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Build Status codecov openSUSE Tumbleweed package

openSUSE-release-tools

Rethink release tooling presentation overview

Everything denoted with a cloud is largely in this repository while the rest is the open-build-service (OBS).

Installation

For non-development usage just install the package.

zypper in openSUSE-release-tools

Many sub-packages are provided which can be found either by searching or looking on the build service.

zypper se openSUSE-release-tools osc-plugin

If CI builds are needed add the appropriate openSUSE:Tools repository.

Usage

All tools provide help documentation accessible via --help.

For osc plugins include the plugin name after osc like the following.

osc staging --help

For other tools execute the tool directly.

osrt-repo-checker --help

See the docs directory or a specific tool directory for specific tool documentation outside of --help. The wiki also contains some additional documentation.

Development

git clone https://github.com/openSUSE/openSUSE-release-tools.git

If working on an osc plugin create symlinks for the plugin and osclib in either ~/.osc-plugins or /usr/lib/osc-plugins. For example to install the staging plugin do the following.

mkdir -p ~/.osc-plugins
ln -sr ./osc-staging.py ./osclib ~/.osc-plugins

It can also be useful to work against a development copy of osc either to utilize new features or to debug/fix functionality. To do so one must place the development copy in the path to be loaded and utilize the wrapper script if working on osc plugins. One method to accomplish this is shown below.

# outside of openSUSE-release-tools checkout
git clone https://github.com/openSUSE/osc.git

# inside openSUSE-release-tools checkout
# note the ending /osc which points to the osc directory within the checkout
ln -s /path/to/osc/osc ./

# to utilize the wrapper for working on osc plugins from osrt checkout
$(realpath ./osc)/../osc-wrapper.py --version

Using Docker Compose, a containerized OBS can be started via one command. The default credentials are Admin and opensuse on 0.0.0.0:3000. You can change the port by setting the environment variable OSRT_EXPOSED_OBS_PORT.

docker-compose -f dist/ci/docker-compose.yml up api

An osc alias is automatically configured as local.

osc -A local api /about

A facsimile of openSUSE:Factory in the form of a subset of the related data can be quickly created in a local OBS instance using the obs_clone tool.

./obs_clone.py --debug --apiurl-target local

Some tests will attempt to run against the local OBS, but not all.

nosetests

Running Continuous Integration

This repository includes all the needed files to set up and run the Continuous Integration test suite. The idea is to use Docker Compose to orchestrate a set of containers, including an OBS instance, and run the tests on top of them. Although they automatically run on GitHub Actions (more on that later), it is easy to run them locally. The following commands must be executed from the root of the repository.

# Mount the current path at the /code directory on the container
sed -i -e "s,../..:,$PWD:," dist/ci/docker-compose.yml

# Run the linter
docker-compose -f dist/ci/docker-compose.yml run flaker

# Run the test full suite (it may take some time)...
docker-compose -f dist/ci/docker-compose.yml run test

# .. or just run a single test (i.e., the 'tests/util_tests.py')
docker-compose -f dist/ci/docker-compose.yml run test run_as_tester nosetests tests/util_tests.py

# We are finished. Now you can shut the containers down.
docker-compose -f dist/ci/docker-compose.yml down

The docker-compose.yml mentions two container images that are built in the openSUSE:Tools:Images project:

  • osrt-miniobs-for-ci is the base of OBS-related services (API, caches, SMTP, and so on).
  • osrt-testenv-tumbleweed used to run the tests. The code and the tests are mounted in the /code directory of this container.

As mentioned before, the main repository uses GitHub Actions to automatically run the tests when a pull request is opened or the code is pushed to the master branch. You can find the details in the workflow definition. Note that, in addition to the steps listed before, code coverage data is submitted to Codecov.

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