Writing Execution Modules

Salt execution modules are the functions called by the salt command.

Modules Are Easy to Write!

Writing Salt execution modules is straightforward.

A Salt execution module is a Python or Cython module placed in a directory called _modules/ at the root of the Salt fileserver. When using the default fileserver backend (i.e. roots), unless environments are otherwise defined in the file_roots config option, the _modules/ directory would be located in /srv/salt/_modules on most systems.

Modules placed in _modules/ will be synced to the minions when any of the following Salt functions are called:

Modules placed in _modules/ will be synced to masters when any of the following Salt runners are called:

Note that a module's default name is its filename (i.e. foo.py becomes module foo), but that its name can be overridden by using a __virtual__ function.

If a Salt module has errors and cannot be imported, the Salt minion will continue to load without issue and the module with errors will simply be omitted.

If adding a Cython module the file must be named <modulename>.pyx so that the loader knows that the module needs to be imported as a Cython module. The compilation of the Cython module is automatic and happens when the minion starts, so only the *.pyx file is required.

Zip Archives as Modules

Python 2.3 and higher allows developers to directly import zip archives containing Python code. By setting enable_zip_modules to True in the minion config, the Salt loader will be able to import .zip files in this fashion. This allows Salt module developers to package dependencies with their modules for ease of deployment, isolation, etc.

For a user, Zip Archive modules behave just like other modules. When executing a function from a module provided as the file my_module.zip, a user would call a function within that module as my_module.<function>.

Creating a Zip Archive Module

A Zip Archive module is structured similarly to a simple Python package. The .zip file contains a single directory with the same name as the module. The module code traditionally in <module_name>.py goes in <module_name>/__init__.py. The dependency packages are subdirectories of <module_name>/.

Here is an example directory structure for the lumberjack module, which has two library dependencies (sleep and work) to be included.

modules $ ls -R lumberjack
__init__.py     sleep           work



The contents of lumberjack/__init__.py show how to import and use these included libraries.

# Libraries included in lumberjack.zip
from lumberjack import sleep, work

def is_ok(person):
    """Checks whether a person is really a lumberjack"""
    return sleep.all_night(person) and work.all_day(person)

Then, create the zip:

modules $ zip -r lumberjack lumberjack
  adding: lumberjack/ (stored 0%)
  adding: lumberjack/__init__.py (deflated 39%)
  adding: lumberjack/sleep/ (stored 0%)
  adding: lumberjack/sleep/__init__.py (deflated 7%)
  adding: lumberjack/work/ (stored 0%)
  adding: lumberjack/work/__init__.py (deflated 7%)
modules $ unzip -l lumberjack.zip
Archive:  lumberjack.zip
  Length     Date   Time    Name
 --------    ----   ----    ----
        0  08-21-15 20:08   lumberjack/
      348  08-21-15 20:08   lumberjack/__init__.py
        0  08-21-15 19:53   lumberjack/sleep/
       83  08-21-15 19:53   lumberjack/sleep/__init__.py
        0  08-21-15 19:53   lumberjack/work/
       81  08-21-15 19:21   lumberjack/work/__init__.py
 --------                   -------
      512                   6 files

Once placed in file_roots, Salt users can distribute and use lumberjack.zip like any other module.

$ sudo salt minion1 saltutil.sync_modules
  - modules.lumberjack
$ sudo salt minion1 lumberjack.is_ok 'Michael Palin'

Cross Calling Execution Modules

All of the Salt execution modules are available to each other and modules can call functions available in other execution modules.

The variable __salt__ is packed into the modules after they are loaded into the Salt minion.

The __salt__ variable is a Python dictionary containing all of the Salt functions. Dictionary keys are strings representing the names of the modules and the values are the functions themselves.

Salt modules can be cross-called by accessing the value in the __salt__ dict:

def foo(bar):
    return __salt__["cmd.run"](bar)

This code will call the run function in the cmd module and pass the argument bar to it.

Calling Execution Modules on the Salt Master

New in version 2016.11.0.

Execution modules can now also be called via the salt-run command using the salt runner.

Preloaded Execution Module Data

When interacting with execution modules often it is nice to be able to read information dynamically about the minion or to load in configuration parameters for a module.

Salt allows for different types of data to be loaded into the modules by the minion.

Grains Data

The values detected by the Salt Grains on the minion are available in a Python dictionary named __grains__ and can be accessed from within callable objects in the Python modules.

To see the contents of the grains dictionary for a given system in your deployment run the grains.items() function:

salt 'hostname' grains.items --output=pprint

Any value in a grains dictionary can be accessed as any other Python dictionary. For example, the grain representing the minion ID is stored in the id key and from an execution module, the value would be stored in __grains__['id'].

Module Configuration

Since parameters for configuring a module may be desired, Salt allows for configuration information from the minion configuration file to be passed to execution modules.

Since the minion configuration file is a YAML document, arbitrary configuration data can be passed in the minion config that is read by the modules. It is therefore strongly recommended that the values passed in the configuration file match the module name. A value intended for the test execution module should be named test.<value>.

