reactive_dag

A domain-agnostic reactive DAG engine for Elixir/Ash apps: a dirty frontier

• depth-ordered incremental drain + change propagation, plus the coordination tuple, leaf-reconcile, and nested-expression lowering that go with it. Extracted from two apps that independently grew the same engine (the Red Hook cascade pipeline and the u2i compliance portal's model_eval), and now shared by both.

Documentation: the guides are the front door — Getting started, Authoring nodes, Sources and scanning, Attestations (human sign-off as a first-class input), and The seams. This README is the reference-style overview.

The substrate decides when and in what order cells recompute; it never decides how or what a value means. Each host brings its domain at the seams:

• ReactiveDag.RecomputeStrategy — how a cell recomputes (cascade: per-key Elixir that may call an LLM / parse a PDF; the portal: one set-based SQL join). Returns the keys that actually changed.
• ReactiveDag.KeyRule — how a change propagates to a parent (identity, a remap, or :all for a whole-cell recompute).
• ReactiveDag.CoordinationWriter — how a cell's coordination tuples are written (the host writes its spine + extension columns in one atomic upsert). A default spine-only writer ships; hosts with extension columns supply their own.

What the library owns

The host owns its physical tables (dirty + tuple, named via config), its op algebra, its recompute executor, and any extension columns on the tuple (the portal's strength modality, cascade's tombstone/fingerprint policy). The library owns the spine and the schedule; the domain differences sit on named seams, not forks.

Authoring a node

A node is an Ash resource with the ReactiveDag.Node extension. The resource IS the node and its own payload table — its reactive block is the computation, its attributes are the rows it materializes. The library closes the payload loop: into returns a row and the lib writes it into this resource — no upsert: needed for the common case.

defmodule MyApp.BudgetRollups do
  use Ash.Resource, data_layer: AshPostgres.DataLayer,   # its OWN payload table
    extensions: [ReactiveDag.Node]

  attributes do
    attribute :key, :string, primary_key?: true          # the payload columns
    attribute :fund, :string
    attribute :total, :float
  end
  actions do
    create :upsert do upsert?(true); upsert_identity(:key); accept([:key, :fund, :total]) end
  end

  reactive do
    op :fold
    key_rule :all
    # read → group_by → reduce each group to one row. `into`'s row is written into
    # THIS resource (keyed by :key) by the library; it Op.puts only changed keys.
    reduce over: :fiscal_lines,
           read:     fn :fiscal_lines -> FiscalDoc |> Ash.read!() end,
           group_by: fn line -> {line.fund, line.fy} end,
           key:      fn {fund, fy} -> "#{fund}|#{fy}" end,
           into:     fn {fund, _fy}, lines -> %{key: …, fund: fund, total: sum(lines)} end
  end
end

upsert: is an optional override — supply it only to write somewhere other than the node's own resource (e.g. an existing shadow table). A tableless node (data_layer: Ash.DataLayer.Simple, no attributes) either supplies upsert: or uses the compute Module escape hatch.

Declarative combinators cover the common shapes; each writes the result set (into the node's resource, or a custom upsert:) and Op.puts only the changed keys:

• reduce — a fold: read over into the BEAM, group, into returns one row per group. (into may instead return a list of rows — a group → many-rows "expand"; each returned row must carry its own :key. There is no separate expand entity; it's this list-returning shape of reduce.) read may be arity-2 (over, dirty_keys -> items) to scope the datastore read to the claimed keys instead of whole-cell — important for large inputs.
• join — a left join over ONE input's rows, split into left/right sides by two key fns: emit one row per left key joined to its right (right may be absent).
• aggregate — a pure-Ash-query fold: the datastore groups + aggregates a relationship (avg/sum/count/…) in ONE query — no rows cross into the BEAM. The node's resource is the group's resource (one row per group); over is its has_many. Only for relationship aggregates (Ash has no arbitrary GROUP BY … → rows); use reduce for in-BEAM folds. Example: aggregate over: :readings, avg: [flow: :avg_flow], count: :day_count.

Anything the combinators can't express — an LLM call, a PDF/Tigris fetch, a bespoke multi-input recompute — uses the module escape hatch, declared as an entity in the same block: compute MyOp where MyOp implements ReactiveDag.Op. (Mirrors Ash's calculate :x, :type, MyModule — the arbitrary case is an entity too, not a schema key beside the declarative ones.) The combinators and the escape hatch coexist in the block.

