| name | apify-actorization |
| description | 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. |
| risk | unknown |
| source | community |
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
- Run
apify init in project root
- Wrap code with SDK lifecycle (see language-specific section below)
- Configure
.actor/input_schema.json
- Test with
apify run --input '{"key": "value"}'
- 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
Verify CLI is logged in:
apify info
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 the Project
Before making changes, understand the project:
- Identify the language - JavaScript/TypeScript, Python, or other
- Find the entry point - The main file that starts execution
- Identify inputs - Command-line arguments, environment variables, config files
- Identify outputs - Files, console output, API responses
- Check for state - Does it need to persist data between runs?
Step 2: Initialize Actor Structure
Run in the project root:
apify init
This creates:
.actor/actor.json - Actor configuration and metadata.actor/input_schema.json - Input definition for the Apify ConsoleDockerfile (if not present) - Container image definition
Step 3: Apply Language-Specific Changes
Choose based on your project's language:
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 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 7: Test Locally
Run the actor with inline input (for JS/TS and Python actors):
apify run --input '{"startUrl": "https://example.com", "maxItems": 10}'
Or use an input file:
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 8: Deploy
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
Apify MCP Tools
If MCP server is configured, use these tools for documentation:
search-apify-docs - Search documentationfetch-apify-docs - Get full doc pages
Otherwise, the MCP Server url: https://mcp.apify.com/?tools=docs.
Resources
