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AI / ML

AI

pyatlan.model.assets.core.a_i.AI(__pydantic_self__, **data: Any)

Bases: Catalog

Description

Source code in pyatlan/model/assets/core/referenceable.py 
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def __init__(__pydantic_self__, **data: Any) -> None:
    super().__init__(**data)
    __pydantic_self__.__fields_set__.update(["attributes", "type_name"])

Attributes

ETHICAL_AI_ACCOUNTABILITY_CONFIG: KeywordField = KeywordField('ethicalAIAccountabilityConfig', 'ethicalAIAccountabilityConfig') class-attribute

Accountability configuration for ensuring the ethical use of an AI asset

ETHICAL_AI_BIAS_MITIGATION_CONFIG: KeywordField = KeywordField('ethicalAIBiasMitigationConfig', 'ethicalAIBiasMitigationConfig') class-attribute

Bias mitigation configuration for ensuring the ethical use of an AI asset

ETHICAL_AI_ENVIRONMENTAL_CONSCIOUSNESS_CONFIG: KeywordField = KeywordField('ethicalAIEnvironmentalConsciousnessConfig', 'ethicalAIEnvironmentalConsciousnessConfig') class-attribute

Environmental consciousness configuration for ensuring the ethical use of an AI asset

ETHICAL_AI_FAIRNESS_CONFIG: KeywordField = KeywordField('ethicalAIFairnessConfig', 'ethicalAIFairnessConfig') class-attribute

Fairness configuration for ensuring the ethical use of an AI asset

ETHICAL_AI_PRIVACY_CONFIG: KeywordField = KeywordField('ethicalAIPrivacyConfig', 'ethicalAIPrivacyConfig') class-attribute

Privacy configuration for ensuring the ethical use of an AI asset

ETHICAL_AI_RELIABILITY_AND_SAFETY_CONFIG: KeywordField = KeywordField('ethicalAIReliabilityAndSafetyConfig', 'ethicalAIReliabilityAndSafetyConfig') class-attribute

Reliability and safety configuration for ensuring the ethical use of an AI asset

ETHICAL_AI_TRANSPARENCY_CONFIG: KeywordField = KeywordField('ethicalAITransparencyConfig', 'ethicalAITransparencyConfig') class-attribute

Transparency configuration for ensuring the ethical use of an AI asset

AIApplication

pyatlan.model.assets.core.a_i_application.AIApplication(__pydantic_self__, **data: Any)

Bases: AI

Description

Source code in pyatlan/model/assets/core/referenceable.py 
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def __init__(__pydantic_self__, **data: Any) -> None:
    super().__init__(**data)
    __pydantic_self__.__fields_set__.update(["attributes", "type_name"])

Attributes

AI_APPLICATION_DEVELOPMENT_STAGE: KeywordField = KeywordField('aiApplicationDevelopmentStage', 'aiApplicationDevelopmentStage') class-attribute

Development stage of the AI application

AI_APPLICATION_VERSION: KeywordField = KeywordField('aiApplicationVersion', 'aiApplicationVersion') class-attribute

Version of the AI application

MODELS: RelationField = RelationField('models') class-attribute

TBC

AIModel

pyatlan.model.assets.core.a_i_model.AIModel(__pydantic_self__, **data: Any)

Bases: AI

Description

Source code in pyatlan/model/assets/core/referenceable.py 
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def __init__(__pydantic_self__, **data: Any) -> None:
    super().__init__(**data)
    __pydantic_self__.__fields_set__.update(["attributes", "type_name"])

Attributes

AI_MODEL_DATASETS_DSL: TextField = TextField('aiModelDatasetsDSL', 'aiModelDatasetsDSL') class-attribute

Search DSL used to define which assets/datasets are part of the AI model.

AI_MODEL_STATUS: KeywordField = KeywordField('aiModelStatus', 'aiModelStatus') class-attribute

Status of the AI model.

AI_MODEL_VERSION: KeywordField = KeywordField('aiModelVersion', 'aiModelVersion') class-attribute

Version of the AI model.

AI_MODEL_VERSIONS: RelationField = RelationField('aiModelVersions') class-attribute

TBC

APPLICATIONS: RelationField = RelationField('applications') class-attribute

TBC

Functions

processes_batch_save(client, process_list: List[Process]) -> List classmethod

Saves a list of Process objects to Atlan in batches to optimize performance. We save the processes in batches of 20.

:param client: Atlan client instance for making API calls :param process_list: list of Process objects to save :returns: list of API responses from each batch save operation

Source code in pyatlan/model/assets/core/a_i_model.py 
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@classmethod
def processes_batch_save(cls, client, process_list: List[Process]) -> List:
    """
    Saves a list of Process objects to Atlan in batches to optimize performance.
    We save the processes in batches of 20.

    :param client: Atlan client instance for making API calls
    :param process_list: list of Process objects to save
    :returns: list of API responses from each batch save operation
    """
    batch_size = 20
    total_processes = len(process_list)
    responses = []

    for i in range(0, total_processes, batch_size):
        batch = process_list[i : i + batch_size]
        response = client.asset.save(batch)
        responses.append(response)

    return responses

processes_creator(ai_model: AIModel, dataset_dict: Dict[AIDatasetType, list]) -> List[Process] classmethod

Creates a list of Process objects representing the relationships between an AI model and its datasets.

:param ai_model: the AI model for which to create processes :param dataset_dict: dictionary mapping AI dataset types to lists of assets :returns: list of Process objects representing the AI model's data lineage :raises ValueError: when the AI model is missing required attributes (guid or name)

Source code in pyatlan/model/assets/core/a_i_model.py 
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@classmethod
def processes_creator(
    cls,
    ai_model: AIModel,
    dataset_dict: Dict[AIDatasetType, list],
) -> List[Process]:
    """
    Creates a list of Process objects representing the relationships between an AI model and its datasets.

