python's logging module for console and file output, extend it with HTTPHandler for remote logging, and improve performance by using custom handlers, threading, thread pools, and asynchronous aiohttp calls to avoid blocking the main program.
This article explains the five underscore naming patterns in Python—single leading, single trailing, double leading, double leading and trailing, and a solitary underscore—detailing their conventions, the name‑mangling mechanism, and how they affect class attributes and imports.
This article introduces Python's DB‑API for interacting with various databases, explains how to use PyMySQL and SQLAlchemy for MySQL, demonstrates basic CRUD operations, safeguards against SQL injection, and shows how to implement thread‑safe connection pools with DBUtils for scalable backend applications.
This tutorial walks through creating a Python program that scrapes product links, names, and images from a Taobao store, logs the process, exports the data to Excel, and provides a user‑friendly Tkinter GUI for searching and controlling the scraper.
This article walks through creating a Python web scraper that extracts financial data for over three thousand listed companies, starting from a simple pandas script and progressively adding error handling, MySQL storage, and multiprocessing to build a robust, production‑ready tool.
This article provides a comprehensive guide to Python’s zip() function, covering basic, advanced, and creative usages, explaining its underlying implementation, highlighting limitations such as the “shortest‑iterator” behavior, and presenting solutions like zip_longest and the upcoming PEP‑618 changes.
This article presents a practical solution for eliminating POI label overlap on maps by applying 2D collision‑detection techniques and the A‑Star path‑finding algorithm to intelligently position labels and draw connector lines, complete with Python and OpenCV code examples.
This article introduces the official Matplotlib cheatsheet on GitHub, highlights its comprehensive coverage of common and advanced plotting techniques, and provides links to high‑resolution images and code examples, helping Python users master data visualization efficiently.
This tutorial introduces Seaborn—a Python statistical visualization library built on matplotlib—covers its advantages, installation methods, a step‑by‑step workflow for importing data, setting up the canvas, creating various plot types (histogram, scatter, bar, line, box, violin, heatmap, etc.), and demonstrates a practical example with full code snippets and visual outputs.
This article explores Python’s core concept that everything is an object, explaining how variables reference objects, the role of the id() and type() functions, and the differences between mutable and immutable objects with practical code examples.
This article introduces time series fundamentals, classification, and challenges for internet businesses, then provides a step‑by‑step Python tutorial on ARIMA modeling—including data loading, stationarity testing, differencing, ACF/PACF analysis, AIC‑based order selection, model training, prediction, error evaluation, exogenous variable integration, and diagnostic checks.
This article analyzes a Scrapy‑Redis crawl of Lianjia data from July 2020, cleans and enriches the dataset, and uses pandas profiling and visualizations to uncover Shanghai’s second‑hand housing price distribution, regional hotspots, housing types, and market dynamics during the first half of 2020.
This tutorial walks you through checking the pre‑installed Python version, locating its binaries, downloading Python 3.6.5 source, installing required dependencies, compiling and installing the interpreter, creating symlinks, and configuring environment variables on a Linux system.
PaddleOCR, the 2020 breakthrough in open‑source OCR, offers ultra‑light 3.5 MB multilingual models, high F1‑score performance across diverse scenarios, easy installation via pip, comprehensive documentation, custom training support, and deployment options for both server and mobile platforms, all backed by detailed benchmarks and code examples.
This tutorial walks you through installing openpyxl, understanding Excel's workbook‑sheet‑cell hierarchy, and provides step‑by‑step code examples for reading, writing, styling, and manipulating Excel files using Python, serving as a handy reference for developers.
This article explains how to implement a user‑based collaborative filtering recommendation system in Python, covering data loading, preprocessing, cosine‑similarity computation, neighbor selection, rating prediction, and generating top‑5 movie recommendations with detailed code examples.
This article explains how to use Python's pandas and numpy libraries to batch‑process dozens of CSV or Excel files, extracting the maximum and minimum values from a specific column efficiently without manual effort.
Discover five essential, free Python tools—including Python Tutor, IPython, Jupyter Notebook, Anaconda, and Skulpt—that boost productivity, simplify learning, and streamline development for anyone seeking powerful, community‑driven solutions.
This tutorial explains how to construct a recommendation system by loading transaction data, creating sparse user‑item and item‑item matrices, applying Log‑Likelihood Ratio for item similarity, and indexing the results into ElasticSearch for real‑time serving, using Python and open‑source big‑data tools.
This article explains Python's mutable and immutable types, shows why a += b and a = a + b behave differently for lists and dictionaries, and clarifies the underlying __add__ versus __iadd__ methods with illustrative diagrams.
This guide explains why a common Bokeh runtime error occurs due to an outdated package, walks you through upgrading Bokeh in PyCharm with step‑by‑step screenshots, and shows the resulting error‑free plot rendering.
This tutorial introduces Python's requests‑html library, covering installation, basic page fetching, link extraction, element selection with CSS and XPath, rendering JavaScript, pagination, direct HTML usage, custom request options, form login, and practical crawling examples.
To enhance object detection robustness, the article discusses various data augmentation methods—including rotation, flipping, random cropping, scaling, color jitter, blurring, transparency adjustment, and image partitioning—providing code examples and illustrating their impact on model performance with before‑and‑after results.
This article provides an extensive overview of feature engineering, covering feature understanding, cleaning, construction, selection, transformation, and dimensionality reduction techniques, illustrated with Python code using the Titanic dataset, and offers practical guidelines for improving data quality and model performance in machine learning projects.
This article explains the principles of leaky‑bucket and token‑bucket rate‑limiting algorithms, compares their behavior in high‑concurrency e‑commerce scenarios, and provides a complete Python implementation to illustrate how token‑bucket can handle burst traffic while maintaining system stability.
Using Python Selenium, the author collected 4,403 Taobao listings for men's shorts, cleaned the data, visualized regional sales, price distribution, top shops, and product characteristics, ultimately identifying the best-selling items and revealing market trends.
Discover five open‑source stock‑trading utilities—funds, ZVT, QUANTAXIS, StockAnalysisSystem, and match‑trade—each offering real‑time data, backtesting, multi‑asset support, and high‑performance matching to help programmers build powerful quantitative finance applications.
This article describes a Python‑based approach that identifies and eliminates WeChat group members who repeatedly post advertisements by defining heuristic rules, capturing screen coordinates with the pynput library, simulating mouse‑clicks and keyboard shortcuts, and processing the extracted data to flag suspicious accounts.
This article surveys the rise of microservices and presents a comprehensive list of widely used Java, .NET, Node.js, Go, and Python frameworks, highlighting their features, adoption statistics, and suitability for building scalable, loosely‑coupled backend systems.
This article explains how Linux command‑line pipelines work, highlights the limitations of traditional shell scripts, and demonstrates how a concise Python script can replace them for counting unique users in log files while remaining easy to read, reusable, and powerful.
