# lazily
Lazy reactive primitives for Rust — Context, Slots, Cells with automatic dependency tracking and cache invalidation.
[](https://crates.io/crates/lazily)
## Overview
`lazily` provides five core primitives for reactive computation:
- **Context** — owns all reactive state and manages the dependency graph
- **Slot** — a lazily-computed cached value that automatically tracks dependencies
- **Cell** — a mutable value that invalidates dependent Slots when changed
- **Signal** — an eager derived value that recomputes the instant a dependency invalidates, with no intermediate unset value
- **Effect** — a side-effect callback that automatically reruns after tracked dependencies invalidate
Values are **lazy by default**: dependents are marked dirty on invalidation but only validated or recomputed when accessed. When you need eager push-style semantics — recompute immediately, observe `v1 -> v2` with no unset window — reach for **`Signal`**, which layers a puller effect over a memoized slot. The `Slot -> Cell -> Signal` progression lets you choose lazy or eager per derived value within one graph.
`ctx.memo()` Slots use a memo guard: if recomputation produces the same value, downstream dirty caches and effects are left alone.
Multiple updates can be grouped with `ctx.batch(...)` so invalidation and effect reruns happen once after the outermost batch exits.
## Feature Set
The full `lazily` capability set and its cross-language coverage across every
binding. Legend: ✅ shipped · `~` partial · `—` absent or not applicable. The
canonical matrix with per-cell notes and platform carve-outs lives in
[`lazily-spec` § Cross-Language Coverage](../lazily-spec/docs/coverage.md).
<!-- coverage-table:start -->
| Feature | Rust | Python | Kotlin | JS | Dart | Zig | Go | C++ |
| --------- | :----: | :------: | :------: | :--: | :----: | :---: | :--: | :---: |
| Reactive graph — `Cell` / `Slot` / `Signal` / `Effect` / memo / batch | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
| Thread-safe context (lock-backed) | ✅ | ✅ | ✅ | — | — | ✅ | ✅ | ✅ |
| Async reactive context | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
| Flat state machine | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
| Harel state charts | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
| Keyed cell collections (`CellMap` / `CellTree`) + reconcile | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
| Memoized semantic tree (`SemTree`) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
| Stable-id alignment (manufactured identity) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
| Reactive queue (`QueueCell` SPSC/MPSC + `QueueStorage` adapter) | ✅ | — | — | — | — | — | — | — |
| Free-text character CRDT (`TextCrdt`) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
| `TextCrdt` delta sync (`version_vector` / `delta_since` / `apply_delta`) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
| Move-aware sequence CRDT (`SeqCrdt`) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
| Lossless tree CRDT core (`LosslessTreeCrdt`, M1) | ✅ | ✅ | ✅ | ✅ | ✅ | — | ✅ | ✅ |
| Lossless tree — dotted-frontier anti-entropy | ✅ | ✅ | ✅ | ✅ | ✅ | — | ✅ | ✅ |
| Lossless tree — concurrent merge convergence | ✅ | ✅ | ✅ | ✅ | ✅ | — | ✅ | ✅ |
| Registers (LWW / MV) + `PnCounter` + `CellCrdt` | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
| IPC wire — `Snapshot` + `Delta` + `CrdtSync` | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
| Shared-memory blob path (`ShmBlobArena`) | ✅ | ✅ | ✅ | ~ | ~ | ✅ | ✅ | ✅ |
| Distributed CRDT plane (`CrdtPlaneRuntime` / anti-entropy) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
| Distributed plane — WebRTC transport + signaling | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
| State projection / mirror | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
| Causal receipts (`CausalReceipts` outcome projection) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
| Message-passing + RPC command plane (`command-plane-v1`) | ✅ | ✅ | ✅ | ✅ | ✅ | — | ✅ | ✅ |
| C-ABI FFI boundary | ✅ | ✅ | ✅ | — | ✅ | ✅ | ✅ | ✅ |
| Permission boundary (`PeerPermissions` / `RemoteOp`) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
| Capability negotiation (`SessionHandshake`) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
| Instrumentation / benchmarks | ✅ | ✅ | ✅ | — | ✅ | ✅ | ✅ | ✅ |
<!-- coverage-table:end -->
CRDT convergence and the wire protocol are pinned by the shared conformance fixtures
and JSON Schemas in [`lazily-spec`](../lazily-spec) and the Lean models in
[`lazily-formal`](../lazily-formal).
