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Posted to commits@airflow.apache.org by as...@apache.org on 2024/10/13 14:55:39 UTC
(airflow) 01/02: Start porting over all the DAG defintion code to the Task SDK
This is an automated email from the ASF dual-hosted git repository.
ash pushed a commit to branch task-sdk-first-code
in repository https://gitbox.apache.org/repos/asf/airflow.git
commit 3c11050ad873e21febd200d07da789ce4f8dae01
Author: Ash Berlin-Taylor <as...@apache.org>
AuthorDate: Sat Oct 12 21:23:18 2024 +0100
Start porting over all the DAG defintion code to the Task SDK
By "definition code" we mean anything needed at definition/parse time
Anything to do with scheduling will stay elsewhere. At least for this very
first commint this duplicates the code from elsewhere; we might want to make
those extend these classes in the same PR so that we don't have duplicated
code.
[skip ci]
---
pyproject.toml | 1 +
task_sdk/pyproject.toml | 15 +-
.../airflow/sdk/definitions/__init__.py} | 24 -
.../airflow/sdk/definitions/abstractoperator.py | 160 +
.../src/airflow/sdk/definitions/baseoperator.py | 1016 +++++
.../src/airflow/sdk/definitions/contextmanager.py | 106 +
task_sdk/src/airflow/sdk/definitions/dag.py | 979 +++++
task_sdk/src/airflow/sdk/definitions/decorators.py | 42 +
task_sdk/src/airflow/sdk/definitions/edges.py | 191 +
task_sdk/src/airflow/sdk/definitions/mixins.py | 122 +
task_sdk/src/airflow/sdk/definitions/node.py | 192 +
task_sdk/src/airflow/sdk/definitions/task_group.py | 645 +++
.../airflow/sdk/exceptions.py} | 24 -
.../{pyproject.toml => src/airflow/sdk/types.py} | 45 +-
task_sdk/tests/defintions/test_dag.py | 78 +
uv.lock | 4220 ++++++++++++++++++++
16 files changed, 7793 insertions(+), 67 deletions(-)
diff --git a/pyproject.toml b/pyproject.toml
index 6edf4e5c711..3a3bde8e23a 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -590,6 +590,7 @@ explicit_package_bases = true
mypy_path = [
"$MYPY_CONFIG_FILE_DIR",
"$MYPY_CONFIG_FILE_DIR/providers/src",
+ "$MYPY_CONFIG_FILE_DIR/task_sdk/src",
]
[[tool.mypy.overrides]]
diff --git a/task_sdk/pyproject.toml b/task_sdk/pyproject.toml
index 149a9731ce9..b0a912d9f04 100644
--- a/task_sdk/pyproject.toml
+++ b/task_sdk/pyproject.toml
@@ -21,7 +21,12 @@ version = "0.1.0.dev0"
description = "Python Task SDK for Apache Airflow DAG Authors"
#readme = "README.md"
requires-python = ">=3.9, <3.13"
-dependencies = []
+dependencies = [
+ "attrs>=24.2.0",
+ "google-re2>=1.1.20240702",
+ "methodtools>=0.4.7",
+ "structlog>=24.4.0",
+]
[build-system]
requires = ["hatchling"]
@@ -33,8 +38,16 @@ packages = ["src/airflow"]
[tool.ruff]
extend = "../pyproject.toml"
src = ["src"]
+namespace-packages = ["src/airflow"]
[tool.ruff.lint.per-file-ignores]
# Ignore Doc rules et al for anything outside of tests
"!src/*" = ["D", "TID253", "S101", "TRY002"]
+
+[tool.uv]
+dev-dependencies = [
+ "pytest-asyncio>=0.24.0",
+ "pytest-mock>=3.14.0",
+ "pytest>=8.3.3",
+]
diff --git a/task_sdk/pyproject.toml b/task_sdk/src/airflow/sdk/definitions/__init__.py
similarity index 59%
copy from task_sdk/pyproject.toml
copy to task_sdk/src/airflow/sdk/definitions/__init__.py
index 149a9731ce9..13a83393a91 100644
--- a/task_sdk/pyproject.toml
+++ b/task_sdk/src/airflow/sdk/definitions/__init__.py
@@ -14,27 +14,3 @@
# KIND, either express or implied. See the License for the
# specific language governing permissions and limitations
# under the License.
-
-[project]
-name = "apache-airflow-task-sdk"
-version = "0.1.0.dev0"
-description = "Python Task SDK for Apache Airflow DAG Authors"
-#readme = "README.md"
-requires-python = ">=3.9, <3.13"
-dependencies = []
-
-[build-system]
-requires = ["hatchling"]
-build-backend = "hatchling.build"
-
-[tool.hatch.build.targets.wheel]
-packages = ["src/airflow"]
-
-[tool.ruff]
-extend = "../pyproject.toml"
-src = ["src"]
-
-[tool.ruff.lint.per-file-ignores]
-
-# Ignore Doc rules et al for anything outside of tests
-"!src/*" = ["D", "TID253", "S101", "TRY002"]
diff --git a/task_sdk/src/airflow/sdk/definitions/abstractoperator.py b/task_sdk/src/airflow/sdk/definitions/abstractoperator.py
new file mode 100644
index 00000000000..d37a478df3a
--- /dev/null
+++ b/task_sdk/src/airflow/sdk/definitions/abstractoperator.py
@@ -0,0 +1,160 @@
+#
+# 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.
+from __future__ import annotations
+
+import datetime
+from abc import abstractmethod
+from collections.abc import (
+ Collection,
+)
+from typing import (
+ TYPE_CHECKING,
+ Any,
+ ClassVar,
+)
+
+from .node import DAGNode
+
+# TaskStateChangeCallback = Callable[[Context], None]
+
+if TYPE_CHECKING:
+ from airflow.models.baseoperator import BaseOperator
+ from airflow.models.baseoperatorlink import BaseOperatorLink
+ from airflow.task.priority_strategy import PriorityWeightStrategy
+
+ from .dag import DAG
+
+DEFAULT_OWNER: str = "airflow"
+DEFAULT_POOL_SLOTS: int = 1
+DEFAULT_PRIORITY_WEIGHT: int = 1
+DEFAULT_EXECUTOR: str | None = None
+DEFAULT_QUEUE: str = "default"
+DEFAULT_IGNORE_FIRST_DEPENDS_ON_PAST: bool = False
+DEFAULT_WAIT_FOR_PAST_DEPENDS_BEFORE_SKIPPING: bool = False
+DEFAULT_RETRIES: int = 0
+DEFAULT_RETRY_DELAY: datetime.timedelta = datetime.timedelta(300)
+MAX_RETRY_DELAY: int = 24 * 60 * 60
+
+# DEFAULT_WEIGHT_RULE: WeightRule = WeightRule(
+# conf.get("core", "default_task_weight_rule", fallback=WeightRule.DOWNSTREAM)
+# )
+# DEFAULT_TRIGGER_RULE: TriggerRule = TriggerRule.ALL_SUCCESS
+DEFAULT_WEIGHT_RULE = 0
+DEFAULT_TRIGGER_RULE = "ALL_SUCCESS" # TriggerRule.ALL_SUCCESS
+DEFAULT_TASK_EXECUTION_TIMEOUT: datetime.timedelta | None = None
+
+
+class NotMapped(Exception):
+ """Raise if a task is neither mapped nor has any parent mapped groups."""
+
+
+class AbstractOperator(DAGNode):
+ """
+ Common implementation for operators, including unmapped and mapped.
+
+ This base class is more about sharing implementations, not defining a common
+ interface. Unfortunately it's difficult to use this as the common base class
+ for typing due to BaseOperator carrying too much historical baggage.
+
+ The union type ``from airflow.models.operator import Operator`` is easier
+ to use for typing purposes.
+
+ :meta private:
+ """
+
+ operator_class: type[BaseOperator] | dict[str, Any]
+
+ weight_rule: PriorityWeightStrategy
+ priority_weight: int
+
+ # Defines the operator level extra links.
+ operator_extra_links: Collection[BaseOperatorLink]
+
+ owner: str
+ task_id: str
+
+ outlets: list
+ inlets: list
+ # TODO:
+ # trigger_rule: TriggerRule
+ _needs_expansion: bool | None = None
+ _on_failure_fail_dagrun = False
+
+ HIDE_ATTRS_FROM_UI: ClassVar[frozenset[str]] = frozenset(
+ (
+ "log",
+ "dag", # We show dag_id, don't need to show this too
+ "node_id", # Duplicates task_id
+ "task_group", # Doesn't have a useful repr, no point showing in UI
+ "inherits_from_empty_operator", # impl detail
+ # Decide whether to start task execution from triggerer
+ "start_trigger_args",
+ "start_from_trigger",
+ # For compatibility with TG, for operators these are just the current task, no point showing
+ "roots",
+ "leaves",
+ # These lists are already shown via *_task_ids
+ "upstream_list",
+ "downstream_list",
+ # Not useful, implementation detail, already shown elsewhere
+ "global_operator_extra_link_dict",
+ "operator_extra_link_dict",
+ )
+ )
+
+ def get_dag(self) -> DAG | None:
+ raise NotImplementedError()
+
+ @property
+ def task_type(self) -> str:
+ raise NotImplementedError()
+
+ @property
+ def operator_name(self) -> str:
+ raise NotImplementedError()
+
+ @property
+ def inherits_from_empty_operator(self) -> bool:
+ raise NotImplementedError()
+
+ @property
+ def dag_id(self) -> str:
+ """Returns dag id if it has one or an adhoc + owner."""
+ dag = self.get_dag()
+ if dag:
+ return dag.dag_id
+ return f"adhoc_{self.owner}"
+
+ @property
+ def node_id(self) -> str:
+ return self.task_id
+
+ @property
+ @abstractmethod
+ def task_display_name(self) -> str: ...
+
+ @property
+ def label(self) -> str | None:
+ if self.task_display_name and self.task_display_name != self.task_id:
+ return self.task_display_name
+ # Prefix handling if no display is given is cloned from taskmixin for compatibility
+ tg = self.task_group
+ if tg and tg.node_id and tg.prefix_group_id:
+ # "task_group_id.task_id" -> "task_id"
+ return self.task_id[len(tg.node_id) + 1 :]
+ return self.task_id
diff --git a/task_sdk/src/airflow/sdk/definitions/baseoperator.py b/task_sdk/src/airflow/sdk/definitions/baseoperator.py
new file mode 100644
index 00000000000..c466f158cc9
--- /dev/null
+++ b/task_sdk/src/airflow/sdk/definitions/baseoperator.py
@@ -0,0 +1,1016 @@
+# 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.
+
+from __future__ import annotations
+
+import abc
+import collections.abc
+import contextlib
+import copy
+import inspect
+from collections.abc import Sequence
+from dataclasses import dataclass
+from functools import total_ordering, wraps
+from types import FunctionType
+from typing import TYPE_CHECKING, Any, ClassVar, TypeVar, cast
+
+from airflow.sdk.definitions.abstractoperator import (
+ DEFAULT_IGNORE_FIRST_DEPENDS_ON_PAST,
+ DEFAULT_OWNER,
+ DEFAULT_POOL_SLOTS,
+ DEFAULT_PRIORITY_WEIGHT,
+ DEFAULT_QUEUE,
+ DEFAULT_RETRIES,
+ DEFAULT_RETRY_DELAY,
+ DEFAULT_TASK_EXECUTION_TIMEOUT,
+ DEFAULT_TRIGGER_RULE,
+ DEFAULT_WAIT_FOR_PAST_DEPENDS_BEFORE_SKIPPING,
+ DEFAULT_WEIGHT_RULE,
+ AbstractOperator,
+)
+from airflow.sdk.definitions.decorators import fixup_decorator_warning_stack
+from airflow.sdk.definitions.node import validate_key
+
+T = TypeVar("T", bound=FunctionType)
+
+if TYPE_CHECKING:
+ # from ..execution_time.context import Context
+ class Context: ...
+
+ class ParamsDict: ...
+
+ from airflow.sdk.definitions.dag import DAG
+ from airflow.sdk.definitions.task_group import TaskGroup
+
+
+# TODO: Task-SDK
+AirflowException = RuntimeError
+ParamsDict = object
+
+
+def _get_parent_defaults(dag: DAG | None, task_group: TaskGroup | None) -> tuple[dict, ParamsDict]:
+ if not dag:
+ return {}, ParamsDict()
+ dag_args = copy.copy(dag.default_args)
+ dag_params = copy.deepcopy(dag.params)
+ if task_group:
+ if task_group.default_args and not isinstance(task_group.default_args, collections.abc.Mapping):
+ raise TypeError("default_args must be a mapping")
+ dag_args.update(task_group.default_args)
+ return dag_args, dag_params
+
+
+def get_merged_defaults(
+ dag: DAG | None,
+ task_group: TaskGroup | None,
+ task_params: collections.abc.MutableMapping | None,
+ task_default_args: dict | None,
+) -> tuple[dict, ParamsDict]:
+ args, params = _get_parent_defaults(dag, task_group)
+ if task_params:
+ if not isinstance(task_params, collections.abc.Mapping):
+ raise TypeError("params must be a mapping")
+ params.update(task_params)
+ if task_default_args:
+ if not isinstance(task_default_args, collections.abc.Mapping):
+ raise TypeError("default_args must be a mapping")
+ args.update(task_default_args)
+ with contextlib.suppress(KeyError):
+ params.update(task_default_args["params"] or {})
+ return args, params
+
+
+class BaseOperatorMeta(abc.ABCMeta):
+ """Metaclass of BaseOperator."""
+
+ @classmethod
+ def _apply_defaults(cls, func: T) -> T:
+ """
+ Look for an argument named "default_args", and fill the unspecified arguments from it.
+
+ Since python2.* isn't clear about which arguments are missing when
+ calling a function, and that this can be quite confusing with multi-level
+ inheritance and argument defaults, this decorator also alerts with
+ specific information about the missing arguments.
+ """
+ # Cache inspect.signature for the wrapper closure to avoid calling it
+ # at every decorated invocation. This is separate sig_cache created
+ # per decoration, i.e. each function decorated using apply_defaults will
+ # have a different sig_cache.
+ sig_cache = inspect.signature(func)
+ non_variadic_params = {
+ name: param
+ for (name, param) in sig_cache.parameters.items()
+ if param.name != "self" and param.kind not in (param.VAR_POSITIONAL, param.VAR_KEYWORD)
+ }
+ non_optional_args = {
+ name
+ for name, param in non_variadic_params.items()
+ if param.default == param.empty and name != "task_id"
+ }
+
+ fixup_decorator_warning_stack(func)
+
+ @wraps(func)
+ def apply_defaults(self: BaseOperator, *args: Any, **kwargs: Any) -> Any:
+ from airflow.sdk.definitions.contextmanager import DagContext, TaskGroupContext
+
+ if args:
+ raise AirflowException("Use keyword arguments when initializing operators")
+
+ instantiated_from_mapped = kwargs.pop(
+ "_airflow_from_mapped",
+ getattr(self, "_BaseOperator__from_mapped", False),
+ )
+
+ dag: DAG | None = kwargs.get("dag") or DagContext.get_current()
+ task_group: TaskGroup | None = kwargs.get("task_group")
+ if dag and not task_group:
+ task_group = TaskGroupContext.get_current(dag)
+
+ default_args, merged_params = get_merged_defaults(
+ dag=dag,
+ task_group=task_group,
+ task_params=kwargs.pop("params", None),
+ task_default_args=kwargs.pop("default_args", None),
+ )
+
+ for arg in sig_cache.parameters:
+ if arg not in kwargs and arg in default_args:
+ kwargs[arg] = default_args[arg]
+
+ missing_args = non_optional_args.difference(kwargs)
+ if len(missing_args) == 1:
+ raise AirflowException(f"missing keyword argument {missing_args.pop()!r}")
+ elif missing_args:
+ display = ", ".join(repr(a) for a in sorted(missing_args))
+ raise AirflowException(f"missing keyword arguments {display}")
+
+ if merged_params:
+ kwargs["params"] = merged_params
+
+ hook = getattr(self, "_hook_apply_defaults", None)
+ if hook:
+ args, kwargs = hook(**kwargs, default_args=default_args)
+ default_args = kwargs.pop("default_args", {})
+
+ if not hasattr(self, "_BaseOperator__init_kwargs"):
+ self._BaseOperator__init_kwargs = {}
+ self._BaseOperator__from_mapped = instantiated_from_mapped
+
+ result = func(self, **kwargs, default_args=default_args)
+
+ # Store the args passed to init -- we need them to support task.map serialization!
+ self._BaseOperator__init_kwargs.update(kwargs) # type: ignore
+
+ # Set upstream task defined by XComArgs passed to template fields of the operator.
+ # BUT: only do this _ONCE_, not once for each class in the hierarchy
+ if not instantiated_from_mapped and func == self.__init__.__wrapped__: # type: ignore[misc]
+ self.set_xcomargs_dependencies()
+ # Mark instance as instantiated.
