Microsoft Azure Schema Registry Avro Encoder Client Library for Python
Project description
Azure Schema Registry Avro Encoder client library for Python
Azure Schema Registry is a schema repository service hosted by Azure Event Hubs, providing schema storage, versioning, and management. This package provides an Avro encoder capable of encoding and decoding payloads containing Schema Registry schema identifiers and Avro-encoded content.
Source code | Package (PyPi) | API reference documentation | Samples | Changelog
Disclaimer
Azure SDK Python packages support for Python 2.7 has ended 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 Avro Encoder client library for Python with pip:
pip install azure-schemaregistry-avroencoder
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 3.6 or later - Install Python
Authenticate the client
Interaction with the Schema Registry Avro Encoder starts with an instance of AvroEncoder class, which takes the schema group name and the Schema Registry Client class. The client constructor takes the Event Hubs fully qualified namespace and and 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
TokenCredential
protocol 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 AvroEncoder using the azure-schemaregistry library:
import os
from azure.schemaregistry import SchemaRegistryClient
from azure.schemaregistry.encoder.avroencoder import AvroEncoder
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 = AvroEncoder(client=schema_registry_client, group_name=group_name)
Key concepts
AvroEncoder
Provides API to encode to and decode from Avro Binary Encoding plus a content type with schema ID. Uses SchemaRegistryClient to get schema IDs from schema content or vice versa.
Supported message models
Support has been added to certain Azure Messaging SDK model classes for interoperability with the AvroEncoder
. These models are subtypes of the MessageType
protocol defined under the azure.schemaregistry.encoder.avroencoder
namespace. Currently, the supported model classes are:
azure.eventhub.EventData
forazure-eventhub>=5.9.0
Message format
If a message type that follows the MessageType protocol is provided to the encoder for encoding, it will set the corresponding content and content type properties, where:
-
content
: Avro payload (in general, format-specific payload)- Avro Binary Encoding
- NOT Avro Object Container File, which includes the schema and defeats the purpose of this encoder to move the schema out of the message payload and into the schema registry.
-
content type
: a string of the formatavro/binary+<schema ID>
, where:avro/binary
is 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
body
property will be set to the content value. - The
content_type
property 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": <Avro encoded payload>, "content_type": 'avro/binary+<schema ID>' }
Examples
The following sections provide several code snippets covering some of the most common Schema Registry tasks, including:
Encoding
Use the AvroEncoder.encode
method to encode content with the given Avro schema.
The method will use a schema previously registered to the Schema Registry service and keep the schema cached for future encoding usage. In order to avoid pre-registering the schema to the service and automatically register it with the encode
method, the keyword argument auto_register=True
should be passed to the AvroEncoder
constructor.
import os
from azure.schemaregistry import SchemaRegistryClient
from azure.schemaregistry.encoder.avroencoder import AvroEncoder
from azure.identity import DefaultAzureCredential
from azure.eventhub import EventData
token_credential = DefaultAzureCredential()
fully_qualified_namespace = os.environ['SCHEMAREGISTRY_FULLY_QUALIFIED_NAMESPACE']
group_name = os.environ['SCHEMAREGISTRY_GROUP']
name = "example.avro.User"
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, token_credential)
schema_registry_client.register_schema(group_name, name, definition, format)
encoder = AvroEncoder(client=schema_registry_client, group_name=group_name)
with encoder:
dict_content = {"name": "Ben", "favorite_number": 7, "favorite_color": "red"}
event_data = encoder.encode(dict_content, schema=definition, message_type=EventData)
# OR
message_content_dict = encoder.encode(dict_content, schema=definition)
event_data = EventData.from_message_content(message_content_dict["content"], message_content_dict["content_type"])
Decoding
Use the AvroEncoder.decode
method to decode the Avro-encoded content by either:
- Passing in a message object that is a subtype of the MessageType protocol.
