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author | Daniel Olshansky <olshansky.daniel@gmail.com> | 2020-01-15 22:51:54 (GMT) |
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committer | Miss Islington (bot) <31488909+miss-islington@users.noreply.github.com> | 2020-01-15 22:51:54 (GMT) |
commit | 01602ae40321ecdb375ee6d44eaeac3255857879 (patch) | |
tree | 26530101fa5c910b465c942ccb0addce4f36bfec /Lib/pstats.py | |
parent | dc0284ee8f7a270b6005467f26d8e5773d76e959 (diff) | |
download | cpython-01602ae40321ecdb375ee6d44eaeac3255857879.zip cpython-01602ae40321ecdb375ee6d44eaeac3255857879.tar.gz cpython-01602ae40321ecdb375ee6d44eaeac3255857879.tar.bz2 |
bpo-37958: Adding get_profile_dict to pstats (GH-15495)
pstats is really useful or profiling and printing the output of the execution of some block of code, but I've found on multiple occasions when I'd like to access this output directly in an easily usable dictionary on which I can further analyze or manipulate.
The proposal is to add a function called get_profile_dict inside of pstats that'll automatically return this data the data in an easily accessible dict.
The output of the following script:
```
import cProfile, pstats
import pprint
from pstats import func_std_string, f8
def fib(n):
if n == 0:
return 0
if n == 1:
return 1
return fib(n-1) + fib(n-2)
pr = cProfile.Profile()
pr.enable()
fib(5)
pr.create_stats()
ps = pstats.Stats(pr).sort_stats('tottime', 'cumtime')
def get_profile_dict(self, keys_filter=None):
"""
Returns a dict where the key is a function name and the value is a dict
with the following keys:
- ncalls
- tottime
- percall_tottime
- cumtime
- percall_cumtime
- file_name
- line_number
keys_filter can be optionally set to limit the key-value pairs in the
retrieved dict.
"""
pstats_dict = {}
func_list = self.fcn_list[:] if self.fcn_list else list(self.stats.keys())
if not func_list:
return pstats_dict
pstats_dict["total_tt"] = float(f8(self.total_tt))
for func in func_list:
cc, nc, tt, ct, callers = self.stats[func]
file, line, func_name = func
ncalls = str(nc) if nc == cc else (str(nc) + '/' + str(cc))
tottime = float(f8(tt))
percall_tottime = -1 if nc == 0 else float(f8(tt/nc))
cumtime = float(f8(ct))
percall_cumtime = -1 if cc == 0 else float(f8(ct/cc))
func_dict = {
"ncalls": ncalls,
"tottime": tottime, # time spent in this function alone
"percall_tottime": percall_tottime,
"cumtime": cumtime, # time spent in the function plus all functions that this function called,
"percall_cumtime": percall_cumtime,
"file_name": file,
"line_number": line
}
func_dict_filtered = func_dict if not keys_filter else { key: func_dict[key] for key in keys_filter }
pstats_dict[func_name] = func_dict_filtered
return pstats_dict
pp = pprint.PrettyPrinter(depth=6)
pp.pprint(get_profile_dict(ps))
```
will produce:
```
{"<method 'disable' of '_lsprof.Profiler' objects>": {'cumtime': 0.0,
'file_name': '~',
'line_number': 0,
'ncalls': '1',
'percall_cumtime': 0.0,
'percall_tottime': 0.0,
'tottime': 0.0},
'create_stats': {'cumtime': 0.0,
'file_name': '/usr/local/Cellar/python/3.7.4/Frameworks/Python.framework/Versions/3.7/lib/python3.7/cProfile.py',
'line_number': 50,
'ncalls': '1',
'percall_cumtime': 0.0,
'percall_tottime': 0.0,
'tottime': 0.0},
'fib': {'cumtime': 0.0,
'file_name': 'get_profile_dict.py',
'line_number': 5,
'ncalls': '15/1',
'percall_cumtime': 0.0,
'percall_tottime': 0.0,
'tottime': 0.0},
'total_tt': 0.0}
```
As an example, this can be used to generate a stacked column chart using various visualization tools which will assist in easily identifying program bottlenecks.
https://bugs.python.org/issue37958
Automerge-Triggered-By: @gpshead
Diffstat (limited to 'Lib/pstats.py')
-rw-r--r-- | Lib/pstats.py | 57 |
1 files changed, 55 insertions, 2 deletions
diff --git a/Lib/pstats.py b/Lib/pstats.py index 4b419a8..e781b91 100644 --- a/Lib/pstats.py +++ b/Lib/pstats.py @@ -25,11 +25,13 @@ import os import time import marshal import re + from enum import Enum from functools import cmp_to_key +from dataclasses import dataclass +from typing import Dict -__all__ = ["Stats", "SortKey"] - +__all__ = ["Stats", "SortKey", "FunctionProfile", "StatsProfile"] class SortKey(str, Enum): CALLS = 'calls', 'ncalls' @@ -52,6 +54,22 @@ class SortKey(str, Enum): return obj +@dataclass(unsafe_hash=True) +class FunctionProfile: + ncalls: int + tottime: float + percall_tottime: float + cumtime: float + percall_cumtime: float + file_name: str + line_number: int + +@dataclass(unsafe_hash=True) +class StatsProfile: + '''Class for keeping track of an item in inventory.''' + total_tt: float + func_profiles: Dict[str, FunctionProfile] + class Stats: """This class is used for creating reports from data generated by the Profile class. It is a "friend" of that class, and imports data either @@ -333,6 +351,41 @@ class Stats: return new_list, msg + def get_stats_profile(self): + """This method returns an instance of StatsProfile, which contains a mapping + of function names to instances of FunctionProfile. Each FunctionProfile + instance holds information related to the function's profile such as how + long the function took to run, how many times it was called, etc... + """ + func_list = self.fcn_list[:] if self.fcn_list else list(self.stats.keys()) + if not func_list: + return StatsProfile(0, {}) + + total_tt = float(f8(self.total_tt)) + func_profiles = {} + stats_profile = StatsProfile(total_tt, func_profiles) + + for func in func_list: + cc, nc, tt, ct, callers = self.stats[func] + file_name, line_number, func_name = func + ncalls = str(nc) if nc == cc else (str(nc) + '/' + str(cc)) + tottime = float(f8(tt)) + percall_tottime = -1 if nc == 0 else float(f8(tt/nc)) + cumtime = float(f8(ct)) + percall_cumtime = -1 if cc == 0 else float(f8(ct/cc)) + func_profile = FunctionProfile( + ncalls, + tottime, # time spent in this function alone + percall_tottime, + cumtime, # time spent in the function plus all functions that this function called, + percall_cumtime, + file_name, + line_number + ) + func_profiles[func_name] = func_profile + + return stats_profile + def get_print_list(self, sel_list): width = self.max_name_len if self.fcn_list: |