Last updated: September 02, 2024
DQOps REST API default_column_check_patterns operations
Operations for managing the configuration of the default column-level checks for columns matching a pattern.
copy_from_default_column_checks_pattern
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
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
Execution
Execution
Execution
Execution
from dqops import client
from dqops.client.api.default_column_check_patterns import copy_from_default_column_checks_pattern
token = 's4mp13_4u7h_70k3n'
dqops_client = client.AuthenticatedClient(
'http://localhost:8888/',
token=token
)
call_result = copy_from_default_column_checks_pattern.sync(
'default',
'default',
client=dqops_client
)
Execution
from dqops import client
from dqops.client.api.default_column_check_patterns import copy_from_default_column_checks_pattern
token = 's4mp13_4u7h_70k3n'
dqops_client = client.AuthenticatedClient(
'http://localhost:8888/',
token=token
)
call_result = await copy_from_default_column_checks_pattern.asyncio(
'default',
'default',
client=dqops_client
)
create_default_column_checks_pattern
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
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 | DefaultColumnChecksPatternModel |
Usage examples
Execution
curl -X POST http://localhost:8888/api/default/checks/column/default^
-H "Accept: application/json"^
-H "Content-Type: application/json"^
-d^
"{\"pattern_name\":\"id columns not null\",\"pattern_spec\":{\"priority\":0,\"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.default_column_check_patterns import create_default_column_checks_pattern
from dqops.client.models import ColumnComparisonProfilingChecksSpecMap, \
ColumnDefaultChecksPatternSpec, \
ColumnMonitoringCheckCategoriesSpec, \
ColumnNullsCountCheckSpec, \
ColumnNullsNullsCountSensorParametersSpec, \
ColumnNullsProfilingChecksSpec, \
ColumnPartitionedCheckCategoriesSpec, \
ColumnProfilingCheckCategoriesSpec, \
DefaultColumnChecksPatternModel, \
MaxCountRule0ErrorParametersSpec, \
TargetColumnPatternSpec
dqops_client = client.Client(
'http://localhost:8888/'
)
request_body = DefaultColumnChecksPatternModel(
pattern_name='id columns not null',
pattern_spec=ColumnDefaultChecksPatternSpec(
priority=0,
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
)
),
comparisons=ColumnComparisonDailyMonitoringChecksSpecMap()
)
),
partitioned_checks=ColumnPartitionedCheckCategoriesSpec()
),
can_edit=True
)
call_result = create_default_column_checks_pattern.sync(
'default',
client=dqops_client,
json_body=request_body
)
Execution
from dqops import client
from dqops.client.api.default_column_check_patterns import create_default_column_checks_pattern
from dqops.client.models import ColumnComparisonProfilingChecksSpecMap, \
ColumnDefaultChecksPatternSpec, \
ColumnMonitoringCheckCategoriesSpec, \
ColumnNullsCountCheckSpec, \
ColumnNullsNullsCountSensorParametersSpec, \
ColumnNullsProfilingChecksSpec, \
ColumnPartitionedCheckCategoriesSpec, \
ColumnProfilingCheckCategoriesSpec, \
DefaultColumnChecksPatternModel, \
MaxCountRule0ErrorParametersSpec, \
TargetColumnPatternSpec
dqops_client = client.Client(
'http://localhost:8888/'
)
request_body = DefaultColumnChecksPatternModel(
pattern_name='id columns not null',
pattern_spec=ColumnDefaultChecksPatternSpec(
priority=0,
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
)
),
comparisons=ColumnComparisonDailyMonitoringChecksSpecMap()
)
),
partitioned_checks=ColumnPartitionedCheckCategoriesSpec()
),
can_edit=True
)
call_result = await create_default_column_checks_pattern.asyncio(
'default',
client=dqops_client,
json_body=request_body
)
Execution
from dqops import client
from dqops.client.api.default_column_check_patterns import create_default_column_checks_pattern
from dqops.client.models import ColumnComparisonProfilingChecksSpecMap, \
ColumnDefaultChecksPatternSpec, \
ColumnMonitoringCheckCategoriesSpec, \
ColumnNullsCountCheckSpec, \
ColumnNullsNullsCountSensorParametersSpec, \
ColumnNullsProfilingChecksSpec, \
ColumnPartitionedCheckCategoriesSpec, \
ColumnProfilingCheckCategoriesSpec, \
DefaultColumnChecksPatternModel, \
MaxCountRule0ErrorParametersSpec, \
TargetColumnPatternSpec
token = 's4mp13_4u7h_70k3n'
dqops_client = client.AuthenticatedClient(
'http://localhost:8888/',
token=token
)
request_body = DefaultColumnChecksPatternModel(
pattern_name='id columns not null',
pattern_spec=ColumnDefaultChecksPatternSpec(
priority=0,
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
)
),
comparisons=ColumnComparisonDailyMonitoringChecksSpecMap()
)
),
partitioned_checks=ColumnPartitionedCheckCategoriesSpec()
),
can_edit=True
)
call_result = create_default_column_checks_pattern.sync(
'default',
client=dqops_client,
json_body=request_body
)
Execution
from dqops import client
from dqops.client.api.default_column_check_patterns import create_default_column_checks_pattern
from dqops.client.models import ColumnComparisonProfilingChecksSpecMap, \
ColumnDefaultChecksPatternSpec, \
ColumnMonitoringCheckCategoriesSpec, \
ColumnNullsCountCheckSpec, \
ColumnNullsNullsCountSensorParametersSpec, \
ColumnNullsProfilingChecksSpec, \
ColumnPartitionedCheckCategoriesSpec, \
ColumnProfilingCheckCategoriesSpec, \
DefaultColumnChecksPatternModel, \
MaxCountRule0ErrorParametersSpec, \
TargetColumnPatternSpec
token = 's4mp13_4u7h_70k3n'
dqops_client = client.AuthenticatedClient(
'http://localhost:8888/',
token=token
)
request_body = DefaultColumnChecksPatternModel(
pattern_name='id columns not null',
pattern_spec=ColumnDefaultChecksPatternSpec(
priority=0,
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
)
),
comparisons=ColumnComparisonDailyMonitoringChecksSpecMap()
)
),
partitioned_checks=ColumnPartitionedCheckCategoriesSpec()
),
can_edit=True
)
call_result = await create_default_column_checks_pattern.asyncio(
'default',
client=dqops_client,
json_body=request_body
)
create_default_column_checks_pattern_target
Creates (adds) a new default column-level checks pattern configuration.
