def _create_string_length_expectation(
self, key: str,
details: dict) -> Optional[ExpectationConfiguration]:
"""https://json-schema.org/understanding-json-schema/reference/string.html#length"""
type_ = details.get("type", None)
minimum = details.get("minLength", None)
maximum = details.get("maxLength", None)
if type_ != JsonSchemaTypes.STRING.value:
return None
if minimum is None and maximum is None:
return None
kwargs = {
"column": key,
}
if minimum == maximum:
kwargs["value"] = minimum
return ExpectationConfiguration(
"expect_column_value_lengths_to_equal",
ExpectationKwargs(kwargs))
if minimum is not None:
kwargs["min_value"] = minimum
if maximum is not None:
kwargs["max_value"] = maximum
return ExpectationConfiguration(
"expect_column_value_lengths_to_be_between",
ExpectationKwargs(kwargs))
def _create_range_expectation(
self, key: str,
details: dict) -> Optional[ExpectationConfiguration]:
"""https://json-schema.org/understanding-json-schema/reference/numeric.html#range"""
type_ = details.get("type", None)
if type_ not in [
JsonSchemaTypes.INTEGER.value, JsonSchemaTypes.NUMBER.value
]:
return None
minimum = details.get("minimum", None)
maximum = details.get("maximum", None)
exclusive_minimum = details.get("exclusiveMinimum", None)
exclusive_maximum = details.get("exclusiveMaximum", None)
if (minimum is None and maximum is None and exclusive_minimum is None
and exclusive_maximum is None):
return None
kwargs: Dict[str, Any] = {"column": key}
if minimum is not None:
kwargs["min_value"] = minimum
if maximum is not None:
kwargs["max_value"] = maximum
if exclusive_minimum is not None:
kwargs["min_value"] = exclusive_minimum
kwargs["strict_min"] = True
if exclusive_maximum is not None:
kwargs["max_value"] = exclusive_maximum
kwargs["strict_max"] = True
return ExpectationConfiguration("expect_column_values_to_be_between",
ExpectationKwargs(kwargs))
def test_catch_exceptions_with_bad_expectation_type():
# We want to catch degenerate cases where an expectation suite is incompatible with
my_df = PandasDataset({"x": range(10)})
my_df._append_expectation(
ExpectationConfiguration(expectation_type="foobar", kwargs={})
)
result = my_df.validate(catch_exceptions=True)
# Find the foobar result
idx = 0
for idx, val_result in enumerate(result.results):
if val_result.expectation_config.expectation_type == "foobar":
break
assert result.results[idx].success is False
assert result.results[idx].expectation_config.expectation_type == "foobar"
assert result.results[idx].expectation_config.kwargs == ExpectationKwargs()
assert result.results[idx].exception_info["raised_exception"] is True
assert (
"AttributeError: 'PandasDataset' object has no attribute 'foobar'"
in result.results[idx].exception_info["exception_traceback"]
)
with pytest.raises(AttributeError):
result = my_df.validate(catch_exceptions=False)
def _create_type_expectation(
self, key: str,
details: dict) -> Optional[ExpectationConfiguration]:
type_ = details.get("type", None)
if type_ is None:
return None
type_list = self.PROFILER_TYPE_LIST_BY_JSON_SCHEMA_TYPE[type_]
kwargs = ExpectationKwargs(column=key, type_list=type_list)
return ExpectationConfiguration(
"expect_column_values_to_be_in_type_list", kwargs)
def test_expectation_decorator_build_config():
eds = ExpectationOnlyDataAsset()
eds.no_op_expectation()
eds.no_op_value_expectation('a')
config = eds.get_expectation_suite()
assert ExpectationConfiguration(expectation_type='no_op_expectation',
kwargs={}) == config.expectations[0]
assert ExpectationConfiguration(
expectation_type='no_op_value_expectation',
kwargs=ExpectationKwargs({'value': 'a'})) == config.expectations[1]
def _create_boolean_expectation(
self, key: str,
details: dict) -> Optional[ExpectationConfiguration]:
"""https://json-schema.org/understanding-json-schema/reference/boolean.html"""
type_ = details.get("type", None)
if type_ != JsonSchemaTypes.BOOLEAN.value:
