# virtualoplossing scrapper (`quotidian_plum/my-actor`) Actor virtualoplossing scrapper - **URL**: https://apify.com/quotidian\_plum/my-actor.md - **Developed by:** [karanbir](https://apify.com/quotidian_plum) (community) - **Categories:** Agents, Lead generation - **Stats:** 1 total users, 0 monthly users, 0.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing Pay per usage This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## JavaScript PuppeteerCrawler Actor template This template is a production ready boilerplate for developing with `PuppeteerCrawler`. The `PuppeteerCrawler` provides a simple framework for parallel crawling of web pages using headless Chrome with Puppeteer. Since `PuppeteerCrawler` uses headless Chrome to download web pages and extract data, it is useful for crawling of websites that require to execute JavaScript. If you're looking for examples or want to learn more visit: - [Crawlee + Apify Platform guide](https://crawlee.dev/docs/guides/apify-platform) - [Examples](https://crawlee.dev/docs/examples/puppeteer-crawler) ### Included features - **[Puppeteer Crawler](https://crawlee.dev/api/puppeteer-crawler/class/PuppeteerCrawler)** - simple framework for parallel crawling of web pages using headless Chrome with Puppeteer - **[Configurable Proxy](https://crawlee.dev/docs/guides/proxy-management#proxy-configuration)** - tool for working around IP blocking - **[Input schema](https://docs.apify.com/platform/actors/development/input-schema)** - define and easily validate a schema for your Actor's input - **[Dataset](https://docs.apify.com/sdk/js/docs/guides/result-storage#dataset)** - store structured data where each object stored has the same attributes - **[Apify SDK](https://docs.apify.com/api/client/js/)** - toolkit for building Actors ### How it works 1. `Actor.getInput()` gets the input from `INPUT.json` where the start urls are defined 2. Create a configuration for proxy servers to be used during the crawling with `Actor.createProxyConfiguration()` to work around IP blocking. Use Apify Proxy or your own Proxy URLs provided and rotated according to the configuration. You can read more about proxy configuration [here](https://crawlee.dev/api/core/class/ProxyConfiguration). 3. Create an instance of Crawlee's Puppeteer Crawler with `new PuppeteerCrawler()`. You can pass [options](https://crawlee.dev/api/puppeteer-crawler/interface/PuppeteerCrawlerOptions) to the crawler constructor as: - `proxyConfiguration` - provide the proxy configuration to the crawler - `requestHandler` - handle each request with custom router defined in the `routes.js` file. 4. Handle requests with the custom router from `routes.js` file. Read more about custom routing for the Cheerio Crawler [here](https://crawlee.dev/api/puppeteer-crawler/function/createPuppeteerRouter) - Create a new router instance with `new createPuppeteerRouter()` - Define default handler that will be called for all URLs that are not handled by other handlers by adding `router.addDefaultHandler(() => { ... })` - Define additional handlers - here you can add your own handling of the page ```javascript router.addHandler('detail', async ({ request, page, log }) => { const title = await page.title(); // You can add your own page handling here await Dataset.pushData({ url: request.loadedUrl, title, }); }); ``` 5. `crawler.run(startUrls);` start the crawler and wait for its finish ### Resources If you're looking for examples or want to learn more visit: - [Crawlee + Apify Platform guide](https://crawlee.dev/docs/guides/apify-platform) - [Documentation](https://crawlee.dev/api/playwright-crawler/class/PlaywrightCrawler) and [examples](https://crawlee.dev/docs/examples/playwright-crawler) - [Node.js tutorials](https://docs.apify.com/academy/node-js) in Academy - [How to scale Puppeteer and Playwright](https://blog.apify.com/how-to-scale-puppeteer-and-playwright/) - [Video guide on getting data using Apify API](https://www.youtube.com/watch?v=ViYYDHSBAKM) - [Integration with Make](https://apify.com/integrations), GitHub, Zapier, Google Drive, and other apps - A short guide on how to create Actors using code templates: [web scraper template](https://www.youtube.com/watch?v=u-i-Korzf8w) ### Getting started For complete information [see this article](https://docs.apify.com/platform/actors/development#build-actor-at-apify-console). In short, you will: 1. Build the Actor 2. Run the Actor ### Pull the Actor for local development If you would like to develop locally, you can pull the existing Actor from Apify console using Apify CLI: 1. Install `apify-cli` **Using Homebrew** ```bash brew install apify-cli ``` **Using NPM** ```bash npm -g install apify-cli ``` 2. Pull the Actor by its unique ``, which is one of the following: - unique name of the Actor to pull (e.g. "apify/hello-world") - or ID of the Actor to pull (e.g. "E2jjCZBezvAZnX8Rb") You can find both by clicking on the Actor title at the top of the page, which will open a modal containing both Actor unique name and Actor ID. This command will copy the Actor into the current directory on your local machine. ```bash apify pull ``` ### Documentation reference To learn more about Apify and Actors, take a look at the following resources: - [Apify SDK for JavaScript documentation](https://docs.apify.com/sdk/js) - [Apify SDK for Python documentation](https://docs.apify.com/sdk/python) - [Apify Platform documentation](https://docs.apify.com/platform) - [Join our developer community on Discord](https://discord.com/invite/jyEM2PRvMU) # Actor input Schema ## `platform` (type: `string`): Select the portal to scrape ## `jobTitle` (type: `string`): e.g. Java Developer ## `location` (type: `string`): e.g. Bangalore ## `maxResults` (type: `integer`): Number of profiles to collect ## `cookies` (type: `array`): Paste cookies here to bypass login and see phone/email ## Actor input object example ```json { "platform": "naukri", "maxResults": 20, "cookies": [] } ```` # Actor output Schema ## `results` (type: `string`): No description # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = {}; // Run the Actor and wait for it to finish const run = await client.actor("quotidian_plum/my-actor").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = {} # Run the Actor and wait for it to finish run = client.actor("quotidian_plum/my-actor").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{}' | apify call quotidian_plum/my-actor --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=quotidian_plum/my-actor", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "virtualoplossing scrapper", "description": "virtualoplossing scrapper", "version": "0.0", "x-build-id": "1xO7RxKLNVPzQGOtm" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/quotidian_plum~my-actor/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-quotidian_plum-my-actor", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/quotidian_plum~my-actor/runs": { "post": { "operationId": "runs-sync-quotidian_plum-my-actor", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/quotidian_plum~my-actor/run-sync": { "post": { "operationId": "run-sync-quotidian_plum-my-actor", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "required": [ "jobTitle", "location" ], "properties": { "platform": { "title": "Platform", "enum": [ "naukri", "linkedin", "indeed" ], "type": "string", "description": "Select the portal to scrape", "default": "naukri" }, "jobTitle": { "title": "Job Title", "type": "string", "description": "e.g. Java Developer" }, "location": { "title": "Location", "type": "string", "description": "e.g. Bangalore" }, "maxResults": { "title": "Max Results", "type": "integer", "description": "Number of profiles to collect", "default": 20 }, "cookies": { "title": "Session Cookies (JSON)", "type": "array", "description": "Paste cookies here to bypass login and see phone/email", "default": [] } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```