Apify actorization

--- 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 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.js