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from functools import update_wrapper
from typing import TYPE_CHECKING, AbstractSet, Any, Callable, Mapping, Optional, Union, overload
import dagster._check as check
from dagster._annotations import deprecated_param
from dagster._core.decorator_utils import format_docstring_for_description
from ..config import ConfigMapping
from ..graph_definition import GraphDefinition
from ..hook_definition import HookDefinition
from ..job_definition import JobDefinition
from ..logger_definition import LoggerDefinition
from ..metadata import RawMetadataValue
from ..policy import RetryPolicy
from ..resource_definition import ResourceDefinition
from ..version_strategy import VersionStrategy
if TYPE_CHECKING:
from ..executor_definition import ExecutorDefinition
from ..partition import PartitionedConfig, PartitionsDefinition
from ..run_config import RunConfig
class _Job:
def __init__(
self,
name: Optional[str] = None,
description: Optional[str] = None,
tags: Optional[Mapping[str, Any]] = None,
metadata: Optional[Mapping[str, RawMetadataValue]] = None,
resource_defs: Optional[Mapping[str, ResourceDefinition]] = None,
config: Optional[
Union[ConfigMapping, Mapping[str, Any], "RunConfig", "PartitionedConfig"]
] = None,
logger_defs: Optional[Mapping[str, LoggerDefinition]] = None,
executor_def: Optional["ExecutorDefinition"] = None,
hooks: Optional[AbstractSet[HookDefinition]] = None,
op_retry_policy: Optional[RetryPolicy] = None,
version_strategy: Optional[VersionStrategy] = None,
partitions_def: Optional["PartitionsDefinition"] = None,
input_values: Optional[Mapping[str, object]] = None,
):
from dagster._core.definitions.run_config import convert_config_input
self.name = name
self.description = description
self.tags = tags
self.metadata = metadata
self.resource_defs = resource_defs
self.config = convert_config_input(config)
self.logger_defs = logger_defs
self.executor_def = executor_def
self.hooks = hooks
self.op_retry_policy = op_retry_policy
self.version_strategy = version_strategy
self.partitions_def = partitions_def
self.input_values = input_values
def __call__(self, fn: Callable[..., Any]) -> JobDefinition:
check.callable_param(fn, "fn")
if not self.name:
self.name = fn.__name__
from dagster._core.definitions.composition import do_composition
(
input_mappings,
output_mappings,
dependencies,
node_defs,
config_mapping,
positional_inputs,
node_input_source_assets,
) = do_composition(
decorator_name="@job",
graph_name=self.name,
fn=fn,
provided_input_defs=[],
provided_output_defs=[],
ignore_output_from_composition_fn=False,
config_mapping=None,
)
graph_def = GraphDefinition(
name=self.name,
dependencies=dependencies,
node_defs=node_defs,
description=self.description or format_docstring_for_description(fn),
input_mappings=input_mappings,
output_mappings=output_mappings,
config=config_mapping,
positional_inputs=positional_inputs,
tags=self.tags,
node_input_source_assets=node_input_source_assets,
)
job_def = graph_def.to_job(
description=self.description or format_docstring_for_description(fn),
resource_defs=self.resource_defs,
config=self.config,
tags=self.tags,
metadata=self.metadata,
logger_defs=self.logger_defs,
executor_def=self.executor_def,
hooks=self.hooks,
op_retry_policy=self.op_retry_policy,
version_strategy=self.version_strategy,
partitions_def=self.partitions_def,
input_values=self.input_values,
)
update_wrapper(job_def, fn)
return job_def
@overload
def job(compose_fn: Callable[..., Any]) -> JobDefinition:
...
@overload
def job(
*,
name: Optional[str] = ...,
description: Optional[str] = ...,
resource_defs: Optional[Mapping[str, object]] = ...,
config: Union[ConfigMapping, Mapping[str, Any], "RunConfig", "PartitionedConfig"] = ...,
tags: Optional[Mapping[str, Any]] = ...,
metadata: Optional[Mapping[str, RawMetadataValue]] = ...,
logger_defs: Optional[Mapping[str, LoggerDefinition]] = ...,
executor_def: Optional["ExecutorDefinition"] = ...,
hooks: Optional[AbstractSet[HookDefinition]] = ...,
op_retry_policy: Optional[RetryPolicy] = ...,
version_strategy: Optional[VersionStrategy] = ...,
partitions_def: Optional["PartitionsDefinition"] = ...,
input_values: Optional[Mapping[str, object]] = ...,
) -> _Job:
...
