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"""Animated values, derived animated nodes, and native-driven animation.

Modeled on React Native's ``Animated`` API with an ``async``-aware

completion contract. The core primitives are:

- [`AnimatedValue`][pythonnative.animated.AnimatedValue]: a numeric

cell attached to native view properties; animations drive it over

time.

- **Derived nodes**: every animated node supports

[`interpolate`][pythonnative.animated.AnimatedNode.interpolate]

(range mapping with numeric, color, and angle outputs) and Python

arithmetic (``opacity * 0.5``, ``x + y``, ``-value``), producing

read-only [`AnimatedNode`][pythonnative.animated.AnimatedNode]

instances that update whenever their inputs change.

- ``Animated.timing`` / ``Animated.spring`` / ``Animated.decay``:

animation factories. The objects they return implement

``__await__``, so you can write ``await Animated.timing(v, to=1.0)``

to suspend until the animation finishes.

- ``Animated.sequence`` / ``Animated.parallel`` / ``Animated.stagger``

/ ``Animated.delay`` / ``Animated.loop``: composition; also

awaitable.

- ``Animated.event``: build an event-prop callback that copies event

fields into animated values (``on_scroll=pn.Animated.event(y=v)``).

- ``Animated.diff_clamp``: accumulate an input's *deltas* into a

clamped range (the collapsing-header primitive).

- ``Animated.View`` / ``Animated.Text`` / ``Animated.Image``:

components whose ``style`` may contain animated nodes, including

inside ``transform`` entries.

Driver architecture (the **native driver**):

When an animation starts, PythonNative compiles its spec (curve,

duration, target value) and offers it to the platform handler of every

native view the value is attached to

([`ViewHandler.start_animation`][pythonnative.native_views.base.ViewHandler.start_animation]).

- **Accepted** (iOS Core Animation, Android ``ViewPropertyAnimator`` /

``DynamicAnimation``): the platform animates the property entirely

natively; no Python code runs per frame. Python receives exactly one

callback when the animation settles, updates the

[`AnimatedValue`][pythonnative.animated.AnimatedValue], and resolves

any awaiting tasks.

- **Declined** (desktop preview, unattached values, callable easings,

values feeding Python-side listeners or derived nodes): a single

background thread ticks the animation at ~60 Hz from Python, pushing

each frame through ``set_animated_property``. Semantics are

identical; only the frame source differs.

Values driven by *events* (scroll offsets via ``Animated.event``,

gesture translations) flow through Python: the native listener fires,

the bound values update, and every attachment (including derived

nodes) is pushed in the same call.

Example:

```python

import pythonnative as pn

@pn.component

def FadeIn():

opacity = pn.use_animated_value(0.0)

async def fade_in():

await pn.Animated.timing(opacity, to=1.0, duration=400)

await pn.Animated.timing(opacity, to=0.5, duration=200)

pn.use_effect(fade_in, [])

return pn.Animated.View(

pn.Text("Hello!"),

style={"opacity": opacity, "padding": 20},

)

```

"""

from __future__ import annotations

import asyncio

import bisect

import itertools

import math

import threading

import time

import weakref

from typing import Any, Callable, Dict, List, Optional, Sequence, Tuple

from .element import Element

from .hooks import use_effect, use_ref

from .runtime import resolve_future

from .style import StyleProp, resolve_style

# Maximum frame rate at which the Python fallback ticker drives

# animations (native-driven animations run at the display's refresh

# rate, managed by the platform).

_TARGET_FPS = 60.0

_FRAME_DT = 1.0 / _TARGET_FPS

# Upper bound on how much wall-clock time the fallback loop will try to

# catch up on in a single iteration after thread starvation. At 60 fps

# this is ~333 ms of simulated motion; further drift is dropped to keep

# the loop responsive.

_MAX_CATCHUP_FRAMES = 20

_EASINGS: Dict[str, Callable[[float], float]] = {

"linear": lambda t: t,

"ease_in": lambda t: t * t,

"ease_out": lambda t: 1.0 - (1.0 - t) * (1.0 - t),

"ease_in_out": lambda t: 3.0 * t * t - 2.0 * t * t * t,

"ease_in_quad": lambda t: t * t,

"ease_out_quad": lambda t: 1.0 - (1.0 - t) * (1.0 - t),

"bounce": lambda t: (

# Robert Penner's bounce out, common easing.

7.5625 * t * t

if t < 1 / 2.75

else (

7.5625 * (t - 1.5 / 2.75) * (t - 1.5 / 2.75) + 0.75

if t < 2 / 2.75

else (

7.5625 * (t - 2.25 / 2.75) * (t - 2.25 / 2.75) + 0.9375

if t < 2.5 / 2.75

else 7.5625 * (t - 2.625 / 2.75) * (t - 2.625 / 2.75) + 0.984375

)

