Microsoft Azure Azure Schema Registry Client Library for Python
Project description
Azure Schema Registry client library for Python
Azure Schema Registry is a schema repository service hosted by Azure Event Hubs, providing schema storage, versioning, and management. The registry is leveraged by encoders to reduce payload size while describing payload structure with schema identifiers rather than full schemas. This package provides:
-
A client library to register and retrieve schemas and their respective properties.
-
An JSON schema-based encoder capable of encoding and decoding payloads containing Schema Registry schema identifiers, corresponding to JSON schemas used for validation, and encoded content.
Source code | Package (PyPi) | Package (Conda) | API reference documentation | Samples | Changelog
Disclaimer
Azure SDK Python packages support for Python 2.7 has ended on 01 January 2022. For more information and questions, please refer to https://github.com/Azure/azure-sdk-for-python/issues/20691
Getting started
Install the package
Install the Azure Schema Registry client library for Python with pip:
pip install azure-schemaregistry
To use the built-in jsonschema validators with the JSON Schema Encoder, install jsonencoder extras:
pip install azure-schemaregistry[jsonencoder]
Prerequisites:
To use this package, you must have:
- Azure subscription - Create a free account
- Azure Schema Registry - Here is the quickstart guide to create a Schema Registry group using the Azure portal.
- Python 3.8 or later - Install Python
Authenticate the client
Interaction with Schema Registry starts with an instance of SchemaRegistryClient class. The client constructor takes an Azure Event Hubs fully qualified namespace and an Azure Active Directory credential:
-
The fully qualified namespace of the Schema Registry instance should follow the format:
<yournamespace>.servicebus.windows.net. -
An AAD credential that implements the TokenCredential protocol should be passed to the constructor. There are implementations of the
TokenCredentialprotocol available in the azure-identity package. To use the credential types provided byazure-identity, please install the Azure Identity client library for Python with pip:
pip install azure-identity
- Additionally, to use the async API, you must first install an async transport, such as aiohttp:
pip install aiohttp
Create client using the azure-identity library:
from azure.schemaregistry import SchemaRegistryClient
from azure.identity import DefaultAzureCredential
credential = DefaultAzureCredential()
# Namespace should be similar to: '<your-eventhub-namespace>.servicebus.windows.net/'
fully_qualified_namespace = os.environ['SCHEMAREGISTRY_FULLY_QUALIFIED_NAMESPACE']
schema_registry_client = SchemaRegistryClient(fully_qualified_namespace, credential)
Create JsonSchemaEncoder using the azure-schemaregistry library:
import os
from azure.schemaregistry import SchemaRegistryClient
from azure.schemaregistry.encoder.jsonencoder import JsonSchemaEncoder
from azure.identity import DefaultAzureCredential
credential = DefaultAzureCredential()
# Namespace should be similar to: '<your-eventhub-namespace>.servicebus.windows.net'
fully_qualified_namespace = os.environ['SCHEMAREGISTRY_FULLY_QUALIFIED_NAMESPACE']
group_name = os.environ['SCHEMAREGISTRY_GROUP']
schema_registry_client = SchemaRegistryClient(fully_qualified_namespace, credential)
encoder = JsonSchemaEncoder(client=schema_registry_client, group_name=group_name)
Key concepts
Client concepts
-
Schema: Schema is the organization or structure for data. More detailed information can be found here.
-
Schema Group: A logical group of similar schemas based on business criteria, which can hold multiple versions of a schema. More detailed information can be found here.
-
SchemaRegistryClient:
SchemaRegistryClientprovides the API for storing and retrieving schemas in schema registry.
