polars.testing.assert_series_equal#

polars.testing.assert_series_equal( left: Series, right: Series, *, check_dtype: bool = True, check_names: bool = True, check_exact: bool = False, rtol: float = 1e-05, atol: float = 1e-08, categorical_as_str: bool = False, nans_compare_equal: bool | None = None, ) → None[source]#

Assert that the left and right Series are equal.

Raises a detailed AssertionError if the Series differ. This function is intended for use in unit tests.

Parameters:

left: The first Series to compare.
right: The second Series to compare.
check_dtype: Require data types to match.
check_names: Require names to match.
check_exact: Require data values to match exactly. If set to False, values are considered equal when within tolerance of each other (see rtol and atol). Logical types like dates are always checked exactly.
rtol: Relative tolerance for inexact checking, given as a fraction of the values in right.
atol: Absolute tolerance for inexact checking.
categorical_as_str: Cast categorical columns to string before comparing. Enabling this helps compare columns that do not share the same string cache.
nans_compare_equal: Consider NaN values to be equal.

See also

assert_frame_equal
assert_series_not_equal

Notes

When using pytest, it may be worthwhile to shorten Python traceback printing by passing --tb=short. The default mode tends to be unhelpfully verbose. More information in the pytest docs.

Examples

>>> from polars.testing import assert_series_equal
>>> s1 = pl.Series([1, 2, 3])
>>> s2 = pl.Series([1, 5, 3])
>>> assert_series_equal(s1, s2)  
Traceback (most recent call last):
...
AssertionError: Series are different (value mismatch)
[left]:  [1, 2, 3]
[right]: [1, 5, 3]