polars.testing.parametric.column#

class polars.testing.parametric.column(
name: str | None = None,
dtype: PolarsDataType | None = None,
strategy: SearchStrategy[Any] | None = None,
allow_null: bool | None = None,
unique: bool = False,
null_probability: float | None = None,
)[source]#

Define a column for use with the dataframes strategy.

Parameters:
namestr

string column name.

dtypePolarsDataType

a polars dtype.

strategystrategy, optional

supports overriding the default strategy for the given dtype.

allow_nullbool, optional

Allow nulls as possible values and allow the Null data type by default.

uniquebool, optional

flag indicating that all values generated for the column should be unique.

null_probabilityfloat, optional

percentage chance (expressed between 0.0 => 1.0) that a generated value is None. this is applied independently of any None values generated by the underlying strategy.

Deprecated since version 0.20.26: Use allow_null instead.

Examples

>>> from polars.testing.parametric import column
>>> dfs = dataframes(
...     [
...         column("x", dtype=pl.Int32, allow_null=True),
...         column("y", dtype=pl.Float64),
...     ],
...     size=2,
... )
>>> dfs.example()
shape: (2, 2)
┌───────────┬────────────┐
│ x         ┆ y          │
│ ---       ┆ ---        │
│ i32       ┆ f64        │
╞═══════════╪════════════╡
│ null      ┆ 1.1755e-38 │
│ 575050513 ┆ inf        │
└───────────┴────────────┘
__init__(
name: str | None = None,
dtype: PolarsDataType | None = None,
strategy: SearchStrategy[Any] | None = None,
allow_null: bool | None = None,
unique: bool = False,
null_probability: float | None = None,
) None[source]#

Methods

__init__([name, dtype, strategy, ...])

Attributes

allow_null

dtype

name

null_probability

strategy

unique