Follow the link to see the source code on GitHub.
POST
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 | DefaultColumnChecksPatternListModel |
Usage examples
Execution
Execution
from dqops import client
from dqops.client.api.default_column_check_patterns import create_default_column_checks_pattern_target
from dqops.client.models import DefaultColumnChecksPatternListModel, \
TargetColumnPatternSpec
dqops_client = client.Client(
'http://localhost:8888/'
)
request_body = DefaultColumnChecksPatternListModel(
pattern_name='default',
priority=100,
disabled=False,
target_column=TargetColumnPatternSpec(
column='id',
connection='dwh'
),
can_edit=True
)
call_result = create_default_column_checks_pattern_target.sync(
'default',
client=dqops_client,
json_body=request_body
)
Execution
from dqops import client
from dqops.client.api.default_column_check_patterns import create_default_column_checks_pattern_target
from dqops.client.models import DefaultColumnChecksPatternListModel, \
TargetColumnPatternSpec
dqops_client = client.Client(
'http://localhost:8888/'
)
request_body = DefaultColumnChecksPatternListModel(
pattern_name='default',
priority=100,
disabled=False,
target_column=TargetColumnPatternSpec(
column='id',
connection='dwh'
),
can_edit=True
)
call_result = await create_default_column_checks_pattern_target.asyncio(
'default',
client=dqops_client,
json_body=request_body
)
Execution
from dqops import client
from dqops.client.api.default_column_check_patterns import create_default_column_checks_pattern_target
from dqops.client.models import DefaultColumnChecksPatternListModel, \
TargetColumnPatternSpec
token = 's4mp13_4u7h_70k3n'
dqops_client = client.AuthenticatedClient(
'http://localhost:8888/',
token=token
)
request_body = DefaultColumnChecksPatternListModel(
pattern_name='default',
priority=100,
disabled=False,
target_column=TargetColumnPatternSpec(
column='id',
connection='dwh'
),
can_edit=True
)
call_result = create_default_column_checks_pattern_target.sync(
'default',
client=dqops_client,
json_body=request_body
)
Execution
from dqops import client
from dqops.client.api.default_column_check_patterns import create_default_column_checks_pattern_target
from dqops.client.models import DefaultColumnChecksPatternListModel, \
TargetColumnPatternSpec
token = 's4mp13_4u7h_70k3n'
dqops_client = client.AuthenticatedClient(
'http://localhost:8888/',
token=token
)
request_body = DefaultColumnChecksPatternListModel(
pattern_name='default',
priority=100,
disabled=False,
target_column=TargetColumnPatternSpec(
column='id',
connection='dwh'
),
can_edit=True
)
call_result = await create_default_column_checks_pattern_target.asyncio(
'default',
client=dqops_client,
json_body=request_body
)
delete_default_column_checks_pattern
Deletes a default column-level checks pattern
Follow the link to see the source code on GitHub.