}

def _resolve_easing(name: Any) -> Callable[[float], float]:

if callable(name):

return name

return _EASINGS.get(str(name), _EASINGS["ease_in_out"])

def _backend() -> Any:

"""Return the active native-view registry (the animation backend)."""

from .native_views import get_registry

return get_registry()

# Process-unique ids for native animations, so completion callbacks can

# be routed without holding references on the native side.

_anim_id_counter = itertools.count(1)

# ======================================================================

# AnimatedNode: the shared graph-node base

# ======================================================================

class AnimatedNode:

"""Base class for every animated node (settable leaves and derived nodes).

An animated node holds a current output value and a set of

``(tag, prop)`` **attachments** binding it to native view

properties. Whenever the node's output changes (a leaf was set or

animated, or an input of a derived node changed), the new value is

pushed to every attachment through the registry's

``set_animated_property`` and to every Python-side listener, then

propagated to derived nodes built from this one.

Derived nodes are constructed with

[`interpolate`][pythonnative.animated.AnimatedNode.interpolate],

with Python arithmetic operators (``+``, ``-``, ``*``, ``/``,

``%``, unary ``-``), or with ``Animated.diff_clamp``. They are

read-only: only [`AnimatedValue`][pythonnative.AnimatedValue]

leaves can be set or animated directly.

"""

__slots__ = ("_subscribers", "_attachments", "_lock", "_children", "__weakref__")

def __init__(self) -> None:

self._subscribers: List[Tuple[str, Callable[[Any], None]]] = []

self._attachments: List[Tuple[int, str]] = []

self._lock = threading.Lock()

# Derived nodes built from this one. Weak so a discarded

# interpolation doesn't keep receiving pushes forever.

self._children: "weakref.WeakSet[AnimatedNode]" = weakref.WeakSet()

# -- value -----------------------------------------------------------

@property

def value(self) -> Any:

"""Return the node's current output value."""

raise NotImplementedError

def __float__(self) -> float:

try:

return float(self.value)

except (TypeError, ValueError):

return 0.0

# -- graph -----------------------------------------------------------

def _adopt_child(self, child: "AnimatedNode") -> None:

with self._lock:

self._children.add(child)

def _has_dependents(self) -> bool:

"""Whether any derived node consumes this node's output."""

with self._lock:

return len(self._children) > 0

def _refresh(self) -> None:

"""Hook for stateful derived nodes to update from their inputs."""

def _propagate(self) -> None:

"""Push the current output to attachments/listeners and descend."""

self._refresh()

current = self.value

with self._lock:

subs = list(self._subscribers)

attachments = list(self._attachments)

children = list(self._children)

if attachments:

try:

backend = _backend()

for tag, prop in attachments:

backend.set_animated_property(tag, prop, current)

except Exception:

pass

for _prop, cb in subs:

try:

cb(current)

except Exception:

pass

for child in children:

child._propagate()

# -- bindings ----------------------------------------------------------

def attach(self, tag: int, prop: str) -> Callable[[], None]:

"""Bind this node to ``prop`` of the native view under ``tag``.

The current value is pushed immediately so the view reflects it

even if no animation is running. Returns a detach callable.

"""

binding = (tag, prop)

with self._lock:

self._attachments.append(binding)

try:

_backend().set_animated_property(tag, prop, self.value)

except Exception:

pass

def _detach() -> None:

with self._lock:

try:

self._attachments.remove(binding)

except ValueError:

pass

return _detach

def attachments(self) -> List[Tuple[int, str]]:

"""Snapshot of the current ``(tag, prop)`` bindings."""

with self._lock:

return list(self._attachments)

# -- listeners ---------------------------------------------------------

def add_listener(self, prop: str, callback: Callable[[Any], None]) -> Callable[[], None]:

"""Register ``callback`` for Python-driven changes to this node.

Returns an unsubscribe callable. ``prop`` is metadata only; it

lets the subscriber differentiate this binding from others on

the same node.

