paguro.LazyDataset[VFM: paguro.models.vfm.vfmodel.VFrameModel]].sink_csv(path: str | Path | IO[bytes] | IO[str] | PartitioningScheme, *, include_bom: bool = False, include_header: bool = True, separator: str = ', ', line_terminator: str = '\n', quote_char: str = '"', batch_size: int = 1024, datetime_format: str | None = None, date_format: str | None = None, time_format: str | None = None, float_scientific: bool | None = None, float_precision: int | None = None, decimal_comma: bool = False, null_value: str | None = None, quote_style: CsvQuoteStyle | None = None, maintain_order: bool = True, storage_options: dict[str, Any] | None = None, credential_provider: CredentialProviderFunction | Literal['auto'] | None = 'auto', retries: int = 2, sync_on_close: SyncOnCloseMethod | None = None, mkdir: bool = False, lazy: bool = False, engine: EngineType = 'auto', optimizations: QueryOptFlags = <polars.lazyframe.opt_flags.QueryOptFlags object>) → polars.LazyFrame | None

See sink_csv