Last updated: July 22, 2025

DQOps REST API column_quality_policies operations

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

---

copy_from_column_quality_policy

Creates (adds) a copy of an existing default column-level checks pattern configuration, under a new name.

Follow the link to see the source code on GitHub.

POST

http://localhost:8888/api/policies/checks/column/{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/column/default/copyfrom/default^
    -H "Accept: application/json"

Execution

from dqops import client
from dqops.client.api.column_quality_policies import copy_from_column_quality_policy

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

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

Execution

from dqops import client
from dqops.client.api.column_quality_policies import copy_from_column_quality_policy

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

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

Execution

from dqops import client
from dqops.client.api.column_quality_policies import copy_from_column_quality_policy

token = 's4mp13_4u7h_70k3n'

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

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

Execution

from dqops import client
from dqops.client.api.column_quality_policies import copy_from_column_quality_policy

token = 's4mp13_4u7h_70k3n'

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

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

---

create_column_quality_policy

Creates (adds) a new default column-level checks pattern configuration by saving a full specification object.

Follow the link to see the source code on GitHub.

POST

http://localhost:8888/api/policies/checks/column/{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	ColumnQualityPolicyModel

Usage examples

curlPython sync clientPython async clientPython auth sync clientPython auth async client

Execution

curl -X POST http://localhost:8888/api/policies/checks/column/default^
    -H "Accept: application/json"^
    -H "Content-Type: application/json"^
    -d^
    "{\"policy_name\":\"id columns not null\",\"policy_spec\":{\"priority\":1000,\"target\":{\"column\":\"id\"},\"monitoring_checks\":{\"daily\":{\"nulls\":{\"daily_nulls_count\":{\"error\":{\"max_count\":0}}}}}},\"can_edit\":true}"

Execution

from dqops import client
from dqops.client.api.column_quality_policies import create_column_quality_policy
from dqops.client.models import ColumnComparisonProfilingChecksSpecMap, \
                                ColumnMonitoringCheckCategoriesSpec, \
                                ColumnNullsCountCheckSpec, \
                                ColumnNullsNullsCountSensorParametersSpec, \
                                ColumnNullsProfilingChecksSpec, \
                                ColumnPartitionedCheckCategoriesSpec, \
                                ColumnProfilingCheckCategoriesSpec, \
                                ColumnQualityPolicyModel, \
                                ColumnQualityPolicySpec, \
                                MaxCountRule0ErrorParametersSpec, \
                                TargetColumnPatternSpec

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

request_body = ColumnQualityPolicyModel(
    policy_name='id columns not null',
    policy_spec=ColumnQualityPolicySpec(
        priority=1000,
        disabled=False,
        target=TargetColumnPatternSpec(column='id'),
        profiling_checks=ColumnProfilingCheckCategoriesSpec(comparisons=ColumnComparisonProfilingChecksSpecMap()),
        monitoring_checks=ColumnMonitoringCheckCategoriesSpec(
            daily=ColumnDailyMonitoringCheckCategoriesSpec(
                nulls=ColumnNullsDailyMonitoringChecksSpec(
                    daily_nulls_count=ColumnNullsCountCheckSpec(
                        parameters=ColumnNullsNullsCountSensorParametersSpec(),
                        error=MaxCountRule0ErrorParametersSpec(max_count=0),
                        disabled=False,
                        exclude_from_kpi=False,
                        include_in_sla=False,
                        always_collect_error_samples=False,
                        do_not_schedule=False
                    )
                ),
                comparisons=ColumnComparisonDailyMonitoringChecksSpecMap()
            )
        ),
        partitioned_checks=ColumnPartitionedCheckCategoriesSpec()
    ),
    can_edit=True
)

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

Execution

from dqops import client
from dqops.client.api.column_quality_policies import create_column_quality_policy
from dqops.client.models import ColumnComparisonProfilingChecksSpecMap, \
                                ColumnMonitoringCheckCategoriesSpec, \
                                ColumnNullsCountCheckSpec, \
                                ColumnNullsNullsCountSensorParametersSpec, \
                                ColumnNullsProfilingChecksSpec, \
                                ColumnPartitionedCheckCategoriesSpec, \
                                ColumnProfilingCheckCategoriesSpec, \
                                ColumnQualityPolicyModel, \
                                ColumnQualityPolicySpec, \
                                MaxCountRule0ErrorParametersSpec, \
                                TargetColumnPatternSpec

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

request_body = ColumnQualityPolicyModel(
    policy_name='id columns not null',
    policy_spec=ColumnQualityPolicySpec(
        priority=1000,
        disabled=False,
        target=TargetColumnPatternSpec(column='id'),
        profiling_checks=ColumnProfilingCheckCategoriesSpec(comparisons=ColumnComparisonProfilingChecksSpecMap()),
        monitoring_checks=ColumnMonitoringCheckCategoriesSpec(
            daily=ColumnDailyMonitoringCheckCategoriesSpec(
                nulls=ColumnNullsDailyMonitoringChecksSpec(
                    daily_nulls_count=ColumnNullsCountCheckSpec(
                        parameters=ColumnNullsNullsCountSensorParametersSpec(),
                        error=MaxCountRule0ErrorParametersSpec(max_count=0),
                        disabled=False,
                        exclude_from_kpi=False,
                        include_in_sla=False,
                        always_collect_error_samples=False,
                        do_not_schedule=False
                    )
                ),
                comparisons=ColumnComparisonDailyMonitoringChecksSpecMap()
            )
        ),
        partitioned_checks=ColumnPartitionedCheckCategoriesSpec()
    ),
    can_edit=True
)

