Parallel Requests Skill

Detect sequential independent HTTP/API calls and refactor them to parallel execution patterns.

When to Use

• Code has 2+ sequential await fetch(), requests.get(), axios.get(), httpx.get(), or similar
• Data aggregation from multiple independent APIs/endpoints
• Pages loading data from multiple microservices
• Batch operations that don’t depend on each other

Detection Rules

Before refactoring, verify requests are truly independent:

JS/TS Patterns

BEFORE (sequential — 3x latency)

const users = await fetch('/api/users').then(r => r.json())
const posts = await fetch('/api/posts').then(r => r.json())
const comments = await fetch('/api/comments').then(r => r.json())

AFTER (parallel — 1x latency)

const [users, posts, comments] = await Promise.all([
  fetch('/api/users').then(r => r.json()),
  fetch('/api/posts').then(r => r.json()),
  fetch('/api/comments').then(r => r.json()),
])

AFTER (with partial failure tolerance)

const results = await Promise.allSettled([
  fetch('/api/users').then(r => r.json()),
  fetch('/api/posts').then(r => r.json()),
  fetch('/api/comments').then(r => r.json()),
])
const [users, posts, comments] = results.map(r =>
  r.status === 'fulfilled' ? r.value : null
)

Python Patterns

BEFORE (synchronous — 3x latency)

users = httpx.get('/api/users').json()
posts = httpx.get('/api/posts').json()
comments = httpx.get('/api/comments').json()

AFTER (asyncio.gather)

async with httpx.AsyncClient() as client:
    users, posts, comments = await asyncio.gather(
        client.get('/api/users'),
        client.get('/api/posts'),
        client.get('/api/comments'),
    )

AFTER (Python 3.11+ TaskGroup)

async with asyncio.TaskGroup() as tg:
    users_task = tg.create_task(client.get('/api/users'))
    posts_task = tg.create_task(client.get('/api/posts'))
    comments_task = tg.create_task(client.get('/api/comments'))
users, posts, comments = users_task.result(), posts_task.result(), comments_task.result()

Other Languages — Quick Reference

See skill/patterns.md for copy-pasteable code blocks in each language.

Dependency Detection & Restructuring

When requests have dependencies, don’t blindly parallelize — restructure:

1. Response of A used in B’s URL/body — Keep sequential, but suggest: “Can these be a single batch API call?”
2. Auth token from A needed for B, C, D — Get token first, then parallelize B+C+D:

   const token = await getAuthToken()
   const [users, posts, comments] = await Promise.all([
     fetch('/api/users', { headers: { Authorization: token } }).then(r => r.json()),
     fetch('/api/posts', { headers: { Authorization: token } }).then(r => r.json()),
     fetch('/api/comments', { headers: { Authorization: token } }).then(r => r.json()),
   ])
   

3. Pagination — Sequential pages, but parallelize processing of each page’s data
4. Always ask: “Is there a batch/bulk endpoint? A GraphQL query that combines these?”

Error Handling

JS/TS — per-request retry example

const withRetry = (fn, retries = 3) =>
  fn().catch(err => retries > 0 ? withRetry(fn, retries - 1) : Promise.reject(err))

const [users, posts] = await Promise.all([
  withRetry(() => fetch('/api/users').then(r => r.json())),
  withRetry(() => fetch('/api/posts').then(r => r.json())),
])

Python — per-request retry example

async def with_retry(coro_fn, retries=3):
    for attempt in range(retries):
        try:
            return await coro_fn()
        except Exception:
            if attempt == retries - 1:
                raise

users, posts = await asyncio.gather(
    with_retry(lambda: client.get('/api/users')),
    with_retry(lambda: client.get('/api/posts')),
)

Concurrency Control

For 10+ parallel requests, limit concurrency to avoid overwhelming the server:

JS/TS — p-limit

import pLimit from 'p-limit'

const limit = pLimit(5)
const results = await Promise.all(
  urls.map(url => limit(() => fetch(url).then(r => r.json())))
)

JS/TS — chunked processing

function chunk<T>(arr: T[], size: number): T[][] {
  return Array.from({ length: Math.ceil(arr.length / size) }, (_, i) =>
    arr.slice(i * size, i * size + size)
  )
}

const results = []
for (const batch of chunk(urls, 5)) {
  const batchResults = await Promise.all(
    batch.map(url => fetch(url).then(r => r.json()))
  )
  results.push(...batchResults)
}

Python — Semaphore

sem = asyncio.Semaphore(5)

async def limited_get(client, url):
    async with sem:
        return await client.get(url)

results = await asyncio.gather(
    *(limited_get(client, url) for url in urls)
)

Anti-patterns

• Don’t parallelize ordered side effects — POST /create then PUT /update must stay sequential
• Don’t Promise.all unbounded arrays without concurrency limit — you’ll DDoS yourself
• Don’t ignore errors — use allSettled or try/catch per request
• Don’t parallelize inside loops where iteration N depends on N-1 — e.g., cursor-based pagination
• Don’t parallelize requests that share mutable state — race conditions are worse than slow code