Last updated: July 22, 2025

DQOps REST API rule_mining operations

Performs rule mining and proposes the configuration of data quality checks and their rule thresholds for tables.

---

apply_proposed_monitoring_checks

Applies the proposed configuration of data quality monitoring checks on a table.

Follow the link to see the source code on GitHub.

PUT

http://localhost:8888/api/connections/{connectionName}/schemas/{schemaName}/tables/{tableName}/monitoring/{timeScale}/applyproposal

Parameters of this method are described below

Property name	Description	Data type	Required
connection_name	Connection name	string
schema_name	Schema name	string
table_name	Table name	string
time_scale	Time scale	CheckTimeScale

Request body

Description	Data type	Required
Proposed configuration of data quality checks to be applied on the table and its columns.	CheckMiningProposalModel

Usage examples

curlPython sync clientPython async clientPython auth sync clientPython auth async client

Execution

curl -X PUT http://localhost:8888/api/connections/sample_connection/schemas/sample_schema/tables/sample_table/monitoring/daily/applyproposal^
    -H "Accept: application/json"^
    -H "Content-Type: application/json"^
    -d^
    "{\"missing_current_statistics\":false,\"missing_current_profiling_check_results\":false,\"column_checks\":{}}"

Execution

from dqops import client
from dqops.client.api.rule_mining import apply_proposed_monitoring_checks
from dqops.client.models import CheckContainerModel, \
                                CheckMiningProposalModel, \
                                CheckModel, \
                                CheckTimeScale, \
                                DefaultRuleSeverityLevel, \
                                FieldModel, \
                                QualityCategoryModel

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

request_body = CheckMiningProposalModel(
    missing_current_statistics=False,
    missing_current_profiling_check_results=False,
    column_checks={

    }
)

call_result = apply_proposed_monitoring_checks.sync(
    'sample_connection',
    'sample_schema',
    'sample_table',
    CheckTimeScale.daily,
    client=dqops_client,
    json_body=request_body
)

Execution

from dqops import client
from dqops.client.api.rule_mining import apply_proposed_monitoring_checks
from dqops.client.models import CheckContainerModel, \
                                CheckMiningProposalModel, \
                                CheckModel, \
                                CheckTimeScale, \
                                DefaultRuleSeverityLevel, \
                                FieldModel, \
                                QualityCategoryModel

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

request_body = CheckMiningProposalModel(
    missing_current_statistics=False,
    missing_current_profiling_check_results=False,
    column_checks={

    }
)

call_result = await apply_proposed_monitoring_checks.asyncio(
    'sample_connection',
    'sample_schema',
    'sample_table',
    CheckTimeScale.daily,
    client=dqops_client,
    json_body=request_body
)

Execution

from dqops import client
from dqops.client.api.rule_mining import apply_proposed_monitoring_checks
from dqops.client.models import CheckContainerModel, \
                                CheckMiningProposalModel, \
                                CheckModel, \
                                CheckTimeScale, \
                                DefaultRuleSeverityLevel, \
                                FieldModel, \
                                QualityCategoryModel

token = 's4mp13_4u7h_70k3n'

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

request_body = CheckMiningProposalModel(
    missing_current_statistics=False,
    missing_current_profiling_check_results=False,
    column_checks={

    }
)

call_result = apply_proposed_monitoring_checks.sync(
    'sample_connection',
    'sample_schema',
    'sample_table',
    CheckTimeScale.daily,
    client=dqops_client,
    json_body=request_body
)

Execution

from dqops import client
from dqops.client.api.rule_mining import apply_proposed_monitoring_checks
from dqops.client.models import CheckContainerModel, \
                                CheckMiningProposalModel, \
                                CheckModel, \
                                CheckTimeScale, \
                                DefaultRuleSeverityLevel, \
                                FieldModel, \
                                QualityCategoryModel

token = 's4mp13_4u7h_70k3n'

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

request_body = CheckMiningProposalModel(
    missing_current_statistics=False,
    missing_current_profiling_check_results=False,
    column_checks={

    }
)

call_result = await apply_proposed_monitoring_checks.asyncio(
    'sample_connection',
    'sample_schema',
    'sample_table',
    CheckTimeScale.daily,
    client=dqops_client,
    json_body=request_body
)

---

apply_proposed_partitioned_checks

Applies the proposed configuration of data quality partitioned checks on a table.

Follow the link to see the source code on GitHub.

