This tutorial explains how to read and write Excel files in Python using xlrd/xlwt for .xls, openpyxl for .xlsx, and pandas for high‑level data handling, including installation commands, code examples, and a practical case of processing a tab‑separated car‑listing file.
This tutorial explains how to set up PrivateGPT, a Python‑based offline LLM solution that runs locally without sending any data to the cloud, covering environment preparation, model download, repository cloning, data ingestion, and interactive querying.
This article demonstrates how to create a Python-based tool that crawls click‑event data from an e‑commerce site, processes and visualizes the information to verify event‑tracking code, covering preparation, data collection, analysis, and visualization steps with complete source code.
This article demonstrates how to ensure data consistency between Redis and MySQL using Python by implementing a synchronization mechanism that monitors MySQL binlog changes and updates Redis cache in real-time.
This tutorial demonstrates how to perform A/B testing on two marketing campaigns using Python, covering data loading, cleaning, merging, and visual analysis of key metrics such as impressions, spend, clicks, searches, content views, add‑to‑cart actions, and purchases to identify the most effective strategy.
This article introduces eight fundamental OpenCV examples—including image reading, display, grayscale conversion, edge detection, resizing, Gaussian blur, and face detection—providing concise Python code snippets and explanations to help readers quickly apply these common computer‑vision techniques.
This article introduces fourteen relatively unknown Python techniques—including the ternary operator, enumerate, zip, list comprehensions, lambda functions, any/all, itertools, generators, decorators, argument unpacking, dynamic imports, dictionary comprehensions, callable objects, underscore separators, and dictionary merging—to help developers write more concise, efficient, and readable code.
This article demonstrates how to use Python, together with the openpyxl and xmind‑sdk libraries, to read a multi‑level Excel test case file, transform its hierarchical data into XMind topics, and generate a visual mind‑map representation of the test cases.
This article introduces the Python Statsmodels library, explains its key features such as linear regression, GLM, time‑series and robust methods, shows how to install it, load data with pandas, perform descriptive statistics, visualizations, hypothesis testing, and simple and multiple linear regression examples.
This article walks through a Python community question about automating office tasks, presents original code for copying Excel files, offers an improved script that recursively moves .xlsx and .xls files, and explains how to adapt the solution for broader file‑automation scenarios.
This article shows how to use Python's os and pandas libraries to automatically traverse nested folders, locate all .xlsx Excel files, and add standardized '经度' and '纬度' column headers, providing a clear, step‑by‑step solution for batch Excel header insertion.
This article explains why adding the decimal numbers 0.1 and 0.2 in binary floating‑point arithmetic yields the surprising result 0.30000000000000004, by detailing the exact 64‑bit representations, the rounding‑to‑nearest‑even rule, and step‑by‑step Python calculations that expose the underlying IEEE‑754 mechanics.
The pdf2docx library uses PyMuPDF and python-docx to extract PDF layouts, paragraphs, images, and tables, offering multi‑process conversion while noting current limitations such as lack of OCR and support for only left‑to‑right languages, and provides simple pip installation and a code example.
This article demonstrates how to use a short Python script with pandas and os modules to automatically locate all .xls and .xlsx files in nested subfolders, add standardized column headers, and save the updated workbooks in a single, streamlined step.
This tutorial demonstrates how to install the python-jenkins library, explore its extensive API methods, and use Python scripts to create, copy, configure, and control Jenkins jobs, nodes, views, plugins, and builds, providing practical examples and code snippets for each operation.
This guide explains how to use Python3, the Requests library, and Beautiful Report to perform automated API testing for WeChat Mini Programs, covering prerequisite knowledge, obtaining an access token, writing test cases, and generating detailed HTML test reports.
Google announced that Colab will soon offer AI-driven code generation, completion, and chat assistance powered by the Codey model, providing a free, multi‑language development tool that rivals GitHub Copilot for Python and machine‑learning workflows.
This article reviews the fifteen Python packages with the highest download counts on PyPI over the past year, explaining each library's purpose, key features, typical use‑cases, and providing code examples to illustrate how they simplify tasks such as HTTP requests, compatibility, cloud interaction, configuration, security, and data handling.
This guide shows how to use Python's os and glob modules to automatically locate every Excel file in nested subfolders, providing step‑by‑step code examples and explanations for extracting file paths and adding headers to each workbook.
This tutorial walks through setting up a Python testing environment, installing required libraries, creating and coding test cases with Selenium, integrating Allure for reporting, and configuring Jenkins to run the tests and publish the results automatically.
This article explains how to create a Python‑based network port scanner that probes a target host, uses sockets and multithreading to detect open TCP ports, and provides clear usage instructions, sample code, and optional enhancements for faster or more comprehensive scanning.