## Development
**Minimum supported Rust version (MSRV): 1.88** — declared via `rust-version` in `Cargo.toml`. The crate uses `let_chains` (stabilized in 1.88) pervasively.
Run the local CI-equivalent suite with:
```bash
make check
```
The Makefile also exposes focused targets such as `make test-tokio`,
`make test-loom`, `make benchmark-check`, and `make benchmark-update`.
## Usage
```rust
use lazily::Context;
let ctx = Context::new();
// Create a mutable cell
let counter = ctx.cell(0i32);
// Create a derived value (automatically tracks dependencies)
let doubled = ctx.computed(|ctx| {
let val = counter.get(ctx);
val * 2
});
assert_eq!(doubled.get(&ctx), 0);
// Mutate the cell — dependents are marked dirty (not recomputed yet)
counter.set(&ctx, 5);
// Slot recomputes lazily on next access
assert_eq!(doubled.get(&ctx), 10);
// Effects run immediately and then after tracked dependencies change
let effect = ctx.effect(move |ctx| {
println!("counter = {}", counter.get(ctx));
});
counter.set(&ctx, 6); // schedules and runs the effect once
effect.dispose(&ctx); // unsubscribes and prevents future reruns
// Batch writes coalesce invalidation and effect reruns.
ctx.batch(|ctx| {
counter.set(ctx, 7);
counter.set(ctx, 8);
});
```
### Decorator-style typed factories
`#[lazily::cell]` and `#[lazily::slot]` provide the same factory style as
`lazily-py`: the factory takes only a typed context and Lazily memoizes the
Cell/Slot handle on that context. `ctx.get(factory)` reads a memoized cell or
slot factory, and `ctx.set(cell_factory, value)` mutates a memoized cell.
This example is covered by `tests/decorator_factories.rs`.
```rust
use lazily::TypedContext;
lazily::define_schema!(CounterSchema);
type CounterContext = TypedContext<CounterSchema>;
#[lazily::cell]
fn counter(_ctx: &CounterContext) -> i32 {
0
}
#[lazily::slot]
fn doubled(ctx: &CounterContext) -> i32 {
ctx.get(counter) * 2
}
let ctx = CounterContext::new();
assert_eq!(ctx.get(doubled), 0);
ctx.set(counter, 5);
assert_eq!(ctx.get(doubled), 10);
```
`define_schema!` intentionally creates a concrete, uninhabited marker type for
stable Rust 2024. It is "opaque" in the everyday sense that user code should not
construct or inspect values of it; Lazily uses only the type identity to prevent
mixing handles from different context families. Rust nightly's
`#[define_opaque]` for `type Alias = impl Trait` is a separate unstable compiler
feature for hidden concrete return types, and is not needed for Lazily context
schemas.
## Why Lazy?
| | Lazy (Slots) | Eager (Signals) |
|---|---|---|
| **When does recomputation happen?** | On access (`get`) | Immediately on change |
| **Wasted work** | Zero — only compute what's read | Can compute values nobody uses |
| **Glitch-free** | By construction | Requires topological sorting |
| **Ordering** | Irrelevant — pull-based | Critical — push-based DAG walk |
| **Use case** | Request handling, data pipelines | UI rendering, real-time updates |
In a web server handling requests, you might have 50 computed values available but any given request only uses 5. With eager reactivity, all 50 recompute on every change. With lazy, only the 5 actually accessed compute.
`lazily` defaults to lazy but does not force the choice on you: derive with `ctx.computed()`/`ctx.memo()` for pull-based laziness, or `ctx.signal()` for the eager column above (UI rendering, real-time mirrors, always-materialized values). Both share the same context, dependency graph, glitch-freedom, and memo guard — pick per value.