PUT

http://localhost:8888/api/connections/{connectionName}/schemas/{schemaName}/tables/{tableName}/partitioned/{timeScale}/applyproposal

Parameters of this method are described below

Property name	Description	Data type	Required
connection_name	Connection name	string
schema_name	Schema name	string
table_name	Table name	string
time_scale	Time scale	CheckTimeScale

Request body

Description	Data type	Required
Proposed configuration of data quality checks to be applied on the table and its columns.	CheckMiningProposalModel

Usage examples

curlPython sync clientPython async clientPython auth sync clientPython auth async client

Execution

curl -X PUT http://localhost:8888/api/connections/sample_connection/schemas/sample_schema/tables/sample_table/partitioned/daily/applyproposal^
    -H "Accept: application/json"^
    -H "Content-Type: application/json"^
    -d^
    "{\"missing_current_statistics\":false,\"missing_current_profiling_check_results\":false,\"column_checks\":{}}"

Execution

from dqops import client
from dqops.client.api.rule_mining import apply_proposed_partitioned_checks
from dqops.client.models import CheckContainerModel, \
                                CheckMiningProposalModel, \
                                CheckModel, \
                                CheckTimeScale, \
                                DefaultRuleSeverityLevel, \
                                FieldModel, \
                                QualityCategoryModel

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

request_body = CheckMiningProposalModel(
    missing_current_statistics=False,
    missing_current_profiling_check_results=False,
    column_checks={

    }
)

call_result = apply_proposed_partitioned_checks.sync(
    'sample_connection',
    'sample_schema',
    'sample_table',
    CheckTimeScale.daily,
    client=dqops_client,
    json_body=request_body
)

Execution

from dqops import client
from dqops.client.api.rule_mining import apply_proposed_partitioned_checks
from dqops.client.models import CheckContainerModel, \
                                CheckMiningProposalModel, \
                                CheckModel, \
                                CheckTimeScale, \
                                DefaultRuleSeverityLevel, \
                                FieldModel, \
                                QualityCategoryModel

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

request_body = CheckMiningProposalModel(
    missing_current_statistics=False,
    missing_current_profiling_check_results=False,
    column_checks={

    }
)

call_result = await apply_proposed_partitioned_checks.asyncio(
    'sample_connection',
    'sample_schema',
    'sample_table',
    CheckTimeScale.daily,
    client=dqops_client,
    json_body=request_body
)

Execution

from dqops import client
from dqops.client.api.rule_mining import apply_proposed_partitioned_checks
from dqops.client.models import CheckContainerModel, \
                                CheckMiningProposalModel, \
                                CheckModel, \
                                CheckTimeScale, \
                                DefaultRuleSeverityLevel, \
                                FieldModel, \
                                QualityCategoryModel

token = 's4mp13_4u7h_70k3n'

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

request_body = CheckMiningProposalModel(
    missing_current_statistics=False,
    missing_current_profiling_check_results=False,
    column_checks={

    }
)

call_result = apply_proposed_partitioned_checks.sync(
    'sample_connection',
    'sample_schema',
    'sample_table',
    CheckTimeScale.daily,
    client=dqops_client,
    json_body=request_body
)

Execution

from dqops import client
from dqops.client.api.rule_mining import apply_proposed_partitioned_checks
from dqops.client.models import CheckContainerModel, \
                                CheckMiningProposalModel, \
                                CheckModel, \
                                CheckTimeScale, \
                                DefaultRuleSeverityLevel, \
                                FieldModel, \
                                QualityCategoryModel

token = 's4mp13_4u7h_70k3n'

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

request_body = CheckMiningProposalModel(
    missing_current_statistics=False,
    missing_current_profiling_check_results=False,
    column_checks={

    }
)

call_result = await apply_proposed_partitioned_checks.asyncio(
    'sample_connection',
    'sample_schema',
    'sample_table',
    CheckTimeScale.daily,
    client=dqops_client,
    json_body=request_body
)

---

apply_proposed_profiling_checks

Applies the proposed configuration of data quality profiling checks on a table.

Follow the link to see the source code on GitHub.

PUT

http://localhost:8888/api/connections/{connectionName}/schemas/{schemaName}/tables/{tableName}/profiling/applyproposal

Parameters of this method are described below

Property name	Description	Data type	Required
connection_name	Connection name	string
schema_name	Schema name	string
table_name	Table name	string

Request body

Description	Data type	Required
Proposed configuration of data quality checks to be applied on the table and its columns.	CheckMiningProposalModel

Usage examples

curlPython sync clientPython async clientPython auth sync clientPython auth async client

Execution

curl -X PUT http://localhost:8888/api/connections/sample_connection/schemas/sample_schema/tables/sample_table/profiling/applyproposal^
    -H "Accept: application/json"^
    -H "Content-Type: application/json"^
    -d^
    "{\"missing_current_statistics\":false,\"missing_current_profiling_check_results\":false,\"column_checks\":{}}"

Execution

from dqops import client
from dqops.client.api.rule_mining import apply_proposed_profiling_checks
from dqops.client.models import CheckContainerModel, \
                                CheckMiningProposalModel, \
                                CheckModel, \
                                DefaultRuleSeverityLevel, \
                                FieldModel, \
                                QualityCategoryModel

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

request_body = CheckMiningProposalModel(
    missing_current_statistics=False,
    missing_current_profiling_check_results=False,
    column_checks={

    }
)

call_result = apply_proposed_profiling_checks.sync(
    'sample_connection',
    'sample_schema',
    'sample_table',
    client=dqops_client,
    json_body=request_body
)

Execution

from dqops import client
from dqops.client.api.rule_mining import apply_proposed_profiling_checks
from dqops.client.models import CheckContainerModel, \
                                CheckMiningProposalModel, \
                                CheckModel, \
                                DefaultRuleSeverityLevel, \
                                FieldModel, \
                                QualityCategoryModel

