Introducing conu – Scripting Containers Made Easier
There has been a need for a simple, easy-to-use handler for writing tests and other code around containers that would implement helpful methods and utilities. For this we introduce conu, a low-level Python library.
This project has been driven from the start by the requirements of container maintainers and testers. In addition to basic image and container management methods, it provides other often used functions, such as container mount, shortcut methods for getting an IP address, exposed ports, logs, name, image extending using source-to-image, and many others.
conu aims for stable engine-agnostic APIs that would be implemented by several container runtime back-ends. Switching between two different container engines should require only minimum effort. When used for testing, one set of tests could be executed for multiple back-ends.
In the following example there is a snippet of code in which we run a container from a specified image, check its output, and gracefully delete.
We have decided our desired container runtime would be docker (now the only fully implemented container runtime). The image is run with an instance of DockerRunBuilder, which is the way to set additional options and custom commands for the docker container run command.
import conu, logging def check_output(image, message): command_build = conu.DockerRunBuilder(command=['echo', message]) container = image.run_via_binary(command_build) try: # check_output assert container.logs_unicode() == message + '\n' finally: #cleanup container.stop() container.delete() if __name__ == '__main__': with conu.DockerBackend(logging_level=logging.DEBUG) as backend: image = backend.ImageClass('registry.access.redhat.com/rhscl/httpd-24-rhel7') check_output(image, message='Hello World!')
Get http response
When dealing with containers that run as services, the container state ‘Running’ is often not enough. We need to check that its port is open and ready to serve, and also to send custom requests to it.
def check_container_port(image): """ run container and wait for successful response from the service exposed via port 8080 """ port=8080 container = image.run_via_binary() container.wait_for_port(port) # check httpd runs http_response = container.http_request(port=port) assert http_response.ok # cleanup container.delete(force=True)
Look inside the container filesystem
To check presence and content of the configuration files, conu provides a way to easily mount the container filesystem with a predefined set of useful methods. The mount is in read-only mode, but we plan to also implement read-write modes in the next releases.
def mount_container_filesystem(image): # run httpd container container = image.run_via_binary() # mount container filesystem with container.mount() as fs: # check presence of httpd configuration file assert fs.file_is_present('/etc/httpd/conf/httpd.conf') # check presence of default httpd index page index_path = ‘/opt/rh/httpd24/root/usr/share/httpd/noindex/index.html’ assert fs.file_is_present(index_path) # and its content index_text = fs.read_file(index_path)
So why not just use docker-py?
Aside from docker, conu also aims to support other container runtimes by providing a generic API. To implement the docker back-end, conu actually uses docker-py. Conu also implements other utilities that are generally used when dealing with containers. Adopting other utilities should be also simple.
And what about container testing frameworks?
You don’t have to be limited by a specified a set of tests. When writing code with conu, you can acquire ports, sockets, and filesystems, and the only limits you have are the ones set by Python. In the cases where conu does not support certain features and you don’t want to deal with a subprocess, there is a run_cmd utility that helps you simply run the desired command.
We are reaching out to you to gather feedback and encourage contribution to conu to make scripting around containers even more efficient. We have already successfully used conu for several image tests (for example here), and it also helped while implementing clients for executing specific kinds of containers.