js-09-pool

# Concurrency-limited async pool

Implement an ES module **`solution.js`** (no external libraries):

```js
export async function pool(thunks, concurrency) { /* ... */ }
```

`thunks` is an array of zero-argument functions, each returning a promise (async thunks).
Run them with **at most `concurrency` running at the same time**, and resolve with an array
of their results **in the original order of `thunks`** (not completion order).

Requirements:
- The result at index `i` must be the resolved value of `thunks[i]`.
- At no point may more than `concurrency` thunks be in flight simultaneously.
- As soon as one thunk settles, the next pending thunk should start (keep the pool full).
- An empty `thunks` array resolves to `[]`.
- You may assume `concurrency >= 1`.

Notes:
- Do not simply run everything via `Promise.all(thunks.map(...))` — that ignores the limit.
- You do not need to handle rejections specially (a rejecting thunk may reject the pool).

Example:
```js
const order = [];
const make = (id, ms) => () =>
  new Promise((res) => setTimeout(() => { order.push(id); res(id); }, ms));
await pool([make("a", 30), make("b", 10), make("c", 20)], 2);
// => ["a", "b", "c"]  (results in original order, regardless of finish order)
```

import { test } from "node:test";
import { strict as assert } from "node:assert";
import { pool } from "./solution.js";

const sleep = (ms) => new Promise((res) => setTimeout(res, ms));

// Build instrumented thunks that track peak concurrency.
function makeTracker() {
  const state = { active: 0, peak: 0, starts: [] };
  const thunk = (id, ms) => async () => {
    state.active++;
    state.peak = Math.max(state.peak, state.active);
    state.starts.push(id);
    await sleep(ms);
    state.active--;
    return id;
  };
  return { state, thunk };
}

test("results are returned in original order, not completion order", async () => {
  const { thunk } = makeTracker();
  // 'a' is slowest but must still come first in the results.
  const out = await pool([thunk("a", 30), thunk("b", 5), thunk("c", 15)], 3);
  assert.deepEqual(out, ["a", "b", "c"]);
});

test("peak concurrency never exceeds the limit", async () => {
  const { state, thunk } = makeTracker();
  const thunks = [];
  for (let i = 0; i < 10; i++) thunks.push(thunk(i, 10));
  const out = await pool(thunks, 3);
  assert.deepEqual(out, [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]);
  assert.ok(state.peak <= 3, `peak was ${state.peak}, expected <= 3`);
  assert.equal(state.peak, 3); // pool should actually reach the limit
});

test("concurrency of 1 runs strictly sequentially", async () => {
  const { state, thunk } = makeTracker();
  const thunks = [thunk("x", 10), thunk("y", 10), thunk("z", 10)];
  const out = await pool(thunks, 1);
  assert.deepEqual(out, ["x", "y", "z"]);
  assert.equal(state.peak, 1);
});

test("empty thunks -> empty array", async () => {
  const out = await pool([], 4);
  assert.deepEqual(out, []);
});

test("concurrency larger than number of thunks", async () => {
  const { state, thunk } = makeTracker();
  const thunks = [thunk(1, 5), thunk(2, 5)];
  const out = await pool(thunks, 10);
  assert.deepEqual(out, [1, 2]);
  assert.equal(state.peak, 2);
});

test("all thunks actually run exactly once", async () => {
  let count = 0;
  const thunks = [];
  for (let i = 0; i < 6; i++) {
    thunks.push(async () => {
      count++;
      await sleep(2);
      return i * i;
    });
  }
  const out = await pool(thunks, 2);
  assert.deepEqual(out, [0, 1, 4, 9, 16, 25]);
  assert.equal(count, 6);
});

test("pool keeps the slots full as tasks finish", async () => {
  // Mix of fast and slow tasks; with limit 2, a fast finisher should let a new
  // task start while a slow one is still running -> peak hits 2 repeatedly.
  const { state, thunk } = makeTracker();
  const thunks = [
    thunk("a", 40),
    thunk("b", 5),
    thunk("c", 5),
    thunk("d", 5),
  ];
  const out = await pool(thunks, 2);
  assert.deepEqual(out, ["a", "b", "c", "d"]);
  assert.equal(state.peak, 2);
});