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

request_body = CheckMiningProposalModel(
    missing_current_statistics=False,
    missing_current_profiling_check_results=False,
    column_checks={

    }
)

call_result = await apply_proposed_profiling_checks.asyncio(
    'sample_connection',
    'sample_schema',
    'sample_table',
    client=dqops_client,
    json_body=request_body
)

Execution

from dqops import client
from dqops.client.api.rule_mining import apply_proposed_profiling_checks
from dqops.client.models import CheckContainerModel, \
                                CheckMiningProposalModel, \
                                CheckModel, \
                                DefaultRuleSeverityLevel, \
                                FieldModel, \
                                QualityCategoryModel

token = 's4mp13_4u7h_70k3n'

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

request_body = CheckMiningProposalModel(
    missing_current_statistics=False,
    missing_current_profiling_check_results=False,
    column_checks={

    }
)

call_result = apply_proposed_profiling_checks.sync(
    'sample_connection',
    'sample_schema',
    'sample_table',
    client=dqops_client,
    json_body=request_body
)

Execution

from dqops import client
from dqops.client.api.rule_mining import apply_proposed_profiling_checks
from dqops.client.models import CheckContainerModel, \
                                CheckMiningProposalModel, \
                                CheckModel, \
                                DefaultRuleSeverityLevel, \
                                FieldModel, \
                                QualityCategoryModel

token = 's4mp13_4u7h_70k3n'

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

request_body = CheckMiningProposalModel(
    missing_current_statistics=False,
    missing_current_profiling_check_results=False,
    column_checks={

    }
)

call_result = await apply_proposed_profiling_checks.asyncio(
    'sample_connection',
    'sample_schema',
    'sample_table',
    client=dqops_client,
    json_body=request_body
)

---

propose_table_monitoring_checks

Proposes the configuration of monitoring checks on a table by generating suggested configuration of checks and their rule thresholds.

Follow the link to see the source code on GitHub.

POST

http://localhost:8888/api/connections/{connectionName}/schemas/{schemaName}/tables/{tableName}/monitoring/{timeScale}/propose

Return value

Property name	Description	Data type
check_mining_proposal_model		CheckMiningProposalModel

Parameters of this method are described below

Property name	Description	Data type	Required
connection_name	Connection name	string
schema_name	Schema name	string
table_name	Table name	string
time_scale	Time scale	CheckTimeScale

Request body

Description	Data type	Required
Data quality check mining parameters which configure which rules are analyzed and proposed	CheckMiningParametersModel

Usage examples

curlPython sync clientPython async clientPython auth sync clientPython auth async client

Execution

curl -X POST http://localhost:8888/api/connections/sample_connection/schemas/sample_schema/tables/sample_table/monitoring/daily/propose^
    -H "Accept: application/json"^
    -H "Content-Type: application/json"^
    -d^
    "{\"severity_level\":\"error\",\"copy_failed_profiling_checks\":false,\"copy_disabled_profiling_checks\":false,\"copy_profiling_checks\":true,\"reconfigure_policy_enabled_checks\":true,\"propose_checks_from_statistics\":true,\"propose_minimum_row_count\":true,\"propose_column_count\":true,\"propose_timeliness_checks\":true,\"propose_nulls_checks\":true,\"propose_not_nulls_checks\":false,\"propose_text_values_data_type\":true,\"propose_column_exists\":true,\"propose_uniqueness_checks\":true,\"propose_numeric_ranges\":true,\"propose_percentile_ranges\":true,\"propose_text_length_ranges\":true,\"propose_word_count_ranges\":true,\"propose_values_in_set_checks\":true,\"values_in_set_treat_rare_values_as_invalid\":true,\"propose_top_values_checks\":true,\"propose_text_conversion_checks\":true,\"propose_bool_percent_checks\":true,\"propose_date_checks\":true,\"propose_standard_pattern_checks\":true,\"detect_regular_expressions\":true,\"propose_whitespace_checks\":true,\"apply_pii_checks\":true,\"propose_custom_checks\":true}"

Expand to see the returned result

{
  "missing_current_statistics" : false,
  "missing_current_profiling_check_results" : false,
  "column_checks" : { }
}

Execution

from dqops import client
from dqops.client.api.rule_mining import propose_table_monitoring_checks
from dqops.client.models import CheckMiningParametersModel, \
                                CheckTimeScale, \
                                TargetRuleSeverityLevel

