# Zalo Discovery Extractor (`getdataforme/zalo-discovery-extractor`) Actor Extract valuable data from Zalo posts with high accuracy and efficiency. Tailor extraction parameters, process large datasets quickly, and export in JSON, CSV, or Excel for market research, competitive intelligence, and more.... - **URL**: https://apify.com/getdataforme/zalo-discovery-extractor.md - **Developed by:** [GetDataForMe](https://apify.com/getdataforme) (community) - **Categories:** AI, Automation, E-commerce - **Stats:** 3 total users, 2 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 ## Zalo Discovery Extractor Welcome to the Zalo Discovery Extractor! This powerful tool is designed to extract valuable data from Zalo posts, providing insights and information that can drive your business forward. Whether you're conducting market research or analyzing competitive intelligence, this extractor ensures high-quality, reliable data at your fingertips. ### Features - **Comprehensive Data Extraction**: Automatically retrieves detailed information from Zalo posts. - **High-Quality Data**: Ensures accuracy and reliability with advanced parsing techniques. - **Customizable Parameters**: Tailor the extraction process to meet specific needs. - **Efficient Performance**: Fast processing times for large datasets. - **Multiple Output Formats**: Export data in JSON, CSV, or Excel formats. ### Input Parameters Table | Parameter | Type | Required | Description | Example | |-------------|---------|----------|--------------------------------------------------|------------------| | `url` | String | Yes | URL of the Zalo post to extract. | `"https://zalo.me/..."` | | `max_pages` | Integer | No | Maximum number of pages to scrape. | `5` | ### Example Usage ```json { "url": "https://zalo.me/vi/post/zalo-lua-chon-ai-nhat-viet-nam", "max_pages": 1 } ```` **Example Output:** ```json { "items": [ { "title": "Zalo l\u1ef1a ch\u1ecdn AI nh\u00e2t Vi\u1ec7t Nam", "description": "\u0110\u1ebfn n\u0103m 2024, Zalo ti\u1ebfp t\u1ee5c c\u00f4ng b\u1ed1 m\u00f4 h\u00ecnh 13 t\u1ef7 tham s\u1ed1...", "product_url": "https://zalo.me/vi/post/zalo-lua-chon-ai-nhat-viet-nam", "image_urls": [ "https://zalo-site.zadn.vn/_next/static/media/tech-zalo-llm.2f3e7b1a.webp" ], "logo": null, "video": null, "video_poster": null, "full_description": "\u0110\u00e2y l\u00e0 minh ch\u1ee9ng r\u00f5 r\u00e0ng r\u1eb1ng tr\u00ecnh \u0111\u1ed9 k\u1ef9 thu\u1eadt c\u1ee7a k\u1ef9 s\u01b0 Vi\u1ec7t Nam...", "actor_id": "s7CYPulVN9HkY2dPo", "run_id": "1gg7rGI0bnQHk87fB" }, { "title": "Kiki Info", "description": "Kiki Info t\u00edch h\u1ee3p trong Zalo: gi\u1ea3i \u0111\u00e1p th\u1eafc m\u1eafc, so\u1ea1n th\u1ea3o n\u1ed9i dung...", "product_url": "https://zalo.me/vi/post/kiki-info", "image_urls": [ "https://zalo-site.zadn.vn/_next/static/media/tech-kiki-info.5aa1b0ec.webp" ], "logo": null, "video": null, "video_poster": null, "full_description": "T\u00ecm ki\u1ebfm th\u00f4ng minh, tr\u1ea3 l\u1eddi nhanh ch\u00f3ng Kiki Info \u0111\u01b0\u1ee3c ra m\u1eaft...", "actor_id": "s7CYPulVN9HkY2dPo", "run_id": "1gg7rGI0bnQHk87fB" } ] } ``` ### Use Cases - **Market Research and Analysis**: Gain insights into market trends and consumer behavior. - **Competitive Intelligence**: Monitor competitors' activities and strategies. - **Price Monitoring**: Track pricing changes across different products. - **Content Aggregation**: Collect and organize content for analysis or reporting. - **Academic Research**: Use data for research projects and studies. - **Business Automation**: Automate data collection processes to save time. ### Installation and Usage 1. Search for "Zalo Discovery 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 is structured with key fields such as `title`, `description`, `product_url`, `image_urls`, and more. Each item represents a Zalo post with detailed information extracted for further analysis. ### Support Section ```markdown ### Support For custom/simplified outputs or bug reports, please contact: - Email: support@getdataforme.com - Subject line: "custom support" - Contact form: 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://zalo.me/vi/ai" ], "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/zalo-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/zalo-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/zalo-discovery-extractor --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=getdataforme/zalo-discovery-extractor", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Zalo Discovery Extractor", "description": "Extract valuable data from Zalo posts with high accuracy and efficiency. Tailor extraction parameters, process large datasets quickly, and export in JSON, CSV, or Excel for market research, competitive intelligence, and more....", "version": "0.0", "x-build-id": "joNWrxjOMh8KetvDT" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/getdataforme~zalo-discovery-extractor/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-getdataforme-zalo-discovery-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/getdataforme~zalo-discovery-extractor/runs": { "post": { "operationId": "runs-sync-getdataforme-zalo-discovery-extractor", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/getdataforme~zalo-discovery-extractor/run-sync": { "post": { "operationId": "run-sync-getdataforme-zalo-discovery-extractor", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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://zalo.me/vi/ai" ], "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 } } } } } } } } } } ```