Writing AppDaemon Apps

AppDaemon is a loosely coupled, sandboxed, multi-threaded Python execution environment for writing automation apps for Home Assistant home automation software. It is intended to complement the Automation and Script components that Home Assistant currently offers.


Example apps that showcase most of these functions are available in the AppDaemon repository:


Anatomy of an App

Automations in AppDaemon are performed by creating a piece of code (essentially a Python Class) and then instantiating it as an Object one or more times by configuring it as an App in the configuration file. The App is given a chance to register itself for whatever events it wants to subscribe to, and AppDaemon will then make calls back into the Object’s code when those events occur, allowing the App to respond to the event with some kind of action.

The first step is to create a unique file within the apps directory (as defined in the AppDaemon section of configuration file - see The Installation Page for further information on the configuration of AppDaemon itself). This file is in fact a Python module, and is expected to contain one or more classes derived from the supplied AppDaemon class, imported from the supplied appdaemon.appapi module. The start of an app might look like this:

import appdaemon.appapi as appapi

class MotionLights(appapi.AppDaemon):

When configured as an app in the config file (more on that later) the lifecycle of the App begins. It will be instantiated as an object by AppDaemon, and immediately, it will have a call made to its initialize() function - this function must appear as part of every app:

def initialize(self):

The initialize function allows the app to register any callbacks it might need for responding to state changes, and also any setup activities. When the initialize() function returns, the App will be dormant until any of its callbacks are activated.

There are several circumstances under which initialize() might be called:

  • Initial start of AppDaemon
  • Following a change to the Class code
  • Following a change to the module parameters
  • Following initial configuration of an app
  • Following a change in the status of Daylight Saving Time
  • Following a restart of Home Assistant

In every case, the App is responsible for recreating any state it might need as if it were the first time it was ever started. If initialize() is called, the app can safely assume that it is either being loaded for the first time, or that all callbacks and timers have been cancelled. In either case, the App will need to recreate them. Depending upon the application, it may be desirable for the App to establish a state, such as whether or not a particular light is on, within the initialize() function to ensure that everything is as expected or to make immediate remedial action (e.g., turn off a light that might have been left on by mistake when the app was restarted).

After the initialize() function is in place, the rest of the app consists of functions that are called by the various callback mechanisms, and any additional functions the user wants to add as part of the program logic. Apps are able to subscribe to two main classes of events:

  • Scheduled Events
  • State Change Events

These, along with their various subscription calls and helper functions, will be described in detail in later sections.

Optionally, a class can add a terminate() function. This function will be called ahead of the reload to allow the class to perform any tidy up that is necessary.

WARNING: Unlike other types of callback, calls to initialize() and terminate() are synchronous to AppDaemon’s management code to ensure that initialization or cleanup is completed before the App is loaded or reloaded. This means that any significant delays in the terminate() code could have the effect of hanging AppDaemon for the duration of that code - this should be avoided.

To wrap up this section, here is a complete functioning App (with comments):

import appdaemon.appapi as appapi
import datetime

 Declare Class
class NightLight(appapi.AppDaemon):
  #initialize() function which will be called at startup and reload
  def initialize(self):
    # Create a time object for 7pm
    time = datetime.time(19, 00, 0)
    # Schedule a daily callback that will call run_daily() at 7pm every night
    self.run_daily(self.run_daily_callback, time)

   # Our callback function will be called by the scheduler every day at 7pm
  def run_daily_callback(self, kwargs):
    # Call to Home Assistant to turn the porch light on

To summarize - an App’s lifecycle consists of being initialized, which allows it to set one or more states and/or schedule callbacks. When those callbacks are activated, the App will typically use one of the Service Calling calls to effect some change to the devices of the system and then wait for the next relevant state change. Finally, if the App is reloaded, there is a call to its terminate() function if it exists. That’s all there is to it!

About the API

The implementation of the API is located in the AppDaemon class that Apps are derived from. The code for the functions is therefore available to the App simply by invoking the name of the function from the object namespace using the self keyword, as in the above examples. self.turn_on() for example is just a method defined in the parent class and made available to the child. This design decision was made to simplify some of the implementation and hide passing of unnecessary variables during the API invocation.

Configuration of Apps

Apps are configured by specifying new sections in the app configuration file - apps.yaml. The name of the section is the name the App is referred to within the system in log files etc. and must be unique.

To configure a new App you need a minimum of two directives:

  • module - the name of the module (without the .py) that contains the class to be used for this App
  • class - the name of the class as defined within the module for the APPs code

Although the section/App name must be unique, it is possible to re-use a class as many times as you want, and conversely to put as many classes in a module as you want. A sample definition for a new App might look as follows:

  module: new
  class: NewApp

When AppDaemon sees the following configuration it will expect to find a class called NewApp defined in a module called new.py in the apps subdirectory. Apps can be placed at the root of the Apps directory or within a subdirectory, an arbitrary depth down - wherever the App is, as long as it is in some subdirectory of the Apps dir, or in the Apps dir itself, AppDaemon will find it. There is no need to include information about the path, just the name of the file itself (without the .py) is sufficient. If names in the subdirectories overlap, AppDir will pick one of them but the exact choice it will make is undefined.

When starting the system for the first time or when reloading an App or Module, the system will log the fact in it’s main log. It is often the case that there is a problem with the class, maybe a syntax error or some other problem. If that is the case, details will be output to the error log allowing the user to remedy the problem and reload.

