chamikaramj commented on code in PR #29561: URL: https://github.com/apache/beam/pull/29561#discussion_r1417928153
########## sdks/python/apache_beam/transforms/wrapper_provider.py: ########## @@ -0,0 +1,186 @@ +# +# 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. +# + +import logging +import typing +from collections import namedtuple + +from apache_beam.transforms import PTransform +from apache_beam.transforms.external import BeamJarExpansionService +from apache_beam.transforms.external import SchemaAwareExternalTransform +from apache_beam.transforms.external import SchemaTransformsConfig +from apache_beam.typehints.schemas import named_tuple_to_schema +from apache_beam.typehints.schemas import typing_from_runner_api + + +def snake_case_to_upper_camel_case(string): + """Convert snake_case to UpperCamelCase""" + components = string.split('_') + output = ''.join(n.capitalize() for n in components) + return output + + +def snake_case_to_lower_camel_case(string): + """Convert snake_case to lowerCamelCase""" + if len(string) <= 1: + return string.lower() + upper = snake_case_to_upper_camel_case(string) + return upper[0].lower() + upper[1:] + + +def camel_case_to_snake_case(string): + """Convert camelCase to snake_case""" + arr = ['_' + n.lower() if n.isupper() else n for n in string] + return ''.join(arr).lstrip('_') + + +# Information regarding a Wrapper parameter. +ParamInfo = namedtuple('ParamInfo', ['type', 'description', 'original_name']) + + +def get_config_with_descriptions(schematransform: SchemaTransformsConfig): + # Prepare a configuration schema that includes types and descriptions + schema = named_tuple_to_schema(schematransform.configuration_schema) + descriptions = schematransform.configuration_schema._field_descriptions + fields_with_descriptions = {} + for field in schema.fields: + fields_with_descriptions[camel_case_to_snake_case(field.name)] = ParamInfo( + typing_from_runner_api(field.type), + descriptions[field.name], + field.name) + + return fields_with_descriptions + + +class Wrapper(PTransform): + """Template for a SchemaTransform Python wrappeer""" + + # These attributes need to be set when a Wrapper type is created + default_expansion_service = None + identifier = None + + def __init__(self, expansion_service=None, **kwargs): + self._kwargs = kwargs + self._expansion_service = \ + expansion_service or self.default_expansion_service + self.schematransform: SchemaTransformsConfig = \ Review Comment: Can the discover_config call be invoked once during wrapper generation instead of being invoked every time a transform is initialized ? ########## sdks/python/apache_beam/transforms/wrapper_provider.py: ########## @@ -0,0 +1,186 @@ +# +# 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. +# + +import logging +import typing +from collections import namedtuple + +from apache_beam.transforms import PTransform +from apache_beam.transforms.external import BeamJarExpansionService +from apache_beam.transforms.external import SchemaAwareExternalTransform +from apache_beam.transforms.external import SchemaTransformsConfig +from apache_beam.typehints.schemas import named_tuple_to_schema +from apache_beam.typehints.schemas import typing_from_runner_api + + +def snake_case_to_upper_camel_case(string): + """Convert snake_case to UpperCamelCase""" + components = string.split('_') + output = ''.join(n.capitalize() for n in components) + return output + + +def snake_case_to_lower_camel_case(string): + """Convert snake_case to lowerCamelCase""" + if len(string) <= 1: + return string.lower() + upper = snake_case_to_upper_camel_case(string) + return upper[0].lower() + upper[1:] + + +def camel_case_to_snake_case(string): + """Convert camelCase to snake_case""" + arr = ['_' + n.lower() if n.isupper() else n for n in string] + return ''.join(arr).lstrip('_') + + +# Information regarding a Wrapper parameter. +ParamInfo = namedtuple('ParamInfo', ['type', 'description', 'original_name']) + + +def get_config_with_descriptions(schematransform: SchemaTransformsConfig): + # Prepare a configuration schema that includes types and descriptions + schema = named_tuple_to_schema(schematransform.configuration_schema) + descriptions = schematransform.configuration_schema._field_descriptions + fields_with_descriptions = {} + for field in schema.fields: + fields_with_descriptions[camel_case_to_snake_case(field.name)] = ParamInfo( + typing_from_runner_api(field.type), + descriptions[field.name], + field.name) + + return fields_with_descriptions + + +class Wrapper(PTransform): + """Template for a SchemaTransform Python wrappeer""" + + # These attributes need to be set when a Wrapper type is created + default_expansion_service = None + identifier = None + + def __init__(self, expansion_service=None, **kwargs): + self._kwargs = kwargs + self._expansion_service = \ + expansion_service or self.default_expansion_service + self.schematransform: SchemaTransformsConfig = \ + SchemaAwareExternalTransform.discover_config( + self._expansion_service, self.identifier) + + def expand(self, input): + camel_case_kwargs = { + snake_case_to_lower_camel_case(k): v + for k, v in self._kwargs.items() + } + + external_schematransform = SchemaAwareExternalTransform( + identifier=self.identifier, + expansion_service=self._expansion_service, + rearrange_based_on_discovery=True, + **camel_case_kwargs) + + input_tags = self.schematransform.inputs + # TODO(ahmedabu98): how do we handle the case of multiple input pcolls? + if input_tags and len(input_tags) == 1: + return {input_tags[0]: input} | external_schematransform + else: + return input.pipeline | external_schematransform + + +class WrapperProvider: + def __init__(self, expansion_services=None): + self.wrappers = {} + self.urn_to_wrapper_name = {} + + if expansion_services is None: + expansion_services = [] + if isinstance(expansion_services, set): + expansion_services = list(expansion_services) + if not isinstance(expansion_services, list): + expansion_services = [expansion_services] + self.expansion_services = expansion_services + + def _create_wrappers(self): + # multiple services can overlap and include the same URNs. If this happens, + # we prioritize by the order of services in the list + identifiers = set() + for service in self.expansion_services: + target = service + if isinstance(service, BeamJarExpansionService): + target = service.gradle_target + try: + schematransform_configs = SchemaAwareExternalTransform.discover(service) + except Exception as e: + logging.exception( + "Encountered an error while discovering expansion service %s:\n%s", + target, + e) + continue + skipped_urns = [] + for config in schematransform_configs: + if config.identifier not in identifiers: + identifiers.add(config.identifier) + identifier_components = config.identifier.split(':') + # We expect URNs like + # `beam:schematransform:org.apache.beam:my_transform:v1` Review Comment: Will it be possible to override this behavior via configs ? I don't think we should strictly rely on this URN format. ########## sdks/python/apache_beam/transforms/wrapper_provider.py: ########## @@ -0,0 +1,186 @@ +# +# 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. +# + +import logging +import typing +from collections import namedtuple + +from apache_beam.transforms import PTransform +from apache_beam.transforms.external import BeamJarExpansionService +from apache_beam.transforms.external import SchemaAwareExternalTransform +from apache_beam.transforms.external import SchemaTransformsConfig +from apache_beam.typehints.schemas import named_tuple_to_schema +from apache_beam.typehints.schemas import typing_from_runner_api + + +def snake_case_to_upper_camel_case(string): + """Convert snake_case to UpperCamelCase""" + components = string.split('_') + output = ''.join(n.capitalize() for n in components) + return output + + +def snake_case_to_lower_camel_case(string): + """Convert snake_case to lowerCamelCase""" + if len(string) <= 1: + return string.lower() + upper = snake_case_to_upper_camel_case(string) + return upper[0].lower() + upper[1:] + + +def camel_case_to_snake_case(string): + """Convert camelCase to snake_case""" + arr = ['_' + n.lower() if n.isupper() else n for n in string] + return ''.join(arr).lstrip('_') + + +# Information regarding a Wrapper parameter. +ParamInfo = namedtuple('ParamInfo', ['type', 'description', 'original_name']) + + +def get_config_with_descriptions(schematransform: SchemaTransformsConfig): + # Prepare a configuration schema that includes types and descriptions + schema = named_tuple_to_schema(schematransform.configuration_schema) + descriptions = schematransform.configuration_schema._field_descriptions + fields_with_descriptions = {} + for field in schema.fields: + fields_with_descriptions[camel_case_to_snake_case(field.name)] = ParamInfo( + typing_from_runner_api(field.type), + descriptions[field.name], + field.name) + + return fields_with_descriptions + + +class Wrapper(PTransform): + """Template for a SchemaTransform Python wrappeer""" + + # These attributes need to be set when a Wrapper type is created + default_expansion_service = None + identifier = None + + def __init__(self, expansion_service=None, **kwargs): + self._kwargs = kwargs + self._expansion_service = \ + expansion_service or self.default_expansion_service + self.schematransform: SchemaTransformsConfig = \ + SchemaAwareExternalTransform.discover_config( + self._expansion_service, self.identifier) + + def expand(self, input): + camel_case_kwargs = { + snake_case_to_lower_camel_case(k): v + for k, v in self._kwargs.items() + } + + external_schematransform = SchemaAwareExternalTransform( + identifier=self.identifier, + expansion_service=self._expansion_service, + rearrange_based_on_discovery=True, + **camel_case_kwargs) + + input_tags = self.schematransform.inputs + # TODO(ahmedabu98): how do we handle the case of multiple input pcolls? + if input_tags and len(input_tags) == 1: + return {input_tags[0]: input} | external_schematransform + else: + return input.pipeline | external_schematransform + + +class WrapperProvider: Review Comment: Please add documentation. ########## sdks/java/core/expansion-service/build.gradle: ########## @@ -0,0 +1,36 @@ +/* + * 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 Review Comment: This creates a circular dependency since sdks/java/expansion-service library depends on sdks/java/core. Was this created just to use GenerateSequence ? Transforms in core should be already available in all the expansion services so you could just use one of them (for example, sdks/java/io/expansion-service). ########## sdks/python/apache_beam/transforms/wrapper_provider_test.py: ########## @@ -0,0 +1,67 @@ +# +# 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. +# +import logging +import os +import unittest + +import pytest + +import apache_beam as beam +from apache_beam.testing.test_pipeline import TestPipeline +from apache_beam.testing.util import assert_that +from apache_beam.testing.util import equal_to +from apache_beam.transforms.external import BeamJarExpansionService +from apache_beam.transforms.wrapper_provider import WrapperProvider + + [email protected]_core_java_expansion_service [email protected]( + os.environ.get('EXPANSION_PORT'), + "EXPANSION_PORT environment var is not provided.") +class WrapperProviderTest(unittest.TestCase): + def setUp(self): + self.test_pipeline = TestPipeline(is_integration_test=True) + + def test_generate_sequence_config_schema(self): + wrapper_provider = WrapperProvider( + BeamJarExpansionService(":sdks:java:core:expansion-service:shadowJar")) + + self.assertTrue('GenerateSequence' in wrapper_provider.get_available()) + generate_sequence = wrapper_provider.get('GenerateSequence') + + config_schema = generate_sequence.configuration_schema + for param in ['start', 'end', 'rate']: + self.assertTrue(param in config_schema) + + def test_run_generate_sequence(self): + wrapper_provider = WrapperProvider( + BeamJarExpansionService(":sdks:java:core:expansion-service:shadowJar")) + + self.assertTrue('GenerateSequence' in wrapper_provider.get_available()) + + generate_sequence = wrapper_provider.get('GenerateSequence') Review Comment: Is it possible to generate generate_sequence.py as an actual Python module that can be inspected by IDEs etc ? ########## sdks/python/apache_beam/transforms/wrapper_provider.py: ########## @@ -0,0 +1,186 @@ +# +# 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. +# + +import logging +import typing +from collections import namedtuple + +from apache_beam.transforms import PTransform +from apache_beam.transforms.external import BeamJarExpansionService +from apache_beam.transforms.external import SchemaAwareExternalTransform +from apache_beam.transforms.external import SchemaTransformsConfig +from apache_beam.typehints.schemas import named_tuple_to_schema +from apache_beam.typehints.schemas import typing_from_runner_api + + +def snake_case_to_upper_camel_case(string): + """Convert snake_case to UpperCamelCase""" + components = string.split('_') + output = ''.join(n.capitalize() for n in components) + return output + + +def snake_case_to_lower_camel_case(string): + """Convert snake_case to lowerCamelCase""" + if len(string) <= 1: + return string.lower() + upper = snake_case_to_upper_camel_case(string) + return upper[0].lower() + upper[1:] + + +def camel_case_to_snake_case(string): + """Convert camelCase to snake_case""" + arr = ['_' + n.lower() if n.isupper() else n for n in string] + return ''.join(arr).lstrip('_') + + +# Information regarding a Wrapper parameter. +ParamInfo = namedtuple('ParamInfo', ['type', 'description', 'original_name']) + + +def get_config_with_descriptions(schematransform: SchemaTransformsConfig): + # Prepare a configuration schema that includes types and descriptions + schema = named_tuple_to_schema(schematransform.configuration_schema) + descriptions = schematransform.configuration_schema._field_descriptions + fields_with_descriptions = {} + for field in schema.fields: + fields_with_descriptions[camel_case_to_snake_case(field.name)] = ParamInfo( + typing_from_runner_api(field.type), + descriptions[field.name], + field.name) + + return fields_with_descriptions + + +class Wrapper(PTransform): + """Template for a SchemaTransform Python wrappeer""" Review Comment: s/wrappeer/wrapper -- This is an automated message from the Apache Git Service. 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