# Zigzag Scraper — Korean Women's Fashion Search & Prices (`kdatafactory/zigzag-scraper`) Actor Scrape Zigzag (지그재그), Korea's largest women's fashion marketplace with 8,000+ shops. Keyword search or ranked feeds via Zigzag's own GraphQL API: product name, shop, KRW price, discount rate, review score and count, image and URL as clean JSON. For K-fashion research and price monitoring. - **URL**: https://apify.com/kdatafactory/zigzag-scraper.md - **Developed by:** [Seok June Park](https://apify.com/kdatafactory) (community) - **Categories:** E-commerce, Automation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $2.00 / 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 ## Zigzag Product Scraper 👗 Scrape **searched** and **ranked** women's-fashion products from [Zigzag](https://zigzag.kr) (지그재그) — Korea's largest women's-fashion marketplace, aggregating **8,000+ shops** — as clean, structured JSON. Get product names, shop names, KRW prices, discount rates, review scores, review counts, and images in one call. Built for **K-fashion trend research**, **dropshipping product sourcing**, and **price monitoring**. > **Try it free.** Apify's free plan includes $5 of monthly platform credit — roughly **2,500 results** from this actor, no credit card required. Set your input, click Start, and export JSON/CSV/Excel. --- ### What it does This actor pulls product data directly from Zigzag's public GraphQL API — the same `GetSearchResult` operation that powers the zigzag.kr web app — so results are fast and complete, with clean cursor pagination. Two modes: - **Search** — every product matching a keyword (e.g. `원피스` dress, `니트` knit, `nike`, `가디건` cardigan). - **Ranking** — the same keyword feed, but each product is assigned a `rank` from its position in Zigzag's default recommendation order (Zigzag ranks its feed by a popularity/relevance blend). --- ### Input | Field | Type | Description | |-------|------|-------------| | `mode` | string | `"search"` or `"ranking"`. | | `query` | string | The search keyword. **Required.** e.g. `원피스`, `니트`, `nike`. | | `maxItems` | integer | Max products to collect. Default `100`. | | `proxyConfiguration` | object | Apify Proxy settings. Optional — runs direct if omitted. | #### Input example ```json { "mode": "ranking", "query": "원피스", "maxItems": 100 } ```` ```json { "mode": "search", "query": "니트", "maxItems": 200 } ``` *** ### Output Each product is one dataset record. Prices are in KRW (Korean won). `rating` is Zigzag's review score (0–5). `rank` is populated in ranking mode only. Prices are reconstructed from Zigzag's `final_price` (what the customer pays) and `discount_rate`: when a product is discounted, `price_krw` is the original list price and `sale_price_krw` is the discounted price; when not discounted, `price_krw` holds the price and `sale_price_krw` is `null`. ```json { "source": "zigzag", "product_id": "169746777", "name": "[🤍여름/MADE]라미 쉬폰 미니 원피스(+NEW컬러)(미니원피스 하객룩 여름원피스)", "brand": "메이빈스", "price_krw": 69895, "sale_price_krw": 39840, "discount_rate": 43, "rating": 4.8, "review_count": 111, "category": null, "rank": 1, "url": "https://store.zigzag.kr/app/catalog/products/169746777", "image_url": "https://cf.image-farm.s.zigzag.kr/original/ad/2026/6/12/202606121459580334_46155.png?width=720&height=720&quality=80&format=jpeg", "scraped_at": "2026-07-09T10:00:46+09:00" } ``` A full 40-item sample from a real run is in [`samples/sample-output.json`](samples/sample-output.json). | Field | Meaning | |-------|---------| | `source` | Always `"zigzag"`. | | `product_id` | Zigzag catalog product id. | | `name` | Product name. | | `brand` | Shop / brand storefront name on Zigzag. | | `price_krw` | Original list price (KRW). | | `sale_price_krw` | Discounted price if on sale, else `null`. | | `discount_rate` | Percent off (integer), or `null` when not discounted. | | `rating` | Zigzag review score, 0–5 (`null` if none). | | `review_count` | Number of reviews (`null` if none). | | `category` | Always `null` — the search feed carries no per-item category label. | | `rank` | Popularity/relevance rank (ranking mode only). | | `url` | Product page URL. | | `image_url` | Thumbnail image URL. | | `scraped_at` | ISO-8601 timestamp (KST, UTC+9). | #### A note on what this actor does **not** return To keep the data honest and privacy-safe, the actor deliberately does **not** sell fields that don't reliably populate or that identify people: - **`category`** is always `null` on the search feed — it is kept in the schema for contract compatibility but is not a sold field. - **Seller/reviewer identity** (nicknames, ids, profiles) is never collected — only shop storefront names and item/price data. *** ### Use cases - **K-fashion trend research** — track which shops, styles, and price points dominate Zigzag's women's-fashion feed for a given keyword. - **Dropshipping / product sourcing** — build a catalog of trending Korean women's-fashion products with images, shops, and prices to source or resell. - **Price & discount monitoring** — watch `price_krw` vs `sale_price_krw` and `discount_rate` over time to catch drops and benchmark competitor pricing. - **AI agents & datasets** — feed structured fashion data into recommendation models, market dashboards, or LLM agents. *** ### ❓ FAQ **Is it legal to scrape this data?** This actor collects only public, non-personal catalog data — the same product listings any Zigzag visitor sees without logging in. No personal data is collected. You are responsible for how you use the data; see the legality note below. **What does it cost in practice?