DELETE
Parameters of this method are described below
| Property name | Description | Data type | Required |
|---|---|---|---|
pattern_name |
Pattern name | string |
Usage examples
Execution
Execution
Execution
Execution
from dqops import client
from dqops.client.api.default_column_check_patterns import delete_default_column_checks_pattern
token = 's4mp13_4u7h_70k3n'
dqops_client = client.AuthenticatedClient(
'http://localhost:8888/',
token=token
)
call_result = delete_default_column_checks_pattern.sync(
'default',
client=dqops_client
)
Execution
from dqops import client
from dqops.client.api.default_column_check_patterns import delete_default_column_checks_pattern
token = 's4mp13_4u7h_70k3n'
dqops_client = client.AuthenticatedClient(
'http://localhost:8888/',
token=token
)
call_result = await delete_default_column_checks_pattern.asyncio(
'default',
client=dqops_client
)
get_all_default_column_checks_patterns
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
Return value
| Property name | Description | Data type |
|---|---|---|
default_column_checks_pattern_list_model |
List[DefaultColumnChecksPatternListModel] |
Usage examples
Execution
Expand to see the returned result
[ {
"pattern_name" : "default",
"priority" : 100,
"disabled" : false,
"target_column" : {
"connection" : "dwh",
"column" : "id"
},
"can_edit" : true
}, {
"pattern_name" : "default",
"priority" : 100,
"disabled" : false,
"target_column" : {
"connection" : "dwh",
"column" : "id"
},
"can_edit" : true
}, {
"pattern_name" : "default",
"priority" : 100,
"disabled" : false,
"target_column" : {
"connection" : "dwh",
"column" : "id"
},
"can_edit" : true
} ]
Execution
from dqops import client
from dqops.client.api.default_column_check_patterns import get_all_default_column_checks_patterns
dqops_client = client.Client(
'http://localhost:8888/',
raise_on_unexpected_status=True
)
call_result = get_all_default_column_checks_patterns.sync(
client=dqops_client
)
Expand to see the returned result
[
DefaultColumnChecksPatternListModel(
pattern_name='default',
priority=100,
disabled=False,
target_column=TargetColumnPatternSpec(
column='id',
connection='dwh'
),
can_edit=True
),
DefaultColumnChecksPatternListModel(
pattern_name='default',
priority=100,
disabled=False,
target_column=TargetColumnPatternSpec(
column='id',
connection='dwh'
),
can_edit=True
),
DefaultColumnChecksPatternListModel(
pattern_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.default_column_check_patterns import get_all_default_column_checks_patterns
dqops_client = client.Client(
'http://localhost:8888/',
raise_on_unexpected_status=True
)
call_result = await get_all_default_column_checks_patterns.asyncio(
client=dqops_client
)
Expand to see the returned result
[
DefaultColumnChecksPatternListModel(
pattern_name='default',
priority=100,
disabled=False,
target_column=TargetColumnPatternSpec(
column='id',
connection='dwh'
),
can_edit=True
),
DefaultColumnChecksPatternListModel(
pattern_name='default',
priority=100,
disabled=False,
target_column=TargetColumnPatternSpec(
column='id',
connection='dwh'
),
can_edit=True
),
DefaultColumnChecksPatternListModel(
pattern_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.default_column_check_patterns import get_all_default_column_checks_patterns
token = 's4mp13_4u7h_70k3n'
dqops_client = client.AuthenticatedClient(
'http://localhost:8888/',
token=token,
raise_on_unexpected_status=True
)
call_result = get_all_default_column_checks_patterns.sync(
client=dqops_client
)
Expand to see the returned result
[
DefaultColumnChecksPatternListModel(
pattern_name='default',
priority=100,
disabled=False,
target_column=TargetColumnPatternSpec(
column='id',
connection='dwh'
),
can_edit=True
),
DefaultColumnChecksPatternListModel(
pattern_name='default',
priority=100,
disabled=False,
target_column=TargetColumnPatternSpec(
column='id',
connection='dwh'
),
can_edit=True
),
DefaultColumnChecksPatternListModel(
pattern_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.default_column_check_patterns import get_all_default_column_checks_patterns
token = 's4mp13_4u7h_70k3n'
dqops_client = client.AuthenticatedClient(
'http://localhost:8888/',
token=token,
raise_on_unexpected_status=True
)
call_result = await get_all_default_column_checks_patterns.asyncio(
client=dqops_client
)
Expand to see the returned result
[
DefaultColumnChecksPatternListModel(
pattern_name='default',
priority=100,
disabled=False,
target_column=TargetColumnPatternSpec(
column='id',
connection='dwh'
),
can_edit=True
),
DefaultColumnChecksPatternListModel(
pattern_name='default',
priority=100,
disabled=False,
target_column=TargetColumnPatternSpec(
column='id',
connection='dwh'
),
can_edit=True
),
DefaultColumnChecksPatternListModel(
pattern_name='default',
priority=100,
disabled=False,
target_column=TargetColumnPatternSpec(
column='id',
connection='dwh'
),
can_edit=True
)
]
get_default_column_checks_pattern
Returns a default checks pattern definition as a full specification object
Follow the link to see the source code on GitHub.