Rye, a Rust‑written Python package manager created by Flask author Armin Ronacher, quickly topped GitHub Trending, offering one‑stop management of Python packages, environments, and projects with features like automatic installation, global isolation tools, and seamless pyproject.toml handling, illustrated through command‑line examples and praised by developers such as Simon Willison.
This article introduces AutoGPT, explains its underlying prompt architecture, built‑in commands, resource management, and JSON response format, and shares insights on how it autonomously executes tasks using large language models in real‑world applications.
This article introduces three Python 3 techniques for bulk file renaming—recursive numbering, renaming based on creation timestamps, and using regular expressions—explaining their advantages, providing complete code examples, and guiding readers on adapting the scripts for their own file management needs.
This guide details the end‑to‑end process of installing GPU drivers, setting up a Python environment, deploying the open‑source Alpaca‑LoRA model, fine‑tuning it with Chinese data on a multi‑GPU server, and performing inference, while highlighting practical challenges and performance observations.
The article explains how Python now exists as both a typed and an untyped language, distinguishes infrastructure code from business‑logic code, and argues that embracing both styles—using type hints for business logic while keeping infrastructure flexible—strengthens developers and improves software quality.
This article explains practical principles and techniques for crafting clear, specific prompts for ChatGPT, demonstrates how to structure prompts with separators and output formats, and provides a step‑by‑step guide—including code examples—for installing the OpenAI Python library, obtaining an API key, and writing a reusable get_completion function to interact with the model.
This tutorial demonstrates how to create a Python script that automatically backs up a chosen source folder to a target location every minute, using shutil and os modules to copy files into timestamped directories for reliable data protection.
This tutorial demonstrates how to use Python's requests and BeautifulSoup libraries to query IMDb for movie details such as title, director, cast, rating, and summary, illustrated with a sample lookup for the film Inception.
This article introduces ten useful pip techniques—including installation, upgrading, version-specific installs, uninstalling, checking for updates, handling compatibility, using domestic mirrors, downloading without installing, and batch installing from requirements files—to help Python developers efficiently manage their packages.
This article demonstrates how to use Python regular expressions together with pandas to parse complex price‑range strings, extract numeric values, normalize missing bounds, split them into separate columns, and optionally convert the results to numeric types for further analysis.
This article presents a collection of Python code examples covering JSON serialization, date‑time formatting, file reading, QR‑code and barcode creation, list and JSON comparison, class method reflection, and automatic file‑size‑based cleanup, providing practical guidance for everyday scripting tasks.
The article introduces SpaceTraders, an old Palm‑OS strategy game now exposed as a RESTful API, shows curl examples for registration, ship purchase, refueling and trading, and explains how building client applications with this API can serve as an engaging way to learn programming concepts.
This tutorial shows how to quickly integrate ChatGPT and Stable Diffusion AIGC models into a WeChat public account or mini‑program using the AIGCaaS platform, covering registration, API Explorer usage, code customization, asynchronous handling, and deployment with Python Flask.
This article introduces Python's DB-API, demonstrates how to install and use PyMySQL for MySQL operations, shows safe query execution, retrieving auto‑increment IDs, and explains two DBUtils connection‑pool patterns with code examples for multithreaded database access.
This article showcases Python's concise syntax and powerful libraries by comparing a simple web request with JavaScript and providing five practical automation scripts—including a URL shortener, fake data generator, YouTube downloader, NATO alphabet encoder, and Selenium-based social‑media login—demonstrating why Python is ideal for repetitive tasks.
Mojo, the new programming language announced by Chris Lattner’s Modular AI, combines Python’s usability with C‑level performance, offering seamless interoperability, extensive compiler optimizations, and scalability for AI workloads, positioning itself as a potential breakthrough in machine‑learning infrastructure and development.
Modular's new Mojo language blends Python's ease of use with C‑level performance, leveraging MLIR and hardware acceleration to claim up to 35,000‑fold speed gains, while offering system‑programming features, zero‑cost abstractions, and a path toward a Python superset for AI development.
This article provides a comprehensive guide to using Pandas for complex queries, data type conversion, sorting, adding and modifying data, advanced filtering, iteration, and functional operations, offering numerous code examples that illustrate how to efficiently clean, transform, and analyze tabular data in Python.
This article introduces eleven practical Pythonic techniques—including destructuring assignment, zip aggregation, lambda usage, underscore placeholders, list comprehensions, dummy functions, regex handling, map/reduce, whitespace trimming, shallow copying, and interpreter shortcuts—each illustrated with clear code examples to help developers write more elegant and efficient Python code.
