def table_Users_domain():
skip_if_python_below_minimum_version()
return Domain(
domain_type=MetricDomainTypes.TABLE,
domain_kwargs=None,
details=None,
)
def single_part_name_parameter_container():
skip_if_python_below_minimum_version()
return ParameterContainer(parameter_nodes={
"mean": ParameterNode({
"mean": 5.0,
}),
})
def column_Date_domain():
skip_if_python_below_minimum_version()
return Domain(
domain_type=MetricDomainTypes.COLUMN,
domain_kwargs={
"column": "Date",
"batch_id": "c260e179bb1bc81d84bba72a8110d8e2",
},
details=None,
)
def rule_without_parameters(empty_data_context, ):
skip_if_python_below_minimum_version()
rule: Rule = Rule(
name="rule_with_no_variables_no_parameters",
domain_builder=ColumnDomainBuilder(data_context=empty_data_context),
expectation_configuration_builders=[
DefaultExpectationConfigurationBuilder(
expectation_type="expect_my_validation")
],
)
return rule
def profiler_with_placeholder_args(
empty_data_context,
profiler_config_with_placeholder_args,
):
skip_if_python_below_minimum_version()
profiler_config_dict: dict = profiler_config_with_placeholder_args.to_json_dict(
)
profiler_config_dict.pop("class_name")
profiler_config_dict.pop("module_name")
profiler: RuleBasedProfiler = RuleBasedProfiler(
**profiler_config_dict, data_context=empty_data_context)
return profiler
def variables_multi_part_name_parameter_container():
skip_if_python_below_minimum_version()
variables_multi_part_name_parameter_node: ParameterNode = ParameterNode({
"false_positive_threshold":
1.0e-2,
})
root_variables_node: ParameterNode = ParameterNode({
"variables":
variables_multi_part_name_parameter_node, # $variables.false_positive_threshold
})
variables: ParameterContainer = ParameterContainer(
parameter_nodes={
"variables": root_variables_node,
})
return variables
def pandas_test_df():
skip_if_python_below_minimum_version()
df: pd.DataFrame = pd.DataFrame({
"Age":
pd.Series(
[
7,
15,
21,
39,
None,
],
dtype="float64",
),
"Date":
pd.Series(
[
datetime.date(2020, 12, 31),
datetime.date(2021, 1, 1),
datetime.date(2021, 2, 21),
datetime.date(2021, 3, 20),
None,
],
dtype="object",
),
"Description":
pd.Series(
[
"child",
"teenager",
"young adult",
"adult",
None,
],
dtype="object",
),
})
df["Date"] = pd.to_datetime(df["Date"])
return df
def rule_with_parameters(
empty_data_context,
column_Age_domain,
column_Date_domain,
variables_multi_part_name_parameter_container,
single_part_name_parameter_container,
multi_part_name_parameter_container,
):
skip_if_python_below_minimum_version()
rule: Rule = Rule(
name="rule_with_parameters",
domain_builder=ColumnDomainBuilder(data_context=empty_data_context),
expectation_configuration_builders=[
DefaultExpectationConfigurationBuilder(
expectation_type="expect_my_validation")
],
)
rule._parameters = {
