casassg commented on a change in pull request #8962:
URL: https://github.com/apache/airflow/pull/8962#discussion_r432601178
##########
File path: airflow/operators/python.py
##########
@@ -145,6 +149,131 @@ def execute_callable(self):
return self.python_callable(*self.op_args, **self.op_kwargs)
+class _PythonFunctionalOperator(BaseOperator):
+ """
+ Wraps a Python callable and captures args/kwargs when called for execution.
+
+ :param python_callable: A reference to an object that is callable
+ :type python_callable: python callable
+ :param op_kwargs: a dictionary of keyword arguments that will get unpacked
+ in your function
+ :type op_kwargs: dict (templated)
+ :param op_args: a list of positional arguments that will get unpacked when
+ calling your callable
+ :type op_args: list (templated)
+ :param multiple_outputs: if set, function return value will be
+ unrolled to multiple XCom values. Dict will unroll to xcom values with
keys as keys.
+ Defaults to False.
+ :type multiple_outputs: bool
+ """
+
+ template_fields = ('op_args', 'op_kwargs')
+ ui_color = '#ffefeb'
+
+ # since we won't mutate the arguments, we should just do the shallow copy
+ # there are some cases we can't deepcopy the objects(e.g protobuf).
+ shallow_copy_attrs = ('python_callable',)
+
+ @apply_defaults
+ def __init__(
+ self,
+ python_callable: Callable,
+ op_args: Tuple[Any],
+ op_kwargs: Dict[str, Any],
+ multiple_outputs: bool = False,
+ **kwargs
+ ) -> None:
+ kwargs['task_id'] = self._get_unique_task_id(kwargs['task_id'],
kwargs.get('dag', None))
+ super().__init__(**kwargs)
+ self.python_callable = python_callable
+
+ # Check that arguments can be binded
+ signature(python_callable).bind(*op_args, **op_kwargs)
+ self.multiple_outputs = multiple_outputs
+ self.op_args = op_args
+ self.op_kwargs = op_kwargs
+
+ @staticmethod
+ def _get_unique_task_id(task_id: str, dag: Optional[DAG]) -> str:
+ dag = dag or DagContext.get_current_dag()
+ if not dag or task_id not in dag.task_ids:
+ return task_id
+ core = re.split(r'__\d+$', task_id)[0]
+ suffixes = sorted(
+ [int(re.split(r'^.+__', task_id)[1])
+ for task_id in dag.task_ids
+ if re.match(rf'^{core}__\d+$', task_id)]
+ )
+ if not suffixes:
+ return f'{core}__1'
+ return f'{core}__{suffixes[-1] + 1}'
+
+ @staticmethod
+ def validate_python_callable(python_callable):
+ """Validate that python callable can be wrapped by operator.
+ Raises exception if invalid.
+
+ :param python_callable: Python object to be validated
+ :raises: TypeError, AirflowException
+ """
+ if not callable(python_callable):
+ raise TypeError('`python_callable` param must be callable')
+ if 'self' in signature(python_callable).parameters.keys():
+ raise AirflowException('@task does not support methods')
Review comment:
Seems `ismethod` does not work.
https://stackoverflow.com/questions/47599749/check-if-function-belongs-to-a-class,
keeping it as is as the __qualname__ may involve a bit more difficult setup
and does not accept functions defined in classes that are not methods.
##########
File path: airflow/operators/python.py
##########
@@ -145,6 +149,131 @@ def execute_callable(self):
return self.python_callable(*self.op_args, **self.op_kwargs)
+class _PythonFunctionalOperator(BaseOperator):
+ """
+ Wraps a Python callable and captures args/kwargs when called for execution.
+
+ :param python_callable: A reference to an object that is callable
+ :type python_callable: python callable
+ :param op_kwargs: a dictionary of keyword arguments that will get unpacked
+ in your function
+ :type op_kwargs: dict (templated)
+ :param op_args: a list of positional arguments that will get unpacked when
+ calling your callable
+ :type op_args: list (templated)
+ :param multiple_outputs: if set, function return value will be
+ unrolled to multiple XCom values. Dict will unroll to xcom values with
keys as keys.
