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{ "actorSpecification": 1, "name": "my-actor", "title": "Getting started with Python Crawlee and BeautifulSoup", "description": "Scrapes titles of websites using Crawlee and BeautifulSoup.", "version": "0.0", "buildTag": "latest", "meta": { "templateId": "python-crawlee-beautifulsoup", "generatedBy": "<FILL-IN-MODEL>" }, "input": "./input_schema.json", "output": "./output_schema.json", "storages": { "dataset": "./dataset_schema.json" }, "dockerfile": "../Dockerfile" }

{ "actorSpecification": 1, "fields": {}, "views": { "overview": { "title": "Overview", "transformation": { "fields": ["title", "url", "h1s", "h2s", "h3s"] }, "display": { "component": "table", "properties": { "title": { "label": "Title", "format": "text" }, "url": { "label": "URL", "format": "link" }, "h1s": { "label": "H1s", "format": "array" }, "h2s": { "label": "H2s", "format": "array" }, "h3s": { "label": "H3s", "format": "array" } } } } } }

{ "title": "Python Crawlee BeautifulSoup Scraper", "type": "object", "schemaVersion": 1, "properties": { "start_urls": { "title": "Start URLs", "type": "array", "description": "URLs to start with", "prefill": [{ "url": "https://apify.com" }], "editor": "requestListSources" } }, "required": ["start_urls"] }

{ "actorOutputSchemaVersion": 1, "title": "Output schema of the files scraper", "properties": { "overview": { "type": "string", "title": "Overview", "template": "{{links.apiDefaultDatasetUrl}}/items?view=overview" } } }

.git .mise.toml .nvim.lua storage # The rest is copied from https://github.com/github/gitignore/blob/main/Python.gitignore # Byte-compiled / optimized / DLL files __pycache__/ *.py[cod] *$py.class # C extensions *.so # Distribution / packaging .Python build/ develop-eggs/ dist/ downloads/ eggs/ .eggs/ lib/ lib64/ parts/ sdist/ var/ wheels/ share/python-wheels/ *.egg-info/ .installed.cfg *.egg MANIFEST # PyInstaller # Usually these files are written by a python script from a template # before PyInstaller builds the exe, so as to inject date/other infos into it. *.manifest *.spec # Installer logs pip-log.txt pip-delete-this-directory.txt # Unit test / coverage reports htmlcov/ .tox/ .nox/ .coverage .coverage.* .cache nosetests.xml coverage.xml *.cover *.py,cover .hypothesis/ .pytest_cache/ cover/ # Translations *.mo *.pot # Django stuff: *.log local_settings.py db.sqlite3 db.sqlite3-journal # Flask stuff: instance/ .webassets-cache # Scrapy stuff: .scrapy # Sphinx documentation docs/_build/ # PyBuilder .pybuilder/ target/ # Jupyter Notebook .ipynb_checkpoints # IPython profile_default/ ipython_config.py # pyenv # For a library or package, you might want to ignore these files since the code is # intended to run in multiple environments; otherwise, check them in: .python-version # pdm # Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control. #pdm.lock # pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it # in version control. # https://pdm.fming.dev/latest/usage/project/#working-with-version-control .pdm.toml .pdm-python .pdm-build/ # PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm __pypackages__/ # Celery stuff celerybeat-schedule celerybeat.pid # SageMath parsed files *.sage.py # Environments .env .venv env/ venv/ ENV/ env.bak/ venv.bak/ # Spyder project settings .spyderproject .spyproject # Rope project settings .ropeproject # mkdocs documentation /site # mypy .mypy_cache/ .dmypy.json dmypy.json # Pyre type checker .pyre/ # pytype static type analyzer .pytype/ # Cython debug symbols cython_debug/ # PyCharm # JetBrains specific template is maintained in a separate JetBrains.gitignore that can # be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore # and can be added to the global gitignore or merged into this file. For a more nuclear # option (not recommended) you can uncomment the following to ignore the entire idea folder. .idea/ # Visual Studio Code # Ignores the folder created by VS Code when changing workspace settings, doing debugger # configuration, etc. Can be commented out to share Workspace Settings within a team .vscode # Zed editor # Ignores the folder created when setting Project Settings in the Zed editor. Can be commented out # to share Project Settings within a team .zed

