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Contributing to Checkmk

Thanks for your interest to contribute to Checkmk on Github!

Here are some ways you can help out:

  • Bug fixes (as pull requests)
  • Feature enhancements (as pull requests)
  • New plugins (via Checkmk Exchange)

Here are the links to major sections of this document:

If you have questions, please create a post at the Checkmk Forum.

We are interested in all feature extensions, which fit to the product and extend it reasonably. Occasionally, we have to decline a change, if e.g. it breaks other functionality, collides with our product roadmap or affects non-functional requirements of the product. Any contribution must also comply with the coding requirements detailed out below. For feature requests, please share your idea via the Checkmk ideas portal.

Contributing code

In general, we follow the standard GitHub workflow which roughly works like this:

  1. Fork the repository on GitHub
  2. Clone the forked repository to your own machine
  3. Commit changes to your own feature branch
  4. Push your work back up to your forked repository
  5. Submit a Pull request (PR) so that we can review your changes
  6. Sign the necessary CLA either directly in the PR via the bot, or sent the signed document to [email protected] (further information).

⚠ Please reply when asked for more information or to update your PR in case in didn't meet the requirements (e.g. failed checks). If there's no response from the author for a longer period of time, we will close the PR (after giving you a heads up).

If it’s your first time to contribute to an open source project, we recommend reading this guide. You may also want to try the GitHub Hello World tutorial.

How to prepare for contributing

We are developing Checkmk on Ubuntu Linux systems. We support these versions:

  • Current LTS
  • Previous LTS
  • Current non-LTS (If you want bleeding edge, then you get it. We won't support the previous non-LTS)

Anything that deviates from it can not be supported.

To set up the development environment do the following:

  1. Fork the repository and clone to your computer

    Then change to the just created project directory.

    cd checkmk

  2. Install development dependencies

    Before you can start working on Checkmk, you will have to install some additional software, like tools for development and testing. Execute this in the project directory:

    $ make setup

    This is optimized for Ubuntu, but you may also get all the required programs on other platforms.

    After the dependencies have been installed, you could execute the shipped tests to ensure everything is working fine before start making changes to Checkmk. If you like to do this, please have a look at the How to execute tests? chapter.

  3. Install pre-commit checks

    In order to keep your commits to our standard we provide a pre-commit configuration and some custom-made checking scripts. You can install it like this:

    Warning: Python3 is required for pre-commit! Installing it with Python 2 will break your environment and leave you unable to use pip due to a backports module clash!

    $ pip3 install pre-commit

    After successful installation, hook it up to your git-repository by issuing the following command inside your git repository:

    $ pre-commit install --allow-missing-config

    The --allow-missing-config parameter is needed so that branches of older versions of Checkmk which don't support this feature and are missing the configuration file won't throw errors.

    Afterwards your commits will automatically be checked for conformity by pre-commit. If you know a check (like mypy for example) would find an issue, but you don't want to fix it right away you can skip execution of the checkers with git commit -n. Please don't push unchecked changes as this will introduce delays and additional work.

    Additional helpers can be found in scripts/. One notable one is scripts/check-current-commit which checks your commit after it has been made. You can then fix errors and amend or squash your commit. You can also use this script in a rebase like such:

    $ git rebase --exec scripts/check-current-commit

    This will rebase your current changes and check each commit for errors. After fixing them you can then continue rebasing.

Once done, you are ready for the next chapter.

How to change Checkmk

  1. Create your feature branch

    The number one rule is to put each piece of work on its own branch. Please note that in general, we only accept changes which are based on the master branch. There is one (rare) exception, namely bug fixes which only affect older branches. So lets start like this:

    $ git checkout master
$ git checkout -b my-feature-branch

    The first command ensures you start with the master branch. The second command created the branch my-feature-branch. Pick some descriptive name you can remember later.

    Let's check if everything worked fine:

    $ git status
On branch my-feature-branch
(...)

  2. Start developing and create one or multiple commits.

    Important: Do one thing in one commit, e.g. don't mix code reorganization and changes of the moved lines. Separate this in two commits.

