#!/usr/bin/env python
# -*- coding: utf-8 -*-
#
# Copyright 2020 Confluent Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from io import BytesIO
from json import loads
from struct import pack, unpack
from fastavro import (parse_schema,
schemaless_reader,
schemaless_writer)
from . import (_MAGIC_BYTE,
Schema,
topic_subject_name_strategy)
from confluent_kafka.serialization import (Deserializer,
SerializationError,
Serializer)
class _ContextStringIO(BytesIO):
"""
Wrapper to allow use of StringIO via 'with' constructs.
"""
def __enter__(self):
return self
def __exit__(self, *args):
self.close()
return False
def _schema_loads(schema_str):
"""
Instantiate a Schema instance from a declaration string.
Args:
schema_str (str): Avro Schema declaration.
.. _Schema declaration:
https://avro.apache.org/docs/current/spec.html#schemas
Returns:
Schema: A Schema instance.
"""
schema_str = schema_str.strip()
# canonical form primitive declarations are not supported
if schema_str[0] != "{" and schema_str[0] != "[":
schema_str = '{"type":' + schema_str + '}'
return Schema(schema_str, schema_type='AVRO')
def _resolve_named_schema(schema, schema_registry_client, named_schemas=None):
"""
Resolves named schemas referenced by the provided schema recursively.
:param schema: Schema to resolve named schemas for.
:param schema_registry_client: SchemaRegistryClient to use for retrieval.
:param named_schemas: Dict of named schemas resolved recursively.
:return: named_schemas dict.
"""
if named_schemas is None:
named_schemas = {}
if schema.references is not None:
for ref in schema.references:
referenced_schema = schema_registry_client.get_version(ref.subject, ref.version)
_resolve_named_schema(referenced_schema.schema, schema_registry_client, named_schemas)
parse_schema(loads(referenced_schema.schema.schema_str), named_schemas=named_schemas)
return named_schemas
[docs]class AvroSerializer(Serializer):
"""
Serializer that outputs Avro binary encoded data with Confluent Schema Registry framing.
Configuration properties:
+---------------------------+----------+--------------------------------------------------+
| Property Name | Type | Description |
+===========================+==========+==================================================+
| | | If True, automatically register the configured |
| ``auto.register.schemas`` | bool | schema with Confluent Schema Registry if it has |
| | | not previously been associated with the relevant |
| | | subject (determined via subject.name.strategy). |
| | | |
| | | Defaults to True. |
+---------------------------+----------+--------------------------------------------------+
| | | Whether to normalize schemas, which will |
| ``normalize.schemas`` | bool | transform schemas to have a consistent format, |
| | | including ordering properties and references. |
+---------------------------+----------+--------------------------------------------------+
| | | Whether to use the latest subject version for |
| ``use.latest.version`` | bool | serialization. |
| | | |
| | | WARNING: There is no check that the latest |
| | | schema is backwards compatible with the object |
| | | being serialized. |
| | | |
| | | Defaults to False. |
+---------------------------+----------+--------------------------------------------------+
| | | Callable(SerializationContext, str) -> str |
| | | |
| ``subject.name.strategy`` | callable | Defines how Schema Registry subject names are |
| | | constructed. Standard naming strategies are |
| | | defined in the confluent_kafka.schema_registry |
| | | namespace. |
| | | |
| | | Defaults to topic_subject_name_strategy. |
+---------------------------+----------+--------------------------------------------------+
Schemas are registered against subject names in Confluent Schema Registry that
define a scope in which the schemas can be evolved. By default, the subject name
is formed by concatenating the topic name with the message field (key or value)
separated by a hyphen.
i.e. {topic name}-{message field}
Alternative naming strategies may be configured with the property
``subject.name.strategy``.
Supported subject name strategies:
+--------------------------------------+------------------------------+
| Subject Name Strategy | Output Format |
+======================================+==============================+
| topic_subject_name_strategy(default) | {topic name}-{message field} |
+--------------------------------------+------------------------------+
| topic_record_subject_name_strategy | {topic name}-{record name} |
+--------------------------------------+------------------------------+
| record_subject_name_strategy | {record name} |
+--------------------------------------+------------------------------+
See `Subject name strategy <https://docs.confluent.io/current/schema-registry/serializer-formatter.html#subject-name-strategy>`_ for additional details.
Note:
Prior to serialization, all values must first be converted to
a dict instance. This may handled manually prior to calling
:py:func:`Producer.produce()` or by registering a `to_dict`
callable with AvroSerializer.
See ``avro_producer.py`` in the examples directory for example usage.
Note:
Tuple notation can be used to determine which branch of an ambiguous union to take.
