Schema declarations on the Application state allows Framework to handle complex serialisation scenarios, while also allowing your IDE and toolchains to provide autocomplete and type checking.

Schema declaration

import writer as wf

class AppSchema(wf.StreamsyncState):
    counter: int

initial_state = wf.init_state({
    "counter": 0
}, schema=AppSchema)

# Event handler
# It receives the session state as an argument and mutates it
def increment(state: AppSchema):
    state.counter += 1

Accessing an attribute by its key is always possible.

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

Attributes missing from the schema remain accessible by their key.

initial_state = wf.init_state({
    "counter": 0,
    "message": None
}, schema=AppSchema)

def increment(state: AppSchema):
    state['message'] = "Hello pigeon"

Schema composition

Schema composition allows you to model a complex Application state.

class MyappSchema(wf.State):
    title: str

class AppSchema(wf.StreamsyncState):
    my_app: MyappSchema
    counter: int

initial_state = wf.init_state({
    "counter": 0,
    "my_app": {
        "title": "Nested value"
    }
}, schema=AppSchema)

Multi-level dictionary

Some components like Vega Lite Chart require specifying a graph in the form of a multi-level dictionary.

A schema allows you to specify that an attribute which contains a dictionary must be treated as a dictionary, rather than as a group of state.

class AppSchema(wf.StreamsyncState):
    vegas_graph: dict

# Without schema, this handler is execute only once
def handle_vega_graph(state: AppSchema):
    graph = state.vega_graph
    graph["data"]["values"][0]["b"] += 1000
    state.vega_graph = graph
    
initial_state = wf.init_state({
    "vegas_graph": {
        "data": {
            "values": [
                {"a": "C", "b": 2}, {"a": "C", "b": 7}, {"a": "C", "b": 4},
                {"a": "D", "b": 1}, {"a": "D", "b": 2}, {"a": "D", "b": 6},
                {"a": "E", "b": 8}, {"a": "E", "b": 4}, {"a": "E", "b": 7}
            ]
        },
        "mark": "bar",
        "encoding": {
            "x": {"field": "a", "type": "nominal"},
            "y": {"aggregate": "average", "field": "b", "type": "quantitative"}
        }
    },
}, schema=AppSchema)

Type checking

A schema allows you to check the integrity of your back-end using the type system. The code below will raise an error with mypy.

$ mypy apps/myapp/main.py
apps/myapp/main.py:7: error: "AppSchema" has no attribute "countr"; maybe "counter"?  [attr-defined] 

Here is the code, can you spot the error ?

import writer as wf

class AppSchema(wf.StreamsyncState):
    counter: int

def increment(state: AppSchema):
    state.countr += 1

initial_state = wf.init_state({
    "counter": 26,
}, schema=AppSchema)