python-schema-registry-client 1.0.0

Python Rest Client to interact against Schema Registry Confluent Server to manage Avro Schemas

# Python Rest Client Schema Registry

[](https://travis-ci.org/marcosschroh/python-schema-registry-client) [](https://github.com/marcosschroh/python-schema-registry-client/blob/master/LICENSE) [](https://codecov.io/gh/marcosschroh/python-schema-registry-client) [](https://img.shields.io/badge/python-3.6%20%7C%203.7-blue.svg)

Python Rest Client to interact against [schema-registry](https://docs.confluent.io/current/schema-registry/index.html) confluent server to manage [Avro Schemas](https://docs.oracle.com/database/nosql-12.1.3.1/GettingStartedGuide/avroschemas.html) resources.

## Requirements

python 3.6+, fastavro>=0.22.3, requests>=2.22.0

## Installation

` pip install python-schema-registry-client ` If you want the Faust functionality:

` pip install python-schema-registry-client[faust] `

## Client API, Serializer, Faust Integration and Schema Server description

Documentation: [https://marcosschroh.github.io/python-schema-registry-client.io](https://marcosschroh.github.io/python-schema-registry-client)

## When use this library?

Usually, we have a situacion like this:


So, our producers/consumers have to serialize/deserialize messages every time that they send/receive from Kafka topics. In this picture, we can imagine a Faust application receiving messages (encoded with an Avro schema) and we want to deserialize them, so we can ask the schema server to do that for us. In this scenario, the MessageSerializer is perfect.

Also, could be a use case that we would like to have an Application only to administrate Avro Schemas (register, update compatibilities, delete old schemas, etc.), so the SchemaRegistryClient is perfect.

## Run Tests

The tests are run against the Schema Server using docker compose, so you will need Docker and Docker Compose installed.

`bash ./scripts/test.sh `