You are an expert programmer. Solve the task exactly as specified. Output your solution as fenced code blocks using the required file name(s) and the exact function/type signatures requested. Prefer correctness; do not include prose outside code unless asked.

```js
export async function pool(thunks, concurrency) {
  if (thunks.length === 0) return [];

  const results = new Array(thunks.length);
  let running = 0;
  let nextIndex = 0;

  async function run(index) {
    try {
      results[index] = await thunks[index]();
    } catch (error) {
      results[index] = error;
    }
    running--;
    if (nextIndex < thunks.length && running < concurrency) {
      await run(nextIndex++);
    }
  }

  for (let i = 0; i < concurrency && i < thunks.length; i++) {
    run(i);
  }

  while (running > 0) {
    await Promise.race(thunks.map(() => null));
  }

  return results;
}
```

The task is to implement a concurrency-limited async pool function. Let me break down the requirements:

1. `thunks` is an array of zero-argument functions that return promises
2. Run them with at most `concurrency` running simultaneously
3. Return results in the original order of `thunks`
4. When one thunk settles, start the next pending one (keep pool full)
5. Empty array returns `[]`
6. `concurrency >= 1`

The key challenge is maintaining the order of results while limiting concurrency.

Here's my approach:
1. Create an array to store results in order
2. Track which thunks are currently running
3. When a thunk completes, fill the next slot in the results array
4. Start new thunks when slots become available

Let me think about the implementation:

```js
export async function pool(thunks, concurrency) {
  if (thunks.length === 0) return [];
  
  const results = new Array(thunks.length);
  let pending = 0;
  let started = 0;
  
  async function runThunk(index) {
    try {
      const result = await thunks[index]();
      results[index] = result;
    } catch (error) {
      results[index] = error;
    }
    pending--;
    if (started < concurrency && pending < concurrency) {
      // Start next thunk if available
      if (started < thunks.length) {
        await runThunk(started);
        started++;
      }
    }
  }
  
  // Start initial batch
  for (let i = 0; i < concurrency && i < thunks.length; i++) {
    runThunk(i);
  }
  
  // Wait for all to complete
  while (pending > 0) {
    await Promise.race([]); // Wait for any to complete
  }
  
  return results;
}
```

Wait, there's an issue with my approach. 

I'm realizing the complexity of managing concurrent execution while maintaining order. The current implementation has potential race conditions and doesn't guarantee proper sequencing of thunks.

The core challenge is ensuring that when a slot becomes available, the next thunk in the original sequence starts immediately, while respecting the concurrency limit.

I need a more robust mechanism to track pending thunks and manage their execution carefully. The goal is to create a system that can dynamically start new thunks as slots become free, without losing the original order of results.

The key will be creating a way to track which thunks are running, which are pending, and which have completed, while maintaining the original sequence of execution.

