lisa.wa.WATraceCollector#

class lisa.wa.WATraceCollector(wa_output, trace_to_df=<function _stub_trace_to_df>, **kwargs)[source]#

Bases: WAArtifactCollectorBase

WA collector for the trace augmentation.

Parameters:: trace_to_df (collections.abc.Callable) – Function used by the collector to convert the lisa.trace.Trace to a pandas.DataFrame.
Variable keyword arguments:: Forwarded to lisa.trace.Trace.

Example:

def trace_idle_analysis(trace):
    cpu = 0
    df = trace.ana.idle.df_cluster_idle_state_residency([cpu])
    df = df.reset_index()
    df['cpu'] = cpu

    # Melt the column 'time' into lines, so that the dataframe is in
    # "database" format: each value is uniquely identified by "tag"
    # columns
    return df.melt(
        var_name='metric',
        value_vars=['time'],
        id_vars=['idle_state'],
     )

WAOutput('wa/output/path').get_collector(
    'trace',
    trace_to_df=trace_idle_analysis,
).df

Attributes

NAME

Properties

`traces`	`lisa.utils.LazyMapping` that maps job names & iteration numbers to their corresponding `lisa.trace.Trace`.
`df` ^inherited	`pandas.DataFrame` containing the data collected.
`logger` ^inherited	Convenience short-hand for `self.get_logger()`.
`stats` ^inherited	Short-hand property equivalent to `self.get_stats()`.

Methods

`get_logger()` ^inherited	Provides a `logging.Logger` named after `cls`.
`get_stats()` ^inherited	Returns a `lisa.stats.Stats` loaded with the result `pandas.DataFrame`.
`log_locals()` ^inherited	Debugging aid: log the local variables of the calling function.

Attributes#

WATraceCollector.NAME = 'trace'#

Properties#

property WATraceCollector.traces[source]#: lisa.utils.LazyMapping that maps job names & iteration numbers to their corresponding lisa.trace.Trace.