    :param ai_model: the AI model for which to create processes
    :param dataset_dict: dictionary mapping AI dataset types to lists of assets
    :returns: list of Process objects representing the AI model's data lineage
    :raises ValueError: when the AI model is missing required attributes (guid or name)
    """
    if not ai_model.guid or not ai_model.name:
        raise ValueError("AI model must have both guid and name attributes")
    process_list = []
    for key, value_list in dataset_dict.items():
        for value in value_list:
            asset_type = Asset._convert_to_real_type_(value)
            if key == AIDatasetType.OUTPUT:
                process_name = f"{ai_model.name} -> {value.name}"
                process_created = Process.creator(
                    name=process_name,
                    connection_qualified_name="default/ai/dataset",
                    inputs=[AIModel.ref_by_guid(guid=ai_model.guid)],
                    outputs=[asset_type.ref_by_guid(guid=value.guid)],  # type: ignore
                    extra_hash_params={key.value},
                )
                process_created.ai_dataset_type = key
            else:
                process_name = f"{value.name} -> {ai_model.name}"
                process_created = Process.creator(
                    name=process_name,
                    connection_qualified_name="default/ai/dataset",
                    inputs=[asset_type.ref_by_guid(guid=value.guid)],  # type: ignore
                    outputs=[AIModel.ref_by_guid(guid=ai_model.guid)],
                    extra_hash_params={key.value},
                )
                process_created.ai_dataset_type = key
            process_list.append(process_created)

    return process_list

AIModelVersion

pyatlan.model.assets.core.a_i_model_version.AIModelVersion(__pydantic_self__, **data: Any)

Bases: AI

Description

Source code in pyatlan/model/assets/core/referenceable.py 
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def __init__(__pydantic_self__, **data: Any) -> None:
    super().__init__(**data)
    __pydantic_self__.__fields_set__.update(["attributes", "type_name"])

Attributes

AI_MODEL: RelationField = RelationField('aiModel') class-attribute

TBC

AI_MODEL_QUALIFIED_NAME: KeywordField = KeywordField('aiModelQualifiedName', 'aiModelQualifiedName') class-attribute

Unique name of the AI model to which this version belongs, used to navigate from a version back to its parent model.

AI_MODEL_VERSION_METRICS: KeywordField = KeywordField('aiModelVersionMetrics', 'aiModelVersionMetrics') class-attribute

Evaluation and performance metrics recorded for this AI model version, stored as key-value pairs (e.g. accuracy, F1 score, precision, recall).

AI_MODEL_VERSION_STAGE: KeywordField = KeywordField('aiModelVersionStage', 'aiModelVersionStage') class-attribute

Lifecycle deployment stage of this AI model version, indicating its readiness for production use.

DatabricksAIModelContext

pyatlan.model.assets.core.databricks_a_i_model_context.DatabricksAIModelContext(__pydantic_self__, **data: Any)

Bases: AIModel

Description

Source code in pyatlan/model/assets/core/referenceable.py 
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def __init__(__pydantic_self__, **data: Any) -> None:
    super().__init__(**data)
    __pydantic_self__.__fields_set__.update(["attributes", "type_name"])

Attributes

AI_MODEL_DATASETS_DSL: TextField = TextField('aiModelDatasetsDSL', 'aiModelDatasetsDSL') class-attribute

Search DSL used to define which assets/datasets are part of the AI model.

AI_MODEL_STATUS: KeywordField = KeywordField('aiModelStatus', 'aiModelStatus') class-attribute

Status of the AI model.

AI_MODEL_VERSION: KeywordField = KeywordField('aiModelVersion', 'aiModelVersion') class-attribute

Version of the AI model.

CALCULATION_VIEW_NAME: KeywordTextField = KeywordTextField('calculationViewName', 'calculationViewName.keyword', 'calculationViewName') class-attribute

Simple name of the calculation view in which this SQL asset exists, or empty if it does not exist within a calculation view.

CALCULATION_VIEW_QUALIFIED_NAME: KeywordField = KeywordField('calculationViewQualifiedName', 'calculationViewQualifiedName') class-attribute

Unique name of the calculation view in which this SQL asset exists, or empty if it does not exist within a calculation view.

CATALOG_DATASET_GUID: KeywordField = KeywordField('catalogDatasetGuid', 'catalogDatasetGuid') class-attribute

Unique identifier of the dataset this asset belongs to.

DATABASE_NAME: KeywordTextField = KeywordTextField('databaseName', 'databaseName.keyword', 'databaseName') class-attribute

Simple name of the database in which this SQL asset exists, or empty if it does not exist within a database.

DATABASE_QUALIFIED_NAME: KeywordField = KeywordField('databaseQualifiedName', 'databaseQualifiedName') class-attribute

Unique name of the database in which this SQL asset exists, or empty if it does not exist within a database.

DATABRICKS_AI_MODEL_CONTEXT_METASTORE_ID: KeywordField = KeywordField('databricksAIModelContextMetastoreId', 'databricksAIModelContextMetastoreId') class-attribute

The id of the model, common across versions.

DATABRICKS_AI_MODEL_SCHEMA: RelationField = RelationField('databricksAIModelSchema') class-attribute

TBC

DATABRICKS_AI_MODEL_VERSIONS: RelationField = RelationField('databricksAIModelVersions') class-attribute

TBC

DBT_MODELS: RelationField = RelationField('dbtModels') class-attribute

TBC

DBT_SEED_ASSETS: RelationField = RelationField('dbtSeedAssets') class-attribute

TBC

DBT_SOURCES: RelationField = RelationField('dbtSources') class-attribute

TBC

DBT_TESTS: RelationField = RelationField('dbtTests') class-attribute

TBC

ETHICAL_AI_ACCOUNTABILITY_CONFIG: KeywordField = KeywordField('ethicalAIAccountabilityConfig', 'ethicalAIAccountabilityConfig') class-attribute

Accountability configuration for ensuring the ethical use of an AI asset

ETHICAL_AI_BIAS_MITIGATION_CONFIG: KeywordField = KeywordField('ethicalAIBiasMitigationConfig', 'ethicalAIBiasMitigationConfig') class-attribute

Bias mitigation configuration for ensuring the ethical use of an AI asset

ETHICAL_AI_ENVIRONMENTAL_CONSCIOUSNESS_CONFIG: KeywordField = KeywordField('ethicalAIEnvironmentalConsciousnessConfig', 'ethicalAIEnvironmentalConsciousnessConfig') class-attribute