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

Execution

from dqops import client
from dqops.client.api.column_quality_policies import create_column_quality_policy
from dqops.client.models import ColumnComparisonProfilingChecksSpecMap, \
                                ColumnMonitoringCheckCategoriesSpec, \
                                ColumnNullsCountCheckSpec, \
                                ColumnNullsNullsCountSensorParametersSpec, \
                                ColumnNullsProfilingChecksSpec, \
                                ColumnPartitionedCheckCategoriesSpec, \
                                ColumnProfilingCheckCategoriesSpec, \
                                ColumnQualityPolicyModel, \
                                ColumnQualityPolicySpec, \
                                MaxCountRule0ErrorParametersSpec, \
                                TargetColumnPatternSpec

token = 's4mp13_4u7h_70k3n'

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

request_body = ColumnQualityPolicyModel(
    policy_name='id columns not null',
    policy_spec=ColumnQualityPolicySpec(
        priority=1000,
        disabled=False,
        target=TargetColumnPatternSpec(column='id'),
        profiling_checks=ColumnProfilingCheckCategoriesSpec(comparisons=ColumnComparisonProfilingChecksSpecMap()),
        monitoring_checks=ColumnMonitoringCheckCategoriesSpec(
            daily=ColumnDailyMonitoringCheckCategoriesSpec(
                nulls=ColumnNullsDailyMonitoringChecksSpec(
                    daily_nulls_count=ColumnNullsCountCheckSpec(
                        parameters=ColumnNullsNullsCountSensorParametersSpec(),
                        error=MaxCountRule0ErrorParametersSpec(max_count=0),
                        disabled=False,
                        exclude_from_kpi=False,
                        include_in_sla=False,
                        always_collect_error_samples=False,
                        do_not_schedule=False
                    )
                ),
                comparisons=ColumnComparisonDailyMonitoringChecksSpecMap()
            )
        ),
        partitioned_checks=ColumnPartitionedCheckCategoriesSpec()
    ),
    can_edit=True
)

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

Execution

from dqops import client
from dqops.client.api.column_quality_policies import create_column_quality_policy
from dqops.client.models import ColumnComparisonProfilingChecksSpecMap, \
                                ColumnMonitoringCheckCategoriesSpec, \
                                ColumnNullsCountCheckSpec, \
                                ColumnNullsNullsCountSensorParametersSpec, \
                                ColumnNullsProfilingChecksSpec, \
                                ColumnPartitionedCheckCategoriesSpec, \
                                ColumnProfilingCheckCategoriesSpec, \
                                ColumnQualityPolicyModel, \
                                ColumnQualityPolicySpec, \
                                MaxCountRule0ErrorParametersSpec, \
                                TargetColumnPatternSpec

token = 's4mp13_4u7h_70k3n'

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

request_body = ColumnQualityPolicyModel(
    policy_name='id columns not null',
    policy_spec=ColumnQualityPolicySpec(
        priority=1000,
        disabled=False,
        target=TargetColumnPatternSpec(column='id'),
        profiling_checks=ColumnProfilingCheckCategoriesSpec(comparisons=ColumnComparisonProfilingChecksSpecMap()),
        monitoring_checks=ColumnMonitoringCheckCategoriesSpec(
            daily=ColumnDailyMonitoringCheckCategoriesSpec(
                nulls=ColumnNullsDailyMonitoringChecksSpec(
                    daily_nulls_count=ColumnNullsCountCheckSpec(
                        parameters=ColumnNullsNullsCountSensorParametersSpec(),
                        error=MaxCountRule0ErrorParametersSpec(max_count=0),
                        disabled=False,
                        exclude_from_kpi=False,
                        include_in_sla=False,
                        always_collect_error_samples=False,
                        do_not_schedule=False
                    )
                ),
                comparisons=ColumnComparisonDailyMonitoringChecksSpecMap()
            )
        ),
        partitioned_checks=ColumnPartitionedCheckCategoriesSpec()
    ),
    can_edit=True
)

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

---

create_column_quality_policy_target

Creates (adds) a new default column-level checks pattern configuration.

Follow the link to see the source code on GitHub.

POST

http://localhost:8888/api/policies/checks/column/{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	ColumnQualityPolicyListModel

Usage examples

curlPython sync clientPython async clientPython auth sync clientPython auth async client

Execution

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

Execution

from dqops import client
from dqops.client.api.column_quality_policies import create_column_quality_policy_target
from dqops.client.models import ColumnQualityPolicyListModel, \
                                TargetColumnPatternSpec

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

request_body = ColumnQualityPolicyListModel(
    policy_name='default',
    priority=100,
    disabled=False,
    target_column=TargetColumnPatternSpec(
        column='id',
        connection='dwh'
    ),
    can_edit=True
)

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

Execution

from dqops import client
from dqops.client.api.column_quality_policies import create_column_quality_policy_target
from dqops.client.models import ColumnQualityPolicyListModel, \
                                TargetColumnPatternSpec

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

request_body = ColumnQualityPolicyListModel(
    policy_name='default',
    priority=100,
    disabled=False,
    target_column=TargetColumnPatternSpec(
        column='id',
        connection='dwh'
    ),
    can_edit=True
)

