st-components 0.1.3

React-style stateful components for Streamlit

st-components

React-inspired stateful components for Streamlit, in pure Python.

st-components adds a small component model on top of Streamlit:

• Component for reusable, stateful UI units
• Element for thin wrappers around Streamlit primitives
• App for render-cycle orchestration, shared theme/config, and root rendering

It keeps Streamlit's rerun model, but gives larger apps a clearer tree structure, local state, and more composable UI.

Table of Contents

• Installation
• Why This Exists
• Quick Start
• Mental Model
• Onboarding Path
• Core API
• Theming and Config
• Elements
• Built-ins
• Examples
• Usage Guidelines
• Non-Goals
• License

Installation

pip install st-components

st-components builds on modict for its data models. State, Props, fibers, Theme, and Config are all modict-based, so they support both attribute access and dict-style access.

Why This Exists

Plain Streamlit is fast to start with, but larger apps often drift toward:

• flattened global st.session_state
• implicit UI structure based on script order
• reusable blocks that are hard to make truly stateful
• callbacks that require too much plumbing

st-components gives you a more explicit structure:

• Components own local state
• Elements wrap Streamlit primitives
• keys stay short and local
• the framework derives full tree paths automatically

Quick Start

from st_components import App, Component
from st_components.elements import button, container


class Counter(Component):

    def __init__(self, **props):
        super().__init__(**props)
        self.state = dict(count=0)

    def increment(self):
        self.state.count += 1

    def render(self):
        return button(key="inc", on_click=self.increment)(
            f"Clicked {self.state.count} times"
        )


app = App()(
    container(key="app")(
        Counter(key="a"),
        Counter(key="b"),
    )
)

app.render()

Each Counter keeps its own state across reruns.

Mental Model

Component

A Component is a stateful unit.

• It has persistent local state.
• Its render() method returns Components, Elements, or plain values.
• A new Python instance is created on each rerun, but its state is restored from a fiber stored in st.session_state.

Element

An Element is a render primitive.

• It usually wraps one Streamlit primitive.
• It does not own persistent local component state.
• Stateful behavior should generally be built by composing Elements inside Components.
• Its render() method is for Streamlit side effects, not for returning application data.

Render Contract

The framework treats Component and Element renders differently:

• Component.render() composes the tree. It may return Components, Elements, tuples, or plain renderable values.
• Element.render() performs Streamlit rendering work in place.
• If an Element.render() returns a value, that return value is not a separate state channel.

In practice:

• use the return value of render() to compose UI
• use set_element_value(...) / get_element_value(...) when an Element needs to expose a current value or runtime handle

This separation matters for wrappers around stateful widgets and runtime-backed elements:

• a widget's current value lives in the element value channel
• a runtime object such as a placeholder or progress handle can also live in that same channel
• both are then reached uniformly through callback context, explicit path, or Ref

Keys

Every Component and Element must have a key.

Keys are intentionally local:

• they only need to be unique among siblings
• they are not global ids
• the framework computes the full path automatically from the render context

This means two nodes can both use key="counter" safely if they live in different branches.

Onboarding Path

If you're new to the library, this is the shortest useful path:

1. Start with App, Component, and a few elements.
2. Use self.state inside components for local UI state.
3. on_change handlers receive the current widget value as value.
4. Use Ref() only when you need path-based reachability later.
5. Add typed State and Props models once the shape stabilizes.

Pattern 1: Keep local state in Components

from st_components import Component
from st_components.elements import button, container, markdown


class Panel(Component):

    def __init__(self, **props):
        super().__init__(**props)
        self.state = dict(open=False)

    def toggle(self):
        self.state.open = not self.state.open

    def render(self):
        return container(key="panel", border=True)(
            button(key="toggle", on_click=self.toggle)(
                "Hide details" if self.state.open else "Show details"
            ),
            markdown(key="body")(
                "Local component state controls this panel."
                if self.state.open
                else "Click the button to reveal more content."
            ),
        )

This is the preferred place for view state, local mode, and coordination between widgets.

Pattern 2: on_change handlers receive value

Widgets already store their value in st.session_state. st-components keeps using that storage, but exposes the current logical element value through a separate framework-level access path.

For ordinary on_change handlers, the current widget value is passed to your callback as value:

from st_components import Component
from st_components.elements import text_input


class NameForm(Component):

    def __init__(self, **props):
        super().__init__(**props)
        self.state = dict(name="")

    def sync_name(self, value):
        self.state.name = value

    def render(self):
        return text_input(
            key="name",
            value=self.state.name,
            on_change=self.sync_name,
        )("Name")

If the callback does nothing except copy the current widget value into one state field, you do not need to write a separate handler like:

def sync_name(self, value):
    self.state.name = value

Use sync_state(...) instead. It reduces this kind of boilerplate by generating that simple sync callback for you:

text_input(
    key="name",
    value=self.state.name,
    on_change=self.sync_state("name"),
)("Name")

More generally, callback payloads follow a simple rule:

• if an event carries a useful value, that value is injected into the handler
• otherwise the handler is called with no extra argument

In practice this means:

• on_change(value) for stateful widgets
• on_submit(value) for chat_input
• on_select(value) for selection-capable charts and dataframes
• on_click() for plain buttons

get_element_value() still exists as the low-level primitive underneath this. Inside a widget callback, it resolves to the Element that triggered that callback through the callback context, so you can still use it when you need the current value indirectly or want to read another element by path.

