Dans les API, le cache désigne une zone de stockage temporaire pour les données afin de réduire le nombre d'allers-retours du serveur et le délai associé à la récupération des mêmes données à plusieurs reprises.
An analogy to use for cache is the grocery store. When the grocer puts a can of soup on the shelf for customers to purchase, that is the same as when an API has the data stored in the cache. Customers can purchase the soup from the shelf, which is the same as when a client requests data from the API and retrieves it from the cache. This eliminates the need for the grocer to take the soup out of a backroom or get it from the warehouse, which is the same as the server needing to execute a request each time the data is needed by clients.
The caching process works by the server storing copies of frequently used or requested data in the cache in order to reduce the amount of time and resources needed to retrieve them. The server will look in the cache first to see if a request is already stored there before going to the server. This can improve performance and latency significantly, since retrieving data from the server can be an expensive process.
For example, a client may request an image from the server. If that image exists in the cache, the server can quickly retrieve it from there and return it to the client. If the image does not exist in cache, the server then needs to fetch it from the database, which takes longer. This is why caching is so important for APIs that are frequently requesting the same data.
Caching can also be used to store responses from complex requests to reduce the time needed by clients to receive their data. By caching the request once, subsequent requests from clients would be much faster since the cached request can quickly be retrieved instead of requiring the server to execute the complex logic again each time.