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

Execution

from dqops import client
from dqops.client.api.column_quality_policies import create_column_quality_policy_target
from dqops.client.models import ColumnQualityPolicyListModel, \
                                TargetColumnPatternSpec

token = 's4mp13_4u7h_70k3n'

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

request_body = ColumnQualityPolicyListModel(
    policy_name='default',
    priority=100,
    disabled=False,
    target_column=TargetColumnPatternSpec(
        column='id',
        connection='dwh'
    ),
    can_edit=True
)

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

Execution

from dqops import client
from dqops.client.api.column_quality_policies import create_column_quality_policy_target
from dqops.client.models import ColumnQualityPolicyListModel, \
                                TargetColumnPatternSpec

token = 's4mp13_4u7h_70k3n'

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

request_body = ColumnQualityPolicyListModel(
    policy_name='default',
    priority=100,
    disabled=False,
    target_column=TargetColumnPatternSpec(
        column='id',
        connection='dwh'
    ),
    can_edit=True
)

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

---

delete_column_quality_policy

Deletes a default column-level checks pattern

Follow the link to see the source code on GitHub.

DELETE

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

Execution

from dqops import client
from dqops.client.api.column_quality_policies import delete_column_quality_policy

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

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

Execution

from dqops import client
from dqops.client.api.column_quality_policies import delete_column_quality_policy

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

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

Execution

from dqops import client
from dqops.client.api.column_quality_policies import delete_column_quality_policy

token = 's4mp13_4u7h_70k3n'

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

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

Execution

from dqops import client
from dqops.client.api.column_quality_policies import delete_column_quality_policy

token = 's4mp13_4u7h_70k3n'

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

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

---

get_column_quality_policies

Returns a flat list of all column-level default check patterns configured for this instance. Default checks are applied on columns dynamically.

Follow the link to see the source code on GitHub.

GET

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

Return value

Property name	Description	Data type
column_quality_policy_list_model		List[ColumnQualityPolicyListModel]

Usage examples

curlPython sync clientPython async clientPython auth sync clientPython auth async client

Execution

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

Expand to see the returned result

[ {
  "policy_name" : "default",
  "priority" : 100,
  "disabled" : false,
  "target_column" : {
    "connection" : "dwh",
    "column" : "id"
  },
  "can_edit" : true
}, {
  "policy_name" : "default",
  "priority" : 100,
  "disabled" : false,
  "target_column" : {
    "connection" : "dwh",
    "column" : "id"
  },
  "can_edit" : true
}, {
  "policy_name" : "default",
  "priority" : 100,
  "disabled" : false,
  "target_column" : {
    "connection" : "dwh",
    "column" : "id"
  },
  "can_edit" : true
} ]

Execution

from dqops import client
from dqops.client.api.column_quality_policies import get_column_quality_policies

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

call_result = get_column_quality_policies.sync(
    client=dqops_client
)

Expand to see the returned result

[
    ColumnQualityPolicyListModel(
        policy_name='default',
        priority=100,
        disabled=False,
        target_column=TargetColumnPatternSpec(
            column='id',
            connection='dwh'
        ),
        can_edit=True
    ),
    ColumnQualityPolicyListModel(
        policy_name='default',
        priority=100,
        disabled=False,
        target_column=TargetColumnPatternSpec(
            column='id',
            connection='dwh'
        ),
        can_edit=True
    ),
    ColumnQualityPolicyListModel(
        policy_name='default',
        priority=100,
        disabled=False,
        target_column=TargetColumnPatternSpec(
            column='id',
            connection='dwh'
        ),
        can_edit=True
    )
]

Execution

from dqops import client
from dqops.client.api.column_quality_policies import get_column_quality_policies

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

call_result = await get_column_quality_policies.asyncio(
    client=dqops_client
)

Expand to see the returned result

[
    ColumnQualityPolicyListModel(
        policy_name='default',
        priority=100,
        disabled=False,
        target_column=TargetColumnPatternSpec(
            column='id',
            connection='dwh'
        ),
        can_edit=True
    ),
    ColumnQualityPolicyListModel(
        policy_name='default',
        priority=100,
        disabled=False,
        target_column=TargetColumnPatternSpec(
            column='id',
            connection='dwh'
        ),
        can_edit=True
    ),
    ColumnQualityPolicyListModel(
        policy_name='default',
        priority=100,
        disabled=False,
        target_column=TargetColumnPatternSpec(
            column='id',
            connection='dwh'
        ),
        can_edit=True
    )
]

Execution

from dqops import client
from dqops.client.api.column_quality_policies import get_column_quality_policies

token = 's4mp13_4u7h_70k3n'

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

call_result = get_column_quality_policies.sync(
    client=dqops_client
)

Expand to see the returned result

[
    ColumnQualityPolicyListModel(
        policy_name='default',
        priority=100,
        disabled=False,
        target_column=TargetColumnPatternSpec(
            column='id',
            connection='dwh'
        ),
        can_edit=True
    ),
    ColumnQualityPolicyListModel(
        policy_name='default',
        priority=100,
        disabled=False,
        target_column=TargetColumnPatternSpec(
            column='id',
            connection='dwh'
        ),
        can_edit=True
    ),
    ColumnQualityPolicyListModel(
        policy_name='default',
        priority=100,
        disabled=False,
        target_column=TargetColumnPatternSpec(
            column='id',
            connection='dwh'
        ),
        can_edit=True
    )
]

Execution

from dqops import client
from dqops.client.api.column_quality_policies import get_column_quality_policies

token = 's4mp13_4u7h_70k3n'

