33 repository-uri
Conversion of column data types with validation and error handling.
Distinguishing note: Focuses on explicit type conversion rather than type inspection.
Explore 33 awesome GitHub repositories matching data & databases · Data Type Casting. Refine with filters or upvote what's useful.
Polars is a high-performance columnar data processing library designed for efficient analytical workflows. It functions as a structured data library that organizes information into typed columns, utilizing the Apache Arrow memory format to enable zero-copy data sharing and cache-friendly, vectorized operations. The engine is built to handle large-scale tabular datasets, providing both local and distributed analytical runtimes that scale from single-machine environments to multi-node clusters. The project distinguishes itself through a sophisticated lazy query engine that constructs abstract e
Converts the data type of a column to a new format with strict error handling.
Yup is a JavaScript schema validation library used to define data shapes and validate runtime values. It functions as an object schema validator and a data coercion engine, allowing developers to transform raw input values into desired types before performing validation checks. The library is distinguished by its support for dynamic schema validation, where rules can be adjusted at runtime based on sibling field values or external context. It also enables recursive data structuring for polymorphic fields and provides a system for extracting static TypeScript interfaces from runtime schema def
Transforms input data through a sequence of coercion rules before performing correctness assertions.
Joi is a JavaScript data validation library used to define schemas that validate, cast, and sanitize data objects. It functions as an object schema validator and parser, ensuring that input data matches specific types and formats before it is processed by an application. The library features a conditional validation engine capable of dynamic schema enforcement, where validation logic and dependencies change based on the values of other keys within an object. It also serves as a data casting and sanitization tool, transforming input values into target types and removing sensitive keys from the
Converts input values into required types, such as transforming numeric strings into numbers, before validation.
Joi is a JavaScript data validation library used to define schemas that ensure the structure and data types of objects remain consistent. It functions as a schema-based validator and object schema definition tool, preventing invalid information from entering an application by checking data against predefined constraints and rules. The library employs a chainable fluent interface and a constraint-based validation engine to build complex validation pipelines. It utilizes recursive tree traversal to validate nested data structures and a type-coercion pipeline to transform input values into the t
Transforms input values into target schema types via a coercion pipeline before applying validation rules.
Crystal is a statically typed, compiled programming language designed for high performance and memory safety. It leverages an LLVM-based compiler to translate source code into optimized machine-executable binaries, while its type-inference-based static analysis enforces strict safety rules during the build process. The language distinguishes itself through a fiber-based concurrent runtime that manages lightweight execution units for asynchronous input and output without blocking the main process. It also features a powerful compile-time macro system that allows for the inspection and transfor
Attempts to cast an object to a specific type and returns nil instead of raising an error if the conversion is not possible.
This project is a MySQL database driver and client for Node.js. It provides a JavaScript implementation of the MySQL protocol to facilitate connecting to, querying, and managing data within MySQL databases. The driver includes a connection pool manager to maintain a cache of reusable database connections, reducing the overhead of frequent network handshakes. It also supports row-by-row result streaming to process large datasets without loading entire result sets into memory. Core capabilities cover SQL query execution, the management of database transactions, and the coordination of multiple
Provides a configurable transformation layer to map MySQL binary data types to JavaScript objects.
This project is an educational resource designed for learning the Python programming language. It serves as a tutorial repository and programming guide, providing a collection of annotated scripts, code examples, and cheatsheets to help users master syntax and core fundamentals. The resource focuses on moving from basic language syntax to advanced implementation, with a particular emphasis on object-oriented programming, the use of the Python standard library, and scripting automation for business workflows. The content covers a broad range of programming capabilities, including control flow
Provides examples of changing values between different data types using constructor functions.
Nim is a statically typed, compiled systems programming language designed for high performance and cross-platform development. It translates high-level source code into C, C++, or JavaScript, allowing developers to produce efficient native binaries or web-compatible scripts from a single codebase. The language emphasizes a clean, indentation-based syntax that simplifies code hierarchy while maintaining the power of a full-featured systems language. What distinguishes Nim is its robust metaprogramming framework, which allows developers to inspect, modify, and generate code structures during th
Transforms values between compatible types with validation and error handling.
Presto is a distributed SQL query engine designed for high-performance analytical processing across heterogeneous data sources. It functions as a data federation platform and massively parallel processing engine, allowing users to execute interactive queries against diverse storage systems without requiring data migration. By mapping remote metadata and structures to a unified relational namespace, it enables seamless cross-platform analysis through a standard SQL interface. The engine distinguishes itself through a pluggable connector architecture and a shared-nothing distributed processing
Transforms values between different data types explicitly with support for null-handling on conversion failure.
gjson is a Go JSON parser designed for schema-less reading and value extraction. It allows for the retrieval of specific data from JSON documents using dot-notation paths without requiring the definition of predefined Go structs. The library provides tools for path-based querying, including the use of wildcards and index-based queries to locate data within objects and arrays. It also functions as a JSON lines processor, treating multi-line documents as arrays to iterate and query individual entries. Additional capabilities include converting JSON values into native Go types such as strings,
Converts raw JSON bytes into native Go types only when explicitly requested by the user.