column_Age_domain.id: single_part_name_parameter_container,
column_Date_domain.id: multi_part_name_parameter_container,
}
return rule
def parameters_with_different_depth_level_values():
skip_if_python_below_minimum_version()
parameter_values: Dict[str, Any] = {
"$parameter.date_strings.yyyy_mm_dd_hh_mm_ss_tz_date_format.value":
"%Y-%m-%d %H:%M:%S %Z",
"$parameter.date_strings.yyyy_mm_dd_hh_mm_ss_tz_date_format.details": {
"confidence": 7.8e-1,
},
"$parameter.date_strings.yyyy_mm_dd_date_format.value":
"%Y-%m-%d",
"$parameter.date_strings.yyyy_mm_dd_date_format.details": {
"confidence": 7.8e-1,
},
"$parameter.date_strings.mm_yyyy_dd_hh_mm_ss_tz_date_format.value":
"%m-%Y-%d %H:%M:%S %Z",
"$parameter.date_strings.mm_yyyy_dd_hh_mm_ss_tz_date_format.details": {
"confidence": 7.8e-1,
},
"$parameter.date_strings.mm_yyyy_dd_date_format.value":
"%m-%Y-%d",
"$parameter.date_strings.mm_yyyy_dd_date_format.details": {
"confidence": 7.8e-1,
},
"$parameter.date_strings.tolerances.max_abs_error_time_milliseconds":
100,
"$parameter.date_strings.tolerances.max_num_conversion_attempts":
5,
"$parameter.tolerances.mostly":
9.1e-1,
"$parameter.tolerances.financial.usd":
1.0,
"$mean":
6.5e-1,
"$parameter.monthly_taxi_fairs.mean_values.value": [
2.3,
9.8,
42.3,
8.1,
38.5,
53.7,
71.43,
16.34,
49.43,
74.35,
51.98,
46.42,
20.01,
69.44,
65.32,
8.83,
55.79,
82.2,
36.93,
83.78,
31.13,
76.93,
67.67,
25.12,
58.04,
79.78,
90.91,
15.26,
61.65,
78.78,
12.99,
],
"$parameter.monthly_taxi_fairs.mean_values.details": {
"confidence": "low",
},
"$parameter.daily_taxi_fairs.mean_values.value": {
"sunday": 71.43,
"monday": 74.35,
"tuesday": 42.3,
"wednesday": 42.3,
"thursday": 82.2,
"friday": 78.78,
"saturday": 91.39,
},
"$parameter.daily_taxi_fairs.mean_values.details": {
"confidence": "medium",
},
"$parameter.weekly_taxi_fairs.mean_values.value": [
{
"sunday": 71.43,
"monday": 74.35,
"tuesday": 42.3,
"wednesday": 42.3,
"thursday": 82.2,
"friday": 78.78,
"saturday": 91.39,
},
{
"sunday": 81.43,
"monday": 84.35,
"tuesday": 52.3,
"wednesday": 43.3,
"thursday": 22.2,
"friday": 98.78,
"saturday": 81.39,
},
{
"sunday": 61.43,
"monday": 34.35,
"tuesday": 82.3,
"wednesday": 72.3,
"thursday": 22.2,
"friday": 38.78,
"saturday": 51.39,
},
{
"sunday": 51.43,
"monday": 64.35,
"tuesday": 72.3,
"wednesday": 82.3,
"thursday": 22.2,
"friday": 98.78,
"saturday": 31.39,
},
{
"sunday": 72.43,
"monday": 77.35,
"tuesday": 46.3,
"wednesday": 47.3,
"thursday": 88.2,
"friday": 79.78,
"saturday": 93.39,
},
{
"sunday": 72.43,
"monday": 73.35,
"tuesday": 41.3,
"wednesday": 49.3,
"thursday": 80.2,
"friday": 78.78,
"saturday": 93.39,
},
{
"sunday": 74.43,
"monday": 78.35,
"tuesday": 49.3,
"wednesday": 43.3,
"thursday": 88.2,
"friday": 72.78,
"saturday": 97.39,
},
{
"sunday": 73.43,
"monday": 72.35,
"tuesday": 40.3,
"wednesday": 40.3,
"thursday": 89.2,