Encoder concepts
-
JsonSchemaEncoder: Provides API to encode content to and decode content from Binary Encoding, validate content against a JSON Schema, and cache schemas/schema IDs retrived from the registry using the
SchemaRegistryClientlocally. -
OutboundMessageContent: Protocol defined under
azure.schemaregistrythat allows forJsonSchemaEncoder.encodeinteroperability with certain Azure Messaging SDK message types. Support has been added to:azure.eventhub.EventDataforazure-eventhub>=5.9.0
-
InboundMessageContent: Protocol defined under
azure.schemaregistrythat allows forJsonSchemaEncoder.decodeinteroperability with certain Azure Messaging SDK message types. Support has been added to:azure.eventhub.EventDataforazure-eventhub>=5.9.0
OutboundMessageContent/InboundMessageContent
If a message type that follows the OutboundMessageContent protocol is provided to the JsonSchemaEncoder, it will set the corresponding content and content type properties. If a message type object that follows the InboundMessageContent protocol is provided to the encoder, it will get the corresponding content and content type properties. These are defined as:
-
content: Binary-encoded, JSON schema-validated payload (in general, format-specific payload) -
content type: a string of the formatapplication/json;serialization=Json+<schema ID>, where:application/json;serialization=Jsonis the format indicator<schema ID>is the hexadecimal representation of GUID, same format and byte order as the string from the Schema Registry service.
If EventData is passed in as the message type, the following properties will be set on the EventData object:
-
The
bodyproperty will be set to the encoded content value. -
The
content_typeproperty will be set to the content type value.
If message type is not provided, and by default, the encoder will create the following dict:
{"content": <encoded payload>, "content_type": 'application/json;serialization=Json+<schema ID>'}
Examples
The following sections provide several code snippets covering some of the most common Schema Registry and Json Schema Encoder tasks, including:
Register a schema
Use SchemaRegistryClient.register_schema method to register a schema.
import os
from azure.identity import DefaultAzureCredential
from azure.schemaregistry import SchemaRegistryClient
token_credential = DefaultAzureCredential()
fully_qualified_namespace = os.environ['SCHEMAREGISTRY_AVRO_FULLY_QUALIFIED_NAMESPACE']
group_name = os.environ['SCHEMA_REGISTRY_GROUP']
name = "your-schema-name"
format = "Avro"
definition = """
{"namespace": "example.avro",
"type": "record",
"name": "User",
"fields": [
{"name": "name", "type": "string"},
{"name": "favorite_number", "type": ["int", "null"]},
{"name": "favorite_color", "type": ["string", "null"]}
]
}
"""
schema_registry_client = SchemaRegistryClient(fully_qualified_namespace=fully_qualified_namespace, credential=token_credential)
with schema_registry_client:
schema_properties = schema_registry_client.register_schema(group_name, name, definition, format)
id = schema_properties.id
Get the schema by id
Get the schema definition and its properties by schema id.
import os
from azure.identity import DefaultAzureCredential
from azure.schemaregistry import SchemaRegistryClient
token_credential = DefaultAzureCredential()
fully_qualified_namespace = os.environ['SCHEMAREGISTRY_AVRO_FULLY_QUALIFIED_NAMESPACE']
schema_id = 'your-schema-id'
schema_registry_client = SchemaRegistryClient(fully_qualified_namespace=fully_qualified_namespace, credential=token_credential)
with schema_registry_client:
schema = schema_registry_client.get_schema(schema_id)
definition = schema.definition
properties = schema.properties
Get the schema by version
Get the schema definition and its properties by schema version.
import os
from azure.identity import DefaultAzureCredential
from azure.schemaregistry import SchemaRegistryClient
token_credential = DefaultAzureCredential()
fully_qualified_namespace = os.environ['SCHEMAREGISTRY_AVRO_FULLY_QUALIFIED_NAMESPACE']
group_name = os.environ["SCHEMAREGISTRY_GROUP"]
name = "your-schema-name"
version = int("<your schema version>")
schema_registry_client = SchemaRegistryClient(fully_qualified_namespace=fully_qualified_namespace, credential=token_credential)
with schema_registry_client:
schema = schema_registry_client.get_schema(group_name=group_name, name=name, version=version)
definition = schema.definition
properties = schema.properties
Get the id of a schema
Get the schema id of a schema by schema definition and its properties.
