apify-local-dev-loop
Set up local Apify Actor development with Apify CLI and Crawlee. Use when creating Actors locally, testing with apify run, or establishing a fast develop-test-deploy cycle. Trigger: "apify dev setup", "apify local development", "develop actor locally", "apify run local".
Best use case
apify-local-dev-loop is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Set up local Apify Actor development with Apify CLI and Crawlee. Use when creating Actors locally, testing with apify run, or establishing a fast develop-test-deploy cycle. Trigger: "apify dev setup", "apify local development", "develop actor locally", "apify run local".
Teams using apify-local-dev-loop should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/apify-local-dev-loop/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How apify-local-dev-loop Compares
| Feature / Agent | apify-local-dev-loop | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Set up local Apify Actor development with Apify CLI and Crawlee. Use when creating Actors locally, testing with apify run, or establishing a fast develop-test-deploy cycle. Trigger: "apify dev setup", "apify local development", "develop actor locally", "apify run local".
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
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SKILL.md Source
# Apify Local Dev Loop
## Overview
Build and test Apify Actors on your local machine before deploying to the platform. Uses the Apify CLI (`apify run`) which emulates the platform environment locally, creating local storage directories for datasets, key-value stores, and request queues.
## Prerequisites
- `npm install -g apify-cli` (global CLI)
- `apify login` completed with valid token
- Node.js 18+
## Actor Project Structure
```
my-actor/
├── .actor/
│ ├── actor.json # Actor metadata and config
│ └── INPUT_SCHEMA.json # Input schema (auto-generates UI on platform)
├── src/
│ └── main.ts # Entry point
├── storage/ # Created by apify run (git-ignored)
│ ├── datasets/default/
│ ├── key_value_stores/default/
│ └── request_queues/default/
├── package.json
└── tsconfig.json
```
## Instructions
### Step 1: Create a New Actor Project
```bash
# Create from template (interactive)
apify create my-actor
# Or create from specific template
apify create my-actor --template project_cheerio_crawler_ts
# Templates: project_empty, project_cheerio_crawler_ts,
# project_playwright_crawler_ts, project_puppeteer_crawler_ts
```
### Step 2: Configure .actor/actor.json
```json
{
"actorSpecification": 1,
"name": "my-actor",
"title": "My Actor",
"description": "Scrapes data from example.com",
"version": "0.1",
"meta": {
"templateId": "project_cheerio_crawler_ts"
},
"input": "./INPUT_SCHEMA.json",
"dockerfile": "./Dockerfile",
"storages": {
"dataset": {
"actorSpecification": 1,
"title": "Scraped items",
"views": {
"overview": {
"title": "Overview",
"transformation": { "fields": ["url", "title", "text"] },
"display": {
"component": "table",
"properties": {
"url": { "label": "URL", "format": "link" },
"title": { "label": "Title" },
"text": { "label": "Content" }
}
}
}
}
}
}
}
```
### Step 3: Define Input Schema
```json
{
"title": "My Actor Input",
"type": "object",
"schemaVersion": 1,
"properties": {
"startUrls": {
"title": "Start URLs",
"type": "array",
"description": "URLs to crawl",
"editor": "requestListSources",
"prefill": [{ "url": "https://example.com" }]
},
"maxPages": {
"title": "Max pages",
"type": "integer",
"description": "Maximum number of pages to crawl",
"default": 10,
"minimum": 1,
"maximum": 1000
}
},
"required": ["startUrls"]
}
```
### Step 4: Write the Actor
```typescript
// src/main.ts
import { Actor } from 'apify';
import { CheerioCrawler } from 'crawlee';
await Actor.init();
const input = await Actor.getInput<{
startUrls: { url: string }[];
maxPages?: number;
}>();
if (!input?.startUrls?.length) {
throw new Error('startUrls is required');
}
const crawler = new CheerioCrawler({
maxRequestsPerCrawl: input.maxPages ?? 10,
async requestHandler({ request, $, enqueueLinks }) {
const title = $('title').text().trim();
const h1 = $('h1').first().text().trim();
await Actor.pushData({
url: request.url,
title,
h1,
timestamp: new Date().toISOString(),
});
// Enqueue links on the same domain
await enqueueLinks({ strategy: 'same-domain' });
},
});
await crawler.run(input.startUrls.map(s => s.url));
await Actor.exit();
```
### Step 5: Run Locally
```bash
# Run with default input from storage/key_value_stores/default/INPUT.json
apify run
# Run with input from command line
apify run --input='{"startUrls":[{"url":"https://example.com"}],"maxPages":5}'
# View results
cat storage/datasets/default/*.json | jq '.'
# Or list dataset files
ls storage/datasets/default/
```
### Step 6: Provide Local Input
Create `storage/key_value_stores/default/INPUT.json`:
```json
{
"startUrls": [{ "url": "https://example.com" }],
"maxPages": 5
}
```
## Local Storage Emulation
`apify run` creates a `storage/` directory that mirrors platform storage:
| Platform Storage | Local Path | Access via SDK |
|-----------------|------------|----------------|
| Default dataset | `storage/datasets/default/` | `Actor.pushData()` |
| Default KV store | `storage/key_value_stores/default/` | `Actor.setValue()` / `Actor.getValue()` |
| Default request queue | `storage/request_queues/default/` | Managed by crawler |
## Hot Reload Development
```json
{
"scripts": {
"start": "tsx src/main.ts",
"dev": "tsx watch src/main.ts",
"test": "vitest"
}
}
```
```bash
# Direct tsx execution (faster iteration than apify run)
npx tsx src/main.ts
# With environment variables emulating platform
APIFY_IS_AT_HOME=0 APIFY_LOCAL_STORAGE_DIR=./storage npx tsx src/main.ts
```
## Testing Actors
```typescript
// tests/main.test.ts
import { describe, it, expect, vi } from 'vitest';
import { Actor } from 'apify';
describe('Actor', () => {
it('should process input correctly', async () => {
vi.spyOn(Actor, 'getInput').mockResolvedValue({
startUrls: [{ url: 'https://example.com' }],
maxPages: 1,
});
const pushSpy = vi.spyOn(Actor, 'pushData').mockResolvedValue(undefined);
// Run actor logic...
// Assert pushData was called with expected shape
expect(pushSpy).toHaveBeenCalledWith(
expect.objectContaining({ url: 'https://example.com' })
);
});
});
```
## Error Handling
| Error | Cause | Solution |
|-------|-------|----------|
| `apify: command not found` | CLI not installed | `npm i -g apify-cli` |
| `INPUT.json not found` | No input provided | Create `storage/key_value_stores/default/INPUT.json` |
| `Cannot find module 'apify'` | SDK not installed | `npm install apify crawlee` |
| `Dockerfile not found` | Missing actor config | Run `apify create` or create `.actor/actor.json` |
## Resources
- [Local Actor Development](https://docs.apify.com/platform/actors/development/quick-start/locally)
- [Apify CLI Reference](https://docs.apify.com/cli/docs/reference)
- [Actor Templates](https://docs.apify.com/platform/actors/development/quick-start)
## Next Steps
See `apify-sdk-patterns` for production-ready Actor code patterns.Related Skills
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