"""

with self._lock:

self._subscribers.append((prop, callback))

def _unsubscribe() -> None:

with self._lock:

try:

self._subscribers.remove((prop, callback))

except ValueError:

pass

return _unsubscribe

def has_listeners(self) -> bool:

"""Whether any Python-side listeners are registered."""

with self._lock:

return bool(self._subscribers)

# -- derivation --------------------------------------------------------

def interpolate(

self,

input_range: Sequence[float],

output_range: Sequence[Any],

extrapolate: str = "extend",

extrapolate_left: Optional[str] = None,

extrapolate_right: Optional[str] = None,

) -> "AnimatedInterpolation":

"""Map this node's value through an input/output range.

Mirrors React Native's ``interpolate``. ``output_range`` may

contain numbers, colors (``"#RRGGBB"`` / ``"#AARRGGBB"``), or

angle strings (``"45deg"`` / ``"0.5rad"``, emitted as numeric

degrees for the ``rotate`` transform).

Args:

input_range: Monotonically non-decreasing breakpoints for

this node's value. At least two entries.

output_range: Output breakpoints, same length as

``input_range``.

extrapolate: Behavior outside the input range:

``"extend"`` (continue the edge segment's slope,

default), ``"clamp"`` (pin to the edge output), or

``"identity"`` (return the input unchanged).

extrapolate_left: Override ``extrapolate`` below the range.

extrapolate_right: Override ``extrapolate`` above the range.

Returns:

A derived, read-only animated node.

Example:

```python

header_height = scroll_y.interpolate(

input_range=[0, 120],

output_range=[160, 56],

extrapolate="clamp",

)

```

"""

return AnimatedInterpolation(

self,

input_range,

output_range,

extrapolate=extrapolate,

extrapolate_left=extrapolate_left,

extrapolate_right=extrapolate_right,

)

# -- arithmetic --------------------------------------------------------

def __add__(self, other: Any) -> "_AnimatedOperation":

return _AnimatedOperation("add", lambda a, b: a + b, [self, other])

def __radd__(self, other: Any) -> "_AnimatedOperation":

return _AnimatedOperation("add", lambda a, b: a + b, [other, self])

def __sub__(self, other: Any) -> "_AnimatedOperation":

return _AnimatedOperation("subtract", lambda a, b: a - b, [self, other])

def __rsub__(self, other: Any) -> "_AnimatedOperation":

return _AnimatedOperation("subtract", lambda a, b: a - b, [other, self])

def __mul__(self, other: Any) -> "_AnimatedOperation":

return _AnimatedOperation("multiply", lambda a, b: a * b, [self, other])

def __rmul__(self, other: Any) -> "_AnimatedOperation":

return _AnimatedOperation("multiply", lambda a, b: a * b, [other, self])

def __truediv__(self, other: Any) -> "_AnimatedOperation":

return _AnimatedOperation("divide", lambda a, b: a / b if b else 0.0, [self, other])

def __rtruediv__(self, other: Any) -> "_AnimatedOperation":

return _AnimatedOperation("divide", lambda a, b: a / b if b else 0.0, [other, self])

def __mod__(self, other: Any) -> "_AnimatedOperation":

return _AnimatedOperation("modulo", lambda a, b: math.fmod(a, b) if b else 0.0, [self, other])

def __neg__(self) -> "_AnimatedOperation":

return _AnimatedOperation("negate", lambda a: -a, [self])

# ======================================================================

# AnimatedValue: the settable leaf

# ======================================================================

class AnimatedValue(AnimatedNode):

"""A numeric cell that can be attached to native view properties.

Animated components (``Animated.View`` et al.) **attach** the value

to ``(tag, prop)`` bindings after mount. Setting the value pushes

the new number to every attached native view through the registry's

``set_animated_property`` (and through every derived node built

from this value), and when an animation can be driven natively, the

platform animates those same bindings directly.

Python-side listeners registered via

[`add_listener`][pythonnative.animated.AnimatedNode.add_listener]

observe every Python-driven change. Natively-driven animations

intentionally skip per-frame Python callbacks (that's the point);

listeners see the final settled value.