Steps to writing an App

  1. Create the code in a new or shared module by deriving a class from AppDaemon, add required callbacks and code
  2. Add the App to the app configuration file
  3. There is no number 3

Reloading Modules and Classes

Reloading of modules is automatic. When the system spots a change in a module, it will automatically reload and recompile the module. It will also figure out which Apps were using that Module and restart them, causing their terminate() functions to be called if they exist, all of their existing callbacks to be cleared, and their initialize() function to be called.

The same is true if changes are made to an App’s configuration - changing the class, or arguments (see later) will cause that app to be reloaded in the same way. The system is also capable of detecting if a new app has been added, or if one has been removed, and it will act appropriately, starting the new app immediately and removing all callbacks for the removed app.

The suggested order for creating a new App is to add the module code first and work until it compiles cleanly, and only then add an entry in the configuration file to actually run it. A good workflow is to continuously monitor the error file (using tail -f on Linux for instance) to ensure that errors are seen and can be remedied.

Passing Arguments to Apps

There wouldn’t be much point in being able to run multiple versions of an App if there wasn’t some way to instruct them to do something different. For this reason it is possible to pass any required arguments to an App, which are then made available to the object at runtime. The arguments themselves can be called anything (apart from module or class) and are simply added into the section after the 2 mandatory directives like so:

  module: myapp
  class: MyApp
  param1: spam
  param2: eggs

Within the Apps code, the 2 parameters (as well as the module and class) are available as a dictionary called args, and accessed as follows:

param1 = self.args["param1"]
param2 = self.args["param2"]

A use case for this might be an App that detects motion and turns on a light. If you have 3 places you want to run this, rather than hardcoding this into 3 separate Apps, you need only code a single app and instantiate it 3 times with different arguments. It might look something like this:

  module: motion_light
  class: MotionLight
  sensor: binary_sensor.downstairs_hall
  light: light.downstairs_hall
  module: motion_light
  class: MotionLight
  sensor: binary_sensor.upstairs_hall
  light: light.upstairs_hall
  module: motion_light
  class: MotionLight
  sensor: binary_sensor.garage
  light: light.garage

Apps can use arbitrarily complex structures within argumens, e.g.:

  - entity1
  - entity2
  - entity3

Which can be accessed as a list in python with:

for entity in self.args.entities:
  do some stuff

Also, this opens the door to really complex parameter structures if required:

    warning_level: 30
    units: degrees
    warning_level: 100
    units: %

Module Dependencies

It is possible for modules to be dependant upon other modules. Some examples where this might be the case are:

  • A Global module that defines constants for use in other modules
  • A module that provides a service for other modules, e.g. a TTS module
  • A Module that provides part of an object hierarchy to other modules

In these cases, when changes are made to one of these modules, we also want the modules that depend upon them to be reloaded. Furthermore, we also want to guarantee that they are loaded in order so that the modules dpended upon by other modules are loaded first.

AppDaemon fully supports this through the use of the dependency directive in the App configuration. Using this directice, each App identifies modules that it depends upon. Note that the dependency is at the module level, not the App level, since a change to the module will force a reload of all apps using it anyway. The dependency directive will identify the module name of the App it cares about, and AppDaemon will see to it that the dependency is loaded before the module depending on it, and that the dependent module will be reloaded if it changes.

For example, an App Consumer, uses another app Sound to play sound files. Sound in turn uses Global to store some global values. We can represent these dependencies as follows:

  module: global
  class: Global

  module: sound
  class: Sound
  dependencies: global # Note - module name not App name

  module: sound
  class: Sound
  dependencies: sound

It is also possible to have multiple dependencies, added as a comma separate list (no spaces)

  module: sound
  class: Sound
  dependencies: sound,global

AppDaemon will write errors to the log if a dependency is missing and it should also detect circular dependencies.

Callback Constraints

Callback constraints are a feature of AppDaemon that removes the need for repetition of some common coding checks. Many Apps will wish to process their callbacks only when certain conditions are met, e.g. someone is home, and it’s after sunset. These kinds of conditions crop up a lot, and use of callback constraints can significantly simplify the logic required within callbacks.

Put simply, callback constraints are one or more conditions on callback execution that can be applied to an individual App. An App’s callbacks will only be executed if all of the constraints are met. If a constraint is absent it will not be checked for.

For example, the presence callback constraint can be added to an App by adding a parameter to it’s configuration like this:

  module: some_module
  class: SomeClass
  constrain_presence: noone

Now, although the initialize() function will be called for SomeClass, and it will have a chance to register as many callbacks as it desires, none of the callbacks will execute, in this case, until everyone has left. This could be useful for an interior motion detector App for instance. There are several different types of constraints:

  • input_boolean
  • input_select
  • presence
  • time

An App can have as many or as few as are required. When more than one constraint is present, they must all evaluate to true to allow the callbacks to be called. Constraints becoming true are not an event in their own right, but if they are all true at a point in time, the next callback that would otherwise been blocked due to constraint failure will now be called. Similarly, if one of the constraints becomes false, the next callback that would otherwise have been called will be blocked.

They are described individually below.


By default, the input_boolean constraint prevents callbacks unless the specified input_boolean is set to “on”. This is useful to allow certain Apps to be turned on and off from the user interface. For example:

  module: some_module
  class: SomeClass
  constrain_input_boolean: input_boolean.enable_motion_detection

If you want to reverse the logic so the constraint is only called when the input_boolean is off, use the optional state parameter by appending “,off” to the argument, e.g.:

  module: some_module
  class: SomeClass
  constrain_input_boolean: input_boolean.enable_motion_detection,off


The input_select constraint prevents callbacks unless the specified input_select is set to one or more of the nominated (comma separated) values. This is useful to allow certain Apps to be turned on and off according to some flag, e.g. a house mode flag.

