class_docstr: Renders the profiling results as an interactive, fully self-contained HTML report that
  can be downloaded and shared without the need for a running server or Python kernel.
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docstr: Args:
      df (pd.DataFrame): Timeseries data.
      meta (Optional[dict]): Timeseries metadata, a 2-level dictionary, first level indexed
          by ``{'frame': {<key>: <value>}, {'series': {<series name>: <desc>}}``.
      result (Optional[BundledResult]): For instantiating the report with pre-computed
          results from a profiler.
      profiler (Optional[BundledProfiler]): The `BundledProfiler` to run the profiling,
          defaults to `DefaultProfiler`.
      profiler_config (Optional[dict]): Profiler's configurations.
      scheduler (Optional[Scheduler]): A `Scheduler`, default's to `Scheduler`.
      scheduler_config (Optional[dict]): Scheduler's configurations.
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code: def __init__(
      self,
      df: pd.DataFrame,
      meta: Optional[dict] = None,
      result: Optional[BundledResult] = None,
      profiler: Optional[BundledProfiler] = None,
      profiler_config: Optional[dict] = None,
      scheduler: Optional[Scheduler] = None,
      scheduler_config: Optional[dict] = None,
  ) -> None:
      """
      Args:
          df (pd.DataFrame): Timeseries data.
          meta (Optional[dict]): Timeseries metadata, a 2-level dictionary, first level indexed
              by ``{'frame': {<key>: <value>}, {'series': {<series name>: <desc>}}``.
          result (Optional[BundledResult]): For instantiating the report with pre-computed
              results from a profiler.
          profiler (Optional[BundledProfiler]): The `BundledProfiler` to run the profiling,
              defaults to `DefaultProfiler`.
          profiler_config (Optional[dict]): Profiler's configurations.
          scheduler (Optional[Scheduler]): A `Scheduler`, default's to `Scheduler`.
          scheduler_config (Optional[dict]): Scheduler's configurations.
      """
      assert df.shape[1] <= 20 and (
          result is None or len(result.result.series) <= 20
      ), "HtmlReport not suitable for sets with more than 20 time series."
      super().__init__(
          df=df,
          meta=meta,
          result=result,
          profiler=profiler,
          profiler_config=profiler_config,
          scheduler=scheduler,
          scheduler_config=scheduler_config,
      )
      self.sections: List[HtmlBlock] = []
      self.duration: Optional[timedelta] = None
      self._html = None
  
file_path: tslumen/tslumen/report/html/report.py
imports: import io
  from typing import Optional, List, Union
  from datetime import datetime, timedelta
  import pandas
  from tslumen.misc import lazyproperty
  from tslumen.scheduling import Scheduler
  from tslumen.profile.base import BundledProfiler, BundledResult
  from tslumen.report.base import Report
  from tslumen.report.html.base import HtmlBlock
  from tslumen.report.html.sections import SectionSummary, SectionTimeSeries, SectionTSFeatures, SectionRelations
label_desc: Use image node_id 1 to create a new HtmlReport object from inherited base classes: Report, HtmlBlock with example: obj = HtmlReport(df, meta, result, profiler, profiler_config, scheduler, scheduler_config)