Event handlers

Events originate in the front-end, for example, when a user clicks a Button component. Using the Builder, these events can be linked to event handlers.

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Plain Python functions

Event handlers are Python functions accessible from main.py. They can be defined in that same file or imported. No decorators or special syntax are required.

# This event handler will add an entry to the log
def handle_click()
    print("Hello")

To specify that a function isn’t an event handler and should remain hidden to the front-end, prefix it with a _ (underscore).

# This function won't be visible in the front-end
# because its name starts with an underscore
def _reticulate(splines):
    r_splines = np.random.normal(size=(splines,100))
    return r_splines

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External handlers

If your main.py file has become cluttered with too many handler functions, you can organize them more effectively using the init_handlers method. This method allows you to register handler functions from other modules. You can pass a single imported module or a list of modules to the init_handlers method to register multiple handlers simultaneously:

# my_app/my_handlers_module.py

def increment(state):
    state["counter"] += 1

You can also call init_handlers within other modules, which allows for a sequence of registrations:

# my_app/another_handlers_module.py

def decrement(state):
    state["counter"] -= 1

Note that for this “chain” to work, you need to import the final module in the sequence into main.py.

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Mutating state

In most cases, event handlers will modify the application state. State can be accessed by including the state argument in the handler, which will provide you with a StreamsyncState object for the session that invoked the handler.

Elements of state can be reached using the square brackets syntax state["my_element"]. Accessing keys that don’t exist will return None.

def handle_click(state):
    state["counter"] += 1

The handler above receives the application state for the relevant session and mutates it. For example, if Bob’s counter was 4, and he clicks on a Button linked to handle_click, his new counter value will be 5. Other sessions remain unaffected.

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Mutation detection

When communicating with the front-end, Framework only sends state elements that have mutated.

To detect which elements have mutated, it relies on assignment (via operators such as =, +=, etc). This is because Python doesn’t offer a performant, reliable mechanism to detect mutations. See the two examples below.

def handle_click(state):
    state["my_df"].sample(frac=1, random_state=random.seed())

    # The self-assignment is necessary when mutating
    # an existing object directly on state

    state["my_df"] = state["my_df"]

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Receiving a payload

Several events include additional data, known as the event’s payload. The event handler can receive that data using the payload argument.

For example, the wf-change event in a Text Input component is triggered every time the value changes. As a payload, it includes the new value.

def handle_input_change(state, payload):
    state["value"] = payload

The content of the payload will vary depending on the event. For example, when a user takes a photo with a Webcam Capture, the picture they took is sent across as a PNG image.

def handle_webcam_capture(payload):
	image_file = payload
	with open(f"picture.png", "wb") as file_handle:
		file_handle.write(image_file)

Handling different payloads across events can be challenging, especially since the shape of the payload may vary. To simplify this process, the Builder provides stub code that can help you get started with writing an event handler. You can access it by clicking the icon located next to the event when configuring the component’s settings. This feature can help you quickly understand the structure of the payload and start writing the appropriate code to handle it.

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Globals

You can use globals and module attributes, just as you would in a standard Python script. This is very convenient for storing a single copy of resource-intensive object.

my_ai = CatIdentifierAI()

def evaluate(state, payload):
    result = my_ai.process(payload)
    state["is_a_cat"] = result

Take into account that globals apply to all users. If you need to store data that’s only relevant to a particular user, use application state.

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Middlewares

Middlewares are functions that run before and after every event handler. They can be used to perform tasks such as logging, error handling, session management, or modifying the state.

import writer as wf

@wf.middleware()
def middleware_before(state, payload, context):
	print("Middleware before event handler")
	state['running'] += 1
	yield
	print("Middleware after event handler")
	state['running'] -= 1

A middleware receives the same parameters as an event handler.

A middleware can be used to handle exceptions that happens in event handlers.

import writer as wf

@wf.middleware()
def middleware_before(state):
	try:
		yield
	except Exception as e:
		state['error_counter'] += 1
		state['last_error'] = str()
	finally:
		pass

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Standard output

The standard output of an app is captured and shown in the code editor’s log. You can use the standard print function to output results.

# Shown every time the app starts
print("Hello world")

def payload_inspector(state, payload):
    # Shown every time the event handler is executed
    print("Payload: " + repr(payload))

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Execution flow

Event handlers run in a thread pool and are non-blocking. Each event is processed independently from each other.

State mutations are sent to the front-end after the function has finished executing. The code in handle_fast will accumulate all mutations and send to the front-end after the function returns. For long-running tasks, Framework will periodically check state and provide partial updates to the user.

def handle_fast(state):
    state["text"] = "Hello"
    state["x"] += 3
    state["y"] += 2

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Asynchronous event handlers

Framework supports asynchronous event handlers, allowing for non-blocking I/O operations directly within event handlers. This is particularly useful for tasks such as fetching data from a database, making HTTP requests, or performing any other I/O bound operation that can benefit from asynchronous execution.

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Defining an asynchronous handler

An asynchronous event handler is defined with the standard async keyword syntax.

# An asynchronous event handler for performing an I/O bound operation
async def handle_async_click(state):
    data = await fetch_data()
    state["data"] = data

In the example above, fetch_data() is an asynchronous function that retrieves data, potentially from a remote source. The await keyword is used to wait for the operation to complete without blocking the main thread, allowing other tasks to run concurrently.

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Awaitable objects

You can use any awaitable object within an async event handler. This includes the output of any function defined with async def, or objects with an __await__ method. This makes it easy to integrate with asynchronous libraries and frameworks.

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Context

The context argument provides additional information about the event.

The context provide the id of component that trigger the event in target field.

def handle_click(state, context: dict):
	last_source_of_click = context['target']
	state["last_source_of_click"] = last_source_of_click

The context provides the event triggered in the event field.

def handle_click(state, context: dict):
	event_type = context['event']
	if event_type == 'click':
		state["last_event"] = 'Click'

The repeater components have additional fields in the context, such as defined in keyVariable and valueVariable.

def handle_repeater_click(state, context: dict):
	key = context['keyVariable']
	state['repeater_content'][key]['last_action'] = 'Clicked' 

More information in Repeater chapter