 Single value
constrain_input_select: input_select.house_mode,Day
 or multiple values
constrain_input_select: input_select.house_mode,Day,Evening,Night


The presence constraint will constrain based on presence of device trackers. It takes 3 possible values: - noone - only allow callback execution when no one is home - anyone - only allow callback execution when one or more person is home - everyone - only allow callback execution when everyone is home

constrain_presence: anyone
constrain_presence: someone
constrain_presence: noone


The time constraint consists of 2 variables, constrain_start_time and constrain_end_time. Callbacks will only be executed if the current time is between the start and end times. - If both are absent no time constraint will exist - If only start is present, end will default to 1 second before midnight - If only end is present, start will default to midnight

The times are specified in a string format with one of the following formats: - HH:MM:SS - the time in Hours Minutes and Seconds, 24 hour format. - sunrise|sunset [+|- HH:MM:SS]- time of the next sunrise or sunset with an optional positive or negative offset in Hours Minutes and seconds

The time based constraint system correctly interprets start and end times that span midnight.

 Run between 8am and 10pm
constrain_start_time: 08:00:00
constrain_end_time: 22:00:00
 Run between sunrise and sunset
constrain_start_time: sunrise
constrain_end_time: sunset
 Run between 45 minutes before sunset and 45 minutes after sunrise the next day
constrain_start_time: sunset - 00:45:00
constrain_end_time: sunrise + 00:45:00


The day constraint consists of as list of days for which the callbacks will fire, e.g.

constrain_days: mon,tue,wed

Callback constraints can also be applied to individual callbacks within Apps, see later for more details.

A Note on Threading

AppDaemon is multithreaded. This means that any time code within an App is executed, it is executed by one of many threads. This is generally not a particularly important consideration for this application; in general, the execution time of callbacks is expected to be far quicker than the frequency of events causing them. However, it should be noted for completeness, that it is certainly possible for different pieces of code within the App to be executed concurrently, so some care may be necessary if different callback for instance inspect and change shared variables. This is a fairly standard caveat with concurrent programming, and if you know enough to want to do this, then you should know enough to put appropriate safeguards in place. For the average user however this shouldn’t be an issue. If there are sufficient use cases to warrant it, I will consider adding locking to the function invocations to make the entire infrastructure threadsafe, but I am not convinced that it is necessary.

An additional caveat of a threaded worker pool environment is that it is the expectation that none of the callbacks tie threads up for a significant amount of time. To do so would eventually lead to thread exhaustion, which would make the system run behind events. No events would be lost as they would be queued, but callbacks would be delayed which is a bad thing.

Given the above, NEVER use Python’s time.sleep() if you want to perform an operation some time in the future, as this will tie up a thread for the period of the sleep. Instead use the scheduler’s run_in() function which will allow you to delay without blocking any threads.

State Operations

A note on Home Assistant State

State within Home Assistant is stored as a collection of dictionaries, one for each entity. Each entity’s dictionary will have some common fields and a number of entity type specific fields The state for an entity will always have the attributes:

  • last_updated
  • last_changed
  • state

Any other attributes such as brightness for a lamp will only be present if the entity supports them, and will be stored in a sub-dictionary called attributes. When specifying these optional attributes in the get_state() call, no special distinction is required between the main attributes and the optional ones - get_state() will figure it out for you.

Also bear in mind that some attributes such as brightness for a light, will not be present when the light is off.

In most cases, the attribute state has the most important value in it, e.g. for a light or switch this will be on or off, for a sensor it will be the value of that sensor. Many of the AppDaemon API calls and callbacks will implicitly return the value of state unless told to do otherwise.

Although the use of get_state() (below) is still supported, as of AppDaemon 2.0.9 it is easier to access HASS state directly as an attribute of the App itself, under the entities attribute.

For instance, to access the state of a binary sensor, you could use:

sensor_state = self.entities.binary_sensor.downstairs_sensor.state

Similarly, accessing any of the entity attributes is also possible:

name = self.entities.binary_sensor.downstairs_sensor.attributes.friendly_name

About Callbacks

A large proportion of home automation revolves around waiting for something to happen and then reacting to it; a light level drops, the sun rises, a door opens etc. Home Assistant keeps track of every state change that occurs within the system and streams that information to AppDaemon almost immediately.

An individual App however usually doesn’t care about the majority of state changes going on in the system; Apps usually care about something very specific, like a specific sensor or light. Apps need a way to be notified when a state change happens that they care about, and be able to ignore the rest. They do this through registering callbacks. A callback allows the App to describe exactly what it is interested in, and tells AppDaemon to make a call into its code in a specific place to be able to react to it - this is a very familiar concept to anyone familiar with event-based programming.

There are 3 types of callbacks within AppDaemon:

  • State Callbacks - react to a change in state
  • Scheduler Callbacks - react to a specific time or interval
  • Event Callbacks - react to specific Home Assistant and Appdaemon events.

All callbacks allow the user to specify additional parameters to be handed to the callback via the standard Python **kwargs mechanism for greater flexibility, these additional arguments are handed to the callback as a standard Python dictionary,

About Registering Callbacks

Each of the various types of callback have their own function or functions for registering the callback:

  • listen_state() for state callbacks
  • Various scheduler calls such as run_once() for scheduler callbacks
  • listen_event() for event callbacks.

