# Aem Article Detail Opp Spider (`getdataforme/aem-article-detail-opp-spider`) Actor The Aem Article Detail Opp Spider is a robust web scraping tool designed for extracting detailed article information from specified URLs.... - **URL**: https://apify.com/getdataforme/aem-article-detail-opp-spider.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 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 --- ## Aem Article Detail Opp Spider ### Introduction The **Aem Article Detail Opp Spider** is a powerful web scraping tool designed to extract detailed information from specified URLs. It efficiently gathers article titles, images, dates, descriptions, and related links, providing comprehensive data for analysis and reporting. ### Features - **Comprehensive Data Extraction**: Captures essential details such as post titles, images, and descriptions. - **Flexible URL Configuration**: Allows input of multiple URLs to scrape. - **Customizable Item Limits**: Set a maximum number of items to scrape per run. - **High-Quality Output**: Ensures data reliability with structured JSON output. - **User-Friendly Setup**: Easy configuration through the Apify Store interface. ### Input Parameters | Parameter | Type | Required | Description | Example | |---------------|---------|----------|-----------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------| | ProductUrls | array | Yes | The product URLs for the spider. | `["https://www.aem.org/news/join-aem%E2%80%99s-member-education-webinar-standards-development-%E2%80%93-autonomy-to-stay-on-top-of-key-industry"]` | | item_limit | integer | No | Maximum items to scrape per actor run. Set to 0 for no limit. | `10` | ### Example Usage #### Input JSON ```json { "ProductUrls": [ "https://www.aem.org/news/join-aem%E2%80%99s-member-education-webinar-standards-development-%E2%80%93-autonomy-to-stay-on-top-of-key-industry" ], "item_limit": 10 } ```` #### Output JSON ```json [ { "post_title": "Join AEM\u2019s Member Education Webinar: Standards Development \u2013 Autonomy to Stay on Top of Key Industry Standards Work", "post_image": "https://divvyhq-media-production.s3.amazonaws.com/attachments/7b161f36e689c450696a3342d2c20b26cd8afb4c31e1e0e5c2c33a28d3736fd9/Standards_Development_Insert.png", "posted_date": "5/1/2025", "time_duration_to_read": "Less Than a Minute Read", "description": "Read About the Latest Industry News. Advancing Equipment Manufacturers in the Global Marketplace. Advocacy, Trade Shows, Market Data and Safety.", "related_articles": [ "https://www.aem.org/news/your-\u2018moment-to-rise\u2019-starts-now-aem-annual-conference-registration-is-open", "https://www.aem.org/news/dairy-equipment-leaders-convene-at-aem\u2019s-milwaukee-headquarters", "https://www.aem.org/news/submit-session-content-for-aem\u2019s-product-safety-stewardship-conference", "https://www.aem.org/news/aem-peer-groups-are-forming-now-\u2013-secure-your-spot-by-june-26", "https://www.aem.org/news/aem-looks-to-redefine-the-aftermarket-segment-through-its-new-customer-lifecycle-support-executive-c" ], "actor_id": "1xFGPBLet5TxAWGcI", "run_id": "bLhTDzlOenMMrhNhR" } ] ``` ### Use Cases - **Market Research and Analysis**: Extract detailed article data for market insights. - **Competitive Intelligence**: Monitor competitor content strategies. - **Price Monitoring**: Track pricing information in industry articles. - **Content Aggregation**: Compile related articles for comprehensive reports. - **Academic Research**: Gather data for research projects. - **Business Automation**: Automate data collection processes. ### Installation and Usage 1. Search for "Aem Article Detail Opp 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 is a JSON array containing objects with the following fields: - `post_title`: The title of the article. - `post_image`: URL of the image associated with the post. - `posted_date`: Date when the article was posted. - `time_duration_to_read`: Estimated reading time. - `description`: Brief description of the article content. - `related_articles`: List of URLs to related articles. - `actor_id`: Unique identifier for the actor run. - `run_id`: Unique identifier for the specific run. ### 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 ## `ProductUrls` (type: `array`): The product urls for the spider. ## `item_limit` (type: `integer`): Maximum items to scrape per actor run. Set to 0 for no limit. ## Actor input object example ```json { "ProductUrls": [ "https://www.aem.org/news/join-aem%E2%80%99s-member-education-webinar-standards-development-%E2%80%93-autonomy-to-stay-on-top-of-key-industry" ], "item_limit": 10 } ``` # Actor output Schema ## `results` (type: `string`): Scraped data items from dataset # 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/aem-article-detail-opp-spider").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/aem-article-detail-opp-spider").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/aem-article-detail-opp-spider --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=getdataforme/aem-article-detail-opp-spider", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Aem Article Detail Opp Spider", "description": "The Aem Article Detail Opp Spider is a robust web scraping tool designed for extracting detailed article information from specified URLs....", "version": "0.0", "x-build-id": "R00q0xxhV4Pna2bxn" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/getdataforme~aem-article-detail-opp-spider/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-getdataforme-aem-article-detail-opp-spider", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/getdataforme~aem-article-detail-opp-spider/runs": { "post": { "operationId": "runs-sync-getdataforme-aem-article-detail-opp-spider", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/getdataforme~aem-article-detail-opp-spider/run-sync": { "post": { "operationId": "run-sync-getdataforme-aem-article-detail-opp-spider", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "properties": { "ProductUrls": { "title": "Product Urls", "minItems": 1, "type": "array", "description": "The product urls for the spider.", "default": [ "https://www.aem.org/news/join-aem%E2%80%99s-member-education-webinar-standards-development-%E2%80%93-autonomy-to-stay-on-top-of-key-industry" ], "items": { "type": "string" } }, "item_limit": { "title": "Item limit", "minimum": 0, "type": "integer", "description": "Maximum items to scrape per actor run. Set to 0 for no limit.", "default": 10 } } }, "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 } } } } } } } } } } ```