Debugging Python Programs¶
Techniques¶
The print statement¶
Sometimes the quickest/easiest solution is just to throw a few print statements into your code. Not a good idea for complex problems. Some very good programmers disdain this technique, calling it sloppy. However others really very good programmers, such as Rob Pike (early contributor to Unix, father of Plan 9, UTF-8, and Go) is said to approve of this method.
IPython¶
IPython is an interactive interpreter shell with more features than the default Python REPL shell.
While not used for debugging per se, an interactive session can be a good way to understand and explore small bits of code.
(venv)$ pip install ipython
Debugger¶
A debugger is a computer program that lets you run your program, line by line and examine the values of variables or look at values passed into functions and let you figure out why it isn’t running the way you expected it to. [1]
Logging¶
While running code in a debugger offers the maximum visibility into its operation, it may be difficult or impossible to correctly simulate a production environment (including number of connections, network topography, load, etc) while a program is running inside a debugger.
Logging statements offer an alternative way to gain insight into your code’s operation. Verbose logging can be especially helpful for understanding bugs in highly concurrent code, where it would be difficult to inspect each thread/process in an ordinary debugger.
Logging is an essential part of 12-Factor methodology for building modern applications.
Debuggers¶
Eclipse¶
Eclipse offers a graphical debugger, making it easy to explore your code and set breakpoints while running in the debugger.
Note: Eclipse’s PyDev debugger is powerful, but notoriously flakey. Expect a few hiccups!
pdb¶
Todo
Brief description of pdb, maybe a simple example.
Common Species of Bug¶
Todo
Add an example for each (?) species of bug.
http://stackoverflow.com/questions/1011431/common-pitfalls-in-python
Indentation¶
Usually results from mixture of tabs & spaces, causing the actual scope of some lines to be different than it appears on the programmer’s screen.
Wrong Number of Arguments¶
A function is called with the wrong number (too few or too many) arguments, causing an exception to be thrown.
Wrong Package¶
You type import foobar, and the module imported is foobar.py in the local folder, not the foobar module in the standard library.
Catchign Multiple Exceptions¶
Be careful catching multiple exception types: [2]
try:
raise KeyError("hmm bug")
except KeyError, TypeError:
print TypeError
This prints “hmm bug”, though it is not a bug; it looks like we are catching exceptions of both types, but instead we are catching KeyError only as variable TypeError.
PythonTutor can help us visualize what is happening.
The correct way to catch multiple exceptions is to put them in parentheses:
try:
raise KeyError("hmm bug")
except (KeyError, TypeError):
print TypeError
Unqualified except: block¶
Do you really want to catch all exceptions? Can your except block really recover from all the exceptions it catches?
Populating Arrays¶
When you need a population of arrays you might be tempted to type something like this: [3]
>>> a=[[1,2,3,4,5]]*4
And sure enough it will give you what you expect when you look at it
>>> from pprint import pprint
>>> pprint(a)
[[1, 2, 3, 4, 5],
[1, 2, 3, 4, 5],
[1, 2, 3, 4, 5],
[1, 2, 3, 4, 5]]
But don’t expect the elements of your population to be seperate objects:
>>> a[0][0] = 2
>>> pprint(a)
[[2, 2, 3, 4, 5],
[2, 2, 3, 4, 5],
[2, 2, 3, 4, 5],
[2, 2, 3, 4, 5]]
Unless this is what you need...
It is worth mentioning a workaround:
a = [[1,2,3,4,5] for i in range(4)]
Footnotes
| [1] | http://cplus.about.com/od/glossar1/g/debugdefinition.htm |
| [2] | http://stackoverflow.com/q/1011431/164308 |
| [3] | http://stackoverflow.com/a/1025447/164308 |