GET
Return value
| Property name | Description | Data type |
|---|---|---|
default_column_checks_pattern_model |
DefaultColumnChecksPatternModel |
Parameters of this method are described below
| Property name | Description | Data type | Required |
|---|---|---|---|
pattern_name |
Column pattern name | string |
Usage examples
Execution
Execution
from dqops import client
from dqops.client.api.default_column_check_patterns import get_default_column_checks_pattern
dqops_client = client.Client(
'http://localhost:8888/',
raise_on_unexpected_status=True
)
call_result = get_default_column_checks_pattern.sync(
'default',
client=dqops_client
)
Expand to see the returned result
DefaultColumnChecksPatternModel(
pattern_name='id columns not null',
pattern_spec=ColumnDefaultChecksPatternSpec(
priority=0,
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
)
),
comparisons=ColumnComparisonDailyMonitoringChecksSpecMap()
)
),
partitioned_checks=ColumnPartitionedCheckCategoriesSpec()
),
can_edit=True
)
Execution
from dqops import client
from dqops.client.api.default_column_check_patterns import get_default_column_checks_pattern
dqops_client = client.Client(
'http://localhost:8888/',
raise_on_unexpected_status=True
)
call_result = await get_default_column_checks_pattern.asyncio(
'default',
client=dqops_client
)
Expand to see the returned result
DefaultColumnChecksPatternModel(
pattern_name='id columns not null',
pattern_spec=ColumnDefaultChecksPatternSpec(
priority=0,
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
)
),
comparisons=ColumnComparisonDailyMonitoringChecksSpecMap()
)
),
partitioned_checks=ColumnPartitionedCheckCategoriesSpec()
),
can_edit=True
)
Execution
from dqops import client
from dqops.client.api.default_column_check_patterns import get_default_column_checks_pattern
token = 's4mp13_4u7h_70k3n'
dqops_client = client.AuthenticatedClient(
'http://localhost:8888/',
token=token,
raise_on_unexpected_status=True
)
call_result = get_default_column_checks_pattern.sync(
'default',
client=dqops_client
)
Expand to see the returned result
DefaultColumnChecksPatternModel(
pattern_name='id columns not null',
pattern_spec=ColumnDefaultChecksPatternSpec(
priority=0,
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
)
),
comparisons=ColumnComparisonDailyMonitoringChecksSpecMap()
)
),
partitioned_checks=ColumnPartitionedCheckCategoriesSpec()
),
can_edit=True
)
Execution
from dqops import client
from dqops.client.api.default_column_check_patterns import get_default_column_checks_pattern
token = 's4mp13_4u7h_70k3n'
dqops_client = client.AuthenticatedClient(
'http://localhost:8888/',
token=token,
raise_on_unexpected_status=True
)
call_result = await get_default_column_checks_pattern.asyncio(
'default',
client=dqops_client
)
Expand to see the returned result
DefaultColumnChecksPatternModel(
pattern_name='id columns not null',
pattern_spec=ColumnDefaultChecksPatternSpec(
priority=0,
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
)
),
comparisons=ColumnComparisonDailyMonitoringChecksSpecMap()
)
),
partitioned_checks=ColumnPartitionedCheckCategoriesSpec()
),
can_edit=True
)
get_default_column_checks_pattern_target
Returns a default checks pattern definition
Follow the link to see the source code on GitHub.
GET
Return value
| Property name | Description | Data type |
|---|---|---|
default_column_checks_pattern_list_model |
DefaultColumnChecksPatternListModel |
Parameters of this method are described below
| Property name | Description | Data type | Required |
|---|---|---|---|
pattern_name |
Column pattern name | string |
Usage examples
Execution
Execution
from dqops import client
from dqops.client.api.default_column_check_patterns import get_default_column_checks_pattern_target
dqops_client = client.Client(
'http://localhost:8888/',
raise_on_unexpected_status=True
)
call_result = get_default_column_checks_pattern_target.sync(
'default',
client=dqops_client
)
Execution
from dqops import client
from dqops.client.api.default_column_check_patterns import get_default_column_checks_pattern_target
dqops_client = client.Client(
'http://localhost:8888/',
raise_on_unexpected_status=True
)
call_result = await get_default_column_checks_pattern_target.asyncio(
'default',
client=dqops_client
)
Execution
from dqops import client
from dqops.client.api.default_column_check_patterns import get_default_column_checks_pattern_target
token = 's4mp13_4u7h_70k3n'
dqops_client = client.AuthenticatedClient(
'http://localhost:8888/',
token=token,
raise_on_unexpected_status=True
)
call_result = get_default_column_checks_pattern_target.sync(
'default',
client=dqops_client
)
Execution
from dqops import client
from dqops.client.api.default_column_check_patterns import get_default_column_checks_pattern_target
token = 's4mp13_4u7h_70k3n'
dqops_client = client.AuthenticatedClient(
'http://localhost:8888/',
token=token,
raise_on_unexpected_status=True
)
call_result = await get_default_column_checks_pattern_target.asyncio(
'default',
client=dqops_client
)
get_default_monitoring_daily_column_checks_pattern
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
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
Execution
curl http://localhost:8888/api/default/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.default_column_check_patterns import get_default_monitoring_daily_column_checks_pattern
dqops_client = client.Client(
'http://localhost:8888/',
raise_on_unexpected_status=True
)
call_result = get_default_monitoring_daily_column_checks_pattern.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,
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.default_column_check_patterns import get_default_monitoring_daily_column_checks_pattern
dqops_client = client.Client(
'http://localhost:8888/',
raise_on_unexpected_status=True
)
call_result = await get_default_monitoring_daily_column_checks_pattern.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,
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.default_column_check_patterns import get_default_monitoring_daily_column_checks_pattern
token = 's4mp13_4u7h_70k3n'
dqops_client = client.AuthenticatedClient(
'http://localhost:8888/',
token=token,
raise_on_unexpected_status=True
)
call_result = get_default_monitoring_daily_column_checks_pattern.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,
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.default_column_check_patterns import get_default_monitoring_daily_column_checks_pattern
token = 's4mp13_4u7h_70k3n'
dqops_client = client.AuthenticatedClient(
'http://localhost:8888/',
token=token,
raise_on_unexpected_status=True
)
call_result = await get_default_monitoring_daily_column_checks_pattern.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,
can_edit=False,
can_run_checks=False,
can_delete_data=False
)
]
)
],
can_edit=False,
can_run_checks=False,
can_delete_data=False
)
get_default_monitoring_monthly_column_checks_pattern
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
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
Execution
curl http://localhost:8888/api/default/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.default_column_check_patterns import get_default_monitoring_monthly_column_checks_pattern
dqops_client = client.Client(
