[yaml] Fix examples catalog tests

sdks/python/apache_beam/yaml/examples/testing/examples_test.py

@@ -40,8 +40,8 @@
 
 
 def check_output(expected: List[str]):
-  def _check_inner(actual: PCollection[str]):
-    formatted_actual = actual | beam.Map(
+  def _check_inner(actual: List[PCollection[str]]):
+    formatted_actual = actual | beam.Flatten() | beam.Map(
         lambda row: str(beam.Row(**row._asdict())))
     assert_matches_stdout(formatted_actual, expected)
 
@@ -59,6 +59,57 @@ def products_csv():
   ])
 
 
+def spanner_data():
+  return [{
+      'shipment_id': 'S1',
+      'customer_id': 'C1',
+      'shipment_date': '2023-05-01',
+      'shipment_cost': 150.0,
+      'customer_name': 'Alice',
+      'customer_email': '[email protected]'
+  },
+          {
+              'shipment_id': 'S2',
+              'customer_id': 'C2',
+              'shipment_date': '2023-06-12',
+              'shipment_cost': 300.0,
+              'customer_name': 'Bob',
+              'customer_email': '[email protected]'
+          },
+          {
+              'shipment_id': 'S3',
+              'customer_id': 'C1',
+              'shipment_date': '2023-05-10',
+              'shipment_cost': 20.0,
+              'customer_name': 'Alice',
+              'customer_email': '[email protected]'
+          },
+          {
+              'shipment_id': 'S4',
+              'customer_id': 'C4',
+              'shipment_date': '2024-07-01',
+              'shipment_cost': 150.0,
+              'customer_name': 'Derek',
+              'customer_email': '[email protected]'
+          },
+          {
+              'shipment_id': 'S5',
+              'customer_id': 'C5',
+              'shipment_date': '2023-05-09',
+              'shipment_cost': 300.0,
+              'customer_name': 'Erin',
+              'customer_email': '[email protected]'
+          },
+          {
+              'shipment_id': 'S6',
+              'customer_id': 'C4',
+              'shipment_date': '2024-07-02',
+              'shipment_cost': 150.0,
+              'customer_name': 'Derek',
+              'customer_email': '[email protected]'
+          }]
+
+
 def create_test_method(
     pipeline_spec_file: str,
     custom_preprocessors: List[Callable[..., Union[Dict, List]]]):
@@ -84,9 +135,12 @@ def test_yaml_example(self):
           pickle_library='cloudpickle',
           **yaml_transform.SafeLineLoader.strip_metadata(pipeline_spec.get(
               'options', {})))) as p:
-        actual = yaml_transform.expand_pipeline(p, pipeline_spec)
-        if not actual:
-          actual = p.transforms_stack[0].parts[-1].outputs[None]
+        actual = [yaml_transform.expand_pipeline(p, pipeline_spec)]
+        if not actual[0]:
+          actual = list(p.transforms_stack[0].parts[-1].outputs.values())
+          for transform in p.transforms_stack[0].parts[:-1]:
+            if transform.transform.label == 'log_for_testing':
+              actual += list(transform.outputs.values())
         check_output(expected)(actual)
 
   return test_yaml_example
@@ -155,9 +209,13 @@ def _wordcount_test_preprocessor(
       env.input_file('kinglear.txt', '\n'.join(lines)))
 
 
-@YamlExamplesTestSuite.register_test_preprocessor(
-    ['test_simple_filter_yaml', 'test_simple_filter_and_combine_yaml'])
-def _file_io_write_test_preprocessor(
+@YamlExamplesTestSuite.register_test_preprocessor([
+    'test_simple_filter_yaml',
+    'test_simple_filter_and_combine_yaml',
+    'test_spanner_read_yaml',
+    'test_spanner_write_yaml'
+])
+def _io_write_test_preprocessor(
     test_spec: dict, expected: List[str], env: TestEnvironment):
 
   if pipeline := test_spec.get('pipeline', None):
@@ -166,8 +224,8 @@ def _file_io_write_test_preprocessor(
         transform['type'] = 'LogForTesting'
         transform['config'] = {
             k: v
-            for k,
-            v in transform.get('config', {}).items() if k.startswith('__')
+            for (k, v) in transform.get('config', {}).items()
+            if (k.startswith('__') or k == 'error_handling')
         }
 
   return test_spec
@@ -191,7 +249,30 @@ def _file_io_read_test_preprocessor(
   return test_spec
 
