#
# 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.
#
# pytype: skip-file
import itertools
from array import array
from apache_beam.coders import typecoders
from apache_beam.coders.coder_impl import StreamCoderImpl
from apache_beam.coders.coders import BooleanCoder
from apache_beam.coders.coders import BytesCoder
from apache_beam.coders.coders import Coder
from apache_beam.coders.coders import FastCoder
from apache_beam.coders.coders import FloatCoder
from apache_beam.coders.coders import IterableCoder
from apache_beam.coders.coders import MapCoder
from apache_beam.coders.coders import NullableCoder
from apache_beam.coders.coders import StrUtf8Coder
from apache_beam.coders.coders import TupleCoder
from apache_beam.coders.coders import VarIntCoder
from apache_beam.portability import common_urns
from apache_beam.portability.api import schema_pb2
from apache_beam.typehints import row_type
from apache_beam.typehints.schemas import PYTHON_ANY_URN
from apache_beam.typehints.schemas import LogicalType
from apache_beam.typehints.schemas import named_tuple_from_schema
from apache_beam.typehints.schemas import schema_from_element_type
from apache_beam.utils import proto_utils
__all__ = ["RowCoder"]
[docs]class RowCoder(FastCoder):
""" Coder for `typing.NamedTuple` instances.
Implements the beam:coder:row:v1 standard coder spec.
"""
def __init__(self, schema):
"""Initializes a :class:`RowCoder`.
Args:
schema (apache_beam.portability.api.schema_pb2.Schema): The protobuf
representation of the schema of the data that the RowCoder will be used
to encode/decode.
"""
self.schema = schema
# Use non-null coders because null values are represented separately
self.components = [
_nonnull_coder_from_type(field.type) for field in self.schema.fields
]
def _create_impl(self):
return RowCoderImpl(self.schema, self.components)
[docs] def is_deterministic(self):
return all(c.is_deterministic() for c in self.components)
[docs] def to_type_hint(self):
return named_tuple_from_schema(self.schema)
def __hash__(self):
return hash(self.schema.SerializeToString())
def __eq__(self, other):
return type(self) == type(other) and self.schema == other.schema
[docs] def to_runner_api_parameter(self, unused_context):
return (common_urns.coders.ROW.urn, self.schema, [])
[docs] @staticmethod
@Coder.register_urn(common_urns.coders.ROW.urn, schema_pb2.Schema)
def from_runner_api_parameter(schema, components, unused_context):
return RowCoder(schema)
[docs] @staticmethod
def from_type_hint(type_hint, registry):
schema = schema_from_element_type(type_hint)
return RowCoder(schema)
[docs] @staticmethod
def from_payload(payload):
# type: (bytes) -> RowCoder
return RowCoder(proto_utils.parse_Bytes(payload, schema_pb2.Schema))
def __reduce__(self):
# when pickling, use bytes representation of the schema. schema_pb2.Schema
# objects cannot be pickled.
return (RowCoder.from_payload, (self.schema.SerializeToString(), ))
typecoders.registry.register_coder(row_type.RowTypeConstraint, RowCoder)
def _coder_from_type(field_type):
coder = _nonnull_coder_from_type(field_type)
if field_type.nullable:
return NullableCoder(coder)
else:
return coder
def _nonnull_coder_from_type(field_type):
type_info = field_type.WhichOneof("type_info")
if type_info == "atomic_type":
if field_type.atomic_type in (schema_pb2.INT32, schema_pb2.INT64):
return VarIntCoder()
elif field_type.atomic_type == schema_pb2.DOUBLE:
return FloatCoder()
elif field_type.atomic_type == schema_pb2.STRING:
return StrUtf8Coder()
elif field_type.atomic_type == schema_pb2.BOOLEAN:
return BooleanCoder()
elif field_type.atomic_type == schema_pb2.BYTES:
return BytesCoder()
elif type_info == "array_type":
return IterableCoder(_coder_from_type(field_type.array_type.element_type))
elif type_info == "map_type":
return MapCoder(
_coder_from_type(field_type.map_type.key_type),
_coder_from_type(field_type.map_type.value_type))
elif type_info == "logical_type":