This article walks through a Python‑based Baidu web‑scraping solution, explaining the problem, showing the debugging process with screenshots, and providing a complete, runnable script that extracts keywords, titles, URLs, descriptions, and site names into a CSV file.
Learn how to create a lightweight, thread‑safe Python configuration manager that reads from and writes to a JSON file, ensures a single global Config instance across multiple threads, and persists changes on program exit using the atexit hook.
This guide explains why Logstash may import fewer rows than exist in a PostgreSQL table, and provides two practical methods—shell‑script ID comparison and Redis‑accelerated set operations—to reliably detect and troubleshoot missing records in Elasticsearch.
This article provides an introductory overview of several widely used programming languages—including Python, Go, C, C++, Java, PHP—and explains why Windows is primarily developed in C++, highlighting each language's origins, key advantages, and typical use cases.
Upgrading from Python 3.7 is essential because the version reaches end‑of‑life in June 2023, losing security fixes and third‑party library support, so developers must plan a migration to newer, maintained releases to keep applications safe and functional.
This article explains how to use pip and Conda to configure, list, freeze, and clean up Python project dependencies, manage virtual environments, and handle cross‑language packages, providing practical commands and tools for reliable environment and dependency management.
Researchers discovered that a specially crafted QR code triggers a memory leak in WeChat’s OCR engine, causing the app to crash on both mobile and desktop platforms; the article explains the underlying bug, provides detailed decoding analysis, and shares Python code to reproduce the malformed QR code.
An unusual QR code triggers a memory‑leak in WeChat’s OCR engine, causing the app to crash on both mobile and desktop; the article explains the underlying null‑pointer exception, shows how the malformed “abnormal QR code” corrupts libqbar.so, and provides Python code to reproduce the bug using OpenCV’s open‑source QR engine.
This tutorial demonstrates how to accelerate processing of a 2.8‑million‑row CSV dataset by using Python's multiprocessing, joblib, and tqdm libraries, covering serial, parallel, and batch processing techniques, performance measurements, and best‑practice code examples for efficient large‑scale data handling.
This guide demonstrates how to use Python's pandas library to merge multiple Excel workbooks—whether from a single folder, across several sheets, or into a single DataFrame—and then convert the resulting data into JSON format, including detailed code examples and explanations.
This article explains how to format positive integer strings with thousand separators in Python by using a concise regular expression and the re.sub function, providing a clear code example and linking to the official documentation for further reference.
This tutorial walks through the complete process of fine‑tuning a Vision Transformer (ViT) model for 14‑class flower image classification on ModelScope, covering dataset preparation, model loading, training configuration, evaluation, and inference with practical code examples.
This article introduces the Python package Pynimate, explains how to install it from PyPI, prepares pandas‑style time‑series data, uses the Barplot function with interpolation parameters to generate smooth animated bar charts, and shows how to export the result as GIF or MP4.
This article explains why and how to fine‑tune the LLaMA‑7B model using the cheap Alpaca‑LoRA approach, covering hardware requirements, dataset preparation, LoRA training, optional model merging and quantization, and provides ready‑to‑run code snippets for single‑ and multi‑GPU setups.
AutoGPT, the latest autonomous AI system, can independently browse the web, use third‑party tools, and execute tasks without human intervention, exemplified by building a React website in minutes, and this article explains its principles, showcases demos, and provides step‑by‑step installation instructions.
This article introduces a collection of lesser‑known Python techniques—including the ternary operator, enumerate, zip, list comprehensions, lambda functions, any/all, itertools, generators, decorators, dynamic imports, dictionary comprehensions, and mutable data structures—each explained with clear examples to help developers write more concise and efficient code.
This article walks through a real‑world Python web‑scraping problem raised in a community, presents a clear solution with parameter adjustments, shows before‑and‑after results, and highlights common pitfalls to help developers reliably extract data.
This article lists the most downloaded Python packages on PyPI over the past year, explains each library’s main features, typical use cases, and why they are popular, and includes code snippets demonstrating common operations such as HTTP requests, date parsing, and RSA encryption.
This article explains how to model massive time‑series data in Cassandra by using bucketing techniques to control partition size, avoid hotspots, and improve write and read performance, including practical CQL schema examples and Python code for concurrent queries.
This article introduces pip, the Python package manager, and provides ten practical tips—including installation, upgrading, batch operations, freezing dependencies, inspecting packages, checking compatibility, and downloading wheels—to help developers efficiently manage Python libraries.
This guide presents ten practical pip techniques—from installing and upgrading pip itself to batch installing, freezing dependencies, checking compatibility, and downloading packages—empowering Python developers to manage third‑party libraries more efficiently and avoid technical debt.