+ Defaults to False.
+ :type multiple_outputs: bool
+ """
+
+ template_fields = ('op_args', 'op_kwargs')
+ ui_color = '#ffefeb'
+
+ # since we won't mutate the arguments, we should just do the shallow copy
+ # there are some cases we can't deepcopy the objects(e.g protobuf).
+ shallow_copy_attrs = ('python_callable',)
+
+ @apply_defaults
+ def __init__(
+ self,
+ python_callable: Callable,
+ op_args: Tuple[Any],
+ op_kwargs: Dict[str, Any],
+ multiple_outputs: bool = False,
+ **kwargs
+ ) -> None:
+ kwargs['task_id'] = self._get_unique_task_id(kwargs['task_id'],
kwargs.get('dag', None))
+ super().__init__(**kwargs)
+ self.python_callable = python_callable
+
+ # Check that arguments can be binded
+ signature(python_callable).bind(*op_args, **op_kwargs)
+ self.multiple_outputs = multiple_outputs
+ self.op_args = op_args
+ self.op_kwargs = op_kwargs
+
+ @staticmethod
+ def _get_unique_task_id(task_id: str, dag: Optional[DAG]) -> str:
+ dag = dag or DagContext.get_current_dag()
+ if not dag or task_id not in dag.task_ids:
+ return task_id
+ core = re.split(r'__\d+$', task_id)[0]
+ suffixes = sorted(
+ [int(re.split(r'^.+__', task_id)[1])
+ for task_id in dag.task_ids
+ if re.match(rf'^{core}__\d+$', task_id)]
+ )
+ if not suffixes:
+ return f'{core}__1'
+ return f'{core}__{suffixes[-1] + 1}'
+
+ @staticmethod
+ def validate_python_callable(python_callable):
+ """Validate that python callable can be wrapped by operator.
+ Raises exception if invalid.
+
+ :param python_callable: Python object to be validated
+ :raises: TypeError, AirflowException
+ """
+ if not callable(python_callable):
+ raise TypeError('`python_callable` param must be callable')
+ if 'self' in signature(python_callable).parameters.keys():
+ raise AirflowException('@task does not support methods')
+
+ def execute(self, context: Dict):
+ return_value = self.python_callable(*self.op_args, **self.op_kwargs)
+ self.log.info("Done. Returned value was: %s", return_value)
+ if not self.multiple_outputs:
+ return return_value
+ if isinstance(return_value, dict):
+ for key in return_value.keys():
+ if not isinstance(key, str):
+ raise AirflowException('Returned dictionary keys must be
strings when using '
+ f'multiple_outputs, found {key}
({type(key)}) instead')
+ for key, value in return_value.items():
+ self.xcom_push(context, key, value)
+ else:
+ self.log.info(f'Returned output was type {type(return_value)}
expected dictionary '
+ 'for multiple_outputs')
Review comment:
Sure, repaced and added test.
##########
File path: airflow/operators/python.py
##########
@@ -145,6 +149,131 @@ def execute_callable(self):
return self.python_callable(*self.op_args, **self.op_kwargs)
+class _PythonFunctionalOperator(BaseOperator):
+ """
+ Wraps a Python callable and captures args/kwargs when called for execution.
+
+ :param python_callable: A reference to an object that is callable
+ :type python_callable: python callable
+ :param op_kwargs: a dictionary of keyword arguments that will get unpacked
+ in your function
+ :type op_kwargs: dict (templated)
+ :param op_args: a list of positional arguments that will get unpacked when
+ calling your callable
+ :type op_args: list (templated)
+ :param multiple_outputs: if set, function return value will be
+ unrolled to multiple XCom values. Dict will unroll to xcom values with
keys as keys.
+ Defaults to False.
+ :type multiple_outputs: bool
+ """
+
+ template_fields = ('op_args', 'op_kwargs')
+ ui_color = '#ffefeb'
+
+ # since we won't mutate the arguments, we should just do the shallow copy
+ # there are some cases we can't deepcopy the objects(e.g protobuf).