Conceptually, this is the value channel for Elements:

• stateful widgets expose their current value there
• runtime-backed Elements may expose a handle there
• access stays the same either way

Pattern 3: Use Ref() for logical reachability

Refs are path-based handles, not live object refs. In practice, you will usually pass them to helpers instead of calling methods on the ref directly.

from st_components import App, Component, Ref, get_component_state, get_element_value
from st_components.elements import button, container, markdown, text_input


name_ref = Ref()
counter_ref = Ref()


class Counter(Component):

    def __init__(self, **props):
        super().__init__(**props)
        self.state = dict(count=0)

    def increment(self):
        self.state.count += 1

    def render(self):
        return button(key="inc", on_click=self.increment)(
            f"Count: {self.state.count}"
        )


class RefDemo(Component):

    def __init__(self, **props):
        super().__init__(**props)
        self.state = dict(snapshot="")

    def capture(self):
        self.state.snapshot = (
            f"name={get_element_value(name_ref, default='')}, "
            f"count={get_component_state(counter_ref).count}"
        )

    def render(self):
        return container(key="demo", border=True)(
            text_input(key="name", ref=name_ref)("Name"),
            Counter(key="counter", ref=counter_ref),
            button(key="capture", on_click=self.capture)("Read refs"),
            markdown(key="snapshot")(self.state.snapshot or "Nothing captured yet."),
        )


App()(RefDemo(key="refs")).render()

Core API

App

App is the root entry point:

App()(MyRoot(key="root")).render()

It also owns the render cycle:

• tracks which component fibers rendered in the current pass
• unmounts fibers that disappeared from the tree
• calls component_did_unmount() for stale components

Component

Subclass Component and implement render().

Useful members:

• self.props
• self.children
• self.state
• self.set_state(...)
• component_did_mount()
• component_did_unmount()
• component_did_update(prev_state)

State

You can initialize state in __init__:

self.state = dict(count=0)

Or declare a typed nested subclass:

from st_components import Component, State
from st_components.elements import button, container, metric


class Counter(Component):

    class CounterState(State):
        count: int = 0
        label: str = "clicks"

    def increment(self):
        self.state.count += 1

    def render(self):
        return container(key="panel", border=True)(
            metric(key="metric", label=self.state.label, value=self.state.count),
            button(key="inc", on_click=self.increment)("Increment"),
        )

Typed state gives you defaults, validation, and a visible schema.

Props

You can also declare typed props with a nested Props subclass:

from modict import modict
from st_components import Component, Props
from st_components.elements import markdown


class Badge(Component):

    class BadgeProps(Props):
        _config = modict.config(extra="forbid")
        label: str = "badge"
        color: str = "blue"

    def render(self):
        return markdown(key="body")(f":{self.props.color}[**{self.props.label}**]")

@component

Use @component for simple functional components:

from st_components import App, component
from st_components.elements import container, markdown


@component
def Callout(props):
    return container(key="box", border=True)(
        markdown(key="body")(f"**{props.title}**\n\n{props.children[0]}")
    )


App()(Callout(key="intro", title="Heads up")("This is a functional component.")).render()

It can also use local state through use_state():

from st_components import component, use_state
from st_components.elements import button, markdown


@component
def Counter(props):
    state = use_state(count=props.initial)

    def increment():
        state.count += 1

    return (
        markdown(key="value")(f"Count: **{state.count}**"),
        button(key="inc", on_click=increment)("Increment"),
    )

use_state(other=None, /, **kwargs)

Minimal state hook for functional components.

@component
def Counter(props):
    state = use_state(count=0)

You can also pass a typed State instance:

from st_components import State, component, use_state
from st_components.elements import button, markdown


class CounterState(State):
    count: int = 0
    step: int = 1


@component
def Counter(props):
    state = use_state(CounterState(count=0, step=2))

    def increment():
        state.count += state.step

    return (
        markdown(key="value")(f"Count: **{state.count}**"),
        button(key="inc", on_click=increment)(f"+ {state.step}"),
    )

get_element_value(path=None, default=None)

Returns the current value of a stateful Element.

• inside the current element or its callback, path may be omitted and the current callback/render context is used
• elsewhere, pass the element path or an Element Ref
• the same API also applies when an Element exposes a runtime handle instead of a plain widget value

get_element_value("app.form.name")
get_element_value(name_ref)

Examples:

• widget value: get_element_value("app.form.name")
• current callback target: get_element_value()
• runtime handle through a ref: bar_ref.value()

get_component_state(path_or_ref)

Returns the current local state of a mounted Component.

get_component_state("app.counter")
get_component_state(counter_ref)

refresh_element(path_or_ref)

Forces a stateful Element to be recreated on the next rerun, so its declared default value is applied again.

refresh_element(name_ref)

Ref

Logical handle to a rendered Component or Element path.