[docs]@deprecated_param(
param="version_strategy",
breaking_version="2.0",
additional_warn_text="Use asset versioning instead.",
)
def job(
compose_fn: Optional[Callable[..., Any]] = None,
*,
name: Optional[str] = None,
description: Optional[str] = None,
resource_defs: Optional[Mapping[str, object]] = None,
config: Optional[
Union[ConfigMapping, Mapping[str, Any], "RunConfig", "PartitionedConfig"]
] = None,
tags: Optional[Mapping[str, Any]] = None,
metadata: Optional[Mapping[str, RawMetadataValue]] = None,
logger_defs: Optional[Mapping[str, LoggerDefinition]] = None,
executor_def: Optional["ExecutorDefinition"] = None,
hooks: Optional[AbstractSet[HookDefinition]] = None,
op_retry_policy: Optional[RetryPolicy] = None,
version_strategy: Optional[VersionStrategy] = None,
partitions_def: Optional["PartitionsDefinition"] = None,
input_values: Optional[Mapping[str, object]] = None,
) -> Union[JobDefinition, _Job]:
"""Creates a job with the specified parameters from the decorated graph/op invocation function.
Using this decorator allows you to build an executable job by writing a function that invokes
ops (or graphs).
Args:
compose_fn (Callable[..., Any]:
The decorated function. The body should contain op or graph invocations. Unlike op
functions, does not accept a context argument.
name (Optional[str]):
The name for the Job. Defaults to the name of the this graph.
resource_defs (Optional[Mapping[str, object]]):
Resources that are required by this graph for execution.
If not defined, `io_manager` will default to filesystem.
config:
Describes how the job is parameterized at runtime.
If no value is provided, then the schema for the job's run config is a standard
format based on its ops and resources.
If a dictionary is provided, then it must conform to the standard config schema, and
it will be used as the job's run config for the job whenever the job is executed.
The values provided will be viewable and editable in the Dagster UI, so be
careful with secrets.
If a :py:class:`RunConfig` object is provided, then it will be used directly as the run config
for the job whenever the job is executed, similar to providing a dictionary.
If a :py:class:`ConfigMapping` object is provided, then the schema for the job's run config is
determined by the config mapping, and the ConfigMapping, which should return
configuration in the standard format to configure the job.
If a :py:class:`PartitionedConfig` object is provided, then it defines a discrete set of config
values that can parameterize the job, as well as a function for mapping those
values to the base config. The values provided will be viewable and editable in the
Dagster UI, so be careful with secrets.
tags (Optional[Dict[str, Any]]):
Arbitrary information that will be attached to the execution of the Job.
Values that are not strings will be json encoded and must meet the criteria that
`json.loads(json.dumps(value)) == value`. These tag values may be overwritten by tag
values provided at invocation time.
metadata (Optional[Dict[str, RawMetadataValue]]):
Arbitrary information that will be attached to the JobDefinition and be viewable in the Dagster UI.
Keys must be strings, and values must be python primitive types or one of the provided
MetadataValue types
logger_defs (Optional[Dict[str, LoggerDefinition]]):
A dictionary of string logger identifiers to their implementations.
executor_def (Optional[ExecutorDefinition]):
How this Job will be executed. Defaults to :py:class:`multiprocess_executor` .
op_retry_policy (Optional[RetryPolicy]): The default retry policy for all ops in this job.
Only used if retry policy is not defined on the op definition or op invocation.
version_strategy (Optional[VersionStrategy]):
Defines how each op (and optionally, resource) in the job can be versioned. If
provided, memoization will be enabled for this job.
partitions_def (Optional[PartitionsDefinition]): Defines a discrete set of partition keys
that can parameterize the job. If this argument is supplied, the config argument
can't also be supplied.
input_values (Optional[Mapping[str, Any]]):
A dictionary that maps python objects to the top-level inputs of a job.
Examples:
.. code-block:: python
@op
def return_one():
return 1
@op
def add_one(in1):
return in1 + 1
@job
def job1():
add_one(return_one())
"""
if compose_fn is not None:
check.invariant(description is None)
return _Job()(compose_fn)
from dagster._core.execution.build_resources import wrap_resources_for_execution
return _Job(
name=name,
description=description,
resource_defs=wrap_resources_for_execution(resource_defs),
config=config,
tags=tags,
metadata=metadata,
logger_defs=logger_defs,
executor_def=executor_def,
hooks=hooks,
op_retry_policy=op_retry_policy,
version_strategy=version_strategy,
partitions_def=partitions_def,
input_values=input_values,
)