+ self._BaseOperator__instantiated = True
+
+ return result
+
+ apply_defaults.__non_optional_args = non_optional_args # type: ignore
+ apply_defaults.__param_names = set(non_variadic_params) # type: ignore
+
+ return cast(T, apply_defaults)
+
+ def __new__(cls, name, bases, namespace, **kwargs):
+ # TODO: Task-SDK
+ # execute_method = namespace.get("execute")
+ # if callable(execute_method) and not getattr(execute_method, "__isabstractmethod__", False):
+ # namespace["execute"] = ExecutorSafeguard().decorator(execute_method)
+ new_cls = super().__new__(cls, name, bases, namespace, **kwargs)
+ with contextlib.suppress(KeyError):
+ # Update the partial descriptor with the class method, so it calls the actual function
+ # (but let subclasses override it if they need to)
+ # TODO: Task-SDK
+ # partial_desc = vars(new_cls)["partial"]
+ # if isinstance(partial_desc, _PartialDescriptor):
+ # partial_desc.class_method = classmethod(partial)
+ ...
+
+ # We patch `__init__` only if the class defines it.
+ if inspect.getmro(new_cls)[1].__init__ is not new_cls.__init__:
+ new_cls.__init__ = cls._apply_defaults(new_cls.__init__)
+
+ return new_cls
+
+
+@total_ordering
+@dataclass(
+ init=False,
+ repr=False,
+)
+class BaseOperator(AbstractOperator, metaclass=BaseOperatorMeta):
+ r"""
+ Abstract base class for all operators.
+
+ Since operators create objects that become nodes in the DAG, BaseOperator
+ contains many recursive methods for DAG crawling behavior. To derive from
+ this class, you are expected to override the constructor and the 'execute'
+ method.
+
+ Operators derived from this class should perform or trigger certain tasks
+ synchronously (wait for completion). Example of operators could be an
+ operator that runs a Pig job (PigOperator), a sensor operator that
+ waits for a partition to land in Hive (HiveSensorOperator), or one that
+ moves data from Hive to MySQL (Hive2MySqlOperator). Instances of these
+ operators (tasks) target specific operations, running specific scripts,
+ functions or data transfers.
+
+ This class is abstract and shouldn't be instantiated. Instantiating a
+ class derived from this one results in the creation of a task object,
+ which ultimately becomes a node in DAG objects. Task dependencies should
+ be set by using the set_upstream and/or set_downstream methods.
+
+ :param task_id: a unique, meaningful id for the task
+ :param owner: the owner of the task. Using a meaningful description
+ (e.g. user/person/team/role name) to clarify ownership is recommended.
+ :param email: the 'to' email address(es) used in email alerts. This can be a
+ single email or multiple ones. Multiple addresses can be specified as a
+ comma or semicolon separated string or by passing a list of strings.
+ :param email_on_retry: Indicates whether email alerts should be sent when a
+ task is retried
+ :param email_on_failure: Indicates whether email alerts should be sent when
+ a task failed
+ :param retries: the number of retries that should be performed before
+ failing the task
+ :param retry_delay: delay between retries, can be set as ``timedelta`` or
+ ``float`` seconds, which will be converted into ``timedelta``,
+ the default is ``timedelta(seconds=300)``.
+ :param retry_exponential_backoff: allow progressively longer waits between
+ retries by using exponential backoff algorithm on retry delay (delay
+ will be converted into seconds)
+ :param max_retry_delay: maximum delay interval between retries, can be set as
+ ``timedelta`` or ``float`` seconds, which will be converted into ``timedelta``.
+ :param start_date: The ``start_date`` for the task, determines
+ the ``execution_date`` for the first task instance. The best practice
+ is to have the start_date rounded
+ to your DAG's ``schedule_interval``. Daily jobs have their start_date
+ some day at 00:00:00, hourly jobs have their start_date at 00:00
+ of a specific hour. Note that Airflow simply looks at the latest
+ ``execution_date`` and adds the ``schedule_interval`` to determine
+ the next ``execution_date``. It is also very important
+ to note that different tasks' dependencies
+ need to line up in time. If task A depends on task B and their
+ start_date are offset in a way that their execution_date don't line
+ up, A's dependencies will never be met. If you are looking to delay
+ a task, for example running a daily task at 2AM, look into the
+ ``TimeSensor`` and ``TimeDeltaSensor``. We advise against using
+ dynamic ``start_date`` and recommend using fixed ones. Read the
+ FAQ entry about start_date for more information.
+ :param end_date: if specified, the scheduler won't go beyond this date
+ :param depends_on_past: when set to true, task instances will run
+ sequentially and only if the previous instance has succeeded or has been skipped.
+ The task instance for the start_date is allowed to run.
+ :param wait_for_past_depends_before_skipping: when set to true, if the task instance
+ should be marked as skipped, and depends_on_past is true, the ti will stay on None state
+ waiting the task of the previous run
+ :param wait_for_downstream: when set to true, an instance of task
+ X will wait for tasks immediately downstream of the previous instance
+ of task X to finish successfully or be skipped before it runs. This is useful if the
+ different instances of a task X alter the same asset, and this asset
+ is used by tasks downstream of task X. Note that depends_on_past
+ is forced to True wherever wait_for_downstream is used. Also note that
+ only tasks *immediately* downstream of the previous task instance are waited
+ for; the statuses of any tasks further downstream are ignored.
+ :param dag: a reference to the dag the task is attached to (if any)
+ :param priority_weight: priority weight of this task against other task.
+ This allows the executor to trigger higher priority tasks before
+ others when things get backed up. Set priority_weight as a higher
+ number for more important tasks.
+ :param weight_rule: weighting method used for the effective total
+ priority weight of the task. Options are:
+ ``{ downstream | upstream | absolute }`` default is ``downstream``
+ When set to ``downstream`` the effective weight of the task is the
+ aggregate sum of all downstream descendants. As a result, upstream
+ tasks will have higher weight and will be scheduled more aggressively
+ when using positive weight values. This is useful when you have
+ multiple dag run instances and desire to have all upstream tasks to
+ complete for all runs before each dag can continue processing
+ downstream tasks. When set to ``upstream`` the effective weight is the
+ aggregate sum of all upstream ancestors. This is the opposite where
+ downstream tasks have higher weight and will be scheduled more
+ aggressively when using positive weight values. This is useful when you
+ have multiple dag run instances and prefer to have each dag complete
+ before starting upstream tasks of other dags. When set to
+ ``absolute``, the effective weight is the exact ``priority_weight``
+ specified without additional weighting. You may want to do this when
+ you know exactly what priority weight each task should have.
+ Additionally, when set to ``absolute``, there is bonus effect of
+ significantly speeding up the task creation process as for very large
+ DAGs. Options can be set as string or using the constants defined in
+ the static class ``airflow.utils.WeightRule``
+ |experimental|
+ Since 2.9.0, Airflow allows to define custom priority weight strategy,
+ by creating a subclass of
+ ``airflow.task.priority_strategy.PriorityWeightStrategy`` and registering
+ in a plugin, then providing the class path or the class instance via
+ ``weight_rule`` parameter. The custom priority weight strategy will be
+ used to calculate the effective total priority weight of the task instance.
+ :param queue: which queue to target when running this job. Not
+ all executors implement queue management, the CeleryExecutor
+ does support targeting specific queues.
+ :param pool: the slot pool this task should run in, slot pools are a
+ way to limit concurrency for certain tasks
+ :param pool_slots: the number of pool slots this task should use (>= 1)
+ Values less than 1 are not allowed.
+ :param sla: time by which the job is expected to succeed. Note that
+ this represents the ``timedelta`` after the period is closed. For
+ example if you set an SLA of 1 hour, the scheduler would send an email
+ soon after 1:00AM on the ``2016-01-02`` if the ``2016-01-01`` instance
+ has not succeeded yet.
+ The scheduler pays special attention for jobs with an SLA and
+ sends alert
+ emails for SLA misses. SLA misses are also recorded in the database
+ for future reference. All tasks that share the same SLA time
+ get bundled in a single email, sent soon after that time. SLA
+ notification are sent once and only once for each task instance.
+ :param execution_timeout: max time allowed for the execution of
+ this task instance, if it goes beyond it will raise and fail.
+ :param on_failure_callback: a function or list of functions to be called when a task instance
+ of this task fails. a context dictionary is passed as a single
+ parameter to this function. Context contains references to related
+ objects to the task instance and is documented under the macros
+ section of the API.
+ :param on_execute_callback: much like the ``on_failure_callback`` except
+ that it is executed right before the task is executed.
+ :param on_retry_callback: much like the ``on_failure_callback`` except
+ that it is executed when retries occur.
+ :param on_success_callback: much like the ``on_failure_callback`` except
+ that it is executed when the task succeeds.
+ :param on_skipped_callback: much like the ``on_failure_callback`` except
+ that it is executed when skipped occur; this callback will be called only if AirflowSkipException get raised.
+ Explicitly it is NOT called if a task is not started to be executed because of a preceding branching
+ decision in the DAG or a trigger rule which causes execution to skip so that the task execution
+ is never scheduled.
+ :param pre_execute: a function to be called immediately before task
+ execution, receiving a context dictionary; raising an exception will
+ prevent the task from being executed.
+
+ |experimental|
+ :param post_execute: a function to be called immediately after task
+ execution, receiving a context dictionary and task result; raising an
+ exception will prevent the task from succeeding.
+
+ |experimental|
+ :param trigger_rule: defines the rule by which dependencies are applied
+ for the task to get triggered. Options are:
+ ``{ all_success | all_failed | all_done | all_skipped | one_success | one_done |
+ one_failed | none_failed | none_failed_min_one_success | none_skipped | always}``
+ default is ``all_success``. Options can be set as string or
+ using the constants defined in the static class
+ ``airflow.utils.TriggerRule``
+ :param resources: A map of resource parameter names (the argument names of the
+ Resources constructor) to their values.
+ :param run_as_user: unix username to impersonate while running the task
+ :param max_active_tis_per_dag: When set, a task will be able to limit the concurrent
+ runs across execution_dates.
+ :param max_active_tis_per_dagrun: When set, a task will be able to limit the concurrent
+ task instances per DAG run.
+ :param executor: Which executor to target when running this task. NOT YET SUPPORTED
+ :param executor_config: Additional task-level configuration parameters that are
+ interpreted by a specific executor. Parameters are namespaced by the name of
+ executor.
+
+ **Example**: to run this task in a specific docker container through
+ the KubernetesExecutor ::
+
+ MyOperator(..., executor_config={"KubernetesExecutor": {"image": "myCustomDockerImage"}})
+
+ :param do_xcom_push: if True, an XCom is pushed containing the Operator's
+ result
+ :param multiple_outputs: if True and do_xcom_push is True, pushes multiple XComs, one for each
+ key in the returned dictionary result. If False and do_xcom_push is True, pushes a single XCom.
+ :param task_group: The TaskGroup to which the task should belong. This is typically provided when not
+ using a TaskGroup as a context manager.
+ :param doc: Add documentation or notes to your Task objects that is visible in
+ Task Instance details View in the Webserver
+ :param doc_md: Add documentation (in Markdown format) or notes to your Task objects
+ that is visible in Task Instance details View in the Webserver
+ :param doc_rst: Add documentation (in RST format) or notes to your Task objects
+ that is visible in Task Instance details View in the Webserver
+ :param doc_json: Add documentation (in JSON format) or notes to your Task objects
+ that is visible in Task Instance details View in the Webserver
+ :param doc_yaml: Add documentation (in YAML format) or notes to your Task objects
+ that is visible in Task Instance details View in the Webserver
+ :param task_display_name: The display name of the task which appears on the UI.
+ :param logger_name: Name of the logger used by the Operator to emit logs.
+ If set to `None` (default), the logger name will fall back to
+ `airflow.task.operators.{class.__module__}.{class.__name__}` (e.g. SimpleHttpOperator will have
+ *airflow.task.operators.airflow.providers.http.operators.http.SimpleHttpOperator* as logger).
+ :param allow_nested_operators: if True, when an operator is executed within another one a warning message
+ will be logged. If False, then an exception will be raised if the operator is badly used (e.g. nested
+ within another one). In future releases of Airflow this parameter will be removed and an exception
+ will always be thrown when operators are nested within each other (default is True).
+
+ **Example**: example of a bad operator mixin usage::
+
+ @task(provide_context=True)
+ def say_hello_world(**context):
+ hello_world_task = BashOperator(
+ task_id="hello_world_task",
+ bash_command="python -c \"print('Hello, world!')\"",
+ dag=dag,
+ )
+ hello_world_task.execute(context)
+ """
+
+ # Implementing Operator.
+ template_fields: ClassVar[Sequence[str]] = ()
+ template_ext: ClassVar[Sequence[str]] = ()
+
+ template_fields_renderers: ClassVar[dict[str, str]] = {}
+
+ # Defines the color in the UI
+ ui_color: str = "#fff"
+ ui_fgcolor: str = "#000"
+
+ pool: str = ""
+
+ # TODO: Mapping
+ # partial: Callable[..., OperatorPartial] = _PartialDescriptor() # type: ignore
+
+ _comps = {
+ "task_id",
+ "dag_id",
+ "owner",
+ "email",
+ "email_on_retry",
+ "retry_delay",
+ "retry_exponential_backoff",
+ "max_retry_delay",
+ "start_date",
+ "end_date",
+ "depends_on_past",
+ "wait_for_downstream",
+ "priority_weight",
+ "sla",
+ "execution_timeout",
+ "on_execute_callback",
+ "on_failure_callback",
+ "on_success_callback",
+ "on_retry_callback",
+ "on_skipped_callback",
+ "do_xcom_push",
+ "multiple_outputs",
+ "allow_nested_operators",
+ "executor",
+ }
+
+ # Defines if the operator supports lineage without manual definitions
+ supports_lineage = False
+
+ # If True then the class constructor was called
+ __instantiated = False
+ # List of args as passed to `init()`, after apply_defaults() has been updated. Used to "recreate" the task
+ # when mapping
+ __init_kwargs: dict[str, Any]
+
+ # Set to True before calling execute method
+ _lock_for_execution = False
+
+ # Set to True for an operator instantiated by a mapped operator.
+ __from_mapped = False
+
+ # TODO:
+ # start_trigger_args: StartTriggerArgs | None = None
+ # start_from_trigger: bool = False
+
+ def __init__(
+ self,
+ task_id: str,
+ owner: str = DEFAULT_OWNER,
+ email: str | Iterable[str] | None = None,
+ retries: int | None = DEFAULT_RETRIES,
+ retry_delay: timedelta | float = DEFAULT_RETRY_DELAY,
+ retry_exponential_backoff: bool = False,
+ max_retry_delay: timedelta | float | None = None,
+ start_date: datetime | None = None,
+ end_date: datetime | None = None,
+ depends_on_past: bool = False,
+ ignore_first_depends_on_past: bool = DEFAULT_IGNORE_FIRST_DEPENDS_ON_PAST,
+ wait_for_past_depends_before_skipping: bool = DEFAULT_WAIT_FOR_PAST_DEPENDS_BEFORE_SKIPPING,
+ wait_for_downstream: bool = False,
+ dag: DAG | None = None,
+ params: MutableMapping | None = None,
+ default_args: dict | None = None,
+ priority_weight: int = DEFAULT_PRIORITY_WEIGHT,
+ # TODO:
+ # weight_rule: str | PriorityWeightStrategy = DEFAULT_WEIGHT_RULE,
+ weight_rule: str = DEFAULT_WEIGHT_RULE,
+ queue: str = DEFAULT_QUEUE,
+ pool: str | None = None,
+ pool_slots: int = DEFAULT_POOL_SLOTS,
+ sla: timedelta | None = None,
+ execution_timeout: timedelta | None = DEFAULT_TASK_EXECUTION_TIMEOUT,
+ # on_execute_callback: None | TaskStateChangeCallback | list[TaskStateChangeCallback] = None,
+ # on_failure_callback: None | TaskStateChangeCallback | list[TaskStateChangeCallback] = None,
+ # on_success_callback: None | TaskStateChangeCallback | list[TaskStateChangeCallback] = None,
+ # on_retry_callback: None | TaskStateChangeCallback | list[TaskStateChangeCallback] = None,
+ # on_skipped_callback: None | TaskStateChangeCallback | list[TaskStateChangeCallback] = None,
+ # pre_execute: TaskPreExecuteHook | None = None,
+ # post_execute: TaskPostExecuteHook | None = None,
+ trigger_rule: str = DEFAULT_TRIGGER_RULE,
+ resources: dict[str, Any] | None = None,
+ run_as_user: str | None = None,
+ task_concurrency: int | None = None,
+ map_index_template: str | None = None,
+ max_active_tis_per_dag: int | None = None,
+ max_active_tis_per_dagrun: int | None = None,
+ executor: str | None = None,
+ executor_config: dict | None = None,
+ do_xcom_push: bool = True,
+ multiple_outputs: bool = False,
+ inlets: Any | None = None,
+ outlets: Any | None = None,
+ task_group: TaskGroup | None = None,
+ doc: str | None = None,
+ doc_md: str | None = None,
+ doc_json: str | None = None,
+ doc_yaml: str | None = None,
+ doc_rst: str | None = None,
+ task_display_name: str | None = None,
+ logger_name: str | None = None,
+ allow_nested_operators: bool = True,
+ **kwargs: Any,
+ ):
+ from airflow.sdk.definitions.contextmanager import DagContext, TaskGroupContext
+
+ self.__init_kwargs = {}
+
+ super().__init__()
+
+ kwargs.pop("_airflow_mapped_validation_only", None)
+ if kwargs:
+ raise RuntimeError(
+ f"Invalid arguments were passed to {self.__class__.__name__} (task_id: {task_id}). "
+ + f"Invalid arguments were:\n**kwargs: {kwargs}",
+ )
+ validate_key(task_id)
+
+ dag = dag or DagContext.get_current()
+ task_group = task_group or TaskGroupContext.get_current(dag)
+
+ self.task_id = task_group.child_id(task_id) if task_group else task_id
+ if not self.__from_mapped and task_group:
+ task_group.add(self)
+
+ self.owner = owner
+ self.email = email
+
+ if execution_timeout is not None and not isinstance(execution_timeout, timedelta):
+ raise ValueError(
+ f"execution_timeout must be timedelta object but passed as type: {type(execution_timeout)}"
+ )
+ self.execution_timeout = execution_timeout
+
+ # TODO:
+ # self.on_execute_callback = on_execute_callback
+ # self.on_failure_callback = on_failure_callback
+ # self.on_success_callback = on_success_callback
+ # self.on_retry_callback = on_retry_callback
+ # self.on_skipped_callback = on_skipped_callback
+ # self._pre_execute_hook = pre_execute
+ # self._post_execute_hook = post_execute
+
+ if start_date and not isinstance(start_date, datetime):
+ self.log.warning("start_date for %s isn't datetime.datetime", self)
+ elif start_date:
+ self.start_date = timezone.convert_to_utc(start_date)
+
+ if end_date:
+ self.end_date = timezone.convert_to_utc(end_date)
+
+ if executor:
+ warnings.warn(
+ "Specifying executors for operators is not yet supported, the value {executor!r} will have no effect",
+ category=UserWarning,
+ stacklevel=2,
+ )
+ self.executor = executor
+ self.executor_config = executor_config or {}
+ self.run_as_user = run_as_user
+ # TODO:
+ # self.retries = parse_retries(retries)
+ self.retries = int(retries)
+ self.queue = queue
+ self.pool = "default" if pool is None else pool
+ self.pool_slots = pool_slots
+ if self.pool_slots < 1:
+ dag_str = f" in dag {dag.dag_id}" if dag else ""
+ raise ValueError(f"pool slots for {self.task_id}{dag_str} cannot be less than 1")
+ self.sla = sla
+
+ """
+ if trigger_rule == "none_failed_or_skipped":
+ warnings.warn(
+ "none_failed_or_skipped Trigger Rule is deprecated. "
+ "Please use `none_failed_min_one_success`.",
+ RemovedInAirflow3Warning,
+ stacklevel=2,
+ )
+ trigger_rule = TriggerRule.NONE_FAILED_MIN_ONE_SUCCESS
+
+ # if not TriggerRule.is_valid(trigger_rule):
+ # raise AirflowException(
+ # f"The trigger_rule must be one of {TriggerRule.all_triggers()},"
+ # f"'{dag.dag_id if dag else ''}.{task_id}'; received '{trigger_rule}'."
