Comparison With Other Tools

There are other options for doing Gherkin-based BDD in Python. We’ve listed the main ones below and why we feel you’re better off using behave. Obviously this comes from our point of view and you may disagree. That’s cool. We’re not worried whichever way you go.

This page may be out of date as the projects mentioned will almost certainly change over time. If anything on this page is out of date, please contact us.

Cucumber

You can actually use Cucumber to run test code written in Python. It uses “rubypython” (dead) to fire up a Python interpreter inside the Ruby process though and this can be somewhat brittle. Obviously we prefer to use something written in Python but if you’ve got an existing workflow based around Cucumber and you have code in multiple languages, Cucumber may be the one for you.

Lettuce

lettuce is similar to behave in that it’s a fairly straight port of the basic functionality of Cucumber. The main differences with behave are:

  • Single decorator for step definitions, @step.
  • The context variable, world, is simply a shared holder of attributes. It never gets cleaned up during the run.
  • Hooks are declared using decorators rather than as simple functions.
  • No support for tags.
  • Step definition code files can be anywhere in the feature directory hierarchy.

The issues we had with Lettuce that stopped us using it were:

  • Lack of tags.
  • The hooks functionality was patchy. For instance it was very hard to clean up the world variable between scenario outlines. Behave clears the scenario-level context between outlines automatically.
  • Lettuce’s handling of stdout would occasionally cause it to crash mid-run in such a way that cleanup hooks were never run.
  • Lettuce uses import hackery so .pyc files are left around and the module namespace is polluted.

Freshen

freshen is a plugin for nose that implements a Gherkin-style language with Python step definitions. The main differences with behave are:

  • Operates as a plugin for nose, and is thus tied to the nose runner and its output model.
  • Has some additions to its Gherkin syntax allowing it to specify specific step definition modules for each feature.
  • Has separate context objects for various levels: glc, ftc and scc. These relate to global, feature and scenario levels respectively.

The issues we had with Freshen that stopped us using it were:

  • The integration with the nose runner made it quite hard to properly debug how and why tests were failing. Quite often you’d get a rather cryptic message with the actual exception having been swallowed.
  • The feature-specific step includes could lead to specific sets of step definitions for each feature despite them warning against doing that.
  • The output being handled by nose meant that you couldn’t do cucumber-style output without the addition of more plugins.
  • The context variable names are cryptic and moving context data from one level to another takes a certain amount of work finding and renaming. The behave context variable is much more flexible.
  • Step functions must have unique names, even though they’re decorated to match different strings.
  • As with Lettuce, Freshen uses import hackery so .pyc files are left around and the module namespace is polluted.
  • Only Before and no contextual before/after control, thus requiring use of atexit for teardown operations and no fine-grained control.

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