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

call_result = await get_column_quality_policies.asyncio(
    client=dqops_client
)

Expand to see the returned result

[
    ColumnQualityPolicyListModel(
        policy_name='default',
        priority=100,
        disabled=False,
        target_column=TargetColumnPatternSpec(
            column='id',
            connection='dwh'
        ),
        can_edit=True
    ),
    ColumnQualityPolicyListModel(
        policy_name='default',
        priority=100,
        disabled=False,
        target_column=TargetColumnPatternSpec(
            column='id',
            connection='dwh'
        ),
        can_edit=True
    ),
    ColumnQualityPolicyListModel(
        policy_name='default',
        priority=100,
        disabled=False,
        target_column=TargetColumnPatternSpec(
            column='id',
            connection='dwh'
        ),
        can_edit=True
    )
]

---

get_column_quality_policy

Returns a default checks pattern definition as a full specification object

Follow the link to see the source code on GitHub.

GET

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

Return value

Property name	Description	Data type
column_quality_policy_model		ColumnQualityPolicyModel

Parameters of this method are described below

Property name	Description	Data type	Required
pattern_name	Column pattern name	string

Usage examples

curlPython sync clientPython async clientPython auth sync clientPython auth async client

Execution

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

Expand to see the returned result

{
  "policy_name" : "id columns not null",
  "policy_spec" : {
    "priority" : 1000,
    "target" : {
      "column" : "id"
    },
    "monitoring_checks" : {
      "daily" : {
        "nulls" : {
          "daily_nulls_count" : {
            "error" : {
              "max_count" : 0
            }
          }
        }
      }
    }
  },
  "can_edit" : true
}

Execution

from dqops import client
from dqops.client.api.column_quality_policies import get_column_quality_policy

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

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

Expand to see the returned result

ColumnQualityPolicyModel(
    policy_name='id columns not null',
    policy_spec=ColumnQualityPolicySpec(
        priority=1000,
        disabled=False,
        target=TargetColumnPatternSpec(column='id'),
        profiling_checks=ColumnProfilingCheckCategoriesSpec(comparisons=ColumnComparisonProfilingChecksSpecMap()),
        monitoring_checks=ColumnMonitoringCheckCategoriesSpec(
            daily=ColumnDailyMonitoringCheckCategoriesSpec(
                nulls=ColumnNullsDailyMonitoringChecksSpec(
                    daily_nulls_count=ColumnNullsCountCheckSpec(
                        parameters=ColumnNullsNullsCountSensorParametersSpec(),
                        error=MaxCountRule0ErrorParametersSpec(max_count=0),
                        disabled=False,
                        exclude_from_kpi=False,
                        include_in_sla=False,
                        always_collect_error_samples=False,
                        do_not_schedule=False
                    )
                ),
                comparisons=ColumnComparisonDailyMonitoringChecksSpecMap()
            )
        ),
        partitioned_checks=ColumnPartitionedCheckCategoriesSpec()
    ),
    can_edit=True
)

Execution

from dqops import client
from dqops.client.api.column_quality_policies import get_column_quality_policy

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

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

Expand to see the returned result

ColumnQualityPolicyModel(
    policy_name='id columns not null',
    policy_spec=ColumnQualityPolicySpec(
        priority=1000,
        disabled=False,
        target=TargetColumnPatternSpec(column='id'),
        profiling_checks=ColumnProfilingCheckCategoriesSpec(comparisons=ColumnComparisonProfilingChecksSpecMap()),
        monitoring_checks=ColumnMonitoringCheckCategoriesSpec(
            daily=ColumnDailyMonitoringCheckCategoriesSpec(
                nulls=ColumnNullsDailyMonitoringChecksSpec(
                    daily_nulls_count=ColumnNullsCountCheckSpec(
                        parameters=ColumnNullsNullsCountSensorParametersSpec(),
                        error=MaxCountRule0ErrorParametersSpec(max_count=0),
                        disabled=False,
                        exclude_from_kpi=False,
                        include_in_sla=False,
                        always_collect_error_samples=False,
                        do_not_schedule=False
                    )
                ),
                comparisons=ColumnComparisonDailyMonitoringChecksSpecMap()
            )
        ),
        partitioned_checks=ColumnPartitionedCheckCategoriesSpec()
    ),
    can_edit=True
)

Execution

from dqops import client
from dqops.client.api.column_quality_policies import get_column_quality_policy

token = 's4mp13_4u7h_70k3n'

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

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

Expand to see the returned result

ColumnQualityPolicyModel(
    policy_name='id columns not null',
    policy_spec=ColumnQualityPolicySpec(
        priority=1000,
        disabled=False,
        target=TargetColumnPatternSpec(column='id'),
        profiling_checks=ColumnProfilingCheckCategoriesSpec(comparisons=ColumnComparisonProfilingChecksSpecMap()),
        monitoring_checks=ColumnMonitoringCheckCategoriesSpec(
            daily=ColumnDailyMonitoringCheckCategoriesSpec(
                nulls=ColumnNullsDailyMonitoringChecksSpec(
                    daily_nulls_count=ColumnNullsCountCheckSpec(
                        parameters=ColumnNullsNullsCountSensorParametersSpec(),
                        error=MaxCountRule0ErrorParametersSpec(max_count=0),
                        disabled=False,
                        exclude_from_kpi=False,
                        include_in_sla=False,
                        always_collect_error_samples=False,
                        do_not_schedule=False
                    )
                ),
                comparisons=ColumnComparisonDailyMonitoringChecksSpecMap()
            )
        ),
        partitioned_checks=ColumnPartitionedCheckCategoriesSpec()
    ),
    can_edit=True
)

