Awesome GitHub RepositoriesMulti-Format Data Persistence

This project is a comprehensive educational guide and framework for building web scrapers using Python. It provides a course-based approach to data extraction, combining a Python crawler framework with tutorials on web reverse engineering and network traffic analysis. The project distinguishes itself by covering advanced extraction challenges, including the decryption of obfuscated JavaScript and the bypass of anti-scraping measures. It specifically addresses mobile application scraping through the simulation of user interactions and the interception of network traffic. The capability surfac

weiboSpider is a Python web scraper and social media crawler designed to extract user profiles, posts, and engagement metrics from Sina Weibo. It functions as an automated data pipeline for academic research and trend analysis, collecting long-form text and multimedia content. The tool distinguishes itself through the use of browser session cookies to authenticate requests and access protected profiles. It implements randomized request pacing and global pauses to manage traffic and avoid platform rate limits, while supporting incremental crawling to capture only new content based on timestamp

This project is an educational resource and a collection of instructional materials for performing data manipulation and statistical analysis using Python. It provides a comprehensive set of guides and code examples for using the Pandas, NumPy, and Matplotlib libraries to analyze structured data. The resource includes a dedicated guide for reshaping, cleaning, and aggregating tabular data and time series via Pandas, alongside a reference for high-performance vectorized operations and linear algebra using NumPy. It also features tutorials for creating publication-quality charts, distribution p

TiddlyWiki5 is a modular wiki engine and non-linear knowledge base that organizes information into small, linked chunks. It can function as a single-file personal wiki where all content and application logic are stored within one HTML file for local-first use, or as a self-hosted wiki server that serves content over HTTP. The project is distinguished by a data-driven architecture where plugins and extensions are treated as stored data entries. It features a filter-based query engine for manipulating structured data and a transclusion system that allows the live content of one entry to be embe

big-AGI is a self-hosted AI frontend and multi-model client that provides a unified workspace for interacting with various large language models. It functions as an orchestration dashboard, allowing users to connect to cloud-based AI providers, aggregator services, and locally hosted model servers. The project is distinguished by its ability to execute prompts across multiple models simultaneously for side-by-side comparison and response synthesis. It enables the merging of outputs from different models to reduce hallucinations and improve accuracy, while using persona-based configuration map

libigl 是一个 C++ 几何处理库，用于分析和操作 3D 三角形和四面体网格。它充当数值线性代数套件和网格操作框架，集成了几何变形引擎以实现刚性和多调和变换。 该项目以其仅头文件的库设计以及对专门变形技术的实现而著称，包括尽可能刚性 (rigid-as-possible) 和多调和形状变形。它还提供了一个可视化工具，用于通过交互式场景控制和网格拾取来渲染表面和标量场。 该库涵盖了广泛的功能，包括用于曲率和测地距离的几何分析、通过等值面提取和三角剖分进行的网格生成，以及通过各向异性变形进行的网格重构。它还支持布尔网格操作、表面参数化以及用于求解拉普拉斯方程和二次规划的数值优化。 该工具包包括用于导入和导出各种 3D 几何格式的实用程序，并支持与 Matlab 的互操作性，以便执行脚本和共享矩阵。

ArrayFire 是一个硬件无关的计算框架和 JIT 编译张量引擎，专为高性能数值计算而设计。它作为一个 GPU 数值计算库和并行信号处理工具包，抽象了硬件后端，允许同一代码库在各种 GPU 架构和 CPU 上执行。 该项目以其使用表达式编译来融合操作并最小化内存开销的 JIT 引擎而脱颖而出。它采用延迟执行图来优化计算链，并提供互操作性原语以与 CUDA 和 OpenCL 等外部计算平台共享数据和执行上下文。 该库涵盖了广泛的功能，包括并行线性代数、数字信号处理和加速计算机视觉。它提供了用于机器学习实现、金融建模模拟以及求解物理系统模拟偏微分方程的工具。其张量管理系统处理多维数组分配、切片和主机-设备数据传输。

这是一个新浪微博网页爬虫和社交媒体数据管道，旨在提取用户资料、帖子、评论和多媒体资源。它作为一个容器化的数据爬虫，自动化收集社交媒体内容和互动指标，并将其存储在本地。 该系统包含一个处理层，利用大语言模型分析抓取的文本，生成摘要和情感分析。它通过一个部署就绪的容器模型脱颖而出，该模型具有用于管理提取任务和监控作业进度的 HTTP 界面。 该爬虫涵盖了广泛的功能，包括通过定时增量更新进行社交媒体监控、将多媒体资源归档到本地磁盘，以及向平面文件或数据库进行多格式数据导出。它还能捕获详细的社交互动，如一级评论和转发。

Joblib 是一套用于并行化计算工作负载和优化大型数值数据集及函数结果存储的实用工具。它作为并行计算库和多进程包装器，将函数执行分配到多个 CPU 核心上，以加速独立任务和计算循环。 该项目提供了一个磁盘缓存框架，将昂贵的函数输出持久化到文件系统，仅在输入参数发生变化时才重新评估。它进一步专注于大型数值数组的序列化，利用高效的压缩和内存映射来优化海量数据集的存储和检索。 该工具包包括并行函数映射功能，并使用可插拔的执行后端来控制任务如何在可用硬件上分配。其存储层涵盖了复杂对象持久化和序列化数据的透明压缩。

CrawlerTutorial 是一个全面的 Python 网络爬虫教程和框架，旨在从静态和动态网站中提取数据。它作为一个网络数据提取管道和 HTTP 请求编排器，涵盖了从初始获取到最终数据存储的爬虫应用程序全生命周期。 该项目提供了关于反机器人绕过技术和 Web API 逆向工程的专业指导。它包括通过身份掩码和代理轮换规避浏览器检测的方法，以及通过分析网络流量和请求签名识别隐藏 API 端点的技术。 该框架包含广泛的功能，包括针对 JavaScript 重度页面的浏览器自动化、通过 QR 码或短信的自动用户身份验证以及会话持久性管理。它还具有用于清理原始文本、删除重复记录并将收集到的信息持久化到平面文件或关系数据库中的数据预处理工具。

xtensor is a C++ multidimensional array library for numerical computing that provides N-dimensional containers with an interface mirroring the NumPy API. It utilizes a lazy evaluation expression engine to defer numerical computations until assignment, which minimizes memory allocations and intermediate copies. The library features a foreign memory array adaptor that allows it to wrap external buffers, such as NumPy arrays, to perform numerical operations in-place without duplicating data. It further optimizes performance through lazy broadcasting and a system that manages the lifetime of temp

This project is a NestJS testing boilerplate and reference implementation. It provides a structured monorepo workspace designed to demonstrate various architectural and testing patterns for NestJS applications. The project features a dockerized test environment and an integration testing framework. It includes a dedicated GraphQL API test suite to validate graph-based endpoints and schemas for queries and mutations. The suite covers a layered testing hierarchy consisting of unit, integration, and end-to-end tests. These capabilities extend across the application and data layers, including da