    Make sure that you commit in logical blocks and write good commit messages.

    If you have finished your work, it's a good time to execute the tests locally to ensure you did not break anything.

    Once you are done with the commits and tests in your feature branch you could push them to your own GitHub fork like this.

    $ git push -u origin my-feature-branch

    In the output of this command you will see a URL which you can open to create a pull request from your feature branch.

  3. Submit a pull request (PR)

    On GitHub in your browser, submit a pull request from your my-feature-branch to the official Checkmk branch you forked from.

    The Github Actions CI bot will start testing your commits for issues. In case there are issues, it will send you a mail and ask you to fix the issues.

Help: I have a conflict

If you are working on a change in a file while the same file changes in the official repository, this will produce a merge conflict once you try to upstream your change.

To avoid that, it is recommended to rebase your own changes often on top of the current upstream branch.

To be able to do this, you need to prepare your project directory once with this command:

$ git remote add upstream https://github.com/Checkmk/checkmk.git

From now, you can always update your feature branches with this command:

$ git pull --rebase upstream master

Using rebase instead of merge gives us a clean git history.

Help: I need to change my commits

In case Github Actions notifies you about issues or the reviewer asks you to change your code, you will have to rework your commits. Be sure, we don't want to upset you :-).

There are several ways to update your changes in Git. We want to have as clean as possible commits, so the best is to apply the changes in a new commit and then meld them together with the previous commit.

This article on how to amend a commit may help you.

How to execute tests

The public repository of Checkmk is integrated with Github Actions CI. Each time a Pull request is submitted, Github Actions will have a look at the changes.

⚠ Important: We only review PRs that are confirmed to be OK by Github Actions. If a check failed, please fix it and update the PR. PRs will be closed if the author didn't respond for at least 14 days.

It is recommended to run all tests locally before submitting a PR. If you want to execute the full test suite, you can do this by executing these commands in the project base directory:

$ make -C tests test-ruff
$ make -C tests test-bandit
$ make -C tests test-unit
$ make -C tests test-format-python
$ make -C tests test-mypy-raw

We highly recommend integrating ruff and mypy into the editor you work with. Most editors will notify you about issues the moment you edit the code.

You could also push your changes to your forked repository and wait for Github Actions to execute the tests for you, but that takes several minutes for each try.

Style guide

Guidelines for coding check plug-ins

Respect the Guidelines for coding check plug-ins.

Commit messages

  • Use the present tense ("Add feature" not "Added feature")
  • Use the imperative mood ("Move cursor to..." not "Moves cursor to...")
  • The first line is a short title (limit to 72 characters or less)
  • Reference issues and pull requests liberally after the first line
  • Write good commit messages

Python

The guidelines listed here are binding for the development of Checkmk in Python.

This list is intended to grow in practice and does not claim to be exhaustive.

If the area of code you are working with deviates from the coding guidelines it might be justifyable to disregard them for the sake of consistency. It would be preferable to modernize the existing code in a separate commit in those cases.

Zen of Python.

Checkmk is mostly written in Python. Most code in this repository is run under a fairly recent version of Python3.

Only rely on non-standard modules that are mentioned in the Pipfile.

Agent plugins: Supported Python versions

The agent plugins are also written for Python 3, but have to be compatible with Python 3.4 or newer. Since they are executed in various Python environments on the monitored hosts, they should have as small dependencies as possible. Best is to only rely on vanilla Python without 3rd party modules.

Use #!/usr/bin/env python3 as shebang.

Besides the Python 3 variant, the agent plugins are also available for Python 2.7. These Python 2 variants (_2.py ending in agents/plugins) are generated automatically from the Python 3 scripts while packaging Checkmk. So no Python 2 script needs to be programmed. The Python 2 files are named [plugin]_2.py. Have a look at agents/plugins/Makefile to see how we generate them.

The agent is automatically dealing with Python 2 and 3 plugins and environments if possible. If a .py file is found and a python3 greater than or equal to Python 3.4 is in the PATH, then this plugin is used. If _2.py file is found and there is a python2 or python in the PATH, then this is used. It is ensured that no plugin is executed in two versions.