Execution

from dqops import client
from dqops.client.api.column_quality_policies import get_column_quality_policy

token = 's4mp13_4u7h_70k3n'

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

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

Expand to see the returned result

ColumnQualityPolicyModel(
    policy_name='id columns not null',
    policy_spec=ColumnQualityPolicySpec(
        priority=1000,
        disabled=False,
        target=TargetColumnPatternSpec(column='id'),
        profiling_checks=ColumnProfilingCheckCategoriesSpec(comparisons=ColumnComparisonProfilingChecksSpecMap()),
        monitoring_checks=ColumnMonitoringCheckCategoriesSpec(
            daily=ColumnDailyMonitoringCheckCategoriesSpec(
                nulls=ColumnNullsDailyMonitoringChecksSpec(
                    daily_nulls_count=ColumnNullsCountCheckSpec(
                        parameters=ColumnNullsNullsCountSensorParametersSpec(),
                        error=MaxCountRule0ErrorParametersSpec(max_count=0),
                        disabled=False,
                        exclude_from_kpi=False,
                        include_in_sla=False,
                        always_collect_error_samples=False,
                        do_not_schedule=False
                    )
                ),
                comparisons=ColumnComparisonDailyMonitoringChecksSpecMap()
            )
        ),
        partitioned_checks=ColumnPartitionedCheckCategoriesSpec()
    ),
    can_edit=True
)

---

get_column_quality_policy_target

Returns a default checks pattern definition

Follow the link to see the source code on GitHub.

GET

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

Return value

Property name	Description	Data type
column_quality_policy_list_model		ColumnQualityPolicyListModel

Parameters of this method are described below

Property name	Description	Data type	Required
pattern_name	Column pattern name	string

Usage examples

curlPython sync clientPython async clientPython auth sync clientPython auth async client

Execution

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

Expand to see the returned result

{
  "policy_name" : "default",
  "priority" : 100,
  "disabled" : false,
  "target_column" : {
    "connection" : "dwh",
    "column" : "id"
  },
  "can_edit" : true
}

Execution

from dqops import client
from dqops.client.api.column_quality_policies import get_column_quality_policy_target

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

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

Expand to see the returned result

ColumnQualityPolicyListModel(
    policy_name='default',
    priority=100,
    disabled=False,
    target_column=TargetColumnPatternSpec(
        column='id',
        connection='dwh'
    ),
    can_edit=True
)

Execution

from dqops import client
from dqops.client.api.column_quality_policies import get_column_quality_policy_target

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

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

Expand to see the returned result

ColumnQualityPolicyListModel(
    policy_name='default',
    priority=100,
    disabled=False,
    target_column=TargetColumnPatternSpec(
        column='id',
        connection='dwh'
    ),
    can_edit=True
)

Execution

from dqops import client
from dqops.client.api.column_quality_policies import get_column_quality_policy_target

token = 's4mp13_4u7h_70k3n'

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

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

Expand to see the returned result

ColumnQualityPolicyListModel(
    policy_name='default',
    priority=100,
    disabled=False,
    target_column=TargetColumnPatternSpec(
        column='id',
        connection='dwh'
    ),
    can_edit=True
)

Execution

from dqops import client
from dqops.client.api.column_quality_policies import get_column_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_column_quality_policy_target.asyncio(
    'default',
    client=dqops_client
)

Expand to see the returned result

ColumnQualityPolicyListModel(
    policy_name='default',
    priority=100,
    disabled=False,
    target_column=TargetColumnPatternSpec(
        column='id',
        connection='dwh'
    ),
    can_edit=True
)

---

get_monitoring_daily_column_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 column level.

Follow the link to see the source code on GitHub.

GET

http://localhost:8888/api/policies/checks/column/{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/column/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.column_quality_policies import get_monitoring_daily_column_quality_policy

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

call_result = get_monitoring_daily_column_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.column_quality_policies import get_monitoring_daily_column_quality_policy

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

call_result = await get_monitoring_daily_column_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.column_quality_policies import get_monitoring_daily_column_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_column_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.column_quality_policies import get_monitoring_daily_column_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_column_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_column_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 column level.

Follow the link to see the source code on GitHub.

GET

http://localhost:8888/api/policies/checks/column/{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/column/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.column_quality_policies import get_monitoring_monthly_column_quality_policy

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

call_result = get_monitoring_monthly_column_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.column_quality_policies import get_monitoring_monthly_column_quality_policy

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

call_result = await get_monitoring_monthly_column_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.column_quality_policies import get_monitoring_monthly_column_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_column_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.column_quality_policies import get_monitoring_monthly_column_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_column_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_column_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 column level.

Follow the link to see the source code on GitHub.

GET

http://localhost:8888/api/policies/checks/column/{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/column/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.column_quality_policies import get_partitioned_daily_column_quality_policy

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

call_result = get_partitioned_daily_column_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.column_quality_policies import get_partitioned_daily_column_quality_policy

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

call_result = await get_partitioned_daily_column_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.column_quality_policies import get_partitioned_daily_column_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_column_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.column_quality_policies import get_partitioned_daily_column_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_column_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_column_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 column level.

Follow the link to see the source code on GitHub.

