taipy.core.data.CSVDataNode

Bases: DataNode, _AbstractFileDataNode, _AbstractTabularDataNode

Data Node stored as a CSV file.

Attributes:

Name	Type	Description
config_id	str	Identifier of the data node configuration. This string must be a valid Python identifier.
scope	Scope	The scope of this data node.
id	str	The unique identifier of this data node.
owner_id	str	The identifier of the owner (sequence_id, scenario_id, cycle_id) or None.
parent_ids	Optional[Set[str]]	The identifiers of the parent tasks or None.
last_edit_date	datetime	The date and time of the last modification.
edits	List[Edit]	The ordered list of edits for that job.
version	str	The string indicates the application version of the data node to instantiate. If not provided, the current version is used.
validity_period	Optional[timedelta]	The duration implemented as a timedelta since the last edit date for which the data node can be considered up-to-date. Once the validity period has passed, the data node is considered stale and relevant tasks will run even if they are skippable (see the Task management page for more details). If validity_period is set to None, the data node is always up-to-date.
edit_in_progress	bool	True if a task computing the data node has been submitted and not completed yet. False otherwise.
editor_id	Optional[str]	The identifier of the user who is currently editing the data node.
editor_expiration_date	Optional[datetime]	The expiration date of the editor lock.
path	str	The path to the CSV file.
properties	dict[str, Any]	A dictionary of additional properties. The properties must have a "default_path" or "path" entry with the path of the CSV file: "default_path" (str): The default path of the CSV file. "encoding" (str): The encoding of the CSV file. The default value is utf-8. "default_data": The default data of the data nodes instantiated from this csv data node. "has_header" (bool): If True, indicates that the CSV file has a header. "exposed_type": The exposed type of the data read from CSV file. The default value is pandas.

write_with_column_names(data, columns=None, job_id=None)

Write a selection of columns.

Parameters:

Name	Type	Description	Default
data	Any	The data to write.	required
columns	Optional[List[str]]	The list of column names to write.	None
job_id	JobId	An optional identifier of the writer.	None