async def test_encode_primitive(self, schemaregistry_fully_qualified_namespace, schemaregistry_group, **kwargs): sr_client = self.create_client(fully_qualified_namespace=schemaregistry_fully_qualified_namespace) sr_avro_encoder = AvroEncoder(client=sr_client, group_name=schemaregistry_group, auto_register_schemas=True) null_type = """{"type": "null"}""" encoded_metadata = await sr_avro_encoder.encode(None, schema=null_type) assert len(encoded_metadata["data"]) == 0 # assert no data encoded
async def test_parse_invalid_type(self, schemaregistry_fully_qualified_namespace, schemaregistry_group, **kwargs): sr_client = self.create_client( fully_qualified_namespace=schemaregistry_fully_qualified_namespace) sr_avro_encoder = AvroEncoder(client=sr_client, group_name=schemaregistry_group, auto_register=True) schema_no_type = """{ "name": "User", "namespace":"example.avro", "fields":[{"name":"name","type":"string"}] }""" with pytest.raises(InvalidSchemaError): await sr_avro_encoder.encode({"name": u"Ben"}, schema=schema_no_type) schema_wrong_type_type = """{ "name":"User", "type":1, "namespace":"example.avro", "fields":[{"name":"name","type":"string"}] }""" with pytest.raises(InvalidSchemaError): await sr_avro_encoder.encode({"name": u"Ben"}, schema=schema_wrong_type_type)
async def test_parse_primitive_types(self, schemaregistry_fully_qualified_namespace, schemaregistry_group, **kwargs): sr_client = self.create_client(fully_qualified_namespace=schemaregistry_fully_qualified_namespace) sr_avro_encoder = AvroEncoder(client=sr_client, group_name=schemaregistry_group, auto_register_schemas=True) primitive_string = "string" with pytest.raises(SchemaParseError) as e: await sr_avro_encoder.encode("hello", schema=primitive_string)
async def test_basic_sr_avro_encoder_decode_readers_schema(self, schemaregistry_fully_qualified_namespace, schemaregistry_group, **kwargs): sr_client = self.create_client(schemaregistry_fully_qualified_namespace) sr_avro_encoder = AvroEncoder(client=sr_client, group_name=schemaregistry_group, auto_register_schemas=True) schema_str = """{"namespace":"example.avro","type":"record","name":"User","fields":[{"name":"name","type":"string"},{"name":"favorite_number","type":["int","null"]},{"name":"favorite_color","type":["string","null"]}]}""" dict_data = {"name": u"Ben", "favorite_number": 7, "favorite_color": u"red"} encoded_metadata = await sr_avro_encoder.encode(dict_data, schema=schema_str) content_type = encoded_metadata["content_type"] encoded_data = encoded_metadata["data"] # readers_schema with removed field readers_schema_remove_field = """{"namespace":"example.avro","type":"record","name":"User","fields":[{"name":"name","type":"string"},{"name":"favorite_number","type":["int","null"]}]}""" encoded_data_dict = {"data": encoded_data, "content_type": content_type} decoded_data = await sr_avro_encoder.decode(encoded_data_dict, readers_schema=readers_schema_remove_field) assert decoded_data["name"] == u"Ben" assert decoded_data["favorite_number"] == 7 # readers_schema with extra field with default readers_schema_extra_field = """{"namespace":"example.avro","type":"record","name":"User","fields":[{"name":"name","type":"string"},{"name":"favorite_number","type":["int","null"]},{"name":"favorite_color","type":["string","null"]}, {"name":"favorite_city","type":["string","null"], "default": "Redmond"}]}""" encoded_data_dict = {"data": encoded_data, "content_type": content_type} decoded_data = await sr_avro_encoder.decode(encoded_data_dict, readers_schema=readers_schema_extra_field) assert decoded_data["name"] == u"Ben" assert decoded_data["favorite_number"] == 7 assert decoded_data["favorite_color"] == "red" assert decoded_data["favorite_city"] == "Redmond" # readers_schema with changed name results in error readers_schema_change_name = """{"namespace":"fakeexample.avro","type":"record","name":"fake_user","fields":[{"name":"name","type":"string"},{"name":"favorite_number","type":["int","null"]},{"name":"favorite_color","type":["string","null"]}]}""" with pytest.raises(SchemaDecodeError): encoded_data_dict = {"data": encoded_data, "content_type": content_type} decoded_data = await sr_avro_encoder.decode(encoded_data_dict, readers_schema=readers_schema_change_name) print(decoded_data)
