Update docs metadata

Author: azure-sdk

docs-ref-services/preview/schemaregistry-avroencoder-readme.md

@@ -3,19 +3,19 @@ title: Azure Schema Registry Avro Encoder client library for Python
 keywords: Azure, python, SDK, API, azure-schemaregistry-avroencoder, schemaregistry
 author: yunhaoling
 ms.author: yuling
-ms.date: 02/10/2022
+ms.date: 03/09/2022
 ms.topic: reference
 ms.prod: azure
 ms.technology: azure
 ms.devlang: python
 ms.service: schemaregistry
 ---
-# Azure Schema Registry Avro Encoder client library for Python - Version 1.0.0b1 
+# Azure Schema Registry Avro Encoder client library for Python - Version 1.0.0b2 
 
 
 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 data.
+Schema Registry schema identifiers and Avro-encoded content.
 
 [Source code][source_code] | [Package (PyPi)][pypi] | [API reference documentation][api_reference] | [Samples][sr_avro_samples] | [Changelog][change_log]
 
@@ -83,13 +83,13 @@ content type with schema ID. Uses [SchemaRegistryClient][schemaregistry_client]
 
 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` for `azure-eventhub==5.9.0b1`
+- `azure.eventhub.EventData` for `azure-eventhub==5.9.0b2`
 
 ### Message format
 
-If a message type that follows the MessageType protocol is provided to the encoder, it will encode the corresponding data and content type properties as follows:
+If a message type that follows the MessageType protocol is provided to the encoder, it will encode the corresponding content and content type properties as follows:
 
-- `data`: Avro payload (in general, format-specific payload)
+- `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
@@ -100,7 +100,7 @@ If a message type that follows the MessageType protocol is provided to the encod
   - `<schema ID>` is the hexadecimal representation of GUID, same format and byte order as the string from the Schema Registry service.
 
 If message type or callback function is not provided, and by default, the encoder will create the following dict:
-`{"data": <Avro encoded payload>, "content_type": 'avro/binary+<schema ID>' }`
+`{"content": <Avro encoded payload>, "content_type": 'avro/binary+<schema ID>' }`
 
 ## Examples
 
@@ -113,7 +113,7 @@ The following sections provide several code snippets covering some of the most c
 
 ### Encoding
 
-Use `AvroEncoder.encode` method to encode dict data with the given Avro schema.
+Use `AvroEncoder.encode` method to encode dict 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. It is also possible to avoid pre-registering the schema to the service and automatically register with the `encode` method by instantiating the `AvroEncoder` with the keyword argument `auto_register_schemas=True`.
 
 ```python
@@ -145,20 +145,20 @@ schema_register_client.register(group_name, name, definition, format)
 encoder = AvroEncoder(client=schema_registry_client, group_name=group_name)
 
 with encoder:
-    dict_data = {"name": "Ben", "favorite_number": 7, "favorite_color": "red"}
-    event_data = encoder.encode(dict_data, schema=definition, message_type=EventData)
+    dict_content = {"name": "Ben", "favorite_number": 7, "favorite_color": "red"}
+    event_data = encoder.encode(dict_content, schema=definition, message_type=EventData)
 
     # OR
 
-    metadata_dict = encoder.encode(dict_data, schema=definition)
-    event_data = EventData.from_message_data(metadata_dict["data"], metadata_dict["content_type"])
+    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 `AvroEncoder.decode` method to decode the bytes value into dict data by either:
+Use `AvroEncoder.decode` method to decode the bytes value into dict content by either:
  - Passing in a message object that is a subtype of the MessageType protocol.
- - Passing in a dict with keys `data`(type bytes) and `content_type` (type string).
+ - Passing in a dict with keys `content`(type bytes) and `content_type` (type string).
 The method automatically retrieves the schema from the Schema Registry Service and keeps the schema cached for future decoding usage.
 
 ```python
@@ -176,19 +176,19 @@ encoder = AvroEncoder(client=schema_registry_client, group_name=group_name)
 
 with encoder:
     # event_data is an EventData object with Avro encoded body
-    decoded_data = encoder.decode(event_data)
+    decoded_content = encoder.decode(event_data)
 
     # OR 
 
-    encoded_bytes = b'<data_encoded_by_azure_schema_registry_avro_encoder>'
+    encoded_bytes = b'<content_encoded_by_azure_schema_registry_avro_encoder>'
     content_type = 'avro/binary+<schema_id_of_corresponding_schema>'
-    data_dict = {"data": encoded_bytes, "content_type": content_type}
-    decoded_data = encoder.decode(data_dict)
+    content_dict = {"content": encoded_bytes, "content_type": content_type}
+    decoded_content = encoder.decode(content_dict)
 ```
 
 ### Event Hubs Sending Integration
 
-Integration with [Event Hubs][eventhubs_repo] to send encoded Avro dict data as the body of EventData.
+Integration with [Event Hubs][eventhubs_repo] to send encoded Avro dict content as the body of EventData.
 