Agent plugins are executed on monitored systems. Here we can not rely on the presence of certain modules. The agent plugin + Check-Plugin must transport a clean message to the user in the GUI, if a dependency is missing (see e.g. Docker plugin).

For new plugins it is okay to use special dependencies, e.g. API bindings. But we have to take older Python versions and incompatibilities into account and produce error agent sections + error messages that tell the user about this issue.

Known issues regarding 3to2 conversion

  • f-strings: Currently 3to2 cannot convert f-strings into python2 compatible syntax. So use format() instead.

Imports

Don't use star import like from module import *. They make it hard to understand which names are really available and needed in the current namespace.

Exception handling

  • Easier to ask for forgiveness than permission

    def get_status(file):
    if not os.path.exists(file):
        print("file not found")
        sys.exit(1)
    with open(file) as f:
        return f.readline()

    vs.

    def get_status(file):
    try:
        with open(file) as f:
            return f.readline()
    except OSError as e:
        print("Unable to open file: %s" % e)
        sys.exit(1)

  • Be as specific as possible when catching exceptions

  • Keep try-blocks as small as possible

  • Don't use except: (Slightly better for special cases: except Exception)

Paths and files

  • Use pathlib.
  • Use context-managers (the with keyword) to open files.
  • You are welcome to refactor old style file IO to pathlib (with tests :-))

String formatting

  • Use classic format strings (%s) for the time being. We'll move over to the new format() syntax in the future, but for the moment we'd like to stay consistent.

Sub processes

  • Use mechanisms that are natively available in Python instead of subprocess/command line tools. Example: Don't use tar command line tools. Use the tarfile module instead. There may be good reasons to go with the command line tools in special situations.

  • Use secure methods for calling external programs to prevent shell injections

    • Use the subprocess module instead of os.system() or os.popen()
    • Use shell=False and close_fds=True with subprocess.
    • Use pipes.quote() in case you need to create a command line string

Argument parsing

  • Use argparse. In agent plugins, which have to support Python <2.5, use optparse.

Logging

  • Use logger or cmk.log, cmk.gui.log as base for logging
  • Add a logger object to self._logger to all classes (Use either a class/object specific child logger, the module level logger or cmk.log.logger)
  • Don't use format strings for log messages. Use logger.info('Hello, %s', world)

HTTP requests

  • Use requests, it's great!
  • Work with requests sessions in case you need to perform multiple requests

Times and Dates

  • Use top level functionality, e.g.: datetime, dateutil

Comments

  • Document the non-obvious. Don't document the how, do document the why.
  • Use doc-strings for classes and methods.

Doctests

Doctests are documentation. They aren't tests. They are executed with our python unit test job by pytest to make sure that the documentation doesn't drift away from the code.

In other words: Use doctests when you want to explain your function with the help of code examples. Don't use them to test the behavior of your function.

Some indicators for not using doctests:

  • You need to import something
  • Without reformatting or using pprint either your function call or your output looks ugly
  • You need to write more than 5 doctests for a single function
  • Your docstring is 2 times longer than the body of the function

Here it is fine to use doctests:

def worst_service_state(*states: int, default: int) -> int:
    """Return the 'worst' aggregation of all states

    Examples:

    >>> worst_service_state(0, 0, default=0)
    0
    >>> worst_service_state(0, 1, 2, 3, default=0)
    2
    """