Environmental consciousness configuration for ensuring the ethical use of an AI asset

ETHICAL_AI_FAIRNESS_CONFIG: KeywordField = KeywordField('ethicalAIFairnessConfig', 'ethicalAIFairnessConfig') class-attribute

Fairness configuration for ensuring the ethical use of an AI asset

ETHICAL_AI_PRIVACY_CONFIG: KeywordField = KeywordField('ethicalAIPrivacyConfig', 'ethicalAIPrivacyConfig') class-attribute

Privacy configuration for ensuring the ethical use of an AI asset

ETHICAL_AI_RELIABILITY_AND_SAFETY_CONFIG: KeywordField = KeywordField('ethicalAIReliabilityAndSafetyConfig', 'ethicalAIReliabilityAndSafetyConfig') class-attribute

Reliability and safety configuration for ensuring the ethical use of an AI asset

ETHICAL_AI_TRANSPARENCY_CONFIG: KeywordField = KeywordField('ethicalAITransparencyConfig', 'ethicalAITransparencyConfig') class-attribute

Transparency configuration for ensuring the ethical use of an AI asset

IS_PROFILED: BooleanField = BooleanField('isProfiled', 'isProfiled') class-attribute

Whether this asset has been profiled (true) or not (false).

LAST_PROFILED_AT: NumericField = NumericField('lastProfiledAt', 'lastProfiledAt') class-attribute

Time (epoch) at which this asset was last profiled, in milliseconds.

QUERY_COUNT: NumericField = NumericField('queryCount', 'queryCount') class-attribute

Number of times this asset has been queried.

QUERY_COUNT_UPDATED_AT: NumericField = NumericField('queryCountUpdatedAt', 'queryCountUpdatedAt') class-attribute

Time (epoch) at which the query count was last updated, in milliseconds.

QUERY_USER_COUNT: NumericField = NumericField('queryUserCount', 'queryUserCount') class-attribute

Number of unique users who have queried this asset.

QUERY_USER_MAP: KeywordField = KeywordField('queryUserMap', 'queryUserMap') class-attribute

Map of unique users who have queried this asset to the number of times they have queried it.

SCHEMA_NAME: KeywordTextField = KeywordTextField('schemaName', 'schemaName.keyword', 'schemaName') class-attribute

Simple name of the schema in which this SQL asset exists, or empty if it does not exist within a schema.

SCHEMA_QUALIFIED_NAME: KeywordField = KeywordField('schemaQualifiedName', 'schemaQualifiedName') class-attribute

Unique name of the schema in which this SQL asset exists, or empty if it does not exist within a schema.

SNOWFLAKE_SEMANTIC_LOGICAL_TABLES: RelationField = RelationField('snowflakeSemanticLogicalTables') class-attribute

TBC

SQL_AI_INSIGHTS_LAST_ANALYZED_AT: NumericField = NumericField('sqlAiInsightsLastAnalyzedAt', 'sqlAiInsightsLastAnalyzedAt') class-attribute

Time (epoch) at which this asset was last analyzed for AI insights, in milliseconds.

Number of popular business questions associated with this asset.

Number of popular filter patterns associated with this asset.

Number of popular join patterns associated with this asset.

SQL_AI_INSIGHTS_RELATIONSHIP_COUNT: NumericField = NumericField('sqlAiInsightsRelationshipCount', 'sqlAiInsightsRelationshipCount') class-attribute

Number of relationship insights associated with this asset.

SQL_AI_MODEL_CONTEXT_QUALIFIED_NAME: KeywordField = KeywordField('sqlAIModelContextQualifiedName', 'sqlAIModelContextQualifiedName') class-attribute

Unique name of the context in which the model versions exist, or empty if it does not exist within an AI model context.

SQL_DBT_MODELS: RelationField = RelationField('sqlDbtModels') class-attribute

TBC

SQL_DBT_SOURCES: RelationField = RelationField('sqlDBTSources') class-attribute

TBC

SQL_HAS_AI_INSIGHTS: BooleanField = BooleanField('sqlHasAiInsights', 'sqlHasAiInsights') class-attribute

Whether this asset has any AI insights data available.

SQL_INSIGHT_BUSINESS_QUESTIONS: RelationField = RelationField('sqlInsightBusinessQuestions') class-attribute

TBC

SQL_INSIGHT_INCOMING_JOINS: RelationField = RelationField('sqlInsightIncomingJoins') class-attribute

TBC

SQL_INSIGHT_OUTGOING_JOINS: RelationField = RelationField('sqlInsightOutgoingJoins') class-attribute

TBC

SQL_IS_SECURE: BooleanField = BooleanField('sqlIsSecure', 'sqlIsSecure') class-attribute

Whether this asset is secure (true) or not (false).

TABLE_NAME: KeywordTextField = KeywordTextField('tableName', 'tableName.keyword', 'tableName') class-attribute

Simple name of the table in which this SQL asset exists, or empty if it does not exist within a table.

TABLE_QUALIFIED_NAME: KeywordField = KeywordField('tableQualifiedName', 'tableQualifiedName') class-attribute

Unique name of the table in which this SQL asset exists, or empty if it does not exist within a table.

VIEW_NAME: KeywordTextField = KeywordTextField('viewName', 'viewName.keyword', 'viewName') class-attribute

Simple name of the view in which this SQL asset exists, or empty if it does not exist within a view.

VIEW_QUALIFIED_NAME: KeywordField = KeywordField('viewQualifiedName', 'viewQualifiedName') class-attribute

Unique name of the view in which this SQL asset exists, or empty if it does not exist within a view.

DatabricksAIModelVersion

pyatlan.model.assets.core.databricks_a_i_model_version.DatabricksAIModelVersion(__pydantic_self__, **data: Any)

Bases: AIModelVersion

Description

Source code in pyatlan/model/assets/core/referenceable.py 
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def __init__(__pydantic_self__, **data: Any) -> None:
    super().__init__(**data)
    __pydantic_self__.__fields_set__.update(["attributes", "type_name"])

Attributes

AI_MODEL_QUALIFIED_NAME: KeywordField = KeywordField('aiModelQualifiedName', 'aiModelQualifiedName') class-attribute

Unique name of the AI model to which this version belongs, used to navigate from a version back to its parent model.