.mise.toml .nvim.lua storage # The rest is copied from https://github.com/github/gitignore/blob/main/Python.gitignore # Byte-compiled / optimized / DLL files __pycache__/ *.py[cod] *$py.class # C extensions *.so # Distribution / packaging .Python build/ develop-eggs/ dist/ downloads/ eggs/ .eggs/ lib/ lib64/ parts/ sdist/ var/ wheels/ share/python-wheels/ *.egg-info/ .installed.cfg *.egg MANIFEST # PyInstaller # Usually these files are written by a python script from a template # before PyInstaller builds the exe, so as to inject date/other infos into it. *.manifest *.spec # Installer logs pip-log.txt pip-delete-this-directory.txt # Unit test / coverage reports htmlcov/ .tox/ .nox/ .coverage .coverage.* .cache nosetests.xml coverage.xml *.cover *.py,cover .hypothesis/ .pytest_cache/ cover/ # Translations *.mo *.pot # Django stuff: *.log local_settings.py db.sqlite3 db.sqlite3-journal # Flask stuff: instance/ .webassets-cache # Scrapy stuff: .scrapy # Sphinx documentation docs/_build/ # PyBuilder .pybuilder/ target/ # Jupyter Notebook .ipynb_checkpoints # IPython profile_default/ ipython_config.py # pyenv # For a library or package, you might want to ignore these files since the code is # intended to run in multiple environments; otherwise, check them in: .python-version # pdm # Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control. #pdm.lock # pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it # in version control. # https://pdm.fming.dev/latest/usage/project/#working-with-version-control .pdm.toml .pdm-python .pdm-build/ # PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm __pypackages__/ # Celery stuff celerybeat-schedule celerybeat.pid # SageMath parsed files *.sage.py # Environments .env .venv env/ venv/ ENV/ env.bak/ venv.bak/ # Spyder project settings .spyderproject .spyproject # Rope project settings .ropeproject # mkdocs documentation /site # mypy .mypy_cache/ .dmypy.json dmypy.json # Pyre type checker .pyre/ # pytype static type analyzer .pytype/ # Cython debug symbols cython_debug/ # PyCharm # JetBrains specific template is maintained in a separate JetBrains.gitignore that can # be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore # and can be added to the global gitignore or merged into this file. For a more nuclear # option (not recommended) you can uncomment the following to ignore the entire idea folder. .idea/ # Zed editor # Ignores the folder created when setting Project Settings in the Zed editor. Can be commented out # to share Project Settings within a team .zed

1# Apify Actors Development Guide 2 3Important: Before you begin, fill in the `generatedBy` property in the meta section of `.actor/actor.json`. Replace it with the tool and model you're currently using, such as "Claude Code with Claude Sonnet 4.5". This helps Apify monitor and improve AGENTS.md for specific AI tools and models. 4 5## What are Apify Actors? 6 7- Actors are serverless programs that run in the cloud. They're inspired by the UNIX philosophy - programs that do one thing well and can be easily combined to build complex systems. 8- Actors are programs packaged as Docker images that run in isolated containers 9 10## Core Concepts 11 12- Accept well-defined JSON input 13- Perform isolated tasks (web scraping, automation, data processing) 14- Produce structured JSON output to datasets and/or store data in key-value stores 15- Can run from seconds to hours or even indefinitely 16- Persist state and can be restarted 17 18## Do 19 20- accept well-defined JSON input and produce structured JSON output 21- use Apify SDK (`apify`) for code running ON Apify platform 22- validate input early with proper error handling and fail gracefully 23- use CheerioCrawler for static HTML content (10x faster than browsers) 24- use PlaywrightCrawler only for JavaScript-heavy sites and dynamic content 25- use router pattern (createCheerioRouter/createPlaywrightRouter) for complex crawls 26- implement retry strategies with exponential backoff for