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

request_body = CheckMiningParametersModel(
    severity_level=TargetRuleSeverityLevel.ERROR,
    copy_failed_profiling_checks=False,
    copy_disabled_profiling_checks=False,
    copy_profiling_checks=True,
    reconfigure_policy_enabled_checks=True,
    propose_checks_from_statistics=True,
    propose_minimum_row_count=True,
    propose_column_count=True,
    propose_timeliness_checks=True,
    propose_nulls_checks=True,
    propose_not_nulls_checks=False,
    propose_text_values_data_type=True,
    propose_column_exists=True,
    propose_uniqueness_checks=True,
    propose_numeric_ranges=True,
    propose_percentile_ranges=True,
    propose_text_length_ranges=True,
    propose_word_count_ranges=True,
    propose_values_in_set_checks=True,
    values_in_set_treat_rare_values_as_invalid=True,
    propose_top_values_checks=True,
    propose_text_conversion_checks=True,
    propose_bool_percent_checks=True,
    propose_date_checks=True,
    propose_standard_pattern_checks=True,
    detect_regular_expressions=True,
    propose_whitespace_checks=True,
    apply_pii_checks=True,
    propose_custom_checks=True
)

call_result = propose_table_monitoring_checks.sync(
    'sample_connection',
    'sample_schema',
    'sample_table',
    CheckTimeScale.daily,
    client=dqops_client,
    json_body=request_body
)

Expand to see the returned result

CheckMiningProposalModel(
    missing_current_statistics=False,
    missing_current_profiling_check_results=False,
    column_checks={

    }
)

Execution

from dqops import client
from dqops.client.api.rule_mining import propose_table_monitoring_checks
from dqops.client.models import CheckMiningParametersModel, \
                                CheckTimeScale, \
                                TargetRuleSeverityLevel

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

request_body = CheckMiningParametersModel(
    severity_level=TargetRuleSeverityLevel.ERROR,
    copy_failed_profiling_checks=False,
    copy_disabled_profiling_checks=False,
    copy_profiling_checks=True,
    reconfigure_policy_enabled_checks=True,
    propose_checks_from_statistics=True,
    propose_minimum_row_count=True,
    propose_column_count=True,
    propose_timeliness_checks=True,
    propose_nulls_checks=True,
    propose_not_nulls_checks=False,
    propose_text_values_data_type=True,
    propose_column_exists=True,
    propose_uniqueness_checks=True,
    propose_numeric_ranges=True,
    propose_percentile_ranges=True,
    propose_text_length_ranges=True,
    propose_word_count_ranges=True,
    propose_values_in_set_checks=True,
    values_in_set_treat_rare_values_as_invalid=True,
    propose_top_values_checks=True,
    propose_text_conversion_checks=True,
    propose_bool_percent_checks=True,
    propose_date_checks=True,
    propose_standard_pattern_checks=True,
    detect_regular_expressions=True,
    propose_whitespace_checks=True,
    apply_pii_checks=True,
    propose_custom_checks=True
)

call_result = await propose_table_monitoring_checks.asyncio(
    'sample_connection',
    'sample_schema',
    'sample_table',
    CheckTimeScale.daily,
    client=dqops_client,
    json_body=request_body
)

Expand to see the returned result

CheckMiningProposalModel(
    missing_current_statistics=False,
    missing_current_profiling_check_results=False,
    column_checks={

    }
)

Execution

from dqops import client
from dqops.client.api.rule_mining import propose_table_monitoring_checks
from dqops.client.models import CheckMiningParametersModel, \
                                CheckTimeScale, \
                                TargetRuleSeverityLevel

token = 's4mp13_4u7h_70k3n'

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

request_body = CheckMiningParametersModel(
    severity_level=TargetRuleSeverityLevel.ERROR,
    copy_failed_profiling_checks=False,
    copy_disabled_profiling_checks=False,
    copy_profiling_checks=True,
    reconfigure_policy_enabled_checks=True,
    propose_checks_from_statistics=True,
    propose_minimum_row_count=True,
    propose_column_count=True,
    propose_timeliness_checks=True,
    propose_nulls_checks=True,
    propose_not_nulls_checks=False,
    propose_text_values_data_type=True,
    propose_column_exists=True,
    propose_uniqueness_checks=True,
    propose_numeric_ranges=True,
    propose_percentile_ranges=True,
    propose_text_length_ranges=True,
    propose_word_count_ranges=True,
    propose_values_in_set_checks=True,
    values_in_set_treat_rare_values_as_invalid=True,
    propose_top_values_checks=True,
    propose_text_conversion_checks=True,
    propose_bool_percent_checks=True,
    propose_date_checks=True,
    propose_standard_pattern_checks=True,
    detect_regular_expressions=True,
    propose_whitespace_checks=True,
    apply_pii_checks=True,
    propose_custom_checks=True
)

call_result = propose_table_monitoring_checks.sync(
    'sample_connection',
    'sample_schema',
    'sample_table',
    CheckTimeScale.daily,
    client=dqops_client,
    json_body=request_body
)

Expand to see the returned result

CheckMiningProposalModel(
    missing_current_statistics=False,
    missing_current_profiling_check_results=False,
    column_checks={

    }
)

Execution

from dqops import client
from dqops.client.api.rule_mining import propose_table_monitoring_checks
from dqops.client.models import CheckMiningParametersModel, \
                                CheckTimeScale, \
                                TargetRuleSeverityLevel

token = 's4mp13_4u7h_70k3n'

