nannyml package

Subpackages

• nannyml.cli package
  • Submodules
    • nannyml.cli.cli module
    • nannyml.cli.run module
  • Module contents
• nannyml.datasets package
  • Subpackages
    • nannyml.datasets.data package
      • Module contents
  • Submodules
    • nannyml.datasets.datasets module
      • load_csv_file_to_df()
      • load_modified_california_housing_dataset()
      • load_synthetic_binary_classification_dataset()
      • load_synthetic_car_loan_dataset()
      • load_synthetic_car_price_dataset()
      • load_synthetic_multiclass_classification_dataset()
  • Module contents
• nannyml.drift package
  • Subpackages
    • nannyml.drift.multivariate package
      • Subpackages
      • Module contents
    • nannyml.drift.univariate package
      • Submodules
      • Module contents
  • Submodules
    • nannyml.drift.ranking module
      • AlertCountRanking
      • Ranker
      • Ranking
  • Module contents
• nannyml.io package
  • Subpackages
    • nannyml.io.db package
      • Submodules
      • Module contents
  • Submodules
    • nannyml.io.base module
      • Reader
      • Writer
      • WriterFactory
    • nannyml.io.file_reader module
      • FileReader
    • nannyml.io.file_writer module
      • FileWriter
    • nannyml.io.pickle_file_writer module
      • PickleFileWriter
    • nannyml.io.raw_files_writer module
      • RawFilesWriter
  • Module contents
• nannyml.performance_calculation package
  • Subpackages
    • nannyml.performance_calculation.metrics package
      • Submodules
      • Module contents
  • Submodules
    • nannyml.performance_calculation.calculator module
      • PerformanceCalculator
    • nannyml.performance_calculation.result module
      • Result
  • Module contents
• nannyml.performance_estimation package
  • Subpackages
    • nannyml.performance_estimation.confidence_based package
      • Submodules
      • Module contents
    • nannyml.performance_estimation.direct_loss_estimation package
      • Submodules
      • Module contents
  • Module contents
• nannyml.plots package
  • Submodules
    • nannyml.plots.colors module
      • Colors
  • Module contents
• nannyml.sampling_error package
  • Submodules
    • nannyml.sampling_error.binary_classification module
      • accuracy_sampling_error()
      • accuracy_sampling_error_components()
      • auroc_sampling_error()
      • auroc_sampling_error_components()
      • f1_sampling_error()
      • f1_sampling_error_components()
      • precision_sampling_error()
      • precision_sampling_error_components()
      • recall_sampling_error()
      • recall_sampling_error_components()
      • specificity_sampling_error()
      • specificity_sampling_error_components()
    • nannyml.sampling_error.multiclass_classification module
      • accuracy_sampling_error()
      • accuracy_sampling_error_components()
      • auroc_sampling_error()
      • auroc_sampling_error_components()
      • f1_sampling_error()
      • f1_sampling_error_components()
      • precision_sampling_error()
      • precision_sampling_error_components()
      • recall_sampling_error()
      • recall_sampling_error_components()
      • specificity_sampling_error()
      • specificity_sampling_error_components()
    • nannyml.sampling_error.regression module
      • mae_sampling_error()
      • mae_sampling_error_components()
      • mape_sampling_error()
      • mape_sampling_error_components()
      • mse_sampling_error()
      • mse_sampling_error_components()
      • msle_sampling_error()
      • msle_sampling_error_components()
      • rmse_sampling_error()
      • rmse_sampling_error_components()
      • rmsle_sampling_error()
      • rmsle_sampling_error_components()
  • Module contents