failed requests 27- use proper concurrency settings (HTTP: 10-50, Browser: 1-5) 28- set sensible defaults in `.actor/input_schema.json` for all optional fields 29- set up output schema in `.actor/output_schema.json` 30- clean and validate data before pushing to dataset 31- use semantic CSS selectors and fallback strategies for missing elements 32- respect robots.txt, ToS, and implement rate limiting with delays 33- check which tools (cheerio/playwright/crawlee) are installed before applying guidance 34- use `Actor.log` for logging (censors sensitive data) 35- implement readiness probe handler for standby Actors 36- handle the `aborting` event to gracefully shut down when Actor is stopped 37 38## Don't 39 40- do not rely on `Dataset.getInfo()` for final counts on Cloud platform 41- do not use browser crawlers when HTTP/Cheerio works (massive performance gains with HTTP) 42- do not hard code values that should be in input schema or environment variables 43- do not skip input validation or error handling 44- do not overload servers - use appropriate concurrency and delays 45- do not scrape prohibited content or ignore Terms of Service 46- do not store personal/sensitive data unless explicitly permitted 47- do not use deprecated options like `requestHandlerTimeoutMillis` on CheerioCrawler (v3.x) 48- do not use `additionalHttpHeaders` - use `preNavigationHooks` instead 49- do not assume that local storage is persistent or automatically synced to Apify Console - when running locally with `apify run`, the `storage/` directory is local-only and is NOT pushed to the Cloud 50- do not disable standby mode (`usesStandbyMode: false`) without explicit permission 51 52## Logging 53 54- **ALWAYS use `Actor.log` for logging** - This logger contains critical security logic including censoring sensitive data (Apify tokens, API keys, credentials) to prevent accidental exposure in logs 55 56### Available Log Levels 57 58The Apify Actor logger provides the following methods for logging: 59 60- `Actor.log.debug()` - Debug level logs (detailed diagnostic information) 61- `Actor.log.info()` - Info level logs (general informational messages) 62- `Actor.log.warning()` - Warning level logs (warning messages for potentially problematic situations) 63- `Actor.log.error()` - Error level logs (error messages for failures) 64- `Actor.log.exception()` - Exception level logs (for exceptions with stack traces) 65 66**Best practices:** 67 68- Use `Actor.log.debug()` for detailed operation-level diagnostics (inside functions) 69- Use `Actor.log.info()` for general informational messages (API requests, successful operations) 70- Use `Actor.log.warning()` for potentially problematic situations (validation failures, unexpected states) 71- Use `Actor.log.error()` for actual errors and failures 72- Use `Actor.log.exception()` for caught exceptions with stack traces 73 74## Graceful Abort Handling 75 76Handle the `aborting` event to terminate the Actor quickly when stopped by user or platform, minimizing costs especially for PPU/PPE+U billing. 77 78```python 79import asyncio 80 81async def on_aborting() -> None: 82 # Persist any state, do any cleanup you need, and terminate the Actor using `await Actor.exit()` explicitly as soon as possible 83 # This will help ensure that the Actor is doing best effort to honor any potential limits on costs of a single run set by the user 84 # Wait 1 second to allow Crawlee/SDK state persistence operations to complete 85 # This is a temporary workaround until SDK implements proper state persistence in the aborting event 86 await asyncio.sleep(1) 87 await Actor.exit() 88 89Actor.on('aborting', on_aborting) 90``` 91 92## Standby Mode 93 94- **NEVER disable standby mode (`usesStandbyMode: false`) in `.actor/actor.json` without explicit permission** - Actor Standby mode solves this problem by letting you have the Actor ready in the background, waiting for the incoming HTTP requests. In a sense, the Actor behaves like a real-time web server or standard API server instead of running the logic once to process everything in batch. Always keep `usesStandbyMode: true` unless there is a specific documented reason to disable it 95- **ALWAYS implement readiness probe handler for standby Actors** - Handle the `x-apify-container-server-readiness-probe` header at GET / endpoint to ensure proper Actor lifecycle management 96 97You can recognize a standby Actor by checking the `usesStandbyMode` property in `.actor/actor.json`. Only implement the readiness probe if this property is set to `true`. 