manually change global printer in Jupyter or IPython.print current stack, when there's no exception.run python code without changes: a script, a module, a commnad.Step 7: Go back to step 1 once bugs appear. Step 6: Erase all recently added printouts, logging and exception messages. Step 5: Examine the printouts and possibly add some more info (then go back to step 2). Step 4: Wait till (hopefully) the bug repeats. Step 2: Add more printouts, logging, and exception messages. Step 1: Notice some exception in a production service. Stop this tedious practice in production: Note: you can deploy more serious frameworks, Yes, of course! That way it might save you even more time (watch out for sensitive data Should I use it after debugging is over, i.e. 18:24:31 main ERROR builtins.ZeroDivisionError: division by zeroįree your exceptions of unnecessary information load: def make_a_cake ( sugar, eggs, milk, flour, salt, water ): is_sweet = sugar > salt is_vegan = not ( eggs or milk ) is_huge = ( sugar + eggs + milk + flour + salt + water > 10000 ) if not ( is_sweet or is_vegan or is_huge ): raise ValueError ( 'This is unacceptable, guess why!' ). 18:24:31 main ERROR return height / width

18:24:31 main ERROR File './temp.py', line 13, in get_ratio 18:24:31 main ERROR File './temp.py', line 10, in get_avg_ratio 18:24:31 main ERROR return get_avg_ratio(, ) 18:24:31 main ERROR File './temp.py', line 7, in main 18:24:31 main ERROR Traceback with variables (most recent call last):

with printing_exc ( file_ = LoggerAsFile ( logger )). Return mean(])īuiltins.ZeroDivisionError: division by zeroĪutomate your logging too: logger = logging. Return mean(get_ratio(h, w) for h, w in )Īnd obtain total debug info spending 0 lines of code: Traceback with variables (most recent call last):įile './temp.py', line 10, in get_avg_ratio Into this (zero debug code): + from traceback_with_variables import activate_by_import def main(): except: - logger.error(f'something happened :(, variables = ') Turn a code totally covered by debug formatting from this: def main(): max_value_str_len = 10000 default_format. Print traceback in interactive mode after an exception: > print_exc()Ĭustomize any of the previous examples: default_format. Using a logger : with printing_exc ( file_ = LoggerAsFile ( logger )): # or ( file_ = LoggerAsFile ( logger )): No exception but you want to print the stack anyway?: print_cur_tb () Work with traceback lines in a custom manner: lines = list ( iter_exc_lines ( e )) Simplest usage in Jupyter or IPython, for the whole program: from traceback_with_variables import activate_in_ipython_by_importĭecorator, for a single function: # def main(): or def some_func(.):Ĭontext, for a single code block: with printing_exc (): Simplest usage in regular Python, for the whole program: from traceback_with_variables import activate_by_import Using without code editing, running your script/command/module: traceback-with-variables tested_script.py. Installation pip install traceback-with-variablesĬonda install -c conda-forge traceback-with-variables I think in this particular domain this is rather achievable, so I'll try. When I started it I wanted to make a tool meeting all standard use cases. :warning: This module is actively updated and has a substantial list of features to add this week: so any proposal or advice or warning is very welcome and will be taken into account of course. Tired of useless job of putting all your variables into debug exception messages? Just stop it.Īutomate it and clean your code. “It is useless work that darkens the heart.” Very simple to use, but versatile when needed. This knowledge helps in diagnosing and fixing issues efficiently, improving the overall reliability of Python applications.Python Traceback (Error Message) Printing Variables Type(exc_value), exc_value, exc_tracebackĪlternatively, you can obtain a formatted string representation of the traceback using the traceback.format_exc() function: import tracebackīy analyzing the traceback object, developers can gain insights into the call stack, track the execution path, and pinpoint the source of errors or exceptions in their code. Traceback_obj = traceback.TracebackException( Here’s an example of the basic syntax: import tracebackĮxc_type, exc_value, exc_traceback = sys.exc_info() To obtain a traceback object, you typically catch an exception using a try-except block and then use one of the functions from the traceback module to generate or work with the traceback.

It represents a stack trace, providing detailed information about the sequence of function calls that led to an exception or error in a Python program. The Python traceback object is a fundamental component used in debugging and error reporting.

Traceback python