+ shallow_copy_attrs = ('python_callable',)
+
+ @apply_defaults
+ def __init__(
+ self,
+ python_callable: Callable,
+ op_args: Tuple[Any],
+ op_kwargs: Dict[str, Any],
+ multiple_outputs: bool = False,
+ **kwargs
+ ) -> None:
+ kwargs['task_id'] = self._get_unique_task_id(kwargs['task_id'],
kwargs.get('dag', None))
+ super().__init__(**kwargs)
+ self.python_callable = python_callable
+
+ # Check that arguments can be binded
+ signature(python_callable).bind(*op_args, **op_kwargs)
+ self.multiple_outputs = multiple_outputs
+ self.op_args = op_args
+ self.op_kwargs = op_kwargs
+
+ @staticmethod
+ def _get_unique_task_id(task_id: str, dag: Optional[DAG]) -> str:
+ dag = dag or DagContext.get_current_dag()
+ if not dag or task_id not in dag.task_ids:
+ return task_id
+ core = re.split(r'__\d+$', task_id)[0]
+ suffixes = sorted(
+ [int(re.split(r'^.+__', task_id)[1])
+ for task_id in dag.task_ids
+ if re.match(rf'^{core}__\d+$', task_id)]
+ )
+ if not suffixes:
+ return f'{core}__1'
+ return f'{core}__{suffixes[-1] + 1}'
+
+ @staticmethod
+ def validate_python_callable(python_callable):
+ """Validate that python callable can be wrapped by operator.
+ Raises exception if invalid.
+
+ :param python_callable: Python object to be validated
+ :raises: TypeError, AirflowException
+ """
+ if not callable(python_callable):
+ raise TypeError('`python_callable` param must be callable')
+ if 'self' in signature(python_callable).parameters.keys():
+ raise AirflowException('@task does not support methods')
+
+ def execute(self, context: Dict):
+ return_value = self.python_callable(*self.op_args, **self.op_kwargs)
+ self.log.info("Done. Returned value was: %s", return_value)
Review comment:
Sg!
##########
File path: airflow/operators/python.py
##########
@@ -145,6 +149,131 @@ def execute_callable(self):
return self.python_callable(*self.op_args, **self.op_kwargs)
+class _PythonFunctionalOperator(BaseOperator):
+ """
+ Wraps a Python callable and captures args/kwargs when called for execution.
+
+ :param python_callable: A reference to an object that is callable
+ :type python_callable: python callable
+ :param op_kwargs: a dictionary of keyword arguments that will get unpacked
+ in your function
+ :type op_kwargs: dict (templated)
+ :param op_args: a list of positional arguments that will get unpacked when
+ calling your callable
+ :type op_args: list (templated)
+ :param multiple_outputs: if set, function return value will be
+ unrolled to multiple XCom values. Dict will unroll to xcom values with
keys as keys.
+ Defaults to False.
+ :type multiple_outputs: bool
+ """
+
+ template_fields = ('op_args', 'op_kwargs')
+ ui_color = '#ffefeb'
+
+ # since we won't mutate the arguments, we should just do the shallow copy
+ # there are some cases we can't deepcopy the objects(e.g protobuf).
+ shallow_copy_attrs = ('python_callable',)
+
+ @apply_defaults
+ def __init__(
+ self,
+ python_callable: Callable,
+ op_args: Tuple[Any],
+ op_kwargs: Dict[str, Any],
+ multiple_outputs: bool = False,
+ **kwargs
+ ) -> None:
+ kwargs['task_id'] = self._get_unique_task_id(kwargs['task_id'],
kwargs.get('dag', None))
+ super().__init__(**kwargs)
+ self.python_callable = python_callable
+
+ # Check that arguments can be binded
+ signature(python_callable).bind(*op_args, **op_kwargs)
+ self.multiple_outputs = multiple_outputs
+ self.op_args = op_args
+ self.op_kwargs = op_kwargs
+
+ @staticmethod
+ def _get_unique_task_id(task_id: str, dag: Optional[DAG]) -> str:
+ dag = dag or DagContext.get_current_dag()
+ if not dag or task_id not in dag.task_ids:
+ return task_id
+ core = re.split(r'__\d+$', task_id)[0]
+ suffixes = sorted(
+ [int(re.split(r'^.+__', task_id)[1])
+ for task_id in dag.task_ids
+ if re.match(rf'^{core}__\d+$', task_id)]
+ )
+ if not suffixes:
+ return f'{core}__1'
+ return f'{core}__{suffixes[-1] + 1}'
Review comment:
Added!
