Bibliotheken für Type-Hint-Validierung in Python
For eine Bibliothek zur Datenvalidierung mittels Python Type Hints, the strongest matches are samuelcolvin/pydantic (Pydantic is the leading Python library for data validation), pydantic/pydantic (Pydantic is the definitive Python library for data validation) and fastapi/sqlmodel (SQLModel integrates database schema definitions with data validation through). Each is ranked by relevance to your query, popularity and recent activity.
Diese Bibliotheken nutzen Python-Typannotationen, um Datenintegrität sicherzustellen und komplexe Objektschemata zu validieren.
Bibliotheken für Type-Hint-Validierung in Python
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- samuelcolvin/pydantic
samuelcolvin/pydantic
28,043Auf GitHub ansehenPydantic is a data validation library and parsing framework for Python. It functions as a type-based schema validator that uses standard Python type annotations to ensure input data conforms to predefined structural schemas. The project provides capabilities for parsing raw data into typed objects through automatic type conversion and validation. This includes the serialization of data and the validation of data structures to enforce correctness. The framework covers several application areas, including the verification of API requests and the management of application configurations. It all
Pydantic is the leading Python library for data validation using type hints, offering runtime validation, serialization/deserialization, JSON Schema generation, and custom validators — exactly what you're looking for.
PythonType-Hint-Based Schema DefinitionsRuntime Type Guards - pydantic/pydantic
pydantic/pydantic
26,932Auf GitHub ansehenPydantic is a data validation and serialization library that enforces schema constraints and performs type conversion on complex data structures. It utilizes standard Python type annotations to define data models, allowing developers to establish structured schemas that automatically enforce business rules and constraints without the need for custom domain-specific languages. The library distinguishes itself by transforming high-level model definitions into optimized code during initialization to minimize runtime overhead. It supports recursive validation for nested data structures and employ
Pydantic is the definitive Python library for data validation using type hints, providing runtime validation, serialization, JSON Schema generation, and custom validators — it matches every required feature and is the canonical answer for this search.
PythonType-Hint-Based Schema Definitions - fastapi/sqlmodel
fastapi/sqlmodel
18,137Auf GitHub ansehenSQLModel is a type-safe object-relational mapping library for Python that integrates database schema definitions with data validation logic. By combining these two roles into a single class, it allows developers to manage relational data structures and enforce data integrity for web APIs simultaneously. The framework is built to support asynchronous database operations, enabling high-performance applications to execute queries and transactions without blocking the main execution thread. The library distinguishes itself by leveraging Python type hints to provide IDE autocompletion and compile-
SQLModel integrates database schema definitions with data validation through Pydantic, using Python type hints for schema definition, runtime validation, serialization, and JSON Schema generation, so it meets the core capability of a type-hint-based validation library even though it is primarily an ORM.
PythonData Schema DefinitionsDatabase ORMsObject-Relational Mapping