Code structuring

  • Use the right data structure for combining data. For more complex code it is important to carefully think about this. This may help you find the right data structure for your data. In increasing order of preference:
    • Dictionaries: Worst possible representation. One has no clue whatsoever about the valid keys nor the valid values for a given key. In addition, they are mutable, which might not be what one wants. In effect, we are abusing a useful mapping type to simulate a struct.
    • Tuples of varying length: Basically the same as dictionaries with all the downsides.
    • Tuples of a fixed length: Slightly better, they have a fixed number of slots and are immutable. Still, one has no clue what a slot should mean.
    • collections.namedtuple: A bit better than tuples of a fixed length, at least the slots have names now. Still no clue about the valid values of a slot.
    • typing.NamedTuple: Kind of OK, slots have names and a type now. Still not really OO, because it is still a dumb data container, but at least we have reached a state where Pascal was in the 70s.
    • A class: This is almost what we want. Note: Classes with tons of static/class methods are actually //not// a class, they are a namespace in disguise, so we should not use them like that.
    • A class with mypy type annotations: This is the optimum. Now we're talking OO and mypy can help us tremendously during e.g. refactorings.
  • Don't use global variables unless you have to and can do so thread-safe.
  • Don't assign attributes to function objects.
  • Use abc for specifying abstract classes, methods and properties and add raise NotImplementedError() in abstract methods and properties)
  • Make class attributes explicit in the constructor or helper functions (Don't add them dynamically e.g. via a dict argument and ''getattr()'')
  • Extensive getter/setters: In Python it is acceptable to simply access class or object members directly. In case you want to protect things from external access make use of @property
  • Use @staticmethod and @classmethod decorators for methods without references to cls or self
  • Use early exits in your functions.

Module: cmk

  • The entire Python code of Checkmk should be under the main module cmk in the future
  • Below cmk.utils there is a module that provides functionalities for all components. These can be imported from anywhere. e.g. below is cmk.utils.log for logging functionalities.
  • At the first module level, the component modules are split up, e.g.:
    • cmk.base
    • cmk.gui
    • cmk.ec
  • All names that a component declares on its main level may be loaded by other components.
    • Another approach may be to explicitly declare the exports in a dedicated sub module, e.g. cmk.ec.export..
    • e.g. if the name load_ec_rule_packs is registered in cmk/ec/__init__.py, the GUI code may access cmk.ec.load_ec_rule_packs.
    • Names from submodules must not be imported from other components.
  • For the CME/CEE there is a module hierarchy under cmk/cee or cmk/cme. The same rules apply as for cmk itself.

Code formatting

  • We supply an .editorconfig file, which is used to automatically configure your editor to adhere to the most basic formatting style, like indents or line-lengths. If your editor doesn't already come with Editorconfig support, install one of the available plugins.
  • We use ruff for automatic formatting of the Python code. Have a look below for further information.
  • We use also ruff for automatic sorting of imports in Python code.

Automatic formatting/sorting with ruff

The ruff configuration file, pyproject.toml, lives in the root directory of the project repository, where ruff picks it up automatically. ruff itself lives in a virtualenv managed by pipenv in check_mk/.venv, you can run it with make format-python.

This make target will then format your code base as well as sort the import statements.

NOTE: You will also find other pyproject.toml files in our code base (at the time of writing, e.g. under packges/cmk-*). Those are individual project settings for our own python packages and may differ from the top-level pyproject.toml.

Manual ruff formatting invocation: Single file

ruff format [the_file.py]

Manual ruff import sorting invocation: Single file

$ run ruff check --select I --fix [the_file.py]

# or with pre-commit installed
$ pre-commit run ruff

Integration with CI

Our CI executes ruff formatting/sorting test on the whole code base:

$ make -C tests test-format-python

Our review tests jobs prevent un-formatted code from being added to the repository.

Editor integration with ruff:

Ruff editor integration

Type checking: mypy

Code can be checked manually with make -C tests test-mypy.

The configuration file is mypy.ini and lives in the root directory of the Checkmk repository. For info about how to type hint refer to mypy docs - Type hints cheat sheet (Python 2).

vim

This is where ALE comes in again. To include mypy there adjust the following things in the .vimrc:

  • Add mypy to the liners. With me it looks like this:

    let g:ale_linters = {
\ 'python': ['pylint', 'mypy'],
\ 'javascript': ['eslint'],
\}

  • Then tell the linter how to run pylint and mypy:

    let g:ale_python_mypy_executable = 'YOUR_REPO_PATH/check_mk/scripts/run-mypy'
let g:ale_python_pylint_executable = 'YOUR_REPO_PATH/check_mk/scripts/run-pylint'
let g:ale_python_pylint_options = '--rcfile YOUR_REPO_PATH/check_mk/.pylintrc'

NOTE

mypy may not support home expansion ("~"), so it is recommended to use an absolute Path for 'YOUR_REPO_PATH'.

