It can be very convenient to have great expectations automatically review a dataset and suggest expectations that may be appropriate. Currently, there’s a very basic, but easily extensible, autoinspection capability available.

Dataset objects have an autoinspect method which allows you to provide a function that will evaluate a dataset object and add expectations to it. By default autoinspect will call the autoinspect function columns_exist which will add an expect_column_to_exist expectation for each column currently present on the dataset.

To implement additional autoinspection functions, you simply take a single parameter, a Dataset, and evaluate and add expectations to that object.

>> import great_expectations as ge
>> df = ge.dataset.PandasDataset({"col": [1, 2, 3, 4, 5]})
>> df.autoinspect(ge.dataset.autoinspect.columns_exist)
>> df.get_expectations_config()
    {'dataset_name': None,
     'meta': {'great_expectations.__version__': '0.4.4__develop'},
     'expectations': [
         {'expectation_type': 'expect_column_to_exist',
          'kwargs': {'column': 'col'}