def download(self,
log_files,
sort='time',
limit=-1,
nfl_filter='',
output_format='default'):
if len(log_files) == 0:
raise NotFoundException(_('no log file found'))
try:
nfl_esc = nfl_filter.replace('(', '\(').replace(')', '\)')
# remove the slash that is intentionally added in the URL
# to avoid failure of filtering stats data.
if nfl_esc.startswith('/'):
nfl_esc = nfl_esc[1:]
stats = Stats2(*log_files)
stats.sort_stats(sort)
if output_format == 'python':
data = self.format_source_code(nfl_filter)
elif output_format == 'json':
data = stats.to_json(nfl_esc, limit)
elif output_format == 'csv':
data = stats.to_csv(nfl_esc, limit)
elif output_format == 'ods':
data = stats.to_ods(nfl_esc, limit)
else:
profile_tmp_all = tempfile.mktemp('.profile', 'all')
stats.dump_stats(profile_tmp_all)
data = open(profile_tmp_all).read()
os.remove(profile_tmp_all)
return data, [('content-type', self.format_dict[output_format])]
except ODFLIBNotInstalled as ex:
raise ex
except Exception as ex:
raise ProfileException(_('Data download error: %s') % ex)
def index_page(self, log_files=None, sort='time', limit=-1,
fulldirs=0, nfl_filter='', profile_id='current', url='#'):
headers = [('content-type', 'text/html')]
if len(log_files) == 0:
return empty_description, headers
try:
stats = Stats2(*log_files)
except (IOError, ValueError):
raise DataLoadFailure(_('Can not load profile data from %s.')
% log_files)
if not fulldirs:
stats.strip_dirs()
stats.sort_stats(sort)
nfl_filter_esc =\
nfl_filter.replace('(', '\(').replace(')', '\)')
amount = [nfl_filter_esc, limit] if nfl_filter_esc else [limit]
profile_html = self.generate_stats_html(stats, self.app_path,
profile_id, *amount)
description = "Profiling information is generated by using\
'%s' profiler." % self.profile_module
sort_repl = '<option value="%s">' % sort
sort_selected = '<option value="%s" selected>' % sort
sort = sort_tmpl.replace(sort_repl, sort_selected)
plist = ''.join(['<option value="%s">%s</option>' % (p, p)
for p in self.profile_log.get_all_pids()])
profile_element = string.Template(profile_tmpl).substitute(
{'profile_list': plist})
profile_repl = '<option value="%s">' % profile_id
profile_selected = '<option value="%s" selected>' % profile_id
profile_element = profile_element.replace(profile_repl,
profile_selected)
limit_repl = '<option value="%s">' % limit
limit_selected = '<option value="%s" selected>' % limit
limit = limit_tmpl.replace(limit_repl, limit_selected)
fulldirs_checked = 'checked' if fulldirs else ''
fulldirs_element = string.Template(fulldirs_tmpl).substitute(
{'fulldir_checked': fulldirs_checked})
nfl_filter_element = string.Template(nfl_filter_tmpl).\
substitute({'nfl_filter': nfl_filter})
form_elements = string.Template(formelements_tmpl).substitute(
{'description': description,
'action': url,
'profile': profile_element,
'sort': sort,
'limit': limit,
'fulldirs': fulldirs_element,
'nfl_filter': nfl_filter_element,
}
)
content = string.Template(index_tmpl).substitute(
{'formelements': form_elements,
'action': url,
'description': description,
'profilehtml': profile_html,
})
return content, headers
def plot(self,
log_files,
sort='time',
limit=10,
nfl_filter='',
metric_selected='cc',
plot_type='bar'):
if not PLOTLIB_INSTALLED:
raise PLOTLIBNotInstalled(_('python-matplotlib not installed.'))
if len(log_files) == 0:
raise NotFoundException(_('no log file found'))
try:
stats = Stats2(*log_files)
stats.sort_stats(sort)
stats_dict = stats.stats
__, func_list = stats.get_print_list([nfl_filter, limit])
nfls = []
performance = []
names = {
'nc': 'Total Call Count',
'cc': 'Primitive Call Count',
'tt': 'Total Time',
'ct': 'Cumulative Time'
}
for func in func_list:
cc, nc, tt, ct, __ = stats_dict[func]
metric = {'cc': cc, 'nc': nc, 'tt': tt, 'ct': ct}
nfls.append(func[2])
performance.append(metric[metric_selected])
y_pos = range(len(nfls))
error = [random.random() for __ in y_pos]
plt.clf()
if plot_type == 'pie':
plt.pie(x=performance,
explode=None,
labels=nfls,
autopct='%1.1f%%')
else:
plt.barh(y_pos,
performance,
xerr=error,
align='center',
alpha=0.4)
plt.yticks(y_pos, nfls)
plt.xlabel(names[metric_selected])
plt.title('Profile Statistics (by %s)' % names[metric_selected])
#plt.gcf().tight_layout(pad=1.2)
profile_img = tempfile.TemporaryFile()
plt.savefig(profile_img, format='png', dpi=300)
profile_img.seek(0)
data = profile_img.read()
os.close(profile_img)
return data, [('content-type', 'image/jpg')]
except Exception as ex:
raise ProfileException(_('plotting results failed due to %s') % ex)