The IEEE Spectrum 2021 programming language ranking shows Python retaining the top spot across overall and multiple sub‑rankings while Microsoft’s C# jumps from 23rd in 2020 to 6th in 2021, reflecting shifting industry demand and emerging trends.
This article explains Python's automatic garbage collection, covering reference counting, the mark-and-sweep algorithm, generational collection, default thresholds, and when to disable or adjust the collector for performance‑critical code.
This article presents a series of Python fundamentals tutorials, covering number reversal, adding class docstrings, setting file encoding, rotating strings, implementing a console progress bar, redirecting print output to files, and merging two lists with sorting, each accompanied by concise code examples.
This tutorial shows how to build a Python script that scrapes daily recipe articles from a website, formats the content, and automatically sends it via email using SMTP, providing a practical example of web scraping and email automation.
This article explains how Ctrip tackled the long, costly ML model development‑to‑deployment pipeline by adopting and extending MLflow for full lifecycle management, covering model persistence, tracking, serving, custom pyfunc models, Dockerized deployment, scaling, and performance monitoring.
Python decorators are a powerful syntactic feature that allow functions, methods, or classes to be wrapped and extended, enabling reusable code for logging, caching, authentication, and more, with detailed explanations of their underlying principles, manual implementations, syntax sugar, and usage with classes and built‑in decorators.
This guide explains how to use Selenium to automate testing of Electron desktop applications on macOS, covering ChromeDriver selection, Electron project creation, packaging into a DMG, writing Python test scripts, and controlling already‑running apps via remote debugging.
This article compares Python's while and for loops, shows benchmark results revealing that for loops run faster due to fewer Python‑level operations, and demonstrates that using built‑in functions like sum or applying a mathematical formula can make looping dramatically faster, often eliminating the loop entirely.
This guide explains how to set up an Enterprise WeChat alert application, obtain the required corpid and secret, and use a Python script with WeChat Work APIs to send real‑time notification messages to all users on mobile devices.
This tutorial explains how to generate donut (ring) charts using Python's Matplotlib library, covering basic pie‑to‑donut conversion, custom colors, label positioning, background styling, annotation markers, and multi‑level donut visualizations with complete code examples.
This article traces the historical origins of coroutines from early COBOL compiler challenges, explains their cooperative execution model, compares them with thread scheduling, and reviews how modern languages like Python, C++ and Go implement coroutine support to improve IO‑bound performance.
This guide introduces Kepler.gl, Uber’s open‑source geospatial visualization library, shows how to install it in a Jupyter notebook, demonstrates creating maps from CSV, GeoJSON or DataFrame sources, customizing charts, extracting configurations, and exporting the result to an HTML file for easy sharing.
This article presents a complete Python implementation of a guess‑the‑word (Hangman) game, explaining its mechanics, providing detailed source code, and offering a simplified version for readers to learn basic programming concepts and game logic.
This article explains why third‑party payment platforms like Alipay are used, describes Alipay's payment flow, outlines the configuration steps to obtain APPID and keys, and provides a complete Python implementation for integrating Alipay into backend services.
This tutorial walks you through building a Python scraper that extracts video titles and URLs from Pear Video, then downloads the videos to your computer using single‑threaded requests, a thread‑pool, and asynchronous asyncio techniques, complete with full code examples.
This article introduces Python process concepts, including process creation with the multiprocessing module, process states, comparison with threads, and practical examples of creating, managing, and communicating with processes, followed by a comprehensive overview of Python list types, their structure, operations, and common usage patterns.
This article walks through creating a Python arithmetic interpreter with the PLY library, covering token definitions, lexer rules, BNF grammar, parser implementation, operator precedence, and a runnable REPL, providing complete code and explanations for each step.
This article presents a collection of Python pitfalls such as random sampling, lambda binding, copying, equality vs identity, and type checks, followed by a concise guide for C/C++ programmers transitioning to Python, and showcases useful tools like CSV handling, itertools, collections, and performance‑debugging techniques.
This tutorial walks through using Selenium to log into Alibaba International, scrape supplier phone numbers and related details across multiple pages, save the data to CSV, download product images, and finally embed those images into an Excel workbook for easy reference.
This article explains the differences between synchronous and asynchronous execution, explores various I/O programming models—including blocking, non‑blocking, multiplexed, signal‑driven, and asynchronous I/O—and describes how event‑driven architectures apply these concepts in server‑side development.
This article demonstrates how to build a reproducible fraud‑detection workflow using scikit‑learn's Pipeline class, comparing a manual script with a pipeline‑based approach on the IEEE‑CIS Kaggle dataset and showing the benefits of modular, repeatable ML code.
