sdks/python/apache_beam/yaml/json_utils.py - beam - Git at Google

 #
 # Licensed to the Apache Software Foundation (ASF) under one or more
 # contributor license agreements.  See the NOTICE file distributed with
 # this work for additional information regarding copyright ownership.
 # The ASF licenses this file to You 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.
 #

 """Utilities for converting between JSON and Beam Schema'd data.

 For internal use, no backward compatibility guarantees.
 """

 import json
 from collections.abc import Callable
 from typing import Any
 from typing import Optional

 import jsonschema

 import apache_beam as beam
 from apache_beam.portability.api import schema_pb2
 from apache_beam.typehints import schemas

 JSON_ATOMIC_TYPES_TO_BEAM = {
     'boolean': schema_pb2.BOOLEAN,
     'integer': schema_pb2.INT64,
     'number': schema_pb2.DOUBLE,
     'string': schema_pb2.STRING,
     'bytes': schema_pb2.BYTES
 }

 BEAM_ATOMIC_TYPES_TO_JSON = {
     schema_pb2.INT16: 'integer',
     schema_pb2.INT32: 'integer',
     schema_pb2.FLOAT: 'number',
     **{
         v: k
         for k, v in JSON_ATOMIC_TYPES_TO_BEAM.items()
     }
 }


 def json_schema_to_beam_schema(
     json_schema: dict[str, Any]) -> schema_pb2.Schema:
   """Returns a Beam schema equivalent for the given Json schema."""
   def maybe_nullable(beam_type, nullable):
     if nullable:
       beam_type.nullable = True
     return beam_type

   json_type = json_schema.get('type', None)
   if json_type != 'object':
     raise ValueError('Expected object type, got {json_type}.')
   if 'properties' not in json_schema:
     # Technically this is a valid (vacuous) schema, but as it's not generally
     # meaningful, throw an informative error instead.
     # (We could add a flag to allow this degenerate case.)
     raise ValueError('Missing properties for {json_schema}.')
   required = set(json_schema.get('required', []))
   return schema_pb2.Schema(
       fields=[
           schemas.schema_field(
               name,
               maybe_nullable(json_type_to_beam_type(t), name not in required),
               description=t.get('description') if isinstance(t, dict) else None)
           for (name, t) in json_schema['properties'].items()
       ])


 def json_type_to_beam_type(json_type: dict[str, Any]) -> schema_pb2.FieldType:
   """Returns a Beam schema type for the given Json (schema) type."""
   if not isinstance(json_type, dict) or 'type' not in json_type:
     raise ValueError(f'Malformed type {json_type}.')
   type_name = json_type['type']
   if type_name in JSON_ATOMIC_TYPES_TO_BEAM:
     return schema_pb2.FieldType(
         atomic_type=JSON_ATOMIC_TYPES_TO_BEAM[type_name])
   elif type_name == 'array':
     return schema_pb2.FieldType(
         array_type=schema_pb2.ArrayType(
             element_type=json_type_to_beam_type(json_type['items'])))
   elif type_name == 'object':
     if 'properties' in json_type:
       return schema_pb2.FieldType(
           row_type=schema_pb2.RowType(
               schema=json_schema_to_beam_schema(json_type)))
     elif 'additionalProperties' in json_type:
       return schema_pb2.FieldType(
           map_type=schema_pb2.MapType(
               key_type=schema_pb2.FieldType(atomic_type=schema_pb2.STRING),
               value_type=json_type_to_beam_type(
                   json_type['additionalProperties'])))
     else:
       raise ValueError(
           f'Object type must have either properties or additionalProperties, '
           f'got {json_type}.')
   else:
     raise ValueError(f'Unable to convert {json_type} to a Beam schema.')