This article walks through a typical Python automation problem where a missing or mismatched file path causes errors, demonstrates how to correct the path, shows two methods for removing the first column after merging tables, and offers practical tips for avoiding similar issues in future scripts.
This article explains how to handle Python environment and dependency management using pip tools such as pip list, pip freeze, pipdeptree, pip‑autoremove, and the conda ecosystem for creating isolated virtual environments, exporting configurations, and integrating with IDEs.
This article walks through practical methods for reading and merging specific Excel sheets with Python's pandas library, providing clear code examples, tips for handling large files, and guidance on asking effective technical questions in community groups.
This article explains why Python uses indentation for block grouping, how floating‑point arithmetic works, why strings are immutable, the purpose of the explicit self parameter, the absence of assignment in expressions, and many other design decisions that shape Python's syntax and runtime behavior.
This guide shows how to collect nationwide weather data for the Qingming Festival via the free QWeather API, process it with Python to generate a CSV file, and visualize the rainfall distribution across China using a desktop data‑visualization tool.
This tutorial shows how to install the JsonPath library, retrieve JSON data from an API, and use both traditional indexing and powerful JsonPath expressions—including filters, wildcards, and slicing—to efficiently extract nested values for automated testing.
The article explains how operations engineers can leverage Python scripts and popular libraries such as paramiko, regex, psutil, fabric, and shutil to automate common tasks like remote command execution, log analysis, system monitoring with alerts, batch software deployment, and file backup and recovery, providing code examples for each scenario.
A Python community member struggled with a regular expression that mishandled backslashes, but by converting the pattern to a raw string with an r prefix, the issue was resolved and the regex matched correctly, illustrating a common pitfall and its simple fix.
This guide introduces RabbitMQ, explains how to install it with Docker, covers basic and advanced producer/consumer usage including acknowledgments, durability, QoS, bindings, and exchange types, and discusses a typical Python reconnection problem, providing a practical overview for backend developers.
This article describes how a mobile development team adopted the ATX automation framework with Python, employing Page Object Model, data‑driven and keyword‑driven techniques to replace manual regression testing, integrate firmware interaction, and streamline test execution and reporting.
This step‑by‑step tutorial shows how to set up a Stable Diffusion web UI, install the required Python environment and GPU‑enabled PyTorch, add Chinese localization and optional LoRA or Deforum extensions, generate realistic human images, create animated videos, and add speech with D‑ID, all ready for deployment on your own AI website.
This article explains why causal inference is essential for moving beyond correlation to decision‑making, introduces the structural causal model framework, and provides a step‑by‑step guide to using Microsoft’s DoWhy Python library for modeling, identification, estimation, and counterfactual analysis.
This article introduces Python's built‑in Turtle graphics library, explaining its drawing principles, import methods, and provides step‑by‑step code examples for creating shapes like triangles, stars, and hexagons, along with usage of color specifications and window configuration options.
This article presents twenty practical Python techniques—including string reversal, title casing, unique element extraction, list multiplication, dictionary merging, and performance timing—that enhance code readability, simplify common tasks, and boost development efficiency for programmers seeking to write cleaner, more effective Python scripts.
Codon, a new Python compiler introduced by IEEE Spectrum, uses static type checking to eliminate runtime overhead, delivering C++‑level performance—10 to 100 times faster than CPython—while targeting genomics, big‑data, and other compute‑intensive domains, though it sacrifices some dynamic Python features.
The article introduces JupyterLab’s new visual debugger, explains why debugging is needed in Jupyter, provides installation commands for the front‑end extension and xeus‑python kernel, describes the debugger’s UI components and capabilities, and compares it with a VS Code visual debugging tool.
This article explains three practical methods—using response.content, apparent_encoding, and custom encode/decode—to resolve Chinese character garbling in Python web crawlers, includes code snippets and screenshots, and offers concise guidance for developers facing this common issue.
This article presents a series of Python programming exercises covering topics such as Narcissistic numbers, four‑digit Armstrong numbers, string reversal, number guessing games, classic algorithms like bubble sort, binary search, recursion, palindrome detection, and many other fundamental coding challenges with complete code examples.
Microsoft announced a dedicated Faster CPython team, led by Mark Shannon and Guido van Rossum, to boost Python’s execution speed through a multi‑stage plan that has already delivered 10‑60% performance gains in Python 3.11 while emphasizing community collaboration and open‑source contributions.
This tutorial walks through creating a simple test device management platform using Python, Flask, and PostgreSQL, covering framework selection, database operations, API definition, and front‑end rendering with HTML and jQuery for a complete end‑to‑end web solution.