This article provides a Python script that uses the itchat and schedule libraries to automatically log in to WeChat, select friends with remarks, and send randomly chosen New Year greeting messages to each contact at a specified date and time.
This article explains a streamlined method to extract and download watermark‑free Douyin short videos by inspecting network requests, locating hidden video URLs, and using a concise Python script with the jsonpath library, highlighting its advantages and remaining limitations.
This tutorial explains how to use the pyecharts library—a Python wrapper for Baidu's ECharts—to generate a wide range of interactive visualizations, including bar, line, pie, map, heatmap, scatter, 3D, and combined charts, with complete code examples and rendering instructions for Jupyter notebooks.
Discover the essential Python tools, IDEs, and libraries for 2022—including PyCharm, Jupyter Notebook, Keras, pip, Scikit‑Learn, Sphinx, Selenium, and Beautiful Soup—to enhance productivity, streamline coding, and empower developers across web, data science, and AI projects.
This tutorial shows how to use Python, ADB, and OpenCV to automate the mobile game Princess Connect, covering environment setup, device communication, screen capture, image matching, OCR, and script snippets for clicking, typing, and switching accounts.
This article surveys the ten most prominent Python libraries for machine learning released in 2021, highlighting both internationally popular and high‑performing Chinese open‑source projects, and explains their main features, performance advantages, and where to find them on GitHub.
This article dissects Optuna’s internal design by building three miniature versions (Minituna v1‑v3) that illustrate its main components, storage layer, sampling APIs, pruning mechanisms, and joint‑sampling concepts, while comparing them with Optuna’s full implementation.
This article explains how to use Python's socket module together with I/O multiplexing techniques such as select, poll, epoll, and the high‑level selectors module to build non‑blocking, scalable network servers that can handle multiple client connections concurrently.
This comprehensive tutorial walks you through installing Selenium and ChromeDriver, initializing browsers (including headless mode), navigating pages, locating elements using various strategies, interacting with forms, handling multiple windows, performing mouse and keyboard actions, implementing explicit and implicit waits, executing JavaScript, and managing cookies for robust web automation and scraping.
This comprehensive guide explains QR code fundamentals—including their structure, versions, error‑correction levels, and data capacity—details the full encoding pipeline from requirement analysis to matrix construction, outlines the decoding steps, explores commercial use cases, and provides practical Python examples using python‑qrcode, Amazing‑QR, and Zxing.
This article reviews the ten most notable Python libraries for machine learning in 2021, covering tools for handling nested data, notebook versioning, lightweight model demos, data management, multimodal augmentation, model monitoring, object detection, fast inference, time‑series forecasting, and neural search.
This tutorial explains pandas' four primary data merging functions—concat, merge, append, and join—detailing their usage, key parameters, and practical code examples to help you efficiently combine DataFrames in various scenarios.
This article provides an in‑depth overview of QR codes, covering their definition, types, structural features, versioning, error‑correction levels, encoding and decoding processes, commercial uses, design considerations, and practical Python examples for generating and reading QR codes.
This guide explains how to collect images from Zhihu’s “美女” topic using Python’s Requests and lxml, filter them with Baidu’s AipFace SDK based on face presence, gender, authenticity, and beauty score, and store the qualified pictures locally.
This article walks through building an image‑captioning system using a TensorFlow 2.0 encoder‑decoder with Bahdanau attention, covering dataset preparation, feature extraction with InceptionV3, model architecture, training with teacher forcing, and inference on the Flickr8K dataset.
This tutorial demonstrates how NumPy can be used to generate and display grayscale, color, gradient, and colormap‑enhanced images in Python with just a few lines of code, covering module import, array creation, image conversion, and advanced color mapping techniques.
This article presents a thorough collection of frequently used pandas commands for importing data, preprocessing, cleaning, transforming, analyzing, and visualizing datasets, complete with code examples and explanations to help Python developers perform efficient data analysis tasks.
This article introduces Python's collections module, explaining the purpose and usage of its specialized container types—including Counter, defaultdict, OrderedDict, namedtuple, deque, and ChainMap—along with their most common methods and practical code examples.
This guide demonstrates how to use a second‑hand housing dataset to create various reports—frequency tables, cross‑tables, and summary statistics—and visualise them with bar and stacked bar charts using Python's pandas library.
This article presents practical Python best‑practice guidelines, including avoiding hard‑coded numeric literals by using enums, limiting raw string manipulation in favor of object‑oriented query building, keeping literal expressions readable, and applying useful tips such as treating booleans as numbers, handling long strings, using infinity constants, and understanding thread‑safety and string‑concatenation performance.
