Gabbi is a tool for running HTTP tests where requests and responses are expressed as declarations in YAML files:
tests: - name: retrieve items GET: /items
See the rest of these docs for more details on the many features and formats for setting request headers and bodies and evaluating responses.
Tests can be run from the command line with gabbi-run or programmatically using either py.test or unittest-style test runners. See installation instructions below.
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.
If you want to get straight to creating tests look at Example Tests, the test files in the source distribution and Test Format. A gabbi-demo repository provides a tutorial of using gabbi to build an API, via the commit history of the repo.
Gabbi works to bridge the gap between human readable YAML files (see Test 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 Test 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 Content 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 Target Host be a Python-based service. Anything talking
HTTP can be tested. A YAML Runner makes it possible to simply
create YAML files and point them at a running server.
As a Python package, gabbi is typically installed via pip:
pip install gabbi
You might want to create a virtual environment; an isolated context for Python packages, keeping gabbi cleany separated from the rest of your system.
Python 3 comes with a built-in tool to create virtual environments:
python3 -m venv venv . venv/bin/activate pip install gabbi
This way we can later use
deactivate and safely remove the
directory, thus erasing any trace of gabbi from the system.
If you prefer to not install gabbi, or perhaps want to use it in a dynamic
fashion in a CI setting, there is an official container image hosted at
docker hub as
cdent/gabbi. It allows running gabbi-run
with any arguments you might need, providing tests on STDIN of via a mounted