async def test_parse_fixed_types(self, schemaregistry_fully_qualified_namespace, schemaregistry_group, **kwargs): sr_client = self.create_client( fully_qualified_namespace=schemaregistry_fully_qualified_namespace) sr_avro_encoder = AvroEncoder(client=sr_client, group_name=schemaregistry_group, auto_register=True) # avro bug: should give warning from IgnoredLogicalType error since precision < 0 #fixed_type_ignore_logical_type_error = """{"type": "fixed", "size": 4, "namespace":"example.avro", "name":"User", "precision": -1}""" #await sr_avro_encoder.encode({}, schema=fixed_type_ignore_logical_type_error) schema_no_size = """{"type": "fixed", "name":"User"}""" with pytest.raises(InvalidSchemaError): # caught AvroException await sr_avro_encoder.encode({}, schema=schema_no_size) schema_no_name = """{"type": "fixed", "size": 3}""" with pytest.raises(InvalidSchemaError): await sr_avro_encoder.encode({}, schema=schema_no_name) schema_wrong_name = """{"type": "fixed", "name": 1, "size": 3}""" with pytest.raises(InvalidSchemaError): await sr_avro_encoder.encode({}, schema=schema_wrong_name) schema_wrong_namespace = """{"type": "fixed", "name": "User", "size": 3, "namespace": 1}""" with pytest.raises(InvalidSchemaError): await sr_avro_encoder.encode({}, schema=schema_wrong_namespace)
async def test_encode_record(self, schemaregistry_fully_qualified_namespace, schemaregistry_group, **kwargs): sr_client = self.create_client(fully_qualified_namespace=schemaregistry_fully_qualified_namespace) sr_avro_encoder = AvroEncoder(client=sr_client, group_name=schemaregistry_group, auto_register_schemas=True) # add below to schema later if possible # {"name":"example.innerrec","type":"record","fields":[{"name":"a","type":"int"}]}, # {"name":"innerenum","type":"enum","symbols":["FOO", "BAR"]}, # {"name":"innerarray","type":"array","items":"int"}, # {"name":"innermap","type":"map","values":"int"}, # {"name":"innerfixed","type":"fixed","size":74} schema_record = """{ "name":"User", "namespace":"example.avro.populatedrecord", "type":"record", "fields":[ {"name":"name","type":"string"}, {"name":"age","type":"int"}, {"name":"married","type":"boolean"}, {"name":"height","type":"float"}, {"name":"randb","type":"bytes"} ] }""" data = { "name": u"Ben", "age": 3, "married": False, "height": 13.5, "randb": b"\u00FF" } encoded_metadata = await sr_avro_encoder.encode(data, schema=schema_record) decoded_data = await sr_avro_encoder.decode(encoded_metadata) assert decoded_data == data
async def main(): schema_registry = SchemaRegistryClient( fully_qualified_namespace=SCHEMAREGISTRY_FULLY_QUALIFIED_NAMESPACE, credential=token_credential, ) encoder = AvroEncoder(client=schema_registry, group_name=GROUP_NAME, auto_register_schemas=True) event_data_ben = await encode_with_callback(encoder) await encoder.close() await token_credential.close()
async def test_parse_invalid_json_string(self, schemaregistry_fully_qualified_namespace, schemaregistry_group, **kwargs): sr_client = self.create_client(fully_qualified_namespace=schemaregistry_fully_qualified_namespace) sr_avro_encoder = AvroEncoder(client=sr_client, group_name=schemaregistry_group, auto_register_schemas=True) invalid_schema = { "name":"User", "type":"record", "namespace":"example.avro", "fields":[{"name":"name","type":"string"}] } invalid_schema_string = "{}".format(invalid_schema) with pytest.raises(SchemaParseError): # caught avro SchemaParseError await sr_avro_encoder.encode({"name": u"Ben"}, schema=invalid_schema_string)
async def main(): schema_registry = SchemaRegistryClient( fully_qualified_namespace=SCHEMAREGISTRY_FULLY_QUALIFIED_NAMESPACE, credential=token_credential, ) encoder = AvroEncoder(client=schema_registry, group_name=GROUP_NAME, auto_register_schemas=True) event_data = await encode_metadata_dict(encoder) decoded_data = await decode_with_data_and_content_type(encoder, event_data) await encoder.close() await token_credential.close()