Input edges: ref (recompute) vs reference (read-as-context)

An input is one of two kinds:

• ref :x (also depends_on [:x], or a combinator's over:) — a recompute edge: when x changes, this node is dirtied and recomputes. The normal edge.
• reference :x — a reference edge: the node READS x as context but is not recomputed when x changes. It's still a real input (validated, ordered by depth so x settles first, read at recompute) — it just doesn't propagate.

Use reference when recompute is expensive/non-deterministic and consults mutable context it shouldn't be re-triggered by — e.g. an LLM step that looks up a human-curated table:

reactive do
  op :map
  compute MyApp.EnhanceMinutes   # an LLM pass
  ref :transcripts               # a transcript change RE-RUNS the LLM
  reference :people              # a people edit does NOT — the LLM just reads
                                 # current people the next time it runs
end

So an edit to a reference input updates it, but drives no regeneration; the consuming node picks up the current value whenever it next recomputes for its own (recompute-edge) reasons.

reactive do
  op :map
  compute MyApp.Ops.EventsExtract   # arbitrary recompute (LLM, fetch, …)
end

# assemble + run a Node-authored graph (no host-written dispatch):
plan = ReactiveDag.Node.graph([BudgetRollups, FiscalLines, …], for_each: &fetch/1)
{:ok, report} =
  ReactiveDag.Drain.run(plan,
    recompute: ReactiveDag.Node.Recompute,   # runs reduce/join/aggregate or compute:
    key_rule:  ReactiveDag.Node.KeyRule)       # reads :identity | :all from the block
# report is a ReactiveDag.Drain.Report — the processing trace: one step per
# recompute (cell, claimed, changed, triggered_by, duration_us) + run totals.

# config
config :reactive_dag,
  repo: MyApp.Repo,
  dirty_table: "my_dirty",
  tuple_table: "my_tuple",
  coordination_writer: MyApp.Writer   # optional; a spine-only default ships

A host can also assemble cells by hand and bring its own strategy/key_rule — ReactiveDag.Graph.build(cells) + ReactiveDag.Drain.run(plan, recompute:, key_rule:) — which is how both apps ran before adopting the Node surface.

Verdict nodes (no payload of their own)

A node whose computed result fits the coordination tuple — a status (and, if the host extends the tuple, a strength) — needs no payload table. Mark it verdict? true: its reduce/join rows carry :status/:strength, which the library writes straight into the tuple via Op.put. No data_layer, no attributes, no upsert:.

defmodule MyApp.StoreEncrypted do
  use Ash.Resource, data_layer: Ash.DataLayer.Simple, extensions: [ReactiveDag.Node]

  reactive do
    op :reconcile
    key_rule :all
    verdict? true                       # result lives in the tuple, not a table
    reduce over: :stores,
           read: …, group_by: …, key: …,
           into: fn store, [r | _] -> %{key: store, status: (if r.enc, do: "present", else: "failing")} end
  end
end

This is the "purely calculated" node: it computes a verdict per key and persists nothing beyond the coordination row. A payload-bearing node (above) computes a typed value that doesn't fit the tuple, so it materializes rows into its own resource. The line between them is exactly whether the result fits the tuple's fixed schema.

Human input

Scanners feed leaves out-of-band; a human edit (a managed list, an approval) writes a leaf too — via whatever the host uses for writes (an Ash action, a plain upsert), then marks the affected cells dirty so the drain propagates the consequences.

The library previously shipped a command frontier — a second, seq-ordered frontier for INTENTS, with per-scope serialization, a blocked/answer human-in-the-loop state, and an audit table. It was removed: in both hosts the commands turned out to be straight CRUD drained inline (enqueue immediately followed by run), so nothing was ever actually queued. The serialization it offered was already provided by the database, the audit trail is better served by a change-log on the resource, and its scope-freeze turned a failed edit into a wedged queue. A deferred/approval-gated write — where a change genuinely waits, unapplied, for a human — is the case that would justify bringing it back.

Status: both hosts run on the substrate — the shared engine spans a per-key Elixir recompute (cascade) and a set-based SQL recompute (the portal), all coordination writes routed through the seam, proven by both suites green. Cascade authors several ops via the Nodereduce/join combinators; the standalone compliance app consumes tagged releases. See ADR-001 for the boundary, the seams, and the design law behind them.