Last updated: July 22, 2025

DQOps REST API table_quality_policies operations

Operations for managing the configuration of data quality policies at a table level. Policies are the default configuration of data quality checks for tables matching a pattern.

---

copy_from_table_quality_policy

Creates (adds) a copy of an existing default table-level checks pattern configuration (data quality policy) under a new name.

Follow the link to see the source code on GitHub.

POST

http://localhost:8888/api/policies/checks/table/{targetPatternName}/copyfrom/{sourcePatternName}

Parameters of this method are described below

Property name	Description	Data type	Required
target_pattern_name	Target pattern name	string
source_pattern_name	Source pattern name	string

Usage examples

curlPython sync clientPython async clientPython auth sync clientPython auth async client

Execution

curl -X POST http://localhost:8888/api/policies/checks/table/default/copyfrom/default^
    -H "Accept: application/json"

Execution

from dqops import client
from dqops.client.api.table_quality_policies import copy_from_table_quality_policy

dqops_client = client.Client(
    'http://localhost:8888/'
)

call_result = copy_from_table_quality_policy.sync(
    'default',
    'default',
    client=dqops_client
)

Execution

from dqops import client
from dqops.client.api.table_quality_policies import copy_from_table_quality_policy

dqops_client = client.Client(
    'http://localhost:8888/'
)

call_result = await copy_from_table_quality_policy.asyncio(
    'default',
    'default',
    client=dqops_client
)

Execution

from dqops import client
from dqops.client.api.table_quality_policies import copy_from_table_quality_policy

token = 's4mp13_4u7h_70k3n'

dqops_client = client.AuthenticatedClient(
    'http://localhost:8888/',
    token=token
)

call_result = copy_from_table_quality_policy.sync(
    'default',
    'default',
    client=dqops_client
)

Execution

from dqops import client
from dqops.client.api.table_quality_policies import copy_from_table_quality_policy

token = 's4mp13_4u7h_70k3n'

dqops_client = client.AuthenticatedClient(
    'http://localhost:8888/',
    token=token
)

call_result = await copy_from_table_quality_policy.asyncio(
    'default',
    'default',
    client=dqops_client
)

---

create_table_quality_policy_pattern

Creates (adds) a new default table-level checks pattern (data quality policy) configuration by saving a full specification object.

Follow the link to see the source code on GitHub.

POST

http://localhost:8888/api/policies/checks/table/{patternName}

Parameters of this method are described below

Property name	Description	Data type	Required
pattern_name	Pattern name	string

Request body

Description	Data type	Required
Default checks pattern model	TableQualityPolicyModel

Usage examples

curlPython sync clientPython async clientPython auth sync clientPython auth async client

Execution

curl -X POST http://localhost:8888/api/policies/checks/table/default^
    -H "Accept: application/json"^
    -H "Content-Type: application/json"^
    -d^
    "{\"policy_name\":\"default\",\"policy_spec\":{\"priority\":1000,\"monitoring_checks\":{\"daily\":{\"volume\":{\"daily_row_count\":{\"warning\":{\"min_count\":1}}}}}},\"can_edit\":true}"

Execution

from dqops import client
from dqops.client.api.table_quality_policies import create_table_quality_policy_pattern
from dqops.client.models import MinCountRule1ParametersSpec, \
                                TableMonitoringCheckCategoriesSpec, \
                                TablePartitionedCheckCategoriesSpec, \
                                TableProfilingCheckCategoriesSpec, \
                                TableQualityPolicyModel, \
                                TableQualityPolicySpec, \
                                TableRowCountCheckSpec, \
                                TableVolumeProfilingChecksSpec, \
                                TableVolumeRowCountSensorParametersSpec, \
                                TargetTablePatternSpec

dqops_client = client.Client(
    'http://localhost:8888/'
)

request_body = TableQualityPolicyModel(
    policy_name='default',
    policy_spec=TableQualityPolicySpec(
        priority=1000,
        disabled=False,
        target=TargetTablePatternSpec(),
        profiling_checks=TableProfilingCheckCategoriesSpec(comparisons=TableComparisonProfilingChecksSpecMap()),
        monitoring_checks=TableMonitoringCheckCategoriesSpec(
            daily=TableDailyMonitoringCheckCategoriesSpec(
                volume=TableVolumeDailyMonitoringChecksSpec(
                    daily_row_count=TableRowCountCheckSpec(
                        parameters=TableVolumeRowCountSensorParametersSpec(),
                        warning=MinCountRule1ParametersSpec(min_count=1),
                        disabled=False,
                        exclude_from_kpi=False,
                        include_in_sla=False,
                        always_collect_error_samples=False,
                        do_not_schedule=False
                    )
                ),
                comparisons=TableComparisonDailyMonitoringChecksSpecMap()
            )
        ),
        partitioned_checks=TablePartitionedCheckCategoriesSpec()
    ),
    can_edit=True
)

call_result = create_table_quality_policy_pattern.sync(
    'default',
    client=dqops_client,
    json_body=request_body
)

Execution

from dqops import client
from dqops.client.api.table_quality_policies import create_table_quality_policy_pattern
from dqops.client.models import MinCountRule1ParametersSpec, \
                                TableMonitoringCheckCategoriesSpec, \
                                TablePartitionedCheckCategoriesSpec, \
                                TableProfilingCheckCategoriesSpec, \
                                TableQualityPolicyModel, \
                                TableQualityPolicySpec, \
                                TableRowCountCheckSpec, \
                                TableVolumeProfilingChecksSpec, \
                                TableVolumeRowCountSensorParametersSpec, \
                                TargetTablePatternSpec

dqops_client = client.Client(
    'http://localhost:8888/'
)

request_body = TableQualityPolicyModel(
    policy_name='default',
    policy_spec=TableQualityPolicySpec(
        priority=1000,
        disabled=False,
        target=TargetTablePatternSpec(),
        profiling_checks=TableProfilingCheckCategoriesSpec(comparisons=TableComparisonProfilingChecksSpecMap()),
        monitoring_checks=TableMonitoringCheckCategoriesSpec(
            daily=TableDailyMonitoringCheckCategoriesSpec(
                volume=TableVolumeDailyMonitoringChecksSpec(
                    daily_row_count=TableRowCountCheckSpec(
                        parameters=TableVolumeRowCountSensorParametersSpec(),
                        warning=MinCountRule1ParametersSpec(min_count=1),
                        disabled=False,
                        exclude_from_kpi=False,
                        include_in_sla=False,
                        always_collect_error_samples=False,
                        do_not_schedule=False
                    )
                ),
                comparisons=TableComparisonDailyMonitoringChecksSpecMap()
            )
        ),
        partitioned_checks=TablePartitionedCheckCategoriesSpec()
    ),
    can_edit=True
)

call_result = await create_table_quality_policy_pattern.asyncio(
    'default',
    client=dqops_client,
    json_body=request_body
)

Execution

from dqops import client
from dqops.client.api.table_quality_policies import create_table_quality_policy_pattern
from dqops.client.models import MinCountRule1ParametersSpec, \
                                TableMonitoringCheckCategoriesSpec, \
                                TablePartitionedCheckCategoriesSpec, \
                                TableProfilingCheckCategoriesSpec, \
                                TableQualityPolicyModel, \
                                TableQualityPolicySpec, \
                                TableRowCountCheckSpec, \
                                TableVolumeProfilingChecksSpec, \
                                TableVolumeRowCountSensorParametersSpec, \
                                TargetTablePatternSpec

token = 's4mp13_4u7h_70k3n'

dqops_client = client.AuthenticatedClient(
    'http://localhost:8888/',
    token=token
)

request_body = TableQualityPolicyModel(
    policy_name='default',
    policy_spec=TableQualityPolicySpec(
        priority=1000,
        disabled=False,
        target=TargetTablePatternSpec(),
        profiling_checks=TableProfilingCheckCategoriesSpec(comparisons=TableComparisonProfilingChecksSpecMap()),
        monitoring_checks=TableMonitoringCheckCategoriesSpec(
            daily=TableDailyMonitoringCheckCategoriesSpec(
                volume=TableVolumeDailyMonitoringChecksSpec(
                    daily_row_count=TableRowCountCheckSpec(
                        parameters=TableVolumeRowCountSensorParametersSpec(),
                        warning=MinCountRule1ParametersSpec(min_count=1),
                        disabled=False,
                        exclude_from_kpi=False,
                        include_in_sla=False,
                        always_collect_error_samples=False,
                        do_not_schedule=False
                    )
                ),
                comparisons=TableComparisonDailyMonitoringChecksSpecMap()
            )
        ),
        partitioned_checks=TablePartitionedCheckCategoriesSpec()
    ),
    can_edit=True
)

call_result = create_table_quality_policy_pattern.sync(
    'default',
    client=dqops_client,
    json_body=request_body
)

Execution

from dqops import client
from dqops.client.api.table_quality_policies import create_table_quality_policy_pattern
from dqops.client.models import MinCountRule1ParametersSpec, \
                                TableMonitoringCheckCategoriesSpec, \
                                TablePartitionedCheckCategoriesSpec, \
                                TableProfilingCheckCategoriesSpec, \
                                TableQualityPolicyModel, \
                                TableQualityPolicySpec, \
                                TableRowCountCheckSpec, \
                                TableVolumeProfilingChecksSpec, \
                                TableVolumeRowCountSensorParametersSpec, \
                                TargetTablePatternSpec

token = 's4mp13_4u7h_70k3n'

dqops_client = client.AuthenticatedClient(
    'http://localhost:8888/',
    token=token
)

request_body = TableQualityPolicyModel(
    policy_name='default',
    policy_spec=TableQualityPolicySpec(
        priority=1000,
        disabled=False,
        target=TargetTablePatternSpec(),
        profiling_checks=TableProfilingCheckCategoriesSpec(comparisons=TableComparisonProfilingChecksSpecMap()),
        monitoring_checks=TableMonitoringCheckCategoriesSpec(
            daily=TableDailyMonitoringCheckCategoriesSpec(
                volume=TableVolumeDailyMonitoringChecksSpec(
                    daily_row_count=TableRowCountCheckSpec(
                        parameters=TableVolumeRowCountSensorParametersSpec(),
                        warning=MinCountRule1ParametersSpec(min_count=1),
                        disabled=False,
                        exclude_from_kpi=False,
                        include_in_sla=False,
                        always_collect_error_samples=False,
                        do_not_schedule=False
                    )
                ),
                comparisons=TableComparisonDailyMonitoringChecksSpecMap()
            )
        ),
        partitioned_checks=TablePartitionedCheckCategoriesSpec()
    ),
    can_edit=True
)

call_result = await create_table_quality_policy_pattern.asyncio(
    'default',
    client=dqops_client,
    json_body=request_body
)

---

create_table_quality_policy_target

Creates (adds) a new default table-level checks pattern configuration (a table-level data quality policy).

Follow the link to see the source code on GitHub.

POST

http://localhost:8888/api/policies/checks/table/{patternName}/target

Parameters of this method are described below

Property name	Description	Data type	Required
pattern_name	Pattern name	string

Request body

Description	Data type	Required
Default checks pattern model with only the target filters	TableQualityPolicyListModel

Usage examples

curlPython sync clientPython async clientPython auth sync clientPython auth async client

Execution

curl -X POST http://localhost:8888/api/policies/checks/table/default/target^
    -H "Accept: application/json"^
    -H "Content-Type: application/json"^
    -d^
    "{\"policy_name\":\"default\",\"priority\":100,\"disabled\":false,\"target_table\":{\"connection\":\"dwh\",\"schema\":\"public\",\"table\":\"fact_*\"},\"can_edit\":true}"

Execution

from dqops import client
from dqops.client.api.table_quality_policies import create_table_quality_policy_target
from dqops.client.models import TableQualityPolicyListModel, \
                                TargetTablePatternSpec

dqops_client = client.Client(
    'http://localhost:8888/'
)

request_body = TableQualityPolicyListModel(
    policy_name='default',
    priority=100,
    disabled=False,
    target_table=TargetTablePatternSpec(
        connection='dwh',
        schema='public',
        table='fact_*'
    ),
    can_edit=True
)

call_result = create_table_quality_policy_target.sync(
    'default',
    client=dqops_client,
    json_body=request_body
)

Execution

from dqops import client
from dqops.client.api.table_quality_policies import create_table_quality_policy_target
from dqops.client.models import TableQualityPolicyListModel, \
                                TargetTablePatternSpec

dqops_client = client.Client(
    'http://localhost:8888/'
)

request_body = TableQualityPolicyListModel(
    policy_name='default',
    priority=100,
    disabled=False,
    target_table=TargetTablePatternSpec(
        connection='dwh',
        schema='public',
        table='fact_*'
    ),
    can_edit=True
)

call_result = await create_table_quality_policy_target.asyncio(
    'default',
    client=dqops_client,
    json_body=request_body
)

Execution

from dqops import client
from dqops.client.api.table_quality_policies import create_table_quality_policy_target
from dqops.client.models import TableQualityPolicyListModel, \
                                TargetTablePatternSpec

token = 's4mp13_4u7h_70k3n'

dqops_client = client.AuthenticatedClient(
    'http://localhost:8888/',
    token=token
)

request_body = TableQualityPolicyListModel(
    policy_name='default',
    priority=100,
    disabled=False,
    target_table=TargetTablePatternSpec(
        connection='dwh',
        schema='public',
        table='fact_*'
    ),
    can_edit=True
)

call_result = create_table_quality_policy_target.sync(
    'default',
    client=dqops_client,
    json_body=request_body
)

Execution

from dqops import client
from dqops.client.api.table_quality_policies import create_table_quality_policy_target
from dqops.client.models import TableQualityPolicyListModel, \
                                TargetTablePatternSpec

token = 's4mp13_4u7h_70k3n'

dqops_client = client.AuthenticatedClient(
    'http://localhost:8888/',
    token=token
)

request_body = TableQualityPolicyListModel(
    policy_name='default',
    priority=100,
    disabled=False,
    target_table=TargetTablePatternSpec(
        connection='dwh',
        schema='public',
        table='fact_*'
    ),
    can_edit=True
)

call_result = await create_table_quality_policy_target.asyncio(
    'default',
    client=dqops_client,
    json_body=request_body
)

---

delete_table_quality_policy

Deletes a default table-level checks pattern (a data quality policy at a column level).