async def test_parse_error_schema_as_record(self, schemaregistry_fully_qualified_namespace, schemaregistry_group, **kwargs): sr_client = self.create_client(fully_qualified_namespace=schemaregistry_fully_qualified_namespace) sr_avro_encoder = AvroEncoder(client=sr_client, group_name=schemaregistry_group, auto_register_schemas=True) schema_error_type = """{ "name":"User", "namespace":"example.avro.error", "type":"error", "fields":[{"name":"name","type":"string"}] }""" encoded_metadata = await sr_avro_encoder.encode({"name": u"Ben"}, schema=schema_error_type) schema_id = encoded_metadata["content_type"].split("+")[1] registered_schema = await sr_client.get_schema(schema_id) decoded_registered_schema = json.loads(registered_schema.definition) assert decoded_registered_schema["type"] == "error"
async def main(): schema_registry = SchemaRegistryClient( fully_qualified_namespace=SCHEMAREGISTRY_FULLY_QUALIFIED_NAMESPACE, credential=token_credential, ) encoder = AvroEncoder(client=schema_registry, group_name=GROUP_NAME, auto_register=True) event_data_ben, event_data_alice = await encode_to_event_data_message( encoder) decoded_content_ben = await decode_event_data_message( encoder, event_data_ben) decoded_content_alice = await decode_event_data_message( encoder, event_data_alice) await encoder.close() await token_credential.close()
async def test_basic_sr_avro_encoder_without_auto_register_schemas( self, schemaregistry_fully_qualified_namespace, schemaregistry_group, **kwargs): sr_client = self.create_client( fully_qualified_namespace=schemaregistry_fully_qualified_namespace) sr_avro_encoder = AvroEncoder(client=sr_client, group_name=schemaregistry_group, auto_register=True) async with sr_client: schema_str = """{"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_str = "{\"type\": \"record\", \"name\": \"User\", \"namespace\": \"example.avro\", \"fields\": [{\"type\": \"string\", \"name\": \"name\"}, {\"type\": [\"int\", \"null\"], \"name\": \"favorite_number\"}, {\"type\": [\"string\", \"null\"], \"name\": \"favorite_color\"}]}" schema = avro.schema.parse(schema_str) dict_content = { "name": u"Ben", "favorite_number": 7, "favorite_color": u"red" } encoded_message_content = await sr_avro_encoder.encode( dict_content, schema=schema_str) content_type = encoded_message_content["content_type"] encoded_content = encoded_message_content["content"] assert content_type.split("+")[0] == 'avro/binary' schema_properties = await sr_client.get_schema_properties( schemaregistry_group, schema.fullname, str(schema), "Avro") schema_id = schema_properties.id assert content_type.split("+")[1] == schema_id encoded_content_dict = { "content": encoded_content, "content_type": content_type } decoded_content = await sr_avro_encoder.decode(encoded_content_dict ) assert decoded_content["name"] == u"Ben" assert decoded_content["favorite_number"] == 7 assert decoded_content["favorite_color"] == u"red"
async def test_basic_sr_avro_encoder_with_request_options(self, **kwargs): schemaregistry_fully_qualified_namespace = kwargs.pop( "schemaregistry_fully_qualified_namespace") schemaregistry_group = kwargs.pop("schemaregistry_group") sr_client = self.create_client( fully_qualified_namespace=schemaregistry_fully_qualified_namespace) sr_avro_encoder = AvroEncoder(client=sr_client, group_name=schemaregistry_group, auto_register=True) schema_str = """{"namespace":"example.avro","type":"record","name":"User","fields":[{"name":"name","type":"string"},{"name":"favorite_number","type":["int","null"]},{"name":"favorite_color","type":["string","null"]}]}""" dict_content = { "name": u"Ben", "favorite_number": 7, "favorite_color": u"red" } with pytest.raises(TypeError) as e: encoded_message_content = await sr_avro_encoder.encode( dict_content, schema=schema_str, request_options={"fake_kwarg": True}) assert 'request() got an unexpected keyword' in str(e.value) encoded_message_content = await sr_avro_encoder.encode( dict_content, schema=schema_str) content_type = encoded_message_content["content_type"] encoded_content = encoded_message_content["content"] encoded_content_dict = { "content": encoded_content, "content_type": content_type } with pytest.raises(TypeError) as e: decoded_content = await sr_avro_encoder.decode( encoded_content_dict, request_options={"fake_kwarg": True}) assert 'request() got an unexpected keyword' in str(e.value)