 ```python
 import os
@@ -224,15 +224,15 @@ eventhub_producer = EventHubProducerClient.from_connection_string(
 
 with eventhub_producer, avro_encoder:
     event_data_batch = eventhub_producer.create_batch()
-    dict_data = {"name": "Bob", "favorite_number": 7, "favorite_color": "red"}
-    event_data = avro_encoder.encode(dict_data, schema=definition, message_type=EventData)
+    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][eventhubs_repo] to receive `EventData` and decoded raw bytes into Avro dict data.
+Integration with [Event Hubs][eventhubs_repo] to receive `EventData` and decoded raw bytes into Avro dict content.
 
 ```python
 import os
@@ -257,7 +257,7 @@ eventhub_consumer = EventHubConsumerClient.from_connection_string(
 )
 
 def on_event(partition_context, event):
-    decoded_data = avro_encoder.decode(event)
+    decoded_content = avro_encoder.decode(event)
 
 with eventhub_consumer, avro_encoder:
     eventhub_consumer.receive(on_event=on_event, starting_position="-1")
@@ -301,7 +301,7 @@ encoder = AvroEncoder(client=schema_registry_client, group_name="<your-group-nam
 Similarly, `logging_enable` can enable detailed logging for a single operation,
 even when it isn't enabled for the client:
 ```py
-encoder.encode(dict_data, schema=schema_definition, logging_enable=True)
+encoder.encode(dict_content, schema=schema_definition, logging_enable=True)
 ```
 
 ## Next steps
@@ -326,17 +326,17 @@ contact [[email protected]](mailto:[email protected]) with any additio
 
 <!-- LINKS -->
 [pip]: https://pypi.org/project/pip/
-[pypi]: https://pypi.org/
+[pypi]: https://pypi.org/project/azure-schemaregistry-avroencoder/
 [python]: https://www.python.org/downloads/
-[azure_core]: https://github.com/Azure/azure-sdk-for-python/blob/azure-schemaregistry-avroencoder_1.0.0b1/sdk/core/azure-core/README.md
+[azure_core]: https://github.com/Azure/azure-sdk-for-python/blob/azure-schemaregistry-avroencoder_1.0.0b2/sdk/core/azure-core/README.md
 [azure_sub]: https://azure.microsoft.com/free/
 [python_logging]: https://docs.python.org/3/library/logging.html
-[sr_avro_samples]: https://github.com/Azure/azure-sdk-for-python/tree/azure-schemaregistry-avroencoder_1.0.0b1/sdk/schemaregistry/azure-schemaregistry-avroencoder/samples
-[api_reference]: https://docs.microsoft.com/python/api/
-[source_code]: https://github.com/Azure/azure-sdk-for-python/tree/azure-schemaregistry-avroencoder_1.0.0b1/sdk/schemaregistry/azure-schemaregistry-avroencoder
-[change_log]: https://github.com/Azure/azure-sdk-for-python/tree/azure-schemaregistry-avroencoder_1.0.0b1/sdk/schemaregistry/azure-schemaregistry-avroencoder/CHANGELOG.md
-[schemaregistry_client]: https://github.com/Azure/azure-sdk-for-python/tree/azure-schemaregistry-avroencoder_1.0.0b1/sdk/schemaregistry/azure-schemaregistry
+[sr_avro_samples]: https://github.com/Azure/azure-sdk-for-python/tree/azure-schemaregistry-avroencoder_1.0.0b2/sdk/schemaregistry/azure-schemaregistry-avroencoder/samples
+[api_reference]: https://docs.microsoft.com/python/api/overview/azure/schemaregistry-avroencoder-readme
+[source_code]: https://github.com/Azure/azure-sdk-for-python/tree/azure-schemaregistry-avroencoder_1.0.0b2/sdk/schemaregistry/azure-schemaregistry-avroencoder
+[change_log]: https://github.com/Azure/azure-sdk-for-python/tree/azure-schemaregistry-avroencoder_1.0.0b2/sdk/schemaregistry/azure-schemaregistry-avroencoder/CHANGELOG.md
+[schemaregistry_client]: https://github.com/Azure/azure-sdk-for-python/tree/azure-schemaregistry-avroencoder_1.0.0b2/sdk/schemaregistry/azure-schemaregistry
 [schemaregistry_service]: https://aka.ms/schemaregistry
-[eventhubs_repo]: https://github.com/Azure/azure-sdk-for-python/tree/azure-schemaregistry-avroencoder_1.0.0b1/sdk/eventhub/azure-eventhub
-[token_credential_interface]: https://github.com/Azure/azure-sdk-for-python/tree/azure-schemaregistry-avroencoder_1.0.0b1/sdk/core/azure-core/azure/core/credentials.py
+[eventhubs_repo]: https://github.com/Azure/azure-sdk-for-python/tree/azure-schemaregistry-avroencoder_1.0.0b2/sdk/eventhub/azure-eventhub
+[token_credential_interface]: https://github.com/Azure/azure-sdk-for-python/tree/azure-schemaregistry-avroencoder_1.0.0b2/sdk/core/azure-core/azure/core/credentials.py
 [pypi_azure_identity]: https://pypi.org/project/azure-identity/

metadata/preview/azure-schemaregistry-avroencoder.json

@@ -1,6 +1,6 @@
 {
   "Name": "azure-schemaregistry-avroencoder",
-  "Version": "1.0.0b1",
+  "Version": "1.0.0b2",
   "DevVersion": null,
   "DirectoryPath": "sdk/schemaregistry/azure-schemaregistry-avroencoder",
   "ServiceDirectory": "schemaregistry",
@@ -10,5 +10,5 @@
   "SdkType": "client",
   "IsNewSdk": false,
   "ArtifactName": "azure-schemaregistry-avroencoder",
-  "ReleaseStatus": "2022-02-09"
+  "ReleaseStatus": "2022-03-09"
 }