+ # )
+ #
+ # self.trigger_rule: TriggerRule = TriggerRule(trigger_rule)
+ # FailStopDagInvalidTriggerRule.check(dag=dag, trigger_rule=self.trigger_rule)
+
+ self.depends_on_past: bool = depends_on_past
+ self.ignore_first_depends_on_past: bool = ignore_first_depends_on_past
+ self.wait_for_past_depends_before_skipping: bool = wait_for_past_depends_before_skipping
+ self.wait_for_downstream: bool = wait_for_downstream
+ if wait_for_downstream:
+ self.depends_on_past = True
+
+ self.retry_delay = coerce_timedelta(retry_delay, key="retry_delay")
+ self.retry_exponential_backoff = retry_exponential_backoff
+ self.max_retry_delay = (
+ max_retry_delay
+ if max_retry_delay is None
+ else coerce_timedelta(max_retry_delay, key="max_retry_delay")
+ )
+
+ # At execution_time this becomes a normal dict
+ self.params: ParamsDict | dict = ParamsDict(params)
+ if priority_weight is not None and not isinstance(priority_weight, int):
+ raise AirflowException(
+ f"`priority_weight` for task '{self.task_id}' only accepts integers, "
+ f"received '{type(priority_weight)}'."
+ )
+ self.priority_weight = priority_weight
+ self.weight_rule = validate_and_load_priority_weight_strategy(weight_rule)
+ self.resources = coerce_resources(resources)
+ if task_concurrency and not max_active_tis_per_dag:
+ # TODO: Remove in Airflow 3.0
+ warnings.warn(
+ "The 'task_concurrency' parameter is deprecated. Please use 'max_active_tis_per_dag'.",
+ RemovedInAirflow3Warning,
+ stacklevel=2,
+ )
+ max_active_tis_per_dag = task_concurrency
+
+ """
+ self.max_active_tis_per_dag: int | None = max_active_tis_per_dag
+ self.max_active_tis_per_dagrun: int | None = max_active_tis_per_dagrun
+ self.do_xcom_push: bool = do_xcom_push
+ self.map_index_template: str | None = map_index_template
+ self.multiple_outputs: bool = multiple_outputs
+
+ self.doc_md = doc_md
+ self.doc_json = doc_json
+ self.doc_yaml = doc_yaml
+ self.doc_rst = doc_rst
+ self.doc = doc
+ # Populate the display field only if provided and different from task id
+ self._task_display_property_value = (
+ task_display_name if task_display_name and task_display_name != task_id else None
+ )
+
+ if dag:
+ self.dag = dag
+
+ """
+ self._log_config_logger_name = "airflow.task.operators"
+ self._logger_name = logger_name
+ self.allow_nested_operators: bool = allow_nested_operators
+
+ # Lineage
+ self.inlets: list = []
+ self.outlets: list = []
+
+ if inlets:
+ self.inlets = (
+ inlets
+ if isinstance(inlets, list)
+ else [
+ inlets,
+ ]
+ )
+
+ if outlets:
+ self.outlets = (
+ outlets
+ if isinstance(outlets, list)
+ else [
+ outlets,
+ ]
+ )
+
+ if isinstance(self.template_fields, str):
+ warnings.warn(
+ f"The `template_fields` value for {self.task_type} is a string "
+ "but should be a list or tuple of string. Wrapping it in a list for execution. "
+ f"Please update {self.task_type} accordingly.",
+ UserWarning,
+ stacklevel=2,
+ )
+ self.template_fields = [self.template_fields]
+
+ self._is_setup = False
+ self._is_teardown = False
+ if SetupTeardownContext.active:
+ SetupTeardownContext.update_context_map(self)
+
+ validate_instance_args(self, BASEOPERATOR_ARGS_EXPECTED_TYPES)
+ """
+
+ def __eq__(self, other):
+ if type(self) is type(other):
+ # Use getattr() instead of __dict__ as __dict__ doesn't return
+ # correct values for properties.
+ return all(getattr(self, c, None) == getattr(other, c, None) for c in self._comps)
+ return False
+
+ def __ne__(self, other):
+ return not self == other
+
+ def __hash__(self):
+ hash_components = [type(self)]
+ for component in self._comps:
+ val = getattr(self, component, None)
+ try:
+ hash(val)
+ hash_components.append(val)
+ except TypeError:
+ hash_components.append(repr(val))
+ return hash(tuple(hash_components))
+
+ # including lineage information
+ def __or__(self, other):
+ """
+ Return [This Operator] | [Operator].
+
+ The inlets of other will be set to pick up the outlets from this operator.
+ Other will be set as a downstream task of this operator.
+ """
+ if isinstance(other, BaseOperator):
+ if not self.outlets and not self.supports_lineage:
+ raise ValueError("No outlets defined for this operator")
+ other.add_inlets([self.task_id])
+ self.set_downstream(other)
+ else:
+ raise TypeError(f"Right hand side ({other}) is not an Operator")
+
+ return self
+
+ # /Composing Operators ---------------------------------------------
+
+ def __gt__(self, other):
+ """
+ Return [Operator] > [Outlet].
+
+ If other is an attr annotated object it is set as an outlet of this Operator.
+ """
+ if not isinstance(other, Iterable):
+ other = [other]
+
+ for obj in other:
+ if not attrs.has(obj):
+ raise TypeError(f"Left hand side ({obj}) is not an outlet")
+ self.add_outlets(other)
+
+ return self
+
+ def __lt__(self, other):
+ """
+ Return [Inlet] > [Operator] or [Operator] < [Inlet].
+
+ If other is an attr annotated object it is set as an inlet to this operator.
+ """
+ if not isinstance(other, Iterable):
+ other = [other]
+
+ for obj in other:
+ if not attr.has(obj):
+ raise TypeError(f"{obj} cannot be an inlet")
+ self.add_inlets(other)
+
+ return self
+
+ def __setattr__(self, key, value):
+ super().__setattr__(key, value)
+ if self.__from_mapped or self._lock_for_execution:
+ return # Skip any custom behavior for validation and during execute.
+ if key in self.__init_kwargs:
+ self.__init_kwargs[key] = value
+ if self.__instantiated and key in self.template_fields:
+ # Resolve upstreams set by assigning an XComArg after initializing
+ # an operator, example:
+ # op = BashOperator()
+ # op.bash_command = "sleep 1"
+ self.set_xcomargs_dependencies()
+
+ def add_inlets(self, inlets: Iterable[Any]):
+ """Set inlets to this operator."""
+ self.inlets.extend(inlets)
+
+ def add_outlets(self, outlets: Iterable[Any]):
+ """Define the outlets of this operator."""
+ self.outlets.extend(outlets)
+
+ def get_dag(self) -> DAG | None:
+ return self._dag
+
+ @property # type: ignore[override]
+ def dag(self) -> DAG: # type: ignore[override]
+ """Returns the Operator's DAG if set, otherwise raises an error."""
+ if self._dag:
+ return self._dag
+ else:
+ raise RuntimeError(f"Operator {self} has not been assigned to a DAG yet")
+
+ @dag.setter
+ def dag(self, dag: DAG | None):
+ """Operators can be assigned to one DAG, one time. Repeat assignments to that same DAG are ok."""
+ from .dag import DAG
+
+ if dag is None:
+ self._dag = None
+ return
+ if not isinstance(dag, DAG):
+ raise TypeError(f"Expected DAG; received {dag.__class__.__name__}")
+ elif self.has_dag() and self.dag is not dag:
+ raise ValueError(f"The DAG assigned to {self} can not be changed.")
+
+ if self.__from_mapped:
+ pass # Don't add to DAG -- the mapped task takes the place.
+ elif dag.task_dict.get(self.task_id) is not self:
+ dag.add_task(self)
+
+ self._dag = dag
+
+ @property
+ def task_display_name(self) -> str:
+ return self._task_display_property_value or self.task_id
+
+ def has_dag(self):
+ """Return True if the Operator has been assigned to a DAG."""
+ return self._dag is not None
+
+ def set_xcomargs_dependencies(self) -> None:
+ """
+ Resolve upstream dependencies of a task.
+
+ In this way passing an ``XComArg`` as value for a template field
+ will result in creating upstream relation between two tasks.
+
+ **Example**: ::
+
+ with DAG(...):
+ generate_content = GenerateContentOperator(task_id="generate_content")
+ send_email = EmailOperator(..., html_content=generate_content.output)
+
+ # This is equivalent to
+ with DAG(...):
+ generate_content = GenerateContentOperator(task_id="generate_content")
+ send_email = EmailOperator(..., html_content="{{ task_instance.xcom_pull('generate_content') }}")
+ generate_content >> send_email
+
+ """
+ from airflow.models.xcom_arg import XComArg
+
+ for field in self.template_fields:
+ if hasattr(self, field):
+ arg = getattr(self, field)
+ XComArg.apply_upstream_relationship(self, arg)
+
+ def on_kill(self) -> None:
+ """
+ Override this method to clean up subprocesses when a task instance gets killed.
+
+ Any use of the threading, subprocess or multiprocessing module within an
+ operator needs to be cleaned up, or it will leave ghost processes behind.
+ """
+
+ def __repr__(self):
+ return f"<Task({self.task_type}): {self.task_id}>"
+
+ @property
+ def operator_class(self) -> type[BaseOperator]: # type: ignore[override]
+ return self.__class__
+
+ @property
+ def task_type(self) -> str:
+ """@property: type of the task."""
+ return self.__class__.__name__
+
+ @property
+ def operator_name(self) -> str:
+ """@property: use a more friendly display name for the operator, if set."""
+ try:
+ return self.custom_operator_name # type: ignore
+ except AttributeError:
+ return self.task_type
+
+ @property
+ def roots(self) -> list[BaseOperator]:
+ """Required by DAGNode."""
+ return [self]
+
+ @property
+ def leaves(self) -> list[BaseOperator]:
+ """Required by DAGNode."""
+ return [self]
+
+ @property
+ def output(self) -> XComArg:
+ """Returns reference to XCom pushed by current operator."""
+ from airflow.models.xcom_arg import XComArg
+
+ return XComArg(operator=self)
+
+ @classmethod
+ def get_serialized_fields(cls):
+ """Stringified DAGs and operators contain exactly these fields."""
+ if not cls.__serialized_fields:
+ from airflow.sdk.definitions.contextmanager import DagContext
+
+ # make sure the following "fake" task is not added to current active
+ # dag in context, otherwise, it will result in
+ # `RuntimeError: dictionary changed size during iteration`
+ # Exception in SerializedDAG.serialize_dag() call.
+ DagContext.push(None)
+ cls.__serialized_fields = frozenset(
+ vars(BaseOperator(task_id="test")).keys()
+ - {
+ "upstream_task_ids",
+ "default_args",
+ "dag",
+ "_dag",
+ "label",
+ "_BaseOperator__instantiated",
+ "_BaseOperator__init_kwargs",
+ "_BaseOperator__from_mapped",
+ "_is_setup",
+ "_is_teardown",
+ "_on_failure_fail_dagrun",
+ }
+ | { # Class level defaults need to be added to this list
+ "start_date",
+ "end_date",
+ "_task_type",
+ "_operator_name",
+ "subdag",
+ "ui_color",
+ "ui_fgcolor",
+ "template_ext",
+ "template_fields",
+ "template_fields_renderers",
+ "params",
+ "is_setup",
+ "is_teardown",
+ "on_failure_fail_dagrun",
+ "map_index_template",
+ "start_trigger_args",
+ "_needs_expansion",
+ "start_from_trigger",
+ }
+ )
+ DagContext.pop()
+
+ return cls.__serialized_fields
+
+ # def serialize_for_task_group(self) -> tuple[DagAttributeTypes, Any]:
+ # """Serialize; required by DAGNode."""
+ # return DagAttributeTypes.OP, self.task_id
+
+ @property
+ def inherits_from_empty_operator(self):
+ """Used to determine if an Operator is inherited from EmptyOperator."""
+ # This looks like `isinstance(self, EmptyOperator) would work, but this also
+ # needs to cope when `self` is a Serialized instance of a EmptyOperator or one
+ # of its subclasses (which don't inherit from anything but BaseOperator).
+ return getattr(self, "_is_empty", False)
+
+ def execute(self, context: Context) -> Any:
+ """
+ Derive when creating an operator.
+
+ Context is the same dictionary used as when rendering jinja templates.
+
+ Refer to get_template_context for more context.
+ """
+ raise NotImplementedError()
diff --git a/task_sdk/src/airflow/sdk/definitions/contextmanager.py b/task_sdk/src/airflow/sdk/definitions/contextmanager.py
new file mode 100644
index 00000000000..fb160e06b35
--- /dev/null
+++ b/task_sdk/src/airflow/sdk/definitions/contextmanager.py
@@ -0,0 +1,106 @@
+#
+# 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.
+from __future__ import annotations
+
+from collections import deque
+from types import ModuleType
+from typing import Generic, TypeVar
+
+from airflow.sdk.definitions.dag import DAG
+from airflow.sdk.definitions.task_group import TaskGroup
+
+T = TypeVar("T")
+
+
+class ContextStack(Generic[T]):
+ active: bool = False
+ _context: deque[T]
+
+ def __init_subclass__(cls) -> None:
+ cls._context = deque()
+ return super().__init_subclass__()
+
+ @classmethod
+ def push(cls, obj: T):
+ cls._context.appendleft(obj)
+ cls.active = True
+
+ @classmethod
+ def pop(cls) -> T | None:
+ return cls._context.popleft()
+
+ @classmethod
+ def get_current(cls) -> T | None:
+ try:
+ return cls._context[0]
+ except IndexError:
+ return None
+
+ @classmethod
+ def is_active(cls) -> bool:
+ """The active property says if any object is currently in scope."""
+ try:
+ cls._context[0]
+ return True
+ except IndexError:
+ return False
+
+
+class DagContext(ContextStack[DAG]):
+ """
+ DAG context is used to keep the current DAG when DAG is used as ContextManager.
+
+ You can use DAG as context:
+
+ .. code-block:: python
+
+ with DAG(
+ dag_id="example_dag",
+ default_args=default_args,
+ schedule="0 0 * * *",
+ dagrun_timeout=timedelta(minutes=60),
+ ) as dag:
+ ...
+
+ If you do this the context stores the DAG and whenever new task is created, it will use
+ such stored DAG as the parent DAG.