Each type of callback shares a number of common mechanisms that increase flexibility.

Callback Level Constraints

When registering a callback, you can add constraints identical to the Application level constraints described earlier. The difference is that a constraint applied to an individual callback only affects that callback and no other. The constraints are applied by adding Python keyword-value style arguments after the positional arguments. The parameters themselves are named identically to the previously described constraints and have identical functionality. For instance, adding:


to a callback registration will ensure that the callback is only run if the callback conditions are met and in addition everyone is present although any other callbacks might run whenever their event fires if they have no constraints.

For example:

self.listen_state(self.motion, "binary_sensor.drive", constrain_presence="everyone")

User Arguments

Any callback has the ability to allow the App creator to pass through arbitrary keyword arguments that will be presented to the callback when it is run. The arguments are added after the positional parameters just like the constraints. The only restriction is that they cannot be the same as any constraint name for obvious reasons. For example, to pass the parameter arg1 = "home assistant" through to a callback you would register a callback as follows:

self.listen_state(self.motion, "binary_sensor.drive", arg1="home assistant")

Then in the callback it is presented back to the function as a dictionary and you could use it as follows:

def motion(self, entity, attribute, old, new, kwargs):
    self.log("Arg1 is {}".format(kwargs["arg1"]))

State Callbacks

AppDaemons’s state callbacks allow an App to listen to a wide variety of events, from every state change in the system, right down to a change of a single attribute of a particular entity. Setting up a callback is done using a single API call listen_state() which takes various arguments to allow it to do all of the above. Apps can register as many or as few callbacks as they want.

About State Callback Functions

When calling back into the App, the App must provide a class function with a known signature for AppDaemon to call. The callback will provide various information to the function to enable the function to respond appropriately. For state callbacks, a class defined callback function should look like this:

def my_callback(self, entity, attribute, old, new, kwargs):
  <do some useful work here>

You can call the function whatever you like - you will reference it in the listen_state() call, and you can create as many callback functions as you need.

The parameters have the following meanings:


A standard Python object reference.


Name of the entity the callback was requested for or None.


Name of the attribute the callback was requested for or None.


The value of the state before the state change.


The value of the state after the state change.

old and new will have varying types depending on the type of callback.


A dictionary containing any constraints and/or additional user specific keyword arguments supplied to the listen_state() call.

Publishing State from an App

Using AppDaemon it is possible to explicitly publish state from an App. The published state can contain whatever you want, and is treated exactly like any other HA state, e.g. to the rest of AppDaemon, and the dashboard it looks like an entity. This means that you can listen for state changes in other apps and also publish arbitary state to the dashboard via use of specific entity IDs. To publish state, you will use set_app_state(). State can be retrieved and listened for with the usual AppDaemon calls.

The Scheduler

AppDaemon contains a powerful scheduler that is able to run with 1 second resolution to fire off specific events at set times, or after set delays, or even relative to sunrise and sunset. In general, events should be fired less than a second after specified but under certain circumstances there may be short additional delays.

About Schedule Callbacks

As with State Change callbacks, Scheduler Callbacks expect to call into functions with a known and specific signature and a class defined Scheduler callback function should look like this:

def my_callback(self, kwargs):
  <do some useful work here>

You can call the function whatever you like; you will reference it in the Scheduler call, and you can create as many callback functions as you need.

The parameters have the following meanings:


A standard Python object reference


A dictionary containing Zero or more keyword arguments to be supplied to the callback.

Creation of Scheduler Callbacks

Scheduler callbacks are created through use of a number of convenience functions which can be used to suit the situation.

Scheduler Randomization

All of the scheduler calls above support 2 additional optional arguments, random_start and random_end. Using these arguments it is possible to randomize the firing of callbacks to the degree desired by setting the appropriate number of seconds with the parameters.

  • random_start - start of range of the random time
  • random_end - end of range of the random time

random_start must always be numerically lower than random_end, they can be negative to denote a random offset before and event, or positive to denote a random offset after an event. The event would be a an absolute or relative time or sunrise/sunset depending on whcih scheduler call you use and these values affect the base time by the spcified amount. If not specified, they will default to 0.

For example:

 Run a callback in 2 minutes minus a random number of seconds between 0 and 60, e.g. run between 60 and 120 seconds from now
self.handle = self.run_in(callback, 120, random_start = -60, **kwargs)
 Run a callback in 2 minutes plus a random number of seconds between 0 and 60, e.g. run between 120 and 180 seconds from now
self.handle = self.run_in(callback, 120, random_end = 60, **kwargs)
 Run a callback in 2 minutes plus or minus a random number of seconds between 0 and 60, e.g. run between 60 and 180 seconds from now
self.handle = self.run_in(callback, 120, random_start = -60, random_end = 60, **kwargs)

Sunrise and Sunset

AppDaemon has a number of features to allow easy tracking of sunrise and sunset as well as a couple of scheduler functions. Note that the scheduler functions also support the randomization parameters described above, but they cannot be used in conjunction with the offset parameter`.

Calling Services

About Services

Services within Home Assistant are how changes are made to the system and its devices. Services can be used to turn lights on and off, set thermostats and a whole number of other things. Home Assistant supplies a single interface to all these disparate services that take arbitrary parameters. AppDaemon provides the call_service() function to call into Home Assistant and run a service. In addition, it also provides convenience functions for some of the more common services making calling them a little easier.