'http://localhost:8888/',
raise_on_unexpected_status=True
)
call_result = get_default_monitoring_monthly_column_checks_pattern.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,
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.default_column_check_patterns import get_default_monitoring_monthly_column_checks_pattern
dqops_client = client.Client(
'http://localhost:8888/',
raise_on_unexpected_status=True
)
call_result = await get_default_monitoring_monthly_column_checks_pattern.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,
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.default_column_check_patterns import get_default_monitoring_monthly_column_checks_pattern
token = 's4mp13_4u7h_70k3n'
dqops_client = client.AuthenticatedClient(
'http://localhost:8888/',
token=token,
raise_on_unexpected_status=True
)
call_result = get_default_monitoring_monthly_column_checks_pattern.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,
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.default_column_check_patterns import get_default_monitoring_monthly_column_checks_pattern
token = 's4mp13_4u7h_70k3n'
dqops_client = client.AuthenticatedClient(
'http://localhost:8888/',
token=token,
raise_on_unexpected_status=True
)
call_result = await get_default_monitoring_monthly_column_checks_pattern.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,
can_edit=False,
can_run_checks=False,
can_delete_data=False
)
]
)
],
can_edit=False,
can_run_checks=False,
can_delete_data=False
)
get_default_partitioned_daily_column_checks_pattern
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
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
Execution
curl http://localhost:8888/api/default/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.default_column_check_patterns import get_default_partitioned_daily_column_checks_pattern
dqops_client = client.Client(
'http://localhost:8888/',
raise_on_unexpected_status=True
)
call_result = get_default_partitioned_daily_column_checks_pattern.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,
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.default_column_check_patterns import get_default_partitioned_daily_column_checks_pattern
dqops_client = client.Client(
'http://localhost:8888/',
raise_on_unexpected_status=True
)
call_result = await get_default_partitioned_daily_column_checks_pattern.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,
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.default_column_check_patterns import get_default_partitioned_daily_column_checks_pattern
token = 's4mp13_4u7h_70k3n'
dqops_client = client.AuthenticatedClient(
'http://localhost:8888/',
token=token,
raise_on_unexpected_status=True
)
call_result = get_default_partitioned_daily_column_checks_pattern.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,
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.default_column_check_patterns import get_default_partitioned_daily_column_checks_pattern
token = 's4mp13_4u7h_70k3n'
dqops_client = client.AuthenticatedClient(
'http://localhost:8888/',
token=token,
raise_on_unexpected_status=True
)
call_result = await get_default_partitioned_daily_column_checks_pattern.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,
can_edit=False,
can_run_checks=False,
can_delete_data=False
)
]
)
],
can_edit=False,
can_run_checks=False,
can_delete_data=False
)
get_default_partitioned_monthly_column_checks_pattern
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
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
Execution
curl http://localhost:8888/api/default/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.default_column_check_patterns import get_default_partitioned_monthly_column_checks_pattern
dqops_client = client.Client(
'http://localhost:8888/',
raise_on_unexpected_status=True
)
call_result = get_default_partitioned_monthly_column_checks_pattern.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,
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.default_column_check_patterns import get_default_partitioned_monthly_column_checks_pattern
dqops_client = client.Client(
'http://localhost:8888/',
raise_on_unexpected_status=True
)
call_result = await get_default_partitioned_monthly_column_checks_pattern.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,
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.default_column_check_patterns import get_default_partitioned_monthly_column_checks_pattern
token = 's4mp13_4u7h_70k3n'
dqops_client = client.AuthenticatedClient(
'http://localhost:8888/',
token=token,
raise_on_unexpected_status=True
)
call_result = get_default_partitioned_monthly_column_checks_pattern.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,
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.default_column_check_patterns import get_default_partitioned_monthly_column_checks_pattern
token = 's4mp13_4u7h_70k3n'
dqops_client = client.AuthenticatedClient(
'http://localhost:8888/',
token=token,
raise_on_unexpected_status=True
)
call_result = await get_default_partitioned_monthly_column_checks_pattern.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,
can_edit=False,
can_run_checks=False,
can_delete_data=False
)
]
)
],
can_edit=False,
can_run_checks=False,
can_delete_data=False
)
get_default_profiling_column_checks_pattern
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
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
Execution
curl http://localhost:8888/api/default/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.default_column_check_patterns import get_default_profiling_column_checks_pattern
dqops_client = client.Client(
'http://localhost:8888/',
raise_on_unexpected_status=True
)
call_result = get_default_profiling_column_checks_pattern.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,
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.default_column_check_patterns import get_default_profiling_column_checks_pattern
dqops_client = client.Client(
'http://localhost:8888/',
raise_on_unexpected_status=True
)
call_result = await get_default_profiling_column_checks_pattern.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,
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.default_column_check_patterns import get_default_profiling_column_checks_pattern
token = 's4mp13_4u7h_70k3n'
dqops_client = client.AuthenticatedClient(
'http://localhost:8888/',
token=token,
raise_on_unexpected_status=True
)
call_result = get_default_profiling_column_checks_pattern.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,
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.default_column_check_patterns import get_default_profiling_column_checks_pattern
token = 's4mp13_4u7h_70k3n'
dqops_client = client.AuthenticatedClient(
'http://localhost:8888/',
token=token,
raise_on_unexpected_status=True
)
call_result = await get_default_profiling_column_checks_pattern.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,
can_edit=False,
can_run_checks=False,
can_delete_data=False
)
]
)
],
can_edit=False,
can_run_checks=False,
can_delete_data=False
)
update_default_column_checks_pattern
Updates an default column-level checks pattern by saving a full specification object
Follow the link to see the source code on GitHub.