+
+ """
+
+ autoregistered_dags: set[tuple[DAG, ModuleType]] = set()
+ current_autoregister_module_name: str | None = None
+
+ @classmethod
+ def pop(cls) -> DAG | None:
+ dag = super().pop()
+ # In a few cases around serialization we explicitly push None in to the stack
+ if cls.current_autoregister_module_name is not None and dag and getattr(dag, "auto_register", True):
+ # mod = sys.modules[cls.current_autoregister_module_name]
+ cls.autoregistered_dags.add((dag, None))
+
+
+class TaskGroupContext(ContextStack[TaskGroup]):
+ """TaskGroup context is used to keep the current TaskGroup when TaskGroup is used as ContextManager."""
+
+ @classmethod
+ def get_current(cls, dag: DAG | None = None) -> TaskGroup | None:
+ if current := super().get_current():
+ return current
+ if dag := dag or DagContext.get_current():
+ # If there's currently a DAG but no TaskGroup, return the root TaskGroup of the dag.
+ return dag.task_group
diff --git a/task_sdk/src/airflow/sdk/definitions/dag.py b/task_sdk/src/airflow/sdk/definitions/dag.py
new file mode 100644
index 00000000000..8a2799d0f51
--- /dev/null
+++ b/task_sdk/src/airflow/sdk/definitions/dag.py
@@ -0,0 +1,979 @@
+#
+# 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.
+from __future__ import annotations
+
+import copy
+import functools
+import itertools
+import logging
+import os
+import pathlib
+import sys
+import weakref
+from collections import abc
+from collections.abc import Collection, Iterable, Iterator
+from datetime import datetime, timedelta
+from inspect import signature
+from re import Pattern
+from typing import (
+ TYPE_CHECKING,
+ Any,
+ Callable,
+ ClassVar,
+ Self,
+ Union,
+ cast,
+)
+from urllib.parse import urlsplit
+
+import attrs
+import jinja2
+import re2
+from dateutil.relativedelta import relativedelta
+
+import airflow.templates
+from airflow import settings
+from airflow.assets import Asset, AssetAlias, BaseAsset
+from airflow.configuration import conf as airflow_conf
+from airflow.exceptions import (
+ AirflowException,
+ DuplicateTaskIdFound,
+ FailStopDagInvalidTriggerRule,
+ ParamValidationError,
+ TaskNotFound,
+)
+from airflow.models.param import DagParam
+from airflow.models.taskinstance import (
+ Context,
+)
+from airflow.sdk.definitions.abstractoperator import AbstractOperator
+from airflow.sdk.definitions.baseoperator import BaseOperator
+from airflow.stats import Stats
+from airflow.timetables.base import Timetable
+from airflow.utils.dag_cycle_tester import check_cycle
+from airflow.utils.decorators import fixup_decorator_warning_stack
+from airflow.utils.trigger_rule import TriggerRule
+from airflow.utils.types import NOTSET, EdgeInfoType
+
+if TYPE_CHECKING:
+ from airflow.decorators import TaskDecoratorCollection
+ from airflow.models.operator import Operator
+ from airflow.utils.task_group import TaskGroup
+
+log = logging.getLogger(__name__)
+
+DEFAULT_VIEW_PRESETS = ["grid", "graph", "duration", "gantt", "landing_times"]
+ORIENTATION_PRESETS = ["LR", "TB", "RL", "BT"]
+
+TAG_MAX_LEN = 100
+
+DagStateChangeCallback = Callable[[Context], None]
+ScheduleInterval = Union[None, str, timedelta, relativedelta]
+
+ScheduleArg = Union[
+ ScheduleInterval,
+ Timetable,
+ BaseAsset,
+ Collection[Union["Asset", "AssetAlias"]],
+]
+
+
+# Defined as a function so that we can avoid import cycles
+def _create_root_group(dag: DAG) -> TaskGroup:
+ from airflow.sdk.definitions.task_group import TaskGroup
+
+ return TaskGroup(group_id=None, dag=dag)
+
+
+_DAG_HASH_ATTRS = frozenset(
+ {
+ "dag_id",
+ "task_ids",
+ "parent_dag",
+ "start_date",
+ "end_date",
+ "schedule_interval",
+ "fileloc",
+ "template_searchpath",
+ "last_loaded",
+ }
+)
+
+# TODO: The following mapping is used to validate that the arguments passed to the DAG are of the correct
+# type. This is a temporary solution until we find a more sophisticated method for argument validation.
+# One potential method is to use `get_type_hints` from the typing module. However, this is not fully
+# compatible with future annotations for Python versions below 3.10. Once we require a minimum Python
+# version that supports `get_type_hints` effectively or find a better approach, we can replace this
+# manual type-checking method.
+DAG_ARGS_EXPECTED_TYPES = {
+ "dag_id": str,
+ "description": str,
+ "max_active_tasks": int,
+ "max_active_runs": int,
+ "max_consecutive_failed_dag_runs": int,
+ "dagrun_timeout": timedelta,
+ "default_view": str,
+ "orientation": str,
+ "catchup": bool,
+ "doc_md": str,
+ "is_paused_upon_creation": bool,
+ "render_template_as_native_obj": bool,
+ "tags": Collection,
+ "auto_register": bool,
+ "fail_stop": bool,
+ "dag_display_name": str,
+}
+
+
+@attrs.define
+class DAG:
+ """
+ A dag (directed acyclic graph) is a collection of tasks with directional dependencies.
+
+ A dag also has a schedule, a start date and an end date (optional). For each schedule,
+ (say daily or hourly), the DAG needs to run each individual tasks as their dependencies
+ are met. Certain tasks have the property of depending on their own past, meaning that
+ they can't run until their previous schedule (and upstream tasks) are completed.
+
+ DAGs essentially act as namespaces for tasks. A task_id can only be
+ added once to a DAG.
+
+ Note that if you plan to use time zones all the dates provided should be pendulum
+ dates. See :ref:`timezone_aware_dags`.
+
+ .. versionadded:: 2.4
+ The *schedule* argument to specify either time-based scheduling logic
+ (timetable), or dataset-driven triggers.
+
+ .. versionchanged:: 3.0
+ The default value of *schedule* has been changed to *None* (no schedule).
+ The previous default was ``timedelta(days=1)``.
+
+ :param dag_id: The id of the DAG; must consist exclusively of alphanumeric
+ characters, dashes, dots and underscores (all ASCII)
+ :param description: The description for the DAG to e.g. be shown on the webserver
+ :param schedule: If provided, this defines the rules according to which DAG
+ runs are scheduled. Possible values include a cron expression string,
+ timedelta object, Timetable, or list of Asset objects.
+ See also :doc:`/howto/timetable`.
+ :param start_date: The timestamp from which the scheduler will
+ attempt to backfill. If this is not provided, backfilling must be done
+ manually with an explicit time range.
+ :param end_date: A date beyond which your DAG won't run, leave to None
+ for open-ended scheduling.
+ :param template_searchpath: This list of folders (non-relative)
+ defines where jinja will look for your templates. Order matters.
+ Note that jinja/airflow includes the path of your DAG file by
+ default
+ :param template_undefined: Template undefined type.
+ :param user_defined_macros: a dictionary of macros that will be exposed
+ in your jinja templates. For example, passing ``dict(foo='bar')``
+ to this argument allows you to ``{{ foo }}`` in all jinja
+ templates related to this DAG. Note that you can pass any
+ type of object here.
+ :param user_defined_filters: a dictionary of filters that will be exposed
+ in your jinja templates. For example, passing
+ ``dict(hello=lambda name: 'Hello %s' % name)`` to this argument allows
+ you to ``{{ 'world' | hello }}`` in all jinja templates related to
+ this DAG.
+ :param default_args: A dictionary of default parameters to be used
+ as constructor keyword parameters when initialising operators.
+ Note that operators have the same hook, and precede those defined
+ here, meaning that if your dict contains `'depends_on_past': True`
+ here and `'depends_on_past': False` in the operator's call
+ `default_args`, the actual value will be `False`.
+ :param params: a dictionary of DAG level parameters that are made
+ accessible in templates, namespaced under `params`. These
+ params can be overridden at the task level.
+ :param max_active_tasks: the number of task instances allowed to run
+ concurrently
+ :param max_active_runs: maximum number of active DAG runs, beyond this
+ number of DAG runs in a running state, the scheduler won't create
+ new active DAG runs
+ :param max_consecutive_failed_dag_runs: (experimental) maximum number of consecutive failed DAG runs,
+ beyond this the scheduler will disable the DAG
+ :param dagrun_timeout: Specify the duration a DagRun should be allowed to run before it times out or
+ fails. Task instances that are running when a DagRun is timed out will be marked as skipped.
+ :param sla_miss_callback: DEPRECATED - The SLA feature is removed in Airflow 3.0, to be replaced with a new implementation in 3.1
+ :param default_view: Specify DAG default view (grid, graph, duration,
+ gantt, landing_times), default grid
+ :param orientation: Specify DAG orientation in graph view (LR, TB, RL, BT), default LR
+ :param catchup: Perform scheduler catchup (or only run latest)? Defaults to True
+ :param on_failure_callback: A function or list of functions to be called when a DagRun of this dag fails.
+ A context dictionary is passed as a single parameter to this function.
+ :param on_success_callback: Much like the ``on_failure_callback`` except
+ that it is executed when the dag succeeds.
+ :param access_control: Specify optional DAG-level actions, e.g.,
+ "{'role1': {'can_read'}, 'role2': {'can_read', 'can_edit', 'can_delete'}}"
+ or it can specify the resource name if there is a DAGs Run resource, e.g.,
+ "{'role1': {'DAG Runs': {'can_create'}}, 'role2': {'DAGs': {'can_read', 'can_edit', 'can_delete'}}"
+ :param is_paused_upon_creation: Specifies if the dag is paused when created for the first time.
+ If the dag exists already, this flag will be ignored. If this optional parameter
+ is not specified, the global config setting will be used.
+ :param jinja_environment_kwargs: additional configuration options to be passed to Jinja
+ ``Environment`` for template rendering
+
+ **Example**: to avoid Jinja from removing a trailing newline from template strings ::
+
+ DAG(
+ dag_id="my-dag",
+ jinja_environment_kwargs={
+ "keep_trailing_newline": True,
+ # some other jinja2 Environment options here
+ },
+ )
+
+ **See**: `Jinja Environment documentation
+ <https://jinja.palletsprojects.com/en/2.11.x/api/#jinja2.Environment>`_
+
+ :param render_template_as_native_obj: If True, uses a Jinja ``NativeEnvironment``
+ to render templates as native Python types. If False, a Jinja
+ ``Environment`` is used to render templates as string values.
+ :param tags: List of tags to help filtering DAGs in the UI.
+ :param owner_links: Dict of owners and their links, that will be clickable on the DAGs view UI.
+ Can be used as an HTTP link (for example the link to your Slack channel), or a mailto link.
+ e.g: {"dag_owner": "https://airflow.apache.org/"}
+ :param auto_register: Automatically register this DAG when it is used in a ``with`` block
+ :param fail_stop: Fails currently running tasks when task in DAG fails.
+ **Warning**: A fail stop dag can only have tasks with the default trigger rule ("all_success").
+ An exception will be thrown if any task in a fail stop dag has a non default trigger rule.
+ :param dag_display_name: The display name of the DAG which appears on the UI.
+ """
+
+ _comps = {
+ "dag_id",
+ "task_ids",
+ "start_date",
+ "end_date",
+ "fileloc",
+ "template_searchpath",
+ "last_loaded",
+ }
+
+ __serialized_fields: ClassVar[frozenset[str] | None] = None
+
+ # NOTE: When updating arguments here, please also keep arguments in @dag()
+ # below in sync. (Search for 'def dag(' in this file.)
+ dag_id: str
+ description: str | None = None
+ schedule: ScheduleArg = NOTSET
+ schedule_interval: ScheduleIntervalArg = NOTSET
+ timetable: Timetable | None = None
+ start_date: datetime | None = None
+ end_date: datetime | None = None
+ full_filepath: str | None = None
+ template_searchpath: str | Iterable[str] | None = None
+ # template_undefined: type[jinja2.StrictUndefined] = jinja2.StrictUndefined
+ default_args: dict | None = attrs.field(factory=dict, converter=copy.copy)
+ concurrency: int | None = None
+ max_active_tasks: int = 16
+ max_active_runs: int = 16
+ max_consecutive_failed_dag_runs: int = -1
+ dagrun_timeout: timedelta | None = None
+ # sla_miss_callback: None | SLAMissCallback | list[SLAMissCallback] = None
+ catchup: bool = True
+ # on_success_callback: None | DagStateChangeCallback | list[DagStateChangeCallback] = None
+ # on_failure_callback: None | DagStateChangeCallback | list[DagStateChangeCallback] = None
+ doc_md: str | None = None
+ params: abc.MutableMapping | None = None
+ access_control: dict | None = None
+ is_paused_upon_creation: bool | None = None
+ jinja_environment_kwargs: dict | None = None
+ render_template_as_native_obj: bool = False
+ tags: list[str] | None = None
+ owner_links: dict[str, str] | None = None
+ auto_register: bool = True
+ fail_stop: bool = False
+ dag_display_name: str | None = None
+
+ task_dict: dict[str, DAGNode] = attrs.field(factory=dict, init=False)
+
+ task_group: TaskGroup = attrs.field(
+ default=attrs.Factory(_create_root_group, takes_self=True), on_setattr=attrs.setters.NO_OP
+ )
+
+ def __repr__(self):
+ return f"<DAG: {self.dag_id}>"
+
+ def __eq__(self, other: Self | Any):
+ if type(self) != type(other):
+ return NotImplemented
+ return all(getattr(self, c, None) == getattr(other, c, None) for c in _DAG_HASH_ATTRS)
+
+ def __ne__(self, other: Any):
+ return not self == other
+
+ def __lt__(self, other):
+ return self.dag_id < other.dag_id
+
+ def __hash__(self):
+ hash_components: list[Any] = [type(self)]
+ for c in _DAG_HASH_ATTRS:
+ # task_ids returns a list and lists can't be hashed
+ if c == "task_ids":
+ val = tuple(self.task_dict)
+ else:
+ val = getattr(self, c, None)
+ try:
+ hash(val)
+ hash_components.append(val)
+ except TypeError:
+ hash_components.append(repr(val))
+ return hash(tuple(hash_components))
+
+ def __enter__(self) -> Self:
+ from .contextmanager import DagContext
+
+ DagContext.push(self)
+ return self
+
+ def __exit__(self, _type, _value, _tb):
+ from .contextmanager import DagContext
+
+ _ = DagContext.pop()
+
+ def get_doc_md(self, doc_md: str | None) -> str | None:
+ if doc_md is None:
+ return doc_md
+
+ if doc_md.endswith(".md"):
+ try:
+ return open(doc_md).read()
+ except FileNotFoundError:
+ return doc_md
+
+ return doc_md
+
+ def validate(self):
+ """
+ Validate the DAG has a coherent setup.
+
+ This is called by the DAG bag before bagging the DAG.
+ """
+ self.validate_schedule_and_params()
+ self.timetable.validate()
+ self.validate_setup_teardown()
+
+ def validate_setup_teardown(self):
+ """
+ Validate that setup and teardown tasks are configured properly.
+
+ :meta private:
+ """
+ for task in self.tasks:
+ if task.is_setup:
+ for down_task in task.downstream_list:
+ if not down_task.is_teardown and down_task.trigger_rule != TriggerRule.ALL_SUCCESS:
+ # todo: we can relax this to allow out-of-scope tasks to have other trigger rules
+ # this is required to ensure consistent behavior of dag
+ # when clearing an indirect setup
+ raise ValueError("Setup tasks must be followed with trigger rule ALL_SUCCESS.")
+ FailStopDagInvalidTriggerRule.check(dag=self, trigger_rule=task.trigger_rule)
+
+ def param(self, name: str, default: Any = NOTSET) -> DagParam:
+ """
+ Return a DagParam object for current dag.
+
+ :param name: dag parameter name.
+ :param default: fallback value for dag parameter.
+ :return: DagParam instance for specified name and current dag.
+ """
+ return DagParam(current_dag=self, name=name, default=default)
+
+ @property
+ def tasks(self) -> list[Operator]:
+ return list(self.task_dict.values())
+
+ @tasks.setter
+ def tasks(self, val):
+ raise AttributeError("DAG.tasks can not be modified. Use dag.add_task() instead.")
+
+ @property
+ def task_ids(self) -> list[str]:
+ return list(self.task_dict)
+
+ @property
+ def teardowns(self) -> list[Operator]:
+ return [task for task in self.tasks if getattr(task, "is_teardown", None)]
+
+ @property
+ def tasks_upstream_of_teardowns(self) -> list[Operator]:
+ upstream_tasks = [t.upstream_list for t in self.teardowns]
+ return [val for sublist in upstream_tasks for val in sublist if not getattr(val, "is_teardown", None)]
+
+ @property
+ def relative_fileloc(self) -> pathlib.Path:
+ """File location of the importable dag 'file' relative to the configured DAGs folder."""
+ path = pathlib.Path(self.fileloc)
+ try:
+ rel_path = path.relative_to(self._processor_dags_folder or settings.DAGS_FOLDER)
+ if rel_path == pathlib.Path("."):
+ return path
+ else:
+ return rel_path
+ except ValueError:
+ # Not relative to DAGS_FOLDER.
+ return path
+
+ @property
+ def folder(self) -> str:
+ """Folder location of where the DAG object is instantiated."""
