apify-actorization

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:

apify --help

If not installed:

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:

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:

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?