"friday": 77.78,
"saturday": 90.39,
},
{
"sunday": 72.43,
"monday": 73.35,
"tuesday": 45.3,
"wednesday": 44.3,
"thursday": 89.2,
"friday": 77.78,
"saturday": 96.39,
},
{
"sunday": 75.43,
"monday": 74.25,
"tuesday": 42.33,
"wednesday": 42.23,
"thursday": 82.21,
"friday": 78.76,
"saturday": 91.37,
},
{
"sunday": 71.43,
"monday": 74.37,
"tuesday": 42.3,
"wednesday": 42.32,
"thursday": 82.23,
"friday": 78.77,
"saturday": 91.49,
},
{
"sunday": 71.63,
"monday": 74.37,
"tuesday": 42.2,
"wednesday": 42.1,
"thursday": 82.29,
"friday": 78.79,
"saturday": 91.39,
},
{
"sunday": 71.42,
"monday": 74.33,
"tuesday": 42.33,
"wednesday": 42.34,
"thursday": 82.25,
"friday": 78.77,
"saturday": 91.69,
},
{
"sunday": 71.44,
"monday": 72.35,
"tuesday": 42.33,
"wednesday": 42.31,
"thursday": 82.29,
"friday": 78.68,
"saturday": 91.49,
},
{
"sunday": 71.44,
"monday": 74.32,
"tuesday": 42.32,
"wednesday": 42.32,
"thursday": 82.29,
"friday": 78.77,
"saturday": 91.49,
},
{
"sunday": 71.44,
"monday": 74.33,
"tuesday": 42.21,
"wednesday": 42.31,
"thursday": 82.27,
"friday": 78.74,
"saturday": 91.49,
},
{
"sunday": 71.33,
"monday": 74.25,
"tuesday": 42.31,
"wednesday": 42.03,
"thursday": 82.02,
"friday": 78.08,
"saturday": 91.38,
},
{
"sunday": 71.41,
"monday": 74.31,
"tuesday": 42.39,
"wednesday": 42.93,
"thursday": 82.92,
"friday": 78.75,
"saturday": 91.49,
},
{
"sunday": 72.43,
"monday": 73.35,
"tuesday": 42.3,
"wednesday": 32.3,
"thursday": 52.2,
"friday": 88.78,
"saturday": 81.39,
},
{
"sunday": 71.43,
"monday": 74.35,
"tuesday": 32.3,
"wednesday": 92.3,
"thursday": 72.2,
"friday": 74.78,
"saturday": 51.39,
},
{
"sunday": 72.43,
"monday": 64.35,
"tuesday": 52.3,
"wednesday": 42.39,
"thursday": 82.28,
"friday": 78.77,
"saturday": 91.36,
},
{
"sunday": 81.43,
"monday": 94.35,
"tuesday": 62.3,
"wednesday": 52.3,
"thursday": 92.2,
"friday": 88.78,
"saturday": 51.39,
},
{
"sunday": 21.43,
"monday": 34.35,
"tuesday": 42.34,
"wednesday": 62.3,
"thursday": 52.2,
"friday": 98.78,
"saturday": 81.39,
},
{
"sunday": 71.33,
"monday": 74.25,
"tuesday": 42.13,
"wednesday": 42.93,
"thursday": 82.82,
"friday": 78.78,
"saturday": 91.39,
},
{
"sunday": 72.43,
"monday": 73.35,
"tuesday": 44.3,
"wednesday": 45.3,
"thursday": 86.2,
"friday": 77.78,
"saturday": 98.39,
},
{
"sunday": 79.43,
"monday": 78.35,
"tuesday": 47.3,
"wednesday": 46.3,
"thursday": 85.2,
"friday": 74.78,
"saturday": 93.39,
},
{
"sunday": 71.42,
"monday": 74.31,
"tuesday": 42.0,
"wednesday": 42.1,
"thursday": 82.23,
"friday": 65.78,
"saturday": 91.26,
},
{
"sunday": 91.43,
"monday": 84.35,
"tuesday": 42.37,
"wednesday": 42.36,
"thursday": 82.25,
"friday": 78.74,
"saturday": 91.32,
},
{
"sunday": 71.33,
"monday": 74.45,
"tuesday": 42.35,
"wednesday": 42.36,
"thursday": 82.27,
"friday": 26.78,
"saturday": 71.39,
},
{
"sunday": 71.53,