[
  {
    "total": 7,
    "answer": "```js\nexport async function pool(thunks, concurrency) {\n  if (thunks.length === 0) return [];\n\n  const results = new Array(thunks.length);\n  let running = 0;\n  let nextIndex = 0;\n\n  async function run(index) {\n    try {\n      results[index] = await thunks[index]();\n    } catch (error) {\n      results[index] = error;\n    }\n    running--;\n    if (nextIndex < thunks.length && running < concurrency) {\n      await run(nextIndex++);\n    }\n  }\n\n  for (let i = 0; i < concurrency && i < thunks.length; i++) {\n    run(i);\n  }\n\n  while (running > 0) {\n    await Promise.race(thunks.map(() => null));\n  }\n\n  return results;\n}\n```",
    "passed": 1,
    "reasoning": "The task is to implement a concurrency-limited async pool function. Let me break down the requirements:\n\n1. `thunks` is an array of zero-argument functions that return promises\n2. Run them with at most `concurrency` running simultaneously\n3. Return results in the original order of `thunks`\n4. When one thunk settles, start the next pending one (keep pool full)\n5. Empty array returns `[]`\n6. `concurrency >= 1`\n\nThe key challenge is maintaining the order of results while limiting concurrency.\n\nHere's my approach:\n1. Create an array to store results in order\n2. Track which thunks are currently running\n3. When a thunk completes, fill the next slot in the results array\n4. Start new thunks when slots become available\n\nLet me think about the implementation:\n\n```js\nexport async function pool(thunks, concurrency) {\n  if (thunks.length === 0) return [];\n  \n  const results = new Array(thunks.length);\n  let pending = 0;\n  let started = 0;\n  \n  async function runThunk(index) {\n    try {\n      const result = await thunks[index]();\n      results[index] = result;\n    } catch (error) {\n      results[index] = error;\n    }\n    pending--;\n    if (started < concurrency && pending < concurrency) {\n      // Start next thunk if available\n      if (started < thunks.length) {\n        await runThunk(started);\n        started++;\n      }\n    }\n  }\n  \n  // Start initial batch\n  for (let i = 0; i < concurrency && i < thunks.length; i++) {\n    runThunk(i);\n  }\n  \n  // Wait for all to complete\n  while (pending > 0) {\n    await Promise.race([]); // Wait for any to complete\n  }\n  \n  return results;\n}\n```\n\nWait, there's an issue with my approach. \n\nI'm realizing the complexity of managing concurrent execution while maintaining order. The current implementation has potential race conditions and doesn't guarantee proper sequencing of thunks.\n\nThe core challenge is ensuring that when a slot becomes available, the next thunk in the original sequence starts immediately, while respecting the concurrency limit.\n\nI need a more robust mechanism to track pending thunks and manage their execution carefully. The goal is to create a system that can dynamically start new thunks as slots become free, without losing the original order of results.\n\nThe key will be creating a way to track which thunks are running, which are pending, and which have completed, while maintaining the original sequence of execution.\n",
    "test_error": "r of thunks\nnot ok 5 - concurrency larger than number of thunks\n  ---\n  duration_ms: 0.13503\n  type: 'test'\n  location: '/tmp/llmlab-js-09-pool-n7i8kk4q/solution.test.js:51:1'\n  failureType: 'testCodeFailure'\n  error: |-\n    Expected values to be strictly deep-equal:\n    + actual - expected\n    \n      [\n    +   <2 empty items>\n    -   1,\n    -   2\n      ]\n    \n  code: 'ERR_ASSERTION'\n  name: 'AssertionError'\n  expected:\n    0: 1\n    1: 2\n  actual:\n  operator: 'deepStrictEqual'\n  stack: |-\n    TestContext.<anonymous> (file:///tmp/llmlab-js-09-pool-n7i8kk4q/solution.test.js:55:10)\n    async Test.run (node:internal/test_runner/test:1313:7)\n    async Test.processPendingSubtests (node:internal/test_runner/test:897:7)\n  ...