Implementing Remote Data Caching in an Angular Application

Your task is to implement a robust remote data caching mechanism within an Angular application. This is crucial for improving user experience by reducing redundant network requests, speeding up data retrieval, and allowing for offline access to previously fetched data. You will leverage Angular's dependency injection and RxJS for an efficient and maintainable solution.

Problem Description

You need to create an Angular service that acts as a remote cache for HTTP requests. This service should intercept outgoing HTTP requests, check if the requested data is already present in the cache, and return cached data if available. If the data is not in the cache, it should fetch the data from the remote source, store it in the cache, and then return it.

Key Requirements:

• Cache Storage: Implement a mechanism to store cached data. A simple in-memory object or Map is acceptable for this challenge.
• Cache Invalidation/Expiration: Implement a basic mechanism for cache invalidation. For this challenge, a simple time-based expiration (e.g., cache entries become stale after a certain duration) will suffice.
• Interceptor Integration: The caching logic should ideally be implemented within an Angular HTTP Interceptor to seamlessly intercept all relevant HTTP requests.
• RxJS Observables: The service and the interceptor should work with RxJS Observables, allowing for reactive data handling.
• Cache Key Generation: A strategy for generating unique cache keys based on the request URL and potentially request body/parameters is needed.
• Handling Different HTTP Methods: The caching should primarily focus on GET requests, but consider how other methods (like POST, PUT, DELETE) might affect the cache.

Expected Behavior:

1. When a component requests data via HTTP (e.g., using Angular's HttpClient):
   • The HTTP Interceptor intercepts the request.
   • If the request is a GET request and the corresponding data exists in the cache and is not expired:
     • The cached data is returned immediately as an Observable.
     • No actual HTTP request is made to the remote server.
   • If the request is a GET request and the data is not in the cache or is expired:
     • The request proceeds to the remote server.
     • Upon successful retrieval of data, the data is stored in the cache with an appropriate expiration timestamp.
     • The fetched data is returned as an Observable.
   • For non-GET requests, the request should proceed to the remote server without cache interaction. You might also consider strategies to invalidate specific cache entries upon certain mutations (e.g., POST, PUT, DELETE).

Edge Cases to Consider:

• Empty Cache: The initial state where no data is cached.
• Stale Data: Data that has expired and needs to be re-fetched.
• Concurrent Requests: Multiple components requesting the same data simultaneously. The cache should ideally serve the first fetched data to subsequent requests while the initial fetch is in progress, or at least prevent multiple identical fetches to the server.
• Request Parameters/Body: How to uniquely identify cached data when requests differ only by parameters or request body.

Examples

Example 1: Fetching User Data

Let's assume we have an API endpoint /api/users/:id that fetches user details.

Scenario:

1. Component A requests user with ID 1. Data is not cached. HTTP request is made.
2. Component B requests user with ID 1 shortly after. Data is now cached and valid.
3. Component C requests user with ID 2. Data is not cached. HTTP request is made.

Input (Conceptual - how components would call it):

// In Component A and B
this.userService.getUser(1).subscribe(user => console.log(user));

// In Component C
this.userService.getUser(2).subscribe(user => console.log(user));

Output (Console Logs):

// First call from Component A:
{ id: 1, name: 'Alice' } // Fetched from remote

// Second call from Component B:
{ id: 1, name: 'Alice' } // Served from cache

// First call from Component C:
{ id: 2, name: 'Bob' }   // Fetched from remote

Explanation:

Component A's request for user 1 triggers a network call. The result is cached. Component B's subsequent request for user 1 hits the cache, returning the data instantly without another network call. Component C's request for user 2 is a new request and thus triggers a network call, and its result is also cached.

Example 2: Cache Expiration

Scenario:

1. Request for user with ID 1 is made. Data is cached.
2. The cache entry for user 1 expires after 60 seconds.
3. A new request for user with ID 1 is made after expiration.

Input (Conceptual):

// First call
this.userService.getUser(1).subscribe(user => console.log('First:', user));

// ... after 60 seconds ...

// Second call
this.userService.getUser(1).subscribe(user => console.log('Second:', user));

Output (Console Logs):

First: { id: 1, name: 'Alice' } // Fetched from remote

Second: { id: 1, name: 'Alice' } // Fetched from remote (cache expired)

Explanation:

The first call fetches and caches the data. After the specified expiration time, the cache entry becomes stale. The second call, even though the URL is the same, will bypass the expired cache and make a new request to the remote server, updating the cache with fresh data.

Constraints

• Cache Expiration Duration: The cache entries should have a configurable expiration duration, with a default of 60 seconds.
• Cache Size: For this challenge, assume the in-memory cache can hold a reasonable number of entries without significant performance degradation. No explicit size limit is enforced.
• HTTP Methods: The caching mechanism should primarily target GET requests. POST, PUT, DELETE, and PATCH requests should bypass the cache and potentially invalidate specific cached entries.
• Request Identification: Cache keys must be generated reliably to distinguish between requests that should yield different data (e.g., /api/items?category=electronics vs. /api/items?category=books). For simplicity, consider only the URL and query parameters for GET requests when generating keys.

Notes

• Consider using RxJS operators like tap, catchError, and potentially shareReplay for efficient observable handling within your interceptor and service.
• Think about how to manage the lifecycle of your cache entries (e.g., when to remove expired items).
• You might want to create a dedicated CacheService to manage the cache storage and expiration logic, and then have your HTTP Interceptor use this service.
• For simplicity in cache key generation for GET requests, you can often combine the URL and the stringified query parameters.
• For mutation operations (POST, PUT, DELETE), a simple approach for invalidation is to clear the entire cache or to provide a mechanism to manually invalidate specific cache keys. For this challenge, clearing the entire cache on any non-GET request is an acceptable starting point.