> The complete documentation index is at [llms.txt](/llms.txt).

This module contains standard expectations that can be used to test data artifacts in a
Bauplan pipeline. Using these expectations instead of hand-made ones will make your
pipeline easier to maintain, and significantly faster and more memory-efficient.

Each function returns a boolean, so that the wrapping function can assert or
print out messages in case of failure.

## expect_column_accepted_values

```python
def expect_column_accepted_values(table: pa.Table, column_name: str, accepted_values: list)
```

Expect all values in the column to come from the list of accepted values.

**Parameters:**
- `table` (pa.Table): the pyarrow table to test.
- `column_name` (str): the column to test.
- `accepted_values` (list): the list of accepted values.

## expect_column_all_null

```python
def expect_column_all_null(table: pa.Table, column_name: str)
```

Expect the column to have all null values.

**Parameters:**
- `table` (pa.Table): the pyarrow table to test.
- `column_name` (str): the column to test.

## expect_column_all_unique

```python
def expect_column_all_unique(table: pa.Table, column_name: str)
```

Expect the column to have all unique values (i.e. no duplicates).

**Parameters:**
- `table` (pa.Table): the pyarrow table to test.
- `column_name` (str): the column to test.

## expect_column_equal_concatenation

```python
def expect_column_equal_concatenation(table: pa.Table, target_column: str, columns: list, separator: str = '')
```

Expect the target column to be equal to the concatenation of the columns in the list.

**Parameters:**
- `table` (pa.Table): the pyarrow table to test.
- `target_column` (str): the column to compare with the concatenation of the columns.
- `columns` (list): the list of columns to concatenate.
- `separator` (str): the separator to use when concatenating the columns.

## expect_column_mean_greater_or_equal_than

```python
def expect_column_mean_greater_or_equal_than(table: pa.Table, column_name: str, value: float)
```

Expect the mean of a column to be equal or greater than the supplied value.

**Parameters:**
- `table` (pa.Table): the pyarrow table to test.
- `column_name` (str): the column to calculate the mean of.
- `value` (float): the value to compare the mean with.

## expect_column_mean_greater_than

```python
def expect_column_mean_greater_than(table: pa.Table, column_name: str, value: float)
```

Expect the mean of a column to be greater than the supplied value.

**Parameters:**
- `table` (pa.Table): the pyarrow table to test.
- `column_name` (str): the column to calculate the mean of.
- `value` (float): the value to compare the mean with.

## expect_column_mean_smaller_or_equal_than

```python
def expect_column_mean_smaller_or_equal_than(table: pa.Table, column_name: str, value: float)
```

Expect the mean of a column to be equal or smaller than the supplied value.

**Parameters:**
- `table` (pa.Table): the pyarrow table to test.
- `column_name` (str): the column to calculate the mean of.
- `value` (float): the value to compare the mean with.

## expect_column_mean_smaller_than

```python
def expect_column_mean_smaller_than(table: pa.Table, column_name: str, value: float)
```

Expect the mean of a column to be smaller than the supplied value.

**Parameters:**
- `table` (pa.Table): the pyarrow table to test.
- `column_name` (str): the column to calculate the mean of.
- `value` (float): the value to compare the mean with.

## expect_column_no_nulls

```python
def expect_column_no_nulls(table: pa.Table, column_name: str)
```

Expect the column to have no null values.

**Parameters:**
- `table` (pa.Table): the pyarrow table to test.
- `column_name` (str): the column to test.

## expect_column_not_unique

```python
def expect_column_not_unique(table: pa.Table, column_name: str)
```

Expect the column to have at least one duplicate value.

**Parameters:**
- `table` (pa.Table): the pyarrow table to test.
- `column_name` (str): the column to test.

## expect_column_some_null

```python
def expect_column_some_null(table: pa.Table, column_name: str)
```

Expect the column to have at least one null.

**Parameters:**
- `table` (pa.Table): the pyarrow table to test.
- `column_name` (str): the column to test.