mlrun.package.packagers.python_standard_library_packagers.BoolPackager

class mlrun.package.packagers.python_standard_library_packagers.BoolPackager

Bases: DefaultPackager

builtins.bool packager.

Packager Summary

Packing Type: builtins.bool

Packing Sub-Classes: False

Priority: Default priority (5)

Default Artifact Types:

• Packing: result

• Unpacking: object

Artifact Types:

• object - Pack a python object, pickling it into a pkl file and store it in an artifact.

  • pickle_module_name - The pickle module name to use for serializing the object.

• result - Pack an object as a result.

Attributes

DEFAULT_PACKING_ARTIFACT_TYPE	The default artifact type to pack as.
DEFAULT_UNPACKING_ARTIFACT_TYPE	The default artifact type to unpack from.
PACK_SUBCLASSES	A flag for indicating whether to also pack all subclasses of the PACKABLE_OBJECT_TYPE.
PRIORITY	The priority of this packager in the packagers collection of the manager (lower is better).
future_clearing_path_list	Get the packager's future clearing path list.
priority	Get the packager's priority.

DEFAULT_PACKING_ARTIFACT_TYPE = 'result'

The default artifact type to pack as.

DEFAULT_UNPACKING_ARTIFACT_TYPE = 'object'

The default artifact type to unpack from.

PACK_SUBCLASSES = False

A flag for indicating whether to also pack all subclasses of the PACKABLE_OBJECT_TYPE.

PRIORITY: int = Ellipsis

The priority of this packager in the packagers collection of the manager (lower is better).

future_clearing_path_list

Get the packager's future clearing path list.

Returns:

The clearing path list.

priority

Get the packager's priority.

Returns:

The packager's priority.

Methods

__init__()
add_future_clearing_path(path)	Mark a path to be cleared by this packager's manager after logging the packaged artifacts.
get_data_item_local_path(data_item[, ...])	Get the local path to the item handled by the data item provided.
get_default_packing_artifact_type(obj)	Get the default artifact type for packing an object of this packager.
get_default_unpacking_artifact_type(data_item)	Get the default artifact type used for unpacking a data item holding an object of this packager.
get_supported_artifact_types()	Get all the supported artifact types on this packager.
is_packable(obj[, artifact_type, configurations])	Check if this packager can pack an object of the provided type as the provided artifact type.
is_unpackable(data_item, type_hint[, ...])	Check if this packager can unpack an input according to the user-given type hint and the provided artifact type.
pack(obj[, key, artifact_type, configurations])	Pack an object as the given artifact type using the provided configurations.
pack_object(obj, key[, pickle_module_name])	Pack a python object, pickling it into a pkl file and store it in an artifact.
pack_result(obj, key)	Pack an object as a result.
unpack(data_item[, artifact_type, instructions])	Unpack the data item's artifact by the provided type using the given instructions.
unpack_object(data_item[, ...])	Unpack the data item's object, unpickle it using the instructions, and return.

__init__()

add_future_clearing_path(path: str | Path)

Mark a path to be cleared by this packager's manager after logging the packaged artifacts.

Parameters:

path -- The path to clear post logging the artifacts.

get_data_item_local_path(data_item: DataItem, add_to_future_clearing_path: bool | None = None) → str

Get the local path to the item handled by the data item provided. The local path can be the same as the data item in case the data item points to a local path, or will be downloaded to a temporary directory and return this newly created temporary local path.

Parameters:

• data_item -- The data item to get its item local path.

• add_to_future_clearing_path -- Whether to add the local path to the future clearing paths list. If None, it will add the path to the list only if the data item is not of kind 'file', meaning it represents a local file and hence we don't want to delete it post running automatically. We wish to delete it only if the local path is temporary (and that will be in case kind is not 'file', so it is being downloaded to a temporary directory).

Returns:

The data item local path.

get_default_packing_artifact_type(obj: Any) → str

Get the default artifact type for packing an object of this packager.

Parameters:

obj -- The about-to-be packed object.

Returns:

The default artifact type.

get_default_unpacking_artifact_type(data_item: DataItem) → str

Get the default artifact type used for unpacking a data item holding an object of this packager. The method is used when a data item is sent for unpacking without it being a package, but is a simple url or an old / manually logged artifact.