"monday": 73.35,
"tuesday": 43.32,
"wednesday": 42.23,
"thursday": 82.32,
"friday": 78.18,
"saturday": 91.49,
},
{
"sunday": 71.53,
"monday": 74.25,
"tuesday": 52.3,
"wednesday": 52.3,
"thursday": 81.23,
"friday": 78.78,
"saturday": 78.39,
},
],
"$parameter.weekly_taxi_fairs.mean_values.details": {
"confidence": "high",
},
}
return parameter_values
def multi_part_name_parameter_container():
"""
$parameter.date_strings.yyyy_mm_dd_hh_mm_ss_tz_date_format.value
$parameter.date_strings.yyyy_mm_dd_hh_mm_ss_tz_date_format.details
$parameter.date_strings.yyyy_mm_dd_date_format.value
$parameter.date_strings.yyyy_mm_dd_date_format.details
$parameter.date_strings.mm_yyyy_dd_hh_mm_ss_tz_date_format.value
$parameter.date_strings.mm_yyyy_dd_hh_mm_ss_tz_date_format.details
$parameter.date_strings.mm_yyyy_dd_date_format.value
$parameter.date_strings.mm_yyyy_dd_date_format.details
$parameter.date_strings.tolerances.max_abs_error_time_milliseconds
$parameter.date_strings.tolerances.max_num_conversion_attempts
$parameter.tolerances.mostly
$mean
$parameter.monthly_taxi_fairs.mean_values.value[0]
$parameter.monthly_taxi_fairs.mean_values.value[1]
$parameter.monthly_taxi_fairs.mean_values.value[2]
$parameter.monthly_taxi_fairs.mean_values.value[3]
$parameter.monthly_taxi_fairs.mean_values.details
$parameter.daily_taxi_fairs.mean_values.value["friday"]
$parameter.daily_taxi_fairs.mean_values.value["saturday"]
$parameter.daily_taxi_fairs.mean_values.value["sunday"]
$parameter.daily_taxi_fairs.mean_values.value["monday"]
$parameter.daily_taxi_fairs.mean_values.details
$parameter.weekly_taxi_fairs.mean_values.value[1]['friday']
$parameter.weekly_taxi_fairs.mean_values.value[18]['saturday']
$parameter.weekly_taxi_fairs.mean_values.value[20]['sunday']
$parameter.weekly_taxi_fairs.mean_values.value[21]['monday']
$parameter.weekly_taxi_fairs.mean_values.details
"""
skip_if_python_below_minimum_version()
root_mean_node: ParameterNode = ParameterNode({
"mean": 6.5e-1,
})
financial_tolerances_parameter_node: ParameterNode = ParameterNode({
"usd":
1.0,
})
tolerances_parameter_node: ParameterNode = ParameterNode({
"mostly":
9.1e-1,
"financial":
financial_tolerances_parameter_node,
})
date_strings_tolerances_parameter_node: ParameterNode = ParameterNode({
"max_abs_error_time_milliseconds":
100,
"max_num_conversion_attempts":
5,
})
date_strings_parameter_node: ParameterNode = ParameterNode({
"yyyy_mm_dd_hh_mm_ss_tz_date_format":
ParameterNode({
"value": "%Y-%m-%d %H:%M:%S %Z",
"details": ParameterNode({
"confidence": 7.8e-1,
}, ),
}),
"yyyy_mm_dd_date_format":
ParameterNode({
"value": "%Y-%m-%d",
"details": ParameterNode({
"confidence": 7.8e-1,
}, ),
}),
"mm_yyyy_dd_hh_mm_ss_tz_date_format":
ParameterNode({
"value": "%m-%Y-%d %H:%M:%S %Z",
"details": ParameterNode({
"confidence": 7.8e-1,
}, ),