"""

__slots__ = ("_value", "_native_group")

def __init__(self, initial: float = 0.0) -> None:

super().__init__()

self._value = float(initial)

# The in-flight native animation group driving this value, if any.

self._native_group: Optional["_NativeAnimationGroup"] = None

@property

def value(self) -> float:

"""Return the current numeric value (without subscribing)."""

return self._value

def set_value(self, new_value: float) -> None:

"""Set the value immediately, pushing to native views and listeners."""

self._apply(float(new_value), push_native=True)

def _apply(self, new_value: float, push_native: bool) -> None:

with self._lock:

self._value = new_value

subs = list(self._subscribers)

attachments = list(self._attachments)

children = list(self._children)

if push_native and attachments:

try:

backend = _backend()

for tag, prop in attachments:

backend.set_animated_property(tag, prop, new_value)

except Exception:

pass

for prop, cb in subs:

try:

cb(new_value)

except Exception:

pass

for child in children:

child._propagate()

# -- native handoff ------------------------------------------------

def _adopt_native_group(self, group: Optional["_NativeAnimationGroup"]) -> None:

previous = self._native_group

self._native_group = group

if previous is not None and previous is not group:

previous.cancel()

def stop_animation(self) -> None:

"""Cancel any in-flight animation on this value (native or Python)."""

self._adopt_native_group(None)

_manager.cancel_for_value(self)

def __repr__(self) -> str:

return f"AnimatedValue({self._value:g})"

# ======================================================================

# Derived nodes

# ======================================================================

def _parse_color_output(value: str) -> Optional[Tuple[int, int, int, int]]:

"""Parse ``"#RRGGBB"`` / ``"#AARRGGBB"`` into an ``(a, r, g, b)`` tuple."""

c = value.strip().lstrip("#")

if len(c) == 6:

c = "FF" + c

if len(c) != 8:

return None

try:

raw = int(c, 16)

except ValueError:

return None

return ((raw >> 24) & 0xFF, (raw >> 16) & 0xFF, (raw >> 8) & 0xFF, raw & 0xFF)

def _parse_angle_output(value: str) -> Optional[float]:

"""Parse ``"45deg"`` / ``"0.5rad"`` into numeric degrees."""

text = value.strip()

try:

if text.endswith("deg"):

return float(text[:-3])

if text.endswith("rad"):

return math.degrees(float(text[:-3]))

except ValueError:

return None

class AnimatedInterpolation(AnimatedNode):

"""Read-only node mapping a parent node through an input/output range.

Built via

[`AnimatedNode.interpolate`][pythonnative.animated.AnimatedNode.interpolate];

see that method for the semantics of the arguments.

"""

__slots__ = (

"_parent",

"_inputs",

"_outputs",

"_kind",

"_left",

"_right",

)

def __init__(

self,

parent: AnimatedNode,

input_range: Sequence[float],

output_range: Sequence[Any],

extrapolate: str = "extend",

extrapolate_left: Optional[str] = None,

extrapolate_right: Optional[str] = None,

) -> None:

super().__init__()

inputs = [float(v) for v in input_range]

outputs = list(output_range)

if len(inputs) < 2:

raise ValueError("interpolate() needs at least two input_range entries")

if len(inputs) != len(outputs):

raise ValueError("interpolate() input_range and output_range must have the same length")

for a, b in zip(inputs, inputs[1:]):

if b < a:

raise ValueError("interpolate() input_range must be monotonically non-decreasing")

kind = "number"

first = outputs[0]

if isinstance(first, str):

if _parse_color_output(first) is not None:

kind = "color"

outputs = [_parse_color_output(str(v)) for v in outputs]

if any(v is None for v in outputs):

raise ValueError("interpolate() color output_range entries must all be colors")

else:

angles = [_parse_angle_output(str(v)) for v in outputs]

if any(v is None for v in angles):

raise ValueError(f"interpolate() cannot parse output value {first!r}")

outputs = angles

else:

outputs = [float(v) for v in outputs]

self._parent = parent

self._inputs = inputs

self._outputs: List[Any] = outputs

self._kind = kind

self._left = extrapolate_left or extrapolate

self._right = extrapolate_right or extrapolate

parent._adopt_child(self)

@property

def value(self) -> Any:

"""Return the interpolated output for the parent's current value."""

