Module `fusion_platform.models.process_service_execution_log`

Process service execution log model class file.

author: Matthew Casey

Classes

class ProcessServiceExecutionLog (session, schema=None)

Expand source code

class ProcessServiceExecutionLog(Model):
    """
    Process service execution log model class providing attributes and methods to manipulate process execution item details.
    """

    # Override the schema.
    _SCHEMA = ProcessServiceExecutionLogSchema()

Process service execution log model class providing attributes and methods to manipulate process execution item details.

Initialises the object.

Args
-----=
session: The linked session object for interfacing with the Fusion Platform^®.
schema: The optional schema to use instead of the schema defined by the class.

Ancestors

Model
fusion_platform.base.Base

Instance variables

prop attributes: Inherited from: Model.attributes

Returns -----= The model attributes as a dictionary.

Methods

def delete(self): Inherited from: Model.delete

Attempts to delete the model object. This assumes the model is deleted using a DELETE RESTful request …
def get(self, **kwargs): Inherited from: Model.get

Gets the model object by loading it from the Fusion Platform^®. Uses the model's current id and base model id for the get unless …
def to_csv(self, exclude=None): Inherited from: Model.to_csv

Converts the model attributes into a CSV string …
def update(self, **kwargs): Inherited from: Model.update

Attempts to update the model object with the given values. For models which have not been persisted, the relevant fields are updated without …

class ProcessServiceExecutionLogSchema (*, only: types.StrSequenceOrSet | None = None, exclude: types.StrSequenceOrSet = (), many: bool | None = None, load_only: types.StrSequenceOrSet = (), dump_only: types.StrSequenceOrSet = (), partial: bool | types.StrSequenceOrSet | None = None, unknown: types.UnknownOption | None = None)

Expand source code

class ProcessServiceExecutionLogSchema(Schema):
    """
    Schema class for process service execution log model.

    Each process service execution log model has the following fields (and nested fields):

    .. include::process_service_execution_log.md
    """
    id = fields.UUID(required=True, metadata={'read_only': True})  # Changed to prevent this being updated.

    created_at = fields.DateTime(required=True, metadata={'read_only': True})  # Changed to prevent this being updated.
    updated_at = fields.DateTime(required=True, metadata={'read_only': True})  # Changed to prevent this being updated.

    process_service_execution_id = fields.UUID(required=True, metadata={'read_only': True})  # Changed to prevent this being updated.
    logged_at = fields.DateTime(required=True, metadata={'read_only': True})  # Changed to prevent this being updated.
    message = fields.String(allow_none=True, metadata={'read_only': True})  # Changed to prevent this being updated.

    class Meta:
        """
        When loading an object, make sure we exclude any unknown fields, rather than raising an exception, and put fields in their definition order.
        """
        unknown = EXCLUDE

Schema class for process service execution log model.

Each process service execution log model has the following fields (and nested fields):

id: The unique identifier for the record.
created_at: When was the record created?
updated_at: When was the record last updated?
process_service_execution_id: The specific execution of the process and service.
logged_at: When was the message logged?
message: The log message.

Ancestors

marshmallow.schema.Schema

Class variables

var OPTIONS_CLASS : type: Defines defaults for marshmallow.Schema.Meta.
var TYPE_MAPPING : dict[type, type[Field]]: The type of the None singleton.
var dict_class : type[dict]: dict() -> new empty dictionary dict(mapping) -> new dictionary initialized from a mapping object's (key, value) pairs dict(iterable) -> new dictionary initialized as if via: d = {} for k, v in iterable: d[k] = v dict(**kwargs) -> new dictionary initialized with the name=value pairs in the keyword argument list. For example: dict(one=1, two=2)
var error_messages : dict[str, str]: The type of the None singleton.