neurtu.timeit(obj, timer='wall_time', number=1, repeat=1, aggregate=('mean', 'max', 'std'), to_dataframe=None, progress_bar=5.0)[source]

A benchmark decorator

This is an alias for Benchmark with wall_time=True.

  • obj ({Delayed, iterable of Delayed}) – delayed object to compute, or an iterable of Delayed objects
  • number (int, default=1) – number of runs to pass to timeit.Timer
  • repeat (int, default=1) – number of repeated measurements
  • aggregate ({collection, False}, default=('mean', 'max', 'std')) – when repeat > 1, different runs are indexed by the runid key. If pandas is installed and aggregate is a collection, aggregate repeated runs with the provided methods.
  • to_dataframe (bool, default=None) – whether to convert parametric results to a daframe. By default convert to dataframe is pandas is installed.
  • progress_bar ({bool, float}, default=5.0) – if a number, and tqdm is installed, display the progress bar when the estimated benchmark time is larger than the given number of seconds. If False, the progress bar will not be displayed.

res – computed timing

Return type:

dict, list or pandas.DataFrame