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README.md
 
 
Solution oriented error handling.odp
 
 
application.py
 
 
chaining.py
 
 
contextmanager.py
 
 
dataerror.py
 
 
fragments.py
 
 
performance.py
 
 

README.md

Solution oriented error handling

Solution oriented error handling is a set of guidelines and best practices using Python's built in error handling mechanisms to keep the productive code clean, derive helpful error messages directly from the code and release resources properly. It simplifies focusing on the productive parts of the code and supporting your applications in case things go wrong.

These are the slides and code examples for a talk given at the EuroPython 2014 conference. A video is a available at https://www.youtube.com/watch?v=kT34QMil-FQ.

  • application.py - a template for a command line application that logs errors the user can fix without a stack trace and the errors only the developer can fix with a stack trace.
  • chaining.py - example usage of exception chaining
  • contextmanager.py - an example on how to implement context managers that properly clean up even if initialization was only partially possibly.
  • dataerror.py - an example on how to define your own exception that can indicate that there is an issue in the data the user provided and should fix. There is both a simple variant that just allows to specify an error message and a more sophisticated on where you can specify the file, line number and column where the error originated from.
  • fragments.py - various code fragments used in the slides
  • performance.py - a performance test showcasing there is hardly any difference in dealing with non existent dictionary keys by means of existence checks, default values and exception handling. This was not mentioned in the talk due time constraints.

The code examples work with Python 3.4+ though most features also apply for Python 2.

An earlier German version of this talk was presented at the Grazer Linuxtag 2013, you can find the slides at https://github.com/roskakori/talks/tree/master/linuxtage/.