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# to you under the Apache License, Version 2.0 (the
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#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
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# 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
import inspect
from typing import TYPE_CHECKING, Any, Callable, ClassVar, Collection, Iterable, Iterator, Sequence
from airflow.compat.functools import cached_property
from airflow.configuration import conf
from airflow.exceptions import AirflowException
from airflow.models.taskmixin import DAGNode
from airflow.utils.context import Context
from airflow.utils.helpers import render_template_as_native, render_template_to_string
from airflow.utils.log.logging_mixin import LoggingMixin
from airflow.utils.session import NEW_SESSION, provide_session
from airflow.utils.trigger_rule import TriggerRule
from airflow.utils.weight_rule import WeightRule
[docs]TaskStateChangeCallback = Callable[[Context], None]
if TYPE_CHECKING:
import jinja2 # Slow import.
from sqlalchemy.orm import Session
from airflow.models.baseoperator import BaseOperator, BaseOperatorLink
from airflow.models.dag import DAG
from airflow.models.mappedoperator import MappedOperator
from airflow.models.operator import Operator
from airflow.models.taskinstance import TaskInstance
[docs]DEFAULT_OWNER: str = conf.get_mandatory_value("operators", "default_owner")
[docs]DEFAULT_POOL_SLOTS: int = 1
[docs]DEFAULT_PRIORITY_WEIGHT: int = 1
[docs]DEFAULT_QUEUE: str = conf.get_mandatory_value("operators", "default_queue")
[docs]DEFAULT_IGNORE_FIRST_DEPENDS_ON_PAST: bool = conf.getboolean(
"scheduler", "ignore_first_depends_on_past_by_default"
)
[docs]DEFAULT_RETRIES: int = conf.getint("core", "default_task_retries", fallback=0)
[docs]DEFAULT_RETRY_DELAY: datetime.timedelta = datetime.timedelta(
seconds=conf.getint("core", "default_task_retry_delay", fallback=300)
)
[docs]DEFAULT_WEIGHT_RULE: WeightRule = WeightRule(
conf.get("core", "default_task_weight_rule", fallback=WeightRule.DOWNSTREAM)
)
[docs]DEFAULT_TRIGGER_RULE: TriggerRule = TriggerRule.ALL_SUCCESS
[docs]DEFAULT_TASK_EXECUTION_TIMEOUT: datetime.timedelta | None = conf.gettimedelta(
"core", "default_task_execution_timeout"
)
[docs]class AbstractOperator(LoggingMixin, 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:
"""
[docs] operator_class: type[BaseOperator] | dict[str, Any]
# Defines the operator level extra links.
# For derived classes to define which fields will get jinjaified.
[docs] template_fields: Collection[str]
# Defines which files extensions to look for in the templated fields.
[docs] template_ext: Sequence[str]
[docs] 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
# 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',
)
)
[docs] def get_dag(self) -> DAG | None:
raise NotImplementedError()
@property
[docs] def task_type(self) -> str:
raise NotImplementedError()
@property
[docs] def operator_name(self) -> str:
raise NotImplementedError()
@property
[docs] def inherits_from_empty_operator(self) -> bool:
raise NotImplementedError()
@property
[docs] 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
[docs] def node_id(self) -> str:
return self.task_id
[docs] def get_template_env(self) -> jinja2.Environment:
"""Fetch a Jinja template environment from the DAG or instantiate empty environment if no DAG."""
# This is imported locally since Jinja2 is heavy and we don't need it
# for most of the functionalities. It is imported by get_template_env()
# though, so we don't need to put this after the 'if dag' check.
from airflow.templates import SandboxedEnvironment
dag = self.get_dag()
if dag:
return dag.get_template_env(force_sandboxed=False)
return SandboxedEnvironment(cache_size=0)
[docs] def prepare_template(self) -> None:
"""Hook triggered after the templated fields get replaced by their content.
If you need your operator to alter the content of the file before the
template is rendered, it should override this method to do so.
