# Apify Actorization > Convert existing projects into Apify Actors - serverless cloud programs. Actorize JavaScript/TypeScript (SDK with Actor.init/exit), Python (async context manager), or any language (CLI wrapper). Use when migrating code to Apify, wrapping CLI tools as Actors, or adding Actor SDK to existing projects. Use when this capability is needed. - Skill: `tomevault-io/apify-actorization` (Agent Skill, multi-file: 2 files) - Install (CLI): `npx skillmds@latest add tomevault-io/apify-actorization` - Raw SKILL.md: https://api.skillmd.com/api/skills/tomevault-io/apify-actorization/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: DevOps & Infra - Author: tomevault-io (https://skillmd.com/u/tomevault-io) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/tomevault-io/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 - 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: ```bash apify --help ``` If not installed: ```bash curl -fsSL https://apify.com/install-cli.sh | bash # Or (Mac): brew install apify-cli # Or (Windows): irm https://apify.com/install-cli.ps1 | iex # Or: npm install -g apify-cli ``` 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, then: ```bash apify login -t $APIFY_TOKEN ``` For remote ops, use `mcpc` — see `apify-ops` skill. ## 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 ANALYZE: 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 INITIALIZE: 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 IMPLEMENT: 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` | ## Step CONFIGURE: 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 TEST: 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 DEPLOY: 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 ## Documentation lookups via mcpc Use the persistent `@apify` session (one-time setup in the `apify-ops` skill): ```bash mcpc --json @apify tools-call search-apify-docs query:="actor input schema" limit:=5 mcpc --json @apify tools-call fetch-apify-docs url:="https://docs.apify.com/platform/actors/running" ``` ## 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 --- > Source: [glueocom/contextractor-ts](https://github.com/glueocom/contextractor-ts) — distributed by [TomeVault](https://tomevault.io).