Common REST API Design Patterns

When working with REST APIs, you may come across common design patterns that can help solve specific problems efficiently. Let's explore some of these design patterns:

1. Pagination: When dealing with large datasets, it is often necessary to retrieve data in chunks or pages. The pagination design pattern allows you to fetch a specified number of records at a time and navigate through the dataset using pagination parameters. This can help improve API performance and reduce the amount of data transferred over the network.

Here's an example of how you can implement pagination in C++:

1#include <iostream>
2#include <vector>
3using namespace std;
4
5// Function to retrieve data from API with pagination
6vector<int> getDataFromAPI(int page) {
7  // replace with API request logic here
8  // use the page parameter to specify the page number
9  // return the data obtained from the API
10}
11
12int main() {
13  int page = 1;
14  vector<int> data;
15
16  // Retrieve data from API until there is no more data
17  while (true) {
18    // Get data for the current page
19    vector<int> pageData = getDataFromAPI(page);
20
21    // Check if there is no more data
22    if (pageData.empty()) {
23      break;
24    }
25
26    // Append the page data to the main data vector
27    data.insert(data.end(), pageData.begin(), pageData.end());
28
29    // Move to the next page
30    page++;
31  }
32
33  // Process the data
34  for (int value : data) {
35    // Process each value
36    cout << value << "\n";
37  }
38
39  return 0;
40}

In this example, the getDataFromAPI function retrieves data from the API for a specified page number. The main function retrieves data using pagination and stores it in a vector. It then processes the retrieved data. You can customize the logic based on your specific API and data requirements.

2. Caching: Caching is a technique that allows you to store API responses in a cache and serve subsequent requests for the same data from the cache instead of making a new request to the API. This can significantly improve API performance by reducing the database or API server load. Popular caching options include in-memory caches like Redis or using caching frameworks like Memcached.

3. Rate Limiting: Rate limiting is a technique used to control the number of requests made to an API within a specific time period. By implementing rate limiting, you can prevent abuse of your API, protect server resources, and ensure fair usage. Rate limiting can be based on various factors such as the number of requests per minute, per IP address, or per user.

These are just a few of the common design patterns used in REST APIs. The choice of design pattern depends on the specific requirements of your API and the problem you are trying to solve. By understanding and utilizing these design patterns, you can create more efficient and scalable REST APIs.

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}

#include <iostream>

#include <vector>

using namespace std;

​

// Pattern: Paginations

​

// Function to retrieve data from API with pagination

vector<int> getDataFromAPI(int page) {

  // replace with API request logic here

  // use the page parameter to specify the page number

  // return the data obtained from the API

}

​

int main() {

  int page = 1;

  vector<int> data;

​

  // Retrieve data from API until there is no more data

  while (true) {

    // Get data for the current page

    vector<int> pageData = getDataFromAPI(page);

​

    // Check if there is no more data

    if (pageData.empty()) {

      break;

    }

​

    // Append the page data to the main data vector

    data.insert(data.end(), pageData.begin(), pageData.end());