98 99### Readiness Probe Implementation Example 100 101```python 102# Apify standby readiness probe 103from http.server import SimpleHTTPRequestHandler 104 105class GetHandler(SimpleHTTPRequestHandler): 106 def do_GET(self): 107 # Handle Apify standby readiness probe 108 if 'x-apify-container-server-readiness-probe' in self.headers: 109 self.send_response(200) 110 self.end_headers() 111 self.wfile.write(b'Readiness probe OK') 112 return 113 114 self.send_response(200) 115 self.end_headers() 116 self.wfile.write(b'Actor is ready') 117``` 118 119Key points: 120 121- Detect the `x-apify-container-server-readiness-probe` header in incoming requests 122- Respond with HTTP 200 status code for both readiness probe and normal requests 123- This enables proper Actor lifecycle management in standby mode 124 125## Commands 126 127```bash 128# Local development 129apify run # Run Actor locally 130 131# Authentication & deployment 132apify login # Authenticate account 133apify push # Deploy to Apify platform 134 135# Help 136apify help # List all commands 137``` 138 139## Safety and Permissions 140 141Allowed without prompt: 142 143- read files with `Actor.get_value()` 144- push data with `Actor.push_data()` 145- set values with `Actor.set_value()` 146- enqueue requests to RequestQueue 147- run locally with `apify run` 148 149Ask first: 150 151- npm/pip package installations 152- apify push (deployment to cloud) 153- proxy configuration changes (requires paid plan) 154- Dockerfile changes affecting builds 155- deleting datasets or key-value stores 156 157## Project Structure 158 159.actor/ 160├── actor.json # Actor config: name, version, env vars, runtime settings 161├── input_schema.json # Input validation & Console form definition 162└── output_schema.json # Specifies where an Actor stores its output 163src/ 164└── main.js # Actor entry point and orchestrator 165storage/ # Local-only storage for development (NOT synced to Cloud) 166├── datasets/ # Output items (JSON objects) 167├── key_value_stores/ # Files, config, INPUT 168└── request_queues/ # Pending crawl requests 169Dockerfile # Container image definition 170AGENTS.md # AI agent instructions (this file) 171 172## Local vs Cloud Storage 173 174When running locally with `apify run`, the Apify SDK emulates Cloud storage APIs using the local `storage/` directory. This local storage behaves differently from Cloud storage: 175 176- **Local storage is NOT persistent** - The `storage/` directory is meant for local development and testing only. Data stored there (datasets, key-value stores, request queues) exists only on your local disk. 177- **Local storage is NOT automatically pushed to Apify Console** - Running `apify run` does not upload any storage data to the Apify platform. The data stays local. 178- **Each local run may overwrite previous data** - The local `storage/` directory is reused between runs, but this is local-only behavior, not Cloud persistence. 179- **Cloud storage only works when running on Apify platform** - After deploying with `apify push` and running the Actor in the Cloud, storage calls (`Actor.push_data()`, `Actor.set_value()`, etc.) interact with real Apify Cloud storage, which is then visible in the Apify Console. 180- **To verify Actor output, deploy and run in Cloud** - Do not rely on local `storage/` contents as proof that data will appear in the Apify Console. Always test by deploying (`apify push`) and running the Actor on the platform. 181 182## Actor Input Schema 183 184The input schema defines the input parameters for an Actor. It's a JSON object comprising various field types supported by the Apify platform. 