return self._compute(float(self._parent))

def _compute(self, x: float) -> Any:

inputs = self._inputs

n = len(inputs)

if x < inputs[0]:

if self._left == "identity":

return x

if self._left == "clamp":

x = inputs[0]

i = 0

elif x > inputs[-1]:

if self._right == "identity":

return x

if self._right == "clamp":

x = inputs[-1]

i = n - 2

else:

i = max(0, min(n - 2, bisect.bisect_right(inputs, x) - 1))

x0, x1 = inputs[i], inputs[i + 1]

span = x1 - x0

t = 0.0 if span <= 0 else (x - x0) / span

if self._kind == "color":

c0 = self._outputs[i]

c1 = self._outputs[i + 1]

t_cl = max(0.0, min(1.0, t))

channels = [int(round(c0[j] + (c1[j] - c0[j]) * t_cl)) for j in range(4)]

a, r, g, b = (max(0, min(255, ch)) for ch in channels)

return f"#{a:02X}{r:02X}{g:02X}{b:02X}"

y0 = self._outputs[i]

y1 = self._outputs[i + 1]

return y0 + (y1 - y0) * t

def __repr__(self) -> str:

return f"AnimatedInterpolation({self._inputs} -> {self._outputs})"

class _AnimatedOperation(AnimatedNode):

"""Read-only node computed from other nodes (and constants) by ``fn``."""

__slots__ = ("_op", "_fn", "_parents")

def __init__(self, op: str, fn: Callable[..., float], parents: List[Any]) -> None:

super().__init__()

self._op = op

self._fn = fn

self._parents = list(parents)

for parent in self._parents:

if isinstance(parent, AnimatedNode):

parent._adopt_child(self)

@property

def value(self) -> float:

args = [float(p) if isinstance(p, AnimatedNode) else float(p) for p in self._parents]

try:

return float(self._fn(*args))

except Exception:

return 0.0

def __repr__(self) -> str:

return f"AnimatedOperation({self._op})"

class _AnimatedDiffClamp(AnimatedNode):

"""Accumulate a parent's *deltas* into a clamped range.

Mirrors React Native's ``Animated.diffClamp``: the output moves by

the same amount as the input but is pinned to ``[min, max]``, so

scrolling far down then slightly up immediately re-reveals a

collapsing header regardless of absolute offset.

"""

__slots__ = ("_parent", "_min", "_max", "_last_input", "_current")

def __init__(self, parent: AnimatedNode, min_value: float, max_value: float) -> None:

super().__init__()

if max_value < min_value:

raise ValueError("diff_clamp() requires min_value <= max_value")

self._parent = parent

self._min = float(min_value)

self._max = float(max_value)

self._last_input = float(parent)

self._current = max(self._min, min(self._max, self._last_input))

parent._adopt_child(self)

@property

def value(self) -> float:

return self._current

def _refresh(self) -> None:

latest = float(self._parent)

delta = latest - self._last_input

self._last_input = latest

self._current = max(self._min, min(self._max, self._current + delta))

# ======================================================================

# Animated.event

# ======================================================================

class AnimatedEvent:

"""Callable event handler copying event fields into animated values.

Built via ``pn.Animated.event(...)``. Each keyword argument names a

field on the incoming event payload (a dict key for scroll payloads

such as ``{"x": ..., "y": ...}``, or an attribute for

[`GestureEvent`][pythonnative.gestures.GestureEvent] instances) and

maps it onto an [`AnimatedValue`][pythonnative.AnimatedValue].

Because the result is an ordinary callable, it can be passed to any

event prop:

```python

scroll_y = pn.use_animated_value(0.0)

pn.ScrollView(..., on_scroll=pn.Animated.event(y=scroll_y))

tx = pn.use_animated_value(0.0)

gestures.Pan(on_change=pn.Animated.event(translation_x=tx))

```

"""

__slots__ = ("_bindings", "_listener")

def __init__(self, listener: Optional[Callable[..., None]] = None, **bindings: AnimatedValue) -> None:

for name, node in bindings.items():

if not isinstance(node, AnimatedValue):

raise TypeError(

f"Animated.event() field {name!r} must map to an AnimatedValue "

f"(got {type(node).__name__}); derived nodes are read-only."

)

self._bindings = dict(bindings)

self._listener = listener

def __call__(self, payload: Any = None, *args: Any) -> None:

"""Write bound payload fields into their values, then run the listener.

Args:

payload: The event payload; a dict is read by key, any

other object by attribute. Missing or non-numeric

fields are skipped.

*args: Extra positional arguments forwarded to the

listener.

