A Python tool for validating data using JSON Schema and converting schemas into data-interchange formats like Avro.
Aptos is a Python tool that validates data using JSON Schema and converts JSON Schema documents into different data-interchange formats like Apache Avro. It solves the problem of ensuring data integrity and enabling schema interoperability across systems by providing both validation and conversion capabilities.
Data scientists, data engineers, and developers who need to validate JSON data against schemas or convert JSON Schema to other formats for data pipelines and integrations.
Developers choose Aptos for its dual functionality of validation and schema conversion in a single tool, its simple CLI and API, and its focus on reducing data-cleaning overhead in data workflows.
Aptos is a Python library and CLI tool that validates client-submitted data against JSON Schema specifications and converts JSON Schema documents into various data-interchange formats. It helps ensure data integrity and facilitates schema interoperability across different systems.
required, minimum, and type.Aptos aims to reduce data-cleaning overhead for data scientists and engineers by providing robust validation and schema conversion tools, promoting cleaner data pipelines and interoperability.
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Combines JSON Schema validation with Avro schema conversion in a single tool, reducing the need for multiple libraries, as shown in the CLI and API examples for both functions.
Provides straightforward command-line and Python interfaces with clear syntax, exemplified by simple commands like 'aptos validate' and code snippets using SchemaParser and visitors.
The README includes detailed usage instructions, visual aids for CLI output, and specific examples for validation and conversion, making it easy to onboard new users.
Aims to reduce data-cleaning overhead for data scientists by enforcing schema compliance, aligning with the project's philosophy of promoting cleaner data pipelines.
Currently only supports Apache Avro for schema conversion; other formats like Protocol Buffers are planned but not available, limiting interoperability with diverse systems.
Tied to Python ecosystems, which may not suit projects in other languages or those requiring cross-platform, high-performance validation due to Python's inherent speed constraints.
Maintained by a single individual, as noted in the README, which could affect the pace of feature development, bug fixes, and long-term community support.