import os
from azure.identity import DefaultAzureCredential
from azure.schemaregistry import SchemaRegistryClient
token_credential = DefaultAzureCredential()
fully_qualified_namespace = os.environ['SCHEMAREGISTRY_AVRO_FULLY_QUALIFIED_NAMESPACE']
group_name = os.environ['SCHEMA_REGISTRY_GROUP']
name = "your-schema-name"
format = "Avro"
definition = """
{"namespace": "example.avro",
"type": "record",
"name": "User",
"fields": [
{"name": "name", "type": "string"},
{"name": "favorite_number", "type": ["int", "null"]},
{"name": "favorite_color", "type": ["string", "null"]}
]
}
"""
schema_registry_client = SchemaRegistryClient(fully_qualified_namespace=fully_qualified_namespace, credential=token_credential)
with schema_registry_client:
schema_properties = schema_registry_client.register_schema(group_name, name, definition, format)
id = schema_properties.id
Encode
Use the SchemaRegistryClient to pre-register the schema. Encode and validate the content with the JsonSchemaEncoder.
The encode method automatically retrieves the schema from the Schema Registry Service, validates against the content, and caches the schema locally.
import os
import json
from azure.schemaregistry import SchemaRegistryClient, SchemaFormat
from azure.schemaregistry.encoder.jsonencoder import JsonSchemaEncoder
from azure.identity import DefaultAzureCredential
from azure.eventhub import EventData
token_credential = DefaultAzureCredential()
fully_qualified_namespace = os.environ['SCHEMAREGISTRY_JSON_FULLY_QUALIFIED_NAMESPACE']
group_name = os.environ['SCHEMAREGISTRY_GROUP']
format = SchemaFormat.JSON
DRAFT2020_12_SCHEMA_IDENTIFIER = "https://json-schema.org/draft/2020-12/schema"
schema = {
"$id": "https://example.com/person.schema.json",
"$schema": "https://json-schema.org/draft/2020-12/schema",
"title": "Person",
"type": "object",
"properties": {
"name": {
"type": "string",
"description": "Person's name."
},
"favorite_color": {
"type": "string",
"description": "Favorite color."
},
"favorite_number": {
"description": "Favorite number.",
"type": "integer",
}
}
}
name = schema["title"]
definition = json.dumps(schema)
schema_registry_client = SchemaRegistryClient(fully_qualified_namespace, token_credential)
schema_properties = schema_registry_client.register_schema(group_name, name, definition, format)
schema_id = schema_properties.id
# group_name only needed if passing `schema` to encode
encoder = JsonSchemaEncoder(client=schema_registry_client, validate=DRAFT2020_12_SCHEMA_IDENTIFIER, group_name=group_name)
with encoder:
dict_content = {"name": "Ben", "favorite_number": 7, "favorite_color": "red"}
event_data = encoder.encode(dict_content, schema_id=schema_id, message_type=EventData)
# OR
message_content_dict = encoder.encode(dict_content, schema_id=schema_id)
event_data = EventData.from_message_content(message_content_dict["content"], message_content_dict["content_type"])
# OR
dict_content = {"name": "Ben", "favorite_number": 7, "favorite_color": "red"}
message_content = encoder.encode(dict_content, schema=definition) # group_name required in constructor when `schema` is passed
Decode
Decode the content with the JsonSchemaEncoder.
The decode method automatically retrieves the schema from the Schema Registry Service, validates against the content, and caches the schema locally.
import os
from azure.schemaregistry import SchemaRegistryClient
from azure.schemaregistry.encoder.jsonencoder import JsonSchemaEncoder
from azure.identity import DefaultAzureCredential
token_credential = DefaultAzureCredential()
fully_qualified_namespace = os.environ['SCHEMAREGISTRY_FULLY_QUALIFIED_NAMESPACE']
group_name = os.environ["SCHEMAREGISTRY_GROUP"]
DRAFT2020_12_SCHEMA_IDENTIFIER = "https://json-schema.org/draft/2020-12/schema"
schema_registry_client = SchemaRegistryClient(fully_qualified_namespace, token_credential)
encoder = JsonSchemaEncoder(client=schema_registry_client, validate=DRAFT2020_12_SCHEMA_IDENTIFIER)
with encoder:
# event_data is an EventData object with encoded body
decoded_content = encoder.decode(event_data)
# OR
# content_dict is a TypedDict with encoded content and JSON content type
decoded_content = encoder.decode(content_dict)
Event Hubs Send Integration
Integration with Event Hubs to send an EventData object with body set to encoded content and corresponding content_type.