This article explains how Python can automate common operations tasks—remote command execution, log parsing, system monitoring with alerts, batch software deployment, and backup/recovery—providing code examples and practical tips to improve efficiency and reduce manual errors.
The article examines ChatGPT’s underlying software architecture, detailing its cloud deployment on AWS and Azure, database choices like PostgreSQL and Redis, front‑end technologies such as TypeScript and React, core AI frameworks including PyTorch and Triton, as well as its container orchestration, monitoring, and programming language ecosystem.
This article introduces beginners to fundamental computer concepts, explains what a program is, and provides a detailed guide on Python variables, their naming rules, common data types, type‑conversion functions, and basic arithmetic operations with illustrative code examples.
This article explains Python's Boolean type, how True and False are represented, demonstrates the bool() function, shows truthy and falsy values, and illustrates logical operators and arithmetic with booleans, while also covering the special None value and common pitfalls.
This article evaluates the five leading Python test automation frameworks—Robot Framework, Pytest, unittest (PyUnit), Behave, and Lettuce—detailing their installation requirements, key features, advantages, disadvantages, and suitability for functional, unit, or behavior‑driven testing to help developers choose the right tool.
This article presents ten practical Python automation scripts covering image and video processing, PDF conversion, API interaction, system notifications, grammar and spell correction, downloading, news fetching, and GUI creation, each accompanied by concise code examples for quick implementation.
The article introduces OpenAI's newly released ChatGPT and Whisper APIs, explains their reduced costs, outlines usage details and model versions, and provides Python code examples for integrating these powerful conversational and speech‑to‑text models into third‑party applications.
The gRPC 1.53.0 release introduces a series of core improvements, language‑specific enhancements for C++, C#, Python and Ruby, as well as bug fixes and new APIs, providing higher stability and performance for modern high‑performance RPC applications.
This article demonstrates how to install and configure the highway‑env reinforcement‑learning environment, set up a DQN agent in Python, and train it on various traffic scenarios, providing code examples and performance visualizations.
This article explains the most frequently used regular expression symbols in Python, covering ordinary metacharacters, the OR operator, escape sequences, anchors, quantifiers, grouping, and shorthand character classes, each illustrated with clear code examples and explanations.
This article introduces the lightweight Python search library Whoosh, outlines its key features, demonstrates how to define a schema, create an index from a CSV dataset, and perform full‑text queries with example code, making it suitable for small‑scale search projects.
This article shares practical Python tips for using PyYAML safely, keeping key order, customizing list indentation, outputting readable Unicode, and introduces alternative YAML libraries such as oyaml, StrictYAML, and ruamel.yaml with code examples.
This tutorial provides a comprehensive introduction to core Python concepts, covering numeric operations, string handling, built‑in functions, common data structures, class and object mechanics, as well as useful utilities such as iteration tools, file I/O and JSON serialization.
DBSCAN is a density‑based clustering algorithm that automatically discovers arbitrarily shaped clusters and isolates noise, with detailed explanations of core, border, and noise points, step‑by‑step examples, Python implementations using scikit‑learn, and guidance on key parameters such as eps and min_samples.
This article demonstrates how to compare the distribution of a variable across control and treatment groups using Python, covering data generation, visual techniques such as boxplots, histograms, KDE, CDF, QQ and ridgeline plots, and a suite of statistical tests including t‑test, SMD, Mann‑Whitney, permutation, chi‑square, Kolmogorov‑Smirnov and ANOVA for both two‑group and multi‑group scenarios.
This article explains Linear Discriminant Analysis (LDA) as a pattern‑recognition technique that projects data onto a low‑dimensional space to maximize class separation, details its mathematical formulation with between‑class and within‑class scatter matrices, and provides a complete Python implementation using scikit‑learn on the Iris dataset, including visualization of the results.
This article introduces Explainable AI (XAI), outlines its importance, describes a step-by-step workflow, and reviews ten Python libraries—including SHAP, LIME, ELI5, Shapash, Anchors, BreakDown, Interpret‑Text, AI Explainability 360, OmniXAI, and XAI—providing usage examples and code snippets.
Robusta is a Python‑based open‑source platform that layers on top of monitoring stacks like Prometheus to automatically detect, diagnose, and remediate Kubernetes alerts through built‑in automations, optional web UI, and Helm‑based installation for cloud‑native environments.
SQLAlchemy 2.0.7 has been released, addressing a critical caching bug in custom operator expressions, fixing typing issues with composite(), adding the PostgreSQL CITEXT type, and improving dialect compatibility, with all changes back‑ported to earlier stable releases.
