| name | apify-actorization |
|---|---|
| description | 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. |
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.
- Run
apify initin 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
- 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
Verify apify CLI is installed:
apify --helpIf not installed:
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-cliVerify CLI is logged in:
apify info # Should return your usernameIf 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:
apify login -t $APIFY_TOKENCopy this checklist to track progress:
- Step 1: Analyze project (language, entry point, inputs, outputs)
- Step 2: Run
apify initto 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.jsonmetadata - Step 7: Test locally with
apify run - Step 8: Deploy with
apify push
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?
Run in the project root:
apify initThis creates:
.actor/actor.json- Actor configuration and metadata.actor/input_schema.json- Input definition for the Apify ConsoleDockerfile(if not present) - Container image definition
Choose based on your project's language:
- JavaScript/TypeScript: See js-ts-actorization.md
- Python: See python-actorization.md
- Other Languages (CLI-based): See cli-actorization.md
| 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 |
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.
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.jsonImportant: Always use apify run, not npm start or python main.py. The CLI sets up the proper environment and storage.
apify pushThis uploads and builds your actor on the Apify platform.
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).
-
.actor/actor.jsonexists with correct name and description -
.actor/actor.jsonvalidates against@apify/json_schemas(actor.schema.json) -
.actor/input_schema.jsondefines all required inputs -
.actor/input_schema.jsonvalidates against@apify/json_schemas(input.schema.json) -
.actor/output_schema.jsondefines output structure (if applicable) -
.actor/output_schema.jsonvalidates against@apify/json_schemas(output.schema.json) -
Dockerfileis 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 runexecutes successfully with test input -
generatedByis set in actor.json meta section
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.
- Actorization Academy - Comprehensive guide
- Apify SDK for JavaScript - Full SDK reference
- Apify SDK for Python - Full SDK reference
- Apify CLI Reference - CLI commands
- Actor Specification - Complete specification