report_pipelines.py

# Copyright (c) 2022 ING Wholesale Banking Advanced Analytics
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from pathlib import Path

from ..base import Pipeline
from ..config import config
from ..io import FileWriter
from ..pipeline.metrics_pipelines import (
    ExpandingReferenceMetricsPipeline,
    ExternalReferenceMetricsPipeline,
    RollingReferenceMetricsPipeline,
    SelfReferenceMetricsPipeline,
)
from ..visualization import (
    AlertSectionGenerator,
    HistogramSection,
    ReportGenerator,
    SectionGenerator,
    TrafficLightSectionGenerator,
)
from ..visualization.overview_section import OverviewSectionGenerator


def get_report_pipeline_class(reference_type, reference):
    _report_pipeline = {
        "self": SelfReference,
        "external": ExternalReference,
        "rolling": RollingReference,
        "expanding": ExpandingReference,
    }
    reference_types = list(_report_pipeline.keys())
    if reference_type not in reference_types:
        raise ValueError(f"reference_type should be one of {str(reference_types)}.")
    if reference_type == "external" and not isinstance(reference, dict):
        raise TypeError("reference should be a dict of histogrammar histograms.")

    return _report_pipeline[reference_type]


class SelfReference(Pipeline):
    def __init__(
        self,
        hists_key="test_hists",
        time_axis="date",
        window=10,
        monitoring_rules={},
        pull_rules={},
        features=None,
        skip_empty_plots=True,
        last_n=0,
        top_n=20,
        plot_hist_n=6,
        report_filepath=None,
        show_stats=None,
        disable_heatmap=None,
        cmap=None,
        **kwargs,
    ):
        """Example pipeline for comparing test data with itself (full test set)

        :param str hists_key: key to test histograms in datastore. default is 'test_hists'
        :param str time_axis: name of datetime feature. default is 'date' (column should be timestamp, date(time) or numeric batch id)
        :param int window: window size for trend detection. default is 10
        :param dict monitoring_rules: traffic light rules
        :param dict pull_rules: pull rules to determine dynamic boundaries
        :param list features: features of histograms to pick up from input data (optional)
        :param bool skip_empty_plots: if false, also show empty plots in report with only nans or zeroes (optional)
        :param int last_n: plot statistic data for last 'n' periods (optional)
        :param int top_n: plot heatmap for top 'n' categories. default is 20 (optional)
        :param int plot_hist_n: plot histograms for last 'n' periods. default is 1 (optional)
        :param str report_filepath: the file path where to output the report (optional)
        :param list show_stats: list of statistic name patterns to show in the report. If None, show all (optional)
        :param list disable_heatmap: list of heatmap types to disable in the report. 'normal' to disable normal heatmap, 'row' to row normalized, 'column' to disable column normalized. If None, show all (optional)
        :param kwargs: residual keyword arguments
        :return: assembled self reference pipeline
        """
        modules = [
            SelfReferenceMetricsPipeline(
                hists_key,
                time_axis,
                window,
                monitoring_rules,
                pull_rules,
                features,
                **kwargs,
            ),
            ReportPipe(
                sections_key="report_sections",
                store_key="html_report",
                skip_empty_plots=skip_empty_plots,
                last_n=last_n,
                top_n=top_n,
                plot_hist_n=plot_hist_n,
                report_filepath=report_filepath,
                show_stats=show_stats,
                disable_heatmap=disable_heatmap,
                cmap=cmap,
            ),
        ]

        super().__init__(modules)


class ExternalReference(Pipeline):
    def __init__(
        self,
        hists_key="test_hists",
        ref_hists_key="ref_hists",
        time_axis="date",
        window=10,
        monitoring_rules={},
        pull_rules={},
        features=None,
        skip_empty_plots=True,
        last_n=0,
        top_n=20,
        plot_hist_n=2,
        report_filepath=None,
        show_stats=None,
        disable_heatmap=None,
        cmap=None,
        **kwargs,
    ):
        """Example pipeline for comparing test data with other (full) external reference set

        :param str hists_key: key to test histograms in datastore. default is 'test_hists'
        :param str ref_hists_key: key to reference histograms in datastore. default is 'ref_hists'
        :param str time_axis: name of datetime feature. default is 'date' (column should be timestamp, date(time) or numeric batch id)
        :param int window: window size for trend detection. default is 10
        :param dict monitoring_rules: traffic light rules
        :param dict pull_rules: pull rules to determine dynamic boundaries
        :param list features: features of histograms to pick up from input data (optional)
        :param bool skip_empty_plots: if false, show empty plots in report with only nans or zeroes (optional)
        :param int last_n: plot statistic data for last 'n' periods (optional)
        :param int top_n: plot heatmap for top 'n' categories. default is 20 (optional)
        :param int plot_hist_n: plot histograms for last 'n' periods. default is 1 (optional)
        :param str report_filepath: the file path where to output the report (optional)
        :param list show_stats: list of statistic name patterns to show in the report. If None, show all (optional)
        :param list disable_heatmap: list of heatmap types to disable in the report. 'normal' to disable normal heatmap, 'row' to row normalized, 'column' to disable column normalized. If None, show all (optional)
        :param kwargs: residual keyword arguments
        :return: assembled external reference pipeline
        """
        modules = [
            ExternalReferenceMetricsPipeline(
                hists_key,
                ref_hists_key,
                time_axis,
                window,
                monitoring_rules,
                pull_rules,
                features,
                **kwargs,
            ),
            ReportPipe(
                sections_key="report_sections",
                store_key="html_report",
                skip_empty_plots=skip_empty_plots,
                last_n=last_n,
                top_n=top_n,
                plot_hist_n=plot_hist_n,
                report_filepath=report_filepath,
                show_stats=show_stats,
                disable_heatmap=disable_heatmap,
                cmap=cmap,
            ),
        ]