Submodules

• nannyml.analytics module
  • SegmentUsageTracker
    • SegmentUsageTracker.SEGMENT_WRITE_KEY
    • SegmentUsageTracker.TEST_UUID
    • SegmentUsageTracker.write_key
  • UsageEvent
    • UsageEvent.CBPE_ESTIMATOR_FIT
    • UsageEvent.CBPE_ESTIMATOR_RUN
    • UsageEvent.MULTIVAR_RECONST_DRIFT_CALC_FIT
    • UsageEvent.MULTIVAR_RECONST_DRIFT_CALC_RUN
    • UsageEvent.OUTPUT_DRIFT_CALC_FIT
    • UsageEvent.OUTPUT_DRIFT_CALC_RUN
    • UsageEvent.PERFORMANCE_CALC_FIT
    • UsageEvent.PERFORMANCE_CALC_RUN
    • UsageEvent.TARGET_DISTRIBUTION_DRIFT_CALC_FIT
    • UsageEvent.TARGET_DISTRIBUTION_DRIFT_CALC_RUN
    • UsageEvent.UNIVAR_STAT_DRIFT_CALC_FIT
    • UsageEvent.UNIVAR_STAT_DRIFT_CALC_RUN
  • UsageTracker
    • UsageTracker.track()
    • UsageTracker.user_metadata
  • track()
• nannyml.base module
  • AbstractCalculator
    • AbstractCalculator.calculate()
    • AbstractCalculator.fit()
  • AbstractCalculatorResult
    • AbstractCalculatorResult.DEFAULT_COLUMNS
    • AbstractCalculatorResult.filter()
    • AbstractCalculatorResult.plot()
    • AbstractCalculatorResult.to_df()
  • AbstractEstimator
    • AbstractEstimator.estimate()
    • AbstractEstimator.fit()
  • AbstractEstimatorResult
    • AbstractEstimatorResult.DEFAULT_COLUMNS
    • AbstractEstimatorResult.filter()
    • AbstractEstimatorResult.plot()
    • AbstractEstimatorResult.to_df()
• nannyml.calibration module
  • Calibrator
    • Calibrator.calibrate()
    • Calibrator.fit()
  • CalibratorFactory
    • CalibratorFactory.create()
    • CalibratorFactory.register_calibrator()
  • IsotonicCalibrator
    • IsotonicCalibrator.calibrate()
    • IsotonicCalibrator.fit()
  • NoopCalibrator
    • NoopCalibrator.calibrate()
    • NoopCalibrator.fit()
  • needs_calibration()
• nannyml.chunk module
  • Chunk
    • Chunk.__len__()
    • Chunk.__repr__()
    • Chunk.merge()
  • Chunker
    • Chunker.split()
  • ChunkerFactory
    • ChunkerFactory.get_chunker()
  • CountBasedChunker
  • DefaultChunker
    • DefaultChunker.DEFAULT_CHUNK_COUNT
  • PeriodBasedChunker
  • SizeBasedChunker
• nannyml.config module
  • ChunkerConfig
    • ChunkerConfig.chunk_count
    • ChunkerConfig.chunk_period
    • ChunkerConfig.chunk_size
  • ColumnMapping
    • ColumnMapping.features
    • ColumnMapping.timestamp
    • ColumnMapping.y_pred
    • ColumnMapping.y_pred_proba
    • ColumnMapping.y_true
  • Config
    • Config.chunker
    • Config.column_mapping
    • Config.ignore_errors
    • Config.input
    • Config.load()
    • Config.output
    • Config.problem_type
    • Config.scheduling
  • CronSchedulingConfig
    • CronSchedulingConfig.crontab
  • DatabaseWriterConfig
    • DatabaseWriterConfig.connection_string
    • DatabaseWriterConfig.model_name
  • InputConfig
    • InputConfig.analysis_data
    • InputConfig.reference_data
    • InputConfig.target_data
  • InputDataConfig
    • InputDataConfig.credentials
    • InputDataConfig.path
    • InputDataConfig.read_args
  • IntervalSchedulingConfig
    • IntervalSchedulingConfig.days
    • IntervalSchedulingConfig.hours
    • IntervalSchedulingConfig.minutes
    • IntervalSchedulingConfig.weeks
  • PickleWriterConfig
    • PickleWriterConfig.credentials
    • PickleWriterConfig.path
    • PickleWriterConfig.write_args
  • RawFileWriterConfig
    • RawFileWriterConfig.credentials
    • RawFileWriterConfig.format
    • RawFileWriterConfig.path
    • RawFileWriterConfig.write_args
  • SchedulingConfig
    • SchedulingConfig.cron
    • SchedulingConfig.interval
  • TargetDataConfig
    • TargetDataConfig.join_column
  • WriterConfig
    • WriterConfig.database
    • WriterConfig.pickle
    • WriterConfig.raw_files
  • get_config_path()
• nannyml.exceptions module
  • CalculatorException
  • CalculatorNotFittedException
  • ChunkerException
  • EstimatorException
  • IOException
  • InvalidArgumentsException
  • InvalidReferenceDataException
  • MissingMetadataException
  • NotFittedException
  • ReaderException
  • WriterException
• nannyml.runner module
  • run()
• nannyml.usage_logging module
  • SegmentUsageTracker
    • SegmentUsageTracker.SEGMENT_WRITE_KEY
    • SegmentUsageTracker.write_key
  • UsageEvent
    • UsageEvent.CBPE_ESTIMATOR_FIT
    • UsageEvent.CBPE_ESTIMATOR_RUN
    • UsageEvent.CBPE_PLOT
    • UsageEvent.CLI_RUN
    • UsageEvent.DLE_ESTIMATOR_FIT
    • UsageEvent.DLE_ESTIMATOR_RUN
    • UsageEvent.DLE_PLOT
    • UsageEvent.MULTIVAR_DRIFT_CALC_FIT
    • UsageEvent.MULTIVAR_DRIFT_CALC_RUN
    • UsageEvent.MULTIVAR_DRIFT_PLOT
    • UsageEvent.PERFORMANCE_CALC_FIT
    • UsageEvent.PERFORMANCE_CALC_RUN
    • UsageEvent.PERFORMANCE_PLOT
    • UsageEvent.UNIVAR_DRIFT_CALC_FIT
    • UsageEvent.UNIVAR_DRIFT_CALC_RUN
    • UsageEvent.UNIVAR_DRIFT_PLOT
    • UsageEvent.WRITE_DB
    • UsageEvent.WRITE_PICKLE
    • UsageEvent.WRITE_RAW
  • UsageLogger
    • UsageLogger.log()
  • disable_usage_logging()
  • enable_usage_logging()
  • get_logger()
  • log_usage()

Module contents

The NannyML library, helping you maintain model performance since 2020.

Use the library to: - Calculate drift on model inputs, outputs and ground truth - Calculate performance metrics for your model - Estimate model performance metrics in the absence of ground truth