185 186### Structure 187 188```json 189{ 190 "title": "<INPUT-SCHEMA-TITLE>", 191 "type": "object", 192 "schemaVersion": 1, 193 "properties": { 194 /* define input fields here */ 195 }, 196 "required": [] 197} 198``` 199 200### Example 201 202```json 203{ 204 "title": "E-commerce Product Scraper Input", 205 "type": "object", 206 "schemaVersion": 1, 207 "properties": { 208 "startUrls": { 209 "title": "Start URLs", 210 "type": "array", 211 "description": "URLs to start scraping from (category pages or product pages)", 212 "editor": "requestListSources", 213 "default": [{ "url": "https://example.com/category" }], 214 "prefill": [{ "url": "https://example.com/category" }] 215 }, 216 "followVariants": { 217 "title": "Follow Product Variants", 218 "type": "boolean", 219 "description": "Whether to scrape product variants (different colors, sizes)", 220 "default": true 221 }, 222 "maxRequestsPerCrawl": { 223 "title": "Max Requests per Crawl", 224 "type": "integer", 225 "description": "Maximum number of pages to scrape (0 = unlimited)", 226 "default": 1000, 227 "minimum": 0 228 }, 229 "proxyConfiguration": { 230 "title": "Proxy Configuration", 231 "type": "object", 232 "description": "Proxy settings for anti-bot protection", 233 "editor": "proxy", 234 "default": { "useApifyProxy": false } 235 }, 236 "locale": { 237 "title": "Locale", 238 "type": "string", 239 "description": "Language/country code for localized content", 240 "default": "cs", 241 "enum": ["cs", "en", "de", "sk"], 242 "enumTitles": ["Czech", "English", "German", "Slovak"] 243 } 244 }, 245 "required": ["startUrls"] 246} 247``` 248 249## Actor Output Schema 250 251The Actor output schema builds upon the schemas for the dataset and key-value store. It specifies where an Actor stores its output and defines templates for accessing that output. Apify Console uses these output definitions to display run results. 252 253### Structure 254 255```json 256{ 257 "actorOutputSchemaVersion": 1, 258 "title": "<OUTPUT-SCHEMA-TITLE>", 259 "properties": { 260 /* define your outputs here */ 261 } 262} 263``` 264 265### Example 266 267```json 268{ 269 "actorOutputSchemaVersion": 1, 270 "title": "Output schema of the files scraper", 271 "properties": { 272 "files": { 273 "type": "string", 274 "title": "Files", 275 "template": "{{links.apiDefaultKeyValueStoreUrl}}/keys" 276 }, 277 "dataset": { 278 "type": "string", 279 "title": "Dataset", 280 "template": "{{links.apiDefaultDatasetUrl}}/items" 281 } 282 } 283} 284``` 285 286### Output Schema Template Variables 287 288- `links` (object) - Contains quick links to most commonly used URLs 289- `links.publicRunUrl` (string) - Public run url in format `https://console.apify.com/view/runs/:runId` 290- `links.consoleRunUrl` (string) - Console run url in format `https://console.apify.com/actors/runs/:runId` 291- `links.apiRunUrl` (string) - API run url in format `https://api.apify.com/v2/actor-runs/:runId` 292- `links.apiDefaultDatasetUrl` (string) - API url of default dataset in format `https://api.apify.com/v2/datasets/:defaultDatasetId` 293- `links.apiDefaultKeyValueStoreUrl` (string) - API url of default key-value store in format `https://api.apify.com/v2/key-value-stores/:defaultKeyValueStoreId` 294- `links.containerRunUrl` (string) - URL of a webserver running inside the run in format `https://<containerId>.runs.apify.net/` 295- `run` (object) - Contains information about the run same as it is returned from the `GET Run` API endpoint 296- `run.defaultDatasetId` (string) - ID of the default dataset 297- `run.defaultKeyValueStoreId` (string) - ID of the default key-value store 298 299## Dataset Schema Specification 300 301The dataset schema defines how your Actor's output data is structured, transformed, and displayed in the Output tab in the Apify Console. 