Typical use:

• keep a Ref() instance on the component
• attach it to an Element or Component with ref=...
• later pass it to get_element_value(ref), get_component_state(ref), or refresh_element(ref)

Available members:

• ref.path
• ref.value(default=None) for Element refs
• ref.state() for Component refs

The methods stay available, but the preferred style is usually to pass refs to helpers.

For Element refs, ref.value() reads the same element value channel as get_element_value(ref). Depending on the Element, that may be:

• a widget value
• a placeholder/container runtime handle
• a progress handle or another Streamlit runtime object intentionally exposed by the wrapper

Element

Subclass Element when you want to wrap a Streamlit primitive directly.

Elements should stay thin. If behavior becomes stateful or orchestration-heavy, move it into a Component.

Theming and Config

App exposes official Streamlit theming and selected config options.

from st_components import App, Theme


app = App(
    theme=Theme(
        base="dark",
        primaryColor="#2dd4bf",
        backgroundColor="#0f172a",
        textColor="#e2e8f0",
        sidebar={"backgroundColor": "#111827"},
    ),
)(
    MyRoot(key="root"),
)

You can also use the built-in ThemeEditorButton to tune a theme visually while building your app:

from st_components import App, Component
from st_components.builtins import ThemeEditorButton
from st_components.elements import container, markdown


class Home(Component):

    def render(self):
        return container(key="page")(
            container(key="hero", border=True)(
                markdown(key="title")("# Hello"),
                markdown(key="body")("Use the built-in theme editor to tune the app live."),
                ThemeEditorButton(key="open", type="primary", title="Theme editor")(),
            )
        )


App()(Home(key="home")).render()

This is useful during development when you want to find a good theme quickly, then later replace it with a fixed Theme(...) in App(...) once the design is settled. If you want the lower-level primitive, ThemeEditorDialog is still available too.

Relevant entry points:

• theme=... accepts a plain dict or typed Theme
• css=... accepts raw CSS, a .css path, or a list mixing both
• config=... accepts selected runtime-relevant config.toml options
• get_app() returns the current app instance, so you can call get_app().set_theme(...), set_css(...), save_theme(), and related helpers during a rerun

Notes:

• Theme fields map to Streamlit theme config keys
• theme persistence goes through .streamlit/config.toml
• runtime application is best-effort; persisted config is the stable source of truth
• CSS is injected after theme application, so CSS can intentionally override theme-driven styles

To see this live:

python -m st_components.examples theme_editor

Elements

Import Streamlit wrappers from st_components.elements:

from st_components.elements import (
    button, checkbox, slider, text_input,
    container, columns, tabs, expander,
    markdown, metric, json,
)

Coverage is organized by package:

• text
• input
• layout
• display
• charts
• media
• feedback

The wrappers stay aligned with Streamlit signatures, with framework-specific key and optional ref.

Built-ins

Import higher-level structural components from st_components.builtins:

from st_components.builtins import (
    Conditional, Case, Switch, Match, Default,
    KeepAlive, ThemeEditorButton, ThemeEditorDialog, Router, Page,
)

Current built-ins include:

• flow helpers: Conditional, Case, Switch, Match, Default, KeepAlive
• app helpers: Router, Page
• theme tooling: ThemeEditor, ThemeEditorButton, ThemeEditorDialog

Examples

Useful examples:

• python -m st_components.examples dashboard
• python -m st_components.examples functional
• python -m st_components.examples flow
• python -m st_components.examples theme_editor
• python -m st_components.examples primitives

You can also still run example files directly from the repository with streamlit run examples/<name>.py.

If you want the fastest onboarding path, start with:

1. python -m st_components.examples dashboard
2. python -m st_components.examples functional
3. python -m st_components.examples theme_editor

Usage Guidelines

Prefer Components for behavior

If something has local state, coordinates several widgets, or behaves like a reusable UI block, it should usually be a Component.

Prefer Elements for thin wrappers

If something is just a direct Streamlit primitive with a compositional API, keep it as an Element.

Keep keys local and boring

Good:

• key="name"
• key="filters"
• key="save"

Bad:

• globally namespaced keys everywhere
• encoded hierarchy inside user keys

Do not duplicate widget state unless you need to

Widget values already live in st.session_state. Copy them into component state only when you want a component-level snapshot, derived state, or cross-widget coordination.

Think in paths, not instances

Because reruns recreate the tree, the stable identity is the resolved path, not the Python object from a previous run.

Non-Goals

st-components is not trying to provide:

• a virtual DOM
• JSX
• imperative control over live UI instances
• a replacement for Streamlit's execution model

It is a structuring layer over Streamlit, not a different frontend runtime.

License

MIT