 def beam_schema_to_json_schema(
     beam_schema: schema_pb2.Schema) -> dict[str, Any]:
   return {
       'type': 'object',
       'properties': {
           field.name: beam_type_to_json_type(field.type)
           for field in beam_schema.fields
       },
       'additionalProperties': False
   }


 def beam_type_to_json_type(beam_type: schema_pb2.FieldType) -> dict[str, Any]:
   type_info = beam_type.WhichOneof("type_info")
   if type_info == "atomic_type":
     if beam_type.atomic_type in BEAM_ATOMIC_TYPES_TO_JSON:
       return {'type': BEAM_ATOMIC_TYPES_TO_JSON[beam_type.atomic_type]}
     else:
       return {}
   elif type_info == "array_type":
     return {
         'type': 'array',
         'items': beam_type_to_json_type(beam_type.array_type.element_type)
     }
   elif type_info == "iterable_type":
     return {
         'type': 'array',
         'items': beam_type_to_json_type(beam_type.iterable_type.element_type)
     }
   elif type_info == "map_type":
     return {
         'type': 'object',
         'properties': {
             '__line__': {
                 'type': 'integer'
             }, '__uuid__': {}
         },
         'additionalProperties': beam_type_to_json_type(
             beam_type.map_type.value_type)
     }
   elif type_info == "row_type":
     return {
         'type': 'object',
         'properties': {
             field.name: beam_type_to_json_type(field.type)
             for field in beam_type.row_type.schema.fields
         },
         'additionalProperties': False
     }
   else:
     return {}


 def json_to_row(beam_type: schema_pb2.FieldType) -> Callable[[Any], Any]:
   """Returns a callable converting Json objects to Beam rows of the given type.

   The input to the returned callable is expected to conform to the Json schema
   corresponding to this Beam type.
   """
   if beam_type.nullable:
     non_null_type = schema_pb2.FieldType()
     non_null_type.CopyFrom(beam_type)
     non_null_type.nullable = False
     non_null_converter = json_to_row(non_null_type)
     return lambda value: None if value is None else non_null_converter(value)

   type_info = beam_type.WhichOneof("type_info")
   if type_info == "atomic_type":
     return lambda value: value
   elif type_info == "array_type":
     element_converter = json_to_row(beam_type.array_type.element_type)
     return lambda value: [element_converter(e) for e in value]
   elif type_info == "iterable_type":
     element_converter = json_to_row(beam_type.iterable_type.element_type)
     return lambda value: [element_converter(e) for e in value]
   elif type_info == "map_type":
     if beam_type.map_type.key_type.atomic_type != schema_pb2.STRING:
       raise TypeError(
           f'Only strings allowd as map keys when converting from JSON, '
           f'found {beam_type}')
     value_converter = json_to_row(beam_type.map_type.value_type)
     return lambda value: {k: value_converter(v) for (k, v) in value.items()}
   elif type_info == "row_type":
     field_nullable_status = {
         field.name: field.type.nullable
         for field in beam_type.row_type.schema.fields
     }

     converters = {
         field.name: json_to_row(field.type)
         for field in beam_type.row_type.schema.fields
     }

     def convert_row(value):
       kwargs = {}
       for name, convert in converters.items():
         if name in value:
           kwargs[name] = convert(value[name])
         elif field_nullable_status[name]:
           kwargs[name] = convert(None)
         else:
           raise KeyError(f"Missing required field: {name}")
       return beam.Row(**kwargs)

     return convert_row
   elif type_info == "logical_type":
     return lambda value: value
   else:
     raise ValueError(f"Unrecognized type_info: {type_info!r}")


 def json_parser(
     beam_schema: schema_pb2.Schema,
     json_schema: Optional[dict[str,
                                Any]] = None) -> Callable[[bytes], beam.Row]:
   """Returns a callable converting Json strings to Beam rows of the given type.

   The input to the returned callable is expected to conform to the Json schema
   corresponding to this Beam type.
   """
   if json_schema is None:
     validate_fn = None
   else:
     cls = jsonschema.validators.validator_for(json_schema)
     cls.check_schema(json_schema)
     validate_fn = _PicklableFromConstructor(
         lambda: jsonschema.validators.validator_for(json_schema)
         (json_schema).validate)

   to_row = json_to_row(
       schema_pb2.FieldType(row_type=schema_pb2.RowType(schema=beam_schema)))

   def parse(s: bytes):
     o = json.loads(s)
     if validate_fn is not None:
       validate_fn(o)
     return to_row(o)

