featurebyte.FeatureJobSettingAnalysis

class FeatureJobSettingAnalysis(

*,

user_id: Optional[PydanticObjectId]=None,

name: Optional[NameStr]=None,

created_at: Optional[datetime]=None,

updated_at: Optional[datetime]=None,

block_modification_by: List[ReferenceInfo]=None,

description: Optional[StrictStr]=None,

catalog_id: PydanticObjectId,

event_table_id: Optional[PydanticObjectId]=None,

event_table_candidate: Optional[EventTableCandidate]=None,

analysis_options: AnalysisOptions,

analysis_parameters: AnalysisParameters,

analysis_result: AnalysisResult,

analysis_report: str,

backtest_summaries: Optional[List[BackTestSummary]]=None

)

Description

The FeatureJobSettingAnalysis object contains the result of the analysis of the data availability and freshness of a table. The metadata held by the object includes a report and recommendation for the configuration of the feature job setting of features associated with the table. Additionally, you can perform a backtest of a manually configured feature job setting.

Parameters

• user_id: Optional[PydanticObjectId]
  
  
• name: Optional[NameStr]
  
  
• created_at: Optional[datetime]
  
  
• updated_at: Optional[datetime]
  
  
• block_modification_by: List[ReferenceInfo]
  
  
• description: Optional[StrictStr]
  
  
• catalog_id: PydanticObjectId
  
  
• event_table_id: Optional[PydanticObjectId]
  
  
• event_table_candidate: Optional[EventTableCandidate]
  
  
• analysis_options: AnalysisOptions
  
  
• analysis_parameters: AnalysisParameters
  
  
• analysis_result: AnalysisResult
  
  
• analysis_report: str
  
  
• backtest_summaries: Optional[List[BackTestSummary]]
  
  

Examples

>>> analysis = invoice_table.create_new_feature_job_setting_analysis(
...   analysis_date=pd.Timestamp('2023-04-10'),
...   analysis_length=36002428,
... )