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"