The mypy-Checker should run with this. With ":ALEInfo" you get information about the error diagnosis below, if it doesn't work.

Editor integration: *macs

  • The mypy.ini should be found by Flycheck without further configuration.

  • To use the correct mypy executable a .dir-locals.el in the root directory of the Checkmk repository is used.

  • Flycheck by default does not execute multiple checkers. To enable the mypy checker after the pylint checker the following snippet can be used e.g. in the dotspacemacs/user-config:

      (with-eval-after-load 'flycheck
    (flycheck-add-next-checker 'python-pylint 'python-mypy))

  • To disable the risky variable warning that is triggered by setting the mypy executable the safe-local-variables variable has to be extended by:

    (eval setq flycheck-python-mypy-executable
           (concat
            (projectile-locate-dominating-file default-directory dir-locals-file)
            "scripts/run-mypy"))

  • An example value of the safe-local-variables variable is e.g.:

    ((eval setq flycheck-python-mypy-executable
       (concat
        (projectile-locate-dominating-file default-directory dir-locals-file)
        "scripts/run-mypy"))
 (py-indent-offset . 4)
 (encoding . utf-8))

Shell scripts

The Linux / Unix agents and several plugins are written in shell code for best portability and transparency. If you would like to change or contribute something, please respect the following things:

Is it appropriate

Contributed Plugins and Local Checks

If you think you need to use more advanced (read: less portable) shell capability for your plugin or local check, such as associative arrays found in e.g. bash, zsh, then you should probably consider using another language like python.

If you're only familiar with shell, or it's all that's available to your particular situation, that's fine, but you should:

  • Put a comment in your code stating that you're open to having your check or plugin rewritten, or why you don't want it rewritten
  • Fail-fast, fail-early e.g
# Restrict this plugin script to bash 4 and newer
if [[ -z "${BASH_VERSION}" ]] || (( "${BASH_VERSINFO[0]}" < 4 )); then
  printf -- '%s\n' "This check requires bash 4 or newer" >&2
  exit 1
fi

Contributions to the agent scripts

If you think you need to use more advanced shell capability for the agent code, then you will need to find another way to achieve what you want to do.

Code style

Format your code according to the following guidelines:

Checkmk specific guidance below supersedes what's offered in those guidelines:

Indentation and column width

  • Line length up to 100 characters is allowed
  • Use 4 spaces for indentation

Function Names

Names are in lowercase, underscored i.e. snake_case(). Names should be meaningful, so the verb_noun style may be worth considering. Microsoft has documentation for approved verbs that may provide some useful guidance.

The Google/ChromiumOS style guides allow for class::function() style names, but do note that this does not appear to be portable. No workaround is suggested at this time, but we expect something like __class_function() may be suitable.

Do not use the function keyword. It is non-portable and considered obsolete.

Bad:

# Haha I gave this function a funny name!
function blurgh() {
    ...
}

Better:

get_checkmk_api() {
    ...
}

Variables and Constants

Typing

Variables in Linux/UNIX shells are untyped. Attempts have been made to bring in some degree of typing via typeset and declare, but these are not portable solutions, so should be avoided.

If you need a variable to be of a specific type, the best advice right now (that we're aware of) is to validate it before you use it.

Pseudoscoping

We practice pseudoscoping to minimize the chances of variables within scripts or functions from clobbering variables within the environment and vice versa.

Variables must be in the appropriate format for its "scope" as defined below:

Environment

We know from long-established convention that environment variables are almost always in UPPERCASE. You can see this in e.g. bash by running set and/or printenv.

We generally shouldn't need to put any variables into the environment, so you should avoid UPPERCASE as much as possible. If you do need a variable in the environment "scope" for whatever reason, use the form MK_VARNAME e.g. MK_VERSION

You might often see this "scope" referred to as the global scope, or shell scope. This scope also contains shell built-in variables.

