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# 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
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from __future__ import annotations
from abc import ABC, abstractmethod
from typing import TYPE_CHECKING, Any, TypeAlias
from airflow._shared.timezones import timezone
from airflow.serialization.definitions.assets import SerializedAsset, SerializedAssetAll, SerializedAssetBase
from airflow.timetables.base import DagRunInfo, DataInterval, Timetable
try:
from airflow.sdk.definitions.asset import BaseAsset
from airflow.serialization.encoders import ensure_serialized_asset
except ModuleNotFoundError:
[docs]
BaseAsset: TypeAlias = SerializedAssetBase # type: ignore[no-redef]
def ensure_serialized_asset(o): # type: ignore[misc,no-redef]
return o
if TYPE_CHECKING:
from collections.abc import Collection, Iterable, Sequence
from pendulum import DateTime
from airflow.timetables.base import TimeRestriction
from airflow.utils.types import DagRunType
class _TrivialTimetable(Timetable):
"""Some code reuse for "trivial" timetables that has nothing complex."""
periodic = False
run_ordering: Sequence[str] = ("logical_date",)
@classmethod
def deserialize(cls, data: dict[str, Any]) -> Timetable:
return cls()
def __eq__(self, other: object) -> bool:
"""
As long as *other* is of the same type.
This is only for testing purposes and should not be relied on otherwise.
"""
from airflow.serialization.encoders import coerce_to_core_timetable
if not isinstance(other := coerce_to_core_timetable(other), type(self)):
return NotImplemented
return True
def __hash__(self):
return hash(self.__class__.__name__)
def infer_manual_data_interval(self, *, run_after: DateTime) -> DataInterval:
return DataInterval.exact(run_after)
class AssetTriggeredTimetable(_TrivialTimetable):
"""
Timetable that never schedules anything.
This should not be directly used anywhere, but only set if a DAG is triggered by assets.
:meta private:
"""
description: str = "Triggered by assets"
def __init__(self, assets: Collection[SerializedAsset] | SerializedAssetBase) -> None:
super().__init__()
# Compatibility: Handle SDK assets if needed so this class works in dag files.
if isinstance(assets, SerializedAssetBase | BaseAsset):
self.asset_condition = ensure_serialized_asset(assets)
else:
self.asset_condition = SerializedAssetAll([ensure_serialized_asset(a) for a in assets])
@classmethod
def deserialize(cls, data: dict[str, Any]) -> Timetable:
from airflow.serialization.decoders import decode_asset_like
return cls(decode_asset_like(data["asset_condition"]))
@property
def summary(self) -> str:
return "Asset"
def serialize(self) -> dict[str, Any]:
from airflow.serialization.encoders import encode_asset_like
return {"asset_condition": encode_asset_like(self.asset_condition)}
def generate_run_id(
self,
*,
run_type: DagRunType,
data_interval: DataInterval | None,
run_after: DateTime,
**extra,
) -> str:
"""
Generate Run ID based on Run Type, run_after and logical Date.
:param run_type: type of DagRun
:param data_interval: the data interval
:param run_after: the date before which dag run won't start.
"""
from airflow.models.dagrun import DagRun
logical_date = data_interval.start if data_interval is not None else run_after
return DagRun.generate_run_id(run_type=run_type, logical_date=logical_date, run_after=run_after)
def next_dagrun_info(
self,
*,
last_automated_data_interval: DataInterval | None,
restriction: TimeRestriction,
) -> DagRunInfo | None:
return None
[docs]
class PartitionMapper(ABC):
"""
Base partition mapper class.
Maps keys from asset events to target dag run partitions.
"""
@abstractmethod
[docs]
def to_downstream(self, key: str) -> str:
"""Return the target key that the given source partition key maps to."""
@abstractmethod
[docs]
def to_upstream(self, key: str) -> Iterable[str]:
"""Yield the source keys that map to the given target partition key."""
[docs]
def serialize(self) -> dict[str, Any]:
return {}
@classmethod
[docs]
def deserialize(cls, data: dict[str, Any]) -> PartitionMapper:
return cls()
[docs]
class IdentityMapper(PartitionMapper):
"""Partition mapper that does not change the key."""
[docs]
def to_downstream(self, key: str) -> str:
return key
[docs]
def to_upstream(self, key: str) -> Iterable[str]:
yield key