test_convert.py

from __future__ import annotations

import pytest

import polars as pl
from polars.exceptions import ComputeError, NoDataError


def test_from_records_schema_inference() -> None:
    data = [[1, 2.1, 3], [4, 5, 6.4]]

    with pytest.raises(TypeError, match="unexpected value"):
        pl.from_records(data)

    result = pl.from_records(data, strict=False)
    assert result.to_dict(as_series=False) == {
        "column_0": [1.0, 2.1, 3.0],
        "column_1": [4.0, 5.0, 6.4],
    }


def test_from_dicts_schema_inference() -> None:
    data = [{"a": 1, "b": 2}, {"a": 3.1, "b": 4.5}]
    result = pl.from_dicts(data)  # type: ignore[arg-type]
    assert result.to_dict(as_series=False) == {
        "a": [1.0, 3.1],
        "b": [2.0, 4.5],
    }


def test_from_dicts_nested_nulls() -> None:
    result = pl.from_dicts([{"a": [None, None]}, {"a": [1, 2]}])
    assert result.to_dict(as_series=False) == {"a": [[None, None], [1, 2]]}


def test_from_dicts_empty() -> None:
    with pytest.raises(NoDataError, match="no data, cannot infer schema"):
        pl.from_dicts([])


def test_from_dicts_all_cols_6716() -> None:
    dicts = [{"a": None} for _ in range(20)] + [{"a": "crash"}]

    with pytest.raises(
        ComputeError, match="make sure that all rows have the same schema"
    ):
        pl.from_dicts(dicts, infer_schema_length=20)
    assert pl.from_dicts(dicts, infer_schema_length=None).dtypes == [pl.String]


def test_dict_float_string_roundtrip_18882() -> None:
    assert pl.from_dicts([{"A": "0.1"}]).to_dicts() == [{"A": "0.1"}]