## Core Concepts
### Context
`Context` owns all Slots and Cells. It manages the dependency graph and provides the API for creating, reading, and mutating reactive values. Think of it as the "world" for your reactive computations — in web frameworks, this maps to a request context, application scope, or component tree.
The current `Context` is intentionally single-threaded. It uses `RefCell` and
non-`Send` callback storage to keep the fast path allocation-only and mutex-free.
Create independent contexts per OS thread for local graphs, or use
`ThreadSafeContext` when one reactive graph must be shared across threads.
### Slot
A `SlotHandle<T>` wraps a compute function `Fn(&Context) -> T`. The result is cached after first access. Dependencies are discovered automatically via a thread-local tracking stack — any Slot or Cell accessed during computation becomes a dependency. `ctx.computed()` is the ergonomic name for a derived value; `ctx.slot()` is the same primitive. Use `ctx.memo()` when `T: PartialEq` and equal recomputations should suppress downstream work.
When a dependency is invalidated, the Slot marks its cached value dirty. It does **not** validate or recompute until `ctx.get()` is called again.
For `ctx.memo()` slots, if recomputation returns a value equal to the previous cache, downstream dirty Slots become fresh without recomputing, and scheduled effects that only depended on unchanged Slots skip cleanup/rerun.
**Dependencies are dynamic.** Every time a Slot recomputes, it re-discovers its dependencies from scratch. If your compute function has conditional branches that access different Cells depending on state, the dependency graph updates automatically. No stale subscriptions, no manual cleanup.
### Cell
A `CellHandle<T>` holds a mutable value. `cell.set(&ctx, value)` and `ctx.set_cell()` compare old and new values via `PartialEq` — if unchanged, no invalidation occurs. If changed, all dependent Slots are recursively marked dirty.
### Signal
A `SignalHandle<T>` is an **eager** derived value — the eager counterpart to a lazy Slot, one step further along the `Slot -> Cell -> Signal` progression. Where a Slot only marks itself dirty on invalidation and recomputes on the next read, a Signal recomputes *the instant a dependency is invalidated*, before the invalidating `set`/`set_cell`/`batch` call returns. The value is always materialized, so observers never see an intermediate unset value — a dependency change drives the value directly from `v1` to `v2`.
```rust
let n = ctx.cell(1);
let doubled = ctx.signal(|ctx| n.get(ctx) * 2); // materialized now: 2
n.set(&ctx, 5); // doubled is already 10 — eager
assert_eq!(doubled.get(&ctx), 10);
```
A Signal is **composed from existing primitives**, not a parallel engine: a memoized Slot (`ctx.memo`) supplies glitch-free, pull-based, memo-guarded recomputation, and a small puller `Effect` re-materializes that slot after every invalidation to supply the eagerness. Consequently a Signal inherits the memo guard (an equal recompute suppresses downstream work) and diamond glitch-freedom (`D = f(A, g(A))` never surfaces a mixed new-`A`/old-`g(A)` intermediate), and batched writes settle to one consistent recomputation at batch exit.
`ctx.signal()` requires `T: PartialEq + 'static` (the memo guard); `get_signal` additionally requires `T: Clone`. `signal.dispose(&ctx)` removes the eager puller — the value stays readable but reverts to lazy (recompute-on-read) behavior. The same primitive is available on `ThreadSafeContext` (`signal`, returning a `Send + Sync` `ThreadSafeSignalHandle<T>`) and `AsyncContext` (`signal_async`, with a non-blocking `get_signal` snapshot and an awaiting `get_signal_async`); see `SPEC.md` for the per-context type bounds and the async eagerness caveat.
### Batch Updates
`ctx.batch(|ctx| { ... })` groups multiple cell updates and explicit slot/cell clears into one invalidation pass. Nested batches flush only when the outermost batch exits. Direct `ctx.get_cell()` reads inside the callback see the latest cell value immediately; changed-cell dependents are marked dirty after the batch, so Slot reads during the callback return their pre-batch cached value until the batch completes.