"""
[docs] def resolve_template_files(self) -> None:
"""Getting the content of files for template_field / template_ext."""
if self.template_ext:
for field in self.template_fields:
content = getattr(self, field, None)
if content is None:
continue
elif isinstance(content, str) and any(content.endswith(ext) for ext in self.template_ext):
env = self.get_template_env()
try:
setattr(self, field, env.loader.get_source(env, content)[0]) # type: ignore
except Exception:
self.log.exception("Failed to resolve template field %r", field)
elif isinstance(content, list):
env = self.get_template_env()
for i, item in enumerate(content):
if isinstance(item, str) and any(item.endswith(ext) for ext in self.template_ext):
try:
content[i] = env.loader.get_source(env, item)[0] # type: ignore
except Exception:
self.log.exception("Failed to get source %s", item)
self.prepare_template()
[docs] def get_direct_relative_ids(self, upstream: bool = False) -> set[str]:
"""Get direct relative IDs to the current task, upstream or downstream."""
if upstream:
return self.upstream_task_ids
return self.downstream_task_ids
[docs] def get_flat_relative_ids(
self,
upstream: bool = False,
found_descendants: set[str] | None = None,
) -> set[str]:
"""Get a flat set of relative IDs, upstream or downstream."""
dag = self.get_dag()
if not dag:
return set()
if found_descendants is None:
found_descendants = set()
task_ids_to_trace = self.get_direct_relative_ids(upstream)
while task_ids_to_trace:
task_ids_to_trace_next: set[str] = set()
for task_id in task_ids_to_trace:
if task_id in found_descendants:
continue
task_ids_to_trace_next.update(dag.task_dict[task_id].get_direct_relative_ids(upstream))
found_descendants.add(task_id)
task_ids_to_trace = task_ids_to_trace_next
return found_descendants
[docs] def get_flat_relatives(self, upstream: bool = False) -> Collection[Operator]:
"""Get a flat list of relatives, either upstream or downstream."""
dag = self.get_dag()
if not dag:
return set()
return [dag.task_dict[task_id] for task_id in self.get_flat_relative_ids(upstream)]
def _iter_all_mapped_downstreams(self) -> Iterator[MappedOperator]:
"""Return mapped nodes that are direct dependencies of the current task.
For now, this walks the entire DAG to find mapped nodes that has this
current task as an upstream. We cannot use ``downstream_list`` since it
only contains operators, not task groups. In the future, we should
provide a way to record an DAG node's all downstream nodes instead.
Note that this does not guarantee the returned tasks actually use the
current task for task mapping, but only checks those task are mapped
operators, and are downstreams of the current task.
To get a list of tasks that uses the current task for task mapping, use
:meth:`iter_mapped_dependants` instead.
"""
from airflow.models.mappedoperator import MappedOperator
from airflow.utils.task_group import TaskGroup
def _walk_group(group: TaskGroup) -> Iterable[tuple[str, DAGNode]]:
"""Recursively walk children in a task group.
This yields all direct children (including both tasks and task
groups), and all children of any task groups.
"""
for key, child in group.children.items():
yield key, child
if isinstance(child, TaskGroup):
yield from _walk_group(child)
dag = self.get_dag()
if not dag:
raise RuntimeError("Cannot check for mapped dependants when not attached to a DAG")
for key, child in _walk_group(dag.task_group):
if key == self.node_id:
continue
if not isinstance(child, MappedOperator):
continue
if self.node_id in child.upstream_task_ids:
yield child
[docs] def iter_mapped_dependants(self) -> Iterator[MappedOperator]:
"""Return mapped nodes that depend on the current task the expansion.
For now, this walks the entire DAG to find mapped nodes that has this
current task as an upstream. We cannot use ``downstream_list`` since it
only contains operators, not task groups. In the future, we should
provide a way to record an DAG node's all downstream nodes instead.
"""
return (
downstream
for downstream in self._iter_all_mapped_downstreams()
if any(p.node_id == self.node_id for p in downstream.iter_mapped_dependencies())
)
[docs] def unmap(self, resolve: None | dict[str, Any] | tuple[Context, Session]) -> BaseOperator:
"""Get the "normal" operator from current abstract operator.
MappedOperator uses this to unmap itself based on the map index. A non-
mapped operator (i.e. BaseOperator subclass) simply returns itself.
:meta private:
"""
raise NotImplementedError()
@property
[docs] def priority_weight_total(self) -> int:
"""
Total priority weight for the task. It might include all upstream or downstream tasks.