Follow the link to see the source code on GitHub.

DELETE

http://localhost:8888/api/policies/checks/table/{patternName}

Parameters of this method are described below

Property name	Description	Data type	Required
pattern_name	Pattern name	string

Usage examples

curlPython sync clientPython async clientPython auth sync clientPython auth async client

Execution

curl -X DELETE http://localhost:8888/api/policies/checks/table/default^
    -H "Accept: application/json"

Execution

from dqops import client
from dqops.client.api.table_quality_policies import delete_table_quality_policy

dqops_client = client.Client(
    'http://localhost:8888/'
)

call_result = delete_table_quality_policy.sync(
    'default',
    client=dqops_client
)

Execution

from dqops import client
from dqops.client.api.table_quality_policies import delete_table_quality_policy

dqops_client = client.Client(
    'http://localhost:8888/'
)

call_result = await delete_table_quality_policy.asyncio(
    'default',
    client=dqops_client
)

Execution

from dqops import client
from dqops.client.api.table_quality_policies import delete_table_quality_policy

token = 's4mp13_4u7h_70k3n'

dqops_client = client.AuthenticatedClient(
    'http://localhost:8888/',
    token=token
)

call_result = delete_table_quality_policy.sync(
    'default',
    client=dqops_client
)

Execution

from dqops import client
from dqops.client.api.table_quality_policies import delete_table_quality_policy

token = 's4mp13_4u7h_70k3n'

dqops_client = client.AuthenticatedClient(
    'http://localhost:8888/',
    token=token
)

call_result = await delete_table_quality_policy.asyncio(
    'default',
    client=dqops_client
)

---

get_monitoring_daily_table_quality_policy

Returns UI model to show and edit the default configuration of the daily monitoring checks that are configured for a check pattern on a table level.

Follow the link to see the source code on GitHub.

GET

http://localhost:8888/api/policies/checks/table/{patternName}/monitoring/daily

Return value

Property name	Description	Data type
check_container_model		CheckContainerModel

Parameters of this method are described below

Property name	Description	Data type	Required
pattern_name	Pattern name	string

Usage examples

curlPython sync clientPython async clientPython auth sync clientPython auth async client

Execution

curl http://localhost:8888/api/policies/checks/table/default/monitoring/daily^
    -H "Accept: application/json"

Expand to see the returned result

{
  "categories" : [ {
    "category" : "sample_category",
    "help_text" : "Sample help text",
    "checks" : [ {
      "check_name" : "sample_check",
      "help_text" : "Sample help text",
      "sensor_parameters" : [ ],
      "sensor_name" : "sample_target/sample_category/table/volume/row_count",
      "quality_dimension" : "sample_quality_dimension",
      "supports_error_sampling" : false,
      "supports_grouping" : false,
      "default_severity" : "error",
      "disabled" : false,
      "exclude_from_kpi" : false,
      "include_in_sla" : false,
      "configured" : false,
      "can_edit" : false,
      "can_run_checks" : false,
      "can_delete_data" : false
    } ]
  } ],
  "can_edit" : false,
  "can_run_checks" : false,
  "can_delete_data" : false
}

Execution

from dqops import client
from dqops.client.api.table_quality_policies import get_monitoring_daily_table_quality_policy

dqops_client = client.Client(
    'http://localhost:8888/',
    raise_on_unexpected_status=True
)

call_result = get_monitoring_daily_table_quality_policy.sync(
    'default',
    client=dqops_client
)

Expand to see the returned result

CheckContainerModel(
    categories=[
        QualityCategoryModel(
            category='sample_category',
            help_text='Sample help text',
            checks=[
                CheckModel(
                    check_name='sample_check',
                    help_text='Sample help text',
                    sensor_parameters=[

                    ],
                    sensor_name='sample_target/sample_category/table/volume/row_count',
                    quality_dimension='sample_quality_dimension',
                    supports_error_sampling=False,
                    supports_grouping=False,
                    standard=False,
                    default_check=False,
                    default_severity=DefaultRuleSeverityLevel.ERROR,
                    disabled=False,
                    exclude_from_kpi=False,
                    include_in_sla=False,
                    configured=False,
                    always_collect_error_samples=False,
                    do_not_schedule=False,
                    can_edit=False,
                    can_run_checks=False,
                    can_delete_data=False
                )
            ]
        )
    ],
    can_edit=False,
    can_run_checks=False,
    can_delete_data=False
)

Execution

from dqops import client
from dqops.client.api.table_quality_policies import get_monitoring_daily_table_quality_policy

dqops_client = client.Client(
    'http://localhost:8888/',
    raise_on_unexpected_status=True
)

call_result = await get_monitoring_daily_table_quality_policy.asyncio(
    'default',
    client=dqops_client
)

Expand to see the returned result

CheckContainerModel(
    categories=[
        QualityCategoryModel(
            category='sample_category',
            help_text='Sample help text',
            checks=[
                CheckModel(
                    check_name='sample_check',
                    help_text='Sample help text',
                    sensor_parameters=[

                    ],
                    sensor_name='sample_target/sample_category/table/volume/row_count',
                    quality_dimension='sample_quality_dimension',
                    supports_error_sampling=False,
                    supports_grouping=False,
                    standard=False,
                    default_check=False,
                    default_severity=DefaultRuleSeverityLevel.ERROR,
                    disabled=False,
                    exclude_from_kpi=False,
                    include_in_sla=False,
                    configured=False,
                    always_collect_error_samples=False,
                    do_not_schedule=False,
                    can_edit=False,
                    can_run_checks=False,
                    can_delete_data=False
                )
            ]
        )
    ],
    can_edit=False,
    can_run_checks=False,
    can_delete_data=False
)

Execution

from dqops import client
from dqops.client.api.table_quality_policies import get_monitoring_daily_table_quality_policy

token = 's4mp13_4u7h_70k3n'

dqops_client = client.AuthenticatedClient(
    'http://localhost:8888/',
    token=token,
    raise_on_unexpected_status=True
)

call_result = get_monitoring_daily_table_quality_policy.sync(
    'default',
    client=dqops_client
)

Expand to see the returned result

CheckContainerModel(
    categories=[
        QualityCategoryModel(
            category='sample_category',
            help_text='Sample help text',
            checks=[
                CheckModel(
                    check_name='sample_check',
                    help_text='Sample help text',
                    sensor_parameters=[

                    ],
                    sensor_name='sample_target/sample_category/table/volume/row_count',
                    quality_dimension='sample_quality_dimension',
                    supports_error_sampling=False,
                    supports_grouping=False,
                    standard=False,
                    default_check=False,
                    default_severity=DefaultRuleSeverityLevel.ERROR,
                    disabled=False,
                    exclude_from_kpi=False,
                    include_in_sla=False,
                    configured=False,
                    always_collect_error_samples=False,
                    do_not_schedule=False,
                    can_edit=False,
                    can_run_checks=False,
                    can_delete_data=False
                )
            ]
        )
    ],
    can_edit=False,
    can_run_checks=False,
    can_delete_data=False
)

Execution

from dqops import client
from dqops.client.api.table_quality_policies import get_monitoring_daily_table_quality_policy

token = 's4mp13_4u7h_70k3n'

dqops_client = client.AuthenticatedClient(
    'http://localhost:8888/',
    token=token,
    raise_on_unexpected_status=True
)

call_result = await get_monitoring_daily_table_quality_policy.asyncio(
    'default',
    client=dqops_client
)

Expand to see the returned result

CheckContainerModel(
    categories=[
        QualityCategoryModel(
            category='sample_category',
            help_text='Sample help text',
            checks=[
                CheckModel(
                    check_name='sample_check',
                    help_text='Sample help text',
                    sensor_parameters=[

                    ],
                    sensor_name='sample_target/sample_category/table/volume/row_count',
                    quality_dimension='sample_quality_dimension',
                    supports_error_sampling=False,
                    supports_grouping=False,
                    standard=False,
                    default_check=False,
                    default_severity=DefaultRuleSeverityLevel.ERROR,
                    disabled=False,
                    exclude_from_kpi=False,
                    include_in_sla=False,
                    configured=False,
                    always_collect_error_samples=False,
                    do_not_schedule=False,
                    can_edit=False,
                    can_run_checks=False,
                    can_delete_data=False
                )
            ]
        )
    ],
    can_edit=False,
    can_run_checks=False,
    can_delete_data=False
)

---

get_monitoring_monthly_table_quality_policy

Returns UI model to show and edit the default configuration of the monthly monitoring checks that are configured for a check pattern on a table level.

Follow the link to see the source code on GitHub.

GET

http://localhost:8888/api/policies/checks/table/{patternName}/monitoring/monthly

Return value

Property name	Description	Data type
check_container_model		CheckContainerModel

Parameters of this method are described below

Property name	Description	Data type	Required
pattern_name	Pattern name	string

Usage examples

curlPython sync clientPython async clientPython auth sync clientPython auth async client

Execution

curl http://localhost:8888/api/policies/checks/table/default/monitoring/monthly^
    -H "Accept: application/json"

Expand to see the returned result

{
  "categories" : [ {
    "category" : "sample_category",
    "help_text" : "Sample help text",
    "checks" : [ {
      "check_name" : "sample_check",
      "help_text" : "Sample help text",
      "sensor_parameters" : [ ],
      "sensor_name" : "sample_target/sample_category/table/volume/row_count",
      "quality_dimension" : "sample_quality_dimension",
      "supports_error_sampling" : false,
      "supports_grouping" : false,
      "default_severity" : "error",
      "disabled" : false,
      "exclude_from_kpi" : false,
      "include_in_sla" : false,
      "configured" : false,
      "can_edit" : false,
      "can_run_checks" : false,
      "can_delete_data" : false
    } ]
  } ],
  "can_edit" : false,
  "can_run_checks" : false,
  "can_delete_data" : false
}

Execution

from dqops import client
from dqops.client.api.table_quality_policies import get_monitoring_monthly_table_quality_policy

dqops_client = client.Client(
    'http://localhost:8888/',
    raise_on_unexpected_status=True
)

call_result = get_monitoring_monthly_table_quality_policy.sync(
    'default',
    client=dqops_client
)

Expand to see the returned result

CheckContainerModel(
    categories=[
        QualityCategoryModel(
            category='sample_category',
            help_text='Sample help text',
            checks=[
                CheckModel(
                    check_name='sample_check',
                    help_text='Sample help text',
                    sensor_parameters=[

                    ],
                    sensor_name='sample_target/sample_category/table/volume/row_count',
                    quality_dimension='sample_quality_dimension',
                    supports_error_sampling=False,
                    supports_grouping=False,
                    standard=False,
                    default_check=False,
                    default_severity=DefaultRuleSeverityLevel.ERROR,
                    disabled=False,
                    exclude_from_kpi=False,
                    include_in_sla=False,
                    configured=False,
                    always_collect_error_samples=False,
                    do_not_schedule=False,
                    can_edit=False,
                    can_run_checks=False,
                    can_delete_data=False
                )
            ]
        )
    ],
    can_edit=False,
    can_run_checks=False,
    can_delete_data=False
)

Execution

from dqops import client
from dqops.client.api.table_quality_policies import get_monitoring_monthly_table_quality_policy

dqops_client = client.Client(
    'http://localhost:8888/',
    raise_on_unexpected_status=True
)

call_result = await get_monitoring_monthly_table_quality_policy.asyncio(
    'default',
    client=dqops_client
)

Expand to see the returned result

CheckContainerModel(
    categories=[
        QualityCategoryModel(
            category='sample_category',
            help_text='Sample help text',
            checks=[
                CheckModel(
                    check_name='sample_check',
                    help_text='Sample help text',
                    sensor_parameters=[

                    ],
                    sensor_name='sample_target/sample_category/table/volume/row_count',
                    quality_dimension='sample_quality_dimension',
                    supports_error_sampling=False,
                    supports_grouping=False,
                    standard=False,
                    default_check=False,
                    default_severity=DefaultRuleSeverityLevel.ERROR,
                    disabled=False,
                    exclude_from_kpi=False,
                    include_in_sla=False,
                    configured=False,
                    always_collect_error_samples=False,
                    do_not_schedule=False,
                    can_edit=False,
                    can_run_checks=False,
                    can_delete_data=False
                )
            ]
        )
    ],
    can_edit=False,
    can_run_checks=False,
    can_delete_data=False
)

Execution

from dqops import client
from dqops.client.api.table_quality_policies import get_monitoring_monthly_table_quality_policy

token = 's4mp13_4u7h_70k3n'

dqops_client = client.AuthenticatedClient(
    'http://localhost:8888/',
    token=token,
    raise_on_unexpected_status=True
)

call_result = get_monitoring_monthly_table_quality_policy.sync(
    'default',
    client=dqops_client
)

Expand to see the returned result

CheckContainerModel(
    categories=[
        QualityCategoryModel(
            category='sample_category',
            help_text='Sample help text',
            checks=[
                CheckModel(
                    check_name='sample_check',
                    help_text='Sample help text',
                    sensor_parameters=[

                    ],
                    sensor_name='sample_target/sample_category/table/volume/row_count',
                    quality_dimension='sample_quality_dimension',
                    supports_error_sampling=False,
                    supports_grouping=False,
                    standard=False,
                    default_check=False,
                    default_severity=DefaultRuleSeverityLevel.ERROR,
                    disabled=False,
                    exclude_from_kpi=False,
                    include_in_sla=False,
                    configured=False,
                    always_collect_error_samples=False,
                    do_not_schedule=False,
                    can_edit=False,
                    can_run_checks=False,
                    can_delete_data=False
                )
            ]
        )
    ],
    can_edit=False,
    can_run_checks=False,
    can_delete_data=False
)

Execution

from dqops import client
from dqops.client.api.table_quality_policies import get_monitoring_monthly_table_quality_policy

token = 's4mp13_4u7h_70k3n'

dqops_client = client.AuthenticatedClient(
    'http://localhost:8888/',
    token=token,
    raise_on_unexpected_status=True
)

call_result = await get_monitoring_monthly_table_quality_policy.asyncio(
    'default',
    client=dqops_client
)

Expand to see the returned result

CheckContainerModel(
    categories=[
        QualityCategoryModel(
            category='sample_category',
            help_text='Sample help text',
            checks=[
                CheckModel(
                    check_name='sample_check',
                    help_text='Sample help text',
                    sensor_parameters=[

                    ],
                    sensor_name='sample_target/sample_category/table/volume/row_count',
                    quality_dimension='sample_quality_dimension',
                    supports_error_sampling=False,
                    supports_grouping=False,
                    standard=False,
                    default_check=False,
                    default_severity=DefaultRuleSeverityLevel.ERROR,
                    disabled=False,
                    exclude_from_kpi=False,
                    include_in_sla=False,
                    configured=False,
                    always_collect_error_samples=False,
                    do_not_schedule=False,
                    can_edit=False,
                    can_run_checks=False,
                    can_delete_data=False
                )
            ]
        )
    ],
    can_edit=False,
    can_run_checks=False,
    can_delete_data=False
)

---

get_partitioned_daily_table_quality_policy

Returns UI model to show and edit the default configuration of the daily partitioned checks that are configured for a check pattern on a table level.

