# Uniqlo Product Scraper (`gauzy_penguin/uniqlo-scraper`) Actor Scrapes product listings from Uniqlo search results. Supports keyword search, categories, pagination, and rate-limit handling. Designed for stable, production-scale scraping. - **URL**: https://apify.com/gauzy\_penguin/uniqlo-scraper.md - **Developed by:** [locas mora](https://apify.com/gauzy_penguin) (community) - **Categories:** E-commerce, AI, Automation - **Stats:** 3 total users, 2 monthly users, 90.9% runs succeeded, 4 bookmarks - **User rating**: 5.00 out of 5 stars ## Pricing from $1.00 / 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. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. 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 ## Uniqlo Scraper ### Overview The **Uniqlo Scraper** is a production-grade Apify actor designed to extract product listings from **uniqlo.com** search results and category pages. This actor is built for **stability, scalability, and ease of use**, providing clean, structured output suitable for analytics, price monitoring, research, and downstream automation. It supports keyword search, category browsing, sorting, pagination, and rate-limit handling. --- ### Key Features - 🔍 Keyword-based product search - 🗂 Category page browsing - ↕️ Multiple sorting modes (relevance, price, newest, top rated) - 📦 Clean, simplified output schema - 🔁 Automatic pagination - 🛡 Built-in retry and rate-limit handling - 🚀 Production-ready and Apify Store compliant --- ### How It Works 1. The actor initializes with your keywords or the selected category. 2. Results are paginated automatically until the requested limit is reached. 3. Each item is simplified into a clean, user-friendly structure. 4. Data is stored in the default Apify dataset. --- ### Input Configuration #### Required Fields | Field | Type | Description | |-------|------|-------------| | `mode` | string | Scraping mode: `search` or `category` | #### Optional Fields | Field | Type | Description | |-------|------|-------------| | `queries` | array | List of search terms — used when `mode = search` (e.g. `["Shorts", "Shirts"]`) | | `category` | string | Category to scrape — used when `mode = category` (see options below) | | `sortBy` | string | Sorting mode (see options below) | | `maxItems` | integer | Maximum number of products to scrape per query or category (min: 100, default: 200) | #### Sorting Options (`sortBy`) - Relevance (default) - New Arrivals - Price low to high - Price high to low - Top Rated #### Available Categories ##### Women - T-Shirts & Sweats - Shirts & Blouses - Sweaters & Cardigans - Bottoms ... ##### Men - T-Shirts & Sweats - Shirts - Sweaters & Cardigans - Pants ... ##### Kids - T-Shirts, Sweats & Fleece - Shirts & Blouses - Jeans & Pants - Dresses ... ##### Baby - Newborn & Infant (0-24M) - Toddler (6M-5Y) ... --- ### Output Data Structure The actor outputs a **simplified, stable schema** designed for analysts and automation pipelines. #### Example Output ```json { "productId": "E470182-000", "name": "Flannel Shirt", "gender": "MEN", "price": { "currency": "USD", "symbol": "$", "base": 49.9, "promo": null, "isDualPrice": false }, "rating": { "average": 4.8, "count": 53 }, "colors": [ { "code": "COL69", "displayCode": "69", "name": "NAVY", "filterCode": "BLUE" }, { "code": "COL01", "displayCode": "01", "name": "OFF WHITE", "filterCode": "WHITE" } ], "sizes": [ { "code": "SMA001", "displayCode": "001", "name": "XXS" }, { "code": "SMA002", "displayCode": "002", "name": "XS" }, { "code": "SMA003", "displayCode": "003", "name": "S" }, { "code": "SMA004", "displayCode": "004", "name": "M" } ], "images": { "main": { "69": { "url": "https://image.uniqlo.com/UQ/ST3/us/imagesgoods/470182/item/usgoods_69_470182_3x4.jpg", "modelGender": "Men" }, "01": { "url": "https://image.uniqlo.com/UQ/ST3/WesternCommon/imagesgoods/470182/item/goods_01_470182_3x4.jpg", "modelGender": null } }, "chips": { "69": "https://image.uniqlo.com/UQ/ST3/WesternCommon/imagesgoods/470182/chip/goods_69_470182_chip.jpg", "01": "https://image.uniqlo.com/UQ/ST3/WesternCommon/imagesgoods/470182/chip/goods_01_470182_chip.jpg" }, "sub": [ { "url": "https://image.uniqlo.com/UQ/ST3/WesternCommon/imagesgoods/470182/sub/goods_470182_sub13_3x4.jpg", "videoUrl": "https://image.uniqlo.com/UQ/ST3/us/imagesgoods/470182/subvideo/usgoods_470182_sub13_video_3x4.mp4" } ] }, "representativeColor": { "code": "COL69", "displayCode": "69", "name": "NAVY", "filterCode": "BLUE" }, "inStock": true, "promotionText": null, "storeStockOnly": false } ```` *** ### Use Cases 1. 