+ return os.path.dirname(self.fileloc)
+
+ @property
+ def owner(self) -> str:
+ """
+ Return list of all owners found in DAG tasks.
+
+ :return: Comma separated list of owners in DAG tasks
+ """
+ return ", ".join({t.owner for t in self.tasks})
+
+ @property
+ def allow_future_exec_dates(self) -> bool:
+ return settings.ALLOW_FUTURE_EXEC_DATES and not self.timetable.can_be_scheduled
+
+ @classmethod
+ def execute_callback(cls, callbacks: list[Callable] | None, context: Context | None, dag_id: str):
+ """
+ Triggers the callbacks with the given context.
+
+ :param callbacks: List of callbacks to call
+ :param context: Context to pass to all callbacks
+ :param dag_id: The dag_id of the DAG to find.
+ """
+ if callbacks and context:
+ for callback in callbacks:
+ cls.logger().info("Executing dag callback function: %s", callback)
+ try:
+ callback(context)
+ except Exception:
+ cls.logger().exception("failed to invoke dag state update callback")
+ Stats.incr("dag.callback_exceptions", tags={"dag_id": dag_id})
+
+ def resolve_template_files(self):
+ for t in self.tasks:
+ t.resolve_template_files()
+
+ def get_template_env(self, *, force_sandboxed: bool = False) -> jinja2.Environment:
+ """Build a Jinja2 environment."""
+ # Collect directories to search for template files
+ searchpath = [self.folder]
+ if self.template_searchpath:
+ searchpath += self.template_searchpath
+
+ # Default values (for backward compatibility)
+ jinja_env_options = {
+ "loader": jinja2.FileSystemLoader(searchpath),
+ "undefined": self.template_undefined,
+ "extensions": ["jinja2.ext.do"],
+ "cache_size": 0,
+ }
+ if self.jinja_environment_kwargs:
+ jinja_env_options.update(self.jinja_environment_kwargs)
+ env: jinja2.Environment
+ if self.render_template_as_native_obj and not force_sandboxed:
+ env = airflow.templates.NativeEnvironment(**jinja_env_options)
+ else:
+ env = airflow.templates.SandboxedEnvironment(**jinja_env_options)
+
+ # Add any user defined items. Safe to edit globals as long as no templates are rendered yet.
+ # http://jinja.pocoo.org/docs/2.10/api/#jinja2.Environment.globals
+ if self.user_defined_macros:
+ env.globals.update(self.user_defined_macros)
+ if self.user_defined_filters:
+ env.filters.update(self.user_defined_filters)
+
+ return env
+
+ def set_dependency(self, upstream_task_id, downstream_task_id):
+ """Set dependency between two tasks that already have been added to the DAG using add_task()."""
+ self.get_task(upstream_task_id).set_downstream(self.get_task(downstream_task_id))
+
+ @property
+ def roots(self) -> list[Operator]:
+ """Return nodes with no parents. These are first to execute and are called roots or root nodes."""
+ return [task for task in self.tasks if not task.upstream_list]
+
+ @property
+ def leaves(self) -> list[Operator]:
+ """Return nodes with no children. These are last to execute and are called leaves or leaf nodes."""
+ return [task for task in self.tasks if not task.downstream_list]
+
+ def topological_sort(self):
+ """
+ Sorts tasks in topographical order, such that a task comes after any of its upstream dependencies.
+
+ Deprecated in place of ``task_group.topological_sort``
+ """
+ from airflow.utils.task_group import TaskGroup
+
+ def nested_topo(group):
+ for node in group.topological_sort():
+ if isinstance(node, TaskGroup):
+ yield from nested_topo(node)
+ else:
+ yield node
+
+ return tuple(nested_topo(self.task_group))
+
+ def __deepcopy__(self, memo):
+ # Switcharoo to go around deepcopying objects coming through the
+ # backdoor
+ cls = self.__class__
+ result = cls.__new__(cls)
+ memo[id(self)] = result
+ for k, v in self.__dict__.items():
+ if k not in ("user_defined_macros", "user_defined_filters", "_log"):
+ setattr(result, k, copy.deepcopy(v, memo))
+
+ result.user_defined_macros = self.user_defined_macros
+ result.user_defined_filters = self.user_defined_filters
+ if hasattr(self, "_log"):
+ result._log = self._log
+ return result
+
+ def partial_subset(
+ self,
+ task_ids_or_regex: str | Pattern | Iterable[str],
+ include_downstream=False,
+ include_upstream=True,
+ include_direct_upstream=False,
+ ):
+ """
+ Return a subset of the current dag based on regex matching one or more tasks.
+
+ Returns a subset of the current dag as a deep copy of the current dag
+ based on a regex that should match one or many tasks, and includes
+ upstream and downstream neighbours based on the flag passed.
+
+ :param task_ids_or_regex: Either a list of task_ids, or a regex to
+ match against task ids (as a string, or compiled regex pattern).
+ :param include_downstream: Include all downstream tasks of matched
+ tasks, in addition to matched tasks.
+ :param include_upstream: Include all upstream tasks of matched tasks,
+ in addition to matched tasks.
+ :param include_direct_upstream: Include all tasks directly upstream of matched
+ and downstream (if include_downstream = True) tasks
+ """
+ from airflow.models.mappedoperator import MappedOperator
+
+ # deep-copying self.task_dict and self._task_group takes a long time, and we don't want all
+ # the tasks anyway, so we copy the tasks manually later
+ memo = {id(self.task_dict): None, id(self._task_group): None}
+ dag = copy.deepcopy(self, memo) # type: ignore
+
+ if isinstance(task_ids_or_regex, (str, Pattern)):
+ matched_tasks = [t for t in self.tasks if re2.findall(task_ids_or_regex, t.task_id)]
+ else:
+ matched_tasks = [t for t in self.tasks if t.task_id in task_ids_or_regex]
+
+ also_include_ids: set[str] = set()
+ for t in matched_tasks:
+ if include_downstream:
+ for rel in t.get_flat_relatives(upstream=False):
+ also_include_ids.add(rel.task_id)
+ if rel not in matched_tasks: # if it's in there, we're already processing it
+ # need to include setups and teardowns for tasks that are in multiple
+ # non-collinear setup/teardown paths
+ if not rel.is_setup and not rel.is_teardown:
+ also_include_ids.update(
+ x.task_id for x in rel.get_upstreams_only_setups_and_teardowns()
+ )
+ if include_upstream:
+ also_include_ids.update(x.task_id for x in t.get_upstreams_follow_setups())
+ else:
+ if not t.is_setup and not t.is_teardown:
+ also_include_ids.update(x.task_id for x in t.get_upstreams_only_setups_and_teardowns())
+ if t.is_setup and not include_downstream:
+ also_include_ids.update(x.task_id for x in t.downstream_list if x.is_teardown)
+
+ also_include: list[Operator] = [self.task_dict[x] for x in also_include_ids]
+ direct_upstreams: list[Operator] = []
+ if include_direct_upstream:
+ for t in itertools.chain(matched_tasks, also_include):
+ upstream = (u for u in t.upstream_list if isinstance(u, (BaseOperator, MappedOperator)))
+ direct_upstreams.extend(upstream)
+
+ # Compiling the unique list of tasks that made the cut
+ # Make sure to not recursively deepcopy the dag or task_group while copying the task.
+ # task_group is reset later
+ def _deepcopy_task(t) -> Operator:
+ memo.setdefault(id(t.task_group), None)
+ return copy.deepcopy(t, memo)
+
+ dag.task_dict = {
+ t.task_id: _deepcopy_task(t)
+ for t in itertools.chain(matched_tasks, also_include, direct_upstreams)
+ }
+
+ def filter_task_group(group, parent_group):
+ """Exclude tasks not included in the subdag from the given TaskGroup."""
+ # We want to deepcopy _most but not all_ attributes of the task group, so we create a shallow copy
+ # and then manually deep copy the instances. (memo argument to deepcopy only works for instances
+ # of classes, not "native" properties of an instance)
+ copied = copy.copy(group)
+
+ memo[id(group.children)] = {}
+ if parent_group:
+ memo[id(group.parent_group)] = parent_group
+ for attr, value in copied.__dict__.items():
+ if id(value) in memo:
+ value = memo[id(value)]
+ else:
+ value = copy.deepcopy(value, memo)
+ copied.__dict__[attr] = value
+
+ proxy = weakref.proxy(copied)
+
+ for child in group.children.values():
+ if isinstance(child, AbstractOperator):
+ if child.task_id in dag.task_dict:
+ task = copied.children[child.task_id] = dag.task_dict[child.task_id]
+ task.task_group = proxy
+ else:
+ copied.used_group_ids.discard(child.task_id)
+ else:
+ filtered_child = filter_task_group(child, proxy)
+
+ # Only include this child TaskGroup if it is non-empty.
+ if filtered_child.children:
+ copied.children[child.group_id] = filtered_child
+
+ return copied
+
+ dag._task_group = filter_task_group(self.task_group, None)
+
+ # Removing upstream/downstream references to tasks and TaskGroups that did not make
+ # the cut.
+ subdag_task_groups = dag.task_group.get_task_group_dict()
+ for group in subdag_task_groups.values():
+ group.upstream_group_ids.intersection_update(subdag_task_groups)
+ group.downstream_group_ids.intersection_update(subdag_task_groups)
+ group.upstream_task_ids.intersection_update(dag.task_dict)
+ group.downstream_task_ids.intersection_update(dag.task_dict)
+
+ for t in dag.tasks:
+ # Removing upstream/downstream references to tasks that did not
+ # make the cut
+ t.upstream_task_ids.intersection_update(dag.task_dict)
+ t.downstream_task_ids.intersection_update(dag.task_dict)
+
+ if len(dag.tasks) < len(self.tasks):
+ dag.partial = True
+
+ return dag
+
+ def has_task(self, task_id: str):
+ return task_id in self.task_dict
+
+ def has_task_group(self, task_group_id: str) -> bool:
+ return task_group_id in self.task_group_dict
+
+ @functools.cached_property
+ def task_group_dict(self):
+ return {k: v for k, v in self._task_group.get_task_group_dict().items() if k is not None}
+
+ def get_task(self, task_id: str) -> Operator:
+ if task_id in self.task_dict:
+ return self.task_dict[task_id]
+ raise TaskNotFound(f"Task {task_id} not found")
+
+ @property
+ def task(self) -> TaskDecoratorCollection:
+ from airflow.decorators import task
+
+ return cast("TaskDecoratorCollection", functools.partial(task, dag=self))
+
+ def add_task(self, task: Operator) -> None:
+ """
+ Add a task to the DAG.
+
+ :param task: the task you want to add
+ """
+ # FailStopDagInvalidTriggerRule.check(dag=self, trigger_rule=task.trigger_rule)
+
+ from airflow.sdk.definitions.contextmanager import TaskGroupContext
+
+ # if the task has no start date, assign it the same as the DAG
+ if not task.start_date:
+ task.start_date = self.start_date
+ # otherwise, the task will start on the later of its own start date and
+ # the DAG's start date
+ elif self.start_date:
+ task.start_date = max(task.start_date, self.start_date)
+
+ # if the task has no end date, assign it the same as the dag
+ if not task.end_date:
+ task.end_date = self.end_date
+ # otherwise, the task will end on the earlier of its own end date and
+ # the DAG's end date
+ elif task.end_date and self.end_date:
+ task.end_date = min(task.end_date, self.end_date)
+
+ task_id = task.node_id
+ if not task.task_group:
+ task_group = TaskGroupContext.get_current(self)
+ if task_group:
+ task_id = task_group.child_id(task_id)
+ task_group.add(task)
+
+ if (
+ task_id in self.task_dict and self.task_dict[task_id] is not task
+ ) or task_id in self.task_group.used_group_ids:
+ raise DuplicateTaskIdFound(f"Task id '{task_id}' has already been added to the DAG")
+ else:
+ self.task_dict[task_id] = task
+ task.dag = self
+ # Add task_id to used_group_ids to prevent group_id and task_id collisions.
+ self.task_group.used_group_ids.add(task_id)
+
+ def add_tasks(self, tasks: Iterable[Operator]) -> None:
+ """
+ Add a list of tasks to the DAG.
+
+ :param tasks: a lit of tasks you want to add
+ """
+ for task in tasks:
+ self.add_task(task)
+
+ def _remove_task(self, task_id: str) -> None:
+ # This is "private" as removing could leave a hole in dependencies if done incorrectly, and this
+ # doesn't guard against that
+ task = self.task_dict.pop(task_id)
+ tg = getattr(task, "task_group", None)
+ if tg:
+ tg._remove(task)
+
+ self.task_count = len(self.task_dict)
+
+ def cli(self):
+ """Exposes a CLI specific to this DAG."""
+ check_cycle(self)
+
+ from airflow.cli import cli_parser
+
+ parser = cli_parser.get_parser(dag_parser=True)
+ args = parser.parse_args()
+ args.func(args, self)
+
+ def get_default_view(self):
+ """Allow backward compatible jinja2 templates."""
+ if self.default_view is None:
+ return airflow_conf.get("webserver", "dag_default_view").lower()
+ else:
+ return self.default_view
+
+ @classmethod
+ def get_serialized_fields(cls):
+ """Stringified DAGs and operators contain exactly these fields."""
+ if not cls.__serialized_fields:
+ exclusion_list = {
+ "schedule_dataset_references",
+ "schedule_dataset_alias_references",
+ "task_outlet_dataset_references",
+ "_old_context_manager_dags",
+ "safe_dag_id",
+ "last_loaded",
+ "user_defined_filters",
+ "user_defined_macros",
+ "partial",
+ "params",
+ "_pickle_id",
+ "_log",
+ "task_dict",
+ "template_searchpath",
+ "sla_miss_callback",
+ "on_success_callback",
+ "on_failure_callback",
+ "template_undefined",
+ "jinja_environment_kwargs",
+ # has_on_*_callback are only stored if the value is True, as the default is False
+ "has_on_success_callback",
+ "has_on_failure_callback",
+ "auto_register",
+ "fail_stop",
+ }
+ cls.__serialized_fields = frozenset(vars(DAG(dag_id="test", schedule=None))) - exclusion_list
+ return cls.__serialized_fields
+
+ def get_edge_info(self, upstream_task_id: str, downstream_task_id: str) -> EdgeInfoType:
+ """Return edge information for the given pair of tasks or an empty edge if there is no information."""
+ # Note - older serialized DAGs may not have edge_info being a dict at all
+ empty = cast(EdgeInfoType, {})
+ if self.edge_info:
+ return self.edge_info.get(upstream_task_id, {}).get(downstream_task_id, empty)
+ else:
+ return empty
+
+ def set_edge_info(self, upstream_task_id: str, downstream_task_id: str, info: EdgeInfoType):
+ """
+ Set the given edge information on the DAG.
+
+ Note that this will overwrite, rather than merge with, existing info.
+ """
+ self.edge_info.setdefault(upstream_task_id, {})[downstream_task_id] = info
+
+ def validate_schedule_and_params(self):
+ """
+ Validate Param values when the DAG has schedule defined.
+
+ Raise exception if there are any Params which can not be resolved by their schema definition.
+ """
+ if not self.timetable.can_be_scheduled:
+ return
+
+ try:
+ self.params.validate()
+ except ParamValidationError as pverr:
+ raise AirflowException(
+ "DAG is not allowed to define a Schedule, "
+ "if there are any required params without default values or default values are not valid."
+ ) from pverr
+
+ def iter_invalid_owner_links(self) -> Iterator[tuple[str, str]]:
+ """
+ Parse a given link, and verifies if it's a valid URL, or a 'mailto' link.
+
+ Returns an iterator of invalid (owner, link) pairs.
+ """
+ for owner, link in self.owner_links.items():
+ result = urlsplit(link)
+ if result.scheme == "mailto":
+ # netloc is not existing for 'mailto' link, so we are checking that the path is parsed
+ if not result.path:
+ yield result.path, link
+ elif not result.scheme or not result.netloc:
+ yield owner, link
+
+
+# NOTE: Please keep the list of arguments in sync with DAG.__init__.
+# Only exception: dag_id here should have a default value, but not in DAG.
+def dag(
+ dag_id: str = "",
+ description: str | None = None,
+ schedule: ScheduleArg = None,
+ start_date: datetime | None = None,
+ end_date: datetime | None = None,
+ template_searchpath: str | Iterable[str] | None = None,
+ template_undefined: type[jinja2.StrictUndefined] = jinja2.StrictUndefined,
+ user_defined_macros: dict | None = None,
+ user_defined_filters: dict | None = None,
+ default_args: dict | None = None,
+ max_active_tasks: int = airflow_conf.getint("core", "max_active_tasks_per_dag"),
+ max_active_runs: int = airflow_conf.getint("core", "max_active_runs_per_dag"),
+ max_consecutive_failed_dag_runs: int = airflow_conf.getint(
+ "core", "max_consecutive_failed_dag_runs_per_dag"
+ ),
+ dagrun_timeout: timedelta | None = None,
+ sla_miss_callback: Any = None,
+ default_view: str = airflow_conf.get_mandatory_value("webserver", "dag_default_view").lower(),
+ orientation: str = airflow_conf.get_mandatory_value("webserver", "dag_orientation"),
+ catchup: bool = airflow_conf.getboolean("scheduler", "catchup_by_default"),
+ on_success_callback: None | DagStateChangeCallback | list[DagStateChangeCallback] = None,
+ on_failure_callback: None | DagStateChangeCallback | list[DagStateChangeCallback] = None,
+ doc_md: str | None = None,
+ params: abc.MutableMapping | None = None,
+ access_control: dict[str, dict[str, Collection[str]]] | dict[str, Collection[str]] | None = None,
+ is_paused_upon_creation: bool | None = None,
+ jinja_environment_kwargs: dict | None = None,
+ render_template_as_native_obj: bool = False,
+ tags: Collection[str] | None = None,
+ owner_links: dict[str, str] | None = None,
+ auto_register: bool = True,
+ fail_stop: bool = False,
+ dag_display_name: str | None = None,
+) -> Callable[[Callable], Callable[..., DAG]]:
+ """
+ Python dag decorator which wraps a function into an Airflow DAG.