        super().__init__(modules)


class RollingReference(Pipeline):
    def __init__(
        self,
        hists_key="test_hists",
        time_axis="date",
        window=10,
        shift=1,
        monitoring_rules={},
        pull_rules={},
        features=None,
        skip_empty_plots=True,
        last_n=0,
        top_n=20,
        plot_hist_n=6,
        report_filepath=None,
        show_stats=None,
        disable_heatmap=None,
        cmap=None,
        **kwargs,
    ):
        """Example pipeline for comparing test data with itself (rolling test set)

        :param str hists_key: key to test histograms in datastore. default is 'test_hists'
        :param str time_axis: name of datetime feature. default is 'date' (column should be timestamp, date(time) or numeric batch id)
        :param int window: size of rolling window and for trend detection. default is 10
        :param int shift: shift in rolling window. default is 1
        :param dict monitoring_rules: traffic light rules
        :param dict pull_rules: pull rules to determine dynamic boundaries
        :param list features: features of histograms to pick up from input data (optional)
        :param bool skip_empty_plots: if false, show empty plots in report with only nans or zeroes (optional)
        :param int last_n: plot statistic data for last 'n' periods (optional)
        :param int top_n: plot heatmap for top 'n' categories. default is 20 (optional)
        :param int plot_hist_n: plot histograms for last 'n' periods. default is 1 (optional)
        :param str report_filepath: the file path where to output the report (optional)
        :param list show_stats: list of statistic name patterns to show in the report. If None, show all (optional)
        :param list disable_heatmap: list of heatmap types to disable in the report. 'normal' to disable normal heatmap, 'row' to row normalized, 'column' to disable column normalized. If None, show all (optional)
        :param kwargs: residual keyword arguments
        :return: assembled rolling reference pipeline
        """
        modules = [
            RollingReferenceMetricsPipeline(
                hists_key,
                time_axis,
                window,
                shift,
                monitoring_rules,
                pull_rules,
                features,
                **kwargs,
            ),
            ReportPipe(
                sections_key="report_sections",
                store_key="html_report",
                skip_empty_plots=skip_empty_plots,
                last_n=last_n,
                top_n=top_n,
                plot_hist_n=plot_hist_n,
                report_filepath=report_filepath,
                show_stats=show_stats,
                disable_heatmap=disable_heatmap,
                cmap=cmap,
            ),
        ]

        super().__init__(modules)


class ExpandingReference(Pipeline):
    def __init__(
        self,
        hists_key="test_hists",
        time_axis="date",
        window=10,
        shift=1,
        monitoring_rules={},
        pull_rules={},
        features=None,
        skip_empty_plots=True,
        last_n=0,
        top_n=20,
        plot_hist_n=6,
        report_filepath=None,
        show_stats=None,
        disable_heatmap=None,
        cmap="autumn_r",
        **kwargs,
    ):
        """Example pipeline for comparing test data with itself (expanding test set)

        :param str hists_key: key to test histograms in datastore. default is 'test_hists'
        :param str time_axis: name of datetime feature. default is 'date' (column should be timestamp, date(time) or numeric batch id)
        :param int window: window size for trend detection. default is 10
        :param int shift: shift in expanding window. default is 1
        :param dict monitoring_rules: traffic light rules
        :param dict pull_rules: pull rules to determine dynamic boundaries
        :param list features: features of histograms to pick up from input data (optional)
        :param bool skip_empty_plots: if false, show empty plots in report with only nans or zeroes (optional)
        :param int last_n: plot statistic data for last 'n' periods (optional)
        :param int top_n: plot heatmap for top 'n' categories. default is 20 (optional)
        :param int plot_hist_n: plot histograms for last 'n' periods. default is 1 (optional)
        :param str report_filepath: the file path where to output the report (optional)
        :param list show_stats: list of statistic name patterns to show in the report. If None, show all (optional)
        :param list disable_heatmap: list of heatmap types to disable in the report. 'normal' to disable normal heatmap, 'row' to row normalized, 'column' to disable column normalized. If None, show all (optional)
        :param kwargs: residual keyword arguments
        :return: assembled expanding reference pipeline
        """
        modules = [
            ExpandingReferenceMetricsPipeline(
                hists_key,
                time_axis,
                window,
                shift,
                monitoring_rules,
                pull_rules,
                features,
                **kwargs,
            ),
            ReportPipe(
                sections_key="report_sections",
                store_key="html_report",
                skip_empty_plots=skip_empty_plots,
                last_n=last_n,
                top_n=top_n,
                plot_hist_n=plot_hist_n,
                report_filepath=report_filepath,
                show_stats=show_stats,
                disable_heatmap=disable_heatmap,
                cmap=cmap,
            ),
        ]

        super().__init__(modules)


class ReportPipe(Pipeline):
    """Pipeline of modules for generating sections and a final report."""