See `fastavro notation <https://fastavro.readthedocs.io/en/latest/writer.html#using-the-tuple-notation-to-specify-which-branch-of-a-union-to-take>`_
Args:
schema_registry_client (SchemaRegistryClient): Schema Registry client instance.
schema_str (str or Schema): Avro `Schema Declaration. <https://avro.apache.org/docs/current/spec.html#schemas>`_ Accepts either a string or a `Schema`(Schema) instance. Note that string definitions cannot reference other schemas. For referencing other schemas, use a Schema instance.
to_dict (callable, optional): Callable(object, SerializationContext) -> dict. Converts object to a dict.
conf (dict): AvroSerializer configuration.
""" # noqa: E501
__slots__ = ['_hash', '_auto_register', '_normalize_schemas', '_use_latest_version',
'_known_subjects', '_parsed_schema',
'_registry', '_schema', '_schema_id', '_schema_name',
'_subject_name_func', '_to_dict', '_named_schemas']
_default_conf = {'auto.register.schemas': True,
'normalize.schemas': False,
'use.latest.version': False,
'subject.name.strategy': topic_subject_name_strategy}
def __init__(self, schema_registry_client, schema_str, to_dict=None, conf=None):
if isinstance(schema_str, str):
schema = _schema_loads(schema_str)
elif isinstance(schema_str, Schema):
schema = schema_str
else:
raise TypeError('You must pass either schema string or schema object')
self._registry = schema_registry_client
self._schema_id = None
self._known_subjects = set()
if to_dict is not None and not callable(to_dict):
raise ValueError("to_dict must be callable with the signature "
"to_dict(object, SerializationContext)->dict")
self._to_dict = to_dict
conf_copy = self._default_conf.copy()
if conf is not None:
conf_copy.update(conf)
self._auto_register = conf_copy.pop('auto.register.schemas')
if not isinstance(self._auto_register, bool):
raise ValueError("auto.register.schemas must be a boolean value")
self._normalize_schemas = conf_copy.pop('normalize.schemas')
if not isinstance(self._normalize_schemas, bool):
raise ValueError("normalize.schemas must be a boolean value")
self._use_latest_version = conf_copy.pop('use.latest.version')
if not isinstance(self._use_latest_version, bool):
raise ValueError("use.latest.version must be a boolean value")
if self._use_latest_version and self._auto_register:
raise ValueError("cannot enable both use.latest.version and auto.register.schemas")
self._subject_name_func = conf_copy.pop('subject.name.strategy')
if not callable(self._subject_name_func):
raise ValueError("subject.name.strategy must be callable")
if len(conf_copy) > 0:
raise ValueError("Unrecognized properties: {}"
.format(", ".join(conf_copy.keys())))
schema_dict = loads(schema.schema_str)
self._named_schemas = _resolve_named_schema(schema, schema_registry_client)
parsed_schema = parse_schema(schema_dict, named_schemas=self._named_schemas)
if isinstance(parsed_schema, list):
# if parsed_schema is a list, we have an Avro union and there
# is no valid schema name. This is fine because the only use of
# schema_name is for supplying the subject name to the registry
# and union types should use topic_subject_name_strategy, which
# just discards the schema name anyway
schema_name = None
else:
# The Avro spec states primitives have a name equal to their type
# i.e. {"type": "string"} has a name of string.
# This function does not comply.
# https://github.com/fastavro/fastavro/issues/415
schema_name = parsed_schema.get("name", schema_dict["type"])
self._schema = schema
self._schema_name = schema_name
self._parsed_schema = parsed_schema
[docs] def __call__(self, obj, ctx):
"""
Serializes an object to Avro binary format, prepending it with Confluent
Schema Registry framing.
Args:
obj (object): The object instance to serialize.
ctx (SerializationContext): Metadata pertaining to the serialization operation.
Raises:
SerializerError: If any error occurs serializing obj.
SchemaRegistryError: If there was an error registering the schema with
Schema Registry, or auto.register.schemas is
false and the schema was not registered.