   return parse


 class _PicklableFromConstructor:
   def __init__(self, constructor):
     self._constructor = constructor
     self._value = None

   def __call__(self, o):
     if self._value is None:
       self._value = self._constructor()
     return self._value(o)

   def __getstate__(self):
     return {'_constructor': self._constructor, '_value': None}


 def row_to_json(beam_type: schema_pb2.FieldType) -> Callable[[Any], Any]:
   """Returns a callable converting rows of the given type to Json objects."""
   type_info = beam_type.WhichOneof("type_info")
   if type_info == "atomic_type":
     return lambda value: value
   elif type_info == "array_type":
     element_converter = row_to_json(beam_type.array_type.element_type)
     return lambda value: [element_converter(e) for e in value]
   elif type_info == "iterable_type":
     element_converter = row_to_json(beam_type.iterable_type.element_type)
     return lambda value: [element_converter(e) for e in value]
   elif type_info == "map_type":
     if beam_type.map_type.key_type.atomic_type != schema_pb2.STRING:
       raise TypeError(
           f'Only strings allowd as map keys when converting to JSON, '
           f'found {beam_type}')
     value_converter = row_to_json(beam_type.map_type.value_type)
     return lambda value: {k: value_converter(v) for (k, v) in value.items()}
   elif type_info == "row_type":
     converters = {
         field.name: row_to_json(field.type)
         for field in beam_type.row_type.schema.fields
     }
     return lambda row: {
         name: converted
         for (name, convert) in converters.items()
         # To filter out nullable fields in rows
         if (converted := convert(getattr(row, name, None))) is not None
     }
   elif type_info == "logical_type":
     return lambda value: value
   else:
     raise ValueError(f"Unrecognized type_info: {type_info!r}")


 def json_formater(
     beam_schema: schema_pb2.Schema) -> Callable[[beam.Row], bytes]:
   """Returns a callable converting rows of the given schema to Json strings."""
   convert = row_to_json(
       schema_pb2.FieldType(row_type=schema_pb2.RowType(schema=beam_schema)))
   return lambda row: json.dumps(convert(row), sort_keys=True).encode('utf-8')


 def _validate_compatible(weak_schema, strong_schema):
   if not weak_schema:
     return
   if weak_schema['type'] != strong_schema['type']:
     raise ValueError(
         'Incompatible types: %r vs %r' %
         (weak_schema['type'] != strong_schema['type']))
   if weak_schema['type'] == 'array':
     _validate_compatible(weak_schema['items'], strong_schema['items'])
   elif weak_schema == 'object':
     for required in strong_schema.get('required', []):
       if required not in weak_schema['properties']:
         raise ValueError('Missing or unkown property %r' % required)
     for name, spec in weak_schema.get('properties', {}):
       if name in strong_schema['properties']:
         try:
           _validate_compatible(spec, strong_schema['properties'][name])
         except Exception as exn:
           raise ValueError('Incompatible schema for %r' % name) from exn
       elif not strong_schema.get('additionalProperties'):
         raise ValueError(
             'Prohibited property: {property}; '
             'perhaps additionalProperties: False is missing?')


 def row_validator(beam_schema: schema_pb2.Schema,
                   json_schema: dict[str, Any]) -> Callable[[Any], Any]:
   """Returns a callable that will fail on elements not respecting json_schema.
   """
   if not json_schema:
     return lambda x: None

   # Validate that this compiles, but avoid pickling the validator itself.
   _ = jsonschema.validators.validator_for(json_schema)(json_schema)
   _validate_compatible(beam_schema_to_json_schema(beam_schema), json_schema)
   validator = None

   convert = row_to_json(
       schema_pb2.FieldType(row_type=schema_pb2.RowType(schema=beam_schema)))

   def validate(row):
     nonlocal validator
     if validator is None:
       validator = jsonschema.validators.validator_for(json_schema)(json_schema)
     # NOTE: A row like BeamSchema_...(name='Bob', score=None, age=25) needs to
     # have any fields that are None to be filtered out or the validator will
     # fail (e.g. {'age': 25, 'name': 'Bob'}).
     validator.validate(convert(row))

   return validate
	#
	# Licensed to the Apache Software Foundation (ASF) under one or more
	# contributor license agreements. See the NOTICE file distributed with
	# this work for additional information regarding copyright ownership.
	# The ASF licenses this file to You 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.
	#

	"""Utilities for converting between JSON and Beam Schema'd data.