### Effect
An `EffectHandle` represents a side-effect callback registered with `ctx.effect()`. Effects run immediately, track any Slots or Cells read during that run, and rerun after those dependencies invalidate. Scheduled effect reruns are flushed after the invalidation pass, so diamond dependency paths coalesce to one rerun. Effects scheduled only by dirty Slot dependencies first validate those Slots and skip cleanup/rerun when values are unchanged.
Effects can return a cleanup closure. Cleanup runs before the next rerun and when the handle is disposed:
```rust
let effect = ctx.effect(move |ctx| {
let value = counter.get(ctx);
move || println!("cleanup for {value}")
});
effect.dispose(&ctx);
```
## API
| Method | Purpose |
|--------|---------|
| `Context::new()` | Create a new context |
| `lazily::define_schema!(Name)` | Define an uninhabited schema marker for `TypedContext<Name>` |
| `ctx.computed(\|ctx\| T)` | Create a derived lazily-computed value |
| `ctx.slot(\|ctx\| T)` | Create a lazily-computed slot; synonym of `ctx.computed()` |
| `ctx.memo(\|ctx\| T)` | Create a lazily-computed slot with a `PartialEq` memoization guard |
| `ctx.memoized_slot::<Key, T, _>(\|ctx\| T)` | Return a context-local factory slot handle, creating it on first use |
| `slot.get(&ctx)` | Get value (computes if unset) |
| `ctx.get(&slot)` | Context method alias for `slot.get(&ctx)` |
| `ctx.cell(value)` | Create a mutable cell |
| `ctx.memoized_cell::<Key, T, _>(\|ctx\| T)` | Return a context-local factory cell handle, creating it on first use |
| `cell.get(&ctx)` | Get cell value |
| `ctx.get_cell(&cell)` | Context method alias for `cell.get(&ctx)` |
| `ctx.set_cell(&cell, value)` | Update cell (marks dependents dirty if changed) |
| `cell.set(&ctx, value)` | Handle method alias for `ctx.set_cell(&cell, value)` |
| `#[lazily::slot] fn name(ctx: &TypedContext<_>) -> T` | Decorator-style typed slot factory over `TypedContext` |
| `#[lazily::cell] fn name(ctx: &TypedContext<_>) -> T` | Decorator-style typed cell factory over `TypedContext` |
| `ctx.signal(\|ctx\| T)` | Create an eager derived value (recomputes on invalidation, no unset window); `T: PartialEq + 'static` |
| `signal.get(&ctx)` | Get the signal's value (`T: Clone`); also `ctx.get_signal(&signal)` |
| `signal.dispose(&ctx)` | Remove the eager puller; value reverts to lazy recompute-on-read |
| `signal.is_active(&ctx)` | Check whether the eager puller is still registered |
| `ctx.batch(\|ctx\| { ... })` | Defer changed-cell dirty marking and explicit clears until the outermost batch exits |
| `ctx.effect(\|ctx\| { ... })` | Run an effect immediately and rerun it after tracked dependencies invalidate |
| `ctx.is_set(&slot)` | Check if slot has a cached, fresh value |
| `slot.clear(&ctx)` | Clear cached value and cascade to dependents |
| `cell.clear_dependents(&ctx)` | Clear downstream slots without changing cell value |
| `effect.dispose(&ctx)` | Dispose an effect and unsubscribe dependencies |
| `effect.is_active(&ctx)` | Check whether an effect is still registered |
### ThreadSafeContext
Enable the `thread-safe` feature (v0.18.0+, was default before):
```bash
cargo test --features thread-safe
```
`ThreadSafeContext` is the mutex-backed counterpart for sharing one reactive
graph across OS threads. It mirrors the core `Context` methods while requiring
`Send + Sync + 'static` values and compute/effect callbacks. The graph lock is
released before user compute callbacks, effect callbacks, or cleanup closures
run, so callbacks can re-enter the same context without deadlocking. If a slot
is invalidated while its callback is running, the stale result is discarded and
the getter retries before returning a fresh value.