AI_MODEL_VERSION_METRICS: KeywordField = KeywordField('aiModelVersionMetrics', 'aiModelVersionMetrics') class-attribute

Evaluation and performance metrics recorded for this AI model version, stored as key-value pairs (e.g. accuracy, F1 score, precision, recall).

AI_MODEL_VERSION_STAGE: KeywordField = KeywordField('aiModelVersionStage', 'aiModelVersionStage') class-attribute

Lifecycle deployment stage of this AI model version, indicating its readiness for production use.

CALCULATION_VIEW_NAME: KeywordTextField = KeywordTextField('calculationViewName', 'calculationViewName.keyword', 'calculationViewName') class-attribute

Simple name of the calculation view in which this SQL asset exists, or empty if it does not exist within a calculation view.

CALCULATION_VIEW_QUALIFIED_NAME: KeywordField = KeywordField('calculationViewQualifiedName', 'calculationViewQualifiedName') class-attribute

Unique name of the calculation view in which this SQL asset exists, or empty if it does not exist within a calculation view.

CATALOG_DATASET_GUID: KeywordField = KeywordField('catalogDatasetGuid', 'catalogDatasetGuid') class-attribute

Unique identifier of the dataset this asset belongs to.

DATABASE_NAME: KeywordTextField = KeywordTextField('databaseName', 'databaseName.keyword', 'databaseName') class-attribute

Simple name of the database in which this SQL asset exists, or empty if it does not exist within a database.

DATABASE_QUALIFIED_NAME: KeywordField = KeywordField('databaseQualifiedName', 'databaseQualifiedName') class-attribute

Unique name of the database in which this SQL asset exists, or empty if it does not exist within a database.

DATABRICKS_AI_MODEL_CONTEXT: RelationField = RelationField('databricksAIModelContext') class-attribute

TBC

DATABRICKS_AI_MODEL_VERSION_ALIASES: KeywordField = KeywordField('databricksAIModelVersionAliases', 'databricksAIModelVersionAliases') class-attribute

The aliases of the model.

DATABRICKS_AI_MODEL_VERSION_ARTIFACT_URI: KeywordField = KeywordField('databricksAIModelVersionArtifactUri', 'databricksAIModelVersionArtifactUri') class-attribute

Artifact uri for the model.

DATABRICKS_AI_MODEL_VERSION_DATASET_COUNT: NumericField = NumericField('databricksAIModelVersionDatasetCount', 'databricksAIModelVersionDatasetCount') class-attribute

Number of datasets.

DATABRICKS_AI_MODEL_VERSION_ID: NumericField = NumericField('databricksAIModelVersionId', 'databricksAIModelVersionId') class-attribute

The id of the model, unique to every version.

DATABRICKS_AI_MODEL_VERSION_METRICS: KeywordField = KeywordField('databricksAIModelVersionMetrics', 'databricksAIModelVersionMetrics') class-attribute

Metrics for an individual experiment.

DATABRICKS_AI_MODEL_VERSION_PARAMS: KeywordField = KeywordField('databricksAIModelVersionParams', 'databricksAIModelVersionParams') class-attribute

Params with key mapped to value for an individual experiment.

DATABRICKS_AI_MODEL_VERSION_RUN_END_TIME: NumericField = NumericField('databricksAIModelVersionRunEndTime', 'databricksAIModelVersionRunEndTime') class-attribute

The run end time of the model.

DATABRICKS_AI_MODEL_VERSION_RUN_ID: KeywordField = KeywordField('databricksAIModelVersionRunId', 'databricksAIModelVersionRunId') class-attribute

The run id of the model.

DATABRICKS_AI_MODEL_VERSION_RUN_NAME: KeywordField = KeywordField('databricksAIModelVersionRunName', 'databricksAIModelVersionRunName') class-attribute

The run name of the model.

DATABRICKS_AI_MODEL_VERSION_RUN_START_TIME: NumericField = NumericField('databricksAIModelVersionRunStartTime', 'databricksAIModelVersionRunStartTime') class-attribute

The run start time of the model.

DATABRICKS_AI_MODEL_VERSION_SOURCE: KeywordField = KeywordField('databricksAIModelVersionSource', 'databricksAIModelVersionSource') class-attribute

Source artifact link for the model.

DATABRICKS_AI_MODEL_VERSION_STATUS: KeywordField = KeywordField('databricksAIModelVersionStatus', 'databricksAIModelVersionStatus') class-attribute

The status of the model.

DBT_MODELS: RelationField = RelationField('dbtModels') class-attribute

TBC

DBT_SEED_ASSETS: RelationField = RelationField('dbtSeedAssets') class-attribute

TBC

DBT_SOURCES: RelationField = RelationField('dbtSources') class-attribute

TBC

DBT_TESTS: RelationField = RelationField('dbtTests') class-attribute

TBC

ETHICAL_AI_ACCOUNTABILITY_CONFIG: KeywordField = KeywordField('ethicalAIAccountabilityConfig', 'ethicalAIAccountabilityConfig') class-attribute

Accountability configuration for ensuring the ethical use of an AI asset

ETHICAL_AI_BIAS_MITIGATION_CONFIG: KeywordField = KeywordField('ethicalAIBiasMitigationConfig', 'ethicalAIBiasMitigationConfig') class-attribute

Bias mitigation configuration for ensuring the ethical use of an AI asset

ETHICAL_AI_ENVIRONMENTAL_CONSCIOUSNESS_CONFIG: KeywordField = KeywordField('ethicalAIEnvironmentalConsciousnessConfig', 'ethicalAIEnvironmentalConsciousnessConfig') class-attribute

Environmental consciousness configuration for ensuring the ethical use of an AI asset

ETHICAL_AI_FAIRNESS_CONFIG: KeywordField = KeywordField('ethicalAIFairnessConfig', 'ethicalAIFairnessConfig') class-attribute

Fairness configuration for ensuring the ethical use of an AI asset

ETHICAL_AI_PRIVACY_CONFIG: KeywordField = KeywordField('ethicalAIPrivacyConfig', 'ethicalAIPrivacyConfig') class-attribute

Privacy configuration for ensuring the ethical use of an AI asset

ETHICAL_AI_RELIABILITY_AND_SAFETY_CONFIG: KeywordField = KeywordField('ethicalAIReliabilityAndSafetyConfig', 'ethicalAIReliabilityAndSafetyConfig') class-attribute

Reliability and safety configuration for ensuring the ethical use of an AI asset

ETHICAL_AI_TRANSPARENCY_CONFIG: KeywordField = KeywordField('ethicalAITransparencyConfig', 'ethicalAITransparencyConfig') class-attribute

Transparency configuration for ensuring the ethical use of an AI asset

IS_PROFILED: BooleanField = BooleanField('isProfiled', 'isProfiled') class-attribute

Whether this asset has been profiled (true) or not (false).