The test execution module contains usage of the module configuration and the default configuration file for the minion contains the information and format used to pass data to the modules. salt.modules.test, conf/minion.

__init__ Function

If you want your module to have different execution modes based on minion configuration, you can use the __init__(opts) function to perform initial module setup. The parameter opts is the complete minion configuration, as also available in the __opts__ dict.

Cheese module initialization example

def __init__(opts):
    Allow foreign imports if configured to do so
    if opts.get("cheese.allow_foreign", False):

Strings and Unicode

An execution module author should always assume that strings fed to the module have already decoded from strings into Unicode. In Python 2, these will be of type 'Unicode' and in Python 3 they will be of type str. Calling from a state to other Salt sub-systems, should pass Unicode (or bytes if passing binary data). In the rare event that a state needs to write directly to disk, Unicode should be encoded to a string immediately before writing to disk. An author may use __salt_system_encoding__ to learn what the encoding type of the system is. For example, 'my_string'.encode(__salt_system_encoding__').

Outputter Configuration

Since execution module functions can return different data, and the way the data is printed can greatly change the presentation, Salt allows for a specific outputter to be set on a function-by-function basis.

This is done be declaring an __outputter__ dictionary in the global scope of the module. The __outputter__ dictionary contains a mapping of function names to Salt outputters.

__outputter__ = {"run": "txt"}

This will ensure that the txt outputter is used to display output from the run function.

Virtual Modules

Virtual modules let you override the name of a module in order to use the same name to refer to one of several similar modules. The specific module that is loaded for a virtual name is selected based on the current platform or environment.

For example, packages are managed across platforms using the pkg module. pkg is a virtual module name that is an alias for the specific package manager module that is loaded on a specific system (for example, yumpkg on RHEL/CentOS systems , and aptpkg on Ubuntu).

Virtual module names are set using the __virtual__ function and the virtual name.

__virtual__ Function

The __virtual__ function returns either a string, True, False, or False with an error string. If a string is returned then the module is loaded using the name of the string as the virtual name. If True is returned the module is loaded using the current module name. If False is returned the module is not loaded. False lets the module perform system checks and prevent loading if dependencies are not met.

Since __virtual__ is called before the module is loaded, __salt__ will be unreliable as not all modules will be available at this point in time. The __pillar__ and __grains__ "dunder" dictionaries are available however.


Modules which return a string from __virtual__ that is already used by a module that ships with Salt will _override_ the stock module.

Returning Error Information from __virtual__

Optionally, Salt plugin modules, such as execution, state, returner, beacon, etc. modules may additionally return a string containing the reason that a module could not be loaded. For example, an execution module called cheese and a corresponding state module also called cheese, both depending on a utility called enzymes should have __virtual__ functions that handle the case when the dependency is unavailable.

Cheese execution (or returner/beacon/etc.) module

    import enzymes

    HAS_ENZYMES = True
except ImportError:
    HAS_ENZYMES = False

def __virtual__():
    only load cheese if enzymes are available
        return "cheese"
        return (
            "The cheese execution module cannot be loaded: enzymes unavailable.",

def slice():
Cheese state module. Note that this works in state modules because it is
guaranteed that execution modules are loaded first

def __virtual__():
    only load cheese if enzymes are available
    # predicate loading of the cheese state on the corresponding execution module
    if "cheese.slice" in __salt__:
        return "cheese"
        return False, "The cheese state module cannot be loaded: enzymes unavailable."


The package manager modules are among the best examples of using the __virtual__ function. A table of all the virtual pkg modules can be found here.

Overriding Virtual Module Providers

Salt often uses OS grains (os, osrelease, os_family, etc.) to determine which module should be loaded as the virtual module for pkg, service, etc. Sometimes this OS detection is incomplete, with new distros popping up, existing distros changing init systems, etc. The virtual modules likely to be affected by this are in the list below (click each item for more information):

If Salt is using the wrong module for one of these, first of all, please report it on the issue tracker, so that this issue can be resolved for a future release. To make it easier to troubleshoot, please also provide the grains.items output, taking care to redact any sensitive information.

Then, while waiting for the SaltStack development team to fix the issue, Salt can be made to use the correct module using the providers option in the minion config file:

  service: systemd
  pkg: aptpkg

The above example will force the minion to use the systemd module to provide service management, and the aptpkg module to provide package management.

For per-state provider overrides, see documentation on state providers.

Logging Restrictions

As a rule, logging should not be done anywhere in a Salt module before it is loaded. This rule apples to all code that would run before the __virtual__() function, as well as the code within the __virtual__() function itself.

If logging statements are made before the virtual function determines if the module should be loaded, then those logging statements will be called repeatedly. This clutters up log files unnecessarily.

Exceptions may be considered for logging statements made at the trace level. However, it is better to provide the necessary information by another means. One method is to return error information in the __virtual__() function.