return None
# TODO map JSONSchema types to which type backend? Pandas? Should this value set be parameterized per back end?
kwargs = ExpectationKwargs(column=key, value_set=[True, False])
return ExpectationConfiguration("expect_column_values_to_be_in_set",
kwargs)
def test_expectation_decorator_build_config():
eds = ExpectationOnlyDataAsset()
eds.no_op_expectation()
eds.no_op_value_expectation("a")
config = eds.get_expectation_suite()
assert (ExpectationConfiguration(expectation_type="no_op_expectation",
kwargs={}) == config.expectations[0])
assert (ExpectationConfiguration(
expectation_type="no_op_value_expectation",
kwargs=ExpectationKwargs({"value": "a"}),
) == config.expectations[1])
def _create_set_expectation(
self, key: str,
details: dict) -> Optional[ExpectationConfiguration]:
"""https://json-schema.org/understanding-json-schema/reference/generic.html#enumerated-values"""
if JsonSchemaTypes.ENUM.value not in details.keys():
return None
enum = details.get("enum", None)
if not isinstance(enum, list):
return None
kwargs = ExpectationKwargs(column=key, value_set=enum)
return ExpectationConfiguration("expect_column_values_to_be_in_set",
kwargs)
def _create_existence_expectation(
self, key: str, details: dict) -> ExpectationConfiguration:
kwargs = ExpectationKwargs(column=key)
description = details.get("description", None)
meta = None
if description:
meta = {
"notes": {
"format": "markdown",
"content": [f"### Description:\n{description}"],
}
}
return ExpectationConfiguration("expect_column_to_exist",
kwargs,
meta=meta)
def kwargs1():
return ExpectationKwargs({
"column": "a",
"value_set": [1, 2, 3],
"result_format": "BASIC"
})
def kwargs3():
return ExpectationKwargs(column="a",
value_set=[1, 2, 3],
result_format="COMPLETE")
def kwargs2():
return ExpectationKwargs(column="a",
value_set=[1, 2, 3],
result_format="BASIC")
def test_expectation_suite_filedata_asset():
# Load in data files
file_path = file_relative_path(__file__,
'../test_sets/toy_data_complete.csv')
# Create FileDataAsset objects
f_dat = ge.data_asset.FileDataAsset(file_path)
# Set up expectations
f_dat.expect_file_line_regex_match_count_to_equal(regex=r',\S',
expected_count=3,
skip=1,
result_format="BASIC",
catch_exceptions=True)
f_dat.expect_file_line_regex_match_count_to_be_between(
regex=r',\S',
expected_max_count=2,
skip=1,
result_format="SUMMARY",
include_config=True)
# Test basic config output
complete_config = f_dat.get_expectation_suite()
assert [
ExpectationConfiguration(
expectation_type='expect_file_line_regex_match_count_to_equal',
kwargs=ExpectationKwargs(expected_count=3, regex=',\\S', skip=1))
] == complete_config.expectations
# Include result format kwargs
complete_config2 = f_dat.get_expectation_suite(
discard_result_format_kwargs=False, discard_failed_expectations=False)
assert [
ExpectationConfiguration(
expectation_type='expect_file_line_regex_match_count_to_equal',
kwargs={
'expected_count': 3,
'regex': ',\\S',
'result_format': "BASIC",
'skip': 1
}),
ExpectationConfiguration(
expectation_type='expect_file_line_regex_match_count_to_be_between',
kwargs={
'expected_max_count': 2,
'regex': ',\\S',
'result_format': 'SUMMARY',
'skip': 1
})
] == complete_config2.expectations
# Discard Failing Expectations
complete_config3 = f_dat.get_expectation_suite(
discard_result_format_kwargs=False, discard_failed_expectations=True)
assert [
ExpectationConfiguration(
expectation_type='expect_file_line_regex_match_count_to_equal',
kwargs={
'expected_count': 3,
'regex': ',\\S',
'result_format': 'BASIC',
'skip': 1
})
] == complete_config3.expectations
def test_expectation_suite_filedata_asset():
# Load in data files
file_path = file_relative_path(__file__,
"../test_sets/toy_data_complete.csv")
# Create FileDataAsset objects
f_dat = ge.data_asset.FileDataAsset(file_path)
# Set up expectations
f_dat.expect_file_line_regex_match_count_to_equal(
regex=r",\S",
expected_count=3,
skip=1,
result_format="BASIC",
catch_exceptions=True,
)
f_dat.expect_file_line_regex_match_count_to_be_between(
regex=r",\S",
expected_max_count=2,
skip=1,
result_format="SUMMARY",
include_config=True,
)
# Test basic config output
complete_config = f_dat.get_expectation_suite()
assert [
ExpectationConfiguration(
expectation_type="expect_file_line_regex_match_count_to_equal",
kwargs=ExpectationKwargs(expected_count=3, regex=",\\S", skip=1),
)
] == complete_config.expectations
# Include result format kwargs
complete_config2 = f_dat.get_expectation_suite(
discard_result_format_kwargs=False, discard_failed_expectations=False)
assert [
ExpectationConfiguration(
expectation_type="expect_file_line_regex_match_count_to_equal",
kwargs={
"expected_count": 3,
"regex": ",\\S",
"result_format": "BASIC",
"skip": 1,
},
),
ExpectationConfiguration(
expectation_type="expect_file_line_regex_match_count_to_be_between",
kwargs={
"expected_max_count": 2,
"regex": ",\\S",
"result_format": "SUMMARY",
"skip": 1,
},
),
] == complete_config2.expectations
# Discard Failing Expectations
complete_config3 = f_dat.get_expectation_suite(
discard_result_format_kwargs=False, discard_failed_expectations=True)
assert [
ExpectationConfiguration(
expectation_type="expect_file_line_regex_match_count_to_equal",
kwargs={
"expected_count": 3,
"regex": ",\\S",
"result_format": "BASIC",
"skip": 1,
},
)
] == complete_config3.expectations