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A running flow threads a single state object - the token - through every node in the graph. Nodes read values from the token and write values back to it. The most important part of the token is a string-keyed map called assigns; it is the primary way nodes share data.

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Assigns

An assign is a named value held on the token. Assigns are how downstream nodes see what earlier nodes produced. Typical patterns:
  • A step that fetches employees from a source system writes the list to an assign named employees.
  • A later node reads that assign, iterates over it, and writes a transformed list to outgoing_employees.
  • A final step reads outgoing_employees and sends it to the target system.
Several nodes exist specifically for managing assigns:
  • Assign Read reads one assign and exposes its value on an output port.
  • Assign Put writes a value coming in on an input port to a named assign.
  • FlowAssign writes a single resolved value to an assign as its own step.
  • FlowCompose builds a struct payload from per-field mapping specs and stores it under an assign.
  • FlowDefault falls back to a computed value when an assign is nil or missing.
Assign Read and Assign Put only make sense inside an inner Data Engine graph - the kind embedded in a FlowTransform, FlowFilter, or FlowSwitch - because they move a value between a port and an assign, and ports only carry individual values in Data Engine mode. At a flow’s top level (flow mode), ports carry the token from one node to the next rather than individual values, so there is nothing on a port for these two to read from or write to. FlowAssign, FlowCompose, and FlowDefault are the flow-level counterparts: they run as flow nodes and write straight to the token’s assigns. Assign names are free-form strings. Choosing consistent names across a flow is important; the editor shows which assigns are written by which nodes, and the run log refers to them by name.

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Pipeline steps

A step is a named unit of work - an operation that reaches out to a source or target system, runs a calculation, or performs a side effect. The FlowAction node is how a step is invoked from a flow. A FlowAction configures:
  • The step to run. Steps are grouped by system in the picker (for example, “Fortnox: Get all projects”). Every step has a stable internal key that persists in saved flows; the display name can change without breaking existing flows.
  • The system integration the step should target, when the step talks to an external system.
  • The step’s options. Each step declares its own typed option schema, and the editor renders a form from it.
  • An on error policy. See Execution and error handling.
  • An optional cache mode, described below.
When a FlowAction runs, it invokes the step and merges the step’s results back into the token’s assigns. Which assigns a step writes is declared by the step itself, so the editor can show what will be available downstream.

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Step caching

Some steps are expensive - fetching a large list from a source system, for example. When the same step with the same inputs would be called more than once in a single run, the result can be memoised. Caching is per-run: the first invocation of a cached step populates the cache, and subsequent invocations with an equivalent cache key reuse the first result. Only the step’s assigns are cached; log entries and errors are not. Steps opt into caching by declaring a cache key. Not every step is cacheable; those that aren’t simply run again each time they are invoked. A FlowAction’s cache mode can be set to force, which bypasses the cache and forwards a signal to the step so any internal caches inside the step’s implementation can also be bypassed. This is the escape hatch for reruns that must see fresh data.

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Reading dated properties

Domain entities in Twine - Employee, Schedule, TimeReport, and so on - carry their history as dated properties. At the flow level, dated properties are read and written through dedicated assign nodes:
  • FlowAssign, FlowCompose, and FlowDefault can each read a dated property as a value source, with an optional as-of date. This is how a flow pulls a dated-property value out of an assign whose value carries that history: FlowAssign extracts a single value and names it, while FlowCompose reads several into the fields of a struct.
  • FlowDatedPropertyPut writes one dated property onto a struct held in an assign.
There is no Attribute node at the flow level. The Data Engine’s Attribute node reads dated properties too, but it only runs inside an inner Data Engine graph - for instance inside a FlowTransform or FlowFilter iterating a list, where the current item is the subject it reads from.