LAST_PROFILED_AT: NumericField = NumericField('lastProfiledAt', 'lastProfiledAt') class-attribute

Time (epoch) at which this asset was last profiled, in milliseconds.

QUERY_COUNT: NumericField = NumericField('queryCount', 'queryCount') class-attribute

Number of times this asset has been queried.

QUERY_COUNT_UPDATED_AT: NumericField = NumericField('queryCountUpdatedAt', 'queryCountUpdatedAt') class-attribute

Time (epoch) at which the query count was last updated, in milliseconds.

QUERY_USER_COUNT: NumericField = NumericField('queryUserCount', 'queryUserCount') class-attribute

Number of unique users who have queried this asset.

QUERY_USER_MAP: KeywordField = KeywordField('queryUserMap', 'queryUserMap') class-attribute

Map of unique users who have queried this asset to the number of times they have queried it.

SCHEMA_NAME: KeywordTextField = KeywordTextField('schemaName', 'schemaName.keyword', 'schemaName') class-attribute

Simple name of the schema in which this SQL asset exists, or empty if it does not exist within a schema.

SCHEMA_QUALIFIED_NAME: KeywordField = KeywordField('schemaQualifiedName', 'schemaQualifiedName') class-attribute

Unique name of the schema in which this SQL asset exists, or empty if it does not exist within a schema.

SNOWFLAKE_SEMANTIC_LOGICAL_TABLES: RelationField = RelationField('snowflakeSemanticLogicalTables') class-attribute

TBC

SQL_AI_INSIGHTS_LAST_ANALYZED_AT: NumericField = NumericField('sqlAiInsightsLastAnalyzedAt', 'sqlAiInsightsLastAnalyzedAt') class-attribute

Time (epoch) at which this asset was last analyzed for AI insights, in milliseconds.

Number of popular business questions associated with this asset.

Number of popular filter patterns associated with this asset.

Number of popular join patterns associated with this asset.

SQL_AI_INSIGHTS_RELATIONSHIP_COUNT: NumericField = NumericField('sqlAiInsightsRelationshipCount', 'sqlAiInsightsRelationshipCount') class-attribute

Number of relationship insights associated with this asset.

SQL_AI_MODEL_CONTEXT_QUALIFIED_NAME: KeywordField = KeywordField('sqlAIModelContextQualifiedName', 'sqlAIModelContextQualifiedName') class-attribute

Unique name of the context in which the model versions exist, or empty if it does not exist within an AI model context.

SQL_DBT_MODELS: RelationField = RelationField('sqlDbtModels') class-attribute

TBC

SQL_DBT_SOURCES: RelationField = RelationField('sqlDBTSources') class-attribute

TBC

SQL_HAS_AI_INSIGHTS: BooleanField = BooleanField('sqlHasAiInsights', 'sqlHasAiInsights') class-attribute

Whether this asset has any AI insights data available.

SQL_INSIGHT_BUSINESS_QUESTIONS: RelationField = RelationField('sqlInsightBusinessQuestions') class-attribute

TBC

SQL_INSIGHT_INCOMING_JOINS: RelationField = RelationField('sqlInsightIncomingJoins') class-attribute

TBC

SQL_INSIGHT_OUTGOING_JOINS: RelationField = RelationField('sqlInsightOutgoingJoins') class-attribute

TBC

SQL_IS_SECURE: BooleanField = BooleanField('sqlIsSecure', 'sqlIsSecure') class-attribute

Whether this asset is secure (true) or not (false).

TABLE_NAME: KeywordTextField = KeywordTextField('tableName', 'tableName.keyword', 'tableName') class-attribute

Simple name of the table in which this SQL asset exists, or empty if it does not exist within a table.

TABLE_QUALIFIED_NAME: KeywordField = KeywordField('tableQualifiedName', 'tableQualifiedName') class-attribute

Unique name of the table in which this SQL asset exists, or empty if it does not exist within a table.

VIEW_NAME: KeywordTextField = KeywordTextField('viewName', 'viewName.keyword', 'viewName') class-attribute

Simple name of the view in which this SQL asset exists, or empty if it does not exist within a view.

VIEW_QUALIFIED_NAME: KeywordField = KeywordField('viewQualifiedName', 'viewQualifiedName') class-attribute

Unique name of the view in which this SQL asset exists, or empty if it does not exist within a view.

SnowflakeAIModelContext

pyatlan.model.assets.core.snowflake_a_i_model_context.SnowflakeAIModelContext(__pydantic_self__, **data: Any)

Bases: AIModel

Description

Source code in pyatlan/model/assets/core/referenceable.py 
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def __init__(__pydantic_self__, **data: Any) -> None:
    super().__init__(**data)
    __pydantic_self__.__fields_set__.update(["attributes", "type_name"])

Attributes

AI_MODEL_DATASETS_DSL: TextField = TextField('aiModelDatasetsDSL', 'aiModelDatasetsDSL') class-attribute

Search DSL used to define which assets/datasets are part of the AI model.

AI_MODEL_STATUS: KeywordField = KeywordField('aiModelStatus', 'aiModelStatus') class-attribute

Status of the AI model.

AI_MODEL_VERSION: KeywordField = KeywordField('aiModelVersion', 'aiModelVersion') class-attribute

Version of the AI model.