📊 Price tracking and market analysis 2. 🛒 Product discovery and catalog building 3. 📈 Trend and inventory monitoring 4. 🤖 Feeding downstream automation pipelines 5. 🧠 Dataset creation and enrichment *** ### Performance & Reliability 1. Automatic retries with exponential backoff 2. Graceful handling of rate limits (403 / 429) 3. Batched dataset writes for efficiency 4. Designed for long-running and large-scale jobs *** ### Support & Maintenance This actor is actively maintained and designed for production usage. For issues or feature requests, please use the Apify platform issue tracker. *** ### Final Notes This actor prioritizes: 1. Data clarity 2. Operational reliability 3. Professional usability It is suitable for both individual users and enterprise-scale workflows. # Actor input Schema ## `mode` (type: `string`): Choose how to scrape data ## `queries` (type: `array`): List of search terms (used when mode = search) ## `category` (type: `string`): Category to scrape (used when mode = category) ## `sortBy` (type: `string`): Choose how results are sorted. ## `maxItems` (type: `integer`): Maximum number of products to scrape per query or category ## Actor input object example ```json { "mode": "search", "queries": [ "Shorts", "Shirts" ], "category": "22210,23295,,", "sortBy": "0", "maxItems": 200 } ``` # 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 = { "queries": [ "Shorts", "Shirts" ] }; // Run the Actor and wait for it to finish const run = await client.actor("gauzy_penguin/uniqlo-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 = { "queries": [ "Shorts", "Shirts", ] } # Run the Actor and wait for it to finish run = client.actor("gauzy_penguin/uniqlo-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 '{ "queries": [ "Shorts", "Shirts" ] }' | apify call gauzy_penguin/uniqlo-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=gauzy_penguin/uniqlo-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Uniqlo Product Scraper", "description": "Scrapes product listings from Uniqlo search results. Supports keyword search, categories, pagination, and rate-limit handling. Designed for stable, production-scale scraping.", "version": "1.0", "x-build-id": "zSSa8sfq2B95VNsuq" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/gauzy_penguin~uniqlo-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-gauzy_penguin-uniqlo-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/gauzy_penguin~uniqlo-scraper/runs": { "post": { "operationId": "runs-sync-gauzy_penguin-uniqlo-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/gauzy_penguin~uniqlo-scraper/run-sync": { "post": { "operationId": "run-sync-gauzy_penguin-uniqlo-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", "required": [ "mode" ], "properties": { "mode": { "title": "Scraping Mode", "enum": [ "search", "category" ], "type": "string", "description": "Choose how to scrape data", "default": "search" }, "queries": { "title": "Search Queries", "type": "array", "description": "List of search terms (used when mode = search)", "items": { "type": "string" } }, "category": { "title": "Category to scrape", "enum": [ "22210,23295,,", "22210,95663,,", "22210,95664,,", "22210,23296,,", "22210,23294,,", "22210,23297,,", "22210,23298,,", "22210,23300,,", "22210,23299,,", "22210,81258,,", "22210,23302,,", "22210,70666,,", "22210,70665,,", "22210,70667,,", "22210,106612,,", "22211,23305,,", "22211,95669,,", "22211,95668,,", "22211,23306,,", "22211,23304,,", "22211,23307,,", "22211,23309,,", "22211,23308,,", "22211,81259,,", "22211,23310,,", "22211,70669,,", "22211,70668,,", "22211,70670,,", "22211,106613,,", "22212,23312,,", "22212,103470,,", "22212,23313,,", "22212,23314,,", "22212,103469,,", "22212,23311,,", "22212,23315,,", "22212,23317,,", "22212,23318,,", "22212,70671,,", "22212,70672,,", "22212,106614,,", "22213,23319,,", "22213,23321,," ], "type": "string", "description": "Category to scrape (used when mode = category)", "default": "22210,23295,," }, "sortBy": { "title": "Sort Results By", "enum": [ "0", "1", "2", "3", "4" ], "type": "string", "description": "Choose how results are sorted.", "default": "0" }, "maxItems": { "title": "Max Items", "minimum": 100, "type": "integer", "description": "Maximum number of products to scrape per query or category", "default": 200 } } }, "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 } } } } } } } } } } ```