How to Install and Uninstall python39-python-subunit Package on openSuSE Tumbleweed

Last updated: May 15,2024

1. Install "python39-python-subunit" package

This guide covers the steps necessary to install python39-python-subunit on openSuSE Tumbleweed

$ sudo zypper refresh $ sudo zypper install python39-python-subunit

2. Uninstall "python39-python-subunit" package

In this section, we are going to explain the necessary steps to uninstall python39-python-subunit on openSuSE Tumbleweed:

$ sudo zypper remove python39-python-subunit

3. Information about the python39-python-subunit package on openSuSE Tumbleweed

Information for package python39-python-subunit:
------------------------------------------------
Repository : openSUSE-Tumbleweed-Oss
Name : python39-python-subunit
Version : 1.4.2-3.5
Arch : noarch
Vendor : openSUSE
Installed Size : 379.0 KiB
Installed : No
Status : not installed
Source package : subunit-1.4.2-3.5.src
Upstream URL : https://github.com/testing-cabal/subunit
Summary : Streaming protocol for test results
Description :
Subunit is a streaming protocol for test results. The protocol is a
binary encoding that is generated and parsed. By design, all the
components of the protocol conceptually fit into the xUnit TestCase ->
TestResult interaction.
Subunit comes with command line filters to process a subunit stream and
language bindings for Python, C, C++ and Shell. Bindings can be
written for other languages.
A number of useful things can be done easily with subunit:
- Test aggregation: Tests run separately can be combined and then
reported/displayed together. For instance, tests from different
languages can be shown as a seamless whole.
- Test archiving: A test run may be recorded and replayed later.
- Test isolation: Tests that may crash or otherwise interact badly with
each other can be run separately and then aggregated, rather than
interfering with each other.
- Grid testing: subunit can act as the necessary serialization and
deserialization to get test runs on distributed machines to be
reported in real time.