CALCULATION_VIEW_NAME: KeywordTextField = KeywordTextField('calculationViewName', 'calculationViewName.keyword', 'calculationViewName') class-attribute

Simple name of the calculation view in which this SQL asset exists, or empty if it does not exist within a calculation view.

CALCULATION_VIEW_QUALIFIED_NAME: KeywordField = KeywordField('calculationViewQualifiedName', 'calculationViewQualifiedName') class-attribute

Unique name of the calculation view in which this SQL asset exists, or empty if it does not exist within a calculation view.

CATALOG_DATASET_GUID: KeywordField = KeywordField('catalogDatasetGuid', 'catalogDatasetGuid') class-attribute

Unique identifier of the dataset this asset belongs to.

DATABASE_NAME: KeywordTextField = KeywordTextField('databaseName', 'databaseName.keyword', 'databaseName') class-attribute

Simple name of the database in which this SQL asset exists, or empty if it does not exist within a database.

DATABASE_QUALIFIED_NAME: KeywordField = KeywordField('databaseQualifiedName', 'databaseQualifiedName') class-attribute

Unique name of the database in which this SQL asset exists, or empty if it does not exist within a database.

DBT_MODELS: RelationField = RelationField('dbtModels') class-attribute

TBC

DBT_SEED_ASSETS: RelationField = RelationField('dbtSeedAssets') class-attribute

TBC

DBT_SOURCES: RelationField = RelationField('dbtSources') class-attribute

TBC

DBT_TESTS: RelationField = RelationField('dbtTests') class-attribute

TBC

ETHICAL_AI_ACCOUNTABILITY_CONFIG: KeywordField = KeywordField('ethicalAIAccountabilityConfig', 'ethicalAIAccountabilityConfig') class-attribute

Accountability configuration for ensuring the ethical use of an AI asset

ETHICAL_AI_BIAS_MITIGATION_CONFIG: KeywordField = KeywordField('ethicalAIBiasMitigationConfig', 'ethicalAIBiasMitigationConfig') class-attribute

Bias mitigation configuration for ensuring the ethical use of an AI asset

ETHICAL_AI_ENVIRONMENTAL_CONSCIOUSNESS_CONFIG: KeywordField = KeywordField('ethicalAIEnvironmentalConsciousnessConfig', 'ethicalAIEnvironmentalConsciousnessConfig') class-attribute

Environmental consciousness configuration for ensuring the ethical use of an AI asset

ETHICAL_AI_FAIRNESS_CONFIG: KeywordField = KeywordField('ethicalAIFairnessConfig', 'ethicalAIFairnessConfig') class-attribute

Fairness configuration for ensuring the ethical use of an AI asset

ETHICAL_AI_PRIVACY_CONFIG: KeywordField = KeywordField('ethicalAIPrivacyConfig', 'ethicalAIPrivacyConfig') class-attribute

Privacy configuration for ensuring the ethical use of an AI asset

ETHICAL_AI_RELIABILITY_AND_SAFETY_CONFIG: KeywordField = KeywordField('ethicalAIReliabilityAndSafetyConfig', 'ethicalAIReliabilityAndSafetyConfig') class-attribute

Reliability and safety configuration for ensuring the ethical use of an AI asset

ETHICAL_AI_TRANSPARENCY_CONFIG: KeywordField = KeywordField('ethicalAITransparencyConfig', 'ethicalAITransparencyConfig') class-attribute

Transparency configuration for ensuring the ethical use of an AI asset

IS_PROFILED: BooleanField = BooleanField('isProfiled', 'isProfiled') class-attribute

Whether this asset has been profiled (true) or not (false).

LAST_PROFILED_AT: NumericField = NumericField('lastProfiledAt', 'lastProfiledAt') class-attribute

Time (epoch) at which this asset was last profiled, in milliseconds.

QUERY_COUNT: NumericField = NumericField('queryCount', 'queryCount') class-attribute

Number of times this asset has been queried.

QUERY_COUNT_UPDATED_AT: NumericField = NumericField('queryCountUpdatedAt', 'queryCountUpdatedAt') class-attribute

Time (epoch) at which the query count was last updated, in milliseconds.

QUERY_USER_COUNT: NumericField = NumericField('queryUserCount', 'queryUserCount') class-attribute

Number of unique users who have queried this asset.

QUERY_USER_MAP: KeywordField = KeywordField('queryUserMap', 'queryUserMap') class-attribute

Map of unique users who have queried this asset to the number of times they have queried it.

SCHEMA_NAME: KeywordTextField = KeywordTextField('schemaName', 'schemaName.keyword', 'schemaName') class-attribute

Simple name of the schema in which this SQL asset exists, or empty if it does not exist within a schema.

SCHEMA_QUALIFIED_NAME: KeywordField = KeywordField('schemaQualifiedName', 'schemaQualifiedName') class-attribute

Unique name of the schema in which this SQL asset exists, or empty if it does not exist within a schema.

SNOWFLAKE_AI_MODEL_SCHEMA: RelationField = RelationField('snowflakeAIModelSchema') class-attribute

TBC

SNOWFLAKE_AI_MODEL_VERSIONS: RelationField = RelationField('snowflakeAIModelVersions') class-attribute

TBC

SNOWFLAKE_SEMANTIC_LOGICAL_TABLES: RelationField = RelationField('snowflakeSemanticLogicalTables') class-attribute

TBC

SQL_AI_INSIGHTS_LAST_ANALYZED_AT: NumericField = NumericField('sqlAiInsightsLastAnalyzedAt', 'sqlAiInsightsLastAnalyzedAt') class-attribute

Time (epoch) at which this asset was last analyzed for AI insights, in milliseconds.

Number of popular business questions associated with this asset.

Number of popular filter patterns associated with this asset.

Number of popular join patterns associated with this asset.

SQL_AI_INSIGHTS_RELATIONSHIP_COUNT: NumericField = NumericField('sqlAiInsightsRelationshipCount', 'sqlAiInsightsRelationshipCount') class-attribute

Number of relationship insights associated with this asset.

SQL_AI_MODEL_CONTEXT_QUALIFIED_NAME: KeywordField = KeywordField('sqlAIModelContextQualifiedName', 'sqlAIModelContextQualifiedName') class-attribute

Unique name of the context in which the model versions exist, or empty if it does not exist within an AI model context.