## Design
- **Lazy by default, eager on demand:** Slots mark dirty on invalidation and validate/recompute on access; `ctx.signal()` opts a value into eager recomputation (a memo-slot + puller-effect composition) with no intermediate unset state
- **Ergonomic aliases:** `ctx.computed()` names derived values while preserving `ctx.slot()` for low-level terminology
- **PartialEq guard:** `CellHandle::set()` only invalidates when value actually changes
- **Memo guard:** Dirty `ctx.memo()` Slots compare recomputed values and suppress downstream recomputation/effect reruns when values are equal
- **Dynamic dependencies:** Edges re-discovered on each recomputation (no stale subscriptions)
- **Batching:** Multiple writes share one invalidation/effect flush boundary
- **Effect scheduling:** Effects rerun after dependency invalidation and coalesce duplicate schedules
- Slot-id-indexed contiguous node storage for the single-threaded fast path
- Interior mutability via `RefCell` (single-threaded)
- Thread-local tracking stack for automatic dependency discovery
- Zero mandatory runtime dependencies in the default library surface
- Optional `instrumentation` feature for benchmark counters, lock timing, and thread-safe lock attribution
## Threading Roadmap
`lazily-rs` guarantees local, single-threaded `Context` graphs plus an explicit
`ThreadSafeContext` for shared graphs. `SlotHandle<T>` and `CellHandle<T>` are
`Send + Sync` when `T` is `Send + Sync`, and `EffectHandle` is also `Send + Sync`,
but handles must be used with their owning context.
Enable the optional `loom` feature to run the thread-safe synchronization model:
```bash
cargo test --features loom --test thread_safe_loom
```
Enable the optional `tokio` feature for sync-on-Tokio integration tests and the
`tokio_sync` example (requires `thread-safe` since v0.18.0 — the integration
exercises `ThreadSafeContext` through `tokio::spawn`):
```bash
cargo test --features "tokio thread-safe"
cargo run --example tokio_sync --features "tokio thread-safe"
```
The feature proves `ThreadSafeContext` can be shared through `tokio::spawn` and
`tokio::task::spawn_blocking`. It does not add async computations or effects;
those need the separate `AsyncContext` design captured in `SPEC.md`, including
in-flight future deduplication, stale completion handling, cleanup ordering, and
separate `Send` versus `LocalSet` surfaces.
`ThreadSafeContext` intentionally keeps one mutex-backed graph lock while
fresh cached slot reads use a per-slot read-mostly cached-value sidecar.
Dependency edges, dirty/revision state, cached-value publication, batching, and
effect queues still mutate under the graph mutex. In-flight recompute waiters
use per-slot generation `Condvar` sidecars so they can park while the compute
owner runs user code, and a completion only wakes waiters for that finished
slot. Per-slot dependency summaries let cell-only dirty refreshes claim the
SlotId-partitioned recompute sidecar and skip the graph-locked `get_refresh`
dependency scan before the final publish mutation. Changed-cell and slot-value
invalidation build an explicit frontier plan, then apply dirty flags, revisions,
and effect scheduling in one graph-mutex mutation boundary; slot-only
changed-cell frontiers may publish dirty state through per-node sidecars with
cache-revision dirty epochs instead. The `thread_safe_graph_propagation` benchmarks
compare fan-out eager validation, fan-out/fan-in lazy dirty epoch publication,
and fan-in batched flush behavior with lock attribution, effect queue pushes,
dependency-edge counters, sidecar dirty marks, sidecar fallbacks, and dirty
epoch advances. Sharded-lock or CAS variants should wait for lock wait/hold
benchmark evidence and a Loom or Shuttle safety model for stale in-flight
completion, invalidation during compute, dynamic dependency cleanup/disposal,
effect scheduling/disposal, and re-entrant callbacks. A lock-free versioned
optimistic read path is deferred
until cached values can be retained independently of graph-protected
erased-value storage.
## Benchmarks
See [BENCHMARKS.md](BENCHMARKS.md) for full benchmark results, regression budgets, lock attribution, and instrumentation profiles.
