dlt.destinations.impl.bigquery.factory

bigquery Objects

class bigquery(Destination[BigQueryClientConfiguration, "BigQueryClient"])

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create_ibis_backend

def create_ibis_backend(
    client: "BigQueryClient",
    read_only: bool = False,
    schemas: "Sequence[Schema]" = ()) -> "BaseBackend"

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Create an ibis bigquery backend for the client's dataset.

__init__

def __init__(credentials: GcpServiceAccountCredentials = None,
             location: str = None,
             has_case_sensitive_identifiers: bool = None,
             enable_atomic_replace: bool = None,
             destination_name: str = None,
             environment: str = None,
             **kwargs: Any) -> None

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Configure the BigQuery destination to use in a pipeline.

All arguments provided here supersede other configuration sources such as environment variables and dlt config files.

Arguments:

• credentials GcpServiceAccountCredentials, optional - Credentials to connect to the BigQuery database. Can be an instance of GcpServiceAccountCredentials or a dict or string with service accounts credentials as used in the Google Cloud
• location str, optional - A location where the datasets will be created, eg. "EU". The default is "US"
• has_case_sensitive_identifiers bool, optional - Is the dataset case-sensitive, defaults to True
• enable_atomic_replace bool, optional - Replace truncate-and-insert tables with a single metadata-preserving WRITE_TRUNCATE_DATA load job. Requires a GCS staging destination.
• destination_name str, optional - Name of the destination, can be used in config section to differentiate between multiple of the same type
• environment str, optional - Environment of the destination
• **kwargs Any - Additional arguments passed to the destination config