}),
"mm_yyyy_dd_date_format":
ParameterNode({
"value": "%m-%Y-%d",
"details": ParameterNode({
"confidence": 7.8e-1,
}, ),
}),
"tolerances":
date_strings_tolerances_parameter_node,
})
monthly_taxi_fairs_parameter_node: ParameterNode = ParameterNode({
"mean_values":
ParameterNode({
"value": [
2.3,
9.8,
42.3,
8.1,
38.5,
53.7,
71.43,
16.34,
49.43,
74.35,
51.98,
46.42,
20.01,
69.44,
65.32,
8.83,
55.79,
82.2,
36.93,
83.78,
31.13,
76.93,
67.67,
25.12,
58.04,
79.78,
90.91,
15.26,
61.65,
78.78,
12.99,
],
"details":
ParameterNode({
"confidence": "low",
}, ),
}),
})
daily_taxi_fairs_parameter_node: ParameterNode = ParameterNode({
"mean_values":
ParameterNode({
"value": {
"sunday": 71.43,
"monday": 74.35,
"tuesday": 42.3,
"wednesday": 42.3,
"thursday": 82.2,
"friday": 78.78,
"saturday": 91.39,
},
"details": ParameterNode({
"confidence": "medium",
}, ),
}),
})
weekly_taxi_fairs_parameter_node: ParameterNode = ParameterNode({
"mean_values":
ParameterNode({
"value": [
{
"sunday": 71.43,
"monday": 74.35,
"tuesday": 42.3,
"wednesday": 42.3,
"thursday": 82.2,
"friday": 78.78,
"saturday": 91.39,
},
{
"sunday": 81.43,
"monday": 84.35,
"tuesday": 52.3,
"wednesday": 43.3,
"thursday": 22.2,
"friday": 98.78,
"saturday": 81.39,
},
{
"sunday": 61.43,
"monday": 34.35,
"tuesday": 82.3,
"wednesday": 72.3,
"thursday": 22.2,
"friday": 38.78,
"saturday": 51.39,
},
{
"sunday": 51.43,
"monday": 64.35,
"tuesday": 72.3,
"wednesday": 82.3,
"thursday": 22.2,
"friday": 98.78,
"saturday": 31.39,
},
{
"sunday": 72.43,
"monday": 77.35,
"tuesday": 46.3,
"wednesday": 47.3,
"thursday": 88.2,
"friday": 79.78,
"saturday": 93.39,
},
{
"sunday": 72.43,
"monday": 73.35,
"tuesday": 41.3,
"wednesday": 49.3,
"thursday": 80.2,
"friday": 78.78,
"saturday": 93.39,
},
{
"sunday": 74.43,
"monday": 78.35,
"tuesday": 49.3,
"wednesday": 43.3,
"thursday": 88.2,
"friday": 72.78,
"saturday": 97.39,
},
{
"sunday": 73.43,
"monday": 72.35,
"tuesday": 40.3,
"wednesday": 40.3,
"thursday": 89.2,
"friday": 77.78,
"saturday": 90.39,
},
{
"sunday": 72.43,
"monday": 73.35,
"tuesday": 45.3,
"wednesday": 44.3,
"thursday": 89.2,
"friday": 77.78,
"saturday": 96.39,
},
{
"sunday": 75.43,
"monday": 74.25,
"tuesday": 42.33,
"wednesday": 42.23,
"thursday": 82.21,
"friday": 78.76,
"saturday": 91.37,
},
{
"sunday": 71.43,
"monday": 74.37,
"tuesday": 42.3,
"wednesday": 42.32,
"thursday": 82.23,
"friday": 78.77,
"saturday": 91.49,
},
{
"sunday": 71.63,
"monday": 74.37,
"tuesday": 42.2,
"wednesday": 42.1,
"thursday": 82.29,
"friday": 78.79,
"saturday": 91.39,
},
{
"sunday": 71.42,
"monday": 74.33,
"tuesday": 42.33,
"wednesday": 42.34,
"thursday": 82.25,
"friday": 78.77,
"saturday": 91.69,
},
{
"sunday": 71.44,
"monday": 72.35,
"tuesday": 42.33,
"wednesday": 42.31,
"thursday": 82.29,
"friday": 78.68,
"saturday": 91.49,
},
{
"sunday": 71.44,