About Events

Events are a fundamental part of how Home Assistant works under the covers. HA has an event bus that all components can read and write to, enabling components to inform other components when important events take place. We have already seen how state changes can be propagated to AppDaemon - a state change however is merely an example of an event within Home Assistant. There are several other event types, among them are:

  • homeassistant_start
  • homeassistant_stop
  • state_changed
  • service_registered
  • call_service
  • service_executed
  • platform_discovered
  • component_loaded

Using AppDaemon, it is possible to subscribe to specific events as well as fire off events.

In addition to the Home Assistant supplied events, AppDaemon adds 2 more events. These are internal to AppDaemon and are not visible on the Home Assistant bus:

  • appd_started - fired once when AppDaemon is first started and after Apps are initialized
  • ha_started - fired every time AppDaemon detects a Home Assistant restart
  • ha_disconnectd - fired once every time AppDaemon loses its connection with HASS

About Event Callbacks

As with State Change and Scheduler callbacks, Event Callbacks expect to call into functions with a known and specific signature and a class defined Scheduler callback function should look like this:

def my_callback(self, event_name, data, kwargs):
  <do some useful work here>

You can call the function whatever you like - you will reference it in the Scheduler call, and you can create as many callback functions as you need.

The parameters have the following meanings:


A standard Python object reference.


Name of the event that was called, e.g. call_service.


Any data that the system supplied with the event as a dict.


A dictionary containing Zero or more user keyword arguments to be supplied to the callback.


Listen event sets up a callback for a specific event, or any event.


handle = listen_event(function, event = None, **kwargs):


A handle that can be used to cancel the callback.



The function to be called when the event is fired.


Name of the event to subscribe to. Can be a standard Home Assistant event such as service_registered or an arbitrary custom event such as "MODE_CHANGE". If no event is specified, listen_event() will subscribe to all events.

**kwargs (optional)

One or more keyword value pairs representing App specific parameters to supply to the callback. If the keywords match values within the event data, they will act as filters, meaning that if they don’t match the values, the callback will not fire.

As an example of this, a Minimote controller when activated will generate an event called zwave.scene_activated, along with 2 pieces of data that are specific to the event - entity_id and scene. If you include keyword values for either of those, the values supplied to the `listen_event()1 call must match the values in the event or it will not fire. If the keywords do not match any of the data in the event they are simply ignored.

Filtering will work with any event type, but it will be necessary to figure out the data associated with the event to understand what values can be filtered on. This can be achieved by examining Home Assistant’s logfiles when the event fires.


self.listen_event(self.mode_event, "MODE_CHANGE")
 Listen for a minimote event activating scene 3:
self.listen_event(self.generic_event, "zwave.scene_activated", scene_id = 3)
 Listen for a minimote event activating scene 3 from a specific minimote:
self.listen_event(self.generic_event, "zwave.scene_activated", entity_id = "minimote_31", scene_id = 3)

Use of Events for Signalling between Home Assistant and AppDaemon

Home Assistant allows for the creation of custom events and existing components can send and receive them. This provides a useful mechanism for signaling back and forth between Home Assistant and AppDaemon. For instance, if you would like to create a UI Element to fire off some code in Home Assistant, all that is necessary is to create a script to fire a custom event, then subscribe to that event in AppDaemon. The script would look something like this:

alias: Day
- event: MODE_CHANGE
    mode: Day

The custom event MODE_CHANGE would be subscribed to with:

self.listen_event(self.mode_event, "MODE_CHANGE")

Home Assistant can send these events in a variety of other places - within automations, and also directly from Alexa intents. Home Assistant can also listen for custom events with it’s automation component. This can be used to signal from AppDaemon code back to home assistant. Here is a sample automation:

    platform: event
    event_type: MODE_CHANGE

This can be triggered with a call to AppDaemon’s fire_event() as follows:

self.fire_event("MODE_CHANGE", mode = "Day")

Use of Events for Interacting with HADashboard

HADashboard listens for certain events. An event type of “hadashboard” will trigger certain actions such as page navigation. For more information see the ` Dashboard configuration pages <DASHBOARD.html>`__

AppDaemon provides convenience funtions to assist with this.


Presence in Home Assistant is tracked using Device Trackers. The state of all device trackers can be found using the get_state() call, however AppDaemon provides several convenience functions to make this easier.

Writing to Logfiles

AppDaemon uses 2 separate logs - the general log and the error log. An AppDaemon App can write to either of these using the supplied convenience methods log() and error(), which are provided as part of parent AppDaemon class, and the call will automatically pre-pend the name of the App making the call. The -D option of AppDaemon can be used to specify what level of logging is required and the logger objects will work as expected.

ApDaemon loggin also allows you to use placeholders for the module, fucntion and line number. If you include the following in the test of your message:


They will automatically be expanded to the appropriate values in the log message.

Getting Information in Apps and Sharing information between Apps

Sharing information between different Apps is very simple if required. Each app gets access to a global dictionary stored in a class attribute called self.global_vars. Any App can add or read any key as required. This operation is not however threadsafe so some care is needed.

In addition, Apps have access to the entire configuration if required, meaning they can access AppDaemon configuration items as well as parameters from other Apps. To use this, there is a class attribute called self.config. It contains a ConfigParser object, which is similar in operation to a Dictionary. To access any apps parameters, simply reference the ConfigParser object using the Apps name (form the config file) as the first key, and the parameter required as the second, for instance:

other_apps_arg = self.config["some_app"]["some_parameter"].