 
+@YamlExamplesTestSuite.register_test_preprocessor(['test_spanner_read_yaml'])
+def _spanner_io_read_test_preprocessor(
+    test_spec: dict, expected: List[str], env: TestEnvironment):
+
+  if pipeline := test_spec.get('pipeline', None):
+    for transform in pipeline.get('transforms', []):
+      if transform.get('type', '').startswith('ReadFromSpanner'):
+        config = transform['config']
+        instance, database = config['instance_id'], config['database_id']
+        if table := config.get('table', None) is None:
+          table = config.get('query', '').split('FROM')[-1].strip()
+        transform['type'] = 'Create'
+        transform['config'] = {
+            k: v
+            for k, v in config.items() if k.startswith('__')
+        }
+        transform['config']['elements'] = INPUT_TABLES[(
+            str(instance), str(database), str(table))]
+
+  return test_spec
+
+
 INPUT_FILES = {'products.csv': products_csv()}
+INPUT_TABLES = {('shipment-test', 'shipment', 'shipments'): spanner_data()}
 
 YAML_DOCS_DIR = os.path.join(os.path.dirname(__file__))
 ExamplesTest = YamlExamplesTestSuite(
@@ -205,6 +286,10 @@ def _file_io_read_test_preprocessor(
     'AggregationExamplesTest',
     os.path.join(YAML_DOCS_DIR, '../transforms/aggregation/*.yaml')).run()
 
+IOTest = YamlExamplesTestSuite(
+    'IOExamplesTest', os.path.join(YAML_DOCS_DIR,
+                                   '../transforms/io/*.yaml')).run()
+
 if __name__ == '__main__':
   logging.getLogger().setLevel(logging.INFO)
   unittest.main()

sdks/python/apache_beam/yaml/examples/io/spanner_read.yaml → sdks/python/apache_beam/yaml/examples/transforms/io/spanner_read.yaml

@@ -18,10 +18,10 @@
 pipeline:
   transforms:
 
-  # Reading data from a Spanner database. The table used here has the following columns:
-  # shipment_id (String), customer_id (String), shipment_date (String), shipment_cost (Float64), customer_name (String), customer_email (String)
-  # ReadFromSpanner transform is called using project_id, instance_id, database_id and a query
-  # A table with a list of columns can also be specified instead of a query
+    # Reading data from a Spanner database. The table used here has the following columns:
+    # shipment_id (String), customer_id (String), shipment_date (String), shipment_cost (Float64), customer_name (String), customer_email (String)
+    # ReadFromSpanner transform is called using project_id, instance_id, database_id and a query
+    # A table with a list of columns can also be specified instead of a query
     - type: ReadFromSpanner
       name: ReadShipments
       config:
@@ -30,18 +30,18 @@ pipeline:
         database_id: 'shipment'
         query: 'SELECT * FROM shipments'
 
-  # Filtering the data based on a specific condition
-  # Here, the condition is used to keep only the rows where the customer_id is 'C1'
+    # Filtering the data based on a specific condition
+    # Here, the condition is used to keep only the rows where the customer_id is 'C1'
     - type: Filter
       name: FilterShipments
       input: ReadShipments
       config:
         language: python
         keep: "customer_id == 'C1'"
 
-  # Mapping the data fields and applying transformations
-  # A new field 'shipment_cost_category' is added with a custom transformation
-  # A callable is defined to categorize shipment cost
+    # Mapping the data fields and applying transformations
+    # A new field 'shipment_cost_category' is added with a custom transformation
+    # A callable is defined to categorize shipment cost
     - type: MapToFields
       name: MapFieldsForSpanner
       input: FilterShipments
@@ -65,16 +65,15 @@ pipeline:
                   else:
                       return 'High Cost'
 
-  # Writing the transformed data to a CSV file          
+    # Writing the transformed data to a CSV file
     - type: WriteToCsv
       name: WriteBig
       input: MapFieldsForSpanner
       config:
         path: shipments.csv
 
 
-  # On executing the above pipeline, a new CSV file is created with the following records
-
+# On executing the above pipeline, a new CSV file is created with the following records
 # Expected:
 #  Row(shipment_id='S1', customer_id='C1', shipment_date='2023-05-01', shipment_cost=150.0, customer_name='Alice', customer_email='[email protected]', shipment_cost_category='Medium Cost')
 #  Row(shipment_id='S3', customer_id='C1', shipment_date='2023-05-10', shipment_cost=20.0, customer_name='Alice', customer_email='[email protected]', shipment_cost_category='Low Cost')

sdks/python/apache_beam/yaml/examples/io/spanner_write.yaml → sdks/python/apache_beam/yaml/examples/transforms/io/spanner_write.yaml

@@ -18,8 +18,8 @@
 pipeline:
   transforms:
 
-  # Step 1: Creating rows to be written to Spanner
-  # The element names correspond to the column names in the Spanner table
+    # Step 1: Creating rows to be written to Spanner
+    # The element names correspond to the column names in the Spanner table
     - type: Create
       name: CreateRows
       config:
@@ -31,10 +31,10 @@ pipeline:
             customer_name: "Erin"
             customer_email: "[email protected]"
 