SQL_DBT_MODELS: RelationField = RelationField('sqlDbtModels') class-attribute

TBC

SQL_DBT_SOURCES: RelationField = RelationField('sqlDBTSources') class-attribute

TBC

SQL_HAS_AI_INSIGHTS: BooleanField = BooleanField('sqlHasAiInsights', 'sqlHasAiInsights') class-attribute

Whether this asset has any AI insights data available.

SQL_INSIGHT_BUSINESS_QUESTIONS: RelationField = RelationField('sqlInsightBusinessQuestions') class-attribute

TBC

SQL_INSIGHT_INCOMING_JOINS: RelationField = RelationField('sqlInsightIncomingJoins') class-attribute

TBC

SQL_INSIGHT_OUTGOING_JOINS: RelationField = RelationField('sqlInsightOutgoingJoins') class-attribute

TBC

SQL_IS_SECURE: BooleanField = BooleanField('sqlIsSecure', 'sqlIsSecure') class-attribute

Whether this asset is secure (true) or not (false).

TABLE_NAME: KeywordTextField = KeywordTextField('tableName', 'tableName.keyword', 'tableName') class-attribute

Simple name of the table in which this SQL asset exists, or empty if it does not exist within a table.

TABLE_QUALIFIED_NAME: KeywordField = KeywordField('tableQualifiedName', 'tableQualifiedName') class-attribute

Unique name of the table in which this SQL asset exists, or empty if it does not exist within a table.

VIEW_NAME: KeywordTextField = KeywordTextField('viewName', 'viewName.keyword', 'viewName') class-attribute

Simple name of the view in which this SQL asset exists, or empty if it does not exist within a view.

VIEW_QUALIFIED_NAME: KeywordField = KeywordField('viewQualifiedName', 'viewQualifiedName') class-attribute

Unique name of the view in which this SQL asset exists, or empty if it does not exist within a view.

SnowflakeAIModelVersion

pyatlan.model.assets.core.snowflake_a_i_model_version.SnowflakeAIModelVersion(__pydantic_self__, **data: Any)

Bases: AIModelVersion

Description

Source code in pyatlan/model/assets/core/referenceable.py 
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def __init__(__pydantic_self__, **data: Any) -> None:
    super().__init__(**data)
    __pydantic_self__.__fields_set__.update(["attributes", "type_name"])

Attributes

AI_MODEL_QUALIFIED_NAME: KeywordField = KeywordField('aiModelQualifiedName', 'aiModelQualifiedName') class-attribute

Unique name of the AI model to which this version belongs, used to navigate from a version back to its parent model.

AI_MODEL_VERSION_METRICS: KeywordField = KeywordField('aiModelVersionMetrics', 'aiModelVersionMetrics') class-attribute

Evaluation and performance metrics recorded for this AI model version, stored as key-value pairs (e.g. accuracy, F1 score, precision, recall).

AI_MODEL_VERSION_STAGE: KeywordField = KeywordField('aiModelVersionStage', 'aiModelVersionStage') class-attribute

Lifecycle deployment stage of this AI model version, indicating its readiness for production use.

CALCULATION_VIEW_NAME: KeywordTextField = KeywordTextField('calculationViewName', 'calculationViewName.keyword', 'calculationViewName') class-attribute

Simple name of the calculation view in which this SQL asset exists, or empty if it does not exist within a calculation view.

CALCULATION_VIEW_QUALIFIED_NAME: KeywordField = KeywordField('calculationViewQualifiedName', 'calculationViewQualifiedName') class-attribute

Unique name of the calculation view in which this SQL asset exists, or empty if it does not exist within a calculation view.

CATALOG_DATASET_GUID: KeywordField = KeywordField('catalogDatasetGuid', 'catalogDatasetGuid') class-attribute

Unique identifier of the dataset this asset belongs to.

DATABASE_NAME: KeywordTextField = KeywordTextField('databaseName', 'databaseName.keyword', 'databaseName') class-attribute

Simple name of the database in which this SQL asset exists, or empty if it does not exist within a database.

DATABASE_QUALIFIED_NAME: KeywordField = KeywordField('databaseQualifiedName', 'databaseQualifiedName') class-attribute

Unique name of the database in which this SQL asset exists, or empty if it does not exist within a database.

DBT_MODELS: RelationField = RelationField('dbtModels') class-attribute

TBC

DBT_SEED_ASSETS: RelationField = RelationField('dbtSeedAssets') class-attribute

TBC

DBT_SOURCES: RelationField = RelationField('dbtSources') class-attribute

TBC

DBT_TESTS: RelationField = RelationField('dbtTests') class-attribute

TBC

ETHICAL_AI_ACCOUNTABILITY_CONFIG: KeywordField = KeywordField('ethicalAIAccountabilityConfig', 'ethicalAIAccountabilityConfig') class-attribute

Accountability configuration for ensuring the ethical use of an AI asset

ETHICAL_AI_BIAS_MITIGATION_CONFIG: KeywordField = KeywordField('ethicalAIBiasMitigationConfig', 'ethicalAIBiasMitigationConfig') class-attribute

Bias mitigation configuration for ensuring the ethical use of an AI asset

ETHICAL_AI_ENVIRONMENTAL_CONSCIOUSNESS_CONFIG: KeywordField = KeywordField('ethicalAIEnvironmentalConsciousnessConfig', 'ethicalAIEnvironmentalConsciousnessConfig') class-attribute

Environmental consciousness configuration for ensuring the ethical use of an AI asset

ETHICAL_AI_FAIRNESS_CONFIG: KeywordField = KeywordField('ethicalAIFairnessConfig', 'ethicalAIFairnessConfig') class-attribute

Fairness configuration for ensuring the ethical use of an AI asset

ETHICAL_AI_PRIVACY_CONFIG: KeywordField = KeywordField('ethicalAIPrivacyConfig', 'ethicalAIPrivacyConfig') class-attribute

Privacy configuration for ensuring the ethical use of an AI asset

ETHICAL_AI_RELIABILITY_AND_SAFETY_CONFIG: KeywordField = KeywordField('ethicalAIReliabilityAndSafetyConfig', 'ethicalAIReliabilityAndSafetyConfig') class-attribute

Reliability and safety configuration for ensuring the ethical use of an AI asset

ETHICAL_AI_TRANSPARENCY_CONFIG: KeywordField = KeywordField('ethicalAITransparencyConfig', 'ethicalAITransparencyConfig') class-attribute

Transparency configuration for ensuring the ethical use of an AI asset

IS_PROFILED: BooleanField = BooleanField('isProfiled', 'isProfiled') class-attribute

Whether this asset has been profiled (true) or not (false).