async def test_parse_record_fields( self, schemaregistry_fully_qualified_namespace, schemaregistry_group, **kwargs): sr_client = self.create_client( fully_qualified_namespace=schemaregistry_fully_qualified_namespace) sr_avro_encoder = AvroEncoder(client=sr_client, group_name=schemaregistry_group, auto_register=True) schema_no_fields = """{ "name":"User", "namespace":"example.avro", "type":"record" }""" with pytest.raises(InvalidSchemaError): await sr_avro_encoder.encode({"name": u"Ben"}, schema=schema_no_fields) schema_wrong_type_fields = """{ "name":"User", "namespace":"example.avro", "type":"record" "fields": "hello" }""" with pytest.raises(InvalidSchemaError): await sr_avro_encoder.encode({"name": u"Ben"}, schema=schema_wrong_type_fields) schema_wrong_field_item_type = """{ "name":"User", "namespace":"example.avro", "type":"record" "fields": ["hello"] }""" with pytest.raises(InvalidSchemaError): await sr_avro_encoder.encode({"name": u"Ben"}, schema=schema_wrong_field_item_type) schema_record_field_no_name = """{ "name":"User", "namespace":"example.avro", "type":"record", "fields":[{"type":"string"}] }""" with pytest.raises(InvalidSchemaError): await sr_avro_encoder.encode({"name": u"Ben"}, schema=schema_record_field_no_name) schema_record_field_wrong_type_name = """{ "name":"User", "namespace":"example.avro", "type":"record", "fields":[{"name": 1, "type":"string"}] }""" with pytest.raises(InvalidSchemaError): await sr_avro_encoder.encode( {"name": u"Ben"}, schema=schema_record_field_wrong_type_name) schema_record_field_with_invalid_order = """{ "name":"User", "namespace":"example.avro.order", "type":"record", "fields":[{"name":"name","type":"string","order":"fake_order"}] }""" with pytest.raises(InvalidSchemaError): await sr_avro_encoder.encode( {"name": u"Ben"}, schema=schema_record_field_with_invalid_order) schema_record_duplicate_fields = """{ "name":"User", "namespace":"example.avro", "type":"record", "fields":[{"name":"name","type":"string"}, {"name":"name","type":"string"}] }""" with pytest.raises(InvalidSchemaError): await sr_avro_encoder.encode({"name": u"Ben"}, schema=schema_record_duplicate_fields) schema_field_type_invalid = """{ "name":"User", "namespace":"example.avro", "type":"record", "fields":[{"name":"name","type":1}] }""" with pytest.raises(InvalidSchemaError): await sr_avro_encoder.encode({"name": u"Ben"}, schema=schema_field_type_invalid)
async def test_parse_record_name(self, schemaregistry_fully_qualified_namespace, schemaregistry_group, **kwargs): sr_client = self.create_client( fully_qualified_namespace=schemaregistry_fully_qualified_namespace) sr_avro_encoder = AvroEncoder(client=sr_client, group_name=schemaregistry_group, auto_register=True) schema_name_has_dot = """{ "namespace": "thrownaway", "name":"User.avro", "type":"record", "fields":[{"name":"name","type":"string"}] }""" encoded_schema = await sr_avro_encoder.encode( {"name": u"Ben"}, schema=schema_name_has_dot) schema_id = encoded_schema["content_type"].split("+")[1] registered_schema = await sr_client.get_schema(schema_id) decoded_registered_schema = json.loads(registered_schema.definition) assert decoded_registered_schema["name"] == "User.avro" assert decoded_registered_schema["namespace"] == "thrownaway" schema_name_no_namespace = """{ "name":"User", "type":"record", "fields":[{"name":"name","type":"string"}] }""" encoded_schema = await sr_avro_encoder.encode( {"name": u"Ben"}, schema=schema_name_no_namespace) schema_id = encoded_schema["content_type"].split("+")[1] registered_schema = await sr_client.get_schema(schema_id) decoded_registered_schema = json.loads(registered_schema.definition) assert