# Project Cheerio Crawler Typescript (`getdataforme/shafa-seller-detail-ec-scraper`) Actor Project Cheerio Crawler Typescript is a powerful web scraping tool using the Cheerio library in TypeScript to efficiently extract structured data from websites. It excels at parsing HTML for online profiles and user-generated content with high-quality, accurate outputs.... - **URL**: https://apify.com/getdataforme/shafa-seller-detail-ec-scraper.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 ## Project Cheerio Crawler Typescript ### Introduction Project Cheerio Crawler Typescript is an advanced web scraping tool designed to efficiently extract structured data from websites using the Cheerio library in a TypeScript environment. This actor excels at parsing HTML documents, making it ideal for gathering detailed information about online profiles and user-generated content. ### Features - **Efficient Data Extraction**: Utilizes the Cheerio library for fast and reliable HTML parsing. - **High-Quality Output**: Ensures accurate and structured data extraction with minimal errors. - **Customizable Inputs**: Flexible input parameters allow tailored scraping configurations. - **Scalable Performance**: Optimized to handle large volumes of data efficiently. - **User-Friendly Interface**: Easy setup and execution within the Apify platform. ### Input Parameters | Parameter | Type | Required | Description | Example | |-----------|--------|----------|--------------------------------------------------|---------| | `url` | String | Yes | The URL of the webpage to scrape. | `"https://example.com/profiles"` | ### Example Usage #### Input JSON ```json { "url": "https://example.com/profiles" } ```` #### Output JSON ```json [ { "type": "profile", "id": 7397050, "shopName": null, "username": "i9839560", "firstName": "Ірина", "lastName": "Гречуха", "showRealName": "SHOW_REAL_NAME_FOR_NOBODY", "sellerRatingInfo": { "overallRating": "5.0", "reviewsCount": 44 }, "followersCount": 95, "middleResponseTime": "Відповідає протягом 12ти годин", "thumbnail": "https://avatars.shafastatic.net/7397050_new_avatar_type1777892753", "sellerRating": 5, "soldProducts": 130, "lastVisit": 1783066577, "deltaDateJoined": "3 роки", "fraudWarning": false, "ban": null, "gender": "GENDER_FEMALE", "isSubscribed": false, "productsCount": 166, "city": { "id": 5, "name": "Київ" }, "hasRecentActivity": true, "orderRate": "75", "isTopSeller": false } ] ``` ### Use Cases - **Market Research and Analysis**: Gather competitor insights and market trends. - **Competitive Intelligence**: Monitor competitors' online presence and strategies. - **Price Monitoring**: Track pricing changes across e-commerce platforms. - **Content Aggregation**: Collect and organize user-generated content for analysis. - **Academic Research**: Support studies in social sciences with real-world data. - **Business Automation**: Automate data collection processes to enhance efficiency. ### Installation and Usage 1. Search for "Project Cheerio Crawler Typescript" 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 of objects, each representing a profile with fields such as `id`, `username`, `firstName`, `lastName`, and more. Key fields include: - **`type`**: Type of data extracted (e.g., "profile"). - **`id`**: Unique identifier for the profile. - **`sellerRatingInfo`**: Contains `overallRating` and `reviewsCount`. - **`city`**: Nested object with `id` and `name`. ### 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! *** ## Description Harness the power of Project Cheerio Crawler Typescript for efficient web scraping with high-quality data extraction. Ideal for market research, competitive intelligence, and price monitoring, this actor offers customizable inputs and scalable performance. Start extracting valuable insights today! # Actor input Schema ## `startUrls` (type: `array`): URLs to start with. ## Actor input object example ```json { "startUrls": [ { "url": "https://shafa.ua/uk/member/i9839560" } ] } ``` # 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 = { "startUrls": [ { "url": "https://shafa.ua/uk/member/i9839560" } ] }; // Run the Actor and wait for it to finish const run = await client.actor("getdataforme/shafa-seller-detail-ec-scraper").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 = { "startUrls": [{ "url": "https://shafa.ua/uk/member/i9839560" }] } # Run the Actor and wait for it to finish run = client.actor("getdataforme/shafa-seller-detail-ec-scraper").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 '{ "startUrls": [ { "url": "https://shafa.ua/uk/member/i9839560" } ] }' | apify call getdataforme/shafa-seller-detail-ec-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=getdataforme/shafa-seller-detail-ec-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Project Cheerio Crawler Typescript", "description": "Project Cheerio Crawler Typescript is a powerful web scraping tool using the Cheerio library in TypeScript to efficiently extract structured data from websites. It excels at parsing HTML for online profiles and user-generated content with high-quality, accurate outputs....", "version": "0.0", "x-build-id": "QlxS9DyF1HAjIplbz" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/getdataforme~shafa-seller-detail-ec-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-getdataforme-shafa-seller-detail-ec-scraper", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/getdataforme~shafa-seller-detail-ec-scraper/runs": { "post": { "operationId": "runs-sync-getdataforme-shafa-seller-detail-ec-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/getdataforme~shafa-seller-detail-ec-scraper/run-sync": { "post": { "operationId": "run-sync-getdataforme-shafa-seller-detail-ec-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "startUrls": { "title": "Start URLs", "type": "array", "description": "URLs to start with.", "items": { "type": "object", "required": [ "url" ], "properties": { "url": { "type": "string", "title": "URL of a web page", "format": "uri" } } } } } }, "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 } } } } } } } } } } ```