- Passing in a dict with keys
content
(type bytes) andcontent_type
(type string). The method automatically retrieves the schema from the Schema Registry Service and keeps the schema cached for future decoding usage.
import os
from azure.schemaregistry import SchemaRegistryClient
from azure.schemaregistry.encoder.avroencoder import AvroEncoder
from azure.identity import DefaultAzureCredential
token_credential = DefaultAzureCredential()
fully_qualified_namespace = os.environ['SCHEMAREGISTRY_FULLY_QUALIFIED_NAMESPACE']
group_name = "<your-group-name>"
schema_registry_client = SchemaRegistryClient(fully_qualified_namespace, token_credential)
encoder = AvroEncoder(client=schema_registry_client)
with encoder:
# event_data is an EventData object with Avro encoded body
dict_content = {"name": "Ben", "favorite_number": 7, "favorite_color": "red"}
event_data = encoder.encode(dict_content, schema=definition, message_type=EventData)
decoded_content = encoder.decode(event_data)
# OR
encoded_bytes = b'<content_encoded_by_azure_schema_registry_avro_encoder>'
content_type = 'avro/binary+<schema_id_of_corresponding_schema>'
content_dict = {"content": encoded_bytes, "content_type": content_type}
decoded_content = encoder.decode(content_dict)
Event Hubs Sending Integration
Integration with Event Hubs to send an EventData
object with body
set to Avro-encoded content and corresponding content_type
.
import os
from azure.eventhub import EventHubProducerClient, EventData
from azure.schemaregistry import SchemaRegistryClient
from azure.schemaregistry.encoder.avroencoder import AvroEncoder
from azure.identity import DefaultAzureCredential
token_credential = DefaultAzureCredential()
fully_qualified_namespace = os.environ['SCHEMAREGISTRY_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']
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, token_credential)
avro_encoder = AvroEncoder(client=schema_registry_client, group_name=group_name, auto_register=True)
eventhub_producer = EventHubProducerClient.from_connection_string(
conn_str=eventhub_connection_str,
eventhub_name=eventhub_name
)
with eventhub_producer, avro_encoder:
event_data_batch = eventhub_producer.create_batch()
dict_content = {"name": "Bob", "favorite_number": 7, "favorite_color": "red"}
event_data = avro_encoder.encode(dict_content, schema=definition, message_type=EventData)
event_data_batch.add(event_data)
eventhub_producer.send_batch(event_data_batch)
Event Hubs Receiving Integration
Integration with Event Hubs to receive an EventData
object and decode the the Avro-encoded body
value.
import os
from azure.eventhub import EventHubConsumerClient
from azure.schemaregistry import SchemaRegistryClient
from azure.schemaregistry.encoder.avroencoder import AvroEncoder
from azure.identity import DefaultAzureCredential
token_credential = DefaultAzureCredential()
fully_qualified_namespace = os.environ['SCHEMAREGISTRY_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_registry_client = SchemaRegistryClient(fully_qualified_namespace, token_credential)
avro_encoder = AvroEncoder(client=schema_registry_client, group_name=group_name)
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 = avro_encoder.decode(event)
with eventhub_consumer, avro_encoder:
eventhub_consumer.receive(on_event=on_event, starting_position="-1")
Troubleshooting
General
Azure Schema Registry Avro Encoder raises exceptions defined in Azure Core if errors are encountered when communicating with the Schema Registry service. Errors related to invalid content/content types and invalid schemas will be raised as azure.schemaregistry.encoder.avroencoder.InvalidContentError
and azure.schemaregistry.encoder.avroencoder.InvalidSchemaError
, respectively, where __cause__
will contain the underlying exception raised by the Apache Avro library.
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.avroencoder import AvroEncoder
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']
credential = DefaultAzureCredential()
schema_registry_client = SchemaRegistryClient(fully_qualified_namespace, credential, logging_enable=True)
# This client will log detailed information about its HTTP sessions, at DEBUG level
encoder = AvroEncoder(client=schema_registry_client, group_name=group_name)
Similarly, logging_enable
can enable detailed logging for a single operation,
even when it isn't enabled for the client:
encoder.encode(dict_content, schema=definition, logging_enable=True)
Next steps
More sample code
Further examples demonstrating common Azure Schema Registry Avro Encoder scenarios are in the samples directory.
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
1.0.0 (2022-05-10)
Note: This is the first stable release of our efforts to create a user-friendly Pythonic Avro Encoder library that integrates with the Python client library for Azure Schema Registry.