To get AppDaemon’s config parameters, use the key “AppDaemon”, e.g.:

app_timezone = self.config["AppDaemon"]["time_zone"]

AppDaemon also exposes configuration from Home Assistant such as the Latitude and Longitude configured in HA. All of the information available from the Home Assistant /api/config endpoint is available in the self.ha_config dictionary. E.g.:

self.log("My current position is {}(Lat), {}(Long)".format(self.ha_config["latitude"], self.ha_config["longitude"]))

And finally, it is also possible to use the AppDaemon as a global area for sharing parameters across Apps. Simply add the required parameters to the AppDaemon section of your config:

ha_url: <some url>
ha_key: <some key>
global_var: hello world

Then access it as follows:

my_global_var = conf.config["AppDaemon"]["global_var"]

Development Workflow

Developing Apps is intended to be fairly simple but is an exercise in programming like any other kind of Python programming. As such, it is expected that apps will contain syntax errors and will generate exceptions during the development process. AppDaemon makes it very easy to iterate through the development process as it will automatically reload code that has changed and also will reload code if any of the parameters in the configuration file change as well.

The recommended workflow for development is as follows:

  • Open a window and tail the appdaemon.log file
  • Open a second window and tail the error.log file
  • Open a third window or the editor of your choice for editing the App

With this setup, you will see that every time you write the file, AppDaemon will log the fact and let you know it has reloaded the App in the appdaemon.log file.

If there is an error in the compilation or a runtime error, this will be directed to the error.log file to enable you to see the error and correct it. When an error occurs, there will also be a warning message in appdaemon.log to tell you to check the error log.

Time Travel

OK, time travel sadly isn’t really possible but it can be very useful when testing Apps. For instance, imagine you have an App that turns a light on every day at sunset. It might be nice to test it without waiting for Sunset - and with AppDaemon’s “Time Travel” features you can.

Choosing a Start Time

Internally, AppDaemon keeps track of it’s own time relative to when it was started. This make is possible to start AppDaemon with a different start time and date to the current time. For instance to test that sunset App, start AppDaemon at a time just before sunset and see if it works as expected. To do this, simply use the “-s” argument on AppDaemon’s command line. e,g,:

$ appdaemon -s "2016-06-06 19:16:00"
2016-09-06 17:16:00 INFO AppDaemon Version 1.3.2 starting
2016-09-06 17:16:00 INFO Got initial state
2016-09-06 17:16:00 INFO Loading Module: /export/hass/appdaemon_test/conf/test_apps/sunset.py

Note the timestamps in the log - AppDaemon believes it is now just before sunset and will process any callbacks appropriately.

Speeding things up

Some Apps need to run for periods of a day or two for you to test all aspects. This can be time consuming, but Time Travel can also help here in two ways. The first is by speeding up time. To do this, simply use the -t option on the command line. This specifies the amount of time a second lasts while time travelling. The default of course is 1 second, but if you change it to 0.1 for instance, AppDaemon will work 10x faster. If you set it to 0, AppDaemon will work as fast as possible and, depending in your hardware, may be able to get through an entire day in a matter of minutes. Bear in mind however, due to the threaded nature of AppDaemon, when you are running with -t 0 you may see actual events firing a little later than expected as the rest of the system tries to keep up with the timer. To set the tick time, start AppDaemon as follows:

$ appdaemon -t 0.1

AppDaemon also has an interval flag - think of this as a second multiplier. If the flag is set to 3600 for instance, each tick of the scheduler will jump the time forward by an hour. This is good for covering vast amounts of time quickly but event firing accuracy will suffer as a result. For example:

$ appdaemon -i 3600

Automatically stopping

AppDaemon can be set to terminate automatically at a specific time. This can be useful if you want to repeatedly rerun a test, for example to test that random values are behaving as expected. Simply specify the end time with the -e flag as follows:

$ appdaemon -e "2016-06-06 10:10:00"
2016-09-06 17:16:00 INFO AppDaemon Version 1.3.2 starting
2016-09-06 17:16:00 INFO Got initial state
2016-09-06 17:16:00 INFO Loading Module: /export/hass/appdaemon_test/conf/test_apps/sunset.py

The -e flag is most useful when used in conjuntion with the -s flag and optionally the -t flag. For example, to run from just before sunset, for an hour, as fast as possible:

$ appdaemon -s "2016-06-06 19:16:00" -e "2016-06-06 20:16:00" -t 0

A Note On Times

Some Apps you write may depend on checking times of events relative to the current time. If you are time travelling this will not work if you use standard python library calls to get the current time and date etc. For this reason, always use the AppDamon supplied time(), date() and datetime() calls, documented earlier. These calls will consult with AppDaemon’s internal time rather than the actual time and give you the correct values.

Other Functions

AppDaemon allows some introspection on its stored schedule and callbacks which may be useful for some applications. The functions:

  • get_scheduler_entries()
  • get_callback_entries()

Return the internal data structures, but do not allow them to be modified directly. Their format may change.

About HASS Disconnections

When AppDaemon is unable to connect initially with Home Assistant, it will hold all Apps in statsis until it initially connects, nothing else will happen and no initialization routines will be called. If AppDaemon has been running connected to Home Assitant for a while and the connection is unexpectedly lost, the following will occur:

  • When HASS first goes down or becomes disconnected, an event called ha_disconnected will fire
  • While disconnected from HASS, Apps will continue to run
  • Schedules will continue to be honored
  • Any operation reading locally cached state will succeed
  • Any operation requiring a call to HASS will log a warning and return without attempting to contact hass
  • Changes to Apps will not force a reload until HASS is reconnected

When a connection to HASS is reestablished, all Apps will be restarted and their initialize() routines will be called.

