def make_table(i, df):
event_header = [
col for col in df.columns
if (col.startswith('__') or col == 'event')
]
df = df[order_as(df.columns, event_header)]
if df.index.name in df.columns:
df.index = df.index.copy(deep=False)
df.index.name = ''
df_widget = pn.widgets.DataFrame(
df,
name=df.attrs.get('name', f'dataframe #{i}'),
formatters={'bool': {
'type': 'tickCross'
}},
# Disable edition of the dataframe
disabled=True,
sortable=False,
# Ensure some columns are always displayed
# Note: Tabulator requires a list of column names instead.
frozen_columns=len(event_header) + 1,
height=400,
autosize_mode='fit_viewport',
row_height=25,
# Only relevant for pn.widgets.Tabulator
#theme='simple',
#selectable='checkbox',
# Avoid transferring too much data at once to the browser
#pagination='remote',
#page_size=100,
)
return df_widget
def make_table(i, df):
event_header = [
col for col in df.columns
if (col.startswith('__') or col == 'event')
]
df = df[order_as(df.columns, event_header)]
if df.index.name in df.columns:
df.index = df.index.copy(deep=False)
df.index.name = ''
df_widget = pn.widgets.Tabulator(
df,
name=df.attrs.get('name', f'dataframe #{i}'),
formatters={'bool': {
'type': 'tickCross'
}},
# Disable edition of the dataframe
disabled=True,
# sortable=False,
# Ensure some columns are always displayed
frozen_columns=event_header,
# For pn.widgets.DataFrame.
# frozen_columns=len(event_header) + 1,
height=400,
# autosize_mode='fit_viewport',
row_height=25,
# Only relevant for pn.widgets.Tabulator
theme='simple',
selectable='toggle',
)
return df_widget
def _get_rtapp_phases(self, event, task, wlgen_profile=None):
df = self.df_rtapp_loop(task, wlgen_profile=wlgen_profile)
df = df[df.event == event]
# Sort START/END phase loop event from newers/older and...
if event == 'start':
df = df[df.phase_loop == 0]
elif event == 'end':
df = df.sort_values(by=['phase_loop', 'thread_loop'],
ascending=False)
# ... keep only the newest/oldest event
grouped = df.groupby(
['__comm', '__pid', 'phase', 'event'],
observed=True,
sort=False
)
df = grouped.head(1)
# Reorder the index and keep only required cols
kept_cols = ['__comm', '__pid', 'phase', 'properties']
kept_cols = order_as(
set(kept_cols) & set(df.columns),
order_as=kept_cols
)
df = (
df.sort_index()[kept_cols]
.reset_index()
.set_index([col for col in kept_cols if col != 'properties'])
)
return df
def format_release(name, sections):
title = f'{name}\n{len(name) * "="}\n'
body = '\n\n'.join(
format_section(marker, _msgs) for marker, _msgs in order_as(
sections.items(),
order_as=MARKERS,
key=itemgetter(0),
))
return f'{title}\n{body}'
def _df_all_events(self,
events,
field_sep=' ',
fields_as_cols=None,
event_as_col=True):
"""
Split implementation to be able to use the cache
"""
if fields_as_cols is None:
fields_as_cols = ['__comm', '__pid', '__cpu']
else:
fields_as_cols = list(fields_as_cols)
trace = self.trace
if not events:
df = pd.DataFrame(
dict.fromkeys((['info'] + fields_as_cols +
['event'] if event_as_col else []), []))
else:
if event_as_col:
fmt = '{fields}'
else:
fmt = '{{event:<{max_len}}}: {{fields}}'.format(max_len=max(
len(event) for event in events))
fields_as_cols_set = set(fields_as_cols)
def make_info_row(row, event):
fields = field_sep.join(f'{key}={value}'
for key, value in row.iteritems()
if key not in fields_as_cols_set)
return fmt.format(
event=event,
fields=fields,
)
def make_info_df(event):
df = trace.df_event(event)
df = pd.DataFrame(
{
'info': df.apply(make_info_row, axis=1, event=event),
**{field: df[field]
for field in fields_as_cols}
},
index=df.index,
)
if event_as_col:
df['event'] = event
return df
df = pd.concat(map(make_info_df, events))
df.sort_index(inplace=True)
df_update_duplicates(df, inplace=True)
# Reorder the columns to provide a better kernelshark-like display
columns_order = (
[col for col in df.columns if col.startswith('__')] +
(['event'] if event_as_col else []) + ['info'])
df = df[order_as(df.columns, columns_order)]
df.attrs['name'] = 'events'
return df