__virtualname__ is a variable that is used by the documentation build system to know the virtual name of a module without calling the __virtual__ function. Modules that return a string from the __virtual__ function must also set the __virtualname__ variable.

To avoid setting the virtual name string twice, you can implement __virtual__ to return the value set for __virtualname__ using a pattern similar to the following:

# Define the module's virtual name
__virtualname__ = "pkg"

def __virtual__():
    Confine this module to Mac OS with Homebrew.

    if salt.utils.path.which("brew") and __grains__["os"] == "MacOS":
        return __virtualname__
    return False

The __virtual__() function can return a True or False boolean, a tuple, or a string. If it returns a True value, this __virtualname__ module-level attribute can be set as seen in the above example. This is the string that the module should be referred to as.

When __virtual__() returns a tuple, the first item should be a boolean and the second should be a string. This is typically done when the module should not load. The first value of the tuple is False and the second is the error message to display for why the module did not load.

For example:

def __virtual__():
    Only load if git exists on the system
    if salt.utils.path.which("git") is None:
        return (False, "The git execution module cannot be loaded: git unavailable.")
        return True


Salt execution modules are documented. The sys.doc() function will return the documentation for all available modules:

salt '*' sys.doc

The sys.doc function simply prints out the docstrings found in the modules; when writing Salt execution modules, please follow the formatting conventions for docstrings as they appear in the other modules.

Adding Documentation to Salt Modules

It is strongly suggested that all Salt modules have documentation added.

To add documentation add a Python docstring to the function.

def spam(eggs):
    A function to make some spam with eggs!

    CLI Example::

        salt '*' test.spam eggs
    return eggs

Now when the sys.doc call is executed the docstring will be cleanly returned to the calling terminal.

Documentation added to execution modules in docstrings will automatically be added to the online web-based documentation.

Add Execution Module Metadata

When writing a Python docstring for an execution module, add information about the module using the following field lists:

:maintainer:    Thomas Hatch <thatch@saltstack.com, Seth House <shouse@saltstack.com>
:maturity:      new
:depends:       python-mysqldb
:platform:      all

The maintainer field is a comma-delimited list of developers who help maintain this module.

The maturity field indicates the level of quality and testing for this module. Standard labels will be determined.

The depends field is a comma-delimited list of modules that this module depends on.

The platform field is a comma-delimited list of platforms that this module is known to run on.

Log Output

You can call the logger from custom modules to write messages to the minion logs. The following code snippet demonstrates writing log messages:

import logging

log = logging.getLogger(__name__)

log.info("Here is Some Information")
log.warning("You Should Not Do That")
log.error("It Is Busted")

Aliasing Functions

Sometimes one wishes to use a function name that would shadow a python built-in. A common example would be set(). To support this, append an underscore to the function definition, def set_():, and use the __func_alias__ feature to provide an alias to the function.

__func_alias__ is a dictionary where each key is the name of a function in the module, and each value is a string representing the alias for that function. When calling an aliased function from a different execution module, state module, or from the cli, the alias name should be used.

__func_alias__ = {
    "set_": "set",
    "list_": "list",

Private Functions

In Salt, Python callable objects contained within an execution module are made available to the Salt minion for use. The only exception to this rule is a callable object with a name starting with an underscore _.

Objects Loaded Into the Salt Minion

def foo(bar):
    return bar

Objects NOT Loaded into the Salt Minion

def _foobar(baz):  # Preceded with an _
    return baz

cheese = {}  # Not a callable Python object

Useful Decorators for Modules

Depends Decorator

When writing execution modules there are many times where some of the module will work on all hosts but some functions have an external dependency, such as a service that needs to be installed or a binary that needs to be present on the system.

Instead of trying to wrap much of the code in large try/except blocks, a decorator can be used.

If the dependencies passed to the decorator don't exist, then the salt minion will remove those functions from the module on that host.

If a fallback_function is defined, it will replace the function instead of removing it

import logging

from salt.utils.decorators import depends

log = logging.getLogger(__name__)

    import dependency_that_sometimes_exists
except ImportError as e:
    log.trace("Failed to import dependency_that_sometimes_exists: {0}".format(e))

def foo():
    Function with a dependency on the "dependency_that_sometimes_exists" module,
    if the "dependency_that_sometimes_exists" is missing this function will not exist
    return True

def _fallback():
    Fallback function for the depends decorator to replace a function with
    return '"dependency_that_sometimes_exists" needs to be installed for this function to exist'

@depends("dependency_that_sometimes_exists", fallback_function=_fallback)
def foo():
    Function with a dependency on the "dependency_that_sometimes_exists" module.
    If the "dependency_that_sometimes_exists" is missing this function will be
    replaced with "_fallback"
    return True

In addition to global dependencies the depends decorator also supports raw booleans.

from salt.utils.decorators import depends

HAS_DEP = False
    import dependency_that_sometimes_exists

    HAS_DEP = True
except ImportError:

def foo():
    return True