+
+ Accepts kwargs for operator kwarg. Can be used to parameterize DAGs.
+
+ :param dag_args: Arguments for DAG object
+ :param dag_kwargs: Kwargs for DAG object.
+ """
+
+ def wrapper(f: Callable) -> Callable[..., DAG]:
+ @functools.wraps(f)
+ def factory(*args, **kwargs):
+ # Generate signature for decorated function and bind the arguments when called
+ # we do this to extract parameters, so we can annotate them on the DAG object.
+ # In addition, this fails if we are missing any args/kwargs with TypeError as expected.
+ f_sig = signature(f).bind(*args, **kwargs)
+ # Apply defaults to capture default values if set.
+ f_sig.apply_defaults()
+
+ # Initialize DAG with bound arguments
+ with DAG(
+ dag_id or f.__name__,
+ description=description,
+ start_date=start_date,
+ end_date=end_date,
+ template_searchpath=template_searchpath,
+ template_undefined=template_undefined,
+ user_defined_macros=user_defined_macros,
+ user_defined_filters=user_defined_filters,
+ default_args=default_args,
+ max_active_tasks=max_active_tasks,
+ max_active_runs=max_active_runs,
+ max_consecutive_failed_dag_runs=max_consecutive_failed_dag_runs,
+ dagrun_timeout=dagrun_timeout,
+ sla_miss_callback=sla_miss_callback,
+ default_view=default_view,
+ orientation=orientation,
+ catchup=catchup,
+ on_success_callback=on_success_callback,
+ on_failure_callback=on_failure_callback,
+ doc_md=doc_md,
+ params=params,
+ access_control=access_control,
+ is_paused_upon_creation=is_paused_upon_creation,
+ jinja_environment_kwargs=jinja_environment_kwargs,
+ render_template_as_native_obj=render_template_as_native_obj,
+ tags=tags,
+ schedule=schedule,
+ owner_links=owner_links,
+ auto_register=auto_register,
+ fail_stop=fail_stop,
+ dag_display_name=dag_display_name,
+ ) as dag_obj:
+ # Set DAG documentation from function documentation if it exists and doc_md is not set.
+ if f.__doc__ and not dag_obj.doc_md:
+ dag_obj.doc_md = f.__doc__
+
+ # Generate DAGParam for each function arg/kwarg and replace it for calling the function.
+ # All args/kwargs for function will be DAGParam object and replaced on execution time.
+ f_kwargs = {}
+ for name, value in f_sig.arguments.items():
+ f_kwargs[name] = dag_obj.param(name, value)
+
+ # set file location to caller source path
+ back = sys._getframe().f_back
+ dag_obj.fileloc = back.f_code.co_filename if back else ""
+
+ # Invoke function to create operators in the DAG scope.
+ f(**f_kwargs)
+
+ # Return dag object such that it's accessible in Globals.
+ return dag_obj
+
+ # Ensure that warnings from inside DAG() are emitted from the caller, not here
+ fixup_decorator_warning_stack(factory)
+ return factory
+
+ return wrapper
diff --git a/task_sdk/src/airflow/sdk/definitions/decorators.py b/task_sdk/src/airflow/sdk/definitions/decorators.py
new file mode 100644
index 00000000000..ab73ba0c924
--- /dev/null
+++ b/task_sdk/src/airflow/sdk/definitions/decorators.py
@@ -0,0 +1,42 @@
+# 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.
+
+from __future__ import annotations
+
+import sys
+from types import FunctionType
+
+
+class _autostacklevel_warn:
+ def __init__(self):
+ self.warnings = __import__("warnings")
+
+ def __getattr__(self, name: str):
+ return getattr(self.warnings, name)
+
+ def __dir__(self):
+ return dir(self.warnings)
+
+ def warn(self, message, category=None, stacklevel=1, source=None):
+ self.warnings.warn(message, category, stacklevel + 2, source)
+
+
+def fixup_decorator_warning_stack(func: FunctionType):
+ if func.__globals__.get("warnings") is sys.modules["warnings"]:
+ # Yes, this is more than slightly hacky, but it _automatically_ sets the right stacklevel parameter to
+ # `warnings.warn` to ignore the decorator.
+ func.__globals__["warnings"] = _autostacklevel_warn()
diff --git a/task_sdk/src/airflow/sdk/definitions/edges.py b/task_sdk/src/airflow/sdk/definitions/edges.py
new file mode 100644
index 00000000000..45d674925f2
--- /dev/null
+++ b/task_sdk/src/airflow/sdk/definitions/edges.py
@@ -0,0 +1,191 @@
+# 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.
+from __future__ import annotations
+
+from collections.abc import Sequence
+from typing import TYPE_CHECKING
+
+from .mixins import DependencyMixin
+
+if TYPE_CHECKING:
+ from .dag import DAG
+
+
+class EdgeModifier(DependencyMixin):
+ """
+ Class that represents edge information to be added between two tasks/operators.
+
+ Has shorthand factory functions, like Label("hooray").
+
+ Current implementation supports
+ t1 >> Label("Success route") >> t2
+ t2 << Label("Success route") << t2
+
+ Note that due to the potential for use in either direction, this waits
+ to make the actual connection between both sides until both are declared,
+ and will do so progressively if multiple ups/downs are added.
+
+ This and EdgeInfo are related - an EdgeModifier is the Python object you
+ use to add information to (potentially multiple) edges, and EdgeInfo
+ is the representation of the information for one specific edge.
+ """
+
+ def __init__(self, label: str | None = None):
+ self.label = label
+ self._upstream: list[DependencyMixin] = []
+ self._downstream: list[DependencyMixin] = []
+
+ @property
+ def roots(self):
+ return self._downstream
+
+ @property
+ def leaves(self):
+ return self._upstream
+
+ @staticmethod
+ def _make_list(
+ item_or_list: DependencyMixin | Sequence[DependencyMixin],
+ ) -> Sequence[DependencyMixin]:
+ if not isinstance(item_or_list, Sequence):
+ return [item_or_list]
+ return item_or_list
+
+ def _save_nodes(
+ self,
+ nodes: DependencyMixin | Sequence[DependencyMixin],
+ stream: list[DependencyMixin],
+ ):
+ from .node import DAGNode
+ from .task_group import TaskGroup
+
+ class XComArg: ...
+
+ for node in self._make_list(nodes):
+ if isinstance(node, (TaskGroup, XComArg, DAGNode)):
+ stream.append(node)
+ else:
+ raise TypeError(
+ f"Cannot use edge labels with {type(node).__name__}, only tasks, XComArg or TaskGroups"
+ )
+
+ def _convert_streams_to_task_groups(self):
+ """
+ Convert a node to a TaskGroup or leave it as a DAGNode.
+
+ Requires both self._upstream and self._downstream.
+
+ To do this, we keep a set of group_ids seen among the streams. If we find that
+ the nodes are from the same TaskGroup, we will leave them as DAGNodes and not
+ convert them to TaskGroups
+ """
+ from .node import DAGNode
+ from .task_group import TaskGroup
+
+ class XComArg: ...
+
+ group_ids = set()
+ for node in [*self._upstream, *self._downstream]:
+ if isinstance(node, DAGNode) and node.task_group:
+ if node.task_group.is_root:
+ group_ids.add("root")
+ else:
+ group_ids.add(node.task_group.group_id)
+ elif isinstance(node, TaskGroup):
+ group_ids.add(node.group_id)
+ elif isinstance(node, XComArg):
+ if isinstance(node.operator, DAGNode) and node.operator.task_group:
+ if node.operator.task_group.is_root:
+ group_ids.add("root")
+ else:
+ group_ids.add(node.operator.task_group.group_id)
+
+ # If all nodes originate from the same TaskGroup, we will not convert them
+ if len(group_ids) != 1:
+ self._upstream = self._convert_stream_to_task_groups(self._upstream)
+ self._downstream = self._convert_stream_to_task_groups(self._downstream)
+
+ def _convert_stream_to_task_groups(self, stream: Sequence[DependencyMixin]) -> Sequence[DependencyMixin]:
+ from .node import DAGNode
+
+ return [
+ node.task_group
+ if isinstance(node, DAGNode) and node.task_group and not node.task_group.is_root
+ else node
+ for node in stream
+ ]
+
+ def set_upstream(
+ self,
+ other: DependencyMixin | Sequence[DependencyMixin],
+ edge_modifier: EdgeModifier | None = None,
+ ):
+ """
+ Set the given task/list onto the upstream attribute, then attempt to resolve the relationship.
+
+ Providing this also provides << via DependencyMixin.
+ """
+ self._save_nodes(other, self._upstream)
+ if self._upstream and self._downstream:
+ # Convert _upstream and _downstream to task_groups only after both are set
+ self._convert_streams_to_task_groups()
+ for node in self._downstream:
+ node.set_upstream(other, edge_modifier=self)
+
+ def set_downstream(
+ self,
+ other: DependencyMixin | Sequence[DependencyMixin],
+ edge_modifier: EdgeModifier | None = None,
+ ):
+ """
+ Set the given task/list onto the downstream attribute, then attempt to resolve the relationship.
+
+ Providing this also provides >> via DependencyMixin.
+ """
+ self._save_nodes(other, self._downstream)
+ if self._upstream and self._downstream:
+ # Convert _upstream and _downstream to task_groups only after both are set
+ self._convert_streams_to_task_groups()
+ for node in self._upstream:
+ node.set_downstream(other, edge_modifier=self)
+
+ def update_relative(
+ self,
+ other: DependencyMixin,
+ upstream: bool = True,
+ edge_modifier: EdgeModifier | None = None,
+ ) -> None:
+ """Update relative if we're not the "main" side of a relationship; still run the same logic."""
+ if upstream:
+ self.set_upstream(other)
+ else:
+ self.set_downstream(other)
+
+ def add_edge_info(self, dag: DAG, upstream_id: str, downstream_id: str):
+ """
+ Add or update task info on the DAG for this specific pair of tasks.
+
+ Called either from our relationship trigger methods above, or directly
+ by set_upstream/set_downstream in operators.
+ """
+ dag.set_edge_info(upstream_id, downstream_id, {"label": self.label})
+
+
+# Factory functions
+def Label(label: str):
+ """Create an EdgeModifier that sets a human-readable label on the edge."""
+ return EdgeModifier(label=label)
diff --git a/task_sdk/src/airflow/sdk/definitions/mixins.py b/task_sdk/src/airflow/sdk/definitions/mixins.py
new file mode 100644
index 00000000000..b4210f94640
--- /dev/null
+++ b/task_sdk/src/airflow/sdk/definitions/mixins.py
@@ -0,0 +1,122 @@
+# 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.
+
+from __future__ import annotations
+
+from abc import abstractmethod
+from collections.abc import Iterable, Sequence
+from typing import TYPE_CHECKING, Any
+
+from ..types import NOTSET, ArgNotSet
+
+if TYPE_CHECKING:
+ from .baseoperator import BaseOperator
+ from .edges import EdgeModifier
+
+# TODO: Should this all just live on DAGNode?
+
+
+class DependencyMixin:
+ """Mixing implementing common dependency setting methods like >> and <<."""
+
+ @property
+ def roots(self) -> Iterable[DependencyMixin]:
+ """
+ List of root nodes -- ones with no upstream dependencies.
+
+ a.k.a. the "start" of this sub-graph
+ """
+ raise NotImplementedError()
+
+ @property
+ def leaves(self) -> Iterable[DependencyMixin]:
+ """
+ List of leaf nodes -- ones with only upstream dependencies.
+
+ a.k.a. the "end" of this sub-graph
+ """
+ raise NotImplementedError()
+
+ @abstractmethod
+ def set_upstream(
+ self, other: DependencyMixin | Sequence[DependencyMixin], edge_modifier: EdgeModifier | None = None
+ ):
+ """Set a task or a task list to be directly upstream from the current task."""
+ raise NotImplementedError()
+
+ @abstractmethod
+ def set_downstream(
+ self, other: DependencyMixin | Sequence[DependencyMixin], edge_modifier: EdgeModifier | None = None
+ ):
+ """Set a task or a task list to be directly downstream from the current task."""
+ raise NotImplementedError()
+
+ def as_setup(self) -> DependencyMixin:
+ """Mark a task as setup task."""
+ raise NotImplementedError()
+
+ def as_teardown(
+ self,
+ *,
+ setups: BaseOperator | Iterable[BaseOperator] | ArgNotSet = NOTSET,
+ on_failure_fail_dagrun: bool | ArgNotSet = NOTSET,
+ ) -> DependencyMixin:
+ """Mark a task as teardown and set its setups as direct relatives."""
+ raise NotImplementedError()
+
+ def update_relative(
+ self, other: DependencyMixin, upstream: bool = True, edge_modifier: EdgeModifier | None = None
+ ) -> None:
+ """
+ Update relationship information about another TaskMixin. Default is no-op.
+
+ Override if necessary.
+ """
+
+ def __lshift__(self, other: DependencyMixin | Sequence[DependencyMixin]):
+ """Implement Task << Task."""
+ self.set_upstream(other)
+ return other
+
+ def __rshift__(self, other: DependencyMixin | Sequence[DependencyMixin]):
+ """Implement Task >> Task."""
+ self.set_downstream(other)
+ return other
+
+ def __rrshift__(self, other: DependencyMixin | Sequence[DependencyMixin]):
+ """Implement Task >> [Task] because list don't have __rshift__ operators."""
+ self.__lshift__(other)
+ return self
+
+ def __rlshift__(self, other: DependencyMixin | Sequence[DependencyMixin]):
+ """Implement Task << [Task] because list don't have __lshift__ operators."""
+ self.__rshift__(other)
+ return self
+
+ @classmethod
+ def _iter_references(cls, obj: Any) -> Iterable[tuple[DependencyMixin, str]]:
+ from .abstractoperator import AbstractOperator
+ # TODO:
+ # from airflow.utils.mixins import ResolveMixin
+
+ if isinstance(obj, AbstractOperator):
+ yield obj, "operator"
+ # elif isinstance(obj, ResolveMixin):
+ # yield from obj.iter_references()
+ elif isinstance(obj, Sequence):
+ for o in obj:
+ yield from cls._iter_references(o)
diff --git a/task_sdk/src/airflow/sdk/definitions/node.py b/task_sdk/src/airflow/sdk/definitions/node.py
new file mode 100644
index 00000000000..0abb0a83c16
--- /dev/null
+++ b/task_sdk/src/airflow/sdk/definitions/node.py
@@ -0,0 +1,192 @@
+# 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.
+
+from __future__ import annotations
+
+from abc import ABCMeta, abstractmethod
+from collections.abc import Iterable, Sequence
+from datetime import datetime
+from typing import TYPE_CHECKING
+
+import attrs
+import methodtools
+import re2
+import structlog
+
+from airflow.sdk.definitions.mixins import DependencyMixin
+
+if TYPE_CHECKING:
+ from airflow.sdk.definitions.dag import DAG
+ from airflow.sdk.definitions.edges import EdgeModifier
+ from airflow.sdk.definitions.task_group import TaskGroup
+ from airflow.sdk.types import Logger
+
+
+KEY_REGEX = re2.compile(r"^[\w.-]+$")
+GROUP_KEY_REGEX = re2.compile(r"^[\w-]+$")
+CAMELCASE_TO_SNAKE_CASE_REGEX = re2.compile(r"(?!^)([A-Z]+)")
+
+
+def validate_key(k: str, max_length: int = 250):
+ """Validate value used as a key."""
+ if not isinstance(k, str):
+ raise TypeError(f"The key has to be a string and is {type(k)}:{k}")
+ if len(k) > max_length:
+ raise ValueError(f"The key has to be less than {max_length} characters")
+ if not KEY_REGEX.match(k):
+ raise ValueError(
+ f"The key {k!r} has to be made of alphanumeric characters, dashes, "
+ + "dots and underscores exclusively"
+ )
+
+
+@attrs.define(hash=False, repr=False)
+class DAGNode(DependencyMixin, metaclass=ABCMeta):
+ """
+ A base class for a node in the graph of a workflow.
+
+ A node may be an Operator or a Task Group, either mapped or unmapped.