This article demonstrates how to use Python and pandas to automatically add a column containing each workbook or sheet name to every sheet in multiple Excel files and then merge all the data into a single file, dramatically reducing manual effort.
This article introduces CatBoost, outlines its key advantages such as automatic handling of categorical features, symmetric trees, and feature combination, and provides a step‑by‑step Python tutorial—including data preparation, model training, visualization, and feature importance analysis—using a CTR prediction dataset.
This tutorial explains how to solve the LeetCode "Lucky Numbers in a List" problem in Python by extracting unique elements, counting their occurrences with map and count, pairing them with zip, filtering with lambda, sorting the result, and finally compressing the whole logic into a single expressive line of code.
This article explains the theory behind variational autoencoders, details their KL‑divergence loss, provides a complete TensorFlow implementation, and demonstrates reconstruction, latent‑space visualization, and novel image generation through sampling and interpolation.
This article explains how to use TensorFlow’s tf.data API to construct high‑performance, flexible data pipelines—from loading images or tensors, applying transformations and data augmentation, to batching, shuffling, caching, prefetching, and feeding the pipeline directly into model.fit for training.
This article introduces the Python libraries memory_profiler and Pytorch‑Memory‑Utils, demonstrates how to measure line‑by‑line CPU memory consumption and GPU memory usage in notebooks and scripts, and explains the additional overhead introduced by PyTorch during model loading.
This tutorial walks through building a TensorFlow 2.0 autoencoder from scratch, preparing the FashionDB dataset, visualizing raw images, projecting them into PCA and t‑SNE spaces, constructing encoder and decoder layers, training the model, and visualizing the resulting latent space to reveal image clusters.
This guide walks you through analyzing a target e‑commerce site, using Selenium to automate searches, extracting product details across multiple pages, handling pagination, parsing HTML with PyQuery, and persisting the collected data into a MySQL database with robust error handling.
This article explains the fundamentals of random forest regression, describes why it outperforms single decision trees for nonlinear or noisy data, defines bootstrapping and bagging, and provides a step‑by‑step Python example using NumPy, Pandas, and Scikit‑Learn’s RandomForestRegressor with data loading, preprocessing, model training, prediction, and evaluation via MSE and R².
The article explains how to keep external API contracts unchanged while replacing a data source by importing all microservice endpoints into Postman, writing pre‑request and test scripts, and optionally using a Python Flask service with deepdiff to automatically compare old and new JSON responses.
This guide provides a comprehensive Vim setup for Python development, covering .vimrc basics, window splitting, code folding, one‑key execution, plugin management with Vundle, auto‑completion tools, syntax checking, color schemes, file navigation, and useful shortcuts.
This article explains how to perform Chinese part-of-speech tagging using the jieba.posseg library in Python, including loading stop words, extracting article content via Newspaper3k, applying precise mode segmentation, filtering, and presenting results in a pandas DataFrame.
The article explains how concurrent updates can cause data loss in high‑traffic scenarios and demonstrates using optimistic and pessimistic locking in PostgreSQL with Python, including EFCore‑style token checks and a retry mechanism via the tenacity library.
This tutorial walks you through creating a fully interactive sales‑data dashboard using Python's Pandas for data handling, Plotly for visualizations, and Streamlit to assemble a sleek web interface, covering data import, sidebar filters, key metrics, charts, and deployment steps.
The article explains why monitoring production ML models is essential to detect data and target drift, describes the open‑source Evidently AI library and its statistical tests, and demonstrates its use on a weather‑forecast example and a plant‑seedling image classification case, including dashboards, code snippets, and visual analysis of drift impact.
This tutorial introduces the Python pyecharts library for creating various map visualizations with Echarts, explains how the code generates HTML files, and provides complete example functions for basic, label‑less, continuous and piecewise visual maps, world and regional maps, plus guidance for using real data.
This tutorial introduces Plotly for Python, showing how to install it, configure offline mode in Jupyter, and create line, scatter, and bar charts with complete code examples and explanations of each visualization type.
This tutorial shows how to crawl the China Meteorological Administration website to obtain today's weather and a six‑day forecast, handle Chinese encoding, extract data with XPath, and save the results into a CSV file using Python's requests and lxml libraries.
This tutorial demonstrates two Python Turtle methods for drawing a festive Christmas tree, providing step‑by‑step code examples, explanations of the drawing logic, and visual results to help beginners learn basic graphics programming in Python.
This article explains practical techniques for improving NLP model accuracy on massive corpora, covering challenges of multi‑field text, word‑embedding choices, a fasttext‑based regression demo with book‑review data, feature engineering tricks, and a comparison with tf‑idf + LASSO.
