aws-glue-schema-registry

What it is and what it does

This package wraps AWS Glue Schema Registry to let Python applications serialize and deserialize messages against centrally managed schemas. It supports Avro and JSON Schema formats, local schema caching to reduce API calls, automatic schema registration, and schema evolution validation. The library is a partial port of the Java reference implementation, covering the core serialization/deserialization workflow but omitting Flink support.

You create a SchemaRegistryClient by passing a boto3 Glue client and registry name, then use it to serialize data with a schema or deserialize messages that carry schema metadata. Optional adapters for kafka-python are available to integrate directly into Kafka producers and consumers. The package depends on boto3 for AWS API access, fastavro and fastjsonschema for schema validation, and orjson for JSON handling.

Use it for:

• Publish Avro-encoded messages to Kafka topics with schema validation and automatic schema registration in AWS Glue.
• Consume messages that carry embedded schema references and deserialize them with schema evolution checks.
• Maintain a centralized schema registry in AWS Glue and enforce schema compatibility across multiple Python services.
• Cache schemas locally to reduce latency and API calls when serializing message streams.
• Migrate existing schemas from a third-party registry into AWS Glue and use this library to read them.

Worth the install?

AI-flagged interpretation of the facts on this page — verify before relying

Serializes and deserializes messages using AWS Glue Schema Registry with support for Avro and JSON Schema formats, including local caching and schema evolution checks.

Yes, if you are already using AWS Glue Schema Registry and need Python integration. The library is stable, has no known vulnerabilities, and low install friction. However, maintenance is dormant (last release 2023-10-17), so do not expect active support or new features; use it only if your schema and messaging patterns are unlikely to change and you can maintain the integration yourself if needed.

Install

aws-glue-schema-registry on PyPI

pip install aws-glue-schema-registry

uv add aws-glue-schema-registry

poetry add aws-glue-schema-registry

Installing aws-glue-schema-registry

Before you install

Low friction install with a pure-Python wheel and five straightforward runtime dependencies. Maintenance is dormant—last release was 2023-10-17 and last commit 2024-11-09—so expect no active bug fixes or feature development, though the codebase is stable enough for production use if your schema needs are static.

License in practice

Apache Software License (permissive) means you can use this freely in commercial and open-source projects with minimal restrictions; just include a copy of the license and note any modifications you make.

Quickstart

import boto3
from aws_glue_schema_registry import SchemaRegistryClient
from aws_glue_schema_registry.avro import AvroSchema

session = boto3.Session(region_name='us-west-2')
glue_client = session.client('glue')
client = SchemaRegistryClient(glue_client, registry_name='my-registry')

with open('schema.avsc', 'r') as f:
    schema = AvroSchema(f.read())

Requires AWS credentials configured via boto3 (environment variables, profile, or explicit session parameters) and an existing AWS Glue Schema Registry.

Verify before relying

• Whether the library's feature parity with the Java implementation is sufficient for your specific use case (Flink support is explicitly missing).
• Performance characteristics and throughput limits when used at scale with large message volumes.
• Specific usage patterns with kafka-python adapter and whether the optional kafka-python extra is required for your workflow.

Package facts

Evidence: aws_glue_schema_registry-1.1.3-py3-none-any.whl

Keywords: aws, glue, schema, registry, avro

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