hooqu.analyzers.runners¶

class hooqu.analyzers.runners.analysis_runner.AnalyzerContext(metric_map: Mapping[hooqu.analyzers.analyzer.Analyzer, hooqu.metrics.Metric] = <factory>)[source]¶

Bases: object

all_metrics()[source]¶

Return type: List[Metric]

metric(analyzer)[source]¶

Return type: Optional[Metric]

metric_map: Mapping[hooqu.analyzers.analyzer.Analyzer, hooqu.metrics.Metric]¶

classmethod success_metrics_as_dataframe(analyzer_context, for_analyzers=None)[source]¶

Return type: DataFrame

hooqu.analyzers.runners.analysis_runner.compute_precondition_failure_metrics(failed_analyzers, data)[source]¶

Return type: AnalyzerContext

hooqu.analyzers.runners.analysis_runner.do_analysis_run(data, analyzers, aggregate_with=None, save_state_with=None, metric_repository_options=None)[source]¶

Compute the metrics from the analyzers configured in the analysis

Parameters

data – data on which to operate
analyzers (Sequence[Analyzer]) – the analyzers to run
aggregate_With ((not implemented)) – load existing states for the configured analyzers and aggregate them (optional)
save_States_With ((not implemented)) – persist resulting states for the configured analyzers (optional)
metric_repository_options ((not implemented)) – options related to the MetricsRepository
file_output_options ((not implemented probably will be removed)) – options related to File Ouput.

Returns

Return type

An AnalyzerContext holding the requested metrics per analyzer

hooqu.analyzers.runners.analysis_runner.run_analyzers_sequentially(data, analyzers, aggregate_with=None, save_state_with=None)[source]¶

Apparently from the initial tests I made there is not a lot of gain from running all the aggregations at once.

Return type: AnalyzerContext

hooqu.analyzers.runners.analysis_runner.run_non_scanning_analyzers(data, analyzers)[source]¶

hooqu.analyzers.runners.analysis_runner.run_scanning_analyzers(data, analyzers, aggregate_with=None, save_state_with=None)[source]¶

Return type: AnalyzerContext