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

request_body = CheckMiningParametersModel(
    severity_level=TargetRuleSeverityLevel.ERROR,
    copy_failed_profiling_checks=False,
    copy_disabled_profiling_checks=False,
    copy_profiling_checks=True,
    reconfigure_policy_enabled_checks=True,
    propose_checks_from_statistics=True,
    propose_minimum_row_count=True,
    propose_column_count=True,
    propose_timeliness_checks=True,
    propose_nulls_checks=True,
    propose_not_nulls_checks=False,
    propose_text_values_data_type=True,
    propose_column_exists=True,
    propose_uniqueness_checks=True,
    propose_numeric_ranges=True,
    propose_percentile_ranges=True,
    propose_text_length_ranges=True,
    propose_word_count_ranges=True,
    propose_values_in_set_checks=True,
    values_in_set_treat_rare_values_as_invalid=True,
    propose_top_values_checks=True,
    propose_text_conversion_checks=True,
    propose_bool_percent_checks=True,
    propose_date_checks=True,
    propose_standard_pattern_checks=True,
    detect_regular_expressions=True,
    propose_whitespace_checks=True,
    apply_pii_checks=True,
    propose_custom_checks=True
)

call_result = await propose_table_monitoring_checks.asyncio(
    'sample_connection',
    'sample_schema',
    'sample_table',
    CheckTimeScale.daily,
    client=dqops_client,
    json_body=request_body
)

Expand to see the returned result

CheckMiningProposalModel(
    missing_current_statistics=False,
    missing_current_profiling_check_results=False,
    column_checks={

    }
)

---

propose_table_partitioned_checks

Proposes the configuration of partitioned checks on a table by generating suggested configuration of checks and their rule thresholds.

Follow the link to see the source code on GitHub.

POST

http://localhost:8888/api/connections/{connectionName}/schemas/{schemaName}/tables/{tableName}/partitioned/{timeScale}/propose

Return value

Property name	Description	Data type
check_mining_proposal_model		CheckMiningProposalModel

Parameters of this method are described below

Property name	Description	Data type	Required
connection_name	Connection name	string
schema_name	Schema name	string
table_name	Table name	string
time_scale	Time scale	CheckTimeScale

Request body

Description	Data type	Required
Data quality check mining parameters which configure which rules are analyzed and proposed	CheckMiningParametersModel

Usage examples

curlPython sync clientPython async clientPython auth sync clientPython auth async client

Execution

curl -X POST http://localhost:8888/api/connections/sample_connection/schemas/sample_schema/tables/sample_table/partitioned/daily/propose^
    -H "Accept: application/json"^
    -H "Content-Type: application/json"^
    -d^
    "{\"severity_level\":\"error\",\"copy_failed_profiling_checks\":false,\"copy_disabled_profiling_checks\":false,\"copy_profiling_checks\":true,\"reconfigure_policy_enabled_checks\":true,\"propose_checks_from_statistics\":true,\"propose_minimum_row_count\":true,\"propose_column_count\":true,\"propose_timeliness_checks\":true,\"propose_nulls_checks\":true,\"propose_not_nulls_checks\":false,\"propose_text_values_data_type\":true,\"propose_column_exists\":true,\"propose_uniqueness_checks\":true,\"propose_numeric_ranges\":true,\"propose_percentile_ranges\":true,\"propose_text_length_ranges\":true,\"propose_word_count_ranges\":true,\"propose_values_in_set_checks\":true,\"values_in_set_treat_rare_values_as_invalid\":true,\"propose_top_values_checks\":true,\"propose_text_conversion_checks\":true,\"propose_bool_percent_checks\":true,\"propose_date_checks\":true,\"propose_standard_pattern_checks\":true,\"detect_regular_expressions\":true,\"propose_whitespace_checks\":true,\"apply_pii_checks\":true,\"propose_custom_checks\":true}"

Expand to see the returned result

{
  "missing_current_statistics" : false,
  "missing_current_profiling_check_results" : false,
  "column_checks" : { }
}

Execution

from dqops import client
from dqops.client.api.rule_mining import propose_table_partitioned_checks
from dqops.client.models import CheckMiningParametersModel, \
                                CheckTimeScale, \
                                TargetRuleSeverityLevel

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

request_body = CheckMiningParametersModel(
    severity_level=TargetRuleSeverityLevel.ERROR,
    copy_failed_profiling_checks=False,
    copy_disabled_profiling_checks=False,
    copy_profiling_checks=True,
    reconfigure_policy_enabled_checks=True,
    propose_checks_from_statistics=True,
    propose_minimum_row_count=True,
    propose_column_count=True,
    propose_timeliness_checks=True,
    propose_nulls_checks=True,
    propose_not_nulls_checks=False,
    propose_text_values_data_type=True,
    propose_column_exists=True,
    propose_uniqueness_checks=True,
    propose_numeric_ranges=True,
    propose_percentile_ranges=True,
    propose_text_length_ranges=True,
    propose_word_count_ranges=True,
    propose_values_in_set_checks=True,
    values_in_set_treat_rare_values_as_invalid=True,
    propose_top_values_checks=True,
    propose_text_conversion_checks=True,
    propose_bool_percent_checks=True,
    propose_date_checks=True,
    propose_standard_pattern_checks=True,
    detect_regular_expressions=True,
    propose_whitespace_checks=True,
    apply_pii_checks=True,
    propose_custom_checks=True
)

call_result = propose_table_partitioned_checks.sync(
    'sample_connection',
    'sample_schema',
    'sample_table',
    CheckTimeScale.daily,
    client=dqops_client,
    json_body=request_body
)