** $2.00 per 1,000 results (launch pricing) + a few cents of platform usage. Example: a 500-result daily pull costs about $1.00/day. Apify's free $5 monthly credit covers ~2,500 results. **Do I need to configure proxies?** No — the default settings work out of the box. For heavy pulls (high `maxItems`), enabling Apify Proxy with the `RESIDENTIAL` group is recommended as optional scaling advice; see the proxy note below. **How fresh is the data?** Every run scrapes the live site at run time. Schedule the actor for recurring snapshots. **What is NOT included?** `category` is always `null` — Zigzag's search feed carries no per-item category label, so it is kept only for schema compatibility. Seller/reviewer identity (nicknames, ids, profiles) is never collected — only shop storefront names and item/price data. *** ### 🇰🇷 More Korean data actors This actor is part of a suite of Korean-platform scrapers by the same maintainer: - [musinsa-scraper](https://apify.com/kdatafactory/musinsa-scraper) — Musinsa fashion products, rankings, and prices. - [29cm-scraper](https://apify.com/kdatafactory/29cm-scraper) — 29CM curated fashion & lifestyle product data. - [wconcept-scraper](https://apify.com/kdatafactory/wconcept-scraper) — W Concept designer fashion catalog and pricing. Browse all: [apify.com/kdatafactory](https://apify.com/kdatafactory) *** ### Rate limiting & legality - The actor collects **only public, non-authenticated data**. It never logs in and never touches private endpoints. - **No personal data** is collected — no seller or reviewer names, profiles, or IDs. Only shop storefront names and item/price data. - Requests are rate-limited: one page at a time with a ≥ 500 ms delay between requests, to stay gentle on Zigzag's servers. - You are responsible for using the data in line with Zigzag's terms of service and applicable law. #### ⚠️ Proxy recommendation Zigzag may block datacenter IPs or high request volumes. For reliable runs — especially at higher `maxItems` — enable **Apify Proxy with the `RESIDENTIAL` group**. The actor automatically uses the proxy configuration you provide (via `proxyConfiguration` in input) and falls back to a direct connection when a proxy tunnel fails or none is set. If you see repeated `GraphQL HTTP 403/429` errors in the log, switch on residential proxy. *** *If this actor saves you time, a rating on the [Store page](https://apify.com/kdatafactory/zigzag-scraper) helps a solo maintainer a lot. Found an issue? Open it in the Issues tab — I respond fast.* # Actor input Schema ## `mode` (type: `string`): What to scrape. 'search' returns products matching a keyword. 'ranking' returns the same keyword feed but assigns each product a popularity rank from its position in Zigzag's default recommendation order. ## `query` (type: `string`): The search keyword to scrape (e.g. '원피스' dress, '니트' knit, 'nike', '가디건' cardigan). Required for both modes. ## `maxItems` (type: `integer`): Maximum number of products to collect. ## `proxyConfiguration` (type: `object`): Apify Proxy settings. RESIDENTIAL is recommended for large runs. If omitted, the actor runs on a direct connection. ## Actor input object example ```json { "mode": "search", "query": "원피스", "maxItems": 100, "proxyConfiguration": { "useApifyProxy": true } } ``` # 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 = { "query": "원피스" }; // Run the Actor and wait for it to finish const run = await client.actor("kdatafactory/zigzag-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 = { "query": "원피스" } # Run the Actor and wait for it to finish run = client.actor("kdatafactory/zigzag-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 '{ "query": "원피스" }' | apify call kdatafactory/zigzag-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=kdatafactory/zigzag-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Zigzag Scraper — Korean Women's Fashion Search & Prices", "description": "Scrape Zigzag (지그재그), Korea's largest women's fashion marketplace with 8,000+ shops. Keyword search or ranked feeds via Zigzag's own GraphQL API: product name, shop, KRW price, discount rate, review score and count, image and URL as clean JSON. For K-fashion research and price monitoring.", "version": "0.1", "x-build-id": "ZntMMihYtniwjZryL" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/kdatafactory~zigzag-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-kdatafactory-zigzag-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/kdatafactory~zigzag-scraper/runs": { "post": { "operationId": "runs-sync-kdatafactory-zigzag-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/kdatafactory~zigzag-scraper/run-sync": { "post": { "operationId": "run-sync-kdatafactory-zigzag-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "query" ], "properties": { "mode": { "title": "Mode", "enum": [ "search", "ranking" ], "type": "string", "description": "What to scrape. 'search' returns products matching a keyword. 'ranking' returns the same keyword feed but assigns each product a popularity rank from its position in Zigzag's default recommendation order.", "default": "search" }, "query": { "title": "Keyword", "type": "string", "description": "The search keyword to scrape (e.g. '원피스' dress, '니트' knit, 'nike', '가디건' cardigan). Required for both modes." }, "maxItems": { "title": "Max items", "minimum": 1, "maximum": 5000, "type": "integer", "description": "Maximum number of products to collect.", "default": 100 }, "proxyConfiguration": { "title": "Proxy configuration", "type": "object", "description": "Apify Proxy settings. RESIDENTIAL is recommended for large runs. If omitted, the actor runs on a direct connection.", "default": { "useApifyProxy": true } } } }, "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 } } } } } } } } } } ```