# StockX Release Calendar Scraper (`xtracto/stockx-release-calendar-scraper`) Actor Pull every upcoming and recently-released drop on StockX with release dates, pre-release bid/ask hype, and category metadata. - **URL**: https://apify.com/xtracto/stockx-release-calendar-scraper.md - **Developed by:** [Xtractoo](https://apify.com/xtracto) (community) - **Categories:** E-commerce, Lead generation, Other - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $3.00 / 1,000 results This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. 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 ## StockX Release Calendar Scraper Pull every upcoming and recently-released drop on StockX with release dates, pre-release bid/ask signals, and full category metadata. ### What you can do with it - **Drop prioritization** — rank tomorrow's releases by pre-release highest bid to decide which drops are worth targeting. - **Resell allocation** — combine `releaseDate` with pre-release ask/bid to plan inventory ahead of time. - **Hype detection** — `preReleaseHighestBid` on items with days until release > 0 is a clean leading indicator of demand. - **Content & editorial** — power "Drops This Week" newsletters, calendars, and apps with fresh structured data. - **Cross-channel alerts** — trigger notifications when an upcoming item crosses a price threshold before release. ### Features - **7 categories supported**: `sneakers`, `apparel`, `electronics`, `accessories`, `collectibles`, `shoes`, `trading-cards`. - **Pagination** — crawls up to N pages per category; stops early when a page has no items. - **Per-release data (20+ fields)**: - Identity: `productId`, `uuid`, `urlKey`, `url`, `title`, `brand`, `model`, `gender`, `primaryCategory`, `productCategory`. - Release timing: `releaseDate` (ISO yyyy-mm-dd), `daysUntilRelease` (negative for already-released items). - Pre-release demand: `preReleaseHighestBid`, `preReleaseLowestAsk`, `annualAveragePrice`, `annualSalesCount`. - Traits: full traits map including colorway, style ID, retail price. - Media: `image`, `thumbUrl`. - **Default Dataset output** — JSON / CSV / Excel / RSS / HTML export. ### Input ```json { "categories": ["sneakers", "apparel"], "maxPagesPerCategory": 3, "maxConcurrency": 2, "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": ["RESIDENTIAL"] } } ```` | Field | Type | Description | | --- | --- | --- | | `categories` | string\[] | One or more of: `sneakers`, `apparel`, `electronics`, `accessories`, `collectibles`, `shoes`, `trading-cards`. | | `maxPagesPerCategory` | int | Pages per category (default 3). | | `maxConcurrency` | int | Parallel category workers (default 2). | | `maxRequestRetries` | int | Per-request retry budget (default 6). | | `proxyConfiguration` | proxy | Apify Proxy or custom list. | ### Sample Output ```json { "category": "sneakers", "page": 1, "urlKey": "nike-air-max-1-86-og-big-bubble-sport-red", "url": "https://stockx.com/nike-air-max-1-86-og-big-bubble-sport-red", "isAd": false, "scrapedAt": "2026-05-09T10:05:17Z", "sourceUrl": "https://stockx.com/releases/upcoming?category=sneakers", "node": { "productId": "3b7a2e14-f8c9-4d5a-b3e7-9c0f2d8a1b46", "title": "Nike Air Max 1 '86 OG Big Bubble Sport Red", "brand": "Nike", "model": "Air Max 1", "gender": "men", "primaryCategory": "Nike", "productCategory": "sneakers", "market": { "state": { "lowestAsk": { "amount": 185 }, "highestBid": { "amount": 138 } } }, "traits": [ { "name": "Release Date", "value": "2026-05-17" }, { "name": "Colorway", "value": "SPORT RED/WHITE-SPORT RED" }, { "name": "Retail Price", "value": "$150" } ] } } ``` ### Notes - `daysUntilRelease` is computed at scrape time relative to UTC. - Public data only — no StockX account required. # Actor input Schema ## `categories` (type: `array`): Pick one or more StockX upcoming-releases categories to crawl. Each is fetched as `https://stockx.com/releases/upcoming?category=` with pagination via `&page=N`. ## `maxPagesPerCategory` (type: `integer`): How many pages to walk per category. Stops early when a page returns no items. ## `maxConcurrency` (type: `integer`): Maximum number of parallel requests. ## `maxRequestRetries` (type: `integer`): How many times a request will be retried before giving up. ## `proxyConfiguration` (type: `object`): Apify Proxy or your own proxy list. RESIDENTIAL group recommended. ## Actor input object example ```json { "categories": [ "sneakers" ], "maxPagesPerCategory": 3, "maxConcurrency": 2, "maxRequestRetries": 6, "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } } ``` # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } }; // Run the Actor and wait for it to finish const run = await client.actor("xtracto/stockx-release-calendar-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${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 = { "proxyConfiguration": { "useApifyProxy": True, "apifyProxyGroups": ["RESIDENTIAL"], } } # Run the Actor and wait for it to finish run = client.actor("xtracto/stockx-release-calendar-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 '{ "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } }' | apify call xtracto/stockx-release-calendar-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=xtracto/stockx-release-calendar-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "StockX Release Calendar Scraper", "description": "Pull every upcoming and recently-released drop on StockX with release dates, pre-release bid/ask hype, and category metadata.", "version": "1.0", "x-build-id": "AHsoSQNL1Sa5DOWbm" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/xtracto~stockx-release-calendar-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-xtracto-stockx-release-calendar-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/xtracto~stockx-release-calendar-scraper/runs": { "post": { "operationId": "runs-sync-xtracto-stockx-release-calendar-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/xtracto~stockx-release-calendar-scraper/run-sync": { "post": { "operationId": "run-sync-xtracto-stockx-release-calendar-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "categories" ], "properties": { "categories": { "title": "Categories", "uniqueItems": true, "type": "array", "description": "Pick one or more StockX upcoming-releases categories to crawl. Each is fetched as `https://stockx.com/releases/upcoming?category=` with pagination via `&page=N`.", "items": { "type": "string", "enum": [ "sneakers", "apparel", "electronics", "accessories", "collectibles", "shoes", "trading-cards" ], "enumTitles": [ "Sneakers", "Apparel", "Electronics", "Accessories", "Collectibles", "Shoes", "Trading Cards" ] }, "default": [ "sneakers" ] }, "maxPagesPerCategory": { "title": "Max pages per category", "minimum": 1, "maximum": 50, "type": "integer", "description": "How many pages to walk per category. Stops early when a page returns no items.", "default": 3 }, "maxConcurrency": { "title": "Max concurrency", "type": "integer", "description": "Maximum number of parallel requests.", "default": 2 }, "maxRequestRetries": { "title": "Max retries", "type": "integer", "description": "How many times a request will be retried before giving up.", "default": 6 }, "proxyConfiguration": { "title": "Proxy configuration", "type": "object", "description": "Apify Proxy or your own proxy list. RESIDENTIAL group recommended." } } }, "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 } } } } } } } } } } ```