# SneakerFiles Release Calendar Scraper (`crawlerbros/sneakerfiles-release-calendar`) Actor Scrape SneakerFiles' sneaker release calendar - upcoming Nike, Air Jordan, adidas and other sneaker drops with release dates, style codes, colorways, retail prices, and images. - **URL**: https://apify.com/crawlerbros/sneakerfiles-release-calendar.md - **Developed by:** [Crawler Bros](https://apify.com/crawlerbros) (community) - **Categories:** Automation, E-commerce, Developer tools - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 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 ## SneakerFiles Release Calendar Scraper Scrape SneakerFiles' sneaker release calendar — upcoming Nike, Air Jordan, adidas, and other brand sneaker drops with release dates, style codes, colorways, retail prices, and images. HTTP-only via the public `sneakerfiles.com` release-date pages. No login, no cookies, no paid proxy required. ### What this actor does - **Full release calendar** — SneakerFiles' combined release-dates page (roughly 11 months of upcoming drops) plus dedicated Nike and Air Jordan calendar pages for maximum coverage of those two brands - **Brand filter** — Nike, Air Jordan, adidas, New Balance, Reebok, Converse, Puma, Saucony, Asics, Vans, or all brands - **Release-date range filter** - **Retail price range filter** - **Sub-line/collection tagging** — Air Jordan 4, Nike Dunk, Nike SB, Nike Air Max, Nike Basketball, Nike Air Force 1, Nike Retro, Nike Kobe, Nike LeBron (when the release belongs to one of these lines) - **Optional retailer purchase links** — each release's own detail page lists confirmed "Where to Buy" retailers (SNKRS, Foot Locker, adidas.com, etc.); opt in via `fetchRetailerLinks` - **Empty fields are omitted** ### Output per release - `title` — sneaker name/colorway headline - `brand` — Nike, Air Jordan, adidas, etc. - `collections[]` — specific sub-line tags (e.g. `["Nike Dunk"]`), when applicable - `releaseDate` (`YYYY-MM-DD`), `releaseMonth` (`YYYY-MM`) - `releaseDateRaw` — original date text, only present if it couldn't be parsed (e.g. a "TBA"-style placeholder) - `colorway` - `styleCode` - `price` (USD) — `priceRaw` instead when the retail price isn't set yet (e.g. `"TBA"`) - `whereToBuy[]` — `{retailer, url}` pairs, only when `fetchRetailerLinks: true` - `imageUrl` - `sourceUrl` — the release's detail page on SneakerFiles - `recordType: "sneakerRelease"`, `scrapedAt` ### Input | Field | Type | Default | Description | |---|---|---|---| | `brand` | string | `all` | Nike / Air Jordan / adidas / New Balance / Reebok / Converse / Puma / Saucony / Asics / Vans / all | | `dateFrom` | string | – | Only releases on/after this date (`YYYY-MM-DD`) | | `dateTo` | string | – | Only releases on/before this date (`YYYY-MM-DD`) | | `minPrice` | int | – | Drop releases priced below this amount (USD) | | `maxPrice` | int | – | Drop releases priced above this amount (USD) | | `maxItems` | int | `100` | Hard cap (1–1000) | | `fetchRetailerLinks` | bool | `false` | Also fetch each release's confirmed retailer purchase links (one extra request per release) | #### Example: all upcoming Nike releases ```json { "brand": "nike", "maxItems": 200 } ```` #### Example: Jordan releases under $200 in a date window ```json { "brand": "air_jordan", "dateFrom": "2026-08-01", "dateTo": "2026-12-31", "maxPrice": 200 } ``` #### Example: full multi-brand calendar ```json { "brand": "all", "maxItems": 300 } ``` ### Use cases - **Release-tracking tools** — power a sneaker drop calendar or reminder app - **Retail/resale intelligence** — monitor upcoming retail prices ahead of resale-market pricing - **Content sites** — auto-populate a brand's or a silhouette's upcoming-release list - **Inventory planning** — retailers/boutiques planning stock ahead of major drops ### Data source / limitations - Data comes from SneakerFiles' own public release-calendar pages (`/release-dates/`, `/nike-release-dates/`, `/air-jordan-release-dates/`) — the same structured cards (release date, colorway, style code, price) SneakerFiles' own website displays. - The calendar is forward-looking (current month through roughly the next 10-11 months); it does not include a historical archive of past releases. - `whereToBuy` requires fetching each matching release's own detail page (one extra request per release), so it's opt-in via `fetchRetailerLinks` rather than always-on — enabling it on a large `maxItems` run will take longer. Very early "date announced only" releases may not have a "Where to Buy" section yet, in which case `whereToBuy` is simply omitted for that record. - Not every release has a confirmed retail price or colorway at the time SneakerFiles publishes it — `price`/`colorway`/`styleCode` are omitted rather than sent as empty/placeholder values when not yet available; a `priceRaw` field is included instead of `price` when SneakerFiles shows a placeholder like "TBA". - Brands beyond Nike/Air Jordan (adidas, New Balance, Reebok, etc.) are sourced from the combined all-brand calendar only — SneakerFiles does not publish separate dedicated calendar pages for those brands, so their coverage reflects whatever SneakerFiles has currently published to that combined page. - No proxy is required to reach SneakerFiles from Apify's datacenter IPs; `proxyConfiguration` is not needed for this actor. ### FAQ **What's SneakerFiles?