# Abckambodza Article Detail Extractor (`getdataforme/abckambodza-article-detail-extractor`) Actor The Abckambodza Article Detail Extractor efficiently extracts comprehensive article details from the Abckambodza website, offering high-quality data with customizable parameters.... - **URL**: https://apify.com/getdataforme/abckambodza-article-detail-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 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 --- ### PART 1: Generate README.md ## Abckambodza Article Detail Extractor The Abckambodza Article Detail Extractor is a powerful tool designed to efficiently extract detailed information from articles on the Abckambodza website. This Actor streamlines data extraction, ensuring high-quality and reliable outputs for various applications. ### Features - **Comprehensive Data Extraction**: Captures all relevant article details including title, content, tags, and related articles. - **High-Quality Outputs**: Ensures accurate and complete data retrieval with minimal errors. - **Flexible Configuration**: Allows customization of input parameters to suit specific needs. - **Efficient Performance**: Optimized for speed and reliability in processing large volumes of data. - **User-Friendly Interface**: Easy setup and execution, even for non-technical users. ### Input Parameters Table | Parameter | Type | Required | Description | Example | |-----------------|----------|----------|-----------------------------------------------------------------------------|------------------------------| | `url` | String | Yes | The URL of the article to extract details from. | `"https://abckambodza.pages.dev/angkor-wat/ta-nei"` | | `maxPages` | Integer | No | Maximum number of pages to scrape (default is 1). | `5` | | `timeout` | Integer | No | Timeout in seconds for each page request. | `30` | | `userAgent` | String | No | Custom User-Agent string for the HTTP requests. | `"Mozilla/5.0"` | | `proxy` | String | No | Proxy server to use for requests (e.g., "http://proxyserver:port"). | `"http://example.com:8080"` | ### Example Usage #### Input JSON ```json { "url": "https://abckambodza.pages.dev/angkor-wat/ta-nei", "maxPages": 1, "timeout": 30, "userAgent": "Mozilla/5.0", "proxy": "http://example.com:8080" } ```` #### Output JSON ```json { "title": "Ta Nei \u2013 cicha \u015bwi\u0105tynia Angkor Wat", "content": "Spokojna i cichutka, w przeciwieństwie do wielu innych \u015bwiątni Angkoru. Ta Nei jest jedną z tych budowli, które nie są tak znane, ale warto odwiedzić. Warto zwiedzać ją bez pośpiechu i cieszyć się spokojem, który tu panuje...", "tags": [ "Kambod\u017ca", "Przewodnik po Kambod\u017cy", "Angkor Wat", "\u015awi\u0105tynie Kambod\u017cy", "\u015awi\u0105tynie Angkoru", "Ta Nei" ], "related_articles": [ { "url": "https://abckambodza.pages.dev/angkor-wat/prasat-chrung", "title": "Prasat Chrung \u2013 ukryte \u015bwi\u0105tynie na rogach Angkor Thom" } ] } ``` ### Use Cases - **Market Research and Analysis**: Extract detailed article data for market insights. - **Competitive Intelligence**: Monitor competitor content and strategies. - **Price Monitoring**: Track pricing information in articles. - **Content Aggregation**: Compile comprehensive datasets from multiple articles. - **Academic Research**: Gather data for scholarly analysis. - **Business Automation**: Automate data extraction processes for efficiency. ### Installation and Usage 1. Search for "Abckambodza Article Detail Extractor" 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 includes: - `title`: The title of the article. - `content`: Full text content of the article. - `tags`: List of tags associated with the article. - `related_articles`: Information on related articles. ### 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! *** ### PART 2: Generate Description (STRICT: 280-295 characters ONLY) # Actor input Schema ## `Urls` (type: `array`): The 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 { "Urls": [ "https://abckambodza.pages.dev/angkor-wat/ta-nei/", "https://abckambodza.pages.dev/angkor-wat/prasat-prei-monti/", "https://abckambodza.pages.dev/angkor-wat/angkor-thom-serce-angkoru/" ], "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/abckambodza-article-detail-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/abckambodza-article-detail-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/abckambodza-article-detail-extractor --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=getdataforme/abckambodza-article-detail-extractor", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Abckambodza Article Detail Extractor", "description": "The Abckambodza Article Detail Extractor efficiently extracts comprehensive article details from the Abckambodza website, offering high-quality data with customizable parameters....", "version": "0.0", "x-build-id": "3hwreGadxbiEMRQAe" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/getdataforme~abckambodza-article-detail-extractor/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-getdataforme-abckambodza-article-detail-extractor", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/getdataforme~abckambodza-article-detail-extractor/runs": { "post": { "operationId": "runs-sync-getdataforme-abckambodza-article-detail-extractor", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/getdataforme~abckambodza-article-detail-extractor/run-sync": { "post": { "operationId": "run-sync-getdataforme-abckambodza-article-detail-extractor", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "Urls": { "title": "Urls", "minItems": 1, "type": "array", "description": "The urls for the spider.", "default": [ "https://abckambodza.pages.dev/angkor-wat/ta-nei/", "https://abckambodza.pages.dev/angkor-wat/prasat-prei-monti/", "https://abckambodza.pages.dev/angkor-wat/angkor-thom-serce-angkoru/" ], "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 } } } } } } } } } } ```