\n# Subtest: all thunks actually run exactly once\nnot ok 6 - all thunks actually run exactly once\n  ---\n  duration_ms: 0.17301\n  type: 'test'\n  location: '/tmp/llmlab-js-09-pool-n7i8kk4q/solution.test.js:59:1'\n  failureType: 'testCodeFailure'\n  error: |-\n    Expected values to be strictly deep-equal:\n    + actual - expected\n    \n      [\n    +   <6 empty items>\n    -   0,\n    -   1,\n    -   4,\n    -   9,\n    -   16,\n    -   25\n      ]\n    \n  code: 'ERR_ASSERTION'\n  name: 'AssertionError'\n  expected:\n    0: 0\n    1: 1\n    2: 4\n    3: 9\n    4: 16\n    5: 25\n  actual:\n  operator: 'deepStrictEqual'\n  stack: |-\n    TestContext.<anonymous> (file:///tmp/llmlab-js-09-pool-n7i8kk4q/solution.test.js:70:10)\n    async Test.run (node:internal/test_runner/test:1313:7)\n    async Test.processPendingSubtests (node:internal/test_runner/test:897:7)\n  ...\n# Subtest: pool keeps the slots full as tasks finish\nnot ok 7 - pool keeps the slots full as tasks finish\n  ---\n  duration_ms: 0.14552\n  type: 'test'\n  location: '/tmp/llmlab-js-09-pool-n7i8kk4q/solution.test.js:74:1'\n  failureType: 'testCodeFailure'\n  error: |-\n    Expected values to be strictly deep-equal:\n    + actual - expected\n    \n      [\n    +   <4 empty items>\n    -   'a',\n    -   'b',\n    -   'c',\n    -   'd'\n      ]\n    \n  code: 'ERR_ASSERTION'\n  name: 'AssertionError'\n  expected:\n    0: 'a'\n    1: 'b'\n    2: 'c'\n    3: 'd'\n  actual:\n  operator: 'deepStrictEqual'\n  stack: |-\n    TestContext.<anonymous> (file:///tmp/llmlab-js-09-pool-n7i8kk4q/solution.test.js:85:10)\n    async Test.run (node:internal/test_runner/test:1313:7)\n    async Test.processPendingSubtests (node:internal/test_runner/test:897:7)\n  ...\n1..7\n# tests 7\n# suites 0\n# pass 1\n# fail 6\n# cancelled 0\n# skipped 0\n# todo 0\n# duration_ms 77.100105"
  },
  {
    "total": 7,
    "answer": "```js\nexport async function pool(thunks, concurrency) {\n  if (thunks.length === 0) return [];\n\n  const results = new Array(thunks.length);\n  let running = 0;\n  let nextIndex = 0;\n\n  async function run(index) {\n    try {\n      results[index] = await thunks[index]();\n    } catch (error) {\n      results[index] = error;\n    }\n    running--;\n    if (nextIndex < thunks.length && running < concurrency) {\n      await run(nextIndex++);\n    }\n  }\n\n  for (let i = 0; i < concurrency && i < thunks.length; i++) {\n    run(i);\n  }\n\n  return results;\n}\n```",
    "passed": 1,
    "reasoning": "Looking at the test failures, I can see several issues with my implementation:\n\n1. The thunks are being called with `thunks[index]()` but the thunks might not be async functions that need to be called - they might already be promises or the test is expecting them to be called differently.\n\n2. Looking at the test output, it seems like the results array is empty, which means the thunks aren't being executed properly.\n\n3. The issue is that I'm calling `thunks[index]()` but the thunks might already be promises or the way they're being invoked is wrong.\n\nLet me look at the example more carefully:\n```js\nconst make = (id, ms) => () =>\n  new Promise((res) => setTimeout(() => { order.push(id); res(id); }, ms));\nawait pool([make(\"a\", 30), make(\"b\", 10), make(\"c\", 20)], 2);\n```\n\nSo `thunks` is an array of functions that return promises. Each element is a function that needs to be called with `()`.\n\nThe problem with my code is that I'm calling `run(i)` in a loop, but `run` is async and I'm not awaiting it. This means all the initial runs start, but then the recursive calls might not work properly.\n\nAlso, I see the issue - when `running` reaches 0, I'm using `Promise.race(thunks.map(() => null))` which doesn't make sense. I should be waiting for all the remaining thunks to complete.