Follow the link to see the source code on GitHub.

GET

http://localhost:8888/api/policies/checks/table/{patternName}/partitioned/daily

Return value

Property name	Description	Data type
check_container_model		CheckContainerModel

Parameters of this method are described below

Property name	Description	Data type	Required
pattern_name	Pattern name	string

Usage examples

curlPython sync clientPython async clientPython auth sync clientPython auth async client

Execution

curl http://localhost:8888/api/policies/checks/table/default/partitioned/daily^
    -H "Accept: application/json"

Expand to see the returned result

{
  "categories" : [ {
    "category" : "sample_category",
    "help_text" : "Sample help text",
    "checks" : [ {
      "check_name" : "sample_check",
      "help_text" : "Sample help text",
      "sensor_parameters" : [ ],
      "sensor_name" : "sample_target/sample_category/table/volume/row_count",
      "quality_dimension" : "sample_quality_dimension",
      "supports_error_sampling" : false,
      "supports_grouping" : false,
      "default_severity" : "error",
      "disabled" : false,
      "exclude_from_kpi" : false,
      "include_in_sla" : false,
      "configured" : false,
      "can_edit" : false,
      "can_run_checks" : false,
      "can_delete_data" : false
    } ]
  } ],
  "can_edit" : false,
  "can_run_checks" : false,
  "can_delete_data" : false
}

Execution

from dqops import client
from dqops.client.api.table_quality_policies import get_partitioned_daily_table_quality_policy

dqops_client = client.Client(
    'http://localhost:8888/',
    raise_on_unexpected_status=True
)

call_result = get_partitioned_daily_table_quality_policy.sync(
    'default',
    client=dqops_client
)

Expand to see the returned result

CheckContainerModel(
    categories=[
        QualityCategoryModel(
            category='sample_category',
            help_text='Sample help text',
            checks=[
                CheckModel(
                    check_name='sample_check',
                    help_text='Sample help text',
                    sensor_parameters=[

                    ],
                    sensor_name='sample_target/sample_category/table/volume/row_count',
                    quality_dimension='sample_quality_dimension',
                    supports_error_sampling=False,
                    supports_grouping=False,
                    standard=False,
                    default_check=False,
                    default_severity=DefaultRuleSeverityLevel.ERROR,
                    disabled=False,
                    exclude_from_kpi=False,
                    include_in_sla=False,
                    configured=False,
                    always_collect_error_samples=False,
                    do_not_schedule=False,
                    can_edit=False,
                    can_run_checks=False,
                    can_delete_data=False
                )
            ]
        )
    ],
    can_edit=False,
    can_run_checks=False,
    can_delete_data=False
)

Execution

from dqops import client
from dqops.client.api.table_quality_policies import get_partitioned_daily_table_quality_policy

dqops_client = client.Client(
    'http://localhost:8888/',
    raise_on_unexpected_status=True
)

call_result = await get_partitioned_daily_table_quality_policy.asyncio(
    'default',
    client=dqops_client
)

Expand to see the returned result

CheckContainerModel(
    categories=[
        QualityCategoryModel(
            category='sample_category',
            help_text='Sample help text',
            checks=[
                CheckModel(
                    check_name='sample_check',
                    help_text='Sample help text',
                    sensor_parameters=[

                    ],
                    sensor_name='sample_target/sample_category/table/volume/row_count',
                    quality_dimension='sample_quality_dimension',
                    supports_error_sampling=False,
                    supports_grouping=False,
                    standard=False,
                    default_check=False,
                    default_severity=DefaultRuleSeverityLevel.ERROR,
                    disabled=False,
                    exclude_from_kpi=False,
                    include_in_sla=False,
                    configured=False,
                    always_collect_error_samples=False,
                    do_not_schedule=False,
                    can_edit=False,
                    can_run_checks=False,
                    can_delete_data=False
                )
            ]
        )
    ],
    can_edit=False,
    can_run_checks=False,
    can_delete_data=False
)

Execution

from dqops import client
from dqops.client.api.table_quality_policies import get_partitioned_daily_table_quality_policy

token = 's4mp13_4u7h_70k3n'

dqops_client = client.AuthenticatedClient(
    'http://localhost:8888/',
    token=token,
    raise_on_unexpected_status=True
)

call_result = get_partitioned_daily_table_quality_policy.sync(
    'default',
    client=dqops_client
)

Expand to see the returned result

CheckContainerModel(
    categories=[
        QualityCategoryModel(
            category='sample_category',
            help_text='Sample help text',
            checks=[
                CheckModel(
                    check_name='sample_check',
                    help_text='Sample help text',
                    sensor_parameters=[

                    ],
                    sensor_name='sample_target/sample_category/table/volume/row_count',
                    quality_dimension='sample_quality_dimension',
                    supports_error_sampling=False,
                    supports_grouping=False,
                    standard=False,
                    default_check=False,
                    default_severity=DefaultRuleSeverityLevel.ERROR,
                    disabled=False,
                    exclude_from_kpi=False,
                    include_in_sla=False,
                    configured=False,
                    always_collect_error_samples=False,
                    do_not_schedule=False,
                    can_edit=False,
                    can_run_checks=False,
                    can_delete_data=False
                )
            ]
        )
    ],
    can_edit=False,
    can_run_checks=False,
    can_delete_data=False
)

Execution

from dqops import client
from dqops.client.api.table_quality_policies import get_partitioned_daily_table_quality_policy

token = 's4mp13_4u7h_70k3n'

dqops_client = client.AuthenticatedClient(
    'http://localhost:8888/',
    token=token,
    raise_on_unexpected_status=True
)

call_result = await get_partitioned_daily_table_quality_policy.asyncio(
    'default',
    client=dqops_client
)

Expand to see the returned result

CheckContainerModel(
    categories=[
        QualityCategoryModel(
            category='sample_category',
            help_text='Sample help text',
            checks=[
                CheckModel(
                    check_name='sample_check',
                    help_text='Sample help text',
                    sensor_parameters=[

                    ],
                    sensor_name='sample_target/sample_category/table/volume/row_count',
                    quality_dimension='sample_quality_dimension',
                    supports_error_sampling=False,
                    supports_grouping=False,
                    standard=False,
                    default_check=False,
                    default_severity=DefaultRuleSeverityLevel.ERROR,
                    disabled=False,
                    exclude_from_kpi=False,
                    include_in_sla=False,
                    configured=False,
                    always_collect_error_samples=False,
                    do_not_schedule=False,
                    can_edit=False,
                    can_run_checks=False,
                    can_delete_data=False
                )
            ]
        )
    ],
    can_edit=False,
    can_run_checks=False,
    can_delete_data=False
)

---

get_partitioned_monthly_table_quality_policy

Returns UI model to show and edit the default configuration of the monthly partitioned checks that are configured for a check pattern on a table level.

Follow the link to see the source code on GitHub.

GET

http://localhost:8888/api/policies/checks/table/{patternName}/partitioned/monthly

Return value

Property name	Description	Data type
check_container_model		CheckContainerModel

Parameters of this method are described below

Property name	Description	Data type	Required
pattern_name	Pattern name	string

Usage examples

curlPython sync clientPython async clientPython auth sync clientPython auth async client

Execution

curl http://localhost:8888/api/policies/checks/table/default/partitioned/monthly^
    -H "Accept: application/json"

Expand to see the returned result

{
  "categories" : [ {
    "category" : "sample_category",
    "help_text" : "Sample help text",
    "checks" : [ {
      "check_name" : "sample_check",
      "help_text" : "Sample help text",
      "sensor_parameters" : [ ],
      "sensor_name" : "sample_target/sample_category/table/volume/row_count",
      "quality_dimension" : "sample_quality_dimension",
      "supports_error_sampling" : false,
      "supports_grouping" : false,
      "default_severity" : "error",
      "disabled" : false,
      "exclude_from_kpi" : false,
      "include_in_sla" : false,
      "configured" : false,
      "can_edit" : false,
      "can_run_checks" : false,
      "can_delete_data" : false
    } ]
  } ],
  "can_edit" : false,
  "can_run_checks" : false,
  "can_delete_data" : false
}

Execution

from dqops import client
from dqops.client.api.table_quality_policies import get_partitioned_monthly_table_quality_policy

dqops_client = client.Client(
    'http://localhost:8888/',
    raise_on_unexpected_status=True
)

call_result = get_partitioned_monthly_table_quality_policy.sync(
    'default',
    client=dqops_client
)

Expand to see the returned result

CheckContainerModel(
    categories=[
        QualityCategoryModel(
            category='sample_category',
            help_text='Sample help text',
            checks=[
                CheckModel(
                    check_name='sample_check',
                    help_text='Sample help text',
                    sensor_parameters=[

                    ],
                    sensor_name='sample_target/sample_category/table/volume/row_count',
                    quality_dimension='sample_quality_dimension',
                    supports_error_sampling=False,
                    supports_grouping=False,
                    standard=False,
                    default_check=False,
                    default_severity=DefaultRuleSeverityLevel.ERROR,
                    disabled=False,
                    exclude_from_kpi=False,
                    include_in_sla=False,
                    configured=False,
                    always_collect_error_samples=False,
                    do_not_schedule=False,
                    can_edit=False,
                    can_run_checks=False,
                    can_delete_data=False
                )
            ]
        )
    ],
    can_edit=False,
    can_run_checks=False,
    can_delete_data=False
)

Execution

from dqops import client
from dqops.client.api.table_quality_policies import get_partitioned_monthly_table_quality_policy

dqops_client = client.Client(
    'http://localhost:8888/',
    raise_on_unexpected_status=True
)

call_result = await get_partitioned_monthly_table_quality_policy.asyncio(
    'default',
    client=dqops_client
)

Expand to see the returned result

CheckContainerModel(
    categories=[
        QualityCategoryModel(
            category='sample_category',
            help_text='Sample help text',
            checks=[
                CheckModel(
                    check_name='sample_check',
                    help_text='Sample help text',
                    sensor_parameters=[

                    ],
                    sensor_name='sample_target/sample_category/table/volume/row_count',
                    quality_dimension='sample_quality_dimension',
                    supports_error_sampling=False,
                    supports_grouping=False,
                    standard=False,
                    default_check=False,
                    default_severity=DefaultRuleSeverityLevel.ERROR,
                    disabled=False,
                    exclude_from_kpi=False,
                    include_in_sla=False,
                    configured=False,
                    always_collect_error_samples=False,
                    do_not_schedule=False,
                    can_edit=False,
                    can_run_checks=False,
                    can_delete_data=False
                )
            ]
        )
    ],
    can_edit=False,
    can_run_checks=False,
    can_delete_data=False
)

Execution

from dqops import client
from dqops.client.api.table_quality_policies import get_partitioned_monthly_table_quality_policy

token = 's4mp13_4u7h_70k3n'

dqops_client = client.AuthenticatedClient(
    'http://localhost:8888/',
    token=token,
    raise_on_unexpected_status=True
)

call_result = get_partitioned_monthly_table_quality_policy.sync(
    'default',
    client=dqops_client
)

Expand to see the returned result

CheckContainerModel(
    categories=[
        QualityCategoryModel(
            category='sample_category',
            help_text='Sample help text',
            checks=[
                CheckModel(
                    check_name='sample_check',
                    help_text='Sample help text',
                    sensor_parameters=[

                    ],
                    sensor_name='sample_target/sample_category/table/volume/row_count',
                    quality_dimension='sample_quality_dimension',
                    supports_error_sampling=False,
                    supports_grouping=False,
                    standard=False,
                    default_check=False,
                    default_severity=DefaultRuleSeverityLevel.ERROR,
                    disabled=False,
                    exclude_from_kpi=False,
                    include_in_sla=False,
                    configured=False,
                    always_collect_error_samples=False,
                    do_not_schedule=False,
                    can_edit=False,
                    can_run_checks=False,
                    can_delete_data=False
                )
            ]
        )
    ],
    can_edit=False,
    can_run_checks=False,
    can_delete_data=False
)

Execution

from dqops import client
from dqops.client.api.table_quality_policies import get_partitioned_monthly_table_quality_policy

token = 's4mp13_4u7h_70k3n'

dqops_client = client.AuthenticatedClient(
    'http://localhost:8888/',
    token=token,
    raise_on_unexpected_status=True
)

call_result = await get_partitioned_monthly_table_quality_policy.asyncio(
    'default',
    client=dqops_client
)

Expand to see the returned result

CheckContainerModel(
    categories=[
        QualityCategoryModel(
            category='sample_category',
            help_text='Sample help text',
            checks=[
                CheckModel(
                    check_name='sample_check',
                    help_text='Sample help text',
                    sensor_parameters=[

                    ],
                    sensor_name='sample_target/sample_category/table/volume/row_count',
                    quality_dimension='sample_quality_dimension',
                    supports_error_sampling=False,
                    supports_grouping=False,
                    standard=False,
                    default_check=False,
                    default_severity=DefaultRuleSeverityLevel.ERROR,
                    disabled=False,
                    exclude_from_kpi=False,
                    include_in_sla=False,
                    configured=False,
                    always_collect_error_samples=False,
                    do_not_schedule=False,
                    can_edit=False,
                    can_run_checks=False,
                    can_delete_data=False
                )
            ]
        )
    ],
    can_edit=False,
    can_run_checks=False,
    can_delete_data=False
)

---

get_profiling_table_quality_policy

Returns UI model to show and edit the default configuration of the profiling checks that are configured for a check pattern on a table level.