GET

http://localhost:8888/api/policies/checks/column/{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/column/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.column_quality_policies import get_partitioned_monthly_column_quality_policy

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

call_result = get_partitioned_monthly_column_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.column_quality_policies import get_partitioned_monthly_column_quality_policy

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

call_result = await get_partitioned_monthly_column_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.column_quality_policies import get_partitioned_monthly_column_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_column_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.column_quality_policies import get_partitioned_monthly_column_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_column_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_column_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 column level.

Follow the link to see the source code on GitHub.

GET

http://localhost:8888/api/policies/checks/column/{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/column/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.column_quality_policies import get_profiling_column_quality_policy

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

call_result = get_profiling_column_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.column_quality_policies import get_profiling_column_quality_policy

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

call_result = await get_profiling_column_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.column_quality_policies import get_profiling_column_quality_policy

token = 's4mp13_4u7h_70k3n'

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

call_result = get_profiling_column_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.column_quality_policies import get_profiling_column_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_column_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
)

---

update_column_quality_policy

Updates an default column-level checks pattern by saving a full specification object

Follow the link to see the source code on GitHub.

PUT

http://localhost:8888/api/policies/checks/column/{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	ColumnQualityPolicyModel

Usage examples

curlPython sync clientPython async clientPython auth sync clientPython auth async client

Execution

curl -X PUT http://localhost:8888/api/policies/checks/column/default^
    -H "Accept: application/json"^
    -H "Content-Type: application/json"^
    -d^
    "{\"policy_name\":\"id columns not null\",\"policy_spec\":{\"priority\":1000,\"target\":{\"column\":\"id\"},\"monitoring_checks\":{\"daily\":{\"nulls\":{\"daily_nulls_count\":{\"error\":{\"max_count\":0}}}}}},\"can_edit\":true}"

Execution

from dqops import client
from dqops.client.api.column_quality_policies import update_column_quality_policy
from dqops.client.models import ColumnComparisonProfilingChecksSpecMap, \
                                ColumnMonitoringCheckCategoriesSpec, \
                                ColumnNullsCountCheckSpec, \
                                ColumnNullsNullsCountSensorParametersSpec, \
                                ColumnNullsProfilingChecksSpec, \
                                ColumnPartitionedCheckCategoriesSpec, \
                                ColumnProfilingCheckCategoriesSpec, \
                                ColumnQualityPolicyModel, \
                                ColumnQualityPolicySpec, \
                                MaxCountRule0ErrorParametersSpec, \
                                TargetColumnPatternSpec

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

request_body = ColumnQualityPolicyModel(
    policy_name='id columns not null',
    policy_spec=ColumnQualityPolicySpec(
        priority=1000,
        disabled=False,
        target=TargetColumnPatternSpec(column='id'),
        profiling_checks=ColumnProfilingCheckCategoriesSpec(comparisons=ColumnComparisonProfilingChecksSpecMap()),
        monitoring_checks=ColumnMonitoringCheckCategoriesSpec(
            daily=ColumnDailyMonitoringCheckCategoriesSpec(
                nulls=ColumnNullsDailyMonitoringChecksSpec(
                    daily_nulls_count=ColumnNullsCountCheckSpec(
                        parameters=ColumnNullsNullsCountSensorParametersSpec(),
                        error=MaxCountRule0ErrorParametersSpec(max_count=0),
                        disabled=False,
                        exclude_from_kpi=False,
                        include_in_sla=False,
                        always_collect_error_samples=False,
                        do_not_schedule=False
                    )
                ),
                comparisons=ColumnComparisonDailyMonitoringChecksSpecMap()
            )
        ),
        partitioned_checks=ColumnPartitionedCheckCategoriesSpec()
    ),
    can_edit=True
)

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

Execution

from dqops import client
from dqops.client.api.column_quality_policies import update_column_quality_policy
from dqops.client.models import ColumnComparisonProfilingChecksSpecMap, \
                                ColumnMonitoringCheckCategoriesSpec, \
                                ColumnNullsCountCheckSpec, \
                                ColumnNullsNullsCountSensorParametersSpec, \
                                ColumnNullsProfilingChecksSpec, \
                                ColumnPartitionedCheckCategoriesSpec, \
                                ColumnProfilingCheckCategoriesSpec, \
                                ColumnQualityPolicyModel, \
                                ColumnQualityPolicySpec, \
                                MaxCountRule0ErrorParametersSpec, \
                                TargetColumnPatternSpec

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

request_body = ColumnQualityPolicyModel(
    policy_name='id columns not null',
    policy_spec=ColumnQualityPolicySpec(
        priority=1000,
        disabled=False,
        target=TargetColumnPatternSpec(column='id'),
        profiling_checks=ColumnProfilingCheckCategoriesSpec(comparisons=ColumnComparisonProfilingChecksSpecMap()),
        monitoring_checks=ColumnMonitoringCheckCategoriesSpec(
            daily=ColumnDailyMonitoringCheckCategoriesSpec(
                nulls=ColumnNullsDailyMonitoringChecksSpec(
                    daily_nulls_count=ColumnNullsCountCheckSpec(
                        parameters=ColumnNullsNullsCountSensorParametersSpec(),
                        error=MaxCountRule0ErrorParametersSpec(max_count=0),
                        disabled=False,
                        exclude_from_kpi=False,
                        include_in_sla=False,
                        always_collect_error_samples=False,
                        do_not_schedule=False
                    )
                ),
                comparisons=ColumnComparisonDailyMonitoringChecksSpecMap()
            )
        ),
        partitioned_checks=ColumnPartitionedCheckCategoriesSpec()
    ),
    can_edit=True
)