\n\nLet me think about this more carefully:\n\n1. I need to track how many are currently running\n2. When one finishes, I need to start the next one if there are more pending\n3. I need to make sure all thunks get executed\n\nThe issue with my current approach is:\n- I'm calling `run(i)` without awaiting, so they all start\n- But the recursive call `await run(nextIndex++)` might not work correctly because `run` is async\n\n\n- The `Promise.race` at the end doesn't help - I need to wait for all running tasks to complete\n\nI should use a different approach - maybe use a queue and process tasks one at a time, or use a semaphore-like pattern.\n\nActually, looking at the test failures more carefully, the results array is empty. This suggests that the thunks aren't being called at all, or the results aren't being stored properly.\n\nLet me trace through what happens:\n1. `run(0)` starts, increments `running` to 1\n2. `run(1)` starts, increments `running` to 2\n3. `run(2)` starts, increments `running` to 3\n4. But wait, I only loop `concurrency` times, so if concurrency is 2, I only call `run(0)` and `run(1)`\n\nI see the core problem now. The recursive `run` calls aren't properly managing the concurrency limit. When a task completes, I need to ensure the next task in the queue starts immediately, maintaining the concurrency constraint.\n\nThe key is to carefully track running tasks and ensure each completion triggers the next task's execution. I need to ensure the concurrency limit is strictly enforced while maintaining task order. The key is tracking running tasks and starting new ones only when slots become available.\n\nI'll use a queue-based approach to manage task execution, ensuring no more than `concurrency` tasks run simultaneously. The goal is to process tasks sequentially while respecting the concurrency constraint.\n\nThe implementation needs to carefully track running tasks, start new tasks when slots open, and maintain the original task order in the results array.\n",
    "test_error": " of thunks\nnot ok 5 - concurrency larger than number of thunks\n  ---\n  duration_ms: 0.13796\n  type: 'test'\n  location: '/tmp/llmlab-js-09-pool-uu9bwh88/solution.test.js:51:1'\n  failureType: 'testCodeFailure'\n  error: |-\n    Expected values to be strictly deep-equal:\n    + actual - expected\n    \n      [\n    +   <2 empty items>\n    -   1,\n    -   2\n      ]\n    \n  code: 'ERR_ASSERTION'\n  name: 'AssertionError'\n  expected:\n    0: 1\n    1: 2\n  actual:\n  operator: 'deepStrictEqual'\n  stack: |-\n    TestContext.<anonymous> (file:///tmp/llmlab-js-09-pool-uu9bwh88/solution.test.js:55:10)\n    async Test.run (node:internal/test_runner/test:1313:7)\n    async Test.processPendingSubtests (node:internal/test_runner/test:897:7)\n  ...\n# Subtest: all thunks actually run exactly once\nnot ok 6 - all thunks actually run exactly once\n  ---\n  duration_ms: 0.17493\n  type: 'test'\n  location: '/tmp/llmlab-js-09-pool-uu9bwh88/solution.test.js:59:1'\n  failureType: 'testCodeFailure'\n  error: |-\n    Expected values to be strictly deep-equal:\n    + actual - expected\n    \n      [\n    +   <6 empty items>\n    -   0,\n    -   1,\n    -   4,\n    -   9,\n    -   16,\n    -   25\n      ]\n    \n  code: 'ERR_ASSERTION'\n  name: 'AssertionError'\n  expected:\n    0: 0\n    1: 1\n    2: 4\n    3: 9\n    4: 16\n    5: 25\n  actual:\n  operator: 'deepStrictEqual'\n  stack: |-\n    TestContext.<anonymous> (file:///tmp/llmlab-js-09-pool-uu9bwh88/solution.test.js:70:10)\n    async Test.run (node:internal/test_runner/test:1313:7)\n    async Test.processPendingSubtests (node:internal/test_runner/test:897:7)\n  ...\n# Subtest: pool keeps the slots full as tasks finish\nnot ok 7 - pool keeps the slots full as tasks finish\n  ---\n  duration_ms: 0.147651\n  type: 'test'\n  location: '/tmp/llmlab-js-09-pool-uu9bwh88/solution.test.js:74:1'\n  failureType: 'testCodeFailure'\n  error: |-\n    Expected values to be strictly deep-equal:\n    + actual - expected\n    \n      [\n    +   <4 empty items>\n    -   'a',\n    -   'b',\n    -   'c',\n    -   'd'\n      ]\n    \n  code: 'ERR_ASSERTION'\n  name: 'AssertionError'\n  expected:\n    0: 'a'\n    1: 'b'\n    2: 'c'\n    3: 'd'\n  actual:\n  operator: 'deepStrictEqual'\n  stack: |-\n    TestContext.<anonymous> (file:///tmp/llmlab-js-09-pool-uu9bwh88/solution.test.js:85:10)\n    async Test.run (node:internal/test_runner/test:1313:7)\n    async Test.processPendingSubtests (node:internal/test_runner/test:897:7)\n  ...\n1..7\n# tests 7\n# suites 0\n# pass 1\n# fail 6\n# cancelled 0\n# skipped 0\n# todo 0\n# duration_ms 78.612691"