Follow the link to see the source code on GitHub.

GET

http://localhost:8888/api/policies/checks/table/{patternName}/profiling

Return value

Property name	Description	Data type
check_container_model		CheckContainerModel

Parameters of this method are described below

Property name	Description	Data type	Required
pattern_name	Pattern name	string

Usage examples

curlPython sync clientPython async clientPython auth sync clientPython auth async client

Execution

curl http://localhost:8888/api/policies/checks/table/default/profiling^
    -H "Accept: application/json"

Expand to see the returned result

{
  "categories" : [ {
    "category" : "sample_category",
    "help_text" : "Sample help text",
    "checks" : [ {
      "check_name" : "sample_check",
      "help_text" : "Sample help text",
      "sensor_parameters" : [ ],
      "sensor_name" : "sample_target/sample_category/table/volume/row_count",
      "quality_dimension" : "sample_quality_dimension",
      "supports_error_sampling" : false,
      "supports_grouping" : false,
      "default_severity" : "error",
      "disabled" : false,
      "exclude_from_kpi" : false,
      "include_in_sla" : false,
      "configured" : false,
      "can_edit" : false,
      "can_run_checks" : false,
      "can_delete_data" : false
    } ]
  } ],
  "can_edit" : false,
  "can_run_checks" : false,
  "can_delete_data" : false
}

Execution

from dqops import client
from dqops.client.api.table_quality_policies import get_profiling_table_quality_policy

dqops_client = client.Client(
    'http://localhost:8888/',
    raise_on_unexpected_status=True
)

call_result = get_profiling_table_quality_policy.sync(
    'default',
    client=dqops_client
)

Expand to see the returned result

CheckContainerModel(
    categories=[
        QualityCategoryModel(
            category='sample_category',
            help_text='Sample help text',
            checks=[
                CheckModel(
                    check_name='sample_check',
                    help_text='Sample help text',
                    sensor_parameters=[

                    ],
                    sensor_name='sample_target/sample_category/table/volume/row_count',
                    quality_dimension='sample_quality_dimension',
                    supports_error_sampling=False,
                    supports_grouping=False,
                    standard=False,
                    default_check=False,
                    default_severity=DefaultRuleSeverityLevel.ERROR,
                    disabled=False,
                    exclude_from_kpi=False,
                    include_in_sla=False,
                    configured=False,
                    always_collect_error_samples=False,
                    do_not_schedule=False,
                    can_edit=False,
                    can_run_checks=False,
                    can_delete_data=False
                )
            ]
        )
    ],
    can_edit=False,
    can_run_checks=False,
    can_delete_data=False
)

Execution

from dqops import client
from dqops.client.api.table_quality_policies import get_profiling_table_quality_policy

dqops_client = client.Client(
    'http://localhost:8888/',
    raise_on_unexpected_status=True
)

call_result = await get_profiling_table_quality_policy.asyncio(
    'default',
    client=dqops_client
)

Expand to see the returned result

CheckContainerModel(
    categories=[
        QualityCategoryModel(
            category='sample_category',
            help_text='Sample help text',
            checks=[
                CheckModel(
                    check_name='sample_check',
                    help_text='Sample help text',
                    sensor_parameters=[

                    ],
                    sensor_name='sample_target/sample_category/table/volume/row_count',
                    quality_dimension='sample_quality_dimension',
                    supports_error_sampling=False,
                    supports_grouping=False,
                    standard=False,
                    default_check=False,
                    default_severity=DefaultRuleSeverityLevel.ERROR,
                    disabled=False,
                    exclude_from_kpi=False,
                    include_in_sla=False,
                    configured=False,
                    always_collect_error_samples=False,
                    do_not_schedule=False,
                    can_edit=False,
                    can_run_checks=False,
                    can_delete_data=False
                )
            ]
        )
    ],
    can_edit=False,
    can_run_checks=False,
    can_delete_data=False
)

Execution

from dqops import client
from dqops.client.api.table_quality_policies import get_profiling_table_quality_policy

token = 's4mp13_4u7h_70k3n'

dqops_client = client.AuthenticatedClient(
    'http://localhost:8888/',
    token=token,
    raise_on_unexpected_status=True
)

call_result = get_profiling_table_quality_policy.sync(
    'default',
    client=dqops_client
)

Expand to see the returned result

CheckContainerModel(
    categories=[
        QualityCategoryModel(
            category='sample_category',
            help_text='Sample help text',
            checks=[
                CheckModel(
                    check_name='sample_check',
                    help_text='Sample help text',
                    sensor_parameters=[

                    ],
                    sensor_name='sample_target/sample_category/table/volume/row_count',
                    quality_dimension='sample_quality_dimension',
                    supports_error_sampling=False,
                    supports_grouping=False,
                    standard=False,
                    default_check=False,
                    default_severity=DefaultRuleSeverityLevel.ERROR,
                    disabled=False,
                    exclude_from_kpi=False,
                    include_in_sla=False,
                    configured=False,
                    always_collect_error_samples=False,
                    do_not_schedule=False,
                    can_edit=False,
                    can_run_checks=False,
                    can_delete_data=False
                )
            ]
        )
    ],
    can_edit=False,
    can_run_checks=False,
    can_delete_data=False
)

Execution

from dqops import client
from dqops.client.api.table_quality_policies import get_profiling_table_quality_policy

token = 's4mp13_4u7h_70k3n'

dqops_client = client.AuthenticatedClient(
    'http://localhost:8888/',
    token=token,
    raise_on_unexpected_status=True
)

call_result = await get_profiling_table_quality_policy.asyncio(
    'default',
    client=dqops_client
)

Expand to see the returned result

CheckContainerModel(
    categories=[
        QualityCategoryModel(
            category='sample_category',
            help_text='Sample help text',
            checks=[
                CheckModel(
                    check_name='sample_check',
                    help_text='Sample help text',
                    sensor_parameters=[

                    ],
                    sensor_name='sample_target/sample_category/table/volume/row_count',
                    quality_dimension='sample_quality_dimension',
                    supports_error_sampling=False,
                    supports_grouping=False,
                    standard=False,
                    default_check=False,
                    default_severity=DefaultRuleSeverityLevel.ERROR,
                    disabled=False,
                    exclude_from_kpi=False,
                    include_in_sla=False,
                    configured=False,
                    always_collect_error_samples=False,
                    do_not_schedule=False,
                    can_edit=False,
                    can_run_checks=False,
                    can_delete_data=False
                )
            ]
        )
    ],
    can_edit=False,
    can_run_checks=False,
    can_delete_data=False
)

---

get_table_quality_policies

Returns a flat list of all table-level default check patterns (data quality policies) configured for this instance. Default checks are applied on tables dynamically.

Follow the link to see the source code on GitHub.

GET

http://localhost:8888/api/policies/checks/table

Return value

Property name	Description	Data type
table_quality_policy_list_model		List[TableQualityPolicyListModel]

Usage examples

curlPython sync clientPython async clientPython auth sync clientPython auth async client

Execution

curl http://localhost:8888/api/policies/checks/table^
    -H "Accept: application/json"

Expand to see the returned result

[ {
  "policy_name" : "default",
  "priority" : 100,
  "disabled" : false,
  "target_table" : {
    "connection" : "dwh",
    "schema" : "public",
    "table" : "fact_*"
  },
  "can_edit" : true
}, {
  "policy_name" : "default",
  "priority" : 100,
  "disabled" : false,
  "target_table" : {
    "connection" : "dwh",
    "schema" : "public",
    "table" : "fact_*"
  },
  "can_edit" : true
}, {
  "policy_name" : "default",
  "priority" : 100,
  "disabled" : false,
  "target_table" : {
    "connection" : "dwh",
    "schema" : "public",
    "table" : "fact_*"
  },
  "can_edit" : true
} ]

Execution

from dqops import client
from dqops.client.api.table_quality_policies import get_table_quality_policies

dqops_client = client.Client(
    'http://localhost:8888/',
    raise_on_unexpected_status=True
)

call_result = get_table_quality_policies.sync(
    client=dqops_client
)

Expand to see the returned result

[
    TableQualityPolicyListModel(
        policy_name='default',
        priority=100,
        disabled=False,
        target_table=TargetTablePatternSpec(
            connection='dwh',
            schema='public',
            table='fact_*'
        ),
        can_edit=True
    ),
    TableQualityPolicyListModel(
        policy_name='default',
        priority=100,
        disabled=False,
        target_table=TargetTablePatternSpec(
            connection='dwh',
            schema='public',
            table='fact_*'
        ),
        can_edit=True
    ),
    TableQualityPolicyListModel(
        policy_name='default',
        priority=100,
        disabled=False,
        target_table=TargetTablePatternSpec(
            connection='dwh',
            schema='public',
            table='fact_*'
        ),
        can_edit=True
    )
]

Execution

from dqops import client
from dqops.client.api.table_quality_policies import get_table_quality_policies

dqops_client = client.Client(
    'http://localhost:8888/',
    raise_on_unexpected_status=True
)

call_result = await get_table_quality_policies.asyncio(
    client=dqops_client
)

Expand to see the returned result

[
    TableQualityPolicyListModel(
        policy_name='default',
        priority=100,
        disabled=False,
        target_table=TargetTablePatternSpec(
            connection='dwh',
            schema='public',
            table='fact_*'
        ),
        can_edit=True
    ),
    TableQualityPolicyListModel(
        policy_name='default',
        priority=100,
        disabled=False,
        target_table=TargetTablePatternSpec(
            connection='dwh',
            schema='public',
            table='fact_*'
        ),
        can_edit=True
    ),
    TableQualityPolicyListModel(
        policy_name='default',
        priority=100,
        disabled=False,
        target_table=TargetTablePatternSpec(
            connection='dwh',
            schema='public',
            table='fact_*'
        ),
        can_edit=True
    )
]

Execution

from dqops import client
from dqops.client.api.table_quality_policies import get_table_quality_policies

token = 's4mp13_4u7h_70k3n'

dqops_client = client.AuthenticatedClient(
    'http://localhost:8888/',
    token=token,
    raise_on_unexpected_status=True
)

call_result = get_table_quality_policies.sync(
    client=dqops_client
)

Expand to see the returned result

[
    TableQualityPolicyListModel(
        policy_name='default',
        priority=100,
        disabled=False,
        target_table=TargetTablePatternSpec(
            connection='dwh',
            schema='public',
            table='fact_*'
        ),
        can_edit=True
    ),
    TableQualityPolicyListModel(
        policy_name='default',
        priority=100,
        disabled=False,
        target_table=TargetTablePatternSpec(
            connection='dwh',
            schema='public',
            table='fact_*'
        ),
        can_edit=True
    ),
    TableQualityPolicyListModel(
        policy_name='default',
        priority=100,
        disabled=False,
        target_table=TargetTablePatternSpec(
            connection='dwh',
            schema='public',
            table='fact_*'
        ),
        can_edit=True
    )
]

Execution

from dqops import client
from dqops.client.api.table_quality_policies import get_table_quality_policies

token = 's4mp13_4u7h_70k3n'

dqops_client = client.AuthenticatedClient(
    'http://localhost:8888/',
    token=token,
    raise_on_unexpected_status=True
)

call_result = await get_table_quality_policies.asyncio(
    client=dqops_client
)

Expand to see the returned result

[
    TableQualityPolicyListModel(
        policy_name='default',
        priority=100,
        disabled=False,
        target_table=TargetTablePatternSpec(
            connection='dwh',
            schema='public',
            table='fact_*'
        ),
        can_edit=True
    ),
    TableQualityPolicyListModel(
        policy_name='default',
        priority=100,
        disabled=False,
        target_table=TargetTablePatternSpec(
            connection='dwh',
            schema='public',
            table='fact_*'
        ),
        can_edit=True
    ),
    TableQualityPolicyListModel(
        policy_name='default',
        priority=100,
        disabled=False,
        target_table=TargetTablePatternSpec(
            connection='dwh',
            schema='public',
            table='fact_*'
        ),
        can_edit=True
    )
]

---

get_table_quality_policy

Returns a default table-level checks pattern (data quality policy) definition as a full specification object

Follow the link to see the source code on GitHub.