Expand to see the returned result

CheckMiningProposalModel(
    missing_current_statistics=False,
    missing_current_profiling_check_results=False,
    column_checks={

    }
)

Execution

from dqops import client
from dqops.client.api.rule_mining import propose_table_partitioned_checks
from dqops.client.models import CheckMiningParametersModel, \
                                CheckTimeScale, \
                                TargetRuleSeverityLevel

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

request_body = CheckMiningParametersModel(
    severity_level=TargetRuleSeverityLevel.ERROR,
    copy_failed_profiling_checks=False,
    copy_disabled_profiling_checks=False,
    copy_profiling_checks=True,
    reconfigure_policy_enabled_checks=True,
    propose_checks_from_statistics=True,
    propose_minimum_row_count=True,
    propose_column_count=True,
    propose_timeliness_checks=True,
    propose_nulls_checks=True,
    propose_not_nulls_checks=False,
    propose_text_values_data_type=True,
    propose_column_exists=True,
    propose_uniqueness_checks=True,
    propose_numeric_ranges=True,
    propose_percentile_ranges=True,
    propose_text_length_ranges=True,
    propose_word_count_ranges=True,
    propose_values_in_set_checks=True,
    values_in_set_treat_rare_values_as_invalid=True,
    propose_top_values_checks=True,
    propose_text_conversion_checks=True,
    propose_bool_percent_checks=True,
    propose_date_checks=True,
    propose_standard_pattern_checks=True,
    detect_regular_expressions=True,
    propose_whitespace_checks=True,
    apply_pii_checks=True,
    propose_custom_checks=True
)

call_result = await propose_table_partitioned_checks.asyncio(
    'sample_connection',
    'sample_schema',
    'sample_table',
    CheckTimeScale.daily,
    client=dqops_client,
    json_body=request_body
)

Expand to see the returned result

CheckMiningProposalModel(
    missing_current_statistics=False,
    missing_current_profiling_check_results=False,
    column_checks={

    }
)

Execution

from dqops import client
from dqops.client.api.rule_mining import propose_table_partitioned_checks
from dqops.client.models import CheckMiningParametersModel, \
                                CheckTimeScale, \
                                TargetRuleSeverityLevel

token = 's4mp13_4u7h_70k3n'

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

request_body = CheckMiningParametersModel(
    severity_level=TargetRuleSeverityLevel.ERROR,
    copy_failed_profiling_checks=False,
    copy_disabled_profiling_checks=False,
    copy_profiling_checks=True,
    reconfigure_policy_enabled_checks=True,
    propose_checks_from_statistics=True,
    propose_minimum_row_count=True,
    propose_column_count=True,
    propose_timeliness_checks=True,
    propose_nulls_checks=True,
    propose_not_nulls_checks=False,
    propose_text_values_data_type=True,
    propose_column_exists=True,
    propose_uniqueness_checks=True,
    propose_numeric_ranges=True,
    propose_percentile_ranges=True,
    propose_text_length_ranges=True,
    propose_word_count_ranges=True,
    propose_values_in_set_checks=True,
    values_in_set_treat_rare_values_as_invalid=True,
    propose_top_values_checks=True,
    propose_text_conversion_checks=True,
    propose_bool_percent_checks=True,
    propose_date_checks=True,
    propose_standard_pattern_checks=True,
    detect_regular_expressions=True,
    propose_whitespace_checks=True,
    apply_pii_checks=True,
    propose_custom_checks=True
)

call_result = propose_table_partitioned_checks.sync(
    'sample_connection',
    'sample_schema',
    'sample_table',
    CheckTimeScale.daily,
    client=dqops_client,
    json_body=request_body
)

Expand to see the returned result

CheckMiningProposalModel(
    missing_current_statistics=False,
    missing_current_profiling_check_results=False,
    column_checks={

    }
)

Execution

from dqops import client
from dqops.client.api.rule_mining import propose_table_partitioned_checks
from dqops.client.models import CheckMiningParametersModel, \
                                CheckTimeScale, \
                                TargetRuleSeverityLevel

token = 's4mp13_4u7h_70k3n'

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

request_body = CheckMiningParametersModel(
    severity_level=TargetRuleSeverityLevel.ERROR,
    copy_failed_profiling_checks=False,
    copy_disabled_profiling_checks=False,
    copy_profiling_checks=True,
    reconfigure_policy_enabled_checks=True,
    propose_checks_from_statistics=True,
    propose_minimum_row_count=True,
    propose_column_count=True,
    propose_timeliness_checks=True,
    propose_nulls_checks=True,
    propose_not_nulls_checks=False,
    propose_text_values_data_type=True,
    propose_column_exists=True,
    propose_uniqueness_checks=True,
    propose_numeric_ranges=True,
    propose_percentile_ranges=True,
    propose_text_length_ranges=True,
    propose_word_count_ranges=True,
    propose_values_in_set_checks=True,
    values_in_set_treat_rare_values_as_invalid=True,
    propose_top_values_checks=True,
    propose_text_conversion_checks=True,
    propose_bool_percent_checks=True,
    propose_date_checks=True,
    propose_standard_pattern_checks=True,
    detect_regular_expressions=True,
    propose_whitespace_checks=True,
    apply_pii_checks=True,
    propose_custom_checks=True
)

call_result = await propose_table_partitioned_checks.asyncio(
    'sample_connection',
    'sample_schema',
    'sample_table',
    CheckTimeScale.daily,
    client=dqops_client,
    json_body=request_body
)