This article reviews the lack of a standard Python project management tool, compares four popular solutions—CookieCutter, PyScaffold, PyBuilder, and Poetry—detailing their installation, generated directory structures, and build commands, while showing how to use Make, tox, and other utilities for testing and packaging.
This article introduces the concept of signals, explains the features of the Python Blinker library, demonstrates various usage patterns—including named, anonymous, multicast, and topic‑based signals—as well as how to integrate Blinker with Flask for custom and built‑in Flask signals, highlighting advantages and limitations.
This article explains the fundamental differences between threads and processes, the role of Python's Global Interpreter Lock (GIL), and how to use the multiprocessing package—including Process, Pool, Queue, Pipe, and synchronization primitives—as well as an overview of concurrent.futures for high‑level concurrent programming in Python.
This tutorial shows how to extract Kindle eBooks, convert them to HTML, clean the markup with BeautifulSoup, and batch‑translate the content line‑by‑line using DeepL API Pro, producing a bilingual eBook with minimal manual effort.
This article presents a comprehensive collection of over thirty Python programming exercises covering basic algorithms such as bubble sort, mathematical computations, string manipulation, file system operations, and utility scripts, each illustrated with code screenshots to help learners practice and master fundamental coding skills.
AutoX offers a one‑click solution for tabular AutoML by defining feature operators, constructing a searchable feature space, applying efficient feature selection, tuning hyper‑parameters, and performing model ensembling, enabling users with limited ML expertise to automatically generate high‑performing predictive models, as demonstrated on multiple Kaggle datasets.
The December 2021 TIOBE index reveals the top 20 programming languages, highlights notable movements such as Python’s three‑month dominance, Swift’s rise into the top ten, and C# as a strong candidate for the upcoming annual award, while also explaining the index’s methodology and its limitations.
This guide outlines six Python advancement directions—full‑stack development, web scraping, data analysis & mining, AI & machine learning, DevOps automation, and testing—detailing essential skills, typical salary ranges, and how each role fits the modern job market.
This tutorial shows how to load a NAM NetCDF file with xarray, smooth 500‑hPa geopotential height and wind components, compute wind speed using MetPy, and create a Lambert Conformal map with Cartopy that displays color‑filled wind speed, height contours, and wind barbs, finally saving the figure as an image.
This tutorial walks through building a complete Alien Invasion arcade game in Python using Pygame, explaining the modular design of settings, ship, alien, bullet, button, game statistics, and scoreboard modules, and demonstrates how to implement game loops, event handling, collision detection, and scoring logic.
This article demonstrates how to use Python with pandas and openpyxl to automatically generate yearly Excel workbooks, create monthly sheets, and add predefined column headers, turning a manual multi‑minute task into a fast, error‑free process.
This tutorial demonstrates how to use Python on Windows to crawl Maoyan movie rankings, extract details such as title, rating, genre, region, and duration, store them in a CSV file, and then perform comprehensive data cleaning, analysis, and visualization with pandas, matplotlib, and WordCloud.
This article compares PyInstaller and Nuitka for converting Python scripts into standalone Windows executables, discusses their advantages and drawbacks, provides step‑by‑step installation of Nuitka, explains key command‑line options, and demonstrates a practical example that yields a tiny, fast‑building executable versus a large, slow‑building PyInstaller output.
This article summarizes Sam Gross’s nogil project—a Python 3.9 fork that removes the GIL—detailing its design changes, early benchmarks, integration challenges, and the community’s discussion on feasibility, performance, and the roadmap toward a GIL‑free CPython.
This article walks through a complete Python workflow that loads the 20 Newsgroups dataset, preprocesses the documents, vectorizes them with TF‑IDF, groups them using KMeans, reduces dimensions with PCA, and visualizes the resulting clusters, illustrating each step with code and plots.
The article details a TensorFlow pipeline for detecting white‑screen screenshots in a WebView, covering data preparation from labeled image folders, a CNN architecture with preprocessing, training and validation steps, model saving, inference usage, and strategies to mitigate over‑fitting.
This tutorial demonstrates how to use Selenium to crawl short comments from a Douban movie page, extract them via XPath, paginate through results, and finally create a visual word cloud using Python's wordcloud library.
This article presents Python scripts for cracking ZIP file passwords, explains how to fix Chinese filename encoding issues, and provides single‑threaded, multithreaded, and dictionary‑based brute‑force methods with detailed code examples and usage instructions.
A recent analysis comparing 27 programming languages shows that despite Python's popularity, it and Perl consume far more energy than languages like C, C++, and Rust, challenging common assumptions about performance and environmental impact.