RESTFul API Support

AppDaemon supports a simple RESTFul API to enable arbitary HTTP connections to pass data to Apps and trigger actions. API Calls must use a content type of application/json, and the response will be JSON encoded. The RESTFul API is disabled by default, but is enabled by adding an ad_port directive to the AppDaemon section of the configuration file. The API can run http or https if desired, separately from the dashboard.

To call into a specific App, construct a URL, use the regular HADashboard URL, and append /api/appdaemon, then add the name of the endpoint as registered by the app on the end, for example:

This URL will call into an App that registered an endpoint named hello_endpoint.

Within the app, a call must be made to register_endpoint() to tell AppDaemon that the app is expecting calls on that endpoint. When registering an endpoint, the App supplies a function to be called when a request comes in to that endpoint and an optional name for the endpoint. If not specified, the name will default to the name of the App as specified in the configuration file.

Apps can have as many endpoints as required, however the names must be unique across all of the Apps in an AppDaemon instance.

It is also possible to remove endpoints with the unregister_endpoint() call, making the endpoints truly dynamic and under the control of the App.

Here is an example of an App using the API:

import appdaemon.appapi as appapi

class API(appapi.AppDaemon):

    def initialize(self):
        self.register_endpoint(my_callback, test_endpoint)

    def my_callback(self, data):


        response = {"message": "Hello World"}

        return response, 200

The response must be a python structure that can be mapped to JSON, or can be blank, in which case specify "" for the response. You should also return an HTML status code, that will be reported back to the caller, 200 should be used for an OK response.

As well as any user specified code, the API can return the following codes:

  • 400 - JSON Decode Error
  • 401 - Unauthorized
  • 404 - App not found

Below is an example of using curl to call into the App shown above:

hass@Pegasus:~$ curl -i -X POST -H "Content-Type: application/json" -d '{"type": "Hello World Test"}'
HTTP/1.1 200 OK
Content-Type: application/json; charset=utf-8
Content-Length: 26
Date: Sun, 06 Aug 2017 16:38:14 GMT
Server: Python/3.5 aiohttp/2.2.3

{"message": "Hello World"}hass@Pegasus:~$

API Security

If you have added a key to the AppDaemon config, AppDaemon will expect to find a header called “x-ad-access” in the request with a value equal to the configured key. A security key is added for the API with the api_key directive described in the Installation Documentation

If these conditions are not met, the call will fail with a return code of 401 Not Authorized. Here is a succesful curl example:

hass@Pegasus:~$ curl -i -X POST -H "x-ad-access: fred" -H "Content-Type: application/json" -d '{"type": "Hello World
HTTP/1.1 200 OK
Content-Type: application/json; charset=utf-8
Content-Length: 26
Date: Sun, 06 Aug 2017 17:30:50 GMT
Server: Python/3.5 aiohttp/2.2.3

{"message": "Hello World"}hass@Pegasus:~$

And an example of a missing key:

hass@Pegasus:~$ curl -i -X POST -H "Content-Type: application/json" Test"}'ype": "Hello World
HTTP/1.1 401 Unauthorized
Content-Length: 112
Content-Type: text/plain; charset=utf-8
Date: Sun, 06 Aug 2017 17:30:43 GMT
Server: Python/3.5 aiohttp/2.2.3

<html><head><title>401 Unauthorized</title></head><body><h1>401 Unauthorized</h1>Error in API Call</body></html>hass@Pegasus:~$

Alexa Support

AppDaemon is able to use the API support to accept calls from Alexa. Amazon Alexa calls can be directed to AppDaemon and arrive as JSON encoded requests. AppDaemon provides several helper functions to assist in understanding the request and responding appropriately. Since Alexa only allows one URL per skill, the mapping will be 1:1 between skills and Apps. When constructing the URL in the Alexa Intent, make sure it points to the correct endpoint for the App you are using for Alexa.

In addition, if you are using API security keys (recommended) you will need to append it to the end of the url as follows:


For more information about configuring Alexa Intents, see the Home Assistant Alexa Documentation

When configuring Alexa support for AppDaemon some care is needed. If as most people are, you are using SSL to access Home Assistant, there is contention for use of the SSL port (443) since Alexa does not allow you to change this. This means that if you want to use AppDaemon with SSL, you will not be able to use Home Assistant remotely over SSL. The way around this is to use NGINX to remap the specific AppDamon API URL to a different port, by adding something like this to the config:

  location /api/appdaemon/ {
  allow all;
  proxy_pass http://localhost:5000;
  proxy_set_header Host $host;
  proxy_redirect http:// http://;

Here we see the default port being remapped to port 5000 which is where AppDamon is listening in my setup.

Since each individual Skill has it’s own URL it is possible to have different skills for Home Assitant and AppDaemon.

Putting it together in an App

The Alexa App is basically just a standard API App that uses Alexa helper functions to understand the incoming request and format a response to be sent back to Amazon, to describe the spoken resonse and card for Alexa.

