patito.Model.examples

classmethod Model.examples(data=None, columns=None)

Generate polars dataframe with dummy data for all unspecified columns.

This constructor accepts the same data format as polars.DataFrame.

Parameters:

• data (Union[dict, Iterable, None]) – Data to populate the dummy dataframe with. If given as an iterable of values, then column names must also be provided. If not provided at all, a dataframe with a single row populated with dummy data is provided.

• columns (Optional[Iterable[str]]) – Ignored if data is provided as a dictionary. If data is provided as an iterable, then columns will be used as the column names in the resulting dataframe. Defaults to None.

Return type:

DataFrame

Returns:

A polars dataframe where all unspecified columns have been filled with dummy data which should pass model validation.

Raises:

TypeError – If one or more of the model fields are not mappable to polars column dtype equivalents.

Example

>>> from typing import Literal
>>> import patito as pt

>>> class Product(pt.Model):
...     product_id: int = pt.Field(unique=True)
...     name: str
...     temperature_zone: Literal["dry", "cold", "frozen"]
...

>>> Product.examples()
shape: (1, 3)
┌──────────────┬──────────────────┬────────────┐
│ name         ┆ temperature_zone ┆ product_id │
│ ---          ┆ ---              ┆ ---        │
│ str          ┆ cat              ┆ i64        │
╞══════════════╪══════════════════╪════════════╡
│ dummy_string ┆ dry              ┆ 0          │
└──────────────┴──────────────────┴────────────┘

>>> Product.examples({"name": ["product A", "product B"]})
shape: (2, 3)
┌───────────┬──────────────────┬────────────┐
│ name      ┆ temperature_zone ┆ product_id │
│ ---       ┆ ---              ┆ ---        │
│ str       ┆ cat              ┆ i64        │
╞═══════════╪══════════════════╪════════════╡
│ product A ┆ dry              ┆ 0          │
│ product B ┆ dry              ┆ 1          │
└───────────┴──────────────────┴────────────┘