	For internal use, no backward compatibility guarantees.
	"""

	import json
	from collections.abc import Callable
	from typing import Any
	from typing import Optional

	import jsonschema

	import apache_beam as beam
	from apache_beam.portability.api import schema_pb2
	from apache_beam.typehints import schemas

	JSON_ATOMIC_TYPES_TO_BEAM = {
	'boolean': schema_pb2.BOOLEAN,
	'integer': schema_pb2.INT64,
	'number': schema_pb2.DOUBLE,
	'string': schema_pb2.STRING,
	'bytes': schema_pb2.BYTES
	}

	BEAM_ATOMIC_TYPES_TO_JSON = {
	schema_pb2.INT16: 'integer',
	schema_pb2.INT32: 'integer',
	schema_pb2.FLOAT: 'number',
	**{
	v: k
	for k, v in JSON_ATOMIC_TYPES_TO_BEAM.items()
	}
	}


	def json_schema_to_beam_schema(
	json_schema: dict[str, Any]) -> schema_pb2.Schema:
	"""Returns a Beam schema equivalent for the given Json schema."""
	def maybe_nullable(beam_type, nullable):
	if nullable:
	beam_type.nullable = True
	return beam_type

	json_type = json_schema.get('type', None)
	if json_type != 'object':
	raise ValueError('Expected object type, got {json_type}.')
	if 'properties' not in json_schema:
	# Technically this is a valid (vacuous) schema, but as it's not generally
	# meaningful, throw an informative error instead.
	# (We could add a flag to allow this degenerate case.)
	raise ValueError('Missing properties for {json_schema}.')
	required = set(json_schema.get('required', []))
	return schema_pb2.Schema(
	fields=[
	schemas.schema_field(
	name,
	maybe_nullable(json_type_to_beam_type(t), name not in required),
	description=t.get('description') if isinstance(t, dict) else None)
	for (name, t) in json_schema['properties'].items()
	])


	def json_type_to_beam_type(json_type: dict[str, Any]) -> schema_pb2.FieldType:
	"""Returns a Beam schema type for the given Json (schema) type."""
	if not isinstance(json_type, dict) or 'type' not in json_type:
	raise ValueError(f'Malformed type {json_type}.')
	type_name = json_type['type']
	if type_name in JSON_ATOMIC_TYPES_TO_BEAM:
	return schema_pb2.FieldType(
	atomic_type=JSON_ATOMIC_TYPES_TO_BEAM[type_name])
	elif type_name == 'array':
	return schema_pb2.FieldType(
	array_type=schema_pb2.ArrayType(
	element_type=json_type_to_beam_type(json_type['items'])))
	elif type_name == 'object':
	if 'properties' in json_type:
	return schema_pb2.FieldType(
	row_type=schema_pb2.RowType(
	schema=json_schema_to_beam_schema(json_type)))
	elif 'additionalProperties' in json_type:
	return schema_pb2.FieldType(
	map_type=schema_pb2.MapType(
	key_type=schema_pb2.FieldType(atomic_type=schema_pb2.STRING),
	value_type=json_type_to_beam_type(
	json_type['additionalProperties'])))
	else:
	raise ValueError(
	f'Object type must have either properties or additionalProperties, '
	f'got {json_type}.')
	else:
	raise ValueError(f'Unable to convert {json_type} to a Beam schema.')