For large-graph evidence, see the [Scale (≥1M cells)](BENCHMARKS.md#scale-1m-cells--lzscalebench) section (a criterion-tracked `scale` group): a spreadsheet-shaped graph of ~2M nodes builds in ~0.13 s and fully recomputes from cold in ~0.10 s, while a single-cell edit + bounded viewport read recomputes only the viewport (~11.5 µs / 1,000 cells, ~5,000× cheaper than a full recalc).
**Google Sheets scale (10,000,000 cells/workbook — the documented limit).** Run at the full Sheets cap, lazily builds the whole workbook in **~0.7 s**, recomputes it cold in **~0.5 s**, and still does a viewport edit in **~11 µs** (scale-independent). (Microsoft Excel's 1,048,576 × 16,384 = 17,179,869,184-cell grid is *capacity*, not populated cells — lazily's sparse arena only pays for populated cells, so the limit is populated-cells vs RAM, not the grid.)
> **A "cell count" here counts two cells per row** — the benchmark models a column of formulas `=A_i + A_{i-1}`, so each row is **one input cell `A_i` plus one formula cell**. `N` rows ⇒ `N` inputs + `N` formulas = `2N` cells, matching how a real sheet mixes value cells and formula cells. (Each formula *depends on* two inputs, but is itself a single cell.) So "10M cells" = 5,000,000 inputs + 5,000,000 formulas.
```bash
cargo bench --features scale-bench --bench scale # default 1M (2M nodes)
LAZILY_SCALE_N=5000000 cargo bench --features scale-bench --bench scale # Google Sheets 10M cells
```
## Multi-Language
lazily is implemented across three languages with shared semantics:
| | [lazily-rs](https://crates.io/crates/lazily) | [lazily-zig](https://github.com/btakita/lazily-zig) | [lazily-py](https://github.com/btakita/lazily-py) |
|---|---|---|---|
| Context | Owned `Context` struct | Explicit allocator | Plain `dict` |
| Slot creation | `Box<dyn Fn>` closures | `comptime` function pointers | Lambdas |
| Cell equality | `PartialEq` trait | `std.meta.eql` | `!=` operator |
| Thread safety | Single-threaded `Context`; explicit `ThreadSafeContext` | Mutex by default | GIL |
| Storage | Unified generics | `.direct` / `.indirect` | Object identity |
## Cross-Channel Compatibility
The cross-language family should use one graph-state protocol across channels:
`IpcMessage::Snapshot` and `IpcMessage::Delta`. Rust FFI is viable as a narrow
C ABI adapter with opaque handles and owned byte buffers, not by sharing live
Rust contexts, closures, typed handles, or references across the ABI.
IPC, WebSocket frames, WebRTC data channels, and FFI byte buffers can then carry
the same permission-filtered snapshots and deltas. Transport code owns framing,
memory ownership, reliability, and back-pressure; lazily semantics stay in the
shared message schema.
Enable the `ffi` feature for the C ABI adapter. It exposes an opaque
`LazilyFfiChannel`, JSON `IpcMessage` validation/classification helpers, and
Rust-owned `LazilyFfiBytes` buffers with an explicit free function. The adapter
re-encodes every accepted frame as canonical `IpcMessage` JSON, so FFI callers
share the same state plane as other channels.
## Related
- [lazily-spec](https://github.com/lazily-hub/lazily-spec) — language-agnostic wire protocol + conformance fixtures shared by every binding
- [lazily-formal](https://github.com/lazily-hub/lazily-formal) — Lean 4 formal model (flat FSM kernel, full Harel state chart, reactive graph kernel, keyed collections, ordered tree, LIS reconciliation, async slot state) with universal proofs every binding inherits
- [lazily-zig](https://github.com/btakita/lazily-zig) — Zig implementation with FFI support
- [lazily-py](https://github.com/btakita/lazily-py) — Python implementation with context-as-dict
- [Blog post: Lazily — Reactive Primitives Done Right](https://briantakita.me/posts/lazily-reactive-signals)
## License
MIT