** A sneaker news and release-tracking site covering Nike, Jordan Brand, adidas, and other major sneaker brands. See [sneakerfiles.com](https://www.sneakerfiles.com/release-dates/). **Why are some releases missing a price or colorway?** Brands often confirm a release date well before finalizing colorway names or retail pricing; SneakerFiles publishes what's confirmed and updates later. This actor reflects whatever is confirmed at scrape time. **Does this include past/already-released sneakers?** No — the calendar is forward-looking. Re-run the actor periodically to capture newly announced releases and to catch releases that have since passed. **How is `collections` different from `brand`?** `brand` is the top-level brand (Nike, Air Jordan, adidas, ...). `collections` is a finer-grained sub-line tag SneakerFiles applies to some releases (e.g. a release can be both `brand: "Nike"` and `collections: ["Nike Dunk"]`). **How fresh is the data?** SneakerFiles updates its release calendar as brands confirm new drops, typically multiple times per week. # Actor input Schema ## `brand` (type: `string`): Only include releases from this brand. `all` includes every brand SneakerFiles tracks. ## `dateFrom` (type: `string`): Only include releases on or after this date. ## `dateTo` (type: `string`): Only include releases on or before this date. ## `minPrice` (type: `integer`): Drop releases priced below this amount. ## `maxPrice` (type: `integer`): Drop releases priced above this amount. ## `maxItems` (type: `integer`): Hard cap on emitted records. ## `fetchRetailerLinks` (type: `boolean`): For each matching release, also fetch its detail page's "Where to Buy" retailer links (adds one extra request per release, so this is off by default). ## Actor input object example ```json { "brand": "all", "maxItems": 100, "fetchRetailerLinks": false } ``` # Actor output Schema ## `items` (type: `string`): Dataset containing all scraped sneaker release entries. # 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 = { "brand": "all", "maxItems": 100, "fetchRetailerLinks": false }; // Run the Actor and wait for it to finish const run = await client.actor("crawlerbros/sneakerfiles-release-calendar").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 = { "brand": "all", "maxItems": 100, "fetchRetailerLinks": False, } # Run the Actor and wait for it to finish run = client.actor("crawlerbros/sneakerfiles-release-calendar").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 '{ "brand": "all", "maxItems": 100, "fetchRetailerLinks": false }' | apify call crawlerbros/sneakerfiles-release-calendar --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=crawlerbros/sneakerfiles-release-calendar", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "SneakerFiles Release Calendar Scraper", "description": "Scrape SneakerFiles' sneaker release calendar - upcoming Nike, Air Jordan, adidas and other sneaker drops with release dates, style codes, colorways, retail prices, and images.", "version": "1.0", "x-build-id": "hh5PgUnTTztKABkeV" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/crawlerbros~sneakerfiles-release-calendar/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-crawlerbros-sneakerfiles-release-calendar", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/crawlerbros~sneakerfiles-release-calendar/runs": { "post": { "operationId": "runs-sync-crawlerbros-sneakerfiles-release-calendar", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/crawlerbros~sneakerfiles-release-calendar/run-sync": { "post": { "operationId": "run-sync-crawlerbros-sneakerfiles-release-calendar", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "brand": { "title": "Brand", "enum": [ "all", "nike", "air_jordan", "adidas", "new_balance", "reebok", "converse", "puma", "saucony", "asics", "vans", "other" ], "type": "string", "description": "Only include releases from this brand. `all` includes every brand SneakerFiles tracks.", "default": "all" }, "dateFrom": { "title": "Release date from (YYYY-MM-DD)", "type": "string", "description": "Only include releases on or after this date." }, "dateTo": { "title": "Release date to (YYYY-MM-DD)", "type": "string", "description": "Only include releases on or before this date." }, "minPrice": { "title": "Min retail price (USD)", "minimum": 0, "maximum": 10000, "type": "integer", "description": "Drop releases priced below this amount." }, "maxPrice": { "title": "Max retail price (USD)", "minimum": 0, "maximum": 10000, "type": "integer", "description": "Drop releases priced above this amount." }, "maxItems": { "title": "Max items", "minimum": 1, "maximum": 1000, "type": "integer", "description": "Hard cap on emitted records.", "default": 100 }, "fetchRetailerLinks": { "title": "Fetch retailer purchase links", "type": "boolean", "description": "For each matching release, also fetch its detail page's \"Where to Buy\" retailer links (adds one extra request per release, so this is off by default).", "default": false } } }, "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 } } } } } } } } } } ```