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How do I find List the item number, description, and category for each pair of i

ID: 3931344 • Letter: H

Question

How do I find List the item number, description, and category for each pair of items that are in the same category. (Example: One such pair would be item CD33 and item DL51, because the category for both items is TOY) How do I find List the item number, description, and category for each pair of items that are in the same category. (Example: One such pair would be item CD33 and item DL51, because the category for both items is TOY) List the item number, description, and category for each pair of items that are in the same category. (Example: One such pair would be item CD33 and item DL51, because the category for both items is TOY)

Explanation / Answer

In the Trading API, this call enables you to retrieve recommendations for a limited number of categories at a time (see details in the table below). If you need data for more categories, download the data by making multiple calls to GetCategorySpecifics.

For applications that support a very wide variety of categories, it may be more practical to use the downloadFile call in the File Transfer API to download a single GetCategorySpecifics response that contains custom Item Specific recommendations for all categories on a given site. The GetCategorySpecifics response is returned as a .zip file attachment. It uses the Recommendations node.

Here's a typical way to use this approach:

The downloadable GetCategorySpecifics response file is updated every few days. When this occurs, eBay generates new file reference and task reference IDs for the new file. If you call GetCategoryFeatures, you may detect that custom Item Specifics have been newly enabled in certain categories since you last downloaded recommendations. In this case, if the file IDs returned by GetCategorySpecifics haven't changed, you can call GetCategorySpecifics directly to retrieve any new recommendations for those specific categories.

Each time you call GetCategorySpecifics, store the response data locally and use that data to fill in recommendations for a listing. Periodically (once a day or weekly, depending on your use case), check to see if the data has changed.

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