neurtu.timeit¶
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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
Benchmarkwith wall_time=True.Parameters: - 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
runidkey. 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.
Returns: res – computed timing
Return type: