Esmail wrote:
Tim Chase wrote:
However the first rule: profile first!
Do you have a favorite profiling tool? What should someone new
to Python (but not programming) use?
I personally use the cheapo method of dropping in a few "print"
statements to dump where I currently am in the app, and then see
where it hangs. "Hmm, it seems to take a long time to get from
step J to step K, I better zoom in on that block of code" I
usually have a good intuition where to go digging first (such as
multi-nested loops, network communications, file I/O, or database
queries) which is fairly close most of the time.
If possible, I'll occasionally comment out the code I suspect (or
perform a null-op instead of actually executing the block) to
confirm that this block is the problem. However, sometimes I
can't readily do that because it sets up data structures that are
needed elsewhere.
There are several profiling tools for Python, including the
cProfile module[1] but I've never gotten to the point where I've
needed that level of detail.
-tkc
[1] http://docs.python.org/library/profile.html
PS: this is a trade-off between "what I've always done" and
"darn, the stdlib provides yet one more battery I could be using
instead of rolling my own". I finally switched to using the csv,
ConfigParser, pdb, and optparse modules because they were faster
routes to better solutions than my own hacks. However I still
tend to just use print statements for profiling & logging instead
of the logging and cProfile modules. I guess I just haven't
experienced enough pain in my own code to switch yet :)
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