Expand to see the returned result

CheckMiningProposalModel(
    missing_current_statistics=False,
    missing_current_profiling_check_results=False,
    column_checks={

    }
)

---

propose_table_profiling_checks

Proposes the configuration of profiling checks on a table by generating suggested configuration of checks and their rule thresholds.

Follow the link to see the source code on GitHub.

POST

http://localhost:8888/api/connections/{connectionName}/schemas/{schemaName}/tables/{tableName}/profiling/propose

Return value

Property name	Description	Data type
check_mining_proposal_model		CheckMiningProposalModel

Parameters of this method are described below

Property name	Description	Data type	Required
connection_name	Connection name	string
schema_name	Schema name	string
table_name	Table name	string

Request body

Description	Data type	Required
Data quality check mining parameters which configure which rules are analyzed and proposed	CheckMiningParametersModel

Usage examples

curlPython sync clientPython async clientPython auth sync clientPython auth async client

Execution

curl -X POST http://localhost:8888/api/connections/sample_connection/schemas/sample_schema/tables/sample_table/profiling/propose^
    -H "Accept: application/json"^
    -H "Content-Type: application/json"^
    -d^
    "{\"severity_level\":\"error\",\"copy_failed_profiling_checks\":false,\"copy_disabled_profiling_checks\":false,\"copy_profiling_checks\":true,\"reconfigure_policy_enabled_checks\":true,\"propose_checks_from_statistics\":true,\"propose_minimum_row_count\":true,\"propose_column_count\":true,\"propose_timeliness_checks\":true,\"propose_nulls_checks\":true,\"propose_not_nulls_checks\":false,\"propose_text_values_data_type\":true,\"propose_column_exists\":true,\"propose_uniqueness_checks\":true,\"propose_numeric_ranges\":true,\"propose_percentile_ranges\":true,\"propose_text_length_ranges\":true,\"propose_word_count_ranges\":true,\"propose_values_in_set_checks\":true,\"values_in_set_treat_rare_values_as_invalid\":true,\"propose_top_values_checks\":true,\"propose_text_conversion_checks\":true,\"propose_bool_percent_checks\":true,\"propose_date_checks\":true,\"propose_standard_pattern_checks\":true,\"detect_regular_expressions\":true,\"propose_whitespace_checks\":true,\"apply_pii_checks\":true,\"propose_custom_checks\":true}"

Expand to see the returned result

{
  "missing_current_statistics" : false,
  "missing_current_profiling_check_results" : false,
  "column_checks" : { }
}

Execution

from dqops import client
from dqops.client.api.rule_mining import propose_table_profiling_checks
from dqops.client.models import CheckMiningParametersModel, \
                                TargetRuleSeverityLevel

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

request_body = CheckMiningParametersModel(
    severity_level=TargetRuleSeverityLevel.ERROR,
    copy_failed_profiling_checks=False,
    copy_disabled_profiling_checks=False,
    copy_profiling_checks=True,
    reconfigure_policy_enabled_checks=True,
    propose_checks_from_statistics=True,
    propose_minimum_row_count=True,
    propose_column_count=True,
    propose_timeliness_checks=True,
    propose_nulls_checks=True,
    propose_not_nulls_checks=False,
    propose_text_values_data_type=True,
    propose_column_exists=True,
    propose_uniqueness_checks=True,
    propose_numeric_ranges=True,
    propose_percentile_ranges=True,
    propose_text_length_ranges=True,
    propose_word_count_ranges=True,
    propose_values_in_set_checks=True,
    values_in_set_treat_rare_values_as_invalid=True,
    propose_top_values_checks=True,
    propose_text_conversion_checks=True,
    propose_bool_percent_checks=True,
    propose_date_checks=True,
    propose_standard_pattern_checks=True,
    detect_regular_expressions=True,
    propose_whitespace_checks=True,
    apply_pii_checks=True,
    propose_custom_checks=True
)

call_result = propose_table_profiling_checks.sync(
    'sample_connection',
    'sample_schema',
    'sample_table',
    client=dqops_client,
    json_body=request_body
)

Expand to see the returned result

CheckMiningProposalModel(
    missing_current_statistics=False,
    missing_current_profiling_check_results=False,
    column_checks={

    }
)

Execution

from dqops import client
from dqops.client.api.rule_mining import propose_table_profiling_checks
from dqops.client.models import CheckMiningParametersModel, \
                                TargetRuleSeverityLevel

