Source code for confluent_kafka.schema_registry.json_schema

#!/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

import json
import struct

from jsonschema import validate, ValidationError, RefResolver

from confluent_kafka.schema_registry import (_MAGIC_BYTE,
                                             Schema,
                                             topic_subject_name_strategy)
from confluent_kafka.serialization import (SerializationError,
                                           Deserializer,
                                           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 _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)
            referenced_schema_dict = json.loads(referenced_schema.schema.schema_str)
            named_schemas[ref.name] = referenced_schema_dict
    return named_schemas


[docs]class JSONSerializer(Serializer): """ Serializer that outputs JSON 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. | | | | | | | | Raises SchemaRegistryError if the schema was not | | | | registered against the subject, or could not be | | | | successfully registered. | +---------------------------+----------+----------------------------------------------------+ | | | 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. Notes: The ``title`` annotation, referred to elsewhere as a record name is not strictly required by the JSON Schema specification. It is however required by this serializer in order to register the schema with Confluent Schema Registry. Prior to serialization, all objects must first be converted to a dict instance. This may be handled manually prior to calling :py:func:`Producer.produce()` or by registering a `to_dict` callable with JSONSerializer. Args: schema_str (str, Schema): `JSON Schema definition. <https://json-schema.org/understanding-json-schema/reference/generic.html>`_ Accepts schema as either a string or a :py:class:`Schema` instance. Note that string definitions cannot reference other schemas. For referencing other schemas, use a :py:class:`Schema` instance. schema_registry_client (SchemaRegistryClient): Schema Registry client instance. to_dict (callable, optional): Callable(object, SerializationContext) -> dict. Converts object to a dict. conf (dict): JsonSerializer 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', '_are_references_provided'] _default_conf = {'auto.register.schemas': True, 'normalize.schemas': False, 'use.latest.version': False, 'subject.name.strategy': topic_subject_name_strategy} def __init__(self, schema_str, schema_registry_client, to_dict=None, conf=None): self._are_references_provided = False if isinstance(schema_str, str): self._schema = Schema(schema_str, schema_type="JSON") elif isinstance(schema_str, Schema): self._schema = schema_str self._are_references_provided = bool(schema_str.references) else: raise TypeError('You must pass either str or Schema') 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 = json.loads(self._schema.schema_str) schema_name = schema_dict.get('title', None) if schema_name is None: raise ValueError("Missing required JSON schema annotation title") self._schema_name = schema_name self._parsed_schema = schema_dict
[docs] def __call__(self, obj, ctx): """ Serializes an object to JSON, prepending it with Confluent Schema Registry framing. Args: obj (object): The object instance to serialize. ctx (SerializationContext): Metadata relevant to the serialization operation. Raises: SerializerError if any error occurs serializing obj. Returns: bytes: None if obj is None, else a byte array containing the JSON serialized data with Confluent Schema Registry framing. """ 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 try: if self._are_references_provided: named_schemas = _resolve_named_schema(self._schema, self._registry) validate(instance=value, schema=self._parsed_schema, resolver=RefResolver(self._parsed_schema.get('$id'), self._parsed_schema, store=named_schemas)) else: validate(instance=value, schema=self._parsed_schema) except ValidationError as ve: raise SerializationError(ve.message) with _ContextStringIO() as fo: # Write the magic byte and schema ID in network byte order (big endian) fo.write(struct.pack('>bI', _MAGIC_BYTE, self._schema_id)) # JSON dump always writes a str never bytes # https://docs.python.org/3/library/json.html fo.write(json.dumps(value).encode('utf8')) return fo.getvalue()
[docs]class JSONDeserializer(Deserializer): """ Deserializer for JSON encoded data with Confluent Schema Registry framing. Args: schema_str (str, Schema): `JSON schema definition <https://json-schema.org/understanding-json-schema/reference/generic.html>`_ Accepts schema as either a string or a :py:class:`Schema` instance. Note that string definitions cannot reference other schemas. For referencing other schemas, use a :py:class:`Schema` instance. from_dict (callable, optional): Callable(dict, SerializationContext) -> object. Converts a dict to a Python object instance. schema_registry_client (SchemaRegistryClient, optional): Schema Registry client instance. Needed if ``schema_str`` is a schema referencing other schemas. """ # noqa: E501 __slots__ = ['_parsed_schema', '_from_dict', '_registry', '_are_references_provided', '_schema'] def __init__(self, schema_str, from_dict=None, schema_registry_client=None): self._are_references_provided = False if isinstance(schema_str, str): schema = Schema(schema_str, schema_type="JSON") elif isinstance(schema_str, Schema): schema = schema_str self._are_references_provided = bool(schema_str.references) if self._are_references_provided and schema_registry_client is None: raise ValueError( """schema_registry_client must be provided if "schema_str" is a Schema instance with references""") else: raise TypeError('You must pass either str or Schema') self._parsed_schema = json.loads(schema.schema_str) self._schema = schema self._registry = schema_registry_client if from_dict is not None and not callable(from_dict): raise ValueError("from_dict must be callable with the signature" " from_dict(dict, SerializationContext) -> object") self._from_dict = from_dict
[docs] def __call__(self, data, ctx): """ Deserialize a JSON encoded record with Confluent Schema Registry framing to a dict, or object instance according to from_dict if from_dict is specified. Args: data (bytes): A JSON serialized record with Confluent Schema Regsitry framing. ctx (SerializationContext): Metadata relevant to the serialization operation. Returns: A dict, or object instance according to from_dict if from_dict is specified. Raises: SerializerError: If there was an error reading the Confluent framing data, or if ``data`` was not successfully validated with the configured schema. """ 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 = struct.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)) # JSON documents are self-describing; no need to query schema obj_dict = json.loads(payload.read()) try: if self._are_references_provided: named_schemas = _resolve_named_schema(self._schema, self._registry) validate(instance=obj_dict, schema=self._parsed_schema, resolver=RefResolver(self._parsed_schema.get('$id'), self._parsed_schema, store=named_schemas)) else: validate(instance=obj_dict, schema=self._parsed_schema) except ValidationError as ve: raise SerializationError(ve.message) if self._from_dict is not None: return self._from_dict(obj_dict, ctx) return obj_dict