Configuration#

Setting the Runner#

Control the execution backend that Daft will run on by calling these functions once at the start of your application.

`daft.context.set_runner_py`	Set the runner for executing Daft dataframes to your local Python interpreter - this is the default behavior.
`daft.context.set_runner_ray`	Set the runner for executing Daft dataframes to a Ray cluster

Configure Daft in various ways during execution.

`daft.set_planning_config`	Globally sets various configuration parameters which control Daft plan construction behavior.
`daft.planning_config_ctx`	Context manager that wraps set_planning_config to reset the config to its original setting afternwards
`daft.set_execution_config`	Globally sets various configuration parameters which control various aspects of Daft execution.
`daft.execution_config_ctx`	Context manager that wraps set_execution_config to reset the config to its original setting afternwards

Configure behavior when Daft interacts with storage (e.g. credentials, retry policies and various other knobs to control performance/resource usage)

These configurations are most often used as inputs to Daft DataFrame reading I/O functions such as in Dataframe Creation.

`daft.io.IOConfig`	Create configurations to be used when accessing storage
`daft.io.S3Config`	Create configurations to be used when accessing an S3-compatible system
`daft.io.S3Credentials`	Create credentials to be used when accessing an S3-compatible system
`daft.io.GCSConfig`	Create configurations to be used when accessing Google Cloud Storage.
`daft.io.AzureConfig`	Create configurations to be used when accessing Azure Blob Storage.