# Enverus Discovery Extractor (`getdataforme/enverus-discovery-extractor`) Actor The Enverus Discovery Spider is a web scraping tool designed for extracting job listings from Enverus's career page. It offers comprehensive data extraction, high-quality and scalable performance, customizable output formats (JSON, CSV, Excel), and a user-friendly interface.... - **URL**: https://apify.com/getdataforme/enverus-discovery-extractor.md - **Developed by:** [GetDataForMe](https://apify.com/getdataforme) (community) - **Categories:** AI, Automation, E-commerce - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $9.00 / 1,000 results This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows. 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. - **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use). - **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`. - **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`. - **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`. - **Any other language** — 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 *** ### README.md ## Enverus Discovery Spider Welcome to the Enverus Discovery Spider! This powerful web scraping tool is designed to extract job listings and other relevant data from Enverus's career page. By leveraging advanced crawling techniques, it ensures high-quality, reliable data that can be used for various business intelligence applications. ### Features - **Comprehensive Data Extraction**: Captures detailed job listings including titles, locations, descriptions, and URLs. - **High-Quality Data**: Ensures accuracy and reliability with robust error handling and validation mechanisms. - **Scalable Performance**: Efficiently handles large volumes of data without compromising speed or quality. - **Customizable Output**: Supports multiple formats such as JSON, CSV, and Excel for easy integration into your workflows. - **User-Friendly Interface**: Simple configuration options make it accessible to both technical and non-technical users. ### Input Parameters | Parameter | Type | Required | Description | Example | |-------------|---------|----------|-----------------------------------------------------------------------------|--------------------------| | `urls` | Array | Yes | List of URLs to scrape. | `[ "https://example.com" ]` | | `maxItems` | Integer | No | Maximum number of items to extract. | `100` | | `delay` | Number | No | Delay between requests in milliseconds. | `2000` | ### Example Usage #### Input JSON ```json { "urls": ["https://www.enverus.com/careers"], "maxItems": 50, "delay": 1000 } ``` #### Output JSON ```json [ { "job_title": "Senior Analyst", "location": "Austin, TX", "description": "Responsible for...", "url": "https://jobs.example.com/senior-analyst" }, ... ] ``` ### Use Cases - **Market Research and Analysis**: Gain insights into job market trends. - **Competitive Intelligence**: Monitor competitor hiring strategies. - **Price Monitoring**: Track salary offerings across industries. - **Content Aggregation**: Compile job listings for newsletters or reports. - **Academic Research**: Analyze employment data for studies. - **Business Automation**: Integrate with HR systems for recruitment processes. ### Installation and Usage 1. Search for "Enverus Discovery Spider" in the Apify Store. 2. Click "Try for free" or "Run". 3. Configure input parameters as needed. 4. Click "Start" to begin extraction. 5. Monitor progress in the log. 6. Export results in your preferred format (JSON, CSV, Excel). ### Output Format The output data is structured with key fields such as `job_title`, `location`, `description`, and `url`. Each entry represents a job listing extracted from the specified URLs. ### Support For custom/simplified outputs or bug reports, please contact: - Email: support@getdataforme.com - Subject line: "custom support" - Contact form: [Contact Us](https://getdataforme.com/contact/) We're here to help you get the most out of this Actor! *** # Actor input Schema ## `item_limit` (type: `integer`): Maximum items to scrape per actor run. Set to 0 for no limit. ## Actor input object example ```json { "item_limit": 10 } ``` # 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("getdataforme/enverus-discovery-extractor").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("getdataforme/enverus-discovery-extractor").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 getdataforme/enverus-discovery-extractor --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=getdataforme/enverus-discovery-extractor", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification Download the OpenAPI definition: https://api.apify.com/v2/actors/1mSJI6YuDhQrG7fFu/builds/TQp0Jh9iJa9ZfE8C7/openapi.json