metadata_db_loader

metadata_db_loader ¤

DatapointDB ¤

DatapointDB(
    device_names: list[str],
    db_user: str,
    db_pass: str,
    db_host: str,
    output_path: str = "data",
    required_uuid_list: list[str] | None = None,
    filter_enabled: bool = True,
    *,
    db_port: int = 5432,
    db_name: str = "config_repository",
    db_driver: str = POSTGRES_DRIVER
)

Load datapoint metadata per device from the PostgreSQL config repository.

Needs the postgres extra (pip install ts-shape[postgres]). repr(db) masks the password.

Initialize the DatapointDB class and load metadata for each device.

Parameters:

Name	Type	Description	Default
`device_names`	`list[str]`	List of device names to retrieve metadata for.	required
`db_user`	`str`	Database user.	required
`db_pass`	`str`	Database password.	required
`db_host`	`str`	Database host.	required
`output_path`	`str`	Directory to save JSON files.	`'data'`
`required_uuid_list`	`list[str] \| None`	List of UUIDs to filter the metadata (optional).	`None`
`filter_enabled`	`bool`	Whether to filter metadata by "enabled == True" and "archived == False" (default is True).	`True`
`db_port`	`int`	Database port. Default 5432.	`5432`
`db_name`	`str`	Database name. Default `"config_repository"`.	`'config_repository'`
`db_driver`	`str`	DB-API driver. Default `"psycopg2"` (the `postgres` extra).	`POSTGRES_DRIVER`

Raises:

Type	Description
`ImportError`	SQLAlchemy or the database driver is not installed.

url `property` ¤

url: URL

The connection URL; str(url) masks the password.

get_all_uuids ¤

get_all_uuids() -> dict[str, list[str]]

Return a dictionary of UUIDs for each device.

get_all_metadata ¤

get_all_metadata() -> dict[str, list[dict[str, str]]]

Return a dictionary of metadata for each device.

display_dataframe ¤

display_dataframe(
    device_name: str | None = None, aggregate: bool = False
) -> None

Display metadata as a DataFrame for a specific device or all devices.