302 303### Example 304 305Consider an example Actor that calls `Actor.pushData()` to store data into dataset: 306 307```python 308# Dataset push example (Python) 309import asyncio 310from datetime import datetime 311from apify import Actor 312 313async def main(): 314 await Actor.init() 315 316 # Actor code 317 await Actor.push_data({ 318 'numericField': 10, 319 'pictureUrl': 'https://www.google.com/images/branding/googlelogo/2x/googlelogo_color_92x30dp.png', 320 'linkUrl': 'https://google.com', 321 'textField': 'Google', 322 'booleanField': True, 323 'dateField': datetime.now().isoformat(), 324 'arrayField': ['#hello', '#world'], 325 'objectField': {}, 326 }) 327 328 # Exit successfully 329 await Actor.exit() 330 331if __name__ == '__main__': 332 asyncio.run(main()) 333``` 334 335To set up the Actor's output tab UI, reference a dataset schema file in `.actor/actor.json`: 336 337```json 338{ 339 "actorSpecification": 1, 340 "name": "book-library-scraper", 341 "title": "Book Library Scraper", 342 "version": "1.0.0", 343 "storages": { 344 "dataset": "./dataset_schema.json" 345 } 346} 347``` 348 349Then create the dataset schema in `.actor/dataset_schema.json`: 350 351```json 352{ 353 "actorSpecification": 1, 354 "fields": {}, 355 "views": { 356 "overview": { 357 "title": "Overview", 358 "transformation": { 359 "fields": [ 360 "pictureUrl", 361 "linkUrl", 362 "textField", 363 "booleanField", 364 "arrayField", 365 "objectField", 366 "dateField", 367 "numericField" 368 ] 369 }, 370 "display": { 371 "component": "table", 372 "properties": { 373 "pictureUrl": { 374 "label": "Image", 375 "format": "image" 376 }, 377 "linkUrl": { 378 "label": "Link", 379 "format": "link" 380 }, 381 "textField": { 382 "label": "Text", 383 "format": "text" 384 }, 385 "booleanField": { 386 "label": "Boolean", 387 "format": "boolean" 388 }, 389 "arrayField": { 390 "label": "Array", 391 "format": "array" 392 }, 393 "objectField": { 394 "label": "Object", 395 "format": "object" 396 }, 397 "dateField": { 398 "label": "Date", 399 "format": "date" 400 }, 401 "numericField": { 402 "label": "Number", 403 "format": "number" 404 } 405 } 406 } 407 } 408 } 409} 410``` 411 412### Structure 413 414```json 415{ 416 "actorSpecification": 1, 417 "fields": {}, 418 "views": { 419 "<VIEW_NAME>": { 420 "title": "string (required)", 421 "description": "string (optional)", 422 "transformation": { 423 "fields": ["string (required)"], 424 "unwind": ["string (optional)"], 425 "flatten": ["string (optional)"], 426 "omit": ["string (optional)"], 427 "limit": "integer (optional)", 428 "desc": "boolean (optional)" 429 }, 430 "display": { 431 "component": "table (required)", 432 "properties": { 433 "<FIELD_NAME>": { 434 "label": "string (optional)", 435 "format": "text|number|date|link|boolean|image|array|object (optional)" 436 } 437 } 438 } 439 } 440 } 441} 442``` 443 444**Dataset Schema Properties:** 445 446- `actorSpecification` (integer, required) - Specifies the version of dataset schema structure document (currently only version 1) 447- `fields` (JSONSchema object, required) - Schema of one dataset object (use JsonSchema Draft 2020-12 or compatible) 448- `views` (DatasetView object, required) - Object with API and UI views description 449 450**DatasetView Properties:** 451 452- `title` (string, required) - Visible in UI Output tab and API 453- `description` (string, optional) - Only available in API response 454- `transformation` (ViewTransformation object, required) - Data transformation applied when loading from Dataset API 455- `display` (ViewDisplay object, required) - Output tab UI visualization definition 456 457**ViewTransformation Properties:** 458 459- `fields` (string[], required) - Fields to present in output (order matches column order) 460- `unwind` (string[], optional) - Deconstructs nested children into parent object 461- `flatten` (string[], optional) - Transforms nested object into flat structure 462- `omit` (string[], optional) - Removes specified fields from output 463- `limit` (integer, optional) - Maximum number of results (default: all) 464- `desc` (boolean, optional) - Sort order (true = newest first) 465 466**ViewDisplay Properties:** 467 468- `component` (string, required) - Only `table` is available 469- `properties` (Object, optional) - Keys matching `transformation.fields` with ViewDisplayProperty values 470 471**ViewDisplayProperty Properties:** 472 473- `label` (string, optional) - Table column header 474- `format` (string, optional) - One of: `text`, `number`, `date`, `link`, `boolean`, `image`, `array`, `object` 475 476## Key-Value Store Schema Specification 477 478The key-value store schema organizes keys into logical groups called collections for easier data management. 