GET

http://localhost:8888/api/policies/checks/table/{patternName}

Return value

Property name	Description	Data type
table_quality_policy_model		TableQualityPolicyModel

Parameters of this method are described below

Property name	Description	Data type	Required
pattern_name	Table pattern name	string

Usage examples

curlPython sync clientPython async clientPython auth sync clientPython auth async client

Execution

curl http://localhost:8888/api/policies/checks/table/default^
    -H "Accept: application/json"

Expand to see the returned result

{
  "policy_name" : "default",
  "policy_spec" : {
    "priority" : 1000,
    "monitoring_checks" : {
      "daily" : {
        "volume" : {
          "daily_row_count" : {
            "warning" : {
              "min_count" : 1
            }
          }
        }
      }
    }
  },
  "can_edit" : true
}

Execution

from dqops import client
from dqops.client.api.table_quality_policies import get_table_quality_policy

dqops_client = client.Client(
    'http://localhost:8888/',
    raise_on_unexpected_status=True
)

call_result = get_table_quality_policy.sync(
    'default',
    client=dqops_client
)

Expand to see the returned result

TableQualityPolicyModel(
    policy_name='default',
    policy_spec=TableQualityPolicySpec(
        priority=1000,
        disabled=False,
        target=TargetTablePatternSpec(),
        profiling_checks=TableProfilingCheckCategoriesSpec(comparisons=TableComparisonProfilingChecksSpecMap()),
        monitoring_checks=TableMonitoringCheckCategoriesSpec(
            daily=TableDailyMonitoringCheckCategoriesSpec(
                volume=TableVolumeDailyMonitoringChecksSpec(
                    daily_row_count=TableRowCountCheckSpec(
                        parameters=TableVolumeRowCountSensorParametersSpec(),
                        warning=MinCountRule1ParametersSpec(min_count=1),
                        disabled=False,
                        exclude_from_kpi=False,
                        include_in_sla=False,
                        always_collect_error_samples=False,
                        do_not_schedule=False
                    )
                ),
                comparisons=TableComparisonDailyMonitoringChecksSpecMap()
            )
        ),
        partitioned_checks=TablePartitionedCheckCategoriesSpec()
    ),
    can_edit=True
)

Execution

from dqops import client
from dqops.client.api.table_quality_policies import get_table_quality_policy

dqops_client = client.Client(
    'http://localhost:8888/',
    raise_on_unexpected_status=True
)

call_result = await get_table_quality_policy.asyncio(
    'default',
    client=dqops_client
)

Expand to see the returned result

TableQualityPolicyModel(
    policy_name='default',
    policy_spec=TableQualityPolicySpec(
        priority=1000,
        disabled=False,
        target=TargetTablePatternSpec(),
        profiling_checks=TableProfilingCheckCategoriesSpec(comparisons=TableComparisonProfilingChecksSpecMap()),
        monitoring_checks=TableMonitoringCheckCategoriesSpec(
            daily=TableDailyMonitoringCheckCategoriesSpec(
                volume=TableVolumeDailyMonitoringChecksSpec(
                    daily_row_count=TableRowCountCheckSpec(
                        parameters=TableVolumeRowCountSensorParametersSpec(),
                        warning=MinCountRule1ParametersSpec(min_count=1),
                        disabled=False,
                        exclude_from_kpi=False,
                        include_in_sla=False,
                        always_collect_error_samples=False,
                        do_not_schedule=False
                    )
                ),
                comparisons=TableComparisonDailyMonitoringChecksSpecMap()
            )
        ),
        partitioned_checks=TablePartitionedCheckCategoriesSpec()
    ),
    can_edit=True
)

Execution

from dqops import client
from dqops.client.api.table_quality_policies import get_table_quality_policy

token = 's4mp13_4u7h_70k3n'

dqops_client = client.AuthenticatedClient(
    'http://localhost:8888/',
    token=token,
    raise_on_unexpected_status=True
)

call_result = get_table_quality_policy.sync(
    'default',
    client=dqops_client
)

Expand to see the returned result

TableQualityPolicyModel(
    policy_name='default',
    policy_spec=TableQualityPolicySpec(
        priority=1000,
        disabled=False,
        target=TargetTablePatternSpec(),
        profiling_checks=TableProfilingCheckCategoriesSpec(comparisons=TableComparisonProfilingChecksSpecMap()),
        monitoring_checks=TableMonitoringCheckCategoriesSpec(
            daily=TableDailyMonitoringCheckCategoriesSpec(
                volume=TableVolumeDailyMonitoringChecksSpec(
                    daily_row_count=TableRowCountCheckSpec(
                        parameters=TableVolumeRowCountSensorParametersSpec(),
                        warning=MinCountRule1ParametersSpec(min_count=1),
                        disabled=False,
                        exclude_from_kpi=False,
                        include_in_sla=False,
                        always_collect_error_samples=False,
                        do_not_schedule=False
                    )
                ),
                comparisons=TableComparisonDailyMonitoringChecksSpecMap()
            )
        ),
        partitioned_checks=TablePartitionedCheckCategoriesSpec()
    ),
    can_edit=True
)

Execution

from dqops import client
from dqops.client.api.table_quality_policies import get_table_quality_policy

token = 's4mp13_4u7h_70k3n'

dqops_client = client.AuthenticatedClient(
    'http://localhost:8888/',
    token=token,
    raise_on_unexpected_status=True
)

call_result = await get_table_quality_policy.asyncio(
    'default',
    client=dqops_client
)

Expand to see the returned result

TableQualityPolicyModel(
    policy_name='default',
    policy_spec=TableQualityPolicySpec(
        priority=1000,
        disabled=False,
        target=TargetTablePatternSpec(),
        profiling_checks=TableProfilingCheckCategoriesSpec(comparisons=TableComparisonProfilingChecksSpecMap()),
        monitoring_checks=TableMonitoringCheckCategoriesSpec(
            daily=TableDailyMonitoringCheckCategoriesSpec(
                volume=TableVolumeDailyMonitoringChecksSpec(
                    daily_row_count=TableRowCountCheckSpec(
                        parameters=TableVolumeRowCountSensorParametersSpec(),
                        warning=MinCountRule1ParametersSpec(min_count=1),
                        disabled=False,
                        exclude_from_kpi=False,
                        include_in_sla=False,
                        always_collect_error_samples=False,
                        do_not_schedule=False
                    )
                ),
                comparisons=TableComparisonDailyMonitoringChecksSpecMap()
            )
        ),
        partitioned_checks=TablePartitionedCheckCategoriesSpec()
    ),
    can_edit=True
)

---

get_table_quality_policy_target

Returns a default checks pattern definition (a data quality policy)

Follow the link to see the source code on GitHub.

GET

http://localhost:8888/api/policies/checks/table/{patternName}/target

Return value

Property name	Description	Data type
table_quality_policy_list_model		TableQualityPolicyListModel

Parameters of this method are described below

Property name	Description	Data type	Required
pattern_name	Table pattern name	string

Usage examples

curlPython sync clientPython async clientPython auth sync clientPython auth async client

Execution

curl http://localhost:8888/api/policies/checks/table/default/target^
    -H "Accept: application/json"

Expand to see the returned result

{
  "policy_name" : "default",
  "priority" : 100,
  "disabled" : false,
  "target_table" : {
    "connection" : "dwh",
    "schema" : "public",
    "table" : "fact_*"
  },
  "can_edit" : true
}

Execution

from dqops import client
from dqops.client.api.table_quality_policies import get_table_quality_policy_target

dqops_client = client.Client(
    'http://localhost:8888/',
    raise_on_unexpected_status=True
)

call_result = get_table_quality_policy_target.sync(
    'default',
    client=dqops_client
)

Expand to see the returned result

TableQualityPolicyListModel(
    policy_name='default',
    priority=100,
    disabled=False,
    target_table=TargetTablePatternSpec(
        connection='dwh',
        schema='public',
        table='fact_*'
    ),
    can_edit=True
)

Execution

from dqops import client
from dqops.client.api.table_quality_policies import get_table_quality_policy_target

dqops_client = client.Client(
    'http://localhost:8888/',
    raise_on_unexpected_status=True
)

call_result = await get_table_quality_policy_target.asyncio(
    'default',
    client=dqops_client
)

Expand to see the returned result

TableQualityPolicyListModel(
    policy_name='default',
    priority=100,
    disabled=False,
    target_table=TargetTablePatternSpec(
        connection='dwh',
        schema='public',
        table='fact_*'
    ),
    can_edit=True
)

Execution

from dqops import client
from dqops.client.api.table_quality_policies import get_table_quality_policy_target

token = 's4mp13_4u7h_70k3n'

dqops_client = client.AuthenticatedClient(
    'http://localhost:8888/',
    token=token,
    raise_on_unexpected_status=True
)

call_result = get_table_quality_policy_target.sync(
    'default',
    client=dqops_client
)

Expand to see the returned result

TableQualityPolicyListModel(
    policy_name='default',
    priority=100,
    disabled=False,
    target_table=TargetTablePatternSpec(
        connection='dwh',
        schema='public',
        table='fact_*'
    ),
    can_edit=True
)

Execution

from dqops import client
from dqops.client.api.table_quality_policies import get_table_quality_policy_target

token = 's4mp13_4u7h_70k3n'

dqops_client = client.AuthenticatedClient(
    'http://localhost:8888/',
    token=token,
    raise_on_unexpected_status=True
)

call_result = await get_table_quality_policy_target.asyncio(
    'default',
    client=dqops_client
)

Expand to see the returned result

TableQualityPolicyListModel(
    policy_name='default',
    priority=100,
    disabled=False,
    target_table=TargetTablePatternSpec(
        connection='dwh',
        schema='public',
        table='fact_*'
    ),
    can_edit=True
)

---

update_monitoring_daily_table_quality_policy

New configuration of the default daily monitoring checks on a table level. These checks will be applied to tables.

Follow the link to see the source code on GitHub.

PUT

http://localhost:8888/api/policies/checks/table/{patternName}/monitoring/daily

Parameters of this method are described below

Property name	Description	Data type	Required
pattern_name	Pattern name	string

Request body

Description	Data type	Required
Model with the changes to be applied to the data quality daily monitoring checks configuration	CheckContainerModel

Usage examples

curlPython sync clientPython async clientPython auth sync clientPython auth async client

Execution

curl -X PUT http://localhost:8888/api/policies/checks/table/default/monitoring/daily^
    -H "Accept: application/json"^
    -H "Content-Type: application/json"^
    -d^
    "{\"categories\":[{\"category\":\"sample_category\",\"help_text\":\"Sample help text\",\"checks\":[{\"check_name\":\"sample_check\",\"help_text\":\"Sample help text\",\"sensor_parameters\":[],\"sensor_name\":\"sample_target/sample_category/table/volume/row_count\",\"quality_dimension\":\"sample_quality_dimension\",\"supports_error_sampling\":false,\"supports_grouping\":false,\"default_severity\":\"error\",\"disabled\":false,\"exclude_from_kpi\":false,\"include_in_sla\":false,\"configured\":false,\"can_edit\":false,\"can_run_checks\":false,\"can_delete_data\":false}]}],\"can_edit\":false,\"can_run_checks\":false,\"can_delete_data\":false}"

Execution

from dqops import client
from dqops.client.api.table_quality_policies import update_monitoring_daily_table_quality_policy
from dqops.client.models import CheckContainerModel, \
                                CheckModel, \
                                DefaultRuleSeverityLevel, \
                                FieldModel, \
                                QualityCategoryModel

dqops_client = client.Client(
    'http://localhost:8888/'
)

request_body = CheckContainerModel(
    categories=[
        QualityCategoryModel(
            category='sample_category',
            help_text='Sample help text',
            checks=[
                CheckModel(
                    check_name='sample_check',
                    help_text='Sample help text',
                    sensor_parameters=[

                    ],
                    sensor_name='sample_target/sample_category/table/volume/row_count',
                    quality_dimension='sample_quality_dimension',
                    supports_error_sampling=False,
                    supports_grouping=False,
                    standard=False,
                    default_check=False,
                    default_severity=DefaultRuleSeverityLevel.ERROR,
                    disabled=False,
                    exclude_from_kpi=False,
                    include_in_sla=False,
                    configured=False,
                    always_collect_error_samples=False,
                    do_not_schedule=False,
                    can_edit=False,
                    can_run_checks=False,
                    can_delete_data=False
                )
            ]
        )
    ],
    can_edit=False,
    can_run_checks=False,
    can_delete_data=False
)

call_result = update_monitoring_daily_table_quality_policy.sync(
    'default',
    client=dqops_client,
    json_body=request_body
)

Execution

from dqops import client
from dqops.client.api.table_quality_policies import update_monitoring_daily_table_quality_policy
from dqops.client.models import CheckContainerModel, \
                                CheckModel, \
                                DefaultRuleSeverityLevel, \
                                FieldModel, \
                                QualityCategoryModel

dqops_client = client.Client(
    'http://localhost:8888/'
)

request_body = CheckContainerModel(
    categories=[
        QualityCategoryModel(
            category='sample_category',
            help_text='Sample help text',
            checks=[
                CheckModel(
                    check_name='sample_check',
                    help_text='Sample help text',
                    sensor_parameters=[

                    ],
                    sensor_name='sample_target/sample_category/table/volume/row_count',
                    quality_dimension='sample_quality_dimension',
                    supports_error_sampling=False,
                    supports_grouping=False,
                    standard=False,
                    default_check=False,
                    default_severity=DefaultRuleSeverityLevel.ERROR,
                    disabled=False,
                    exclude_from_kpi=False,
                    include_in_sla=False,
                    configured=False,
                    always_collect_error_samples=False,
                    do_not_schedule=False,
                    can_edit=False,
                    can_run_checks=False,
                    can_delete_data=False
                )
            ]
        )
    ],
    can_edit=False,
    can_run_checks=False,
    can_delete_data=False
)

call_result = await update_monitoring_daily_table_quality_policy.asyncio(
    'default',
    client=dqops_client,
    json_body=request_body
)

Execution

from dqops import client
from dqops.client.api.table_quality_policies import update_monitoring_daily_table_quality_policy
from dqops.client.models import CheckContainerModel, \
                                CheckModel, \
                                DefaultRuleSeverityLevel, \
                                FieldModel, \
                                QualityCategoryModel

token = 's4mp13_4u7h_70k3n'

dqops_client = client.AuthenticatedClient(
    'http://localhost:8888/',
    token=token
)

request_body = CheckContainerModel(
    categories=[
        QualityCategoryModel(
            category='sample_category',
            help_text='Sample help text',
            checks=[
                CheckModel(
                    check_name='sample_check',
                    help_text='Sample help text',
                    sensor_parameters=[

                    ],
                    sensor_name='sample_target/sample_category/table/volume/row_count',
                    quality_dimension='sample_quality_dimension',
                    supports_error_sampling=False,
                    supports_grouping=False,
                    standard=False,
                    default_check=False,
                    default_severity=DefaultRuleSeverityLevel.ERROR,
                    disabled=False,
                    exclude_from_kpi=False,
                    include_in_sla=False,
                    configured=False,
                    always_collect_error_samples=False,
                    do_not_schedule=False,
                    can_edit=False,
                    can_run_checks=False,
                    can_delete_data=False
                )
            ]
        )
    ],
    can_edit=False,
    can_run_checks=False,
    can_delete_data=False
)

call_result = update_monitoring_daily_table_quality_policy.sync(
    'default',
    client=dqops_client,
    json_body=request_body
)

Execution

from dqops import client
from dqops.client.api.table_quality_policies import update_monitoring_daily_table_quality_policy
from dqops.client.models import CheckContainerModel, \
                                CheckModel, \
                                DefaultRuleSeverityLevel, \
                                FieldModel, \
                                QualityCategoryModel

token = 's4mp13_4u7h_70k3n'

dqops_client = client.AuthenticatedClient(
    'http://localhost:8888/',
    token=token
)

request_body = CheckContainerModel(
    categories=[
        QualityCategoryModel(
            category='sample_category',
            help_text='Sample help text',
            checks=[
                CheckModel(
                    check_name='sample_check',
                    help_text='Sample help text',
                    sensor_parameters=[

                    ],
                    sensor_name='sample_target/sample_category/table/volume/row_count',
                    quality_dimension='sample_quality_dimension',
                    supports_error_sampling=False,
                    supports_grouping=False,
                    standard=False,
                    default_check=False,
                    default_severity=DefaultRuleSeverityLevel.ERROR,
                    disabled=False,
                    exclude_from_kpi=False,
                    include_in_sla=False,
                    configured=False,
                    always_collect_error_samples=False,
                    do_not_schedule=False,
                    can_edit=False,
                    can_run_checks=False,
                    can_delete_data=False
                )
            ]
        )
    ],
    can_edit=False,
    can_run_checks=False,
    can_delete_data=False
)

call_result = await update_monitoring_daily_table_quality_policy.asyncio(
    'default',
    client=dqops_client,
    json_body=request_body
)

---

update_monitoring_monthly_table_quality_policy

New configuration of the default monthly monitoring checks on a table level. These checks will be applied to tables.