This tool is a command-line processor designed for querying, updating, and transforming structured data files. It functions as a versatile engine for manipulating YAML, JSON, TOML, and XML documents, allowing users to perform complex operations directly from the terminal. By utilizing a path-based expression language, it enables precise navigation and modification of data structures within configuration files and infrastructure-as-code workflows. What distinguishes this tool is its ability to perform in-place document mutations while preserving original formatting, comments, and metadata. It
Forces specific data types for input values to override automatic detection.
Ajv is a JSON Schema validator and schema compilation engine used to verify that JavaScript objects conform to specific JSON Schema definitions. It functions as a data coercer and localization tool, allowing for the application of default values and the translation of validation error messages into different languages. The project converts declarative JSON Schema definitions into optimized JavaScript functions to increase validation speed. It supports the extension of validation logic through custom keywords and the generation of standalone validation code that executes without external depen
Casts data values into required types based on schema definitions during the validation process.
dbt-core is a command-line framework for transforming data within a warehouse using modular SQL and version control. It functions as a data transformation engine that enables users to define data structures and business logic through declarative configuration files, which the system then compiles into executable code. By managing complex data dependencies through a directed acyclic graph, it ensures that transformation tasks execute in the correct order while maintaining a manifest-driven state to track lineage and execution history. The project distinguishes itself through an adapter-based d
Specifies explicit data types for columns during the loading process to ensure data consistency.
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
Uses model casting to automatically convert database timestamps into date objects for consistent manipulation.
imbalanced-learn is a dataset balancing framework and Python machine learning extension designed to resample training data and reduce the impact of class imbalance. It provides a toolkit of algorithms for adjusting class distributions to improve model performance on minority class prediction. As a scikit-learn resampling library, it extends the ecosystem with specialized tools for balancing datasets through over-sampling and under-sampling techniques. This allows for the correction of skewed class proportions to reduce model bias toward the majority class. The library implements the scikit-l
Ensures input arrays are converted into consistent NumPy or Pandas formats before applying sampling algorithms.
RxKotlin is a reactive programming library and asynchronous stream processor that provides Kotlin language extensions for composing event-based data streams. It serves as a set of Kotlin bindings for RxJava, allowing developers to transform, filter, and flatten sequences of data emitted over time. The library focuses on integrating RxJava patterns into Kotlin projects by applying language-specific conventions and idioms. It utilizes extension functions to simplify reactive programming patterns, reduce boilerplate, and optimize workflows within the reactive ecosystem. The toolkit covers a bro
Uses language-level type constraints to filter and cast stream elements while maintaining compile-time type safety.
Lance is a versioned columnar data format and storage engine designed as a multimodal AI lakehouse. It serves as a vector database storage engine and a cloud object store dataset manager, organizing images, video, audio, and embeddings into a unified format optimized for machine learning workflows. The project distinguishes itself by combining a columnar layout for structured data with a specialized blob store for large multimodal tensors. It implements a hybrid search engine that integrates vector similarity search, full-text search, and SQL analytics on a single dataset, supported by a stor
Changes the data type of a specific column by rewriting only that column's data to disk.
Hazelcast is a distributed data platform that combines an in-memory data grid with a stream processing engine to support real-time analytics and event-driven applications. It functions as a partitioned, distributed key-value store that replicates data across cluster nodes to provide low-latency access and high availability. The platform also serves as a distributed SQL query engine, allowing users to execute standard SQL statements against both in-memory datasets and external data sources. What distinguishes Hazelcast is its use of a distributed consensus subsystem to maintain strongly consis
Converts values between different types using casting and formatting functions for strings, numbers, and timestamps.
Larastan is a static analysis extension and type inference engine for PHP designed to detect bugs and type errors in Laravel applications. It extends PHPStan to resolve framework-specific patterns and magic methods, providing a rule-based scanning engine to audit code quality without executing the application. The tool specializes in Eloquent analysis, verifying that model properties, casts, and relationships align with database schemas and migrations. It tracks types across Eloquent collections, custom builders, and model factories to ensure type safety during database operations and iterati
Checks that the return type and array shape of model casts match the expected configuration.
From Java To Kotlin - Your Cheat Sheet For Java To Kotlin
Shows Kotlin's safe-cast operator combining type checking and smart casting.