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KicksDB relies on Meilisearch to search and filter products, our following endpoints uses Meilisearch under the hood:
  • StockX
  • GOAT
  • Shopify
  • Kream
These endpoints often have query parameter to search for products and filters parameter to filter products based on certain criteria. This recipe will show you how to use filters parameter.

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Filtering products

You should consult the structure of the indexes below to understand the available filters. For example, if you want to filter products by brand, you can use the brand filter, like this: 
brand = "Nike";
Due to special characters, you might have to encode the filters to avoid errors, it should give a result like this: 
GET https://api.kicks.dev/v3/stockx/products?filters=brand%3D%22Nike%22
It’s possible to combine multiple filters, like this: 
brand = "Nike" AND product_type = "sneakers";
Finally, some filters use nested objects, like this: 
prices["USD_US"]["9.5"] < 100;
Values in quotes are not case sensitive.

Meilisearch documentation

You can consult the Meilisearch documentation for more information about the filters.

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Indexes

Indexes are refreshed every 12 hours, you can consult the structure of the indexes below.

StockX

GOAT

Shopify

Kream

SNKRS

Novelship

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StockX

{
  "slug": "string",
  "brand": "string",
  "gender": "string",
  "product_type": "string",
  "category": "string",
  "secondary_category": "string",
  "categories": ["string"],
  "sku": "string",
  "rank": "number",
  "release_date": "string",
  "colorway": "string",
  "prices": {
    "currency_market": {
      // ^ Example: "USD_US"
      "size": "float"
      // ^ Example: 9.5 -- Value is the lowest price for this size
    }
  },
  "barcodes": ["string"],
  "breadcrumbs": ["string"],
  "updated_at": "date-time",
  "created_at": "date-time"
}

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GOAT

{
  "brand": "string",
  "slug": "string",
  "sku": "string",
  "colorway": "string",
  "release_date": "string", // Format: YYYYMMDD or YYYY
  "rank": "number",
  "product_type": "string",
  "category": "string",
  "model": "string",
  "season": "string",
  "prices": {
    "<currency>": { "<size>": "float" }
    // ^ Example: "USD": { "9": 123.45 }
  }
}

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Shopify

{
  "id": "string",
  "product_id": "number",
  "title": "string", // searchable
  "slug": "string", // searchable, filterable
  "brand": "string", // searchable, filterable
  "product_type": "string", // searchable, filterable
  "sku": "string", // searchable, filterable
  "sku_cleaned": "string", // filterable
  "tags": ["string"], 
  "shop_name": "string", // filterable
  "updated_at": "string", // sortable
  "published_at": "string", // sortable
  "prices": { // filterable
    "string": "number" // size: price
  },
  "barcodes": ["string"], // filterable
  "cursor": "number" // filterable, sortable
}
We recommend using sku_cleaned when filtering by SKU. Shopify forces shops to append the size or an unique identifier to each variant. By using sku_cleaned you match the SKU 310805-012 instead of shop’s defined 310805-012-25.

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Kream

{
  "id": "number", // sortable
  "name": "string", // searchable
  "brand": "string", // searchable, filterable
  "category": "string", // searchable, filterable
  "colorway": "string", // searchable, filterable
  "gender": "string", // filterable
  "sku": "string", // searchable, filterable
  "release_date": "string", // filterable, sortable
}

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SNKRS

{
  "id": "string",
  "country_code": "string", // filterable
  "title": "string", // searchable
  "subtitle": "string", // searchable
  "slug": "string", // searchable, filterable
  "skus": ["string"], // searchable, filterable
  "barcodes": ["string"], // searchable, filterable
  "product_type": "string", // filterable
  "status": "string", // filterable
  "exclusive": "boolean", // filterable
  "start_date": "string", // filterable
}

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Novelship

{
  "id": "string",
  "name": "string", // searchable
  "brand": "string", // searchable, filterable
  "slug": "string", // searchable, filterable
  "sku": "string", // searchable, filterable
  "colorway": "string", // filterable
  "release_date": "string", // filterable
  "retail_price": "number", // filterable
  "product_type": "string", // filterable
  "model": "string", // searchable, filterable
  "season": "string", // filterable
}