To

cognite.neat._session._to.ToAPI

API used to write the contents of a NeatSession to a specified destination. For instance writing information rules or DMS rules to a NEAT rules Excel spreadsheet, or writing a verified data model to CDF.

excel(io, include_reference=True, include_properties='all', add_empty_rows=False)

Export the verified data model to Excel.

Parameters:

Name	Type	Description	Default
io	Any	The file path or file-like object to write the Excel file to.	required
include_reference	bool | DataModelIdentifier	If True, the reference data model will be included. Defaults to True. Note that this only applies if you have created the data model using the create.enterprise_model(...), create.solution_model(), or create.data_product_model() methods. You can also provide a DataModelIdentifier directly, which will be read from CDF	True
include_properties	Literal['same-space', 'all']	The properties to include in the Excel file. Defaults to "all". - "same-space": Only properties that are in the same space as the data model will be included.	'all'
add_empty_rows	bool	If True, empty rows will be added between each component. Defaults to False.	False

Example

Export information model to excel rules sheet

information_rules_file_name = "information_rules.xlsx"
neat.to.excel(information_rules_file_name)

Example

Read CogniteCore model, convert it to an enterprise model, and export it to an excel file

client = CogniteClient()
neat = NeatSession(client)

neat.read.cdf(("cdf_cdm", "CogniteCore", "v1"))
neat.create.enterprise_model(
    data_model_id=("sp_doctrino_space", "ExtensionCore", "v1"),
    org_name="MyOrg",
)
dms_rules_file_name = "dms_rules.xlsx"
neat.to.excel(dms_rules_file_name, include_reference=True)

Example

Read the data model ("my_space", "ISA95Model", "v5") and export it to an excel file with the CogniteCore model in the reference sheets. ```python client = CogniteClient() neat = NeatSession(client)

neat.read.cdf(("my_space", "ISA95Model", "v5")) dms_rules_file_name = "dms_rules.xlsx" neat.to.excel(dms_rules_file_name, include_reference=("cdf_cdm", "CogniteCore", "v1"))

session(io)

Export the current session to a file.

Parameters:

Name	Type	Description	Default
io	Any	The file path to file-like object to write the session to.	required

Example

Export the session to a file

session_file_name = "neat_session.zip"
neat.to.session(session_file_name)

yaml(io=None, format='neat', skip_system_spaces=True)

Export the verified data model to YAML.

Parameters:

Name	Type	Description	Default
io	Any | None	The file path or file-like object to write the YAML file to. Defaults to None.	None
format	Literal['neat', 'toolkit']	The format of the YAML file. Defaults to "neat".	'neat'
skip_system_spaces	bool	If True, system spaces will be skipped. Defaults to True.	True

YAML formats

• "neat": This is the format Neat uses to store the data model.
• "toolkit": This is the format used by Cognite Toolkit, that matches the CDF API.

Returns:

Type	Description
str | None	str | None: If io is None, the YAML string will be returned. Otherwise, None will be returned.

Example

Export to yaml file in the case of "neat" format

your_yaml_file_name = "neat_rules.yaml"
neat.to.yaml(your_yaml_file_name, format="neat")

Example

Export yaml files as a zip folder in the case of "toolkit" format

your_zip_folder_name = "toolkit_data_model_files.zip"
neat.to.yaml(your_zip_folder_name, format="toolkit")

Example

Export yaml files to a folder in the case of "toolkit" format

your_folder_name = "my_project/data_model_files"
neat.to.yaml(your_folder_name, format="toolkit")

cognite.neat._session._to.CDFToAPI

Write a verified Data Model and Instances to CDF.

instances(space=None, space_property=None)

Export the verified DMS instances to CDF.

Parameters:

Name	Type	Description	Default
space	str | None	Name of instance space to use. Default is to suffix the schema space with '_instances'. Note this space is required to be different from the space with the data model.	None
space_property	str | None	This is an alternative to the 'space' argument. If provided, the space will set to the value of the property with the given name for each instance. If the property is not found, the 'space' argument will be used. Defaults to None.	None

Returns:

Name	Type	Description
UploadResultList	UploadResultList	The result of the upload.

Example

Export instances to CDF

neat.to.cdf.instances()

Export instances to CDF using the dataSetId property as the space

neat.to.cdf.instances(space_property="dataSetId")

data_model(existing='update', dry_run=False, drop_data=False, components=None)

Export the verified DMS data model to CDF.

Parameters:

Name	Type	Description	Default
existing	Literal['fail', 'skip', 'update', 'force', 'recreate']	What to do if the component already exists. Defaults to "update". See the note below for more information about the options.	'update'
dry_run	bool	If True, no changes will be made to CDF. Defaults to False.	False
drop_data	bool	If existing is 'force' or 'recreate' and the operation will lead to data loss, the component will be skipped unless drop_data is True. Defaults to False. Note this only applies to spaces and containers if they contain data.	False
components	Component | Collection[Component] | None	The components to export. If None, all components will be exported. Defaults to None.	None

Data Model creation modes

• "fail": If any component already exists, the export will fail.
• "skip": If any component already exists, it will be skipped.
• "update": If any component already exists, it will be updated.
• "force": If any component already exists, and the update fails, it will be deleted and recreated.
• "recreate": All components will be deleted and recreated. The exception is spaces, which will be updated.