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

Execution

from dqops import client
from dqops.client.api.column_quality_policies import update_column_quality_policy
from dqops.client.models import ColumnComparisonProfilingChecksSpecMap, \
                                ColumnMonitoringCheckCategoriesSpec, \
                                ColumnNullsCountCheckSpec, \
                                ColumnNullsNullsCountSensorParametersSpec, \
                                ColumnNullsProfilingChecksSpec, \
                                ColumnPartitionedCheckCategoriesSpec, \
                                ColumnProfilingCheckCategoriesSpec, \
                                ColumnQualityPolicyModel, \
                                ColumnQualityPolicySpec, \
                                MaxCountRule0ErrorParametersSpec, \
                                TargetColumnPatternSpec

token = 's4mp13_4u7h_70k3n'

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

request_body = ColumnQualityPolicyModel(
    policy_name='id columns not null',
    policy_spec=ColumnQualityPolicySpec(
        priority=1000,
        disabled=False,
        target=TargetColumnPatternSpec(column='id'),
        profiling_checks=ColumnProfilingCheckCategoriesSpec(comparisons=ColumnComparisonProfilingChecksSpecMap()),
        monitoring_checks=ColumnMonitoringCheckCategoriesSpec(
            daily=ColumnDailyMonitoringCheckCategoriesSpec(
                nulls=ColumnNullsDailyMonitoringChecksSpec(
                    daily_nulls_count=ColumnNullsCountCheckSpec(
                        parameters=ColumnNullsNullsCountSensorParametersSpec(),
                        error=MaxCountRule0ErrorParametersSpec(max_count=0),
                        disabled=False,
                        exclude_from_kpi=False,
                        include_in_sla=False,
                        always_collect_error_samples=False,
                        do_not_schedule=False
                    )
                ),
                comparisons=ColumnComparisonDailyMonitoringChecksSpecMap()
            )
        ),
        partitioned_checks=ColumnPartitionedCheckCategoriesSpec()
    ),
    can_edit=True
)

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

Execution

from dqops import client
from dqops.client.api.column_quality_policies import update_column_quality_policy
from dqops.client.models import ColumnComparisonProfilingChecksSpecMap, \
                                ColumnMonitoringCheckCategoriesSpec, \
                                ColumnNullsCountCheckSpec, \
                                ColumnNullsNullsCountSensorParametersSpec, \
                                ColumnNullsProfilingChecksSpec, \
                                ColumnPartitionedCheckCategoriesSpec, \
                                ColumnProfilingCheckCategoriesSpec, \
                                ColumnQualityPolicyModel, \
                                ColumnQualityPolicySpec, \
                                MaxCountRule0ErrorParametersSpec, \
                                TargetColumnPatternSpec

token = 's4mp13_4u7h_70k3n'

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

request_body = ColumnQualityPolicyModel(
    policy_name='id columns not null',
    policy_spec=ColumnQualityPolicySpec(
        priority=1000,
        disabled=False,
        target=TargetColumnPatternSpec(column='id'),
        profiling_checks=ColumnProfilingCheckCategoriesSpec(comparisons=ColumnComparisonProfilingChecksSpecMap()),
        monitoring_checks=ColumnMonitoringCheckCategoriesSpec(
            daily=ColumnDailyMonitoringCheckCategoriesSpec(
                nulls=ColumnNullsDailyMonitoringChecksSpec(
                    daily_nulls_count=ColumnNullsCountCheckSpec(
                        parameters=ColumnNullsNullsCountSensorParametersSpec(),
                        error=MaxCountRule0ErrorParametersSpec(max_count=0),
                        disabled=False,
                        exclude_from_kpi=False,
                        include_in_sla=False,
                        always_collect_error_samples=False,
                        do_not_schedule=False
                    )
                ),
                comparisons=ColumnComparisonDailyMonitoringChecksSpecMap()
            )
        ),
        partitioned_checks=ColumnPartitionedCheckCategoriesSpec()
    ),
    can_edit=True
)

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

---

update_column_quality_policy_target

Updates an default column-level checks pattern, changing only the target object

Follow the link to see the source code on GitHub.

PUT

http://localhost:8888/api/policies/checks/column/{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	ColumnQualityPolicyListModel

Usage examples

curlPython sync clientPython async clientPython auth sync clientPython auth async client

Execution

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

Execution

from dqops import client
from dqops.client.api.column_quality_policies import update_column_quality_policy_target
from dqops.client.models import ColumnQualityPolicyListModel, \
                                TargetColumnPatternSpec

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

request_body = ColumnQualityPolicyListModel(
    policy_name='default',
    priority=100,
    disabled=False,
    target_column=TargetColumnPatternSpec(
        column='id',
        connection='dwh'
    ),
    can_edit=True
)

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

Execution

from dqops import client
from dqops.client.api.column_quality_policies import update_column_quality_policy_target
from dqops.client.models import ColumnQualityPolicyListModel, \
                                TargetColumnPatternSpec

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

request_body = ColumnQualityPolicyListModel(
    policy_name='default',
    priority=100,
    disabled=False,
    target_column=TargetColumnPatternSpec(
        column='id',
        connection='dwh'
    ),
    can_edit=True
)

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

Execution

from dqops import client
from dqops.client.api.column_quality_policies import update_column_quality_policy_target
from dqops.client.models import ColumnQualityPolicyListModel, \
                                TargetColumnPatternSpec

token = 's4mp13_4u7h_70k3n'

