> ## Documentation Index
> Fetch the complete documentation index at: https://mage-staging.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Data validation

> Every data loader and transformer block has data validation capabilities built-in.

You can define 1 or more test functions in a single block. Each test function
accepts a data object as an argument.

Within the body of the function, you can write any type of test you want to
validate the input data.

After the block’s main code is executed, the output data is passed into each
test function for validation. If any tests fail, then the block run will also
fail.

***

### Example

Here is an example of a transformer block with 2 tests:

```python theme={null}
from pandas import DataFrame

if 'transformer' not in globals():
    from mage_ai.data_preparation.decorators import transformer
if 'test' not in globals():
    from mage_ai.data_preparation.decorators import test

COLUMNS_TO_USE = ['name']


@transformer
def transform_df(df: DataFrame, *args, **kwargs) -> DataFrame:
    return df.iloc[:1][COLUMNS_TO_USE]


@test
def test_number_of_rows(df) -> None:
    assert len(df.index) >= 2, 'The output has more than 1 row.'


@test
def test_columns(df) -> None:
    assert df.columns[0] != COLUMNS_TO_USE[0], 'The output columns don’t match.'
```

<Note>
  You can combine all your data validations into 1 test function or you can
  split them up into multiple test functions. The benefit of splitting them up
  is that they can run in parallel, speeding up the data validation.
</Note>

***

### Log output

Each test run is recorded and can be viewed in the logs. Here is an example:

```
Start executing block.
--------------------------------------------------------------
2/2 tests passed.
Finish executing block.
```