JobModel

This module contains the JobModel class, which is used to validate the job description

class DIRAC.WorkloadManagementSystem.Utilities.JobModel.BaseJobDescriptionModel(*, arguments: str = None, bannedSites: set[str] = None, cpuTime: int = 86400, executable: str, executionEnvironment: dict = None, gridCE: str = None, inputSandbox: set[str] = None, inputData: set[str] = None, inputDataPolicy: str = None, jobConfigArgs: str = None, jobGroup: str = None, jobType: str = 'User', jobName: str = 'Name', logLevel: str = 'INFO', maxNumberOfProcessors: int = None, minNumberOfProcessors: int = 1, outputData: set[str] = None, outputPath: str = None, outputSandbox: set[str] = None, outputSE: str = None, platform: str = None, priority: int = 1, sites: set[str] = None, stderr: str = 'std.err', stdout: str = 'std.out', tags: set[str] = None, extraFields: dict[str, Any] = None)

Bases: BaseModel

Base model for the job description (not parametric)

Config: alias of BaseConfig

__init__(**data: Any) → None

Create a new model by parsing and validating input data from keyword arguments.

Raises ValidationError if the input data cannot be parsed to form a valid model.

classmethod addLFNPrefixIfStringStartsWithASlash(v: set[str])

classmethod addTagsDependingOnNumberOfProcessors(values)

arguments: str

bannedSites: set[str]

classmethod checkCPUTimeBounds(v)

classmethod checkExecutableIsNotAnEmptyString(v: str)

classmethod checkInputDataDoesntContainDoubleSlashes(v)

classmethod checkJobTypeIsAllowed(v: str)

classmethod checkLFNSandboxesAreWellFormated(v: set[str])

classmethod checkLogLevelIsValid(v: str)

classmethod checkMaxNumberOfProcessorsBounds(v)

classmethod checkMinNumberOfProcessorsBounds(v)

classmethod checkNumberOfInputDataFiles(values)

classmethod checkPlatform(v: str)

classmethod checkPriorityBounds(v)

classmethod checkSites(v: set[str])

classmethod checkThatMaxNumberOfProcessorsIsGreaterThanMinNumberOfProcessors(values)

classmethod checkThatSitesAndBannedSitesAreNotMutuallyExclusive(values)

classmethod construct(_fields_set: SetStr | None = None, **values: Any) → Model: Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values

Duplicate a model, optionally choose which fields to include, exclude and change.

Parameters:

include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model

Returns:

new model instance

cpuTime: int

dict(*, include: AbstractSetIntStr | MappingIntStrAny | None = None, exclude: AbstractSetIntStr | MappingIntStrAny | None = None, by_alias: bool = False, skip_defaults: bool | None = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) → DictStrAny: Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

executable: str

executionEnvironment: dict

extraFields: dict[str, Any]

classmethod from_orm(obj: Any) → Model

gridCE: str

inputData: set[str]

inputDataPolicy: str

inputSandbox: set[str]

jobConfigArgs: str

jobGroup: str

jobName: str

jobType: str

json(*, include: AbstractSetIntStr | MappingIntStrAny | None = None, exclude: AbstractSetIntStr | MappingIntStrAny | None = None, by_alias: bool = False, skip_defaults: bool | None = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Callable[[Any], Any] | None = None, models_as_dict: bool = True, **dumps_kwargs: Any) → unicode

Generate a JSON representation of the model, include and exclude arguments as per dict().

encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().

logLevel: str

maxNumberOfProcessors: int

minNumberOfProcessors: int

outputData: set[str]

outputPath: str

outputSE: str

outputSandbox: set[str]

classmethod parse_file(path: str | Path, *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model

classmethod parse_obj(obj: Any) → Model

classmethod parse_raw(b: str | bytes, *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model

platform: str

priority: int

classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') → DictStrAny

classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) → unicode

sites: set[str]

stderr: str

stdout: str

tags: set[str]

classmethod update_forward_refs(**localns: Any) → None: Try to update ForwardRefs on fields based on this Model, globalns and localns.

classmethod validate(value: Any) → Model

class DIRAC.WorkloadManagementSystem.Utilities.JobModel.JobDescriptionModel(*, arguments: str = None, bannedSites: set[str] = None, cpuTime: int = 86400, executable: str, executionEnvironment: dict = None, gridCE: str = None, inputSandbox: set[str] = None, inputData: set[str] = None, inputDataPolicy: str = None, jobConfigArgs: str = None, jobGroup: str = None, jobType: str = 'User', jobName: str = 'Name', logLevel: str = 'INFO', maxNumberOfProcessors: int = None, minNumberOfProcessors: int = 1, outputData: set[str] = None, outputPath: str = None, outputSandbox: set[str] = None, outputSE: str = None, platform: str = None, priority: int = 1, sites: set[str] = None, stderr: str = 'std.err', stdout: str = 'std.out', tags: set[str] = None, extraFields: dict[str, Any] = None, owner: str, ownerGroup: str, vo: str)

Bases: BaseJobDescriptionModel

Model for the job description (non parametric job with user credentials, i.e server side)

Config: alias of BaseConfig