	def beam_schema_to_json_schema(
	beam_schema: schema_pb2.Schema) -> dict[str, Any]:
	return {
	'type': 'object',
	'properties': {
	field.name: beam_type_to_json_type(field.type)
	for field in beam_schema.fields
	},
	'additionalProperties': False
	}


	def beam_type_to_json_type(beam_type: schema_pb2.FieldType) -> dict[str, Any]:
	type_info = beam_type.WhichOneof("type_info")
	if type_info == "atomic_type":
	if beam_type.atomic_type in BEAM_ATOMIC_TYPES_TO_JSON:
	return {'type': BEAM_ATOMIC_TYPES_TO_JSON[beam_type.atomic_type]}
	else:
	return {}
	elif type_info == "array_type":
	return {
	'type': 'array',
	'items': beam_type_to_json_type(beam_type.array_type.element_type)
	}
	elif type_info == "iterable_type":
	return {
	'type': 'array',
	'items': beam_type_to_json_type(beam_type.iterable_type.element_type)
	}
	elif type_info == "map_type":
	return {
	'type': 'object',
	'properties': {
	'__line__': {
	'type': 'integer'
	}, '__uuid__': {}
	},
	'additionalProperties': beam_type_to_json_type(
	beam_type.map_type.value_type)
	}
	elif type_info == "row_type":
	return {
	'type': 'object',
	'properties': {
	field.name: beam_type_to_json_type(field.type)
	for field in beam_type.row_type.schema.fields
	},
	'additionalProperties': False
	}
	else:
	return {}


	def json_to_row(beam_type: schema_pb2.FieldType) -> Callable[[Any], Any]:
	"""Returns a callable converting Json objects to Beam rows of the given type.

	The input to the returned callable is expected to conform to the Json schema
	corresponding to this Beam type.
	"""
	if beam_type.nullable:
	non_null_type = schema_pb2.FieldType()
	non_null_type.CopyFrom(beam_type)
	non_null_type.nullable = False
	non_null_converter = json_to_row(non_null_type)
	return lambda value: None if value is None else non_null_converter(value)

	type_info = beam_type.WhichOneof("type_info")
	if type_info == "atomic_type":
	return lambda value: value
	elif type_info == "array_type":
	element_converter = json_to_row(beam_type.array_type.element_type)
	return lambda value: [element_converter(e) for e in value]
	elif type_info == "iterable_type":
	element_converter = json_to_row(beam_type.iterable_type.element_type)
	return lambda value: [element_converter(e) for e in value]
	elif type_info == "map_type":
	if beam_type.map_type.key_type.atomic_type != schema_pb2.STRING:
	raise TypeError(
	f'Only strings allowd as map keys when converting from JSON, '
	f'found {beam_type}')
	value_converter = json_to_row(beam_type.map_type.value_type)
	return lambda value: {k: value_converter(v) for (k, v) in value.items()}
	elif type_info == "row_type":
	field_nullable_status = {
	field.name: field.type.nullable
	for field in beam_type.row_type.schema.fields
	}

	converters = {
	field.name: json_to_row(field.type)
	for field in beam_type.row_type.schema.fields
	}

	def convert_row(value):
	kwargs = {}
	for name, convert in converters.items():
	if name in value:
	kwargs[name] = convert(value[name])
	elif field_nullable_status[name]:
	kwargs[name] = convert(None)
	else:
	raise KeyError(f"Missing required field: {name}")
	return beam.Row(**kwargs)

	return convert_row
	elif type_info == "logical_type":
	return lambda value: value
	else:
	raise ValueError(f"Unrecognized type_info: {type_info!r}")


	def json_parser(
	beam_schema: schema_pb2.Schema,
	json_schema: Optional[dict[str,
	Any]] = None) -> Callable[[bytes], beam.Row]:
	"""Returns a callable converting Json strings to Beam rows of the given type.

	The input to the returned callable is expected to conform to the Json schema
	corresponding to this Beam type.
	"""
	if json_schema is None:
	validate_fn = None
	else:
	cls = jsonschema.validators.validator_for(json_schema)
	cls.check_schema(json_schema)
	validate_fn = _PicklableFromConstructor(
	lambda: jsonschema.validators.validator_for(json_schema)
	(json_schema).validate)

	to_row = json_to_row(
	schema_pb2.FieldType(row_type=schema_pb2.RowType(schema=beam_schema)))

	def parse(s: bytes):
	o = json.loads(s)
	if validate_fn is not None:
	validate_fn(o)
	return to_row(o)