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

request_body = ColumnQualityPolicyListModel(
    policy_name='default',
    priority=100,
    disabled=False,
    target_column=TargetColumnPatternSpec(
        column='id',
        connection='dwh'
    ),
    can_edit=True
)

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

Execution

from dqops import client
from dqops.client.api.column_quality_policies import update_column_quality_policy_target
from dqops.client.models import ColumnQualityPolicyListModel, \
                                TargetColumnPatternSpec

token = 's4mp13_4u7h_70k3n'

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

request_body = ColumnQualityPolicyListModel(
    policy_name='default',
    priority=100,
    disabled=False,
    target_column=TargetColumnPatternSpec(
        column='id',
        connection='dwh'
    ),
    can_edit=True
)

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

---

update_monitoring_daily_column_quality_policy

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

Follow the link to see the source code on GitHub.

PUT

http://localhost:8888/api/policies/checks/column/{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/column/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.column_quality_policies import update_monitoring_daily_column_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_column_quality_policy.sync(
    'default',
    client=dqops_client,
    json_body=request_body
)

Execution

from dqops import client
from dqops.client.api.column_quality_policies import update_monitoring_daily_column_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_column_quality_policy.asyncio(
    'default',
    client=dqops_client,
    json_body=request_body
)

Execution

from dqops import client
from dqops.client.api.column_quality_policies import update_monitoring_daily_column_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_column_quality_policy.sync(
    'default',
    client=dqops_client,
    json_body=request_body
)

Execution

from dqops import client
from dqops.client.api.column_quality_policies import update_monitoring_daily_column_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_column_quality_policy.asyncio(
    'default',
    client=dqops_client,
    json_body=request_body
)

---

update_monitoring_monthly_column_quality_policy

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

Follow the link to see the source code on GitHub.

PUT

http://localhost:8888/api/policies/checks/column/{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/column/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.column_quality_policies import update_monitoring_monthly_column_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_column_quality_policy.sync(
    'default',
    client=dqops_client,
    json_body=request_body
)

Execution

from dqops import client
from dqops.client.api.column_quality_policies import update_monitoring_monthly_column_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_column_quality_policy.asyncio(
    'default',
    client=dqops_client,
    json_body=request_body
)

Execution

from dqops import client
from dqops.client.api.column_quality_policies import update_monitoring_monthly_column_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_column_quality_policy.sync(
    'default',
    client=dqops_client,
    json_body=request_body
)

Execution

from dqops import client
from dqops.client.api.column_quality_policies import update_monitoring_monthly_column_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_column_quality_policy.asyncio(
    'default',
    client=dqops_client,
    json_body=request_body
)

---

update_partitioned_daily_column_quality_policy

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

Follow the link to see the source code on GitHub.

PUT

http://localhost:8888/api/policies/checks/column/{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/column/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.column_quality_policies import update_partitioned_daily_column_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_column_quality_policy.sync(
    'default',
    client=dqops_client,
    json_body=request_body
)

Execution

from dqops import client
from dqops.client.api.column_quality_policies import update_partitioned_daily_column_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_column_quality_policy.asyncio(
    'default',
    client=dqops_client,
    json_body=request_body
)

Execution

from dqops import client
from dqops.client.api.column_quality_policies import update_partitioned_daily_column_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_column_quality_policy.sync(
    'default',
    client=dqops_client,
    json_body=request_body
)

Execution

from dqops import client
from dqops.client.api.column_quality_policies import update_partitioned_daily_column_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_column_quality_policy.asyncio(
    'default',
    client=dqops_client,
    json_body=request_body
)

---

update_partitioned_monthly_column_quality_policy

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

Follow the link to see the source code on GitHub.

PUT

http://localhost:8888/api/policies/checks/column/{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/column/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.column_quality_policies import update_partitioned_monthly_column_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_column_quality_policy.sync(
    'default',
    client=dqops_client,
    json_body=request_body
)

Execution

from dqops import client
from dqops.client.api.column_quality_policies import update_partitioned_monthly_column_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_column_quality_policy.asyncio(
    'default',
    client=dqops_client,
    json_body=request_body
)

Execution

from dqops import client
from dqops.client.api.column_quality_policies import update_partitioned_monthly_column_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_column_quality_policy.sync(
    'default',
    client=dqops_client,
    json_body=request_body
)

Execution

from dqops import client
from dqops.client.api.column_quality_policies import update_partitioned_monthly_column_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_column_quality_policy.asyncio(
    'default',
    client=dqops_client,
    json_body=request_body
)

---

update_profiling_column_quality_policy

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

Follow the link to see the source code on GitHub.

PUT

http://localhost:8888/api/policies/checks/column/{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/column/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.column_quality_policies import update_profiling_column_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_column_quality_policy.sync(
    'default',
    client=dqops_client,
    json_body=request_body
)

Execution

from dqops import client
from dqops.client.api.column_quality_policies import update_profiling_column_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_column_quality_policy.asyncio(
    'default',
    client=dqops_client,
    json_body=request_body
)

Execution

from dqops import client
from dqops.client.api.column_quality_policies import update_profiling_column_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_column_quality_policy.sync(
    'default',
    client=dqops_client,
    json_body=request_body
)

Execution

from dqops import client
from dqops.client.api.column_quality_policies import update_profiling_column_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_column_quality_policy.asyncio(
    'default',
    client=dqops_client,
    json_body=request_body
)