Jay Taylor's notesback to listing index
GitHub - cknd/stackprinter: Debugging-friendly exceptions for Python[web search]
This is a more helpful version of Python's built-in exception message: It shows more code context and the current values of nearby variables. That answers many of the questions I'd ask an interactive debugger: Where in the code was the crash, what's in the relevant variables, and why was that function called with those arguments. It either prints to the console or gives you a string for logging.
pip3 install stackprinter
Traceback (most recent call last): File "demo.py", line 12, in <module> dangerous_function(somelist + anotherlist) File "demo.py", line 6, in dangerous_function return sorted(blub, key=lambda xs: sum(xs)) File "demo.py", line 6, in <lambda> return sorted(blub, key=lambda xs: sum(xs)) TypeError: unsupported operand type(s) for +: 'int' and 'str'
File demo.py, line 12, in <module> 9 somelist = [[1,2], [3,4]] 10 anotherlist = [['5', 6]] 11 spam = numpy.zeros((3,3)) --> 12 dangerous_function(somelist + anotherlist) 13 except: .................................................. somelist = [[1, 2, ], [3, 4, ], ] anotherlist = [['5', 6, ], ] spam = 3x3 array([[0. 0. 0.] [0. 0. 0.] [0. 0. 0.]]) .................................................. File demo.py, line 6, in dangerous_function 5 def dangerous_function(blub): --> 6 return sorted(blub, key=lambda xs: sum(xs)) .................................................. blub = [[1, 2, ], [3, 4, ], ['5', 6, ], ] .................................................. File demo.py, line 6, in <lambda> 3 4 5 def dangerous_function(blub): --> 6 return sorted(blub, key=lambda xs: sum(xs)) 7 .................................................. xs = ['5', 6, ] .................................................. TypeError: unsupported operand type(s) for +: 'int' and 'str'
I sometimes use this locally instead of a real debugger, but mostly it helps me sleep when my code runs somewhere where the only debug tool is a log file (though it's not a fully-grown error monitoring system).
By default, it tries to be somewhat polite about screen space (showing only a handful of source lines & the function header, and only the variables in those lines, and only (?) 500 characters per variable). You can configure exactly how verbose things should be.
It outputs plain text normally, which is good for log files. There's also a color mode for some reason , with a few different color schemes for light and dark backgrounds. (The colors track different variables instead of the language syntax.)
To replace the default python crash printout, call
set_excepthook() somewhere. This will print detailed stacktraces for any uncaught exception except KeyboardInterrupts (to stderr, by default). You could also make this permanent for your python installation.
import stackprinter stackprinter.set_excepthook(style='darkbg2') # for jupyter notebooks try style='lightbg'
For more control, call
format() inside an
show() prints to stderr by default,
format() returns a string, for custom logging.
try: something() except: # print the current exception to stderr: stackprinter.show() # ...or instead, get a string for logging: logger.error(stackprinter.format())
Or pass specific exceptions explicitly:
try: something() except RuntimeError as exc: tb = stackprinter.format(exc) logger.error('The front fell off.\n' + tb)
It's also possible to integrate this neatly with standard logging calls through a bit of extra plumbing.
configure_logging() # adds a custom log formatter, see link above try: something() except: logger.exception('The front fell off.') # Logs a rich traceback along with the given message
For all the config options see the docstring of
Printing the current call stack
To see your own thread's current call stack, call
format anywhere outside of exception handling.
stackprinter.show() # or format()
Printing the stack of another thread
To inspect the call stack of any other running thread:
thread = threading.Thread(target=something) thread.start() # (...) stackprinter.show(thread) # or format(thread)
Making it stick
To permanently replace the crash message for your python installation, you could put a file
sitecustomize.py into the
site-packages directory under one of the paths revealed by
python -c "import site; print(site.PREFIXES)", with contents like this:
# in e.g. some_virtualenv/lib/python3.x/site-packages/sitecustomize.py: import stackprinter stackprinter.set_excepthook(style='darkbg2')
That would give you colorful tracebacks automatically every time, even in the REPL.
(You could do a similar thing for IPython, but they have their own method, where the file goes into
~/.ipython/profile_default/startup instead, and also I don't want to talk about what this module does to set an excepthook under IPython.)
For now, the documentation consists only of some fairly detailed docstrings, e.g. those of
This displays variable values as they are at the time of formatting. In multi-threaded programs, variables can change while we're busy walking the stack & printing them. So, if nothing seems to make sense, consider that your exception and the traceback messages are from slightly different times. Sadly, there is no responsible way to freeze all other threads as soon as we want to inspect some thread's call stack (...or is there?)
How it works
Basically, this is a frame formatter. For each frame on the call stack, it grabs the source code to find out which source lines reference which variables. Then it displays code and variables in the neighbourhood of the last executed line.
Since this already requires a map of where each variable occurs in the code, it was difficult not to also implement the whole semantic highlighting color thing seen in the screenshots. The colors are ANSI escape codes now, but it should be fairly straightforward™ to render the underlying data without any 1980ies terminal technology. Say, a foldable and clickable HTML page with downloadable pickled variables. For now you'll have to pipe the ANSI strings through ansi2html or something.
The format and everything is inspired by the excellent
ultratb in IPython. One day I'd like to contribute the whole "find out which variables in
globals are nearby in the source and print only those" machine over there, after trimming its complexity a bit.
Tracing a piece of code
More for curiosity than anything else, you can watch a piece of code execute step-by-step, printing a trace of all calls & returns 'live' as they are happening. Slows everything down though, of course.
with stackprinter.TracePrinter(style='darkbg2'): dosomething()
tp = stackprinter.TracePrinter(style='darkbg2') tp.enable() dosomething() # (...) +1 million lines tp.disable()