collect-all-results-into-a-list

description: Use Stream.runCollect to execute a stream and collect all its emitted values into a Chunk. globs: "**/*.ts" alwaysApply: true

Collect All Results into a List

Rule: Use Stream.runCollect to execute a stream and collect all its emitted values into a Chunk.

Example

This example creates a stream of numbers, filters for only the even ones, transforms them into strings, and then uses runCollect to gather the final results into a Chunk.

import { Effect, Stream, Chunk } from "effect";

const program = Stream.range(1, 10).pipe(
  // Find all the even numbers
  Stream.filter((n) => n % 2 === 0),
  // Transform them into strings
  Stream.map((n) => `Even number: ${n}`),
  // Run the stream and collect the results
  Stream.runCollect
);

const programWithLogging = Effect.gen(function* () {
  const results = yield* program;
  yield* Effect.log(
    `Collected results: ${JSON.stringify(Chunk.toArray(results))}`
  );
  return results;
});

Effect.runPromise(programWithLogging);
/*
Output:
Collected results: [
  'Even number: 2',
  'Even number: 4',
  'Even number: 6',
  'Even number: 8',
  'Even number: 10'
]
*/

Explanation:
A "sink" is a terminal operator that consumes a stream and produces a final Effect. Stream.runCollect is the most fundamental sink. It provides the bridge from the lazy, pull-based world of Stream back to the familiar world of a single Effect that resolves with a standard data structure.

Using Stream.runCollect is essential when:

1. You Need the Final Result: The goal of your pipeline is to produce a complete list of transformed items that you need to use in a subsequent step (e.g., to return as a single JSON array from an API).
2. Simplicity is Key: It's the most straightforward way to "run" a stream and see its output. It declaratively states your intent: "execute this entire pipeline and give me all the results."
3. The Dataset is Bounded: It's designed for streams where the total number of items is known to be finite and small enough to fit comfortably in memory.