Features Added
AvroEncoder
sync and async classes provide the functionality to encode and decode content which follows a schema with the RecordSchema format, as defined by the Apache Avro specification. The Apache Avro library is used as the implementation for encoding and decoding. The encoder will automatically register and retrieve schemas from Azure Schema Registry Service. It provides the following methods:- constructor: If
auto_register=True
keyword is passed in, will automatically register schemas passed in to theencode
method. Otherwise, and by default, will require pre-registering of schemas passed toencode
. Takes agroup_name
argument that is optional when decoding, but required for encoding. encode
: Encodes dict content into bytes according to the given schema and registers schema if needed. Returns either a dict of encoded content and corresponding content type or aMessageType
subtype object, depending on arguments provided.decode
: Decodes bytes content into dict content by automatically retrieving schema from the service.
- constructor: If
MessageContent
TypedDict has been introduced with the following required keys:content
: The bytes content.content_type
: The string content type, which holds the schema ID and the record format indicator.
MessageType
has been introduced with the following methods:from_message_content
: Class method that creates an object with given bytes content and string content type.__message_content__
: Returns aMessageContent
object with content and content type values set to their respective properties on the object.
- Schemas and Schema IDs are cached locally, so that multiple calls with the same schema/schema ID will not trigger multiple service calls.
- The number of hits, misses, and total entries for the schema/schema ID caches will be logged at an info level when a new entry is added.
InvalidContentError
has been introduced for errors related to invalid content and content types, where__cause__
will contain the underlying exception raised by the Avro library.InvalidSchemaError
has been introduced for errors related to invalid schemas, where__cause__
will contain the underlying exception raised by the Apache Avro library.- The
encode
anddecode
methods onAvroEncoder
support the following message models:azure.eventhub.EventData
inazure-eventhub>=5.9.0
Other Changes
- This package is meant to replace the azure-schemaregistry-avroserializer package, which will no longer be supported.
group_name
is now an optional parameter in the sync and asyncAvroEncoder
constructors.
1.0.0b3 (2022-04-05)
Breaking Changes
auto_register_schemas
keyword in the sync and asyncAvroEncoder
constructors has been renamedauto_register
.SchemaParseError
,SchemaEncodeError
, andSchemaDecodeError
have been replaced withInvalidContentError
andInvalidSchemaError
. The errors have been added under theazure.schemaregistry.encoder.avroencoder
namespace.- The
exceptions
module inazure.schemaregistry.encoder.avroencoder
has been removed. - The
encode
method on the sync and asyncAvroEncoder
only allows subtypes of theMessageType
protocol as values to themessage_type
optional parameter, rather than any callable that has the method signature(content: bytes, content_type: str, **kwargs: Any)
. - The number of hits/misses, in addition to number of entries, for the schema/schema ID caches will be logged at an info level when a new entry is added.
Other Changes
- This release and future releases will not have backward compatibility support for decoding data that was encoded with the AvroSerializer.
- The
encode
anddecode
methods onAvroEncoder
support the following message models:azure.eventhub.EventData
inazure-eventhub==5.9.0b3
1.0.0b2 (2022-03-09)
Features Added
request_options
has been added toencode
anddecode
onAvroEncoder
as an optional parameter to be passed into client requests.- The size of the current schema/schema ID caches will be logged at an info level when a new entry has been added.
Breaking Changes
MessageMetadataDict
has been renamedMessageContent
.data
inMessageContent
has been renamedcontent
.- The
data
parameter inencode
anddecode
on the sync and asyncAvroEncoder
has been renamedcontent
. - The
from_message_data
method in theMessageType
protocol has been renamedfrom_message_content
. Thedata
parameter infrom_message_content
has been renamedcontent
. - The
__message_data__
method in theMessageType
protocol has been renamed__message_content__
.
Other Changes
- This beta release will be backward compatible for decoding data that was encoded with the AvroSerializer.
- The
encode
anddecode
methods onAvroEncoder
support the following message models:azure.eventhub.EventData
inazure-eventhub==5.9.0b2
1.0.0b1 (2022-02-09)
This version and all future versions will require Python 3.6+. Python 2.7 is no longer supported.
Features Added
- This package is meant to replace the azure-schemaregistry-avroserializer.
- APIs have been updated to allow for encoding directly to and decoding from message type objects, where the data value is the Avro encoded payload.
- The content type of the message will hold the schema ID and record format indicator.
Other Changes
- This beta release will be backward compatible for decoding data that was encoded with the AvroSerializer.
- The
encode
anddecode
methods onAvroEncoder
support the following message models:azure.eventhub.EventData
inazure-eventhub==5.9.0b1
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