Script

Variables in the script "scope" often tend to be mistakenly written in UPPERCASE, which gives rise to the possibility of clobbering a legitimate variable in the environment "scope". This can have results that are potentially hilarious, or potentially bad depending on your point of view.

For that reason, UPPERCASE variable names are strongly discouraged outside the environment scope.

Instead, use lowercase, with underscores to separate words i.e. snake_case.

GNU Autoconf's documentation also states:

As a general rule, shell variable names containing a lower-case letter are safe; you can define and use these variables without worrying about their effect on the underlying system, and without worrying about whether the shell changes them unexpectedly.

Try, also, to use meaningful names. This is meaningless:

for f in $(lsblk -ln -o NAME); do
    ...

Whereas this is better:

for block_device in $(lsblk -ln -o NAME); do
    ...

This also reduces/eliminates unexpected in-scope collisions.

Exception: C-Style for (( i=0; i<max_count; i++ )); do style loops, as the var i is usually self-contained and is shorthand for 'integer'

You should consider unsetting your variables once you're done with them, though this isn't strictly necessary.

Function / Local

bash and others allow you to define variables as local within a function e.g.

get_api_user() {
    local username
    username=Shelly
    ...
}

Unfortunately this is not portable and attempts at workarounds are ... somewhat hackish. So our approach to solve this is to simply prepend any variables within a function with an underscore. We also unset the variable immediately prior to the function closure. For example:

get_api_user() {
    _username=Shelly
    ...
    unset -v _username
}
Curly braces

Curly braces are used on ${arrays[@]} and ${variable/modif/ications}. To maintain consistency, you should use curly braces on normal variables too.

Curly braces around variables improves readability when syntax coloring is not available. ${this_variable} stands out within this block of text.

They also allow us to more robustly format outputs e.g.

$ time_metric=5
$ echo "$time_metricmins"

$ echo "${time_metric}mins"
5mins

In the first example, there is no such variable as $timemetricmins.

In the second example, the curly braces explicitly tell the shell interpreter where the variable name boundaries are. Instead of applying this via trial and error, the simplest approach is to just use curly braces by default.

Exception: When you're in an arithmetic context e.g. $(( time_metric + 10 ))

Exceptions to the exception: If your var is an array element or requires transformation e.g.

  • $(( "${time_metrics[2]}" + 20 ))
  • $(( "${10#time_metric}" + 10 ))
Constants

To make a variable constant (a.k.a. an "immutable variable"), use readonly, defined and set separately e.g.

MK_CONSTANT="Polaris"
readonly MK_CONSTANT

Variable pseudoscopes recap

  • Environment: ${MK_UPPERCASE}
  • Script: ${meaningful_snake_case}
  • Function / Local: ${_underscore_prepended_snake_case} with unset -v
  • Constants: The appropriate above form set to readonly

Linting

Use shellcheck for your changes before submitting patches.

The best results are achieved with a direct integration into your preferred editor, so that you are immediately informed about possible problems during programming.

The various agent scripts are not clean at the moment, but we aim to clean this up in the near future.

Do note that while Shellcheck is an excellent tool, it's not perfect. Sometimes it alerts on code that may actually be desired. In this scenario, you must use a disable directive with a comment that justifies your reason for this. It may also be useful to reference a git commit hash or werk number.

# This function is sourced outside of this library, where it does parse args
# See commit abcd3456 and/or werk 1234
# shellcheck disable=SC2120
foo() {

Formatting

You may use shfmt to help with formatting.

If you don't have a Go environment ready, the easiest way is to use it is using a prepared docker image (See bottom of project README). We have a shortcut to this, which is also used by our CI system.

Execute this in checkmk git directory:

$ sudo docker run --rm -v "$(pwd):/sh" -w /sh peterdavehello/shfmt shfmt -i 4 -ci -w agents/check_mk_agent.linux

Portability

  • We are loosely aiming for "POSIX plus simple named arrays"

  • echo is a portability nightmare. Prefer printf instead.

  • Existing scripts have been written using a variety of shells. Scripts that use bash have tended to be written for bash 3.x.