Parameters:

data_item -- The about-to-be unpacked data item.

Returns:

The default artifact type.

get_supported_artifact_types() → list[str]

Get all the supported artifact types on this packager.

Returns:

A list of all the supported artifact types.

is_packable(obj: Any, artifact_type: str | None = None, configurations: dict | None = None) → bool

Check if this packager can pack an object of the provided type as the provided artifact type.

The method is implemented to validate the object's type and artifact type by checking if the given object type matches the variable PACKABLE_OBJECT_TYPE with respect to the PACK_SUBCLASSES class variable. If it does, it checks if the given artifact type is in the list returned from get_supported_artifact_types.

Parameters:

• obj -- The object to pack.

• artifact_type -- The artifact type to log the object as.

• configurations -- The log hint configurations passed by the user.

Returns:

True if packable and False otherwise.

is_unpackable(data_item: DataItem, type_hint: type, artifact_type: str | None = None) → bool

Check if this packager can unpack an input according to the user-given type hint and the provided artifact type.

The default implementation tries to match the packable object type of this packager to the given type hint. If it matches, it looks for the artifact type in the list returned from get_supported_artifact_types.

Parameters:

• data_item -- The input data item to check if unpackable.

• type_hint -- The type hint of the input to unpack (the object type to be unpacked).

• artifact_type -- The artifact type to unpack the object as.

Returns:

True if unpackable and False otherwise.

pack(obj: Any, key: str | None = None, artifact_type: str | None = None, configurations: dict | None = None) → tuple[mlrun.artifacts.base.Artifact, dict] | dict

Pack an object as the given artifact type using the provided configurations.

Parameters:

• obj -- The object to pack.

• key -- The key of the artifact.

• artifact_type -- Artifact type to log to MLRun. If passing None, the default artifact type is used.

• configurations -- Log hints configurations to pass to the packing method.

Returns:

If the packed object is an artifact, a tuple of the packed artifact and unpacking instructions dictionary. If the packed object is a result, a dictionary containing the result key and value.

pack_object(obj: Any, key: str, pickle_module_name: str = 'cloudpickle') → tuple[mlrun.artifacts.base.Artifact, dict]

Pack a python object, pickling it into a pkl file and store it in an artifact.

Parameters:

• obj -- The object to pack and log.

• key -- The artifact's key.

• pickle_module_name -- The pickle module name to use for serializing the object.

Returns:

The artifacts and its pickling instructions.

pack_result(obj: Any, key: str) → dict

Pack an object as a result.

Parameters:

• obj -- The object to pack and log.

• key -- The result's key.

Returns:

The result dictionary.

unpack(data_item: DataItem, artifact_type: str | None = None, instructions: dict | None = None) → Any

Unpack the data item's artifact by the provided type using the given instructions.

Parameters:

• data_item -- The data input to unpack.

• artifact_type -- The artifact type to unpack the data item as. If passing None, the default artifact type is used.

• instructions -- Additional instructions noted in the package to pass to the unpacking method.

Returns:

The unpacked data item's object.

Raises:

MLRunPackageUnpackingError -- In case the packager could not unpack the data item.

unpack_object(data_item: DataItem, pickle_module_name: str = 'cloudpickle', object_module_name: str | None = None, python_version: str | None = None, pickle_module_version: str | None = None, object_module_version: str | None = None) → Any

Unpack the data item's object, unpickle it using the instructions, and return.

Warnings of mismatching python and module versions between the original pickling interpreter and this one may be raised.

Parameters:

• data_item -- The data item holding the pkl file.

• pickle_module_name -- Module to use for unpickling the object.

• object_module_name -- The original object's module. Used to verify that the current interpreter object module version matches the pickled object version before unpickling the object.

• python_version -- The python version in which the original object was pickled. Used to verify that the current interpreter python version matches the pickled object version before unpickling the object.

• pickle_module_version -- The pickle module version. Used to verify that the current interpreter module version matches the one that pickled the object before unpickling it.

• object_module_version -- The original object's module version to match to the interpreter's module version.

Returns:

The un-pickled python object.