"""

for name, node in self._bindings.items():

raw: Any = None

if isinstance(payload, dict):

raw = payload.get(name)

elif payload is not None:

raw = getattr(payload, name, None)

if raw is None:

continue

try:

node.set_value(float(raw))

except (TypeError, ValueError):

continue

if self._listener is not None:

try:

self._listener(payload, *args)

except Exception:

pass

# ======================================================================

# Python fallback driver

# ======================================================================

class _AnimationManager:

"""Single-threaded fallback driver for Python-ticked animations.

Holds a list of ``_RunningAnimation`` instances and ticks them at

~60 Hz. The thread starts on first use and idles when nothing is

active. Native-driven animations never touch this loop.

"""

def __init__(self) -> None:

self._lock = threading.Lock()

self._animations: List[_RunningAnimation] = []

self._thread: Optional[threading.Thread] = None

self._stopped = False

def add(self, anim: "_RunningAnimation") -> None:

with self._lock:

self._animations.append(anim)

self._ensure_thread_locked()

def remove(self, anim: "_RunningAnimation") -> None:

with self._lock:

try:

self._animations.remove(anim)

except ValueError:

pass

def cancel_for_value(self, value: AnimatedValue) -> None:

"""Cancel every queued/running Python-driven animation on ``value``."""

with self._lock:

stale = [a for a in self._animations if a.value is value]

for anim in stale:

self._animations.remove(anim)

for anim in stale:

anim._finish()

def _ensure_thread_locked(self) -> None:

if self._thread is not None and self._thread.is_alive():

return

self._thread = threading.Thread(target=self._loop, daemon=True, name="pn-animated")

self._thread.start()

def _loop(self) -> None:

last = time.monotonic()

# Clamping the per-tick dt is important for numerical stability:

# an underdamped spring with a 0.3 s step explodes immediately,

# and the animation thread can be starved for several frames

# during render bursts. We integrate physics on a clamped dt

# (max 2 target frames) and sub-step when wall-clock has

# advanced more than that, so the perceived motion still tracks

# real time at most a couple of frames behind. After an extreme

# starvation (e.g. the app was backgrounded for seconds) we cap

# the catch-up at ``_MAX_CATCHUP_FRAMES`` worth of physics; any

# further wall-clock drift is dropped on the floor, which keeps

# the loop responsive instead of spinning forward through

# hundreds of substeps.

max_step = _FRAME_DT * 2.0

max_catchup = _FRAME_DT * _MAX_CATCHUP_FRAMES

while not self._stopped:

now = time.monotonic()

dt = now - last

last = now

with self._lock:

active = list(self._animations)

if not active:

time.sleep(0.05)

last = time.monotonic()

continue

remaining = min(dt, max_catchup)

while remaining > 0.0:

step = remaining if remaining <= max_step else max_step

remaining -= step

for anim in active:

if getattr(anim, "_completed", False):

continue

try:

finished = anim.advance(step)

except Exception:

finished = True

if finished:

self.remove(anim)

time.sleep(_FRAME_DT)

_manager = _AnimationManager()

# ======================================================================

# Python-driven animation primitives (the fallback path)

# ======================================================================

class _RunningAnimation:

"""Base class for Python-ticked animations; ``advance()`` returns True when done."""

def __init__(self, value: AnimatedValue) -> None:

self.value = value

self._completion_futures: List[asyncio.Future[None]] = []

self._completed = False

def add_completion_future(self, future: asyncio.Future[None]) -> None:

"""Register ``future`` to be resolved when the animation ends."""

self._completion_futures.append(future)

if self._completed:

resolve_future(future, None)

def advance(self, dt: float) -> bool:

raise NotImplementedError

def _finish(self) -> None:

if self._completed:

return

self._completed = True

for fut in self._completion_futures:

resolve_future(fut, None)

class _TimingAnimation(_RunningAnimation):

def __init__(

self,

value: AnimatedValue,

to: float,

duration: float,

easing: Callable[[float], float],

) -> None:

super().__init__(value)

self._from = value.value

self._to = float(to)

self._duration = max(0.001, float(duration) / 1000.0)

self._easing = easing

self._elapsed = 0.0

def advance(self, dt: float) -> bool:

self._elapsed += dt

progress = min(1.0, self._elapsed / self._duration)

eased = self._easing(progress)

new_val = self._from + (self._to - self._from) * eased

self.value.set_value(new_val)

if progress >= 1.0:

self._finish()

return True

return False

class _SpringAnimation(_RunningAnimation):

