pythonnative/src/pythonnative/animated.py at refs/heads/main · pythonnative/pythonnative · GitHub

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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. Awaiting yields an

[`AnimationResult`][pythonnative.animated.AnimationResult] whose

``finished`` flag is ``False`` when the animation was stopped or

interrupted; ``handle.start(callback)`` passes the same value.

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

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

awaitable. A composite is ``finished`` only if every child finished.

- [`Easing`][pythonnative.animated.Easing]: serializable easing

descriptors for ``Animated.timing`` (``Easing.ease_in_out``,

``Easing.bezier(0.2, 0.8, 0.2, 1.0)``, ...). Every renderer evaluates

the same curve definitions; a plain Python callable is still accepted

but ticks in Python.

- ``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**):

Mounted bindings install a serialized graph of connected values, arithmetic,

interpolation, and view properties. When an animation starts, PythonNative

offers its timing, spring, or decay specification to the renderer through

the backend's ``start_animation`` hook (see

[`BridgeBackend`][pythonnative.native_views.bridge_backend.BridgeBackend]).

- **Accepted**: the renderer evaluates the graph and applies its bindings

without Python work on every frame. Completion callbacks settle the

[`AnimatedValue`][pythonnative.animated.AnimatedValue] and resolve

awaiting tasks.

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

values feeding Python-side listeners, or an unsupported backend): 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.

On mobile, scroll and gesture bindings feed graph values before input is

queued to Python. Derived expressions can run in the renderer alongside their

source drivers. Backends without graph support use Python for derived bindings.

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 functools

import itertools

import math

import threading

import time

import weakref

from dataclasses import dataclass

from typing import Any, Callable, Dict, FrozenSet, Generator, List, Mapping, Optional, Sequence, Tuple, Union, cast

from .element import Element

from .hooks import Ref, use_effect, use_ref

from .runtime import resolve_future

from .style import Style, 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

# Velocity (points per millisecond) below which a decay animation is at

# rest. React Native's ``DecayAnimation`` stops when a frame moves the

# value by less than 0.1 points; at 60 Hz that is about 0.006 pt/ms. We

# use the tighter 0.001 pt/ms so the tail of a fling is never clipped

# visibly, and every native decay driver shares this constant.

DECAY_REST_VELOCITY = 0.001

# React Native's default ``deceleration`` for ``Animated.decay``.

DEFAULT_DECAY_DECELERATION = 0.998

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

# Easing

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

_BEZIER_EPSILON = 1e-7

_BEZIER_NEWTON_ITERATIONS = 8

_BEZIER_BISECTION_ITERATIONS = 40

def _bezier_component(t: float, p1: float, p2: float) -> float:

"""Evaluate one axis of a cubic bezier anchored at ``0`` and ``1``."""

inv = 1.0 - t

return 3.0 * inv * inv * t * p1 + 3.0 * inv * t * t * p2 + t * t * t

def _bezier_slope(t: float, p1: float, p2: float) -> float:

"""Derivative of ``_bezier_component`` with respect to ``t``."""

inv = 1.0 - t

return 3.0 * inv * inv * p1 + 6.0 * inv * t * (p2 - p1) + 3.0 * t * t * (1.0 - p2)

@functools.lru_cache(maxsize=64)

def _bezier_function(x1: float, y1: float, x2: float, y2: float) -> Callable[[float], float]:

"""Build a ``progress -> eased`` function for a CSS-style cubic bezier.

The curve is parametric, so evaluating it at a given horizontal

``progress`` means solving ``bezier_x(t) = progress`` for ``t`` first.

Newton-Raphson from a linear guess converges in a handful of steps

for well-behaved curves; when the slope is too flat for Newton to be

trusted, bisection on ``[0, 1]`` finishes the job.

"""

if x1 == y1 and x2 == y2:

return lambda progress: min(1.0, max(0.0, progress))

def solve_t(x: float) -> float:

t = x

for _ in range(_BEZIER_NEWTON_ITERATIONS):

error = _bezier_component(t, x1, x2) - x

if abs(error) < _BEZIER_EPSILON:

return t

slope = _bezier_slope(t, x1, x2)

if abs(slope) < 1e-6:

break

t -= error / slope

lo, hi = 0.0, 1.0

for _ in range(_BEZIER_BISECTION_ITERATIONS):

t = (lo + hi) / 2.0

if _bezier_component(t, x1, x2) < x:

lo = t

else:

hi = t

if hi - lo < _BEZIER_EPSILON:

break

return t

def evaluate(progress: float) -> float:

if progress <= 0.0:

return 0.0

if progress >= 1.0:

return 1.0

return _bezier_component(solve_t(progress), y1, y2)

return evaluate

def _bounce(t: float) -> float:

"""Robert Penner's bounce-out, the curve React Native ships as ``Easing.bounce``."""

if t < 1 / 2.75:

return 7.5625 * t * t

if t < 2 / 2.75:

t -= 1.5 / 2.75

return 7.5625 * t * t + 0.75

if t < 2.5 / 2.75:

t -= 2.25 / 2.75

return 7.5625 * t * t + 0.9375

t -= 2.625 / 2.75

return 7.5625 * t * t + 0.984375

# Canonical definitions of the named easings. Every renderer (the Python

# ticker, Swift, Kotlin, and the browser preview) implements exactly these

# curves under these names; they follow React Native's ``Easing`` module,

# where ``ease`` is ``bezier(0.42, 0, 1, 1)`` and ``ease_in`` /

# ``ease_out`` / ``ease_in_out`` are ``Easing.in`` / ``out`` / ``inOut``

# of it, which coincide with the CSS ``ease-in`` / ``ease-out`` /

# ``ease-in-out`` keywords.

_NAMED_EASING_BEZIERS: Dict[str, Tuple[float, float, float, float]] = {

"ease": (0.42, 0.0, 1.0, 1.0),

"ease_in": (0.42, 0.0, 1.0, 1.0),

"ease_out": (0.0, 0.0, 0.58, 1.0),

"ease_in_out": (0.42, 0.0, 0.58, 1.0),

}

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

"linear": lambda t: t,

"ease": _bezier_function(*_NAMED_EASING_BEZIERS["ease"]),

"ease_in": _bezier_function(*_NAMED_EASING_BEZIERS["ease_in"]),

"ease_out": _bezier_function(*_NAMED_EASING_BEZIERS["ease_out"]),

"ease_in_out": _bezier_function(*_NAMED_EASING_BEZIERS["ease_in_out"]),

"quad": lambda t: t * t,

"cubic": lambda t: t * t * t,

"bounce": _bounce,

}

EASING_NAMES: Tuple[str, ...] = tuple(_NAMED_EASING_FUNCTIONS)

"""The easing names ``Animated.timing`` accepts as strings."""

@dataclass(frozen=True)

class EasingSpec:

"""A serializable easing curve for ``Animated.timing``.

Build instances through the [`Easing`][pythonnative.animated.Easing]

namespace (``Easing.ease_in_out``, ``Easing.bezier(...)``) rather

than directly. The descriptor crosses the bridge as data, so the

native drivers can run the curve on the UI thread, and it evaluates

identically in Python for the fallback ticker and for tests.

Attributes:

name: One of the named curves (``"linear"``, ``"ease"``,

``"ease_in"``, ``"ease_out"``, ``"ease_in_out"``,

``"quad"``, ``"cubic"``, ``"bounce"``) or ``"bezier"``.

points: The ``(x1, y1, x2, y2)`` control points when ``name`` is

``"bezier"``; ``None`` otherwise.

"""

name: str

points: Optional[Tuple[float, float, float, float]] = None

def __post_init__(self) -> None:

if self.name == "bezier":

if self.points is None or len(self.points) != 4:

raise ValueError("Easing.bezier() needs exactly four control-point coordinates")

x1, _y1, x2, _y2 = self.points

if not (0.0 <= x1 <= 1.0 and 0.0 <= x2 <= 1.0):

raise ValueError("Easing.bezier() x control points must lie within [0, 1]")

elif self.name not in _NAMED_EASING_FUNCTIONS:

raise ValueError(f"Unknown easing {self.name!r}; expected one of {', '.join(EASING_NAMES)} or 'bezier'")

elif self.points is not None:

raise ValueError(f"Easing {self.name!r} does not take control points")

def evaluate(self, progress: float) -> float:

"""Return the eased value for ``progress`` in ``[0, 1]``."""

return _easing_function(self)(progress)

def to_wire(self) -> Any:

"""Return the bridge representation: the name, or ``[x1, y1, x2, y2]`` for a bezier."""

if self.name == "bezier":

assert self.points is not None

return [float(p) for p in self.points]

return self.name

def __repr__(self) -> str:

if self.name == "bezier":

return f"Easing.bezier{self.points}"

return f"Easing.{self.name}"

class _EasingNamespace:

"""Public ``Easing`` namespace: named curves plus ``bezier(...)``.

Mirrors React Native's ``Easing`` module. Each attribute is a frozen

[`EasingSpec`][pythonnative.animated.EasingSpec]:

| Name | Curve |

| --- | --- |

| ``linear`` | ``t`` |

| ``ease`` | ``bezier(0.42, 0, 1, 1)`` |

| ``ease_in`` | ``bezier(0.42, 0, 1, 1)`` (CSS ``ease-in``) |

| ``ease_out`` | ``bezier(0, 0, 0.58, 1)`` (CSS ``ease-out``) |

| ``ease_in_out`` | ``bezier(0.42, 0, 0.58, 1)`` (CSS ``ease-in-out``) |

| ``quad`` | ``t * t`` |

| ``cubic`` | ``t * t * t`` |

| ``bounce`` | Penner bounce-out |

``Animated.timing(easing=...)`` also accepts these names as plain

strings; any other string raises ``ValueError``.

