deb-python-gabbi/docs/source/index.rst

format loader example jsonpath host fixtures handlers runner release faq gabbi

Gabbi

Gabbi is a tool for running HTTP tests where requests and responses are expressed as declarations in a collection of YAML files. The simplest test looks like this:

tests:
- name: A test
  GET: /api/resources/id

See the rest of these docs for more details on the many features and formats for setting request headers and bodies and evaluating responses.

The name is derived from "gabby": excessively talkative. In a test environment having visibility of what a test is actually doing is a good thing. This is especially true when the goal of a test is to test the HTTP, not the testing infrastructure. Gabbi tries to put the HTTP interaction in the foreground of testing.

Tests can be run using unittest <test_loaders> style test runners or py.test or from the command line with a gabbi-run <runner> script.

If you want to get straight to creating tests look at example, the test files in the source distribution and format. A gabbi-demo repository provides a tutorial of using gabbi to build an API, via the commit history of the repo.

Purpose

Gabbi works to bridge the gap between human readable YAML files (see format for details) that represent HTTP requests and expected responses and the rather complex world of automated testing.

Each YAML file represents an ordered list of HTTP requests along with the expected responses. This allows a single file to represent a process in the API being tested. For example:

• Create a resource.
• Retrieve a resource.
• Delete a resource.
• Retrieve a resource again to confirm it is gone.

At the same time it is still possible to ask gabbi to run just one request. If it is in a sequence of tests, those tests prior to it in the YAML file will be run (in order). In any single process any test will only be run once. Concurrency is handled such that one file runs in one process.

These features mean that it is possible to create tests that are useful for both humans (as tools for learning, improving and developing APIs) and automated CI systems.

Significant flexibility and power is available in the format to make it relatively straightforward to test existing complex APIs. This extended functionality includes the use of JSONPath to query response bodies and templating of test data to allow access to the prior HTTP response in the current request. For APIs which do not use JSON additional handlers can be created.

Care should be taken when using this functionality when you are creating a new API. If your API is so complex that it needs complex test files then you may wish to take that as a sign that your API itself too complex. One goal of gabbi is to encourage transparent and comprehensible APIs.

Though gabbi is written in Python and under the covers uses unittest data structures and processes, there is no requirement that the host be a Python-based service. Anything talking HTTP can be tested. A runner makes it possible to simply create YAML files and point them at a running server.