Here is a sample Alexa App that can be extended for whatever intents you want to configure.

import appdaemon.appapi as appapi
import random
import globals

class Alexa(appapi.AppDaemon):

    def initialize(self):

    def api_call(self, data):
        intent = self.get_alexa_intent(data)

        if intent is None:
            self.log("Alexa error encountered: {}".format(self.get_alexa_error(data)))
            return "", 201

        intents = {
            "StatusIntent": self.StatusIntent,
            "LocateIntent": self.LocateIntent,

        if intent in intents:
            speech, card, title = intents[intent](data)
            response = self.format_alexa_response(speech = speech, card = card, title = title)
            self.log("Recieved Alexa request: {}, answering: {}".format(intent, speech))
            response = self.format_alexa_response(speech = "I'm sorry, the {} does not exist within AppDaemon".format(intent))

        return response, 200

    def StatusIntent(self, data):
        response = self.HouseStatus()
        return response, response, "House Status"

    def LocateIntent(self, data):
        user = self.get_alexa_slot_value(data, "User")

        if user is not None:
            if user.lower() == "jack":
                response = self.Jack()
            elif user.lower() == "andrew":
                response = self.Andrew()
            elif user.lower() == "wendy":
                response = self.Wendy()
            elif user.lower() == "brett":
                response = "I have no idea where Brett is, he never tells me anything"
                response = "I'm sorry, I don't know who {} is".format(user)
            response = "I'm sorry, I don't know who that is"

        return response, response, "Where is {}?".format(user)

    def HouseStatus(self):

        status = "The downstairs temperature is {} degrees farenheit,".format(self.entities.sensor.downstairs_thermostat_temperature.state)
        status += "The upstairs temperature is {} degrees farenheit,".format(self.entities.sensor.upstairs_thermostat_temperature.state)
        status += "The outside temperature is {} degrees farenheit,".format(self.entities.sensor.side_temp_corrected.state)
        status += self.Wendy()
        status += self.Andrew()
        status += self.Jack()

        return status

    def Wendy(self):
        location = self.get_state(globals.wendy_tracker)
        if location == "home":
            status = "Wendy is home,"
            status = "Wendy is away,"

        return status

    def Andrew(self):
        location = self.get_state(globals.andrew_tracker)
        if location == "home":
            status = "Andrew is home,"
            status = "Andrew is away,"

        return status

    def Jack(self):
        responses = [
            "Jack is asleep on his chair",
            "Jack just went out bowling with his kitty friends",
            "Jack is in the hall cupboard",
            "Jack is on the back of the den sofa",
            "Jack is on the bed",
            "Jack just stole a spot on daddy's chair",
            "Jack is in the kitchen looking out of the window",
            "Jack is looking out of the front door",
            "Jack is on the windowsill behind the bed",
            "Jack is out checking on his clown suit",
            "Jack is eating his treats",
            "Jack just went out for a walk in the neigbourhood",
            "Jack is by his bowl waiting for treats"

        return random.choice(responses)

Google API.AI

Similarly, Google’s API.AI for Google home is supported - here is the Google version of the same App.To set up Api.ai with your google home refer to the apiai component in home-assistant. Once it is setup you can use the appdaemon API as the webhook.

import appdaemon.appapi as appapi import random import globals

class Apiai(appapi.AppDaemon):

def initialize(self):
def api_call(self, data):

intent = self.get_apiai_intent(data)

if intent is None:
self.log(“Apiai error encountered: Result is empty”) return “”, 201
intents = {
“StatusIntent”: self.StatusIntent, “LocateIntent”: self.LocateIntent,


if intent in intents:
speech = intents[intent](data) response = self.format_apiai_response(speech) self.log(“Recieved Apai request: {}, answering: {}”.format(intent, speech))
response = self.format_apaiai_response(speech = “I’m sorry, the {} does not exist within AppDaemon”.format(intent))

return response, 200

def StatusIntent(self, data):
response = self.HouseStatus() return response
def LocateIntent(self, data):

user = self.get_apiai_slot_value(data, “User”)

if user is not None:
if user.lower() == “jack”:
response = self.Jack()
elif user.lower() == “andrew”:
response = self.Andrew()
elif user.lower() == “wendy”:
response = self.Wendy()
elif user.lower() == “brett”:
response = “I have no idea where Brett is, he never tells me anything”
response = “I’m sorry, I don’t know who {} is”.format(user)
response = “I’m sorry, I don’t know who that is”

return response

def HouseStatus(self):

status = “The downstairs temperature is {} degrees farenheit,”.format(self.entities.sensor.downstairs_thermostat_temperature.state) status += “The upstairs temperature is {} degrees farenheit,”.format(self.entities.sensor.upstairs_thermostat_temperature.state) status += “The outside temperature is {} degrees farenheit,”.format(self.entities.sensor.side_temp_corrected.state) status += self.Wendy() status += self.Andrew() status += self.Jack()

return status

def Wendy(self):

location = self.get_state(globals.wendy_tracker) if location == “home”:

status = “Wendy is home,”
status = “Wendy is away,”

return status

def Andrew(self):

location = self.get_state(globals.andrew_tracker) if location == “home”:

status = “Andrew is home,”
status = “Andrew is away,”

return status

def Jack(self):
responses = [
“Jack is asleep on his chair”, “Jack just went out bowling with his kitty friends”, “Jack is in the hall cupboard”, “Jack is on the back of the den sofa”, “Jack is on the bed”, “Jack just stole a spot on daddy’s chair”, “Jack is in the kitchen looking out of the window”, “Jack is looking out of the front door”, “Jack is on the windowsill behind the bed”, “Jack is out checking on his clown suit”, “Jack is eating his treats”, “Jack just went out for a walk in the neigbourhood”, “Jack is by his bowl waiting for treats”


return random.choice(responses)