import os
from azure.eventhub import EventHubProducerClient, EventData
from azure.schemaregistry import SchemaRegistryClient
from azure.schemaregistry.encoder.jsonencoder import JsonSchemaEncoder
from azure.identity import DefaultAzureCredential
token_credential = DefaultAzureCredential()
fully_qualified_namespace = os.environ['SCHEMAREGISTRY_JSON_FULLY_QUALIFIED_NAMESPACE']
group_name = os.environ['SCHEMAREGISTRY_GROUP']
eventhub_connection_str = os.environ['EVENT_HUB_CONN_STR']
eventhub_name = os.environ['EVENT_HUB_NAME']
schema_id = os.environ['PERSON_JSON_SCHEMA_ID']
DRAFT2020_12_SCHEMA_IDENTIFIER = "https://json-schema.org/draft/2020-12/schema"
schema_registry_client = SchemaRegistryClient(fully_qualified_namespace, token_credential)
json_schema_encoder = JsonSchemaEncoder(client=schema_registry_client, validate=DRAFT2020_12_SCHEMA_IDENTIFIER)
eventhub_producer = EventHubProducerClient.from_connection_string(
conn_str=eventhub_connection_str,
eventhub_name=eventhub_name
)
with eventhub_producer, json_schema_encoder:
event_data_batch = eventhub_producer.create_batch()
dict_content = {"name": "Bob", "favorite_number": 7, "favorite_color": "red"}
event_data = json_schema_encoder.encode(dict_content, schema_id=schema_id, message_type=EventData)
event_data_batch.add(event_data)
eventhub_producer.send_batch(event_data_batch)
Event Hubs Receive Integration
Integration with Event Hubs to receive an EventData object and decode the encoded body value.
import os
from azure.eventhub import EventHubConsumerClient
from azure.schemaregistry import SchemaRegistryClient
from azure.schemaregistry.encoder.jsonencoder import JsonSchemaEncoder
from azure.identity import DefaultAzureCredential
token_credential = DefaultAzureCredential()
fully_qualified_namespace = os.environ['SCHEMAREGISTRY_JSON_FULLY_QUALIFIED_NAMESPACE']
group_name = os.environ['SCHEMAREGISTRY_GROUP']
eventhub_connection_str = os.environ['EVENT_HUB_CONN_STR']
eventhub_name = os.environ['EVENT_HUB_NAME']
DRAFT2020_12_SCHEMA_IDENTIFIER = "https://json-schema.org/draft/2020-12/schema"
schema_registry_client = SchemaRegistryClient(fully_qualified_namespace, token_credential)
json_schema_encoder = JsonSchemaEncoder(client=schema_registry_client, validate=DRAFT2020_12_SCHEMA_IDENTIFIER)
eventhub_consumer = EventHubConsumerClient.from_connection_string(
conn_str=eventhub_connection_str,
consumer_group='$Default',
eventhub_name=eventhub_name,
)
def on_event(partition_context, event):
decoded_content = json_schema_encoder.decode(event)
with eventhub_consumer, json_schema_encoder:
eventhub_consumer.receive(on_event=on_event, starting_position="-1")
Troubleshooting
General
Schema Registry clients raise exceptions defined in Azure Core if errors are encountered when communicating with the Schema Registry service.
Errors when encoding and decoding related to invalid content/content types will be raised as azure.schemaregistry.encoder.jsonencoder.InvalidContentError, where __cause__ will possibly contain an underlying exception.
Logging
This library uses the standard logging library for logging. Basic information about HTTP sessions (URLs, headers, etc.) is logged at INFO level.
