pprofile 1.3

Line-granularity, thread-aware deterministic pure-python profiler

Contents

• Overview

• Usage

• Thread-aware profiling

  • Limitations

Line-granularity, thread-aware deterministic pure-python profiler

Inspired from Robert Kern’s line_profiler .

Overview

Python’s standard profiling tools have a callable-level granularity, which means it is only possible to tell which function is a hot-spot, not which lines in that function.

Robert Kern’s line_profiler is a very nice alternative providing line-level profiling granularity, but in my opinion it has a few drawbacks which (in addition to the attractive technical chalenge) made me start pprofile:

• It is not pure-python. This choice makes sense for performance but makes usage with pypy difficult and requires installation (I value execution straight from checkout).

• It requires source code modification to select what should be profiled. I prefer to have the option to do an in-depth, non-intrusive profiling.

• As an effect of previous point, it does not have a notion above individual callable, annotating functions but not whole files - preventing module import profiling.

• Profiling recursive code provides unexpected results (recursion cost is accumulated on callable’s first line) because it doesn’t track call stack. This may be unintended, and may be fixed at some point in line_profiler.

Usage

As a command:

$ pprofile some_python_executable

Once some_python_executable returns, prints annotated code of each file involved in the execution (output can be directed to a file using -o/–out arguments).

As a command with conflicting argument names: use “–” before profiled executable name:

$ pprofile -- foo --out bla

As a module:

import pprofile

profiler = pprofile.Profile()
def someHotSpotCallable():
    with profiler:
        # Some hot-spot code

Alternative to with, allowing to end profiling in a different place:

def someHotSpotCallable():
    profiler.enable()
    # Some hot-spot code
    someOtherFunction()

def someOtherFunction():
    # Some more hot-spot code
    profiler.disable()

Then, to display anotated source on stdout:

profiler.print_stats()

(several similar methods are available).

Sample output (standard threading.py removed from output for readability):

$ pprofile --threads 0 demo/threads.py
Command line: ['demo/threads.py']
Total duration: 1.00573s
File: demo/threads.py
File duration: 1.00168s (99.60%)
Line #|      Hits|         Time| Time per hit|      %|Source code
------+----------+-------------+-------------+-------+-----------
     1|         2|  3.21865e-05|  1.60933e-05|  0.00%|import threading
     2|         1|  5.96046e-06|  5.96046e-06|  0.00%|import time
     3|         0|            0|            0|  0.00%|
     4|         2|   1.5974e-05|  7.98702e-06|  0.00%|def func():
     5|         1|      1.00111|      1.00111| 99.54%|  time.sleep(1)
     6|         0|            0|            0|  0.00%|
     7|         2|  2.00272e-05|  1.00136e-05|  0.00%|def func2():
     8|         1|  1.69277e-05|  1.69277e-05|  0.00%|  pass
     9|         0|            0|            0|  0.00%|
    10|         1|  1.81198e-05|  1.81198e-05|  0.00%|t1 = threading.Thread(target=func)
(call)|         1|  0.000610828|  0.000610828|  0.06%|# /usr/lib/python2.7/threading.py:436 __init__
    11|         1|  1.52588e-05|  1.52588e-05|  0.00%|t2 = threading.Thread(target=func)
(call)|         1|  0.000438929|  0.000438929|  0.04%|# /usr/lib/python2.7/threading.py:436 __init__
    12|         1|  4.79221e-05|  4.79221e-05|  0.00%|t1.start()
(call)|         1|  0.000843048|  0.000843048|  0.08%|# /usr/lib/python2.7/threading.py:485 start
    13|         1|  6.48499e-05|  6.48499e-05|  0.01%|t2.start()
(call)|         1|   0.00115609|   0.00115609|  0.11%|# /usr/lib/python2.7/threading.py:485 start
    14|         1|  0.000205994|  0.000205994|  0.02%|(func(), func2())
(call)|         1|      1.00112|      1.00112| 99.54%|# demo/threads.py:4 func
(call)|         1|  3.09944e-05|  3.09944e-05|  0.00%|# demo/threads.py:7 func2
    15|         1|  7.62939e-05|  7.62939e-05|  0.01%|t1.join()
(call)|         1|  0.000423908|  0.000423908|  0.04%|# /usr/lib/python2.7/threading.py:653 join
    16|         1|  5.26905e-05|  5.26905e-05|  0.01%|t2.join()
(call)|         1|  0.000320196|  0.000320196|  0.03%|# /usr/lib/python2.7/threading.py:653 join

Note that time.sleep call is not counted as such. For some reason, python is not generating c_call/c_return/c_exception events (which are ignored by current code, as a result).

Generating callgrind-format output in a file instead of stdout:

$ pprofile --format callgrind --out treads.log demo/threads.py

Can be opened, for example, with kcachegrind.

Thread-aware profiling

ThreadProfile class provides the same features are Profile, but uses threading.settrace to propagate tracing to threading.Thread threads started after profiling is enabled.

Limitations

The time spent in another thread is not discounted from interrupted line. On the long run, it should not be a problem if switches are evenly distributed among lines, but threads executing fewer lines will appear as eating more cpu time than they really do.

This is not specific to simultaneous multi-thread profiling: profiling a single thread of a multi-threaded application will also be polluted by time spent in other threads.