##########
File path: airflow/operators/python.py
##########
@@ -145,6 +148,142 @@ def execute_callable(self):
return self.python_callable(*self.op_args, **self.op_kwargs)
+class _PythonFunctionalOperator(BaseOperator):
+ """
+ Wraps a Python callable and captures args/kwargs when called for execution.
+
+ :param python_callable: A reference to an object that is callable
+ :type python_callable: python callable
+ :param multiple_outputs: if set, function return value will be
+ unrolled to multiple XCom values. List/Tuples will unroll to xcom
values
+ with index as key. Dict will unroll to xcom values with keys as keys.
+ Defaults to False.
+ :type multiple_outputs: bool
+ """
+
+ template_fields = ('_op_args', '_op_kwargs')
+ ui_color = '#ffefeb'
+
+ # since we won't mutate the arguments, we should just do the shallow copy
+ # there are some cases we can't deepcopy the objects(e.g protobuf).
+ shallow_copy_attrs = ('python_callable',)
+
+ @apply_defaults
+ def __init__(
+ self,
+ python_callable: Callable,
+ multiple_outputs: bool = False,
+ *args,
+ **kwargs
+ ) -> None:
+ dag = kwargs.get('dag', None) or DagContext.get_current_dag()
+ kwargs['task_id'] = self._get_unique_task_id(kwargs['task_id'], dag)
+ self._validate_python_callable(python_callable)
+ super().__init__(*args, **kwargs)
+ self.python_callable = python_callable
+ self.multiple_outputs = multiple_outputs
+ self._kwargs = kwargs
+ self._op_args: List[Any] = []
+ self._called = False
+ self._op_kwargs: Dict[str, Any] = {}
+
+ @staticmethod
+ def _get_unique_task_id(task_id, dag):
+ if not dag or task_id not in dag.task_ids:
+ return task_id
+ core = re.split(r'__\d+$', task_id)[0]
+ suffixes = sorted(
+ [int(re.split(r'^.+__', task_id)[1])
+ for task_id in dag.task_ids
+ if re.match(rf'^{core}__\d+$', task_id)]
+ )
+ if not suffixes:
+ return f'{core}__1'
+ return f'{core}__{suffixes[-1] + 1}'
+
+ @staticmethod
+ def _validate_python_callable(python_callable):
+ if not callable(python_callable):
+ raise AirflowException('`python_callable` param must be callable')
+ if 'self' in signature(python_callable).parameters.keys():
+ raise AirflowException('@task does not support methods')
+
+ def __call__(self, *args, **kwargs):
+ # If args/kwargs are set, then operator has been called. Raise
exception
+ if self._called:
+ raise AirflowException('@task decorated functions can only be
called once. If you need to reuse '
+ 'it several times in a DAG, use the `copy`
method.')
+
+ # If we have no DAG, reinitialize class to capture DAGContext and DAG
default args.
+ if not self.has_dag():
+ self.__init__(python_callable=self.python_callable,
+ multiple_outputs=self.multiple_outputs,
+ **self._kwargs)
+
+ # Capture args/kwargs
+ self._op_args = args
+ self._op_kwargs = kwargs
+ self._called = True
+ return XComArg(self)
+
+ def copy(self, task_id: Optional[str] = None, **kwargs):
+ """
+ Create a copy of the task, allow to overwrite ctor kwargs if needed.
+
+ If alias is created a new DAGContext, apply defaults and set new DAG
as the operator DAG.