This article demonstrates how to collect historical Beijing weather data using Python web‑scraping, clean and transform it with pandas, visualize overall and monthly patterns, and extract insights such as the first winter snowfall each year and annual snow‑day counts.
This article details a step‑by‑step performance optimization of a Python backend service, covering requirement analysis, architecture redesign with caching and Redis queues, load‑testing results, TCP TIME_WAIT issues, and kernel parameter tweaks that ultimately raised throughput to 50,000 QPS with zero errors.
This tutorial shows how to recreate the classic WeChat airplane battle game using Python and Pygame, covering environment setup, player and enemy plane implementation, keyboard controls, bullet collision detection, and includes full source code and screenshots.
This article explains Python's import mechanism in depth, covering modules, packages, __init__.py files, absolute and relative imports, the role of sys.path, import hooks, meta_path finders, path entry finders, module specs, and loader objects, with code examples and practical tips.
This article introduces the high‑performance gRPC framework, explains why it uses HTTP/2 and Protocol Buffers, outlines its core components, and provides a step‑by‑step Python tutorial with environment setup, code generation, server and client implementations, and common application scenarios.
This article walks through the complete process of moving an Oracle database to PostgreSQL, covering the rationale for open‑source and cloud solutions, the three core migration phases, hands‑on demos of AWS SCT, Ora2PG, and a Python‑based data‑replication example, plus performance results.
This article derives the policy‑gradient objective for discrete actions, implements the Monte‑Carlo REINFORCE algorithm in PyTorch, explains the actor‑critic framework, introduces Advantage Actor‑Critic (A2C) versus A3C, and demonstrates their performance on the OpenAI Gym CartPole‑v0 environment.
This tutorial walks through installing the Mayavi library, explains its core mlab module and API, and provides a series of Python code examples—including mesh, points3d, plot3d, imshow, surf, contour3d, and quiver3d—to demonstrate how to create various 3‑D visualizations.
This article walks through scraping Bilibili documentary data with Python, processing it using pandas, and visualizing regional distributions, genre comparisons, yearly trends, episode lengths, popularity metrics, and comment timing to uncover insights about Chinese, UK, and US documentary patterns.
This article introduces the lightweight Python visualization library cutecharts, explains its installation, and provides step‑by‑step code examples for creating line, bar, pie, radar, scatter charts and combined page charts, demonstrating how to customize options such as labels, legends, colors, and inner radius.
This article explains how to automate the replacement of Excel row data into Word templates using Python, offering two approaches—one with python-docx and win32com for .doc conversion, and another leveraging zipfile to edit the underlying XML—complete with code examples and troubleshooting tips.
This guide walks through cloning the Sentry and Snuba repositories, installing macOS system dependencies, configuring Python and Rust toolchains, launching Docker containers for ClickHouse, Kafka and Redis, running Snuba migrations, and finally starting the dev server to query events via a local UI.
This article walks through creating a satellite image classification pipeline using PyTorch and a pretrained ResNet34 model, covering dataset preparation, project structure, data loading, model definition, training, validation, loss/accuracy plotting, and inference on new images with detailed code examples and results.
This article introduces the Python NetworkX library, covering its installation via Anaconda, fundamental graph creation, node and edge manipulation, attribute handling, directed and multigraph features, built‑in generators, analysis functions, and visualization with Matplotlib, all illustrated with concrete code examples.
This article benchmarks Python while and for loops, shows that for loops are faster due to fewer operations, demonstrates how built‑in functions like sum and direct arithmetic formulas can achieve orders‑of‑magnitude speedups, and concludes that the quickest way to "loop" in Python is to avoid loops altogether.
This tutorial introduces Kepler.gl, an open‑source geospatial visualization library from Uber, showing how to install it in a Jupyter notebook, create maps, load CSV or DataFrame data, customize charts via the GUI, retrieve configurations, and export the interactive map to HTML.
This article provides a step‑by‑step guide to building, training, and evaluating a custom object detection model using PyTorch Faster R‑CNN on a microcontroller dataset, covering data preparation, configuration, model modification, training loops, loss visualization, and inference on new images.
This article demonstrates how to use Python's Selenium WebDriver to log into Alibaba International, scrape company contact information across multiple pages, save the data to CSV, download product images, and embed them into an Excel file, providing a complete automation workflow.
This guide demonstrates how to use Python on macOS to scrape love quotes, store them, and automatically launch QQ to send a random quote each day, including code snippets and steps to set up an Automator app for startup execution.
This guide explains what Shodan is, why internet‑connected devices are vulnerable, and provides step‑by‑step instructions—including environment setup, API key registration, basic Python searches, and advanced facet queries—to safely explore and analyze exposed devices.