Example (lines are reported as taking longer to execute when profiled along with another thread - although the other thread is not profiled):

$ demo/embedded.py
Total duration: 1.00013s
File: demo/embedded.py
File duration: 1.00003s (99.99%)
Line #|      Hits|         Time| Time per hit|      %|Source code
------+----------+-------------+-------------+-------+-----------
     1|         0|            0|            0|  0.00%|#!/usr/bin/env python
     2|         0|            0|            0|  0.00%|import threading
     3|         0|            0|            0|  0.00%|import pprofile
     4|         0|            0|            0|  0.00%|import time
     5|         0|            0|            0|  0.00%|import sys
     6|         0|            0|            0|  0.00%|
     7|         1|   1.5974e-05|   1.5974e-05|  0.00%|def func():
     8|         0|            0|            0|  0.00%|  # Busy loop, so context switches happe, so context switches happenn
     9|         1|  1.40667e-05|  1.40667e-05|  0.00%|  end = time.time() + 1
    10|    146604|     0.511392|  3.48826e-06| 51.13%|  while time.time() < end:
    11|    146603|      0.48861|  3.33288e-06| 48.85%|    pass
    12|         0|            0|            0|  0.00%|
    13|         0|            0|            0|  0.00%|# Single-treaded run
    14|         0|            0|            0|  0.00%|prof = pprofile.Profile()
    15|         0|            0|            0|  0.00%|with prof:
    16|         0|            0|            0|  0.00%|  func()
(call)|         1|      1.00003|      1.00003| 99.99%|# ./demo/embedded.py:7 func
    17|         0|            0|            0|  0.00%|prof.annotate(sys.stdout, __file__)
    18|         0|            0|            0|  0.00%|
    19|         0|            0|            0|  0.00%|# Dual-threaded run
    20|         0|            0|            0|  0.00%|t1 = threading.Thread(target=func)
    21|         0|            0|            0|  0.00%|prof = pprofile.Profile()
    22|         0|            0|            0|  0.00%|with prof:
    23|         0|            0|            0|  0.00%|  t1.start()
    24|         0|            0|            0|  0.00%|  func()
    25|         0|            0|            0|  0.00%|  t1.join()
    26|         0|            0|            0|  0.00%|prof.annotate(sys.stdout, __file__)
Total duration: 1.00129s
File: demo/embedded.py
File duration: 1.00004s (99.88%)
Line #|      Hits|         Time| Time per hit|      %|Source code
------+----------+-------------+-------------+-------+-----------
[...]
     7|         1|  1.50204e-05|  1.50204e-05|  0.00%|def func():
     8|         0|            0|            0|  0.00%|  # Busy loop, so context switches happe, so context switches happenn
     9|         1|  2.38419e-05|  2.38419e-05|  0.00%|  end = time.time() + 1
    10|     64598|     0.538571|  8.33728e-06| 53.79%|  while time.time() < end:
    11|     64597|     0.461432|  7.14324e-06| 46.08%|    pass
[...]

This also means that the sum of the percentage of all lines can exceed 100%. It can reach the number of concurrent threads (200% with 2 threads being busy for the whole profiled executiong time, etc).

Example with 3 threads (same as first example, this time with thread profiling enabled):

$ pprofile demo/threads.py
Command line: ['demo/threads.py']
Total duration: 1.00798s
File: demo/threads.py
File duration: 3.00604s (298.22%)
Line #|      Hits|         Time| Time per hit|      %|Source code
------+----------+-------------+-------------+-------+-----------
     1|         2|  3.21865e-05|  1.60933e-05|  0.00%|import threading
     2|         1|  6.91414e-06|  6.91414e-06|  0.00%|import time
     3|         0|            0|            0|  0.00%|
     4|         4|  3.91006e-05|  9.77516e-06|  0.00%|def func():
     5|         3|      3.00539|       1.0018|298.16%|  time.sleep(1)
     6|         0|            0|            0|  0.00%|
     7|         2|  2.31266e-05|  1.15633e-05|  0.00%|def func2():
     8|         1|  2.38419e-05|  2.38419e-05|  0.00%|  pass
     9|         0|            0|            0|  0.00%|
    10|         1|  1.81198e-05|  1.81198e-05|  0.00%|t1 = threading.Thread(target=func)
(call)|         1|  0.000612974|  0.000612974|  0.06%|# /usr/lib/python2.7/threading.py:436 __init__
    11|         1|  1.57356e-05|  1.57356e-05|  0.00%|t2 = threading.Thread(target=func)
(call)|         1|  0.000438213|  0.000438213|  0.04%|# /usr/lib/python2.7/threading.py:436 __init__
    12|         1|  6.60419e-05|  6.60419e-05|  0.01%|t1.start()
(call)|         1|  0.000913858|  0.000913858|  0.09%|# /usr/lib/python2.7/threading.py:485 start
    13|         1|   6.8903e-05|   6.8903e-05|  0.01%|t2.start()
(call)|         1|   0.00167513|   0.00167513|  0.17%|# /usr/lib/python2.7/threading.py:485 start
    14|         1|  0.000200272|  0.000200272|  0.02%|(func(), func2())
(call)|         1|      1.00274|      1.00274| 99.48%|# demo/threads.py:4 func
(call)|         1|  4.19617e-05|  4.19617e-05|  0.00%|# demo/threads.py:7 func2
    15|         1|  9.58443e-05|  9.58443e-05|  0.01%|t1.join()
(call)|         1|  0.000411987|  0.000411987|  0.04%|# /usr/lib/python2.7/threading.py:653 join
    16|         1|  5.29289e-05|  5.29289e-05|  0.01%|t2.join()
(call)|         1|  0.000316143|  0.000316143|  0.03%|# /usr/lib/python2.7/threading.py:653 join

Note that the call time is not added to file total: it’s already accounted for inside “func”.