LAST_PROFILED_AT: NumericField = NumericField('lastProfiledAt', 'lastProfiledAt') class-attribute

Time (epoch) at which this asset was last profiled, in milliseconds.

QUERY_COUNT: NumericField = NumericField('queryCount', 'queryCount') class-attribute

Number of times this asset has been queried.

QUERY_COUNT_UPDATED_AT: NumericField = NumericField('queryCountUpdatedAt', 'queryCountUpdatedAt') class-attribute

Time (epoch) at which the query count was last updated, in milliseconds.

QUERY_USER_COUNT: NumericField = NumericField('queryUserCount', 'queryUserCount') class-attribute

Number of unique users who have queried this asset.

QUERY_USER_MAP: KeywordField = KeywordField('queryUserMap', 'queryUserMap') class-attribute

Map of unique users who have queried this asset to the number of times they have queried it.

SCHEMA_NAME: KeywordTextField = KeywordTextField('schemaName', 'schemaName.keyword', 'schemaName') class-attribute

Simple name of the schema in which this SQL asset exists, or empty if it does not exist within a schema.

SCHEMA_QUALIFIED_NAME: KeywordField = KeywordField('schemaQualifiedName', 'schemaQualifiedName') class-attribute

Unique name of the schema in which this SQL asset exists, or empty if it does not exist within a schema.

SNOWFLAKE_AI_MODEL_CONTEXT: RelationField = RelationField('snowflakeAIModelContext') class-attribute

TBC

SNOWFLAKE_AI_MODEL_VERSION_ALIASES: KeywordField = KeywordField('snowflakeAIModelVersionAliases', 'snowflakeAIModelVersionAliases') class-attribute

The aliases for the model version.

SNOWFLAKE_AI_MODEL_VERSION_FUNCTIONS: KeywordField = KeywordField('snowflakeAIModelVersionFunctions', 'snowflakeAIModelVersionFunctions') class-attribute

Functions used in the model version.

SNOWFLAKE_AI_MODEL_VERSION_METRICS: KeywordField = KeywordField('snowflakeAIModelVersionMetrics', 'snowflakeAIModelVersionMetrics') class-attribute

Metrics for an individual experiment.

SNOWFLAKE_AI_MODEL_VERSION_NAME: KeywordField = KeywordField('snowflakeAIModelVersionName', 'snowflakeAIModelVersionName') class-attribute

Version part of the model name.

SNOWFLAKE_AI_MODEL_VERSION_TYPE: KeywordField = KeywordField('snowflakeAIModelVersionType', 'snowflakeAIModelVersionType') class-attribute

The type of the model version.

SNOWFLAKE_SEMANTIC_LOGICAL_TABLES: RelationField = RelationField('snowflakeSemanticLogicalTables') class-attribute

TBC

SQL_AI_INSIGHTS_LAST_ANALYZED_AT: NumericField = NumericField('sqlAiInsightsLastAnalyzedAt', 'sqlAiInsightsLastAnalyzedAt') class-attribute

Time (epoch) at which this asset was last analyzed for AI insights, in milliseconds.

Number of popular business questions associated with this asset.

Number of popular filter patterns associated with this asset.

Number of popular join patterns associated with this asset.

SQL_AI_INSIGHTS_RELATIONSHIP_COUNT: NumericField = NumericField('sqlAiInsightsRelationshipCount', 'sqlAiInsightsRelationshipCount') class-attribute

Number of relationship insights associated with this asset.

SQL_AI_MODEL_CONTEXT_QUALIFIED_NAME: KeywordField = KeywordField('sqlAIModelContextQualifiedName', 'sqlAIModelContextQualifiedName') class-attribute

Unique name of the context in which the model versions exist, or empty if it does not exist within an AI model context.

SQL_DBT_MODELS: RelationField = RelationField('sqlDbtModels') class-attribute

TBC

SQL_DBT_SOURCES: RelationField = RelationField('sqlDBTSources') class-attribute

TBC

SQL_HAS_AI_INSIGHTS: BooleanField = BooleanField('sqlHasAiInsights', 'sqlHasAiInsights') class-attribute

Whether this asset has any AI insights data available.

SQL_INSIGHT_BUSINESS_QUESTIONS: RelationField = RelationField('sqlInsightBusinessQuestions') class-attribute

TBC

SQL_INSIGHT_INCOMING_JOINS: RelationField = RelationField('sqlInsightIncomingJoins') class-attribute

TBC

SQL_INSIGHT_OUTGOING_JOINS: RelationField = RelationField('sqlInsightOutgoingJoins') class-attribute

TBC

SQL_IS_SECURE: BooleanField = BooleanField('sqlIsSecure', 'sqlIsSecure') class-attribute

Whether this asset is secure (true) or not (false).

TABLE_NAME: KeywordTextField = KeywordTextField('tableName', 'tableName.keyword', 'tableName') class-attribute

Simple name of the table in which this SQL asset exists, or empty if it does not exist within a table.

TABLE_QUALIFIED_NAME: KeywordField = KeywordField('tableQualifiedName', 'tableQualifiedName') class-attribute

Unique name of the table in which this SQL asset exists, or empty if it does not exist within a table.

VIEW_NAME: KeywordTextField = KeywordTextField('viewName', 'viewName.keyword', 'viewName') class-attribute

Simple name of the view in which this SQL asset exists, or empty if it does not exist within a view.

VIEW_QUALIFIED_NAME: KeywordField = KeywordField('viewQualifiedName', 'viewQualifiedName') class-attribute

Unique name of the view in which this SQL asset exists, or empty if it does not exist within a view.