3 个仓库
Awesome GitHub RepositoriesData Accessors
Logic for transforming, validating, or computing model attributes during read and write operations within data layers.
Distinguishing note: Focuses specifically on attribute-level transformation and access logic rather than general database connectivity or schema definition.
Explore 3 awesome GitHub repositories matching data & databases · Data Accessors. Refine with filters or upvote what's useful.
Awesome Data Accessors GitHub Repositories
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- sequelize/sequelize
sequelize/sequelize
30,349在 GitHub 上查看Sequelize is an object-relational mapping library that provides a unified interface for managing relational data through code. By implementing the Active Record pattern, it maps database tables to application objects, allowing developers to perform standard create, read, update, and delete operations using high-level method calls. The library abstracts complex database interactions by translating these calls into optimized, engine-specific SQL statements, ensuring consistent behavior across different database systems. The project distinguishes itself through a comprehensive suite of tools for
Sequelize allows transforming or validating model attributes using custom getter and setter logic to ensure data integrity during read and write operations.
TypeScriptdb2-ibm-ifeature-richjavascript - dask/dask
dask/dask
13,746在 GitHub 上查看Dask 是一个并行计算框架和分布式任务调度器，旨在将 Python 数据科学工作流从单机扩展到大型集群。它作为一个集群资源管理器，通过将任务及其依赖项表示为有向无环图来编排计算逻辑。这种架构允许系统在管理复杂执行要求的同时，自动将工作负载分配到可用硬件上。 该项目通过一个延迟评估引擎脱颖而出，该引擎将数据操作推迟到明确请求时才执行，从而实现全局图优化和高效的资源分配。它结合了内存感知数据溢出功能，以防止在处理超过可用内存的数据集时系统崩溃，并利用任务图融合将操作序列组合成单个执行步骤，从而最大限度地减少调度开销和节点间通信。 该平台为大规模数据分析提供了全面的功能面，包括对分布式机器学习、高性能计算集成和并行数据处理的支持。它提供了用于集群生命周期管理、性能分析和任务执行实时监控的广泛工具。用户可以在各种基础设施上部署这些环境，包括本地硬件、云提供商、容器化系统和高性能计算集群。
Adds domain-specific methods to data structures by attaching custom accessors to series, dataframes, or index objects.
Pythondasknumpypandas - alexeymezenin/laravel-best-practices
alexeymezenin/laravel-best-practices
12,299在 GitHub 上查看This project is a comprehensive guide to architectural standards and coding patterns for developing maintainable applications within the Laravel framework. It focuses on clean code standards, applying the single responsibility and DRY principles to ensure codebase predictability and consistency. The guide emphasizes decoupling components by moving business logic into service layers and shifting input validation into dedicated request classes to keep controllers lean. It advocates for the use of a service container and dependency injection to reduce class coupling and improve testability. The
Employs model accessors and mutators to transform and compute attributes during read and write operations.