# Special case for the Any logical type. Just use the default coder for an
# unknown Python object.
if field_type.logical_type.urn == PYTHON_ANY_URN:
return typecoders.registry.get_coder(object)
logical_type = LogicalType.from_runner_api(field_type.logical_type)
return LogicalTypeCoder(
logical_type, _coder_from_type(field_type.logical_type.representation))
elif type_info == "row_type":
return RowCoder(field_type.row_type.schema)
# The Java SDK supports several more types, but the coders are not yet
# standard, and are not implemented in Python.
raise ValueError(
"Encountered a type that is not currently supported by RowCoder: %s" %
field_type)
class RowCoderImpl(StreamCoderImpl):
"""For internal use only; no backwards-compatibility guarantees."""
SIZE_CODER = VarIntCoder().get_impl()
NULL_MARKER_CODER = BytesCoder().get_impl()
def __init__(self, schema, components):
self.schema = schema
self.constructor = named_tuple_from_schema(schema)
self.components = list(c.get_impl() for c in components)
self.has_nullable_fields = any(
field.type.nullable for field in self.schema.fields)
def encode_to_stream(self, value, out, nested):
nvals = len(self.schema.fields)
self.SIZE_CODER.encode_to_stream(nvals, out, True)
attrs = [getattr(value, f.name) for f in self.schema.fields]
words = array('B')
if self.has_nullable_fields:
nulls = list(attr is None for attr in attrs)
if any(nulls):
words = array('B', itertools.repeat(0, (nvals + 7) // 8))
for i, is_null in enumerate(nulls):
words[i // 8] |= is_null << (i % 8)
self.NULL_MARKER_CODER.encode_to_stream(words.tostring(), out, True)
for c, field, attr in zip(self.components, self.schema.fields, attrs):
if attr is None:
if not field.type.nullable:
raise ValueError(
"Attempted to encode null for non-nullable field \"{}\".".format(
field.name))
continue
c.encode_to_stream(attr, out, True)
def decode_from_stream(self, in_stream, nested):
nvals = self.SIZE_CODER.decode_from_stream(in_stream, True)
words = array('B')
words.fromstring(self.NULL_MARKER_CODER.decode_from_stream(in_stream, True))
if words:
nulls = ((words[i // 8] >> (i % 8)) & 0x01 for i in range(nvals))
else:
nulls = itertools.repeat(False, nvals)
# If this coder's schema has more attributes than the encoded value, then
# the schema must have changed. Populate the unencoded fields with nulls.
if len(self.components) > nvals:
nulls = itertools.chain(
nulls, itertools.repeat(True, len(self.components) - nvals))
# Note that if this coder's schema has *fewer* attributes than the encoded
# value, we just need to ignore the additional values, which will occur
# here because we only decode as many values as we have coders for.
return self.constructor(
*(
None if is_null else c.decode_from_stream(in_stream, True) for c,
is_null in zip(self.components, nulls)))
def _make_value_coder(self, nulls=itertools.repeat(False)):
components = [
component for component,
is_null in zip(self.components, nulls) if not is_null
] if self.has_nullable_fields else self.components
return TupleCoder(components).get_impl()
class LogicalTypeCoder(FastCoder):
def __init__(self, logical_type, representation_coder):
self.logical_type = logical_type
self.representation_coder = representation_coder
def _create_impl(self):
return LogicalTypeCoderImpl(self.logical_type, self.representation_coder)
def is_deterministic(self):
return self.representation_coder.is_deterministic()
def to_type_hint(self):
return self.logical_type.language_type()
class LogicalTypeCoderImpl(StreamCoderImpl):
def __init__(self, logical_type, representation_coder):
self.logical_type = logical_type
self.representation_coder = representation_coder.get_impl()
def encode_to_stream(self, value, out, nested):
return self.representation_coder.encode_to_stream(
self.logical_type.to_representation_type(value), out, nested)
def decode_from_stream(self, in_stream, nested):
return self.logical_type.to_language_type(
self.representation_coder.decode_from_stream(in_stream, nested))