    def __init__(
        self,
        sections_key="report_sections",
        store_key="html_report",
        profiles_section="Profiles",
        comparisons_section="Comparisons",
        traffic_lights_section="Traffic Lights",
        alerts_section="Alerts",
        histograms_section="Histograms",
        report_filepath=None,
        show_stats=None,
        skip_empty_plots=True,
        last_n=0,
        top_n=20,
        skip_first_n=0,
        skip_last_n=0,
        plot_hist_n=6,
        disable_heatmap=None,
        cmap=None,
    ):
        """Initialize an instance of Report.

        :param str sections_key: key to store sections data in the datastore
        :param str store_key: key to store the HTML report data in the datastore
        :param str profiles_section: name for the profile data section. default is 'Profiles'
        :param str comparisons_section: name for the comparison data section. default is 'Comparisons'
        :param str traffic_lights_section: name for the traffic light section. default is 'Traffic Lights'
        :param str alerts_section: name for the alerts section. default is 'Alerts'
        :param str histograms_section: name for the histograms section. default is 'Histograms'
        :param str report_filepath: the file path where to output the report (optional)
        :param bool skip_empty_plots: if false, also show empty plots in report with only nans or zeroes (optional)
        :param int last_n: plot statistic data for last 'n' periods (optional)
        :param int top_n: plot heatmap for top 'n' categories. default is 20 (optional)
        :param int skip_first_n: when plotting data skip first 'n' periods. last_n takes precedence (optional)
        :param int skip_last_n: when plotting data skip last 'n' periods. last_n takes precedence (optional)
        :param int plot_hist_n: plot histograms for last 'n' periods. default is 1 (optional)
        :param list show_stats: list of statistic name patterns to show in the report. If None, show all (optional)
        :param list disable_heatmap: list of heatmap types to disable in the report. 'normal' to disable normal heatmap, 'row' to row normalized, 'column' to disable column normalized. If None, show all (optional)
        """
        self.store_key = store_key

        # dictionary of section descriptions
        descs = config["section_descriptions"]

        # default keyword arguments for each section
        sg_kws = {
            "store_key": sections_key,
            "skip_empty_plots": skip_empty_plots,
            "last_n": last_n,
            "skip_first_n": skip_first_n,
            "skip_last_n": skip_last_n,
            "show_stats": show_stats,
        }

        modules = [
            OverviewSectionGenerator(
                read_key="traffic_lights",
                description=descs.get("overview", ""),
                section_name="Overview",
                **sg_kws,
            ),
            # generate section with histogram
            HistogramSection(
                read_key="split_hists",
                store_key=sections_key,
                section_name=histograms_section,
                hist_name_starts_with="histogram",
                last_n=plot_hist_n,
                top_n=top_n,
                description=descs.get("histograms", ""),
                disable_heatmap=disable_heatmap,
                cmap=cmap,
            ),
            # section showing all traffic light alerts of monitored statistics
            TrafficLightSectionGenerator(
                read_key="traffic_lights",
                description=descs.get("traffic_lights", ""),
                section_name=traffic_lights_section,
                **sg_kws,
            ),
            # section with a summary of traffic light alerts
            AlertSectionGenerator(
                read_key="alerts",
                description=descs.get("alerts", ""),
                section_name=alerts_section,
                **sg_kws,
            ),
            # section of histogram and pull comparison statistics
            SectionGenerator(
                dynamic_bounds="dynamic_bounds_comparisons",
                static_bounds="static_bounds_comparisons",
                section_name=comparisons_section,
                ignore_stat_endswith=["_mean", "_std", "_pull"],
                read_key="comparisons",
                description=descs.get("comparisons", ""),
                **sg_kws,
            ),
            # section of profiled statistics with dynamic or static traffic light bounds
            SectionGenerator(
                dynamic_bounds="dynamic_bounds",
                section_name=profiles_section,
                static_bounds="static_bounds",
                ignore_stat_endswith=["_mean", "_std", "_pull"],
                read_key="profiles",
                description=descs.get("profiles", ""),
                **sg_kws,
            ),
            # generate report
            ReportGenerator(read_key=sections_key, store_key=store_key),
        ]
        if isinstance(report_filepath, (str, Path)) and len(report_filepath) > 0:
            modules.append(FileWriter(store_key, file_path=report_filepath))

        super().__init__(modules=modules)

    def transform(self, datastore):
        self.logger.info(f'Generating report "{self.store_key}".')
        return super().transform(datastore)