PUT
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 | DefaultColumnChecksPatternModel |
Usage examples
Execution
curl -X PUT http://localhost:8888/api/default/checks/column/default^
-H "Accept: application/json"^
-H "Content-Type: application/json"^
-d^
"{\"pattern_name\":\"id columns not null\",\"pattern_spec\":{\"priority\":0,\"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.default_column_check_patterns import update_default_column_checks_pattern
from dqops.client.models import ColumnComparisonProfilingChecksSpecMap, \
ColumnDefaultChecksPatternSpec, \
ColumnMonitoringCheckCategoriesSpec, \
ColumnNullsCountCheckSpec, \
ColumnNullsNullsCountSensorParametersSpec, \
ColumnNullsProfilingChecksSpec, \
ColumnPartitionedCheckCategoriesSpec, \
ColumnProfilingCheckCategoriesSpec, \
DefaultColumnChecksPatternModel, \
MaxCountRule0ErrorParametersSpec, \
TargetColumnPatternSpec
dqops_client = client.Client(
'http://localhost:8888/'
)
request_body = DefaultColumnChecksPatternModel(
pattern_name='id columns not null',
pattern_spec=ColumnDefaultChecksPatternSpec(
priority=0,
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
)
),
comparisons=ColumnComparisonDailyMonitoringChecksSpecMap()
)
),
partitioned_checks=ColumnPartitionedCheckCategoriesSpec()
),
can_edit=True
)
call_result = update_default_column_checks_pattern.sync(
'default',
client=dqops_client,
json_body=request_body
)
Execution
from dqops import client
from dqops.client.api.default_column_check_patterns import update_default_column_checks_pattern
from dqops.client.models import ColumnComparisonProfilingChecksSpecMap, \
ColumnDefaultChecksPatternSpec, \
ColumnMonitoringCheckCategoriesSpec, \
ColumnNullsCountCheckSpec, \
ColumnNullsNullsCountSensorParametersSpec, \
ColumnNullsProfilingChecksSpec, \
ColumnPartitionedCheckCategoriesSpec, \
ColumnProfilingCheckCategoriesSpec, \
DefaultColumnChecksPatternModel, \
MaxCountRule0ErrorParametersSpec, \
TargetColumnPatternSpec
dqops_client = client.Client(
'http://localhost:8888/'
)
request_body = DefaultColumnChecksPatternModel(
pattern_name='id columns not null',
pattern_spec=ColumnDefaultChecksPatternSpec(
priority=0,
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
)
),
comparisons=ColumnComparisonDailyMonitoringChecksSpecMap()
)
),
partitioned_checks=ColumnPartitionedCheckCategoriesSpec()
),
can_edit=True
)
call_result = await update_default_column_checks_pattern.asyncio(
'default',
client=dqops_client,
json_body=request_body
)
Execution
from dqops import client
from dqops.client.api.default_column_check_patterns import update_default_column_checks_pattern
from dqops.client.models import ColumnComparisonProfilingChecksSpecMap, \
ColumnDefaultChecksPatternSpec, \
ColumnMonitoringCheckCategoriesSpec, \
ColumnNullsCountCheckSpec, \
ColumnNullsNullsCountSensorParametersSpec, \
ColumnNullsProfilingChecksSpec, \
ColumnPartitionedCheckCategoriesSpec, \
ColumnProfilingCheckCategoriesSpec, \
DefaultColumnChecksPatternModel, \
MaxCountRule0ErrorParametersSpec, \
TargetColumnPatternSpec
token = 's4mp13_4u7h_70k3n'
dqops_client = client.AuthenticatedClient(
'http://localhost:8888/',
token=token
)
request_body = DefaultColumnChecksPatternModel(
pattern_name='id columns not null',
pattern_spec=ColumnDefaultChecksPatternSpec(
priority=0,
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
)
),
comparisons=ColumnComparisonDailyMonitoringChecksSpecMap()
)
),
partitioned_checks=ColumnPartitionedCheckCategoriesSpec()
),
can_edit=True
)
call_result = update_default_column_checks_pattern.sync(
'default',
client=dqops_client,
json_body=request_body
)
Execution
from dqops import client
from dqops.client.api.default_column_check_patterns import update_default_column_checks_pattern
from dqops.client.models import ColumnComparisonProfilingChecksSpecMap, \
ColumnDefaultChecksPatternSpec, \
ColumnMonitoringCheckCategoriesSpec, \
ColumnNullsCountCheckSpec, \
ColumnNullsNullsCountSensorParametersSpec, \
ColumnNullsProfilingChecksSpec, \
ColumnPartitionedCheckCategoriesSpec, \
ColumnProfilingCheckCategoriesSpec, \
DefaultColumnChecksPatternModel, \
MaxCountRule0ErrorParametersSpec, \
TargetColumnPatternSpec
token = 's4mp13_4u7h_70k3n'
dqops_client = client.AuthenticatedClient(
'http://localhost:8888/',
token=token
)
request_body = DefaultColumnChecksPatternModel(
pattern_name='id columns not null',
pattern_spec=ColumnDefaultChecksPatternSpec(
priority=0,
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
)
),
comparisons=ColumnComparisonDailyMonitoringChecksSpecMap()
)
),
partitioned_checks=ColumnPartitionedCheckCategoriesSpec()
),
can_edit=True
)
call_result = await update_default_column_checks_pattern.asyncio(
'default',
client=dqops_client,
json_body=request_body
)
update_default_column_checks_pattern_target
Updates an default column-level checks pattern, changing only the target object
Follow the link to see the source code on GitHub.
PUT
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 | DefaultColumnChecksPatternListModel |
Usage examples
Execution
Execution
from dqops import client
from dqops.client.api.default_column_check_patterns import update_default_column_checks_pattern_target
from dqops.client.models import DefaultColumnChecksPatternListModel, \
TargetColumnPatternSpec
dqops_client = client.Client(
'http://localhost:8888/'
)
