assert_collection_equal#

diffly.testing.assert_collection_equal(
left: dy.Collection,
right: dy.Collection,
/,
*,
check_dtypes: bool = True,
abs_tol: float | Mapping[str, float] = 1e-08,
rel_tol: float | Mapping[str, float] = 1e-05,
abs_tol_temporal: dt.timedelta | Mapping[str, dt.timedelta] = datetime.timedelta(0),
show_perfect_column_matches: bool = False,
top_k_column_changes: int = 0,
sample_k_rows_only: int = 0,
show_sample_primary_key_per_change: bool = False,
left_name: str = Side.LEFT,
right_name: str = Side.RIGHT,
slim: bool = False,
hidden_columns: list[str] | None = None,
) → None[source]#

Assert that two dataframely collections are equal.

Two collections are considered equal if they are instances of the same collection type, have the same set of members, and all members are equal.

Parameters:

  • left – The first collection in the comparison.

  • right – The second collection in the comparison.

  • check_dtypes – Whether to check that the data types of columns match exactly.

  • abs_tol – Absolute tolerance for comparing floating point types. If a Mapping is provided, it should map from column name to absolute tolerance for every column in the data frame.

  • rel_tol – Relative tolerance for comparing floating point types. If a Mapping is provided, it should map from column name to relative tolerance for every column in the data frame.

  • abs_tol_temporal – Absolute tolerance for comparing temporal types. If a Mapping is provided, it should map from column name to absolute temporal tolerance for every column in the data frame.

  • show_perfect_column_matches – Whether to include column matches in the assertion error even if the column match rate is 100%.

  • top_k_column_changes – The maximum number of column values changes to display for columns with a match rate below 100% in the summary. When enabling this feature, make sure that no sensitive data is leaked.

  • sample_k_rows_only – The number of rows to show in the “Rows left/right only” section of the summary. If 0 (default), no rows are shown. Only the primary key will be printed. An error will be raised if a positive number is provided and any of the primary key columns is also in hidden_columns.

  • show_sample_primary_key_per_change – Whether to show a sample primary key per column change in the summary. If False (default), no primary key values are shown. A sample primary key can only be shown if top_k_column_changes is greater than 0, as each sample primary key is linked to a specific column change. An error will be raised if True and any of the primary key columns is also in hidden_columns.

  • left_name – Custom display name for the left data frame.

  • right_name – Custom display name for the right data frame.

  • slim – Whether to generate a slim summary. In slim mode, the summary is as concise as possible, only showing sections that contain differences. As the structure of the summary can vary, it should only be used by advanced users who are familiar with the summary format.

  • hidden_columns – Columns for which no values are printed, e.g. because they contain sensitive information.

Raises:

AssertionError – If the collections are not equal.