Follow the link to see the source code on GitHub.

PUT

http://localhost:8888/api/policies/checks/table/{patternName}/monitoring/monthly

Parameters of this method are described below

Property name	Description	Data type	Required
pattern_name	Pattern name	string

Request body

Description	Data type	Required
Model with the changes to be applied to the data quality monthly monitoring checks configuration	CheckContainerModel

Usage examples

curlPython sync clientPython async clientPython auth sync clientPython auth async client

Execution

curl -X PUT http://localhost:8888/api/policies/checks/table/default/monitoring/monthly^
    -H "Accept: application/json"^
    -H "Content-Type: application/json"^
    -d^
    "{\"categories\":[{\"category\":\"sample_category\",\"help_text\":\"Sample help text\",\"checks\":[{\"check_name\":\"sample_check\",\"help_text\":\"Sample help text\",\"sensor_parameters\":[],\"sensor_name\":\"sample_target/sample_category/table/volume/row_count\",\"quality_dimension\":\"sample_quality_dimension\",\"supports_error_sampling\":false,\"supports_grouping\":false,\"default_severity\":\"error\",\"disabled\":false,\"exclude_from_kpi\":false,\"include_in_sla\":false,\"configured\":false,\"can_edit\":false,\"can_run_checks\":false,\"can_delete_data\":false}]}],\"can_edit\":false,\"can_run_checks\":false,\"can_delete_data\":false}"

Execution

from dqops import client
from dqops.client.api.table_quality_policies import update_monitoring_monthly_table_quality_policy
from dqops.client.models import CheckContainerModel, \
                                CheckModel, \
                                DefaultRuleSeverityLevel, \
                                FieldModel, \
                                QualityCategoryModel

dqops_client = client.Client(
    'http://localhost:8888/'
)

request_body = CheckContainerModel(
    categories=[
        QualityCategoryModel(
            category='sample_category',
            help_text='Sample help text',
            checks=[
                CheckModel(
                    check_name='sample_check',
                    help_text='Sample help text',
                    sensor_parameters=[

                    ],
                    sensor_name='sample_target/sample_category/table/volume/row_count',
                    quality_dimension='sample_quality_dimension',
                    supports_error_sampling=False,
                    supports_grouping=False,
                    standard=False,
                    default_check=False,
                    default_severity=DefaultRuleSeverityLevel.ERROR,
                    disabled=False,
                    exclude_from_kpi=False,
                    include_in_sla=False,
                    configured=False,
                    always_collect_error_samples=False,
                    do_not_schedule=False,
                    can_edit=False,
                    can_run_checks=False,
                    can_delete_data=False
                )
            ]
        )
    ],
    can_edit=False,
    can_run_checks=False,
    can_delete_data=False
)

call_result = update_monitoring_monthly_table_quality_policy.sync(
    'default',
    client=dqops_client,
    json_body=request_body
)

Execution

from dqops import client
from dqops.client.api.table_quality_policies import update_monitoring_monthly_table_quality_policy
from dqops.client.models import CheckContainerModel, \
                                CheckModel, \
                                DefaultRuleSeverityLevel, \
                                FieldModel, \
                                QualityCategoryModel

dqops_client = client.Client(
    'http://localhost:8888/'
)

request_body = CheckContainerModel(
    categories=[
        QualityCategoryModel(
            category='sample_category',
            help_text='Sample help text',
            checks=[
                CheckModel(
                    check_name='sample_check',
                    help_text='Sample help text',
                    sensor_parameters=[

                    ],
                    sensor_name='sample_target/sample_category/table/volume/row_count',
                    quality_dimension='sample_quality_dimension',
                    supports_error_sampling=False,
                    supports_grouping=False,
                    standard=False,
                    default_check=False,
                    default_severity=DefaultRuleSeverityLevel.ERROR,
                    disabled=False,
                    exclude_from_kpi=False,
                    include_in_sla=False,
                    configured=False,
                    always_collect_error_samples=False,
                    do_not_schedule=False,
                    can_edit=False,
                    can_run_checks=False,
                    can_delete_data=False
                )
            ]
        )
    ],
    can_edit=False,
    can_run_checks=False,
    can_delete_data=False
)

call_result = await update_monitoring_monthly_table_quality_policy.asyncio(
    'default',
    client=dqops_client,
    json_body=request_body
)

Execution

from dqops import client
from dqops.client.api.table_quality_policies import update_monitoring_monthly_table_quality_policy
from dqops.client.models import CheckContainerModel, \
                                CheckModel, \
                                DefaultRuleSeverityLevel, \
                                FieldModel, \
                                QualityCategoryModel

token = 's4mp13_4u7h_70k3n'

dqops_client = client.AuthenticatedClient(
    'http://localhost:8888/',
    token=token
)

request_body = CheckContainerModel(
    categories=[
        QualityCategoryModel(
            category='sample_category',
            help_text='Sample help text',
            checks=[
                CheckModel(
                    check_name='sample_check',
                    help_text='Sample help text',
                    sensor_parameters=[

                    ],
                    sensor_name='sample_target/sample_category/table/volume/row_count',
                    quality_dimension='sample_quality_dimension',
                    supports_error_sampling=False,
                    supports_grouping=False,
                    standard=False,
                    default_check=False,
                    default_severity=DefaultRuleSeverityLevel.ERROR,
                    disabled=False,
                    exclude_from_kpi=False,
                    include_in_sla=False,
                    configured=False,
                    always_collect_error_samples=False,
                    do_not_schedule=False,
                    can_edit=False,
                    can_run_checks=False,
                    can_delete_data=False
                )
            ]
        )
    ],
    can_edit=False,
    can_run_checks=False,
    can_delete_data=False
)

call_result = update_monitoring_monthly_table_quality_policy.sync(
    'default',
    client=dqops_client,
    json_body=request_body
)

Execution

from dqops import client
from dqops.client.api.table_quality_policies import update_monitoring_monthly_table_quality_policy
from dqops.client.models import CheckContainerModel, \
                                CheckModel, \
                                DefaultRuleSeverityLevel, \
                                FieldModel, \
                                QualityCategoryModel

token = 's4mp13_4u7h_70k3n'

dqops_client = client.AuthenticatedClient(
    'http://localhost:8888/',
    token=token
)

request_body = CheckContainerModel(
    categories=[
        QualityCategoryModel(
            category='sample_category',
            help_text='Sample help text',
            checks=[
                CheckModel(
                    check_name='sample_check',
                    help_text='Sample help text',
                    sensor_parameters=[

                    ],
                    sensor_name='sample_target/sample_category/table/volume/row_count',
                    quality_dimension='sample_quality_dimension',
                    supports_error_sampling=False,
                    supports_grouping=False,
                    standard=False,
                    default_check=False,
                    default_severity=DefaultRuleSeverityLevel.ERROR,
                    disabled=False,
                    exclude_from_kpi=False,
                    include_in_sla=False,
                    configured=False,
                    always_collect_error_samples=False,
                    do_not_schedule=False,
                    can_edit=False,
                    can_run_checks=False,
                    can_delete_data=False
                )
            ]
        )
    ],
    can_edit=False,
    can_run_checks=False,
    can_delete_data=False
)

call_result = await update_monitoring_monthly_table_quality_policy.asyncio(
    'default',
    client=dqops_client,
    json_body=request_body
)

---

update_partitioned_daily_table_quality_policy

New configuration of the default daily partitioned checks on a table level. These checks will be applied to tables.

Follow the link to see the source code on GitHub.

PUT

http://localhost:8888/api/policies/checks/table/{patternName}/partitioned/daily

Parameters of this method are described below

Property name	Description	Data type	Required
pattern_name	Pattern name	string

Request body

Description	Data type	Required
Model with the changes to be applied to the data quality daily partitioned checks configuration	CheckContainerModel

Usage examples

curlPython sync clientPython async clientPython auth sync clientPython auth async client

Execution

curl -X PUT http://localhost:8888/api/policies/checks/table/default/partitioned/daily^
    -H "Accept: application/json"^
    -H "Content-Type: application/json"^
    -d^
    "{\"categories\":[{\"category\":\"sample_category\",\"help_text\":\"Sample help text\",\"checks\":[{\"check_name\":\"sample_check\",\"help_text\":\"Sample help text\",\"sensor_parameters\":[],\"sensor_name\":\"sample_target/sample_category/table/volume/row_count\",\"quality_dimension\":\"sample_quality_dimension\",\"supports_error_sampling\":false,\"supports_grouping\":false,\"default_severity\":\"error\",\"disabled\":false,\"exclude_from_kpi\":false,\"include_in_sla\":false,\"configured\":false,\"can_edit\":false,\"can_run_checks\":false,\"can_delete_data\":false}]}],\"can_edit\":false,\"can_run_checks\":false,\"can_delete_data\":false}"

Execution

from dqops import client
from dqops.client.api.table_quality_policies import update_partitioned_daily_table_quality_policy
from dqops.client.models import CheckContainerModel, \
                                CheckModel, \
                                DefaultRuleSeverityLevel, \
                                FieldModel, \
                                QualityCategoryModel

dqops_client = client.Client(
    'http://localhost:8888/'
)

request_body = CheckContainerModel(
    categories=[
        QualityCategoryModel(
            category='sample_category',
            help_text='Sample help text',
            checks=[
                CheckModel(
                    check_name='sample_check',
                    help_text='Sample help text',
                    sensor_parameters=[

                    ],
                    sensor_name='sample_target/sample_category/table/volume/row_count',
                    quality_dimension='sample_quality_dimension',
                    supports_error_sampling=False,
                    supports_grouping=False,
                    standard=False,
                    default_check=False,
                    default_severity=DefaultRuleSeverityLevel.ERROR,
                    disabled=False,
                    exclude_from_kpi=False,
                    include_in_sla=False,
                    configured=False,
                    always_collect_error_samples=False,
                    do_not_schedule=False,
                    can_edit=False,
                    can_run_checks=False,
                    can_delete_data=False
                )
            ]
        )
    ],
    can_edit=False,
    can_run_checks=False,
    can_delete_data=False
)

call_result = update_partitioned_daily_table_quality_policy.sync(
    'default',
    client=dqops_client,
    json_body=request_body
)

Execution

from dqops import client
from dqops.client.api.table_quality_policies import update_partitioned_daily_table_quality_policy
from dqops.client.models import CheckContainerModel, \
                                CheckModel, \
                                DefaultRuleSeverityLevel, \
                                FieldModel, \
                                QualityCategoryModel

dqops_client = client.Client(
    'http://localhost:8888/'
)

request_body = CheckContainerModel(
    categories=[
        QualityCategoryModel(
            category='sample_category',
            help_text='Sample help text',
            checks=[
                CheckModel(
                    check_name='sample_check',
                    help_text='Sample help text',
                    sensor_parameters=[

                    ],
                    sensor_name='sample_target/sample_category/table/volume/row_count',
                    quality_dimension='sample_quality_dimension',
                    supports_error_sampling=False,
                    supports_grouping=False,
                    standard=False,
                    default_check=False,
                    default_severity=DefaultRuleSeverityLevel.ERROR,
                    disabled=False,
                    exclude_from_kpi=False,
                    include_in_sla=False,
                    configured=False,
                    always_collect_error_samples=False,
                    do_not_schedule=False,
                    can_edit=False,
                    can_run_checks=False,
                    can_delete_data=False
                )
            ]
        )
    ],
    can_edit=False,
    can_run_checks=False,
    can_delete_data=False
)

call_result = await update_partitioned_daily_table_quality_policy.asyncio(
    'default',
    client=dqops_client,
    json_body=request_body
)

Execution

from dqops import client
from dqops.client.api.table_quality_policies import update_partitioned_daily_table_quality_policy
from dqops.client.models import CheckContainerModel, \
                                CheckModel, \
                                DefaultRuleSeverityLevel, \
                                FieldModel, \
                                QualityCategoryModel

token = 's4mp13_4u7h_70k3n'

dqops_client = client.AuthenticatedClient(
    'http://localhost:8888/',
    token=token
)

request_body = CheckContainerModel(
    categories=[
        QualityCategoryModel(
            category='sample_category',
            help_text='Sample help text',
            checks=[
                CheckModel(
                    check_name='sample_check',
                    help_text='Sample help text',
                    sensor_parameters=[

                    ],
                    sensor_name='sample_target/sample_category/table/volume/row_count',
                    quality_dimension='sample_quality_dimension',
                    supports_error_sampling=False,
                    supports_grouping=False,
                    standard=False,
                    default_check=False,
                    default_severity=DefaultRuleSeverityLevel.ERROR,
                    disabled=False,
                    exclude_from_kpi=False,
                    include_in_sla=False,
                    configured=False,
                    always_collect_error_samples=False,
                    do_not_schedule=False,
                    can_edit=False,
                    can_run_checks=False,
                    can_delete_data=False
                )
            ]
        )
    ],
    can_edit=False,
    can_run_checks=False,
    can_delete_data=False
)

call_result = update_partitioned_daily_table_quality_policy.sync(
    'default',
    client=dqops_client,
    json_body=request_body
)

Execution

from dqops import client
from dqops.client.api.table_quality_policies import update_partitioned_daily_table_quality_policy
from dqops.client.models import CheckContainerModel, \
                                CheckModel, \
                                DefaultRuleSeverityLevel, \
                                FieldModel, \
                                QualityCategoryModel

token = 's4mp13_4u7h_70k3n'

dqops_client = client.AuthenticatedClient(
    'http://localhost:8888/',
    token=token
)

request_body = CheckContainerModel(
    categories=[
        QualityCategoryModel(
            category='sample_category',
            help_text='Sample help text',
            checks=[
                CheckModel(
                    check_name='sample_check',
                    help_text='Sample help text',
                    sensor_parameters=[

                    ],
                    sensor_name='sample_target/sample_category/table/volume/row_count',
                    quality_dimension='sample_quality_dimension',
                    supports_error_sampling=False,
                    supports_grouping=False,
                    standard=False,
                    default_check=False,
                    default_severity=DefaultRuleSeverityLevel.ERROR,
                    disabled=False,
                    exclude_from_kpi=False,
                    include_in_sla=False,
                    configured=False,
                    always_collect_error_samples=False,
                    do_not_schedule=False,
                    can_edit=False,
                    can_run_checks=False,
                    can_delete_data=False
                )
            ]
        )
    ],
    can_edit=False,
    can_run_checks=False,
    can_delete_data=False
)

call_result = await update_partitioned_daily_table_quality_policy.asyncio(
    'default',
    client=dqops_client,
    json_body=request_body
)

---

update_partitioned_monthly_table_quality_policy

New configuration of the default monthly partitioned checks on a table level. These checks will be applied to tables.

