#
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# 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 argparse
import contextlib
import json
import yaml
import apache_beam as beam
from apache_beam.io.filesystems import FileSystems
from apache_beam.typehints.schemas import LogicalType
from apache_beam.typehints.schemas import MillisInstant
from apache_beam.yaml import yaml_transform
def _preparse_jinja_flags(argv):
"""Promotes any flags to --jinja_variables based on --jinja_variable_flags.
This is to facilitate tools (such as dataflow templates) that must pass
options as un-nested flags.
"""
parser = argparse.ArgumentParser()
parser.add_argument(
'--jinja_variable_flags',
default=[],
type=lambda s: s.split(','),
help='A list of flag names that should be used as jinja variables.')
parser.add_argument(
'--jinja_variables',
default={},
type=json.loads,
help='A json dict of variables used when invoking the jinja preprocessor '
'on the provided yaml pipeline.')
jinja_args, other_args = parser.parse_known_args(argv)
if not jinja_args.jinja_variable_flags:
return argv
jinja_variable_parser = argparse.ArgumentParser()
for flag_name in jinja_args.jinja_variable_flags:
jinja_variable_parser.add_argument('--' + flag_name)
jinja_flag_variables, pipeline_args = jinja_variable_parser.parse_known_args(
other_args)
jinja_args.jinja_variables.update(
**
{k: v
for (k, v) in vars(jinja_flag_variables).items() if v is not None})
if jinja_args.jinja_variables:
pipeline_args = pipeline_args + [
'--jinja_variables=' + json.dumps(jinja_args.jinja_variables)
]
return pipeline_args
def _parse_arguments(argv):
parser = argparse.ArgumentParser()
parser.add_argument(
'--yaml_pipeline',
'--pipeline_spec',
help='A yaml description of the pipeline to run.')
parser.add_argument(
'--yaml_pipeline_file',
'--pipeline_spec_file',
help='A file containing a yaml description of the pipeline to run.')
parser.add_argument(
'--json_schema_validation',
default='generic',
help='none: do no pipeline validation against the schema; '
'generic: validate the pipeline shape, but not individual transforms; '
'per_transform: also validate the config of known transforms')
parser.add_argument(
'--jinja_variables',
default=None,
type=json.loads,
help='A json dict of variables used when invoking the jinja preprocessor '
'on the provided yaml pipeline.')
return parser.parse_known_args(argv)
def _pipeline_spec_from_args(known_args):
if known_args.yaml_pipeline_file and known_args.yaml_pipeline:
raise ValueError(
"Exactly one of yaml_pipeline or yaml_pipeline_file must be set.")
elif known_args.yaml_pipeline_file:
with FileSystems.open(known_args.yaml_pipeline_file) as fin:
pipeline_yaml = fin.read().decode()
elif known_args.yaml_pipeline:
pipeline_yaml = known_args.yaml_pipeline
else:
raise ValueError(
"Exactly one of yaml_pipeline or yaml_pipeline_file must be set.")
return pipeline_yaml
@contextlib.contextmanager
def _fix_xlang_instant_coding():
# Scoped workaround for https://github.com/apache/beam/issues/28151.
old_registry = LogicalType._known_logical_types
LogicalType._known_logical_types = old_registry.copy()
try:
LogicalType.register_logical_type(MillisInstant)
yield
finally:
LogicalType._known_logical_types = old_registry
[docs]
def run(argv=None):
argv = _preparse_jinja_flags(argv)
known_args, pipeline_args = _parse_arguments(argv)
pipeline_template = _pipeline_spec_from_args(known_args)
pipeline_yaml = yaml_transform.expand_jinja(
pipeline_template, known_args.jinja_variables or {})
pipeline_spec = yaml.load(pipeline_yaml, Loader=yaml_transform.SafeLineLoader)
with _fix_xlang_instant_coding():
with beam.Pipeline( # linebreak for better yapf formatting
options=beam.options.pipeline_options.PipelineOptions(
pipeline_args,
pickle_library='cloudpickle',
**yaml_transform.SafeLineLoader.strip_metadata(pipeline_spec.get(
'options', {}))),
display_data={'yaml': pipeline_yaml,
'yaml_jinja_template': pipeline_template,
'yaml_jinja_variables': json.dumps(
known_args.jinja_variables)}) as p:
print("Building pipeline...")
yaml_transform.expand_pipeline(
p, pipeline_spec, validate_schema=known_args.json_schema_validation)
print("Running pipeline...")
if __name__ == '__main__':
import logging
logging.getLogger().setLevel(logging.INFO)
run()