Word-Formatter-Pro is a cross-platform desktop application and CLI tool for automatically formatting Word documents (.docx, .doc, .wps, .txt, .md) into a consistent Chinese government/official document style. It is built with Python, uses Tkinter for the GUI, python-docx for document manipulation, and integrates with WPS/Word COM on Windows or LibreOffice on macOS/Linux for legacy format conversion. The application features intelligent detection of headings (four levels), title/subtitle, figure/table captions, attachments, and can perform conservative symbol normalization, table auto-formatting, and blank line compression for text sources. The architecture is well-separated: a core formatting engine independent of GUI, a CLI interface, a configuration module, and a bundled Agent Skill. The code is actively maintained, with regular version releases and built-in unit tests covering critical logic.
The system-monitoring-center is a Linux desktop application for real-time system resource monitoring and management. It provides a tabbed interface displaying CPU, memory, disk, network, GPU, sensors, processes, services, users, and system information. The application allows users to monitor performance metrics, manage processes and services, and view detailed hardware information through a modular architecture. Built with Python and Tkinter using the Sun Valley theme, the application follows a modular structure where each tab (CPU, Memory, etc.) implements a consistent interface (tab_gui, initial_func, loop_func). Core system data is gathered by the Libsysmon module via /proc, /sys, and system commands (dmidecode, lspci, etc.). The GUI features interactive charts, process/service management capabilities, and supports internationalization across 15+ languages. Configuration is managed through a version-aware system in Config.py. Key reusable components include Common.py for generic GUI utilities (sortable treeviews, search entries, charting canvases) and Config.py for persistent settings management. The application demonstrates good engineering practices with clear separation of concerns, active maintenance, and low technical drift despite Linux-specific dependencies.
tksheet is a pure Python Tkinter widget library that provides a full-featured, interactive spreadsheet-like table and treeview component for embedding in desktop applications. It renders only visible cells using Tkinter canvases, supporting cell editing, dropdowns, checkboxes, progress bars, notes/tooltips, find/replace, sorting, undo/redo, clipboard operations, and extensive theming. The architecture is modular, with separate classes for the main table, column headers, row index, text editor, and dropdown windows, all orchestrated by a central `Sheet` class that exposes a rich API for data manipulation and event handling. The library demonstrates strong software craftsmanship through its use of reusable patterns such as `Span` objects for addressing cell ranges with method chaining, `DotDict` for attribute-accessible configuration dictionaries, and a consistent `EventDataDict` structure for undo/redo and event propagation. It also includes self-contained utility modules for data formatting (`Formatter` class) and sorting (natural, version, and fast sort keys) that could be extracted and reused independently. Development of tksheet has officially ceased except for bug fixes and behavioral issues, as stated in the README. The codebase is mature and stable, with extensive documentation and a changelog spanning multiple major versions. While the library is tightly coupled to Tkinter and has some code duplication across similar components (e.g., column headers and row index), it remains a high-quality, production-ready widget for any Python GUI application requiring tabular data interaction.
WxCleaner is a lightweight desktop application for detecting and removing duplicate files, primarily targeting WeChat file folders. It presents a ttkbootstrap-based GUI where users select a directory, scan for duplicates using a three-stage hashing strategy (file size, partial SHA-256, full SHA-256), and then selectively delete files by moving them to the system recycle bin via send2trash. The architecture cleanly separates the scanning logic (scanner.py) from the GUI (wx_gui.py), with main.py as the entry point. The application is functional, well-structured for its scope, and demonstrates practical file system operations with progress feedback. It is not a data research project; it is a pure utility application.
This repository is a comprehensive collection of over 1000 Python GUI example applications and tutorials, spanning multiple frameworks: PyQt5, PyQt6, PySide2, PySide6, Tkinter, Kivy, DearPyGui, Flet, NiceGUI, and Streamlit. It serves as an educational resource for developers learning desktop GUI programming, with step-by-step tutorials and full demo applications like calculators, media players, web browsers, games (Minesweeper, Solitaire), paint programs, and data-driven apps (weather, currency, crypto). The codebase is organized by framework, with each framework containing tutorials, demos, and reusable custom widgets. While the examples are functional and well-documented, the repository suffers from massive duplication across Qt bindings (identical logic replicated four times with minor API adaptations), some deprecated API usage (e.g., QWebEnginePage.NavigationType in Qt6, fixer.io API endpoints), and occasional cross-binding import errors. The most valuable parts are the self-contained custom widgets in the widgets/ directories, which demonstrate clean signal-based design and can be extracted into other Qt projects with minimal modification.
InfoSpider is a Windows-only desktop application that aggregates personal data from over 20 online services (e.g., GitHub, JD, Taobao, Alipay, Zhihu, Bilibili) using Selenium-based browser automation and a companion Chrome extension. The user launches a wxPython GUI, selects a data source, logs in via an automated Chrome window, and the tool scrapes orders, bills, contacts, posts, and other personal information, saving it as JSON files. Some spiders also generate HTML charts (word clouds, time-series plots) from the scraped data. The repository includes a separate, experimental PyTorch LSTM model for stock price prediction in `tests/DeepAnalysis/`, which is not integrated into the main tool. The codebase is a monolithic collection of spider scripts with a simple GUI wrapper, relying on outdated library versions (Selenium 3.141.0, pandas 1.0.1) and brittle automation patterns (hardcoded selectors, sleep-based waits). It has not seen active development since 2020 and carries significant technical drift and maintenance risks.