Follow the link to see the source code on GitHub.

PUT

http://localhost:8888/api/policies/checks/table/{patternName}/partitioned/monthly

Parameters of this method are described below

Property name	Description	Data type	Required
pattern_name	Pattern name	string

Request body

Description	Data type	Required
Model with the changes to be applied to the data quality monthly partitioned checks configuration	CheckContainerModel

Usage examples

curlPython sync clientPython async clientPython auth sync clientPython auth async client

Execution

curl -X PUT http://localhost:8888/api/policies/checks/table/default/partitioned/monthly^
    -H "Accept: application/json"^
    -H "Content-Type: application/json"^
    -d^
    "{\"categories\":[{\"category\":\"sample_category\",\"help_text\":\"Sample help text\",\"checks\":[{\"check_name\":\"sample_check\",\"help_text\":\"Sample help text\",\"sensor_parameters\":[],\"sensor_name\":\"sample_target/sample_category/table/volume/row_count\",\"quality_dimension\":\"sample_quality_dimension\",\"supports_error_sampling\":false,\"supports_grouping\":false,\"default_severity\":\"error\",\"disabled\":false,\"exclude_from_kpi\":false,\"include_in_sla\":false,\"configured\":false,\"can_edit\":false,\"can_run_checks\":false,\"can_delete_data\":false}]}],\"can_edit\":false,\"can_run_checks\":false,\"can_delete_data\":false}"

Execution

from dqops import client
from dqops.client.api.table_quality_policies import update_partitioned_monthly_table_quality_policy
from dqops.client.models import CheckContainerModel, \
                                CheckModel, \
                                DefaultRuleSeverityLevel, \
                                FieldModel, \
                                QualityCategoryModel

dqops_client = client.Client(
    'http://localhost:8888/'
)

request_body = CheckContainerModel(
    categories=[
        QualityCategoryModel(
            category='sample_category',
            help_text='Sample help text',
            checks=[
                CheckModel(
                    check_name='sample_check',
                    help_text='Sample help text',
                    sensor_parameters=[

                    ],
                    sensor_name='sample_target/sample_category/table/volume/row_count',
                    quality_dimension='sample_quality_dimension',
                    supports_error_sampling=False,
                    supports_grouping=False,
                    standard=False,
                    default_check=False,
                    default_severity=DefaultRuleSeverityLevel.ERROR,
                    disabled=False,
                    exclude_from_kpi=False,
                    include_in_sla=False,
                    configured=False,
                    always_collect_error_samples=False,
                    do_not_schedule=False,
                    can_edit=False,
                    can_run_checks=False,
                    can_delete_data=False
                )
            ]
        )
    ],
    can_edit=False,
    can_run_checks=False,
    can_delete_data=False
)

call_result = update_partitioned_monthly_table_quality_policy.sync(
    'default',
    client=dqops_client,
    json_body=request_body
)

Execution

from dqops import client
from dqops.client.api.table_quality_policies import update_partitioned_monthly_table_quality_policy
from dqops.client.models import CheckContainerModel, \
                                CheckModel, \
                                DefaultRuleSeverityLevel, \
                                FieldModel, \
                                QualityCategoryModel

dqops_client = client.Client(
    'http://localhost:8888/'
)

request_body = CheckContainerModel(
    categories=[
        QualityCategoryModel(
            category='sample_category',
            help_text='Sample help text',
            checks=[
                CheckModel(
                    check_name='sample_check',
                    help_text='Sample help text',
                    sensor_parameters=[

                    ],
                    sensor_name='sample_target/sample_category/table/volume/row_count',
                    quality_dimension='sample_quality_dimension',
                    supports_error_sampling=False,
                    supports_grouping=False,
                    standard=False,
                    default_check=False,
                    default_severity=DefaultRuleSeverityLevel.ERROR,
                    disabled=False,
                    exclude_from_kpi=False,
                    include_in_sla=False,
                    configured=False,
                    always_collect_error_samples=False,
                    do_not_schedule=False,
                    can_edit=False,
                    can_run_checks=False,
                    can_delete_data=False
                )
            ]
        )
    ],
    can_edit=False,
    can_run_checks=False,
    can_delete_data=False
)

call_result = await update_partitioned_monthly_table_quality_policy.asyncio(
    'default',
    client=dqops_client,
    json_body=request_body
)

Execution

from dqops import client
from dqops.client.api.table_quality_policies import update_partitioned_monthly_table_quality_policy
from dqops.client.models import CheckContainerModel, \
                                CheckModel, \
                                DefaultRuleSeverityLevel, \
                                FieldModel, \
                                QualityCategoryModel

token = 's4mp13_4u7h_70k3n'

dqops_client = client.AuthenticatedClient(
    'http://localhost:8888/',
    token=token
)

request_body = CheckContainerModel(
    categories=[
        QualityCategoryModel(
            category='sample_category',
            help_text='Sample help text',
            checks=[
                CheckModel(
                    check_name='sample_check',
                    help_text='Sample help text',
                    sensor_parameters=[

                    ],
                    sensor_name='sample_target/sample_category/table/volume/row_count',
                    quality_dimension='sample_quality_dimension',
                    supports_error_sampling=False,
                    supports_grouping=False,
                    standard=False,
                    default_check=False,
                    default_severity=DefaultRuleSeverityLevel.ERROR,
                    disabled=False,
                    exclude_from_kpi=False,
                    include_in_sla=False,
                    configured=False,
                    always_collect_error_samples=False,
                    do_not_schedule=False,
                    can_edit=False,
                    can_run_checks=False,
                    can_delete_data=False
                )
            ]
        )
    ],
    can_edit=False,
    can_run_checks=False,
    can_delete_data=False
)

call_result = update_partitioned_monthly_table_quality_policy.sync(
    'default',
    client=dqops_client,
    json_body=request_body
)

Execution

from dqops import client
from dqops.client.api.table_quality_policies import update_partitioned_monthly_table_quality_policy
from dqops.client.models import CheckContainerModel, \
                                CheckModel, \
                                DefaultRuleSeverityLevel, \
                                FieldModel, \
                                QualityCategoryModel

token = 's4mp13_4u7h_70k3n'

dqops_client = client.AuthenticatedClient(
    'http://localhost:8888/',
    token=token
)

request_body = CheckContainerModel(
    categories=[
        QualityCategoryModel(
            category='sample_category',
            help_text='Sample help text',
            checks=[
                CheckModel(
                    check_name='sample_check',
                    help_text='Sample help text',
                    sensor_parameters=[

                    ],
                    sensor_name='sample_target/sample_category/table/volume/row_count',
                    quality_dimension='sample_quality_dimension',
                    supports_error_sampling=False,
                    supports_grouping=False,
                    standard=False,
                    default_check=False,
                    default_severity=DefaultRuleSeverityLevel.ERROR,
                    disabled=False,
                    exclude_from_kpi=False,
                    include_in_sla=False,
                    configured=False,
                    always_collect_error_samples=False,
                    do_not_schedule=False,
                    can_edit=False,
                    can_run_checks=False,
                    can_delete_data=False
                )
            ]
        )
    ],
    can_edit=False,
    can_run_checks=False,
    can_delete_data=False
)

call_result = await update_partitioned_monthly_table_quality_policy.asyncio(
    'default',
    client=dqops_client,
    json_body=request_body
)

---

update_profiling_table_quality_policy

New configuration of the default profiling checks on a table level. These checks will be applied to tables.

Follow the link to see the source code on GitHub.

PUT

http://localhost:8888/api/policies/checks/table/{patternName}/profiling

Parameters of this method are described below

Property name	Description	Data type	Required
pattern_name	Pattern name	string

Request body

Description	Data type	Required
Model with the changes to be applied to the data quality profiling checks configuration	CheckContainerModel

Usage examples

curlPython sync clientPython async clientPython auth sync clientPython auth async client

Execution

curl -X PUT http://localhost:8888/api/policies/checks/table/default/profiling^
    -H "Accept: application/json"^
    -H "Content-Type: application/json"^
    -d^
    "{\"categories\":[{\"category\":\"sample_category\",\"help_text\":\"Sample help text\",\"checks\":[{\"check_name\":\"sample_check\",\"help_text\":\"Sample help text\",\"sensor_parameters\":[],\"sensor_name\":\"sample_target/sample_category/table/volume/row_count\",\"quality_dimension\":\"sample_quality_dimension\",\"supports_error_sampling\":false,\"supports_grouping\":false,\"default_severity\":\"error\",\"disabled\":false,\"exclude_from_kpi\":false,\"include_in_sla\":false,\"configured\":false,\"can_edit\":false,\"can_run_checks\":false,\"can_delete_data\":false}]}],\"can_edit\":false,\"can_run_checks\":false,\"can_delete_data\":false}"

Execution

from dqops import client
from dqops.client.api.table_quality_policies import update_profiling_table_quality_policy
from dqops.client.models import CheckContainerModel, \
                                CheckModel, \
                                DefaultRuleSeverityLevel, \
                                FieldModel, \
                                QualityCategoryModel

dqops_client = client.Client(
    'http://localhost:8888/'
)

request_body = CheckContainerModel(
    categories=[
        QualityCategoryModel(
            category='sample_category',
            help_text='Sample help text',
            checks=[
                CheckModel(
                    check_name='sample_check',
                    help_text='Sample help text',
                    sensor_parameters=[

                    ],
                    sensor_name='sample_target/sample_category/table/volume/row_count',
                    quality_dimension='sample_quality_dimension',
                    supports_error_sampling=False,
                    supports_grouping=False,
                    standard=False,
                    default_check=False,
                    default_severity=DefaultRuleSeverityLevel.ERROR,
                    disabled=False,
                    exclude_from_kpi=False,
                    include_in_sla=False,
                    configured=False,
                    always_collect_error_samples=False,
                    do_not_schedule=False,
                    can_edit=False,
                    can_run_checks=False,
                    can_delete_data=False
                )
            ]
        )
    ],
    can_edit=False,
    can_run_checks=False,
    can_delete_data=False
)

call_result = update_profiling_table_quality_policy.sync(
    'default',
    client=dqops_client,
    json_body=request_body
)

Execution

from dqops import client
from dqops.client.api.table_quality_policies import update_profiling_table_quality_policy
from dqops.client.models import CheckContainerModel, \
                                CheckModel, \
                                DefaultRuleSeverityLevel, \
                                FieldModel, \
                                QualityCategoryModel

dqops_client = client.Client(
    'http://localhost:8888/'
)

request_body = CheckContainerModel(
    categories=[
        QualityCategoryModel(
            category='sample_category',
            help_text='Sample help text',
            checks=[
                CheckModel(
                    check_name='sample_check',
                    help_text='Sample help text',
                    sensor_parameters=[

                    ],
                    sensor_name='sample_target/sample_category/table/volume/row_count',
                    quality_dimension='sample_quality_dimension',
                    supports_error_sampling=False,
                    supports_grouping=False,
                    standard=False,
                    default_check=False,
                    default_severity=DefaultRuleSeverityLevel.ERROR,
                    disabled=False,
                    exclude_from_kpi=False,
                    include_in_sla=False,
                    configured=False,
                    always_collect_error_samples=False,
                    do_not_schedule=False,
                    can_edit=False,
                    can_run_checks=False,
                    can_delete_data=False
                )
            ]
        )
    ],
    can_edit=False,
    can_run_checks=False,
    can_delete_data=False
)

call_result = await update_profiling_table_quality_policy.asyncio(
    'default',
    client=dqops_client,
    json_body=request_body
)

Execution

from dqops import client
from dqops.client.api.table_quality_policies import update_profiling_table_quality_policy
from dqops.client.models import CheckContainerModel, \
                                CheckModel, \
                                DefaultRuleSeverityLevel, \
                                FieldModel, \
                                QualityCategoryModel

token = 's4mp13_4u7h_70k3n'

dqops_client = client.AuthenticatedClient(
    'http://localhost:8888/',
    token=token
)

request_body = CheckContainerModel(
    categories=[
        QualityCategoryModel(
            category='sample_category',
            help_text='Sample help text',
            checks=[
                CheckModel(
                    check_name='sample_check',
                    help_text='Sample help text',
                    sensor_parameters=[