+ """
+
+ dag: DAG | None = attrs.field(kw_only=True, default=None)
+ task_group: TaskGroup | None = attrs.field(kw_only=True, default=None)
+ """The task_group that contains this node"""
+ start_date: datetime | None = attrs.field(kw_only=True, default=None)
+ end_date: datetime | None = attrs.field(kw_only=True, default=None)
+ upstream_task_ids: set[str] = attrs.field(init=False, factory=set)
+ downstream_task_ids: set[str] = attrs.field(init=False, factory=set)
+
+ @property
+ @abstractmethod
+ def node_id(self) -> str:
+ raise NotImplementedError()
+
+ @property
+ def label(self) -> str | None:
+ tg = self.task_group
+ if tg and tg.node_id and tg.prefix_group_id:
+ # "task_group_id.task_id" -> "task_id"
+ return self.node_id[len(tg.node_id) + 1 :]
+ return self.node_id
+
+ def has_dag(self) -> bool:
+ return self.dag is not None
+
+ @property
+ def dag_id(self) -> str:
+ """Returns dag id if it has one or an adhoc/meaningless ID."""
+ if self.dag:
+ return self.dag.dag_id
+ return "_in_memory_dag_"
+
+ @methodtools.lru_cache()
+ @property
+ def log(self) -> Logger:
+ typ = type(self)
+ name = f"{typ.__module__}.{typ.__qualname__}"
+ return structlog.get_logger(logger_name=name)
+
+ def _set_relatives(
+ self,
+ task_or_task_list: DependencyMixin | Sequence[DependencyMixin],
+ upstream: bool = False,
+ edge_modifier: EdgeModifier | None = None,
+ ) -> None:
+ """Set relatives for the task or task list."""
+ from airflow.models.baseoperator import BaseOperator
+ from airflow.models.mappedoperator import MappedOperator
+
+ if not isinstance(task_or_task_list, Sequence):
+ task_or_task_list = [task_or_task_list]
+
+ task_list: list[DAGNode] = []
+ for task_object in task_or_task_list:
+ task_object.update_relative(self, not upstream, edge_modifier=edge_modifier)
+ relatives = task_object.leaves if upstream else task_object.roots
+ for task in relatives:
+ if not isinstance(task, (BaseOperator, MappedOperator)):
+ raise TypeError(
+ f"Relationships can only be set between Operators; received {task.__class__.__name__}"
+ )
+ task_list.append(task)
+
+ # relationships can only be set if the tasks share a single DAG. Tasks
+ # without a DAG are assigned to that DAG.
+ dags: set[DAG] = {task.dag for task in [*self.roots, *task_list] if task.has_dag() and task.dag}
+
+ if len(dags) > 1:
+ raise AirflowException(f"Tried to set relationships between tasks in more than one DAG: {dags}")
+ elif len(dags) == 1:
+ dag = dags.pop()
+ else:
+ raise ValueError(
+ "Tried to create relationships between tasks that don't have DAGs yet. "
+ + f"Set the DAG for at least one task and try again: {[self, *task_list]}"
+ )
+
+ if not self.has_dag():
+ # If this task does not yet have a dag, add it to the same dag as the other task.
+ self.dag = dag
+
+ for task in task_list:
+ if dag and not task.has_dag():
+ # If the other task does not yet have a dag, add it to the same dag as this task and
+ dag.add_task(task)
+ if upstream:
+ task.downstream_task_ids.add(self.node_id)
+ self.upstream_task_ids.add(task.node_id)
+ if edge_modifier:
+ edge_modifier.add_edge_info(self.dag, task.node_id, self.node_id)
+ else:
+ self.downstream_task_ids.add(task.node_id)
+ task.upstream_task_ids.add(self.node_id)
+ if edge_modifier:
+ edge_modifier.add_edge_info(self.dag, self.node_id, task.node_id)
+
+ def set_downstream(
+ self,
+ task_or_task_list: DependencyMixin | Sequence[DependencyMixin],
+ edge_modifier: EdgeModifier | None = None,
+ ) -> None:
+ """Set a node (or nodes) to be directly downstream from the current node."""
+ self._set_relatives(task_or_task_list, upstream=False, edge_modifier=edge_modifier)
+
+ def set_upstream(
+ self,
+ task_or_task_list: DependencyMixin | Sequence[DependencyMixin],
+ edge_modifier: EdgeModifier | None = None,
+ ) -> None:
+ """Set a node (or nodes) to be directly upstream from the current node."""
+ self._set_relatives(task_or_task_list, upstream=True, edge_modifier=edge_modifier)
+
+ @property
+ def downstream_list(self) -> Iterable[DAGNode]:
+ """List of nodes directly downstream."""
+ if not self.dag:
+ raise RuntimeError(f"Operator {self} has not been assigned to a DAG yet")
+ return [self.dag.get_task(tid) for tid in self.downstream_task_ids]
+
+ @property
+ def upstream_list(self) -> Iterable[DAGNode]:
+ """List of nodes directly upstream."""
+ if not self.dag:
+ raise RuntimeError(f"Operator {self} has not been assigned to a DAG yet")
+ return [self.dag.get_task(tid) for tid in self.upstream_task_ids]
+
+ # def serialize_for_task_group(self) -> tuple[DagAttributeTypes, Any]:
+ # """Serialize a task group's content; used by TaskGroupSerialization."""
+ # raise NotImplementedError()
diff --git a/task_sdk/src/airflow/sdk/definitions/task_group.py b/task_sdk/src/airflow/sdk/definitions/task_group.py
new file mode 100644
index 00000000000..6bcda41d2d2
--- /dev/null
+++ b/task_sdk/src/airflow/sdk/definitions/task_group.py
@@ -0,0 +1,645 @@
+#
+# 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.
+"""A collection of closely related tasks on the same DAG that should be grouped together visually."""
+
+from __future__ import annotations
+
+import copy
+import functools
+import operator
+import weakref
+from collections.abc import Generator, Iterator, Sequence
+from typing import TYPE_CHECKING, Any
+
+import attrs
+import methodtools
+import re2
+
+from airflow.exceptions import (
+ AirflowDagCycleException,
+ AirflowException,
+ DuplicateTaskIdFound,
+ TaskAlreadyInTaskGroup,
+)
+from airflow.sdk.definitions.node import DAGNode
+from airflow.serialization.enums import DagAttributeTypes
+
+if TYPE_CHECKING:
+ from airflow.models.expandinput import ExpandInput
+ from airflow.sdk.definitions.abstractoperator import AbstractOperator
+ from airflow.sdk.definitions.baseoperator import BaseOperator
+ from airflow.sdk.definitions.dag import DAG
+ from airflow.sdk.definitions.edges import EdgeModifier
+ from airflow.sdk.definitions.mixins import DependencyMixin
+
+# TODO: The following mapping is used to validate that the arguments passed to the TaskGroup are of the
+# correct type. This is a temporary solution until we find a more sophisticated method for argument
+# validation. One potential method is to use get_type_hints from the typing module. However, this is not
+# fully compatible with future annotations for Python versions below 3.10. Once we require a minimum Python
+# version that supports `get_type_hints` effectively or find a better approach, we can replace this
+# manual type-checking method.
+TASKGROUP_ARGS_EXPECTED_TYPES = {
+ "group_id": str,
+ "prefix_group_id": bool,
+ "tooltip": str,
+ "ui_color": str,
+ "ui_fgcolor": str,
+ "add_suffix_on_collision": bool,
+}
+
+
+@attrs.define()
+class TaskGroup(DAGNode):
+ """
+ A collection of tasks.
+
+ When set_downstream() or set_upstream() are called on the TaskGroup, it is applied across
+ all tasks within the group if necessary.
+
+ :param group_id: a unique, meaningful id for the TaskGroup. group_id must not conflict
+ with group_id of TaskGroup or task_id of tasks in the DAG. Root TaskGroup has group_id
+ set to None.
+ :param prefix_group_id: If set to True, child task_id and group_id will be prefixed with
+ this TaskGroup's group_id. If set to False, child task_id and group_id are not prefixed.
+ Default is True.
+ :param parent_group: The parent TaskGroup of this TaskGroup. parent_group is set to None
+ for the root TaskGroup.
+ :param dag: The DAG that this TaskGroup belongs to.
+ :param default_args: A dictionary of default parameters to be used
+ as constructor keyword parameters when initialising operators,
+ will override default_args defined in the DAG level.
+ Note that operators have the same hook, and precede those defined
+ here, meaning that if your dict contains `'depends_on_past': True`
+ here and `'depends_on_past': False` in the operator's call
+ `default_args`, the actual value will be `False`.
+ :param tooltip: The tooltip of the TaskGroup node when displayed in the UI
+ :param ui_color: The fill color of the TaskGroup node when displayed in the UI
+ :param ui_fgcolor: The label color of the TaskGroup node when displayed in the UI
+ :param add_suffix_on_collision: If this task group name already exists,
+ automatically add `__1` etc suffixes
+ """
+
+ group_id: str
+ prefix_group_id: bool = True
+ parent_group: TaskGroup | None = None
+ dag: DAG | None = None
+ default_args: dict[str, Any] = attrs.field(factory=dict, converter=copy.deepcopy)
+ children: dict[str, DAGNode] = attrs.field(factory=dict, init=False)
+
+ upstream_group_ids: set[str | None] = attrs.field(factory=set, init=False)
+ downstream_group_ids: set[str | None] = attrs.field(factory=set, init=False)
+ upstream_task_ids: set[str] = attrs.field(factory=set, init=False)
+ downstream_task_ids: str[str] = attrs.field(factory=set, init=False)
+
+ used_group_ids: set[str] = attrs.field(factory=set, init=False, on_setattr=attrs.setters.NO_OP)
+
+ def __atrs_post_init__(self):
+ if self.parent_group:
+ self.parent_group.add(self)
+ if self.parent_group.default_args:
+ self.default_args = {**self.parent_group.default_args, **self.default_args}
+
+ if self.group_id:
+ self.used_group_ids.add(self.group_id)
+ self.used_group_ids.add(self.downstream_join_id)
+ self.used_group_ids.add(self.upstream_join_id)
+
+ def _check_for_group_id_collisions(self, add_suffix_on_collision: bool):
+ if self._group_id is None:
+ return
+ # if given group_id already used assign suffix by incrementing largest used suffix integer
+ # Example : task_group ==> task_group__1 -> task_group__2 -> task_group__3
+ if self._group_id in self.used_group_ids:
+ if not add_suffix_on_collision:
+ raise DuplicateTaskIdFound(f"group_id '{self._group_id}' has already been added to the DAG")
+ base = re2.split(r"__\d+$", self._group_id)[0]
+ suffixes = sorted(
+ int(re2.split(r"^.+__", used_group_id)[1])
+ for used_group_id in self.used_group_ids
+ if used_group_id is not None and re2.match(rf"^{base}__\d+$", used_group_id)
+ )
+ if not suffixes:
+ self._group_id += "__1"
+ else:
+ self._group_id = f"{base}__{suffixes[-1] + 1}"
+
+ @classmethod
+ def create_root(cls, dag: DAG) -> TaskGroup:
+ """Create a root TaskGroup with no group_id or parent."""
+ return cls(group_id=None, dag=dag)
+
+ @property
+ def node_id(self):
+ return self.group_id
+
+ @property
+ def is_root(self) -> bool:
+ """Returns True if this TaskGroup is the root TaskGroup. Otherwise False."""
+ return not self.group_id
+
+ @property
+ def parent_group(self) -> TaskGroup | None:
+ return self.task_group
+
+ def __iter__(self):
+ for child in self.children.values():
+ if isinstance(child, TaskGroup):
+ yield from child
+ else:
+ yield child
+
+ def add(self, task: DAGNode) -> DAGNode:
+ """
+ Add a task to this TaskGroup.
+
+ :meta private:
+ """
+ from airflow.sdk.definitions.abstractoperator import AbstractOperator
+ from airflow.sdk.definitions.contextmanager import TaskGroupContext
+
+ if TaskGroupContext.active:
+ if task.task_group and task.task_group != self:
+ task.task_group.children.pop(task.node_id, None)
+ task.task_group = self
+ existing_tg = task.task_group
+ if isinstance(task, AbstractOperator) and existing_tg is not None and existing_tg != self:
+ raise TaskAlreadyInTaskGroup(task.node_id, existing_tg.node_id, self.node_id)
+
+ # Set the TG first, as setting it might change the return value of node_id!
+ task.task_group = weakref.proxy(self)
+ key = task.node_id
+
+ if key in self.children:
+ node_type = "Task" if hasattr(task, "task_id") else "Task Group"
+ raise DuplicateTaskIdFound(f"{node_type} id '{key}' has already been added to the DAG")
+
+ if isinstance(task, TaskGroup):
+ if self.dag:
+ if task.dag is not None and self.dag is not task.dag:
+ raise RuntimeError(
+ "Cannot mix TaskGroups from different DAGs: %s and %s", self.dag, task.dag
+ )
+ task.dag = self.dag
+ if task.children:
+ raise AirflowException("Cannot add a non-empty TaskGroup")
+
+ self.children[key] = task
+ return task
+
+ def _remove(self, task: DAGNode) -> None:
+ key = task.node_id
+
+ if key not in self.children:
+ raise KeyError(f"Node id {key!r} not part of this task group")
+
+ self.used_group_ids.remove(key)
+ del self.children[key]
+
+ @property
+ def group_id(self) -> str | None:
+ """group_id of this TaskGroup."""
+ if self.task_group and self.task_group.prefix_group_id and self.task_group._group_id:
+ # defer to parent whether it adds a prefix
+ return self.task_group.child_id(self._group_id)
+
+ return self._group_id
+
+ @property
+ def label(self) -> str | None:
+ """group_id excluding parent's group_id used as the node label in UI."""
+ return self._group_id
+
+ def update_relative(
+ self, other: DependencyMixin, upstream: bool = True, edge_modifier: EdgeModifier | None = None
+ ) -> None:
+ """
+ Override TaskMixin.update_relative.
+
+ Update upstream_group_ids/downstream_group_ids/upstream_task_ids/downstream_task_ids
+ accordingly so that we can reduce the number of edges when displaying Graph view.
+ """
+ if isinstance(other, TaskGroup):
+ # Handles setting relationship between a TaskGroup and another TaskGroup
+ if upstream:
+ parent, child = (self, other)
+ if edge_modifier:
+ edge_modifier.add_edge_info(self.dag, other.downstream_join_id, self.upstream_join_id)
+ else:
+ parent, child = (other, self)
+ if edge_modifier:
+ edge_modifier.add_edge_info(self.dag, self.downstream_join_id, other.upstream_join_id)
+
+ parent.upstream_group_ids.add(child.group_id)
+ child.downstream_group_ids.add(parent.group_id)
+ else:
+ # Handles setting relationship between a TaskGroup and a task
+ for task in other.roots:
+ if not isinstance(task, DAGNode):
+ raise AirflowException(
+ "Relationships can only be set between TaskGroup "
+ f"or operators; received {task.__class__.__name__}"
+ )
+
+ # Do not set a relationship between a TaskGroup and a Label's roots
+ if self == task:
+ continue
+
+ if upstream:
+ self.upstream_task_ids.add(task.node_id)
+ if edge_modifier:
+ edge_modifier.add_edge_info(self.dag, task.node_id, self.upstream_join_id)
+ else:
+ self.downstream_task_ids.add(task.node_id)
+ if edge_modifier:
+ edge_modifier.add_edge_info(self.dag, self.downstream_join_id, task.node_id)
+
+ def _set_relatives(
+ self,
+ task_or_task_list: DependencyMixin | Sequence[DependencyMixin],
+ upstream: bool = False,
+ edge_modifier: EdgeModifier | None = None,
+ ) -> None:
+ """
+ Call set_upstream/set_downstream for all root/leaf tasks within this TaskGroup.
+
+ Update upstream_group_ids/downstream_group_ids/upstream_task_ids/downstream_task_ids.
+ """
+ if not isinstance(task_or_task_list, Sequence):
+ task_or_task_list = [task_or_task_list]
+
+ for task_like in task_or_task_list:
+ self.update_relative(task_like, upstream, edge_modifier=edge_modifier)
+
+ if upstream:
+ for task in self.get_roots():
+ task.set_upstream(task_or_task_list)
+ else:
+ for task in self.get_leaves():
+ task.set_downstream(task_or_task_list)
+
+ def __enter__(self) -> TaskGroup:
+ from airflow.sdk.definitions.contextmanager import TaskGroupContext
+
+ TaskGroupContext.push(self)
+ return self
+
+ def __exit__(self, _type, _value, _tb):
+ from airflow.sdk.definitions.contextmanager import TaskGroupContext
+
+ TaskGroupContext.pop()
+
+ def has_task(self, task: BaseOperator) -> bool:
+ """Return True if this TaskGroup or its children TaskGroups contains the given task."""
+ if task.task_id in self.children:
+ return True
+
+ return any(child.has_task(task) for child in self.children.values() if isinstance(child, TaskGroup))
+
+ @property
+ def roots(self) -> list[BaseOperator]:
+ """Required by DependencyMixin."""
+ return list(self.get_roots())
+
+ @property
+ def leaves(self) -> list[BaseOperator]:
+ """Required by DependencyMixin."""
+ return list(self.get_leaves())
+
+ def get_roots(self) -> Generator[BaseOperator, None, None]:
+ """Return a generator of tasks with no upstream dependencies within the TaskGroup."""
+ tasks = list(self)
+ ids = {x.task_id for x in tasks}
+ for task in tasks:
+ if task.upstream_task_ids.isdisjoint(ids):
+ yield task
+
+ def get_leaves(self) -> Generator[BaseOperator, None, None]:
+ """Return a generator of tasks with no downstream dependencies within the TaskGroup."""
