gx_basic.py

### Does not work

expectation_suite_name = "my_expectation_suite"
checkpoint_name = "my_checkpoint"

context = gx.get_context()

# # Initialize expectation suite
def init_expectation_suite():
    expectation_suite = context.add_expectation_suite(
        expectation_suite_name=expectation_suite_name
    )
    # Expect column 'name' to exist
    expect_column_name = ExpectationConfiguration(
        expectation_type="expect_column_to_exist", kwargs={"column": "name"}
    )
    # Expect column 'age' to have values between 18 and 65
    expect_column_age = ExpectationConfiguration(
        expectation_type="expect_column_values_to_be_between",
        kwargs={"column": "age", "min_value": 18, "max_value": 65},
    )
    # Expect column 'salary' to have a mean between 45000 and 80000
    expect_column_salary = ExpectationConfiguration(
        expectation_type="expect_column_mean_to_be_between",
        kwargs={"column": "salary", "min_value": 45000, "max_value": 80000},
    )
    expectation_suite.add_expectation_configurations(
        expectation_configurations=[
            expect_column_name,
            expect_column_age,
            expect_column_salary,
        ]
    )
    return expectation_suite


expectation_suite = init_expectation_suite()


# Initialize data
def init_batch_request():
    data = pd.DataFrame(
        {
            "name": ["Alice", "Bob", "Charlie"],
            "age": [25, 30, 35],
            "salary": [50000, 60000, 70000],
        }
    )
    this_data_source = context.sources.add_pandas(name="my_pandas_datasource")
    this_data_asset = this_data_source.add_dataframe_asset(name="my_dataframe_asset")
    batch_request = this_data_asset.build_batch_request(dataframe=data)
    return batch_request


batch_request = init_batch_request()


checkpoint = context.add_or_update_checkpoint(
    name=checkpoint_name,
    expectation_suite_name=expectation_suite_name,
    batch_request=batch_request,
)
checkpoint_result = checkpoint.run(run_name=f"run_{datetime.now()}")