tiled.adapters.table.TableAdapter

class tiled.adapters.table.TableAdapter(partitions: DataFrame | DataFrame, structure: TableStructure, *, metadata: Dict[str, str | int | float | bool | Dict[str, Dict[str, str | int | float | bool | Dict[str, JSON] | List[JSON]]] | List[Dict[str, str | int | float | bool | Dict[str, JSON] | List[JSON]]]] | None = None, specs: List[Spec] | None = None, access_policy: AccessPolicy | None = None)

Wrap a dataframe-like object in an interface that Tiled can serve.

Examples

>>> df = pandas.DataFrame({"a": [1, 2, 3], "b": [4, 5, 6]})
>>> DataFrameAdapter.from_pandas(df, npartitions=1)

__init__(partitions: DataFrame | DataFrame, structure: TableStructure, *, metadata: Dict[str, str | int | float | bool | Dict[str, Dict[str, str | int | float | bool | Dict[str, JSON] | List[JSON]]] | List[Dict[str, str | int | float | bool | Dict[str, JSON] | List[JSON]]]] | None = None, specs: List[Spec] | None = None, access_policy: AccessPolicy | None = None) → None

Parameters:

partitions

structure

metadata

specs

access_policy

Methods

__init__(partitions, structure, *[, ...])	Parameters:
from_dask_dataframe(ddf[, metadata, specs, ...])	Parameters:
from_pandas(*args[, metadata, specs, ...])	Parameters:
items()	Returns:
metadata()	Returns:
read([fields])	Parameters:
read_partition(partition[, fields])	Parameters:
structure()	Returns:

Attributes

structure_family