  • In the future, we will attempt to make our shell code more portable, which means reducing bashisms. If you're making shell code now, try to approach it with portability in mind. Your code may be used on older systems and/or commercial unices (e.g. AIX, Solaris etc).

  • ksh is in some ways a reasonable lowest common denominator to target as it's virtually everywhere, and its syntax is almost directly runnable in bash, zsh and others. Be aware, however, that there are many variants of ksh. oksh is a decent variant.

  • Ubuntu's DashAsBinSh wiki page can give you some ideas on more portable scripting, and dash is a readily available shell that you can test your code within. Do be aware that dash is stricter than our goals.

  • The needs of busybox ash (i.e. for openwrt) may also be something to consider

  • A tool like shall might be useful

The Unofficial Strict Mode

There is a lot of advice on the internet to "always use The Unofficial Strict Mode."

It is usually presented as a brilliant catch-all that will magically fix every shell scripting issue. It is usually in a form similar to:

set -euo pipefail

This is well-meaning, but flawed advice. Firstly, it's not portable, so it's disqualified by default for our purposes. Secondly, it comes with its own flaws. Some of these options have reasonable uses, but it's dangerous to think that this one-line incantation is somehow perfect. You can read more about it, and specifically set -e at one of the following links (read at least the first):

Performance

Let's be honest: Compared to almost anything else, shell performance is suboptimal. Especially in bash. We use shell for Linux/UNIX hosts because, for better or worse, it is the most portable option. Nonetheless, we can at least try to be mindful about how we construct our code, in order to squeeze out as much performance as we can.

It may help to think of this competitively, or as a challenge. Constantly ask yourself "can I optimize this code any further?"

For a simple and classic example, we have the good old "Useless Use of Cat":

cat haystack.txt | grep needle

This causes a pointless fork and process, as well as a waste of a pipe with associated buffering and broken pipe risks, as grep can address files directly, i.e.

grep needle haystack.txt

We also often find "Useless Use of Cat" paired with "Useless Use of Grep | Awk", e.g.

cat haystack.txt | grep needle | awk '{print $2}'

awk, like grep, can address files directly, and given that it has searching built in, it can actually do all of this in one shot:

awk '/needle/{print $2}' haystack.txt

Or to do so case insensitively:

awk 'tolower($0) ~ /needle/{print $2}' haystack.txt

Often we see blocks of if...elif...elif...elif's that can and should be replaced with a cleaner and meaner case...esac statement.

The style guides linked to earlier both state:

Given the choice between invoking a shell built-in and invoking a separate process, choose the built-in.

We prefer the use of built-ins such as the Parameter Expansion functions in bash(1) as it’s more robust and portable (especially when compared to things like sed).

Often (but not always) there are massive performance gains to be had through the use of built-ins, usually at the expense of some readability. This can be counter-balanced via explanatory comments.

Localization

The user interface of Checkmk can be localized using Weblate. We are very happy about any contributions to the localization of Checkmk. To contribute, please first register an account at our Weblate server. Afterwards, you can iterate through untranslated source strings and localize them. See this forum post for further information.

Please note that any PRs which directly edit the PO-files will be disregarded, since the localization should be done exclusively via Weblate to avoid merge conflicts.

Translation of technical terms

Technical terms outside Checkmk like "container" may be translated according to the common usage for that technology.

There are several terms in Checkmk that may be kept for a better understanding. Some of them are:

  • Host
  • Service
  • Check
  • Item
  • DOWN, UP, PENDING

Consistency

Be consistent in the terms you use for a thing, e.g. in case of a server one could say something like "host", "system", "server" or "device". Decide to use one name for one thing and use it consistently in all translations.

Copyright and Licensing

The open source part of Checkmk is licensed under the terms of the GNU GPLv2 License. Any new code must be compatible with those terms.

To ensure that, please always add our current licensing information to any new files you want to contribute. The licensing information can be found at the beginning of already existing files and looks something like

# Copyright (C) 2022 Checkmk GmbH - License: GNU General Public License v2
# This file is part of Checkmk (https://checkmk.com). It is subject to the terms and
# conditions defined in the file COPYING, which is part of this source code package.