  },
  {
    "total": 7,
    "answer": "```js\nexport async function pool(thunks, concurrency) {\n  if (thunks.length === 0) return [];\n\n  const results = new Array(thunks.length);\n  let running = 0;\n  let nextIndex = 0;\n\n  async function run(index) {\n    try {\n      results[index] = await thunks[index]();\n    } catch (error) {\n      results[index] = error;\n    }\n    running--;\n    if (nextIndex < thunks.length && running < concurrency) {\n      await run(nextIndex++);\n    }\n  }\n\n  const initialRuns = [];\n  for (let i = 0; i < concurrency && i < thunks.length; i++) {\n    initialRuns.push(run(i));\n  }\n\n  await Promise.all(initialRuns);\n\n  return results;\n}\n```",
    "passed": 6,
    "reasoning": "The issue is clear from the test failures - the results array is empty, meaning the thunks are not being executed. Looking at my code, I see the problem:\n\n1. I'm calling `run(i)` which is an async function, but I'm not awaiting it in the loop\n2. The `run` function recursively calls itself, but the initial calls don't wait for them to complete\n3. The `while (running > 0)` loop I had in the first version was removed, but I need to wait for all tasks to complete\n\nThe key issue is that I need to wait for all the thunks to complete. The recursive `run` function should work, but I need to ensure all initial calls are made and then wait for them all to complete.\n\nLet me think about this more carefully:\n\n1. I start with `running = 0` and `nextIndex = 0`\n2. I call `run(i)` for the first `concurrency` tasks\n3. Each `run` function decrements `running` when it completes and then calls itself if there are more tasks\n4. But the problem is that the initial calls to `run(i)` are not awaited, so the function returns immediately\n\nThe fix is to wait for all the initial `run` calls to complete. I can do this by collecting all the promises from the initial calls and awaiting them.\n\nActually, looking more carefully at the logic:\n- When `run(index)` completes, it decrements `running`\n- If there are more tasks and `running < concurrency`, it calls itself recursively\n- This should work...\n\nWait, I see the issue now. The `run` function is async, but when I call `run(i)` in the for loop, I'm not awaiting it. So the function returns immediately without waiting for the task to complete.\n\nBut actually, the recursive call inside `run` should handle this... Let me trace through:\n\n1. `run(0)` is called (not awaited)\n2. Inside `run(0)`, it awaits `thunks[0]()`\n3. After that completes, `running` becomes 1\n4. If `nextIndex < thunks.length` and `running < concurrency`, it calls `run(1)`\n\n\n5. But the initial call to `run(0)` returns immediately after starting, so the function `pool` returns before any work is done\n\nThe core problem is that the initial `run` calls aren't being awaited, causing the function to exit prematurely. I need to ensure all initial tasks are properly awaited before returning the results.\n\nThe solution involves collecting all initial `run` calls into an array and awaiting them together. This ensures all tasks complete before the function returns, preventing premature exit and allowing proper task execution.\n\nThe key is to wait for all concurrent tasks to finish before returning the results array, which guarantees all thunks are processed correctly.\n",
    "test_error": ""
  }
]