Returns:
bytes: Confluent Schema Registry encoded Avro bytes
"""
if obj is None:
return None
subject = self._subject_name_func(ctx, self._schema_name)
if subject not in self._known_subjects:
if self._use_latest_version:
latest_schema = self._registry.get_latest_version(subject)
self._schema_id = latest_schema.schema_id
else:
# Check to ensure this schema has been registered under subject_name.
if self._auto_register:
# The schema name will always be the same. We can't however register
# a schema without a subject so we set the schema_id here to handle
# the initial registration.
self._schema_id = self._registry.register_schema(subject,
self._schema,
self._normalize_schemas)
else:
registered_schema = self._registry.lookup_schema(subject,
self._schema,
self._normalize_schemas)
self._schema_id = registered_schema.schema_id
self._known_subjects.add(subject)
if self._to_dict is not None:
value = self._to_dict(obj, ctx)
else:
value = obj
with _ContextStringIO() as fo:
# Write the magic byte and schema ID in network byte order (big endian)
fo.write(pack('>bI', _MAGIC_BYTE, self._schema_id))
# write the record to the rest of the buffer
schemaless_writer(fo, self._parsed_schema, value)
return fo.getvalue()
[docs]class AvroDeserializer(Deserializer):
"""
Deserializer for Avro binary encoded data with Confluent Schema Registry
framing.
Note:
By default, Avro complex types are returned as dicts. This behavior can
be overriden by registering a callable ``from_dict`` with the deserializer to
convert the dicts to the desired type.
See ``avro_consumer.py`` in the examples directory in the examples
directory for example usage.
Args:
schema_registry_client (SchemaRegistryClient): Confluent Schema Registry
client instance.
schema_str (str, Schema, optional): Avro reader schema declaration Accepts either a string or a `Schema`(
Schema) instance. If not provided, the writer schema will be used as the reader schema. Note that string
definitions cannot reference other schemas. For referencing other schemas, use a Schema instance.
from_dict (callable, optional): Callable(dict, SerializationContext) -> object.
Converts a dict to an instance of some object.
return_record_name (bool): If True, when reading a union of records, the result will
be a tuple where the first value is the name of the record and the second value is
the record itself. Defaults to False.
See Also:
`Apache Avro Schema Declaration <https://avro.apache.org/docs/current/spec.html#schemas>`_
`Apache Avro Schema Resolution <https://avro.apache.org/docs/1.8.2/spec.html#Schema+Resolution>`_
"""
__slots__ = ['_reader_schema', '_registry', '_from_dict', '_writer_schemas', '_return_record_name', '_schema',
'_named_schemas']
def __init__(self, schema_registry_client, schema_str=None, from_dict=None, return_record_name=False):
schema = None
if schema_str is not None:
if isinstance(schema_str, str):
schema = _schema_loads(schema_str)
elif isinstance(schema_str, Schema):
schema = schema_str
else:
raise TypeError('You must pass either schema string or schema object')
self._schema = schema
self._registry = schema_registry_client
self._writer_schemas = {}
if schema:
schema_dict = loads(self._schema.schema_str)
self._named_schemas = _resolve_named_schema(self._schema, schema_registry_client)
self._reader_schema = parse_schema(schema_dict,
named_schemas=self._named_schemas)
else:
self._named_schemas = None
self._reader_schema = None
if from_dict is not None and not callable(from_dict):
raise ValueError("from_dict must be callable with the signature "
"from_dict(SerializationContext, dict) -> object")
self._from_dict = from_dict
self._return_record_name = return_record_name
if not isinstance(self._return_record_name, bool):
raise ValueError("return_record_name must be a boolean value")
[docs] def __call__(self, data, ctx):
"""
Deserialize Avro binary encoded data with Confluent Schema Registry framing to
a dict, or object instance according to from_dict, if specified.
Arguments:
data (bytes): bytes
ctx (SerializationContext): Metadata relevant to the serialization
operation.
Raises:
SerializerError: if an error occurs parsing data.
Returns:
object: If data is None, then None. Else, a dict, or object instance according
to from_dict, if specified.
""" # noqa: E501
if data is None:
return None
if len(data) <= 5:
raise SerializationError("Expecting data framing of length 6 bytes or "
"more but total data size is {} bytes. This "
"message was not produced with a Confluent "
"Schema Registry serializer".format(len(data)))
with _ContextStringIO(data) as payload:
magic, schema_id = unpack('>bI', payload.read(5))
if magic != _MAGIC_BYTE:
raise SerializationError("Unexpected magic byte {}. This message "
"was not produced with a Confluent "
"Schema Registry serializer".format(magic))
writer_schema = self._writer_schemas.get(schema_id, None)
if writer_schema is None:
registered_schema = self._registry.get_schema(schema_id)
self._named_schemas = _resolve_named_schema(registered_schema, self._registry)
prepared_schema = _schema_loads(registered_schema.schema_str)
writer_schema = parse_schema(loads(
prepared_schema.schema_str), named_schemas=self._named_schemas)
self._writer_schemas[schema_id] = writer_schema
obj_dict = schemaless_reader(payload,
writer_schema,
self._reader_schema,
self._return_record_name)
if self._from_dict is not None:
return self._from_dict(obj_dict, ctx)
return obj_dict