request_body = DefaultColumnChecksPatternListModel(
pattern_name='default',
priority=100,
disabled=False,
target_column=TargetColumnPatternSpec(
column='id',
connection='dwh'
),
can_edit=True
)
call_result = update_default_column_checks_pattern_target.sync(
'default',
client=dqops_client,
json_body=request_body
)
Execution
from dqops import client
from dqops.client.api.default_column_check_patterns import update_default_column_checks_pattern_target
from dqops.client.models import DefaultColumnChecksPatternListModel, \
TargetColumnPatternSpec
dqops_client = client.Client(
'http://localhost:8888/'
)
request_body = DefaultColumnChecksPatternListModel(
pattern_name='default',
priority=100,
disabled=False,
target_column=TargetColumnPatternSpec(
column='id',
connection='dwh'
),
can_edit=True
)
call_result = await update_default_column_checks_pattern_target.asyncio(
'default',
client=dqops_client,
json_body=request_body
)
Execution
from dqops import client
from dqops.client.api.default_column_check_patterns import update_default_column_checks_pattern_target
from dqops.client.models import DefaultColumnChecksPatternListModel, \
TargetColumnPatternSpec
token = 's4mp13_4u7h_70k3n'
dqops_client = client.AuthenticatedClient(
'http://localhost:8888/',
token=token
)
request_body = DefaultColumnChecksPatternListModel(
pattern_name='default',
priority=100,
disabled=False,
target_column=TargetColumnPatternSpec(
column='id',
connection='dwh'
),
can_edit=True
)
call_result = update_default_column_checks_pattern_target.sync(
'default',
client=dqops_client,
json_body=request_body
)
Execution
from dqops import client
from dqops.client.api.default_column_check_patterns import update_default_column_checks_pattern_target
from dqops.client.models import DefaultColumnChecksPatternListModel, \
TargetColumnPatternSpec
token = 's4mp13_4u7h_70k3n'
dqops_client = client.AuthenticatedClient(
'http://localhost:8888/',
token=token
)
request_body = DefaultColumnChecksPatternListModel(
pattern_name='default',
priority=100,
disabled=False,
target_column=TargetColumnPatternSpec(
column='id',
connection='dwh'
),
can_edit=True
)
call_result = await update_default_column_checks_pattern_target.asyncio(
'default',
client=dqops_client,
json_body=request_body
)
update_default_monitoring_daily_column_checks_pattern
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
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
Execution
curl -X PUT http://localhost:8888/api/default/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.default_column_check_patterns import update_default_monitoring_daily_column_checks_pattern
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,
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_default_monitoring_daily_column_checks_pattern.sync(
'default',
client=dqops_client,
json_body=request_body
)
Execution
from dqops import client
from dqops.client.api.default_column_check_patterns import update_default_monitoring_daily_column_checks_pattern
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,
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_default_monitoring_daily_column_checks_pattern.asyncio(
'default',
client=dqops_client,
json_body=request_body
)
Execution
from dqops import client
from dqops.client.api.default_column_check_patterns import update_default_monitoring_daily_column_checks_pattern
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,
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_default_monitoring_daily_column_checks_pattern.sync(
'default',
client=dqops_client,
json_body=request_body
)
Execution
from dqops import client
from dqops.client.api.default_column_check_patterns import update_default_monitoring_daily_column_checks_pattern
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,
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_default_monitoring_daily_column_checks_pattern.asyncio(
'default',
client=dqops_client,
json_body=request_body
)
update_default_monitoring_monthly_column_checks_pattern
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
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
Execution
curl -X PUT http://localhost:8888/api/default/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.default_column_check_patterns import update_default_monitoring_monthly_column_checks_pattern
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,
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_default_monitoring_monthly_column_checks_pattern.sync(
'default',
client=dqops_client,
json_body=request_body
)
Execution
from dqops import client
from dqops.client.api.default_column_check_patterns import update_default_monitoring_monthly_column_checks_pattern
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,
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_default_monitoring_monthly_column_checks_pattern.asyncio(
'default',
client=dqops_client,
json_body=request_body
)
Execution
from dqops import client
from dqops.client.api.default_column_check_patterns import update_default_monitoring_monthly_column_checks_pattern
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,
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_default_monitoring_monthly_column_checks_pattern.sync(
'default',
client=dqops_client,
json_body=request_body
)
Execution
from dqops import client
