def results(self):
"""Return cProfile results in a dictionary for template context."""
# Make sure nothing is printed to stdout
output = StringIO.StringIO()
stats = pstats.Stats(self.c_profile, stream=output)
stats.sort_stats("cumulative")
self.c_profile.create_stats()
results = {
"raw_stats": base64.b64encode(marshal.dumps(self.c_profile.stats)),
"total_call_count": stats.total_calls,
"total_time": util.seconds_fmt(stats.total_tt),
"calls": []
}
width, list_func_names = stats.get_print_list([80])
for func_name in list_func_names:
primitive_call_count, total_call_count, total_time, cumulative_time, callers = stats.stats[
func_name]
func_desc = pstats.func_std_string(func_name)
callers_names = map(
lambda func_name: pstats.func_std_string(func_name),
callers.keys())
callers_desc = map(
lambda name: {
"func_desc": name,
"func_desc_short": util.short_method_fmt(name)
}, callers_names)
results["calls"].append({
"primitive_call_count":
primitive_call_count,
"total_call_count":
total_call_count,
"cumulative_time":
util.seconds_fmt(cumulative_time, 2),
"total_time":
util.seconds_fmt(total_time, 2),
"per_call_cumulative":
util.seconds_fmt(cumulative_time / primitive_call_count, 2)
if primitive_call_count else "",
"func_desc":
func_desc,
"func_desc_short":
util.short_method_fmt(func_desc),
"callers_desc":
callers_desc,
})
output.close()
return results
def results(self):
"""Return cProfile results in a dictionary for template context."""
# Make sure nothing is printed to stdout
output = StringIO.StringIO()
stats = pstats.Stats(self.c_profile, stream=output)
stats.sort_stats("cumulative")
self.c_profile.create_stats()
results = {
"raw_stats": base64.b64encode(marshal.dumps(self.c_profile.stats)),
"total_call_count": stats.total_calls,
"total_time": util.seconds_fmt(stats.total_tt),
"calls": []
}
width, list_func_names = stats.get_print_list([80])
for func_name in list_func_names:
primitive_call_count, total_call_count, total_time, cumulative_time, callers = stats.stats[func_name]
func_desc = pstats.func_std_string(func_name)
callers_names = map(lambda func_name: pstats.func_std_string(func_name), callers.keys())
callers_desc = map(
lambda name: {"func_desc": name, "func_desc_short": util.short_method_fmt(name)},
callers_names)
results["calls"].append({
"primitive_call_count": primitive_call_count,
"total_call_count": total_call_count,
"cumulative_time": util.seconds_fmt(cumulative_time, 2),
"total_time": util.seconds_fmt(total_time, 2),
"per_call_cumulative": util.seconds_fmt(cumulative_time / primitive_call_count, 2) if primitive_call_count else "",
"func_desc": func_desc,
"func_desc_short": util.short_method_fmt(func_desc),
"callers_desc": callers_desc,
})
output.close()
return results
def profiler_results(self):
"""Return the CPU profiler results for this request, if any.
This will return a dictionary containing results for either the
sampling profiler, instrumented profiler results, or a simple
start/stop timer if both profilers are disabled."""
total_time = util.seconds_fmt(self.end - self.start, 0)
results = {"total_time": total_time}
if self.instrumented_prof:
results.update(self.instrumented_prof.results())
elif self.sampling_prof:
results.update(self.sampling_prof.results())
return results
def profiler_results(self):
"""Return the CPU profiler results for this request, if any.
This will return a dictionary containing results for either the
sampling profiler, instrumented profiler results, or a simple
start/stop timer if both profilers are disabled."""
total_time = util.seconds_fmt(self.end - self.start, 0)
results = {"total_time": total_time}
if self.instrumented_prof:
results.update(self.instrumented_prof.results())
elif self.sampling_prof:
results.update(self.sampling_prof.results())
return results