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

request_body = CheckMiningParametersModel(
    severity_level=TargetRuleSeverityLevel.ERROR,
    copy_failed_profiling_checks=False,
    copy_disabled_profiling_checks=False,
    copy_profiling_checks=True,
    reconfigure_policy_enabled_checks=True,
    propose_checks_from_statistics=True,
    propose_minimum_row_count=True,
    propose_column_count=True,
    propose_timeliness_checks=True,
    propose_nulls_checks=True,
    propose_not_nulls_checks=False,
    propose_text_values_data_type=True,
    propose_column_exists=True,
    propose_uniqueness_checks=True,
    propose_numeric_ranges=True,
    propose_percentile_ranges=True,
    propose_text_length_ranges=True,
    propose_word_count_ranges=True,
    propose_values_in_set_checks=True,
    values_in_set_treat_rare_values_as_invalid=True,
    propose_top_values_checks=True,
    propose_text_conversion_checks=True,
    propose_bool_percent_checks=True,
    propose_date_checks=True,
    propose_standard_pattern_checks=True,
    detect_regular_expressions=True,
    propose_whitespace_checks=True,
    apply_pii_checks=True,
    propose_custom_checks=True
)

call_result = await propose_table_profiling_checks.asyncio(
    'sample_connection',
    'sample_schema',
    'sample_table',
    client=dqops_client,
    json_body=request_body
)

Expand to see the returned result

CheckMiningProposalModel(
    missing_current_statistics=False,
    missing_current_profiling_check_results=False,
    column_checks={

    }
)

Execution

from dqops import client
from dqops.client.api.rule_mining import propose_table_profiling_checks
from dqops.client.models import CheckMiningParametersModel, \
                                TargetRuleSeverityLevel

token = 's4mp13_4u7h_70k3n'

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

request_body = CheckMiningParametersModel(
    severity_level=TargetRuleSeverityLevel.ERROR,
    copy_failed_profiling_checks=False,
    copy_disabled_profiling_checks=False,
    copy_profiling_checks=True,
    reconfigure_policy_enabled_checks=True,
    propose_checks_from_statistics=True,
    propose_minimum_row_count=True,
    propose_column_count=True,
    propose_timeliness_checks=True,
    propose_nulls_checks=True,
    propose_not_nulls_checks=False,
    propose_text_values_data_type=True,
    propose_column_exists=True,
    propose_uniqueness_checks=True,
    propose_numeric_ranges=True,
    propose_percentile_ranges=True,
    propose_text_length_ranges=True,
    propose_word_count_ranges=True,
    propose_values_in_set_checks=True,
    values_in_set_treat_rare_values_as_invalid=True,
    propose_top_values_checks=True,
    propose_text_conversion_checks=True,
    propose_bool_percent_checks=True,
    propose_date_checks=True,
    propose_standard_pattern_checks=True,
    detect_regular_expressions=True,
    propose_whitespace_checks=True,
    apply_pii_checks=True,
    propose_custom_checks=True
)

call_result = propose_table_profiling_checks.sync(
    'sample_connection',
    'sample_schema',
    'sample_table',
    client=dqops_client,
    json_body=request_body
)

Expand to see the returned result

CheckMiningProposalModel(
    missing_current_statistics=False,
    missing_current_profiling_check_results=False,
    column_checks={

    }
)

Execution

from dqops import client
from dqops.client.api.rule_mining import propose_table_profiling_checks
from dqops.client.models import CheckMiningParametersModel, \
                                TargetRuleSeverityLevel

token = 's4mp13_4u7h_70k3n'

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

request_body = CheckMiningParametersModel(
    severity_level=TargetRuleSeverityLevel.ERROR,
    copy_failed_profiling_checks=False,
    copy_disabled_profiling_checks=False,
    copy_profiling_checks=True,
    reconfigure_policy_enabled_checks=True,
    propose_checks_from_statistics=True,
    propose_minimum_row_count=True,
    propose_column_count=True,
    propose_timeliness_checks=True,
    propose_nulls_checks=True,
    propose_not_nulls_checks=False,
    propose_text_values_data_type=True,
    propose_column_exists=True,
    propose_uniqueness_checks=True,
    propose_numeric_ranges=True,
    propose_percentile_ranges=True,
    propose_text_length_ranges=True,
    propose_word_count_ranges=True,
    propose_values_in_set_checks=True,
    values_in_set_treat_rare_values_as_invalid=True,
    propose_top_values_checks=True,
    propose_text_conversion_checks=True,
    propose_bool_percent_checks=True,
    propose_date_checks=True,
    propose_standard_pattern_checks=True,
    detect_regular_expressions=True,
    propose_whitespace_checks=True,
    apply_pii_checks=True,
    propose_custom_checks=True
)

call_result = await propose_table_profiling_checks.asyncio(
    'sample_connection',
    'sample_schema',
    'sample_table',
    client=dqops_client,
    json_body=request_body
)

Expand to see the returned result

CheckMiningProposalModel(
    missing_current_statistics=False,
    missing_current_profiling_check_results=False,
    column_checks={

    }
)