"""Damped harmonic spring driver."""

def __init__(

self,

value: AnimatedValue,

to: float,

stiffness: float,

damping: float,

mass: float,

initial_velocity: float = 0.0,

) -> None:

super().__init__(value)

self._to = float(to)

self._velocity = float(initial_velocity)

self._stiffness = float(stiffness)

self._damping = float(damping)

self._mass = float(mass)

self._rest_threshold = 0.001

def advance(self, dt: float) -> bool:

x = self.value.value

a = (-self._stiffness * (x - self._to) - self._damping * self._velocity) / self._mass

self._velocity += a * dt

new_x = x + self._velocity * dt

self.value.set_value(new_x)

if abs(new_x - self._to) < self._rest_threshold and abs(self._velocity) < self._rest_threshold:

self.value.set_value(self._to)

self._finish()

return True

return False

class _DecayAnimation(_RunningAnimation):

def __init__(self, value: AnimatedValue, velocity: float, deceleration: float) -> None:

super().__init__(value)

self._velocity = float(velocity)

self._deceleration = float(deceleration)

self._rest_threshold = 0.001

def advance(self, dt: float) -> bool:

self._velocity *= math.exp(-self._deceleration * dt * 1000.0)

new_x = self.value.value + self._velocity * dt

self.value.set_value(new_x)

if abs(self._velocity) < self._rest_threshold:

self._finish()

return True

return False

class _DelayAnimation(_RunningAnimation):

def __init__(self, duration_ms: float) -> None:

super().__init__(AnimatedValue(0.0))

self._elapsed = 0.0

self._duration = max(0.001, duration_ms / 1000.0)

def advance(self, dt: float) -> bool:

self._elapsed += dt

if self._elapsed >= self._duration:

self._finish()

return True

return False

# ======================================================================

# Native-driven animation group

# ======================================================================

class _NativeAnimationGroup:

"""One logical animation fanned out to N natively-animated views.

Each attached ``(tag, prop)`` binding gets its own ``anim_id``; the

group completes when the platform reports completion for all of

them. Cancellation asks each platform handler for the current

presentation value so the ``AnimatedValue`` lands wherever the view

visually was.

"""

def __init__(self, value: AnimatedValue, final_value: float) -> None:

self.value = value

self.final_value = final_value

self._targets: Dict[int, Tuple[int, str]] = {} # anim_id -> (tag, prop)

self._pending: set = set()

self._completion_futures: List[asyncio.Future[None]] = []

self._completed = False

self._lock = threading.Lock()

def add_target(self, anim_id: int, tag: int, prop: str) -> None:

with self._lock:

self._targets[anim_id] = (tag, prop)

self._pending.add(anim_id)

_native_groups[anim_id] = self

def add_completion_future(self, future: asyncio.Future[None]) -> None:

with self._lock:

done = self._completed

if not done:

self._completion_futures.append(future)

if done:

resolve_future(future, None)

def target_completed(self, anim_id: int, finished: bool) -> None:

with self._lock:

self._pending.discard(anim_id)

remaining = len(self._pending)

_native_groups.pop(anim_id, None)

if remaining == 0:

self._settle(self.final_value if finished else None)

def cancel(self) -> None:

"""Cancel all in-flight native animations, syncing to presentation values."""

with self._lock:

targets = dict(self._targets)

self._pending.clear()

presentation: Optional[float] = None

try:

backend = _backend()

for anim_id, (tag, _prop) in targets.items():

_native_groups.pop(anim_id, None)

current = backend.cancel_animation(tag, anim_id)

if current is not None:

try:

presentation = float(current)

except (TypeError, ValueError):

pass

except Exception:

pass

self._settle(presentation)

def _settle(self, end_value: Optional[float]) -> None:

with self._lock:

if self._completed:

return

self._completed = True

futures = list(self._completion_futures)

self._completion_futures.clear()

if self.value._native_group is self:

self.value._native_group = None

if end_value is not None:

# The native side already shows this value; update the

# Python cell (and listeners) without re-pushing.

self.value._apply(end_value, push_native=False)

for fut in futures:

resolve_future(fut, None)

View remainder of file in raw view

pythonnative/src/pythonnative/animated.py at main · andevsr/pythonnative · GitHub

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