479 480### Example 481 482Consider an example Actor that calls `Actor.setValue()` to save records into the key-value store: 483 484```python 485# Key-Value Store set example (Python) 486import asyncio 487from apify import Actor 488 489async def main(): 490 await Actor.init() 491 492 # Actor code 493 await Actor.set_value('document-1', 'my text data', content_type='text/plain') 494 495 image_id = '123' # example placeholder 496 image_buffer = b'...' # bytes buffer with image data 497 await Actor.set_value(f'image-{image_id}', image_buffer, content_type='image/jpeg') 498 499 # Exit successfully 500 await Actor.exit() 501 502if __name__ == '__main__': 503 asyncio.run(main()) 504``` 505 506To configure the key-value store schema, reference a schema file in `.actor/actor.json`: 507 508```json 509{ 510 "actorSpecification": 1, 511 "name": "data-collector", 512 "title": "Data Collector", 513 "version": "1.0.0", 514 "storages": { 515 "keyValueStore": "./key_value_store_schema.json" 516 } 517} 518``` 519 520Then create the key-value store schema in `.actor/key_value_store_schema.json`: 521 522```json 523{ 524 "actorKeyValueStoreSchemaVersion": 1, 525 "title": "Key-Value Store Schema", 526 "collections": { 527 "documents": { 528 "title": "Documents", 529 "description": "Text documents stored by the Actor", 530 "keyPrefix": "document-" 531 }, 532 "images": { 533 "title": "Images", 534 "description": "Images stored by the Actor", 535 "keyPrefix": "image-", 536 "contentTypes": ["image/jpeg"] 537 } 538 } 539} 540``` 541 542### Structure 543 544```json 545{ 546 "actorKeyValueStoreSchemaVersion": 1, 547 "title": "string (required)", 548 "description": "string (optional)", 549 "collections": { 550 "<COLLECTION_NAME>": { 551 "title": "string (required)", 552 "description": "string (optional)", 553 "key": "string (conditional - use key OR keyPrefix)", 554 "keyPrefix": "string (conditional - use key OR keyPrefix)", 555 "contentTypes": ["string (optional)"], 556 "jsonSchema": "object (optional)" 557 } 558 } 559} 560``` 561 562**Key-Value Store Schema Properties:** 563 564- `actorKeyValueStoreSchemaVersion` (integer, required) - Version of key-value store schema structure document (currently only version 1) 565- `title` (string, required) - Title of the schema 566- `description` (string, optional) - Description of the schema 567- `collections` (Object, required) - Object where each key is a collection ID and value is a Collection object 568 569**Collection Properties:** 570 571- `title` (string, required) - Collection title shown in UI tabs 572- `description` (string, optional) - Description appearing in UI tooltips 573- `key` (string, conditional\*) - Single specific key for this collection 574- `keyPrefix` (string, conditional\*) - Prefix for keys included in this collection 575- `contentTypes` (string[], optional) - Allowed content types for validation 576- `jsonSchema` (object, optional) - JSON Schema Draft 07 format for `application/json` content type validation 577 578\*Either `key` or `keyPrefix` must be specified for each collection, but not both. 579 580## Apify MCP Tools 581 582If MCP server is configured, use these tools for documentation: 583 584- `search-apify-docs` - Search documentation 585- `fetch-apify-docs` - Get full doc pages 586 587Otherwise, reference: `@https://mcp.apify.com/` 588 589## Resources 590 591- [docs.apify.com/llms.txt](https://docs.apify.com/llms.txt) - Quick reference 592- [docs.apify.com/llms-full.txt](https://docs.apify.com/llms-full.txt) - Complete docs 593- [crawlee.dev](https://crawlee.dev) - Crawlee documentation 594- [whitepaper.actor](https://raw.githubusercontent.com/apify/actor-whitepaper/refs/heads/master/README.md) - Complete Actor specification