                    ],
                    sensor_name='sample_target/sample_category/table/volume/row_count',
                    quality_dimension='sample_quality_dimension',
                    supports_error_sampling=False,
                    supports_grouping=False,
                    standard=False,
                    default_check=False,
                    default_severity=DefaultRuleSeverityLevel.ERROR,
                    disabled=False,
                    exclude_from_kpi=False,
                    include_in_sla=False,
                    configured=False,
                    always_collect_error_samples=False,
                    do_not_schedule=False,
                    can_edit=False,
                    can_run_checks=False,
                    can_delete_data=False
                )
            ]
        )
    ],
    can_edit=False,
    can_run_checks=False,
    can_delete_data=False
)

call_result = update_profiling_table_quality_policy.sync(
    'default',
    client=dqops_client,
    json_body=request_body
)

Execution

from dqops import client
from dqops.client.api.table_quality_policies import update_profiling_table_quality_policy
from dqops.client.models import CheckContainerModel, \
                                CheckModel, \
                                DefaultRuleSeverityLevel, \
                                FieldModel, \
                                QualityCategoryModel

token = 's4mp13_4u7h_70k3n'

dqops_client = client.AuthenticatedClient(
    'http://localhost:8888/',
    token=token
)

request_body = CheckContainerModel(
    categories=[
        QualityCategoryModel(
            category='sample_category',
            help_text='Sample help text',
            checks=[
                CheckModel(
                    check_name='sample_check',
                    help_text='Sample help text',
                    sensor_parameters=[

                    ],
                    sensor_name='sample_target/sample_category/table/volume/row_count',
                    quality_dimension='sample_quality_dimension',
                    supports_error_sampling=False,
                    supports_grouping=False,
                    standard=False,
                    default_check=False,
                    default_severity=DefaultRuleSeverityLevel.ERROR,
                    disabled=False,
                    exclude_from_kpi=False,
                    include_in_sla=False,
                    configured=False,
                    always_collect_error_samples=False,
                    do_not_schedule=False,
                    can_edit=False,
                    can_run_checks=False,
                    can_delete_data=False
                )
            ]
        )
    ],
    can_edit=False,
    can_run_checks=False,
    can_delete_data=False
)

call_result = await update_profiling_table_quality_policy.asyncio(
    'default',
    client=dqops_client,
    json_body=request_body
)

---

update_table_quality_policy

Updates an default table-level checks pattern (data quality policy) by saving a full specification object

Follow the link to see the source code on GitHub.

PUT

http://localhost:8888/api/policies/checks/table/{patternName}

Parameters of this method are described below

Property name	Description	Data type	Required
pattern_name	Pattern name	string

Request body

Description	Data type	Required
Default checks pattern model	TableQualityPolicyModel

Usage examples

curlPython sync clientPython async clientPython auth sync clientPython auth async client

Execution

curl -X PUT http://localhost:8888/api/policies/checks/table/default^
    -H "Accept: application/json"^
    -H "Content-Type: application/json"^
    -d^
    "{\"policy_name\":\"default\",\"policy_spec\":{\"priority\":1000,\"monitoring_checks\":{\"daily\":{\"volume\":{\"daily_row_count\":{\"warning\":{\"min_count\":1}}}}}},\"can_edit\":true}"

Execution

from dqops import client
from dqops.client.api.table_quality_policies import update_table_quality_policy
from dqops.client.models import MinCountRule1ParametersSpec, \
                                TableMonitoringCheckCategoriesSpec, \
                                TablePartitionedCheckCategoriesSpec, \
                                TableProfilingCheckCategoriesSpec, \
                                TableQualityPolicyModel, \
                                TableQualityPolicySpec, \
                                TableRowCountCheckSpec, \
                                TableVolumeProfilingChecksSpec, \
                                TableVolumeRowCountSensorParametersSpec, \
                                TargetTablePatternSpec

dqops_client = client.Client(
    'http://localhost:8888/'
)

request_body = TableQualityPolicyModel(
    policy_name='default',
    policy_spec=TableQualityPolicySpec(
        priority=1000,
        disabled=False,
        target=TargetTablePatternSpec(),
        profiling_checks=TableProfilingCheckCategoriesSpec(comparisons=TableComparisonProfilingChecksSpecMap()),
        monitoring_checks=TableMonitoringCheckCategoriesSpec(
            daily=TableDailyMonitoringCheckCategoriesSpec(
                volume=TableVolumeDailyMonitoringChecksSpec(
                    daily_row_count=TableRowCountCheckSpec(
                        parameters=TableVolumeRowCountSensorParametersSpec(),
                        warning=MinCountRule1ParametersSpec(min_count=1),
                        disabled=False,
                        exclude_from_kpi=False,
                        include_in_sla=False,
                        always_collect_error_samples=False,
                        do_not_schedule=False
                    )
                ),
                comparisons=TableComparisonDailyMonitoringChecksSpecMap()
            )
        ),
        partitioned_checks=TablePartitionedCheckCategoriesSpec()
    ),
    can_edit=True
)

call_result = update_table_quality_policy.sync(
    'default',
    client=dqops_client,
    json_body=request_body
)

Execution

from dqops import client
from dqops.client.api.table_quality_policies import update_table_quality_policy
from dqops.client.models import MinCountRule1ParametersSpec, \
                                TableMonitoringCheckCategoriesSpec, \
                                TablePartitionedCheckCategoriesSpec, \
                                TableProfilingCheckCategoriesSpec, \
                                TableQualityPolicyModel, \
                                TableQualityPolicySpec, \
                                TableRowCountCheckSpec, \
                                TableVolumeProfilingChecksSpec, \
                                TableVolumeRowCountSensorParametersSpec, \
                                TargetTablePatternSpec

dqops_client = client.Client(
    'http://localhost:8888/'
)

request_body = TableQualityPolicyModel(
    policy_name='default',
    policy_spec=TableQualityPolicySpec(
        priority=1000,
        disabled=False,
        target=TargetTablePatternSpec(),
        profiling_checks=TableProfilingCheckCategoriesSpec(comparisons=TableComparisonProfilingChecksSpecMap()),
        monitoring_checks=TableMonitoringCheckCategoriesSpec(
            daily=TableDailyMonitoringCheckCategoriesSpec(
                volume=TableVolumeDailyMonitoringChecksSpec(
                    daily_row_count=TableRowCountCheckSpec(
                        parameters=TableVolumeRowCountSensorParametersSpec(),
                        warning=MinCountRule1ParametersSpec(min_count=1),
                        disabled=False,
                        exclude_from_kpi=False,
                        include_in_sla=False,
                        always_collect_error_samples=False,
                        do_not_schedule=False
                    )
                ),
                comparisons=TableComparisonDailyMonitoringChecksSpecMap()
            )
        ),
        partitioned_checks=TablePartitionedCheckCategoriesSpec()
    ),
    can_edit=True
)

call_result = await update_table_quality_policy.asyncio(
    'default',
    client=dqops_client,
    json_body=request_body
)

Execution

from dqops import client
from dqops.client.api.table_quality_policies import update_table_quality_policy
from dqops.client.models import MinCountRule1ParametersSpec, \
                                TableMonitoringCheckCategoriesSpec, \
                                TablePartitionedCheckCategoriesSpec, \
                                TableProfilingCheckCategoriesSpec, \
                                TableQualityPolicyModel, \
                                TableQualityPolicySpec, \
                                TableRowCountCheckSpec, \
                                TableVolumeProfilingChecksSpec, \
                                TableVolumeRowCountSensorParametersSpec, \
                                TargetTablePatternSpec

token = 's4mp13_4u7h_70k3n'

dqops_client = client.AuthenticatedClient(
    'http://localhost:8888/',
    token=token
)

request_body = TableQualityPolicyModel(
    policy_name='default',
    policy_spec=TableQualityPolicySpec(
        priority=1000,
        disabled=False,
        target=TargetTablePatternSpec(),
        profiling_checks=TableProfilingCheckCategoriesSpec(comparisons=TableComparisonProfilingChecksSpecMap()),
        monitoring_checks=TableMonitoringCheckCategoriesSpec(
            daily=TableDailyMonitoringCheckCategoriesSpec(
                volume=TableVolumeDailyMonitoringChecksSpec(
                    daily_row_count=TableRowCountCheckSpec(
                        parameters=TableVolumeRowCountSensorParametersSpec(),
                        warning=MinCountRule1ParametersSpec(min_count=1),
                        disabled=False,
                        exclude_from_kpi=False,
                        include_in_sla=False,
                        always_collect_error_samples=False,
                        do_not_schedule=False
                    )
                ),
                comparisons=TableComparisonDailyMonitoringChecksSpecMap()
            )
        ),
        partitioned_checks=TablePartitionedCheckCategoriesSpec()
    ),
    can_edit=True
)

call_result = update_table_quality_policy.sync(
    'default',
    client=dqops_client,
    json_body=request_body
)

Execution

from dqops import client
from dqops.client.api.table_quality_policies import update_table_quality_policy
from dqops.client.models import MinCountRule1ParametersSpec, \
                                TableMonitoringCheckCategoriesSpec, \
                                TablePartitionedCheckCategoriesSpec, \
                                TableProfilingCheckCategoriesSpec, \
                                TableQualityPolicyModel, \
                                TableQualityPolicySpec, \
                                TableRowCountCheckSpec, \
                                TableVolumeProfilingChecksSpec, \
                                TableVolumeRowCountSensorParametersSpec, \
                                TargetTablePatternSpec

token = 's4mp13_4u7h_70k3n'

dqops_client = client.AuthenticatedClient(
    'http://localhost:8888/',
    token=token
)

request_body = TableQualityPolicyModel(
    policy_name='default',
    policy_spec=TableQualityPolicySpec(
        priority=1000,
        disabled=False,
        target=TargetTablePatternSpec(),
        profiling_checks=TableProfilingCheckCategoriesSpec(comparisons=TableComparisonProfilingChecksSpecMap()),
        monitoring_checks=TableMonitoringCheckCategoriesSpec(
            daily=TableDailyMonitoringCheckCategoriesSpec(
                volume=TableVolumeDailyMonitoringChecksSpec(
                    daily_row_count=TableRowCountCheckSpec(
                        parameters=TableVolumeRowCountSensorParametersSpec(),
                        warning=MinCountRule1ParametersSpec(min_count=1),
                        disabled=False,
                        exclude_from_kpi=False,
                        include_in_sla=False,
                        always_collect_error_samples=False,
                        do_not_schedule=False
                    )
                ),
                comparisons=TableComparisonDailyMonitoringChecksSpecMap()
            )
        ),
        partitioned_checks=TablePartitionedCheckCategoriesSpec()
    ),
    can_edit=True
)

call_result = await update_table_quality_policy.asyncio(
    'default',
    client=dqops_client,
    json_body=request_body
)

---

update_table_quality_policy_target

Updates an default table-level checks pattern (data quality policy), changing only the target object

Follow the link to see the source code on GitHub.

PUT

http://localhost:8888/api/policies/checks/table/{patternName}/target

Parameters of this method are described below

Property name	Description	Data type	Required
pattern_name	Pattern name	string

Request body

Description	Data type	Required
Default checks pattern model	TableQualityPolicyListModel

Usage examples

curlPython sync clientPython async clientPython auth sync clientPython auth async client

Execution

curl -X PUT http://localhost:8888/api/policies/checks/table/default/target^
    -H "Accept: application/json"^
    -H "Content-Type: application/json"^
    -d^
    "{\"policy_name\":\"default\",\"priority\":100,\"disabled\":false,\"target_table\":{\"connection\":\"dwh\",\"schema\":\"public\",\"table\":\"fact_*\"},\"can_edit\":true}"

Execution

from dqops import client
from dqops.client.api.table_quality_policies import update_table_quality_policy_target
from dqops.client.models import TableQualityPolicyListModel, \
                                TargetTablePatternSpec

dqops_client = client.Client(
    'http://localhost:8888/'
)

request_body = TableQualityPolicyListModel(
    policy_name='default',
    priority=100,
    disabled=False,
    target_table=TargetTablePatternSpec(
        connection='dwh',
        schema='public',
        table='fact_*'
    ),
    can_edit=True
)

call_result = update_table_quality_policy_target.sync(
    'default',
    client=dqops_client,
    json_body=request_body
)

Execution

from dqops import client
from dqops.client.api.table_quality_policies import update_table_quality_policy_target
from dqops.client.models import TableQualityPolicyListModel, \
                                TargetTablePatternSpec

dqops_client = client.Client(
    'http://localhost:8888/'
)

request_body = TableQualityPolicyListModel(
    policy_name='default',
    priority=100,
    disabled=False,
    target_table=TargetTablePatternSpec(
        connection='dwh',
        schema='public',
        table='fact_*'
    ),
    can_edit=True
)

call_result = await update_table_quality_policy_target.asyncio(
    'default',
    client=dqops_client,
    json_body=request_body
)

Execution

from dqops import client
from dqops.client.api.table_quality_policies import update_table_quality_policy_target
from dqops.client.models import TableQualityPolicyListModel, \
                                TargetTablePatternSpec

token = 's4mp13_4u7h_70k3n'

dqops_client = client.AuthenticatedClient(
    'http://localhost:8888/',
    token=token
)

request_body = TableQualityPolicyListModel(
    policy_name='default',
    priority=100,
    disabled=False,
    target_table=TargetTablePatternSpec(
        connection='dwh',
        schema='public',
        table='fact_*'
    ),
    can_edit=True
)

call_result = update_table_quality_policy_target.sync(
    'default',
    client=dqops_client,
    json_body=request_body
)

Execution

from dqops import client
from dqops.client.api.table_quality_policies import update_table_quality_policy_target
from dqops.client.models import TableQualityPolicyListModel, \
                                TargetTablePatternSpec

token = 's4mp13_4u7h_70k3n'

dqops_client = client.AuthenticatedClient(
    'http://localhost:8888/',
    token=token
)

request_body = TableQualityPolicyListModel(
    policy_name='default',
    priority=100,
    disabled=False,
    target_table=TargetTablePatternSpec(
        connection='dwh',
        schema='public',
        table='fact_*'
    ),
    can_edit=True
)

call_result = await update_table_quality_policy_target.asyncio(
    'default',
    client=dqops_client,
    json_body=request_body
)