MAmau·Dec 30, 2015
Here is a profiler developed by dropbox using the same technique described in the article:
- https://blogs.dropbox.com/tech/2012/07/plop-low-overhead-pro...
- https://github.com/bdarnell/plop
In Profiling Python in Productionbdarnell
plop
Python2012–2015
bdarnell / plop · Archived
plop
Python Low-Overhead Profiler
4Distinct people
4Mentions
0Explicit recommenders
921GitHub stars
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What it is
Python Low-Overhead Profiler
GitHub
Where it is used
No documented product use has been verified yet.
What people are saying
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HN mentions by year4 dated mentions
Observed mentions: 2012-07-10 22:22:15 UTC to 2015-12-30 09:02:01 UTC.
Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.
View mention counts and date ranges
| Period | Start (UTC) | End (exclusive, UTC) | Mentions | Submissions | Comments |
|---|---|---|---|---|---|
| 2012 | 2012-01-01 00:00:00 UTC | 2013-01-01 00:00:00 UTC | 1 | 0 | 1 |
| 2013 | 2013-01-01 00:00:00 UTC | 2014-01-01 00:00:00 UTC | 1 | 0 | 1 |
| 2014 | 2014-01-01 00:00:00 UTC | 2015-01-01 00:00:00 UTC | 1 | 0 | 1 |
| 2015 | 2015-01-01 00:00:00 UTC | 2016-01-01 00:00:00 UTC | 1 | 0 | 1 |
What Hacker News says
4 sourcesGNU/Linux emacs user for Python dev.
The ability to browser a code easily, when you don't actually know the code, is a lot of time that will be saved.
Pycharm is the best tool I know that does it out of the box.
I don't know about its debugging facility (I think you mean setting break points), probably https://github.com/narfdotpl/debug will work just fine. I've been doing 1 year and a half of debugging Python code and used it three times. Most of the time the workflow is this:
0) add logs?
1) reproduce the bug
2) read the logs?
3) read the code?
4) if the best fix is found fix it else restart at 0)
Other useful tools for debugging:
- http://dpaste.com/hold/1751069/ this is the basic version of what I use at work. It's a data descriptor [1]
- http://faulthandler.readthedocs.org/ "for when there is no traceback"
- Since you do UI, most lik
Read the rest
ely you'll deal with asynchronous callback style code (non-yield based), the traceback of a callback is not always useful ie. you want to know to which code it is answering to. For that matter you need tweak the event-loop code... having this patch at hand is helpful. e.g. say you do a asynchronous call to retrieve something in the database, the call probably looks like "query(callback=query_callback)", when the "query_callback" will be called by the event loop with the result of the query as arguments, most likely the immediate top frame is the event-loop (if it's not the previous frame, it's the one before...) and "query" function will not be in the callstack of course... If "query_callback" is used as a callback of several asynchronous calls, you can not find the "calling code" with "find usage" of your IDE... I think asyncio fix this
Profiling:
- http://www.vrplumber.com/programming/runsnakerun/
- https://github.com/bdarnell/plop
- https://github.com/wyplay/pytracemalloc it is integrated in Python 3.4
I also use gdb on python coredumps.
[1] http://www.cafepy.com/article/python_attributes_and_methods/...
You can also use a statistical/sampling profiler like https://github.com/bdarnell/plop. This is useful for getting profile data from a live server because it has much lower overhead than the other options and can be turned on and off while the application is running.
In Profiling Python Like a BossDoing this:
>python -m plop.viewer --datadir=/tmp/profile.out
Causes this:
>ImportError: No module named pstats_loader
Traceback (most recent call last):
File "/usr/lib/python2.7/runpy.py", line 162, in _run_module_as_main
"__main__", fname, loader, pkg_name)
File "/usr/lib/python2.7/runpy.py", line 72, in _run_code
exec code in run_globals
File "/home/callen/.virtualenvs/scar/lib/python2.7/site-packages/plop/viewer.py", line 12, in <module>
from plop.pstats_loader import load_pstats
I can't find it in
>https://github.com/bdarnell/plop/tree/master/plop
either.
Commenting out line 12 in viewer.py appears to get it past that error. I don't enjoy hacking up library code installed by pip in my virtualenvs.
In Plop: Low-overhead profiling for Python