decoded_registered_schema["name"] == "User" assert "namespace" not in decoded_registered_schema schema_invalid_fullname = """{ "name":"abc", "type":"record", "namespace":"9example.avro", "fields":[{"name":"name","type":"string"}] }""" with pytest.raises(InvalidSchemaError): await sr_avro_encoder.encode({"name": u"Ben"}, schema=schema_invalid_fullname) schema_invalid_name_in_fullname = """{ "name":"1abc", "type":"record", "fields":[{"name":"name","type":"string"}] }""" with pytest.raises(InvalidSchemaError): await sr_avro_encoder.encode( {"name": u"Ben"}, schema=schema_invalid_name_in_fullname) schema_invalid_name_reserved_type = """{ "name":"record", "type":"record", "fields":[{"name":"name","type":"string"}] }""" with pytest.raises(InvalidSchemaError): await sr_avro_encoder.encode( {"name": u"Ben"}, schema=schema_invalid_name_reserved_type) schema_wrong_type_name = """{ "name":1, "type":"record", "namespace":"example.avro", "fields":[{"name":"name","type":"string"}] }""" with pytest.raises(InvalidSchemaError): await sr_avro_encoder.encode({"name": u"Ben"}, schema=schema_wrong_type_name) schema_no_name = """{ "namespace":"example.avro", "type":"record", "fields":[{"name":"name","type":"string"}] }""" with pytest.raises(InvalidSchemaError): await sr_avro_encoder.encode({"name": u"Ben"}, schema=schema_no_name)
async def test_basic_sr_avro_encoder_with_auto_register_schemas( self, schemaregistry_fully_qualified_namespace, schemaregistry_group, **kwargs): sr_client = self.create_client( fully_qualified_namespace=schemaregistry_fully_qualified_namespace) sr_avro_encoder = AvroEncoder(client=sr_client, group_name=schemaregistry_group, auto_register=True) async with sr_client: schema_str = """{"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_str = "{\"type\": \"record\", \"name\": \"User\", \"namespace\": \"example.avro\", \"fields\": [{\"type\": \"string\", \"name\": \"name\"}, {\"type\": [\"int\", \"null\"], \"name\": \"favorite_number\"}, {\"type\": [\"string\", \"null\"], \"name\": \"favorite_color\"}]}" schema = avro.schema.parse(schema_str) dict_content = { "name": u"Ben", "favorite_number": 7, "favorite_color": u"red" } encoded_message_content = await sr_avro_encoder.encode( dict_content, schema=schema_str) content_type = encoded_message_content["content_type"] encoded_content = encoded_message_content["content"] # wrong data type dict_content_bad = { "name": u"Ben", "favorite_number": 7, "favorite_color": 7 } with pytest.raises(InvalidContentError) as e: encoded_message_content = await sr_avro_encoder.encode( dict_content_bad, schema=schema_str) assert "schema_id" in e.value.details assert content_type.split("+")[0] == 'avro/binary' schema_properties = await sr_client.get_schema_properties( schemaregistry_group, schema.fullname, str(schema), "Avro") schema_id = schema_properties.id assert content_type.split("+")[1] == schema_id encoded_content_dict = { "content": encoded_content, "content_type": content_type } decoded_content = await sr_avro_encoder.decode(encoded_content_dict ) assert decoded_content["name"] == u"Ben" assert decoded_content["favorite_number"] == 7 assert decoded_content["favorite_color"] == u"red" # bad content type encoded_content_dict["content_type"] = 'a+b+c' with pytest.raises(InvalidContentError) as e: decoded_content = await sr_avro_encoder.decode( encoded_content_dict) # check that AvroEncoder won't work with message types that don't follow protocols class BadExample: def __init__(self, not_content): self.not_content = not_content with pytest.raises(TypeError) as e: await sr_avro_encoder.encode({"name": u"Ben"}, schema=schema_str, message_type=BadExample) assert "subtype of the MessageType" in (str(e.value)) bad_ex = BadExample('fake') with pytest.raises(TypeError) as e: await sr_avro_encoder.decode(message=bad_ex) assert "subtype of the MessageType" in (str(e.value)) # check that AvroEncoder will work with message types that follow protocols class GoodExample: def __init__(self, content, **kwargs): self.content = content self.content_type = None self.extra = kwargs.pop('extra', None) @classmethod def from_message_content(cls, content: bytes, content_type: str, **kwargs): ge = cls(content) ge.content_type = content_type return ge def __message_content__(self): return { "content": self.content, "content_type": self.content_type } good_ex_obj = await sr_avro_encoder.encode( dict_content, schema=schema_str, message_type=GoodExample, extra='val') decoded_content_obj = await sr_avro_encoder.decode( message=good_ex_obj) assert decoded_content_obj["name"] == u"Ben" assert decoded_content_obj["favorite_number"] == 7 assert decoded_content_obj["favorite_color"] == u"red"
async def test_basic_sr_avro_encoder_decode_readers_schema( self, schemaregistry_fully_qualified_namespace, schemaregistry_group, **kwargs): sr_client = self.create_client( fully_qualified_namespace=schemaregistry_fully_qualified_namespace) sr_avro_encoder = AvroEncoder(client=sr_client, group_name=schemaregistry_group, auto_register=True) schema_str = """{"namespace":"example.avro","type":"record","name":"User","fields":[{"name":"name","type":"string"},{"name":"favorite_number","type":["int","null"]},{"name":"favorite_color","type":["string","null"]}]}""" dict_content = { "name": u"Ben", "favorite_number": 7, "favorite_color": u"red" } encoded_message_content = await sr_avro_encoder.encode( dict_content, schema=schema_str) content_type = encoded_message_content["content_type"] encoded_content = encoded_message_content["content"] # readers_schema with removed field readers_schema_remove_field = """{"namespace":"example.avro","type":"record","name":"User","fields":[{"name":"name","type":"string"},{"name":"favorite_number","type":["int","null"]}]}""" encoded_content_dict = { "content": encoded_content, "content_type": content_type } decoded_content = await sr_avro_encoder.decode( encoded_content_dict, readers_schema=readers_schema_remove_field) assert decoded_content["name"] == u"Ben" assert decoded_content["favorite_number"] == 7 # readers_schema with extra field with default readers_schema_extra_field = """{"namespace":"example.avro","type":"record","name":"User","fields":[{"name":"name","type":"string"},{"name":"favorite_number","type":["int","null"]},{"name":"favorite_color","type":["string","null"]}, {"name":"favorite_city","type":["string","null"], "default": "Redmond"}]}""" encoded_content_dict = { "content": encoded_content, "content_type": content_type } decoded_content = await sr_avro_encoder.decode( encoded_content_dict, readers_schema=readers_schema_extra_field) assert decoded_content["name"] == u"Ben" assert decoded_content["favorite_number"] == 7 assert decoded_content["favorite_color"] == "red" assert decoded_content["favorite_city"] == "Redmond" # readers_schema with changed name results in error readers_schema_change_name = """{"namespace":"fakeexample.avro","type":"record","name":"fake_user","fields":[{"name":"name","type":"string"},{"name":"favorite_number","type":["int","null"]},{"name":"favorite_color","type":["string","null"]}]}""" with pytest.raises(InvalidSchemaError) as e: decoded_content = await sr_avro_encoder.decode( encoded_content_dict, readers_schema=readers_schema_change_name) assert "Incompatible schemas" in e.value.message assert "schema_id" in e.value.details assert "schema_definition" in e.value.details # invalid readers_schema invalid_schema = { "name": "User", "type": "record", "namespace": "example.avro", "fields": [{ "name": "name", "type": "string" }] } invalid_schema_string = "{}".format(invalid_schema) with pytest.raises(InvalidSchemaError) as e: decoded_content = await sr_avro_encoder.decode( encoded_content_dict, readers_schema=invalid_schema_string) assert "Invalid schema" in e.value.message assert "schema_id" in e.value.details assert "schema_definition" in e.value.details
