Source code for bigframes._config.sampling_options

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"""Options for downsampling."""

from __future__ import annotations

import dataclasses
from typing import Literal, Optional


[docs] @dataclasses.dataclass class SamplingOptions: """ Encapsulates the configuration for data sampling. """ max_download_size: Optional[int] = 500 """ Download size threshold in MB. Default 500. If value set to None, the download size won't be checked. """ enable_downsampling: bool = False """ Whether to enable downsampling. Default False. If max_download_size is exceeded when downloading data (e.g., to_pandas()), the data will be downsampled if enable_downsampling is True, otherwise, an error will be raised. """ sampling_method: Literal["head", "uniform"] = "uniform" """ Downsampling algorithms to be chosen from. Default "uniform". The choices are: "head": This algorithm returns a portion of the data from the beginning. It is fast and requires minimal computations to perform the downsampling.; "uniform": This algorithm returns uniform random samples of the data. """ random_state: Optional[int] = None """ The seed for the uniform downsampling algorithm. Default None. If provided, the uniform method may take longer to execute and require more computation. """
[docs] def with_max_download_size(self, max_rows: Optional[int]) -> SamplingOptions: """Configures the maximum download size for data sampling in MB Args: max_rows (None or int): An int value for the maximum row size. Returns: bigframes._config.sampling_options.SamplingOptions: The configuration for data sampling. """ return SamplingOptions( max_rows, self.enable_downsampling, self.sampling_method, self.random_state )
[docs] def with_method(self, method: Literal["head", "uniform"]) -> SamplingOptions: """Configures the downsampling algorithms to be chosen from Args: method (None or Literal): A literal string value of either head or uniform data sampling method. Returns: bigframes._config.sampling_options.SamplingOptions: The configuration for data sampling. """ return SamplingOptions(self.max_download_size, True, method, self.random_state)
[docs] def with_random_state(self, state: Optional[int]) -> SamplingOptions: """Configures the seed for the uniform downsampling algorithm Args: state (None or int): An int value for the data sampling random state Returns: bigframes._config.sampling_options.SamplingOptions: The configuration for data sampling. """ return SamplingOptions( self.max_download_size, self.enable_downsampling, self.sampling_method, state, )
[docs] def with_disabled(self) -> SamplingOptions: """Configures whether to disable downsampling Returns: bigframes._config.sampling_options.SamplingOptions: The configuration for data sampling. """ return SamplingOptions( self.max_download_size, False, self.sampling_method, self.random_state )