	return parse


	class _PicklableFromConstructor:
	def __init__(self, constructor):
	self._constructor = constructor
	self._value = None

	def __call__(self, o):
	if self._value is None:
	self._value = self._constructor()
	return self._value(o)

	def __getstate__(self):
	return {'_constructor': self._constructor, '_value': None}


	def row_to_json(beam_type: schema_pb2.FieldType) -> Callable[[Any], Any]:
	"""Returns a callable converting rows of the given type to Json objects."""
	type_info = beam_type.WhichOneof("type_info")
	if type_info == "atomic_type":
	return lambda value: value
	elif type_info == "array_type":
	element_converter = row_to_json(beam_type.array_type.element_type)
	return lambda value: [element_converter(e) for e in value]
	elif type_info == "iterable_type":
	element_converter = row_to_json(beam_type.iterable_type.element_type)
	return lambda value: [element_converter(e) for e in value]
	elif type_info == "map_type":
	if beam_type.map_type.key_type.atomic_type != schema_pb2.STRING:
	raise TypeError(
	f'Only strings allowd as map keys when converting to JSON, '
	f'found {beam_type}')
	value_converter = row_to_json(beam_type.map_type.value_type)
	return lambda value: {k: value_converter(v) for (k, v) in value.items()}
	elif type_info == "row_type":
	converters = {
	field.name: row_to_json(field.type)
	for field in beam_type.row_type.schema.fields
	}
	return lambda row: {
	name: converted
	for (name, convert) in converters.items()
	# To filter out nullable fields in rows
	if (converted := convert(getattr(row, name, None))) is not None
	}
	elif type_info == "logical_type":
	return lambda value: value
	else:
	raise ValueError(f"Unrecognized type_info: {type_info!r}")


	def json_formater(
	beam_schema: schema_pb2.Schema) -> Callable[[beam.Row], bytes]:
	"""Returns a callable converting rows of the given schema to Json strings."""
	convert = row_to_json(
	schema_pb2.FieldType(row_type=schema_pb2.RowType(schema=beam_schema)))
	return lambda row: json.dumps(convert(row), sort_keys=True).encode('utf-8')


	def _validate_compatible(weak_schema, strong_schema):
	if not weak_schema:
	return
	if weak_schema['type'] != strong_schema['type']:
	raise ValueError(
	'Incompatible types: %r vs %r' %
	(weak_schema['type'] != strong_schema['type']))
	if weak_schema['type'] == 'array':
	_validate_compatible(weak_schema['items'], strong_schema['items'])
	elif weak_schema == 'object':
	for required in strong_schema.get('required', []):
	if required not in weak_schema['properties']:
	raise ValueError('Missing or unkown property %r' % required)
	for name, spec in weak_schema.get('properties', {}):
	if name in strong_schema['properties']:
	try:
	_validate_compatible(spec, strong_schema['properties'][name])
	except Exception as exn:
	raise ValueError('Incompatible schema for %r' % name) from exn
	elif not strong_schema.get('additionalProperties'):
	raise ValueError(
	'Prohibited property: {property}; '
	'perhaps additionalProperties: False is missing?')


	def row_validator(beam_schema: schema_pb2.Schema,
	json_schema: dict[str, Any]) -> Callable[[Any], Any]:
	"""Returns a callable that will fail on elements not respecting json_schema.
	"""
	if not json_schema:
	return lambda x: None

	# Validate that this compiles, but avoid pickling the validator itself.
	_ = jsonschema.validators.validator_for(json_schema)(json_schema)
	_validate_compatible(beam_schema_to_json_schema(beam_schema), json_schema)
	validator = None

	convert = row_to_json(
	schema_pb2.FieldType(row_type=schema_pb2.RowType(schema=beam_schema)))

	def validate(row):
	nonlocal validator
	if validator is None:
	validator = jsonschema.validators.validator_for(json_schema)(json_schema)
	# NOTE: A row like BeamSchema_...(name='Bob', score=None, age=25) needs to
	# have any fields that are None to be filtered out or the validator will
	# fail (e.g. {'age': 25, 'name': 'Bob'}).
	validator.validate(convert(row))

	return validate