from dqops.client.api.default_column_check_patterns import update_default_monitoring_monthly_column_checks_pattern
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,
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_default_monitoring_monthly_column_checks_pattern.asyncio(
'default',
client=dqops_client,
json_body=request_body
)
update_default_partitioned_daily_column_checks_pattern
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
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
Execution
curl -X PUT http://localhost:8888/api/default/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.default_column_check_patterns import update_default_partitioned_daily_column_checks_pattern
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,
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_default_partitioned_daily_column_checks_pattern.sync(
'default',
client=dqops_client,
json_body=request_body
)
Execution
from dqops import client
from dqops.client.api.default_column_check_patterns import update_default_partitioned_daily_column_checks_pattern
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,
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_default_partitioned_daily_column_checks_pattern.asyncio(
'default',
client=dqops_client,
json_body=request_body
)
Execution
from dqops import client
from dqops.client.api.default_column_check_patterns import update_default_partitioned_daily_column_checks_pattern
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,
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_default_partitioned_daily_column_checks_pattern.sync(
'default',
client=dqops_client,
json_body=request_body
)
Execution
from dqops import client
from dqops.client.api.default_column_check_patterns import update_default_partitioned_daily_column_checks_pattern
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,
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_default_partitioned_daily_column_checks_pattern.asyncio(
'default',
client=dqops_client,
json_body=request_body
)
update_default_partitioned_monthly_column_checks_pattern
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
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
Execution
curl -X PUT http://localhost:8888/api/default/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.default_column_check_patterns import update_default_partitioned_monthly_column_checks_pattern
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,
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_default_partitioned_monthly_column_checks_pattern.sync(
'default',
client=dqops_client,
json_body=request_body
)
Execution
from dqops import client
from dqops.client.api.default_column_check_patterns import update_default_partitioned_monthly_column_checks_pattern
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,
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_default_partitioned_monthly_column_checks_pattern.asyncio(
'default',
client=dqops_client,
json_body=request_body
)
Execution
from dqops import client
from dqops.client.api.default_column_check_patterns import update_default_partitioned_monthly_column_checks_pattern
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,
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_default_partitioned_monthly_column_checks_pattern.sync(
'default',
client=dqops_client,
json_body=request_body
)
Execution
from dqops import client
from dqops.client.api.default_column_check_patterns import update_default_partitioned_monthly_column_checks_pattern
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,
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_default_partitioned_monthly_column_checks_pattern.asyncio(
'default',
client=dqops_client,
json_body=request_body
)
update_default_profiling_column_checks_pattern
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
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
Execution
curl -X PUT http://localhost:8888/api/default/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.default_column_check_patterns import update_default_profiling_column_checks_pattern
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,
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_default_profiling_column_checks_pattern.sync(
'default',
client=dqops_client,
json_body=request_body
)
Execution
from dqops import client
from dqops.client.api.default_column_check_patterns import update_default_profiling_column_checks_pattern
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,
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_default_profiling_column_checks_pattern.asyncio(
'default',
client=dqops_client,
json_body=request_body
)
Execution
from dqops import client
from dqops.client.api.default_column_check_patterns import update_default_profiling_column_checks_pattern
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,
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_default_profiling_column_checks_pattern.sync(
'default',
client=dqops_client,
json_body=request_body
)
Execution
from dqops import client
from dqops.client.api.default_column_check_patterns import update_default_profiling_column_checks_pattern
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,
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_default_profiling_column_checks_pattern.asyncio(
'default',
client=dqops_client,
json_body=request_body
)