Detailed DEBUG level logging, including request/response bodies and unredacted
headers, can be enabled on a client with the logging_enable argument:
import sys
import os
import logging
from azure.schemaregistry import SchemaRegistryClient
from azure.schemaregistry.encoder.jsonencoder import JsonSchemaEncoder
from azure.identity import DefaultAzureCredential
# Create a logger for the SDK
logger = logging.getLogger('azure.schemaregistry')
logger.setLevel(logging.DEBUG)
# Configure a console output
handler = logging.StreamHandler(stream=sys.stdout)
logger.addHandler(handler)
fully_qualified_namespace = os.environ['SCHEMAREGISTRY_FULLY_QUALIFIED_NAMESPACE']
group_name = os.environ['SCHEMAREGISTRY_GROUP']
DRAFT2020_12_SCHEMA_IDENTIFIER = "https://json-schema.org/draft/2020-12/schema"
credential = DefaultAzureCredential()
# This client will log detailed information about its HTTP sessions, at DEBUG level
schema_registry_client = SchemaRegistryClient(fully_qualified_namespace, credential, logging_enable=True)
encoder = JsonSchemaEncoder(client=schema_registry_client, validate=DRAFT2020_12_SCHEMA_IDENTIFIER)
Similarly, logging_enable can enable detailed logging for a single operation,
even when it isn't enabled for the client:
schema_registry_client.get_schema(schema_id, logging_enable=True)
Next steps
More sample code
Please take a look at the samples directory for detailed examples of how to use this library to register and retrieve schema to/from Schema Registry.
Contributing
This project welcomes contributions and suggestions. Most contributions require you to agree to a Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us the rights to use your contribution. For details, visit https://cla.microsoft.com.
When you submit a pull request, a CLA-bot will automatically determine whether you need to provide a CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions provided by the bot. You will only need to do this once across all repos using our CLA.
This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact opencode@microsoft.com with any additional questions or comments.
Release History
1.3.0 (2024-09-18)
This version and all future versions will require Python 3.8+. Python 3.7 is no longer supported.
Features Added
- Sync and async
JsonSchemaEncoderhave been added underazure.schemaregistry.encoder.jsonencoder. InvalidContentErrorhave been added underazure.schemaregistry.encoder.jsonencoderfor use with theJsonSchemaEncoder.MessageContent,OutboundMessageContent,InboundMessageContent, andSchemaContentValidatehave been added underazure.schemaregistryas protocols for use with theJsonSchemaEncoderand/or future encoder implementations.JsonandCustomhave been added to supported formats inSchemaFormat.V2022_10has been added toApiVersionand set as the default API version.
Bugs Fixed
- Fixed a bug in sync/async
register_schemaandget_schema_propertiesthat did not accept case insensitive strings as an argument to theformatparameter. - Fixed a bug where unknown content type strings from the service raised a client error, rather than being returned as a string in the SchemaProperties
formatproperty.
Other Changes
- Updated azure-core minimum dependency to 1.28.0.
- Added support for Python 3.11 and 3.12.
- The following features have been temporarily pulled out and will be added back in future previews as we work towards a stable release:
V2023_07_01inApiVersion.PROTOBUFinSchemaFormat.
1.3.0b3 (2023-11-09)
Features Added
V2023_07_01has been added toApiVersionand set as the default API version.Protobufhas been added to supported formats inSchemaFormat.
Other Changes
- Added support for Python 3.12.
1.3.0b2 (2023-08-09)
Features Added
The following features are experimental and may be removed:
- Sync and async
JsonSchemaEncoderhave been added underazure.schemaregistry.encoder.jsonencoder. InvalidContentErrorandJsonSchemaDraftIdentifierhave been added underazure.schemaregistry.encoder.jsonencoderfor use with theJsonSchemaEncoder.MessageType,MessageContent,SchemaContentValidate,SchemaEncoderhave been added underazure.schemaregistryas protocols to define/for use with theJsonSchemaEncoderand future encoder implementations.
