CommonLibrary

Common library functions for ApertureDB. This will not have a big class structure, but rather a collection of functions This is the place to put functions that are reused in codebase.

import_module_by_path

import_module_by_path(filepath: str) -> Any

This function imports a module given a path to a python file.

create_connector

create_connector(name: Optional[str] = None, key: Optional[str] = None, create_config_for_colab_secret=True) -> Connector

Create a connector to the database.

This function chooses a configuration in the folowing order: 1. The configuration named by the name parameter or key parameter 2. The configuration described in the APERTUREDB_KEY environment variable. 3. The configuration described in the APERTUREDB_KEY Google Colab secret. 4. The configuration described in the APERTUREDB_JSON environment variable. 5. The configuration described in the APERTUREDB_JSON Google Colab secret. 6. The configuration described in the APERTUREDB_JSON secret in a .env file. 7. The configuration named by the APERTUREDB_CONFIG environment variable. 8. The active configuration.

If there are both global and local configurations with the same name, the global configuration is preferred.

See adb config command-line tool for more information.

Parameters:

Name	Type	Description	Default
name	str	The name of the configuration to use. Default is None.	None
create_config_for_colab_secret	bool	Whether to create a configuration from the Google Colab secret. Default is True.	True

Returns:

Name	Type	Description
Connector	Connector	The connector to the database.

Note about Google Colab secret: This secret is available in the context of a notebook running on Google Colab. In particular, it is not available to the adb CLI tool running in a Colab notebook or any scripts run within a notebook. To resolve this issue, a configuration is automatically created and activated in this case. Use the create_config_for_colab_secret parameter to disable this behavior.

execute_query

execute_query(client: Connector, query: Commands, blobs: Blobs = [], success_statuses: list[int] = [0], response_handler: Optional[Callable] = None, commands_per_query: int = 1, blobs_per_query: int = 0, strict_response_validation: bool = False, cmd_index=None, error_handler: Optional[Callable] = None) -> Tuple[int, CommandResponses, Blobs]

Execute a batch of queries, doing useful logging around it. Calls the response handler if provided.

This should be used (without the parallel machinery) instead of Connector.query to keep the response handling consistent, better logging, etc.

Parameters:

Name	Type	Description	Default
client	Connector	The database connector.	required
query	Commands	List of commands to execute.	required
blobs	Blobs	List of blobs to send.	[]
success_statuses	list[int]	The list of success statuses. Defaults to [0].	[0]
response_handler	Callable	The response handler. Defaults to None.	None
commands_per_query	int	The number of commands per query. Defaults to 1.	1
blobs_per_query	int	The number of blobs per query. Defaults to 0.	0
strict_response_validation	bool	Whether to strictly validate the response. Defaults to False.	False
cmd_index	int	The index of the command or batch, passed to the response handler. Defaults to None.	None
error_handler	Callable	Callback invoked when the query returns an unexpected status or fails. Expected signature is error_handler(query, response, blobs). Defaults to None.	None

Returns:

Name	Type	Description
int	int	The result code. - 0 : if all commands succeeded - 1 : if there was -1 in the response - 2 : For any other code.
CommandResponses	CommandResponses	The response.
Blobs	Blobs	The blobs.

issue_deprecation_warning

issue_deprecation_warning(old_name, new_name)

Issue a deprecation warning for a function and class.