"monday": 74.32,
"tuesday": 42.32,
"wednesday": 42.32,
"thursday": 82.29,
"friday": 78.77,
"saturday": 91.49,
},
{
"sunday": 71.44,
"monday": 74.33,
"tuesday": 42.21,
"wednesday": 42.31,
"thursday": 82.27,
"friday": 78.74,
"saturday": 91.49,
},
{
"sunday": 71.33,
"monday": 74.25,
"tuesday": 42.31,
"wednesday": 42.03,
"thursday": 82.02,
"friday": 78.08,
"saturday": 91.38,
},
{
"sunday": 71.41,
"monday": 74.31,
"tuesday": 42.39,
"wednesday": 42.93,
"thursday": 82.92,
"friday": 78.75,
"saturday": 91.49,
},
{
"sunday": 72.43,
"monday": 73.35,
"tuesday": 42.3,
"wednesday": 32.3,
"thursday": 52.2,
"friday": 88.78,
"saturday": 81.39,
},
{
"sunday": 71.43,
"monday": 74.35,
"tuesday": 32.3,
"wednesday": 92.3,
"thursday": 72.2,
"friday": 74.78,
"saturday": 51.39,
},
{
"sunday": 72.43,
"monday": 64.35,
"tuesday": 52.3,
"wednesday": 42.39,
"thursday": 82.28,
"friday": 78.77,
"saturday": 91.36,
},
{
"sunday": 81.43,
"monday": 94.35,
"tuesday": 62.3,
"wednesday": 52.3,
"thursday": 92.2,
"friday": 88.78,
"saturday": 51.39,
},
{
"sunday": 21.43,
"monday": 34.35,
"tuesday": 42.34,
"wednesday": 62.3,
"thursday": 52.2,
"friday": 98.78,
"saturday": 81.39,
},
{
"sunday": 71.33,
"monday": 74.25,
"tuesday": 42.13,
"wednesday": 42.93,
"thursday": 82.82,
"friday": 78.78,
"saturday": 91.39,
},
{
"sunday": 72.43,
"monday": 73.35,
"tuesday": 44.3,
"wednesday": 45.3,
"thursday": 86.2,
"friday": 77.78,
"saturday": 98.39,
},
{
"sunday": 79.43,
"monday": 78.35,
"tuesday": 47.3,
"wednesday": 46.3,
"thursday": 85.2,
"friday": 74.78,
"saturday": 93.39,
},
{
"sunday": 71.42,
"monday": 74.31,
"tuesday": 42.0,
"wednesday": 42.1,
"thursday": 82.23,
"friday": 65.78,
"saturday": 91.26,
},
{
"sunday": 91.43,
"monday": 84.35,
"tuesday": 42.37,
"wednesday": 42.36,
"thursday": 82.25,
"friday": 78.74,
"saturday": 91.32,
},
{
"sunday": 71.33,
"monday": 74.45,
"tuesday": 42.35,
"wednesday": 42.36,
"thursday": 82.27,
"friday": 26.78,
"saturday": 71.39,
},
{
"sunday": 71.53,
"monday": 73.35,
"tuesday": 43.32,
"wednesday": 42.23,
"thursday": 82.32,
"friday": 78.18,
"saturday": 91.49,
},
{
"sunday": 71.53,
"monday": 74.25,
"tuesday": 52.3,
"wednesday": 52.3,
"thursday": 81.23,
"friday": 78.78,
"saturday": 78.39,
},
],
"details":
ParameterNode({
"confidence": "high",
}, ),
}),
})
parameter_multi_part_name_parameter_node: ParameterNode = ParameterNode({
"date_strings":
date_strings_parameter_node,
"tolerances":
tolerances_parameter_node,
"monthly_taxi_fairs":
monthly_taxi_fairs_parameter_node,
"daily_taxi_fairs":
daily_taxi_fairs_parameter_node,
"weekly_taxi_fairs":
weekly_taxi_fairs_parameter_node,
})
root_parameter_node: ParameterNode = ParameterNode({
"parameter":
parameter_multi_part_name_parameter_node,
})
return ParameterContainer(parameter_nodes={
"parameter": root_parameter_node,
"mean": root_mean_node,
})