# First, specify the base Docker image. # You can see the Docker images from Apify at https://hub.docker.com/r/apify/. # You can also use any other image from Docker Hub. FROM apify/actor-python:3.14 USER myuser # Second, copy just requirements.txt into the Actor image, # since it should be the only file that affects the dependency install in the next step, # in order to speed up the build COPY --chown=myuser:myuser requirements.txt ./ # Install the packages specified in requirements.txt, # Print the installed Python version, pip version # and all installed packages with their versions for debugging RUN echo "Python version:" \ && python --version \ && echo "Pip version:" \ && pip --version \ && echo "Installing dependencies:" \ && pip install -r requirements.txt \ && echo "All installed Python packages:" \ && pip freeze # Next, copy the remaining files and directories with the source code. # Since we do this after installing the dependencies, quick build will be really fast # for most source file changes. COPY --chown=myuser:myuser . ./ # Use compileall to ensure the runnability of the Actor Python code. RUN python3 -m compileall -q src/ # Specify how to launch the source code of your Actor. # By default, the "python3 -m src" command is run CMD ["python3", "-m", "src"]

1"""Module defines the main entry point for the Apify Actor. 2 3Feel free to modify this file to suit your specific needs. 4 5To build Apify Actors, utilize the Apify SDK toolkit, read more at the official documentation: 6https://docs.apify.com/sdk/python 7""" 8 9from __future__ import annotations 10 11import asyncio 12 13from apify import Actor, Event 14from crawlee.crawlers import BeautifulSoupCrawler, BeautifulSoupCrawlingContext 15 16 17async def main() -> None: 18 """Define a main entry point for the Apify Actor. 19 20 This coroutine is executed using `asyncio.run()`, so it must remain an asynchronous function for proper execution. 21 Asynchronous execution is required for communication with Apify platform, and it also enhances performance in 22 the field of web scraping significantly. 23 """ 24 # Enter the context of the Actor. 25 async with Actor: 26 # Handle graceful abort - Actor is being stopped by user or platform 27 async def on_aborting() -> None: 28 # Persist any state, do any cleanup you need, and terminate the Actor using 29 # `await Actor.exit()` explicitly as soon as possible. This will help ensure that 30 # the Actor is doing best effort to honor any potential limits on costs of a 31 # single run set by the user. 32 # Wait 1 second to allow Crawlee/SDK state persistence operations to complete 33 # This is a temporary workaround until SDK implements proper state persistence in the aborting event 34 await asyncio.sleep(1) 35 await Actor.exit() 36 37 Actor.on(Event.ABORTING, on_aborting) 38 39 # Retrieve the Actor input, and use default values if not provided. 40 actor_input = await Actor.get_input() or {} 41 start_urls = [ 42 url.get('url') 43 for url in actor_input.get( 44 'start_urls', 45 [{'url': 'https://apify.com'}], 46 ) 47 ] 48 49 # Exit if no start URLs are provided. 50 if not start_urls: 51 Actor.log.info('No start URLs specified in Actor input, exiting...') 52 await Actor.exit() 53 54 # Create a crawler. 55 crawler = BeautifulSoupCrawler( 56 # Limit the crawl to max requests. Remove or increase it for crawling all links. 57 max_requests_per_crawl=10, 58 ) 59 60 # Define a request handler, which will be called for every request. 61 @crawler.router.default_handler 62 async def request_handler(context: BeautifulSoupCrawlingContext) -> None: 63 url = context.request.url 64 Actor.log.info(f'Scraping {url}...') 65 66 # Extract the desired data. 67 data = { 68 'url': context.request.url, 69 'title': context.soup.title.string if context.soup.title else None, 70 'h1s': [h1.text for h1 in context.soup.find_all('h1')], 71 'h2s': [h2.text for h2 in context.soup.find_all('h2')], 72 'h3s': [h3.text for h3 in context.soup.find_all('h3')], 73 } 74 75 # Store the extracted data to the default dataset. 76 await context.push_data(data) 77 78 # Enqueue additional links found on the current page. 79 await context.enqueue_links() 80 81 # Run the crawler with the starting requests. 82 await crawler.run(start_urls)

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