Example:

```python

pn.Animated.timing(opacity, to=1.0, easing=pn.Easing.ease_out)

pn.Animated.timing(x, to=200, easing=pn.Easing.bezier(0.2, 0.8, 0.2, 1.0))

```

"""

linear = EasingSpec("linear")

ease = EasingSpec("ease")

ease_in = EasingSpec("ease_in")

ease_out = EasingSpec("ease_out")

ease_in_out = EasingSpec("ease_in_out")

quad = EasingSpec("quad")

cubic = EasingSpec("cubic")

bounce = EasingSpec("bounce")

@staticmethod

def bezier(x1: float, y1: float, x2: float, y2: float) -> EasingSpec:

"""Return a cubic-bezier easing with the CSS ``cubic-bezier(x1, y1, x2, y2)`` control points.

``x1`` and ``x2`` must lie in ``[0, 1]``; ``y1`` and ``y2`` may

overshoot for anticipation or bounce effects.

"""

return EasingSpec("bezier", (float(x1), float(y1), float(x2), float(y2)))

Easing = _EasingNamespace()

EasingLike = Union[EasingSpec, str, Callable[[float], float]]

"""What ``Animated.timing(easing=...)`` accepts."""

def _resolve_easing(easing: Any) -> Union[EasingSpec, Callable[[float], float]]:

"""Normalize an ``easing`` argument to an ``EasingSpec`` or a Python callable.

Raises:

ValueError: For a string that is not one of ``EASING_NAMES``.

TypeError: For anything that is not a spec, a name, or a callable.

"""

if isinstance(easing, EasingSpec):

return easing

if isinstance(easing, str):

if easing in _NAMED_EASING_FUNCTIONS:

return EasingSpec(easing)

raise ValueError(

f"Unknown easing {easing!r}; expected one of {', '.join(EASING_NAMES)}, "

"an Easing.* descriptor, or a callable"

)

if callable(easing):

return easing

raise TypeError(f"easing must be an Easing descriptor, a name, or a callable (got {type(easing).__name__})")

def _easing_function(easing: Union[EasingSpec, Callable[[float], float]]) -> Callable[[float], float]:

"""Return the ``progress -> eased`` callable for a resolved easing."""

if isinstance(easing, EasingSpec):

if easing.name == "bezier":

assert easing.points is not None

return _bezier_function(*easing.points)

return _NAMED_EASING_FUNCTIONS[easing.name]

return easing

def _backend() -> Any:

"""Return the active view backend (the animation backend), or ``None`` off device.

Headless code that never installed a backend (plain ``AnimatedValue``

arithmetic in a unit test) still works: every caller treats ``None``

as "no renderer to push to."

"""

from .native_views import get_backend

try:

return get_backend()

except Exception:

return None

# 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, push_native: bool = True) -> None:

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

Args:

push_native: When ``False`` the renderer already shows this

frame (a native-evaluated graph sample), so only Python

state, listeners, and dependents are updated.

"""

self._refresh()

current = self.value

with self._lock:

subs = list(self._subscribers)

attachments = list(self._attachments)

children = list(self._children)

if push_native and attachments:

backend = _backend()

if backend is not None:

try:

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(push_native)

# -- 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)

backend = _backend()

if backend is not None:

try:

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

except Exception:

pass

from .animation_graph import install

install(self)

def _detach() -> None:

with self._lock:

try:

self._attachments.remove(binding)

except ValueError:

pass

install(self, detached_tag=tag)

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)

from .animation_graph import install

graph = install(self)

if graph and graph["bindings"]:

backend = _backend()

if backend is not None:

backend.set_animated_property(graph["bindings"][0][0], f"_pn_graph:{id(self)}", float(new_value))

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:

backend = _backend()

if backend is not None:

try:

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(push_native)

# -- 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:

sample = float(raw)

except (TypeError, ValueError):

continue

if getattr(_backend(), "install_animation_graph", None) is not None: # None backend: plain set

# The renderer evaluated the installed graph at the input

# timestamp, so this frame is already on screen. Update the

# Python cell, its listeners, and stateful dependents such

# as ``diff_clamp`` without echoing an older frame back.

node._apply(sample, push_native=False)

else:

node.set_value(sample)

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:

View remainder of file in raw view

pythonnative/src/pythonnative/animated.py at refs/heads/main · pythonnative/pythonnative · GitHub

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