Depending on the weight rule:
- WeightRule.ABSOLUTE - only own weight
- WeightRule.DOWNSTREAM - adds priority weight of all downstream tasks
- WeightRule.UPSTREAM - adds priority weight of all upstream tasks
"""
if self.weight_rule == WeightRule.ABSOLUTE:
return self.priority_weight
elif self.weight_rule == WeightRule.DOWNSTREAM:
upstream = False
elif self.weight_rule == WeightRule.UPSTREAM:
upstream = True
else:
upstream = False
dag = self.get_dag()
if dag is None:
return self.priority_weight
return self.priority_weight + sum(
dag.task_dict[task_id].priority_weight
for task_id in self.get_flat_relative_ids(upstream=upstream)
)
@cached_property
@cached_property
@cached_property
[docs] def render_template_fields(
self,
context: Context,
jinja_env: jinja2.Environment | None = None,
) -> None:
"""Template all attributes listed in template_fields.
If the operator is mapped, this should return the unmapped, fully
rendered, and map-expanded operator. The mapped operator should not be
modified. However, ``context`` will be modified in-place to reference
the unmapped operator for template rendering.
If the operator is not mapped, this should modify the operator in-place.
"""
raise NotImplementedError()
@provide_session
def _do_render_template_fields(
self,
parent: Any,
template_fields: Iterable[str],
context: Context,
jinja_env: jinja2.Environment,
seen_oids: set[int],
*,
session: Session = NEW_SESSION,
) -> None:
for attr_name in template_fields:
try:
value = getattr(parent, attr_name)
except AttributeError:
raise AttributeError(
f"{attr_name!r} is configured as a template field "
f"but {parent.task_type} does not have this attribute."
)
if not value:
continue
try:
rendered_content = self.render_template(
value,
context,
jinja_env,
seen_oids,
)
except Exception:
self.log.exception(
"Exception rendering Jinja template for task '%s', field '%s'. Template: %r",
self.task_id,
attr_name,
value,
)
raise
else:
setattr(parent, attr_name, rendered_content)
[docs] def render_template(
self,
content: Any,
context: Context,
jinja_env: jinja2.Environment | None = None,
seen_oids: set[int] | None = None,
) -> Any:
"""Render a templated string.
If *content* is a collection holding multiple templated strings, strings
in the collection will be templated recursively.
:param content: Content to template. Only strings can be templated (may
be inside a collection).
:param context: Dict with values to apply on templated content
:param jinja_env: Jinja environment. Can be provided to avoid
re-creating Jinja environments during recursion.
:param seen_oids: template fields already rendered (to avoid
*RecursionError* on circular dependencies)
:return: Templated content
"""
# "content" is a bad name, but we're stuck to it being public API.
value = content
del content
if seen_oids is not None:
oids = seen_oids
else:
oids = set()
if id(value) in oids:
return value
if not jinja_env:
jinja_env = self.get_template_env()
from airflow.models.param import DagParam
from airflow.models.xcom_arg import XComArg
if isinstance(value, str):
if any(value.endswith(ext) for ext in self.template_ext): # A filepath.
template = jinja_env.get_template(value)
else:
template = jinja_env.from_string(value)
dag = self.get_dag()
if dag and dag.render_template_as_native_obj:
return render_template_as_native(template, context)
return render_template_to_string(template, context)
if isinstance(value, (DagParam, XComArg)):
return value.resolve(context)
# Fast path for common built-in collections.
if value.__class__ is tuple:
return tuple(self.render_template(element, context, jinja_env, oids) for element in value)
elif isinstance(value, tuple): # Special case for named tuples.
return value.__class__(*(self.render_template(el, context, jinja_env, oids) for el in value))
elif isinstance(value, list):
return [self.render_template(element, context, jinja_env, oids) for element in value]
elif isinstance(value, dict):
return {k: self.render_template(v, context, jinja_env, oids) for k, v in value.items()}
elif isinstance(value, set):
return {self.render_template(element, context, jinja_env, oids) for element in value}
# More complex collections.
self._render_nested_template_fields(value, context, jinja_env, oids)
return value
def _render_nested_template_fields(
self,
value: Any,
context: Context,
jinja_env: jinja2.Environment,
seen_oids: set[int],
) -> None:
if id(value) in seen_oids:
return
seen_oids.add(id(value))
try:
nested_template_fields = value.template_fields
except AttributeError:
# content has no inner template fields
return
self._do_render_template_fields(value, nested_template_fields, context, jinja_env, seen_oids)