+
+ :param task_id: Task id for the new operator
+ :type task_id: Optional[str]
+ """
+ if task_id:
+ self._kwargs['task_id'] = task_id
+ return _PythonFunctionalOperator(
+ python_callable=self.python_callable,
+ multiple_outputs=self.multiple_outputs,
+ **{**kwargs, **self._kwargs}
+ )
+
+ def execute(self, context: Dict):
+ return_value = self.python_callable(*self._op_args, **self._op_kwargs)
+ self.log.info("Done. Returned value was: %s", return_value)
+ if not self.multiple_outputs:
+ return return_value
+ if isinstance(return_value, dict):
+ for key, value in return_value.items():
+ self.xcom_push(context, str(key), value)
+ elif isinstance(return_value, (list, tuple)):
+ for key, value in enumerate(return_value):
+ self.xcom_push(context, str(key), value)
+ return return_value
+
+
+def task(python_callable: Optional[Callable] = None, **kwargs):
+ """
+ Python operator decorator. Wraps a function into an Airflow operator.
+ Accepts kwargs for operator kwarg. Will try to wrap operator into DAG at
declaration or
+ on function invocation. Use alias to reuse function in the DAG.
+
+ :param python_callable: Function to decorate
+ :type python_callable: Optional[Callable]
+ :param multiple_outputs: if set, function return value will be
+ unrolled to multiple XCom values. List/Tuples will unroll to xcom
values
+ with index as key. Dict will unroll to xcom values with keys as keys.
+ Defaults to False.
+ :type multiple_outputs: bool
+
+ """
+ def wrapper(f):
+ """Python wrapper to generate PythonFunctionalOperator out of simple
python functions.
+ Used for Airflow functional interface
+ """
+ return _PythonFunctionalOperator(python_callable=f,
task_id=f.__name__, **kwargs)
+ if callable(python_callable):
+ return wrapper(python_callable)
+ elif python_callable is not None:
+ raise AirflowException('No args allowed while using @task, use kwargs
instead')
+ return wrapper
Review comment:
Yes, this code will fail when you do:
```
@task
def example(...)
...
```
decorators get function as the first arg. If we want to allow both kwargs
and no kwargs we need to do this small and more verbose approach.
##########
File path: airflow/operators/python.py
##########
@@ -145,6 +149,131 @@ def execute_callable(self):
return self.python_callable(*self.op_args, **self.op_kwargs)
+class _PythonFunctionalOperator(BaseOperator):
+ """
+ Wraps a Python callable and captures args/kwargs when called for execution.
+
+ :param python_callable: A reference to an object that is callable
+ :type python_callable: python callable
+ :param op_kwargs: a dictionary of keyword arguments that will get unpacked
+ in your function
+ :type op_kwargs: dict (templated)
+ :param op_args: a list of positional arguments that will get unpacked when
+ calling your callable
+ :type op_args: list (templated)
+ :param multiple_outputs: if set, function return value will be
+ unrolled to multiple XCom values. Dict will unroll to xcom values with
keys as keys.
+ Defaults to False.
+ :type multiple_outputs: bool
+ """
+
+ template_fields = ('op_args', 'op_kwargs')
+ ui_color = '#ffefeb'
+
+ # since we won't mutate the arguments, we should just do the shallow copy
+ # there are some cases we can't deepcopy the objects(e.g protobuf).
+ shallow_copy_attrs = ('python_callable',)
+
+ @apply_defaults
+ def __init__(
+ self,
+ python_callable: Callable,
+ op_args: Tuple[Any],
+ op_kwargs: Dict[str, Any],
+ multiple_outputs: bool = False,
+ **kwargs
+ ) -> None:
+ kwargs['task_id'] = self._get_unique_task_id(kwargs['task_id'],
kwargs.get('dag', None))
+ super().__init__(**kwargs)
Review comment:
Why is this preferred?
##########
File path: airflow/operators/python.py
##########
@@ -145,6 +149,131 @@ def execute_callable(self):
return self.python_callable(*self.op_args, **self.op_kwargs)
+class _PythonFunctionalOperator(BaseOperator):
+ """
+ Wraps a Python callable and captures args/kwargs when called for execution.
