apify-actorization

What this skill does

# Apify Actorization

Actorization converts existing software into reusable serverless applications compatible with the Apify platform. Actors are programs packaged as Docker images that accept well-defined JSON input, perform an action, and optionally produce structured JSON output.

## Quick Start

1. Run `apify init` in project root
2. Wrap code with SDK lifecycle (see language-specific section below)
3. Configure `.actor/input_schema.json`
4. Test with `apify run --input '{"key": "value"}'`
5. Deploy with `apify push`

## When to Use This Skill

- Converting an existing project to run on Apify platform
- Adding Apify SDK integration to a project
- Wrapping a CLI tool or script as an Actor
- Migrating a Crawlee project to Apify

## Prerequisites

Verify `apify` CLI is installed:

```bash
apify --help
```

If not installed:

```bash
brew install apify-cli

# Or: npm install -g apify-cli
# Or install from an official release package that your OS package manager verifies
```

Verify CLI is logged in:

```bash
apify info  # Should return your username
```

If not logged in, check if `APIFY_TOKEN` environment variable is defined. If not, ask the user to generate one at https://console.apify.com/settings/integrations, add it to their shell or secret manager without putting the literal token in command history, then run:

```bash
apify login
```

## Actorization Checklist

Copy this checklist to track progress:

- [ ] Step 1: Analyze project (language, entry point, inputs, outputs)
- [ ] Step 2: Run `apify init` to create Actor structure
- [ ] Step 3: Apply language-specific SDK integration
- [ ] Step 4: Configure `.actor/input_schema.json`
- [ ] Step 5: Configure `.actor/output_schema.json` (if applicable)
- [ ] Step 6: Update `.actor/actor.json` metadata
- [ ] Step 7: Test locally with `apify run`
- [ ] Step 8: Deploy with `apify push`

## Step 1: Analyze the Project

Before making changes, understand the project:

1. **Identify the language** - JavaScript/TypeScript, Python, or other
2. **Find the entry point** - The main file that starts execution
3. **Identify inputs** - Command-line arguments, environment variables, config files
4. **Identify outputs** - Files, console output, API responses
5. **Check for state** - Does it need to persist data between runs?

## Step 2: Initialize Actor Structure

Run in the project root:

```bash
apify init
```

This creates:
- `.actor/actor.json` - Actor configuration and metadata
- `.actor/input_schema.json` - Input definition for the Apify Console
- `Dockerfile` (if not present) - Container image definition

## Step 3: Apply Language-Specific Changes

Choose based on your project's language:

- **JavaScript/TypeScript**: See [js-ts-actorization.md](references/js-ts-actorization.md)
- **Python**: See [python-actorization.md](references/python-actorization.md)
- **Other Languages (CLI-based)**: See [cli-actorization.md](references/cli-actorization.md)

### Quick Reference

| Language | Install | Wrap Code |
|----------|---------|-----------|
| JS/TS | `npm install apify` | `await Actor.init()` ... `await Actor.exit()` |
| Python | `pip install apify` | `async with Actor:` |
| Other | Use CLI in wrapper script | `apify actor:get-input` / `apify actor:push-data` |

## Steps 4-6: Configure Schemas

See [schemas-and-output.md](references/schemas-and-output.md) for detailed configuration of:
- Input schema (`.actor/input_schema.json`)
- Output schema (`.actor/output_schema.json`)
- Actor configuration (`.actor/actor.json`)
- State management (request queues, key-value stores)

Validate schemas against `@apify/json_schemas` npm package.

## Step 4: Test Locally

Run the actor with inline input (for JS/TS and Python actors):

```bash
apify run --input '{"startUrl": "https://example.com", "maxItems": 10}'
```

Or use an input file:

```bash
apify run --input-file ./test-input.json
```

**Important:** Always use `apify run`, not `npm start` or `python main.py`. The CLI sets up the proper environment and storage.

## Step 5: Deploy

```bash
apify push
```

This uploads and builds your actor on the Apify platform.

## Monetization (Optional)

After deploying, you can monetize your actor in the Apify Store. The recommended model is **Pay Per Event (PPE)**:

- Per result/item scraped
- Per page processed
- Per API call made

Configure PPE in the Apify Console under Actor > Monetization. Charge for events in your code with `await Actor.charge('result')`.

Other options: **Rental** (monthly subscription) or **Free** (open source).

## Pre-Deployment Checklist

- [ ] `.actor/actor.json` exists with correct name and description
- [ ] `.actor/actor.json` validates against `@apify/json_schemas` (`actor.schema.json`)
- [ ] `.actor/input_schema.json` defines all required inputs
- [ ] `.actor/input_schema.json` validates against `@apify/json_schemas` (`input.schema.json`)
- [ ] `.actor/output_schema.json` defines output structure (if applicable)
- [ ] `.actor/output_schema.json` validates against `@apify/json_schemas` (`output.schema.json`)
- [ ] `Dockerfile` is present and builds successfully
- [ ] `Actor.init()` / `Actor.exit()` wraps main code (JS/TS)
- [ ] `async with Actor:` wraps main code (Python)
- [ ] Inputs are read via `Actor.getInput()` / `Actor.get_input()`
- [ ] Outputs use `Actor.pushData()` or key-value store
- [ ] `apify run` executes successfully with test input
- [ ] `generatedBy` is set in actor.json meta section

## Apify MCP Tools

If MCP server is configured, use these tools for documentation:

- `search-apify-docs` - Search documentation
- `fetch-apify-docs` - Get full doc pages

Otherwise, the MCP Server url: `https://mcp.apify.com/?tools=docs`.

## Resources

- [Actorization Academy](https://docs.apify.com/academy/actorization) - Comprehensive guide
- [Apify SDK for JavaScript](https://docs.apify.com/sdk/js) - Full SDK reference
- [Apify SDK for Python](https://docs.apify.com/sdk/python) - Full SDK reference
- [Apify CLI Reference](https://docs.apify.com/cli) - CLI commands
- [Actor Specification](https://raw.githubusercontent.com/apify/actor-whitepaper/refs/heads/master/README.md) - Complete specification

## Limitations
- Use this skill only when the task clearly matches the scope described above.
- Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
- Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.