"fields": [ {"name": "name", "type": "string"}, {"name": "favorite_number", "type": ["int", "null"]}, {"name": "favorite_color", "type": ["string", "null"]} ] }""" # create an EventHubProducerClient instance eventhub_producer = EventHubProducerClient.from_connection_string( conn_str=EVENTHUB_CONNECTION_STR, eventhub_name=EVENTHUB_NAME) # create a AvroEncoder instance azure_credential = DefaultAzureCredential() # create a AvroEncoder instance avro_encoder = AvroEncoder(client=SchemaRegistryClient( fully_qualified_namespace=SCHEMAREGISTRY_FULLY_QUALIFIED_NAMESPACE, credential=azure_credential), group_name=GROUP_NAME, auto_register=True) async def send_event_data_batch(producer, encoder): event_data_batch = await producer.create_batch() dict_content = { "name": "Bob", "favorite_number": 7, "favorite_color": "red" } # Use the encode method to convert dict object to bytes with the given avro schema and set body of EventData. # The encode method will automatically register the schema into the Schema Registry Service and # schema will be cached locally for future usage. event_data = await encoder.encode(content=dict_content,
async def test_basic_sr_avro_encoder_with_auto_register_schemas(self, schemaregistry_fully_qualified_namespace, schemaregistry_group, **kwargs): sr_client = self.create_client(schemaregistry_fully_qualified_namespace) sr_avro_encoder = AvroEncoder(client=sr_client, group_name=schemaregistry_group, auto_register_schemas=True) async with sr_client: schema_str = """{"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_str = "{\"type\": \"record\", \"name\": \"User\", \"namespace\": \"example.avro\", \"fields\": [{\"type\": \"string\", \"name\": \"name\"}, {\"type\": [\"int\", \"null\"], \"name\": \"favorite_number\"}, {\"type\": [\"string\", \"null\"], \"name\": \"favorite_color\"}]}" schema = avro.schema.parse(schema_str) dict_data = {"name": u"Ben", "favorite_number": 7, "favorite_color": u"red"} encoded_metadata = await sr_avro_encoder.encode(dict_data, schema=schema_str) content_type = encoded_metadata["content_type"] encoded_data = encoded_metadata["data"] assert content_type.split("+")[0] == 'avro/binary' schema_properties = await sr_client.get_schema_properties(schemaregistry_group, schema.fullname, str(schema), "Avro") schema_id = schema_properties.id assert content_type.split("+")[1] == schema_id encoded_data_dict = {"data": encoded_data, "content_type": content_type} decoded_data = await sr_avro_encoder.decode(encoded_data_dict) assert decoded_data["name"] == u"Ben" assert decoded_data["favorite_number"] == 7 assert decoded_data["favorite_color"] == u"red" # check that AvroEncoder won't work with message types that don't follow protocols class BadExample: def __init__(self, not_data): self.not_data = not_data with pytest.raises(SchemaEncodeError) as e: # caught avro SchemaParseError await sr_avro_encoder.encode({"name": u"Ben"}, schema=schema_str, message_type=BadExample) assert "subtype of the MessageType" in (str(e.value)) bad_ex = BadExample('fake') with pytest.raises(SchemaDecodeError) as e: # caught avro SchemaParseError await sr_avro_encoder.decode(message=bad_ex) assert "subtype of the MessageType" in (str(e.value)) # check that AvroEncoder will work with message types that follow protocols class GoodExample: def __init__(self, data: bytes, content_type: str, **kwargs): self.data = data self.content_type = content_type self.extra = kwargs.pop('extra', None) def __message_data__(self): return {"data": self.data, "content_type": self.content_type} def good_callback(data: bytes, content_type: str, **kwargs): return GoodExample(data, content_type, **kwargs) good_ex_obj = await sr_avro_encoder.encode(dict_data, schema=schema_str, message_type=GoodExample, extra='val') good_ex_callback = await sr_avro_encoder.encode(dict_data, schema=schema_str, message_type=good_callback, extra='val') decoded_data_obj = await sr_avro_encoder.decode(message=good_ex_obj) decoded_data_callback = await sr_avro_encoder.decode(message=good_ex_callback) assert decoded_data_obj["name"] == u"Ben" assert decoded_data_obj["favorite_number"] == 7 assert decoded_data_obj["favorite_color"] == u"red" assert decoded_data_callback["name"] == u"Ben" assert decoded_data_callback["favorite_number"] == 7 assert decoded_data_callback["favorite_color"] == u"red"