+ tasks = list(self)
+ ids = {x.task_id for x in tasks}
+
+ def has_non_teardown_downstream(task, exclude: str):
+ for down_task in task.downstream_list:
+ if down_task.task_id == exclude:
+ continue
+ elif down_task.task_id not in ids:
+ continue
+ elif not down_task.is_teardown:
+ return True
+ return False
+
+ def recurse_for_first_non_teardown(task):
+ for upstream_task in task.upstream_list:
+ if upstream_task.task_id not in ids:
+ # upstream task is not in task group
+ continue
+ elif upstream_task.is_teardown:
+ yield from recurse_for_first_non_teardown(upstream_task)
+ elif task.is_teardown and upstream_task.is_setup:
+ # don't go through the teardown-to-setup path
+ continue
+ # return unless upstream task already has non-teardown downstream in group
+ elif not has_non_teardown_downstream(upstream_task, exclude=task.task_id):
+ yield upstream_task
+
+ for task in tasks:
+ if task.downstream_task_ids.isdisjoint(ids):
+ if not task.is_teardown:
+ yield task
+ else:
+ yield from recurse_for_first_non_teardown(task)
+
+ def child_id(self, label):
+ """Prefix label with group_id if prefix_group_id is True. Otherwise return the label as-is."""
+ if self.prefix_group_id:
+ group_id = self.group_id
+ if group_id:
+ return f"{group_id}.{label}"
+
+ return label
+
+ @property
+ def upstream_join_id(self) -> str:
+ """
+ Creates a unique ID for upstream dependencies of this TaskGroup.
+
+ If this TaskGroup has immediate upstream TaskGroups or tasks, a proxy node called
+ upstream_join_id will be created in Graph view to join the outgoing edges from this
+ TaskGroup to reduce the total number of edges needed to be displayed.
+ """
+ return f"{self.group_id}.upstream_join_id"
+
+ @property
+ def downstream_join_id(self) -> str:
+ """
+ Creates a unique ID for downstream dependencies of this TaskGroup.
+
+ If this TaskGroup has immediate downstream TaskGroups or tasks, a proxy node called
+ downstream_join_id will be created in Graph view to join the outgoing edges from this
+ TaskGroup to reduce the total number of edges needed to be displayed.
+ """
+ return f"{self.group_id}.downstream_join_id"
+
+ def get_task_group_dict(self) -> dict[str, TaskGroup]:
+ """Return a flat dictionary of group_id: TaskGroup."""
+ task_group_map = {}
+
+ def build_map(task_group):
+ if not isinstance(task_group, TaskGroup):
+ return
+
+ task_group_map[task_group.group_id] = task_group
+
+ for child in task_group.children.values():
+ build_map(child)
+
+ build_map(self)
+ return task_group_map
+
+ def get_child_by_label(self, label: str) -> DAGNode:
+ """Get a child task/TaskGroup by its label (i.e. task_id/group_id without the group_id prefix)."""
+ return self.children[self.child_id(label)]
+
+ def serialize_for_task_group(self) -> tuple[DagAttributeTypes, Any]:
+ """Serialize task group; required by DAGNode."""
+ from airflow.serialization.serialized_objects import TaskGroupSerialization
+
+ return DagAttributeTypes.TASK_GROUP, TaskGroupSerialization.serialize_task_group(self)
+
+ def hierarchical_alphabetical_sort(self):
+ """
+ Sort children in hierarchical alphabetical order.
+
+ - groups in alphabetical order first
+ - tasks in alphabetical order after them.
+
+ :return: list of tasks in hierarchical alphabetical order
+ """
+ return sorted(
+ self.children.values(), key=lambda node: (not isinstance(node, TaskGroup), node.node_id)
+ )
+
+ def topological_sort(self):
+ """
+ Sorts children in topographical order, such that a task comes after any of its upstream dependencies.
+
+ :return: list of tasks in topological order
+ """
+ # This uses a modified version of Kahn's Topological Sort algorithm to
+ # not have to pre-compute the "in-degree" of the nodes.
+ graph_unsorted = copy.copy(self.children)
+
+ graph_sorted: list[DAGNode] = []
+
+ # special case
+ if not self.children:
+ return graph_sorted
+
+ # Run until the unsorted graph is empty.
+ while graph_unsorted:
+ # Go through each of the node/edges pairs in the unsorted graph. If a set of edges doesn't contain
+ # any nodes that haven't been resolved, that is, that are still in the unsorted graph, remove the
+ # pair from the unsorted graph, and append it to the sorted graph. Note here that by using
+ # the values() method for iterating, a copy of the unsorted graph is used, allowing us to modify
+ # the unsorted graph as we move through it.
+ #
+ # We also keep a flag for checking that graph is acyclic, which is true if any nodes are resolved
+ # during each pass through the graph. If not, we need to exit as the graph therefore can't be
+ # sorted.
+ acyclic = False
+ for node in list(graph_unsorted.values()):
+ for edge in node.upstream_list:
+ if edge.node_id in graph_unsorted:
+ break
+ # Check for task's group is a child (or grand child) of this TG,
+ tg = edge.task_group
+ while tg:
+ if tg.node_id in graph_unsorted:
+ break
+ tg = tg.task_group
+
+ if tg:
+ # We are already going to visit that TG
+ break
+ else:
+ acyclic = True
+ del graph_unsorted[node.node_id]
+ graph_sorted.append(node)
+
+ if not acyclic:
+ raise AirflowDagCycleException(f"A cyclic dependency occurred in dag: {self.dag_id}")
+
+ return graph_sorted
+
+ def iter_mapped_task_groups(self) -> Iterator[MappedTaskGroup]:
+ """
+ Return mapped task groups in the hierarchy.
+
+ Groups are returned from the closest to the outmost. If *self* is a
+ mapped task group, it is returned first.
+
+ :meta private:
+ """
+ group: TaskGroup | None = self
+ while group is not None:
+ if isinstance(group, MappedTaskGroup):
+ yield group
+ group = group.task_group
+
+ def iter_tasks(self) -> Iterator[AbstractOperator]:
+ """Return an iterator of the child tasks."""
+ from airflow.models.abstractoperator import AbstractOperator
+
+ groups_to_visit = [self]
+
+ while groups_to_visit:
+ visiting = groups_to_visit.pop(0)
+
+ for child in visiting.children.values():
+ if isinstance(child, AbstractOperator):
+ yield child
+ elif isinstance(child, TaskGroup):
+ groups_to_visit.append(child)
+ else:
+ raise ValueError(
+ f"Encountered a DAGNode that is not a TaskGroup or an AbstractOperator: {type(child)}"
+ )
+
+
+class MappedTaskGroup(TaskGroup):
+ """
+ A mapped task group.
+
+ This doesn't really do anything special, just holds some additional metadata
+ for expansion later.
+
+ Don't instantiate this class directly; call *expand* or *expand_kwargs* on
+ a ``@task_group`` function instead.
+ """
+
+ def __init__(self, *, expand_input: ExpandInput, **kwargs: Any) -> None:
+ super().__init__(**kwargs)
+ self._expand_input = expand_input
+
+ def iter_mapped_dependencies(self) -> Iterator[DAGNode]:
+ """Upstream dependencies that provide XComs used by this mapped task group."""
+ from airflow.models.xcom_arg import XComArg
+
+ for op, _ in XComArg.iter_xcom_references(self._expand_input):
+ yield op
+
+ @methodtools.lru_cache(maxsize=None)
+ def get_parse_time_mapped_ti_count(self) -> int:
+ """
+ Return the Number of instances a task in this group should be mapped to, when a DAG run is created.
+
+ This only considers literal mapped arguments, and would return *None*
+ when any non-literal values are used for mapping.
+
+ If this group is inside mapped task groups, all the nested counts are
+ multiplied and accounted.
+
+ :meta private:
+
+ :raise NotFullyPopulated: If any non-literal mapped arguments are encountered.
+ :return: The total number of mapped instances each task should have.
+ """
+ return functools.reduce(
+ operator.mul,
+ (g._expand_input.get_parse_time_mapped_ti_count() for g in self.iter_mapped_task_groups()),
+ )
+
+ def __exit__(self, exc_type, exc_val, exc_tb):
+ for op, _ in self._expand_input.iter_references():
+ self.set_upstream(op)
+ super().__exit__(exc_type, exc_val, exc_tb)
+
+
+def task_group_to_dict(task_item_or_group):
+ """Create a nested dict representation of this TaskGroup and its children used to construct the Graph."""
+ from airflow.models.abstractoperator import AbstractOperator
+ from airflow.models.mappedoperator import MappedOperator
+
+ if isinstance(task := task_item_or_group, AbstractOperator):
+ setup_teardown_type = {}
+ is_mapped = {}
+ if task.is_setup is True:
+ setup_teardown_type["setupTeardownType"] = "setup"
+ elif task.is_teardown is True:
+ setup_teardown_type["setupTeardownType"] = "teardown"
+ if isinstance(task, MappedOperator):
+ is_mapped["isMapped"] = True
+ return {
+ "id": task.task_id,
+ "value": {
+ "label": task.label,
+ "labelStyle": f"fill:{task.ui_fgcolor};",
+ "style": f"fill:{task.ui_color};",
+ "rx": 5,
+ "ry": 5,
+ **is_mapped,
+ **setup_teardown_type,
+ },
+ }
+ task_group = task_item_or_group
+ is_mapped = isinstance(task_group, MappedTaskGroup)
+ children = [
+ task_group_to_dict(child) for child in sorted(task_group.children.values(), key=lambda t: t.label)
+ ]
+
+ if task_group.upstream_group_ids or task_group.upstream_task_ids:
+ children.append(
+ {
+ "id": task_group.upstream_join_id,
+ "value": {
+ "label": "",
+ "labelStyle": f"fill:{task_group.ui_fgcolor};",
+ "style": f"fill:{task_group.ui_color};",
+ "shape": "circle",
+ },
+ }
+ )
+
+ if task_group.downstream_group_ids or task_group.downstream_task_ids:
+ # This is the join node used to reduce the number of edges between two TaskGroup.
+ children.append(
+ {
+ "id": task_group.downstream_join_id,
+ "value": {
+ "label": "",
+ "labelStyle": f"fill:{task_group.ui_fgcolor};",
+ "style": f"fill:{task_group.ui_color};",
+ "shape": "circle",
+ },
+ }
+ )
+
+ return {
+ "id": task_group.group_id,
+ "value": {
+ "label": task_group.label,
+ "labelStyle": f"fill:{task_group.ui_fgcolor};",
+ "style": f"fill:{task_group.ui_color}",
+ "rx": 5,
+ "ry": 5,
+ "clusterLabelPos": "top",
+ "tooltip": task_group.tooltip,
+ "isMapped": is_mapped,
+ },
+ "children": children,
+ }
diff --git a/task_sdk/pyproject.toml b/task_sdk/src/airflow/sdk/exceptions.py
similarity index 59%
copy from task_sdk/pyproject.toml
copy to task_sdk/src/airflow/sdk/exceptions.py
index 149a9731ce9..13a83393a91 100644
--- a/task_sdk/pyproject.toml
+++ b/task_sdk/src/airflow/sdk/exceptions.py
@@ -14,27 +14,3 @@
# KIND, either express or implied. See the License for the
# specific language governing permissions and limitations
# under the License.
-
-[project]
-name = "apache-airflow-task-sdk"
-version = "0.1.0.dev0"
-description = "Python Task SDK for Apache Airflow DAG Authors"
-#readme = "README.md"
-requires-python = ">=3.9, <3.13"
-dependencies = []
-
-[build-system]
-requires = ["hatchling"]
-build-backend = "hatchling.build"
-
-[tool.hatch.build.targets.wheel]
-packages = ["src/airflow"]
-
-[tool.ruff]
-extend = "../pyproject.toml"
-src = ["src"]
-
-[tool.ruff.lint.per-file-ignores]
-
-# Ignore Doc rules et al for anything outside of tests
-"!src/*" = ["D", "TID253", "S101", "TRY002"]
diff --git a/task_sdk/pyproject.toml b/task_sdk/src/airflow/sdk/types.py
similarity index 58%
copy from task_sdk/pyproject.toml
copy to task_sdk/src/airflow/sdk/types.py
index 149a9731ce9..172ff733a14 100644
--- a/task_sdk/pyproject.toml
+++ b/task_sdk/src/airflow/sdk/types.py
@@ -15,26 +15,35 @@
# specific language governing permissions and limitations
# under the License.
-[project]
-name = "apache-airflow-task-sdk"
-version = "0.1.0.dev0"
-description = "Python Task SDK for Apache Airflow DAG Authors"
-#readme = "README.md"
-requires-python = ">=3.9, <3.13"
-dependencies = []
+from __future__ import annotations
-[build-system]
-requires = ["hatchling"]
-build-backend = "hatchling.build"
+from typing import TYPE_CHECKING
-[tool.hatch.build.targets.wheel]
-packages = ["src/airflow"]
-[tool.ruff]
-extend = "../pyproject.toml"
-src = ["src"]
+class ArgNotSet:
+ """
+ Sentinel type for annotations, useful when None is not viable.
-[tool.ruff.lint.per-file-ignores]
+ Use like this::
-# Ignore Doc rules et al for anything outside of tests
-"!src/*" = ["D", "TID253", "S101", "TRY002"]
+ def is_arg_passed(arg: Union[ArgNotSet, None] = NOTSET) -> bool:
+ if arg is NOTSET:
+ return False
+ return True
+
+
+ is_arg_passed() # False.
+ is_arg_passed(None) # True.
+ """
+
+
+NOTSET = ArgNotSet()
+
+
+if TYPE_CHECKING:
+ import structlog
+
+ Logger = structlog.typing.FilteringBoundLogger
+else:
+
+ class Logger: ...
diff --git a/task_sdk/tests/defintions/test_dag.py b/task_sdk/tests/defintions/test_dag.py
new file mode 100644
index 00000000000..e07e3a8bfa8
--- /dev/null
+++ b/task_sdk/tests/defintions/test_dag.py
@@ -0,0 +1,78 @@
+# 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.
+
+from __future__ import annotations
+
+from datetime import UTC, datetime
+
+from airflow.sdk.definitions.baseoperator import BaseOperator
+from airflow.sdk.definitions.dag import DAG
+
+DEFAULT_DATE = datetime(2016, 1, 1, tzinfo=UTC)
+
+
+class TestDag:
+ def test_dag_as_context_manager(self):
+ """
+ Test DAG as a context manager.
+ When used as a context manager, Operators are automatically added to
+ the DAG (unless they specify a different DAG)
+ """
+ dag = DAG("dag", schedule=None, start_date=DEFAULT_DATE, default_args={"owner": "owner1"})
+ dag2 = DAG("dag2", schedule=None, start_date=DEFAULT_DATE, default_args={"owner": "owner2"})
+
+ with dag:
+ op1 = BaseOperator(task_id="op1")
+ op2 = BaseOperator(task_id="op2", dag=dag2)
+
+ assert op1.dag is dag
+ assert op1.owner == "owner1"
+ assert op2.dag is dag2
+ assert op2.owner == "owner2"
+
+ with dag2:
+ op3 = BaseOperator(task_id="op3")
+
+ assert op3.dag is dag2
+ assert op3.owner == "owner2"
+
+ with dag:
+ with dag2:
+ op4 = BaseOperator(task_id="op4")
+ op5 = BaseOperator(task_id="op5")
+
+ assert op4.dag is dag2
+ assert op5.dag is dag
+ assert op4.owner == "owner2"
+ assert op5.owner == "owner1"
+
+ with DAG("creating_dag_in_cm", schedule=None, start_date=DEFAULT_DATE) as dag:
+ BaseOperator(task_id="op6")
+
+ assert dag.dag_id == "creating_dag_in_cm"
+ assert dag.tasks[0].task_id == "op6"
+
+ with dag:
+ with dag:
+ op7 = BaseOperator(task_id="op7")
+ op8 = BaseOperator(task_id="op8")
+ op9 = BaseOperator(task_id="op8")
+ op9.dag = dag2
+
+ assert op7.dag == dag
+ assert op8.dag == dag
+ assert op9.dag == dag2
diff --git a/uv.lock b/uv.lock
new file mode 100644
index 00000000000..d3508fac220
--- /dev/null
+++ b/uv.lock
@@ -0,0 +1,4220 @@
+version = 1
+requires-python = ">=3.9, <3.13"
+resolution-markers = [
+ "python_full_version < '3.12'",
+ "python_full_version >= '3.12'",
+]
+
+[manifest]
+members = [
+ "apache-airflow",
+ "apache-airflow-task-sdk",
+ "local-providers",
+]
+
+[[package]]
+name = "aiohappyeyeballs"
+version = "2.4.3"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/bc/69/2f6d5a019bd02e920a3417689a89887b39ad1e350b562f9955693d900c40/aiohappyeyeballs-2.4.3.tar.gz", hash = "sha256:75cf88a15106a5002a8eb1dab212525c00d1f4c0fa96e551c9fbe6f09a621586", size = 21809 }
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+]
+
+[[package]]
+name = "aiohttp"
+version = "3.10.9"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+ { name = "aiohappyeyeballs" },
+ { name = "aiosignal" },
+ { name = "async-timeout", marker = "python_full_version < '3.11'" },
+ { name = "attrs" },
+ { name = "frozenlist" },
+ { name = "multidict" },
+ { name = "yarl" },
+]
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