-  # Step 2: Writing the created rows to a Spanner database
-  # We require the project ID, instance ID, database ID and table ID to connect to Spanner
-  # Error handling can be specified optionally to ensure any failed operations aren't lost
-  # The failed data is passed on in the pipeline and can be handled 
+    # Step 2: Writing the created rows to a Spanner database
+    # We require the project ID, instance ID, database ID and table ID to connect to Spanner
+    # Error handling can be specified optionally to ensure any failed operations aren't lost
+    # The failed data is passed on in the pipeline and can be handled
     - type: WriteToSpanner
       name: WriteSpanner
       input: CreateRows
@@ -46,8 +46,11 @@ pipeline:
         error_handling:
           output: my_error_output
 
-  # Step 3: Writing the failed records to a JSON file
+    # Step 3: Writing the failed records to a JSON file
     - type: WriteToJson
       input: WriteSpanner.my_error_output
       config:
         path: errors.json
+
+# Expected:
+#  Row(shipment_id='S5', customer_id='C5', shipment_date='2023-05-09', shipment_cost=300.0, customer_name='Erin', customer_email='[email protected]')

sdks/python/apache_beam/yaml/generate_yaml_docs.py

@@ -30,7 +30,7 @@
 from apache_beam.version import __version__ as beam_version
 from apache_beam.yaml import json_utils
 from apache_beam.yaml import yaml_provider
-from apache_beam.yaml.yaml_mapping import ErrorHandlingConfig
+from apache_beam.yaml.yaml_errors import ErrorHandlingConfig
 
 
 def _singular(name):

sdks/python/apache_beam/yaml/yaml_errors.py

@@ -0,0 +1,88 @@
+#
+# 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 functools
+import inspect
+from typing import NamedTuple
+
+import apache_beam as beam
+from apache_beam.typehints.row_type import RowTypeConstraint
+
+
+class ErrorHandlingConfig(NamedTuple):
+  """Class to define Error Handling parameters.
+
+      Args:
+        output (str): Name to use for the output error collection
+      """
+  output: str
+  # TODO: Other parameters are valid here too, but not common to Java.
+
+
+def exception_handling_args(error_handling_spec):
+  if error_handling_spec:
+    return {
+        'dead_letter_tag' if k == 'output' else k: v
+        for (k, v) in error_handling_spec.items()
+    }
+  else:
+    return None
+
+
+def map_errors_to_standard_format(input_type):
+  # TODO(https://github.com/apache/beam/issues/24755): Switch to MapTuple.
+
+  return beam.Map(
+      lambda x: beam.Row(
+          element=x[0], msg=str(x[1][1]), stack=''.join(x[1][2]))
+  ).with_output_types(
+      RowTypeConstraint.from_fields([("element", input_type), ("msg", str),
+                                     ("stack", str)]))
+
+
+def maybe_with_exception_handling(inner_expand):
+  def expand(self, pcoll):
+    wrapped_pcoll = beam.core._MaybePValueWithErrors(
+        pcoll, self._exception_handling_args)
+    return inner_expand(self, wrapped_pcoll).as_result(
+        map_errors_to_standard_format(pcoll.element_type))
+
+  return expand
+
+
+def maybe_with_exception_handling_transform_fn(transform_fn):
+  @functools.wraps(transform_fn)
+  def expand(pcoll, error_handling=None, **kwargs):
+    wrapped_pcoll = beam.core._MaybePValueWithErrors(
+        pcoll, exception_handling_args(error_handling))
+    return transform_fn(wrapped_pcoll, **kwargs).as_result(
+        map_errors_to_standard_format(pcoll.element_type))
+
+  original_signature = inspect.signature(transform_fn)
+  new_parameters = list(original_signature.parameters.values())
+  error_handling_param = inspect.Parameter(
+      'error_handling',
+      inspect.Parameter.KEYWORD_ONLY,
+      default=None,
+      annotation=ErrorHandlingConfig)
+  if new_parameters[-1].kind == inspect.Parameter.VAR_KEYWORD:
+    new_parameters.insert(-1, error_handling_param)
+  else:
+    new_parameters.append(error_handling_param)
+  expand.__signature__ = original_signature.replace(parameters=new_parameters)
+
+  return expand

sdks/python/apache_beam/yaml/yaml_io.py

@@ -45,7 +45,7 @@
 from apache_beam.portability.api import schema_pb2
 from apache_beam.typehints import schemas
 from apache_beam.yaml import json_utils
-from apache_beam.yaml import yaml_mapping
+from apache_beam.yaml import yaml_errors
 from apache_beam.yaml import yaml_provider
 
 
@@ -289,7 +289,7 @@ def formatter(row):
 
 
 @beam.ptransform_fn
-@yaml_mapping.maybe_with_exception_handling_transform_fn
+@yaml_errors.maybe_with_exception_handling_transform_fn
 def read_from_pubsub(
     root,
     *,
@@ -393,7 +393,7 @@ def mapper(msg):
 
 
 @beam.ptransform_fn
-@yaml_mapping.maybe_with_exception_handling_transform_fn
+@yaml_errors.maybe_with_exception_handling_transform_fn
 def write_to_pubsub(
     pcoll,
     *,