Optimize Data Retrieval with Catalog Caching

The catalog_cache method in the Groclake library is used to trigger caching of specific product data. This ensures that the product details, identified by their groc_item_id, are stored and optimized for faster retrieval in future operations.

Python

try
catalog_cache = catalog.cache(cache_object)
print("catalog_cache_data----", catalog_cache)

Example cache object

cache_object = {
  "groc_item_id": ["2147483647"]
}

Example App Code

cache_object = {
  "groc_item_id": ["2147483647"]
}

catalog_cache = catalog.cache(cache_object)
print("catalog_cache_data----", catalog_cache)

#RESPONSE FROM CATALOG CACHE
#
# {
#     "catalog_cache_request_id": "0b6f7624-f176-461a-828b-1ba9bf3d56ac"
# }