1.3.0b1 (2023-01-12)
Features Added
V2022_10has been added toApiVersionand set as the default api version.JsonandCustomhave been added to supported formats inSchemaFormat.- At the time of this release, only Draft 3 of JSON schemas is currently supported by the service.
Bugs Fixed
- Fixed a bug in sync/async
register_schemaandget_schema_propertiesthat did not accept case insensitive strings as an argument to theformatparameter.
Other Changes
- Added support for Python 3.11.
1.2.0 (2022-10-10)
This version and all future versions will require Python 3.7+, Python 3.6 is no longer supported.
Features Added
group_name,name, andversionhave been added as optional parameters to theget_schemamethod on the sync and asyncSchemaRegistryClient.versionhas been added toSchemaProperties.
Other Changes
- Updated azure-core minimum dependency to 1.24.0.
- Added distributed tracing support for sync and async
SchemaRegistryClient.
1.1.0 (2022-05-10)
This version and all future versions will require Python 3.6+. Python 2.7 is no longer supported.
Features Added
group_nameandnamehave been added as instance variables toSchemaProperties.
Other Changes
- Updated azure-core minimum dependency to 1.23.0.
1.0.0 (2021-11-10)
Note: This is the first stable release of our efforts to create a user-friendly and Pythonic client library for Azure Schema Registry.
Features Added
SchemaRegistryClientis the top-level client class interacting with the Azure Schema Registry Service. It provides three methods:register_schema: Store schema in the service by providing schema group name, schema name, schema definition, and schema format.get_schema: Get schema definition and its properties by schema id.get_schema_properties: Get schema properties by providing schema group name, schema name, schema definition, and schema format.
SchemaPropertieshas the following instance variables:idandformat:- The type of
formathas been changed fromstrtoSchemaFormat.
- The type of
Schemahas the following properties:propertiesanddefinition.SchemaFormatprovides the schema format to be stored by the service. Currently, the only supported format isAvro.api_versionhas been added as a keyword arg to the sync and asyncSchemaRegistryClientconstructors.
Breaking Changes
versioninstance variable inSchemaPropertieshas been removed.schema_definitioninstance variable inSchemahas been renameddefinition.idparameter inget_schemamethod on sync and asyncSchemaRegistryClienthas been renamedschema_id.schema_definitionparameter inregister_schemaandget_schema_propertiesmethods on sync and asyncSchemaRegistryClienthas been renameddefinition.serializernamespace has been removed fromazure.schemaregistry.
1.0.0b3 (2021-10-05)
Breaking Changes
get_schema_idmethod on sync and asyncSchemaRegistryClienthas been renamedget_schema_properties.schema_idparameter inget_schemamethod on sync and asyncSchemaRegistryClienthas been renamedid.register_schemaandget_schema_propertiesmethods on sync and asyncSchemaRegistryClientnow take in the following parameters in the given order:group_name, which has been renamed fromschema_groupname, which has been renamed fromschema_nameschema_definition, which has been renamed fromschema_contentformat, which has been renamed fromserialization_type
endpointparameter inSchemaRegistryClientconstructor has been renamedfully_qualified_namespacelocationinstance variable inSchemaPropertieshas been removed.SchemaandSchemaPropertiesno longer have positional parameters, as they will not be constructed by the user.
Other Changes
- Updated azure-core dependency to 1.19.0.
- Removed caching support of registered schemas so requests are sent to the service to register schemas, get schema properties, and get schemas.
1.0.0b2 (2021-08-17)
This version and all future versions will require Python 2.7 or Python 3.6+, Python 3.5 is no longer supported.
Features Added
- Support caching of registered schemas and send requests to the service only if the cache does not have the looked-up schema/schema ID.
1.0.0b1 (2020-09-09)
Version 1.0.0b1 is the first preview of our efforts to create a user-friendly and Pythonic client library for Azure Schema Registry.
New features
SchemaRegistryClientis the top-level client class interacting with the Azure Schema Registry Service. It provides three methods:register_schema: Store schema into the service.get_schema: Get schema content and its properties by schema id.get_schema_id: Get schema id and its properties by schema group, schema name, serialization type and schema content.
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