+
+ :param python_callable: A reference to an object that is callable
+ :type python_callable: python callable
+ :param op_kwargs: a dictionary of keyword arguments that will get unpacked
+ in your function
+ :type op_kwargs: dict (templated)
+ :param op_args: a list of positional arguments that will get unpacked when
+ calling your callable
+ :type op_args: list (templated)
+ :param multiple_outputs: if set, function return value will be
+ unrolled to multiple XCom values. Dict will unroll to xcom values with
keys as keys.
+ Defaults to False.
+ :type multiple_outputs: bool
+ """
+
+ template_fields = ('op_args', 'op_kwargs')
+ ui_color = '#ffefeb'
+
+ # since we won't mutate the arguments, we should just do the shallow copy
+ # there are some cases we can't deepcopy the objects(e.g protobuf).
+ shallow_copy_attrs = ('python_callable',)
+
+ @apply_defaults
+ def __init__(
+ self,
+ python_callable: Callable,
+ op_args: Tuple[Any],
+ op_kwargs: Dict[str, Any],
+ multiple_outputs: bool = False,
+ **kwargs
+ ) -> None:
+ kwargs['task_id'] = self._get_unique_task_id(kwargs['task_id'],
kwargs.get('dag', None))
+ super().__init__(**kwargs)
+ self.python_callable = python_callable
+
+ # Check that arguments can be binded
+ signature(python_callable).bind(*op_args, **op_kwargs)
+ self.multiple_outputs = multiple_outputs
+ self.op_args = op_args
+ self.op_kwargs = op_kwargs
+
+ @staticmethod
+ def _get_unique_task_id(task_id: str, dag: Optional[DAG]) -> str:
+ dag = dag or DagContext.get_current_dag()
+ if not dag or task_id not in dag.task_ids:
+ return task_id
+ core = re.split(r'__\d+$', task_id)[0]
+ suffixes = sorted(
+ [int(re.split(r'^.+__', task_id)[1])
+ for task_id in dag.task_ids
+ if re.match(rf'^{core}__\d+$', task_id)]
+ )
+ if not suffixes:
+ return f'{core}__1'
+ return f'{core}__{suffixes[-1] + 1}'
+
+ @staticmethod
+ def validate_python_callable(python_callable):
+ """Validate that python callable can be wrapped by operator.
+ Raises exception if invalid.
+
+ :param python_callable: Python object to be validated
+ :raises: TypeError, AirflowException
+ """
+ if not callable(python_callable):
+ raise TypeError('`python_callable` param must be callable')
+ if 'self' in signature(python_callable).parameters.keys():
+ raise AirflowException('@task does not support methods')
+
+ def execute(self, context: Dict):
+ return_value = self.python_callable(*self.op_args, **self.op_kwargs)
+ self.log.info("Done. Returned value was: %s", return_value)
+ if not self.multiple_outputs:
+ return return_value
+ if isinstance(return_value, dict):
+ for key in return_value.keys():
+ if not isinstance(key, str):
+ raise AirflowException('Returned dictionary keys must be
strings when using '
+ f'multiple_outputs, found {key}
({type(key)}) instead')
+ for key, value in return_value.items():
+ self.xcom_push(context, key, value)
+ else:
+ self.log.info(f'Returned output was type {type(return_value)}
expected dictionary '
+ 'for multiple_outputs')
+ return return_value
+
+
+def task(python_callable: Optional[Callable] = None, **kwargs):
+ """
+ Python operator decorator. Wraps a function into an Airflow operator.
+ Accepts kwargs for operator kwarg. Will try to wrap operator into DAG at
declaration or
+ on function invocation. Use alias to reuse function in the DAG.
+
+ :param python_callable: Function to decorate
+ :type python_callable: Optional[Callable]
+ :param multiple_outputs: if set, function return value will be
+ unrolled to multiple XCom values. List/Tuples will unroll to xcom
values
+ with index as key. Dict will unroll to xcom values with keys as keys.
+ Defaults to False.
+ :type multiple_outputs: bool
Review comment:
Added it here for visibility.
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