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Dropbox · Redux
Practice Redux questions specifically asked in Dropbox interviews – ideal for online test preparation, technical rounds and final HR discussions.
Questions
18
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Company
Dropbox
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Subject
Redux
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Go through each question and its explanation. Use this page for targeted revision just before your Dropbox Redux round.
State immutability ensures that we never modify the existing state directly but always create new state objects, which enables features like time-travel debugging and proper change detection. Immutability makes state changes predictable, helps React optimize rendering through shallow comparison, and prevents hard-to-track bugs caused by unintended mutations.
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Immer wraps your reducer in a produce function that provides a draft state you can safely mutate, and Immer tracks all changes to produce an immutable updated state using structural sharing for efficiency. You can write either mutating logic or return new state, but never both in the same reducer case because returning a new value tells Immer to ignore the draft mutations. Be careful not to return the draft state itself, avoid mutating state from outside the produce wrapper, and remember that async code or callbacks might not work as expected since they execute outside Immer's tracking context.
RTK automatically configures Redux DevTools Extension without any setup, providing time-travel debugging, action history inspection, and state diff viewing out of the box. The DevTools integration shows clean, readable action types generated by createSlice like userSlice/login instead of constants, makes it easy to track when and why state changed, and allows you to replay actions or jump to specific states for debugging. The automatic setup means developers can start debugging immediately without configuration, and the clearer action naming makes the debugging process more intuitive.
fetchBaseQuery is RTK Query's recommended lightweight wrapper around the native fetch API that handles common tasks like setting base URLs, adding headers, handling request/response transformations, and parsing responses. It supports features like automatic JSON parsing, adding authentication tokens via prepareHeaders, custom response handlers, and timeout configuration. While fetchBaseQuery covers most use cases, you can also create custom baseQuery functions using axios or other HTTP clients if needed.
Redux-thunk middleware allows you to dispatch functions (thunks) instead of plain action objects, where these functions receive dispatch and getState as arguments and can contain async logic or conditional dispatching. This enables you to write action creators that return functions which can perform side effects like API calls, dispatch multiple actions sequentially, or dispatch actions conditionally based on current state. Thunks are the simplest and most common way to handle async logic in Redux applications.
Custom middleware follows the pattern store goes to next goes to action arrow, where you can inspect the action, call next with action to pass it along, dispatch other actions, access state with store.getState, or add side effects like logging or analytics. You would create custom middleware for cross-cutting concerns like authentication token injection, request/response logging, crash reporting, analytics tracking, action validation, or implementing complex side effect patterns not covered by existing middleware. The middleware receives the store API with dispatch and getState, the next middleware function, and the action, giving you full control over action flow.
Test reducers as pure functions by passing in a known state and action, then asserting that the returned state matches your expectations, without any mocking or complex setup required. Since reducers are pure functions, they are very easy to test in isolation by simply calling them with test data and checking the output. You can test initial state, individual action handlers, edge cases, and state transitions independently, making reducer tests fast, reliable, and maintainable.
Start migration by installing Redux Toolkit alongside existing Redux without removing anything, then convert your store creation to use configureStore which automatically includes DevTools and middleware while still accepting your existing reducers. Next, identify a small, isolated slice to convert first, rewrite it using createSlice which generates actions automatically, update components to use the new action creators, and test thoroughly before moving to the next slice. Convert action creators to use createAsyncThunk for async operations, gradually replace hand-written reducers with createSlice reducers, migrate to RTK Query if you have extensive data fetching replacing thunks and hand-written cache logic, and update tests to work with new patterns. Complete the migration by removing old Redux files once all features are converted, cleaning up unused dependencies, and updating documentation with new patterns.
Design Redux state to be normalized with entities stored by ID to eliminate duplication, keep it minimal by deriving computed data in selectors rather than storing it, organize by domain or data type rather than UI structure, and keep related data together in slices for easier updates. Avoid deeply nested structures that make updates complex, don't put UI state that doesn't need sharing in Redux, maintain a clear separation between domain data and UI state, and ensure state structure supports efficient updates and lookups. Consider using TypeScript to define state shape explicitly, think about how data will be accessed and updated, and remember that flat structures are easier to work with than deep trees.
An action creator is a function that creates and returns an action object, encapsulating the logic of creating actions and making the code more maintainable and reusable. Instead of manually creating action objects everywhere in your code, action creators provide a consistent way to create actions with the correct type and payload structure. They also make it easier to change action structure later since you only need to update the action creator function rather than finding all places where actions are created.
createSlice automatically generates action creators and action types that correspond to the reducer functions you define, eliminating the need to write them manually. It takes a slice name, initial state, and an object of reducer functions, and returns a slice object containing the reducer and auto-generated action creators. This dramatically reduces boilerplate and makes the code more maintainable since actions and reducers are defined together.
RTK Query is a powerful data fetching and caching tool built on top of Redux Toolkit that can be integrated into your RTK store by adding the API slice reducer and middleware. It leverages RTK's capabilities while providing a comprehensive solution for managing server state, automatic refetching, cache invalidation, and optimistic updates. RTK Query works with any async data source including REST, GraphQL, and other protocols.
Queries are endpoints used for reading data and have automatic caching and refetching behavior, typically corresponding to GET requests, while mutations are for creating, updating, or deleting data and trigger cache invalidation without automatic refetching, typically using POST, PUT, PATCH, or DELETE. Queries can be triggered automatically when components mount or dependencies change, whereas mutations must be manually triggered by user actions. RTK Query treats these differently to optimize data management and performance.
RTK Query uses a tag-based system where queries declare what tags they provide using providesTags, and mutations declare what tags they invalidate using invalidatesTags, creating automatic relationships between data operations. For example, a getPosts query might provide tags Posts and each individual Post with ID, while a createPost mutation invalidates the Posts list tag to trigger a refetch. Tags can be simple strings for entire collections or objects with type and id for individual items, enabling granular control like invalidating only specific posts or all posts in a category. This declarative approach eliminates manual refetch logic and keeps your UI synchronized with backend state automatically.
You customize baseQuery when you need to add authentication headers to all requests using prepareHeaders, handle token refresh logic when auth tokens expire, transform all responses or errors globally, add request interceptors for logging or analytics, or integrate with a different HTTP client like axios instead of fetch. You can wrap fetchBaseQuery with additional logic using a custom baseQuery function that calls the base query and processes results, allowing you to implement patterns like automatic retry on failure, request queuing, or global error handling. Common use cases include adding Bearer tokens from Redux state, refreshing expired tokens transparently, normalizing error responses, and adding request correlation IDs for debugging.
The recommended approach is incremental migration where you convert one feature or slice at a time from vanilla Redux to RTK, allowing the old and new patterns to coexist during the transition. Start by installing Redux Toolkit alongside existing Redux, convert your store setup to configureStore which works with existing reducers, then gradually convert individual reducer files to createSlice while keeping your application running. This minimizes risk, allows for testing each conversion independently, and doesn't require stopping feature development during migration.
Redux Saga uses ES6 generator functions to handle complex async flows, race conditions, task cancellation, parallel requests, and sophisticated orchestration patterns that are difficult with thunks. Sagas provide better testability since effects are plain objects, support advanced patterns like takeLatest, debounce, throttle, and retry logic declaratively, and make complex async workflows easier to reason about. However, the learning curve is steeper than thunks, making sagas better suited for complex applications while thunks suffice for simpler needs.
Handle errors in createAsyncThunk by using try-catch blocks in your payload creator to catch exceptions, then return rejectWithValue with error data to provide custom error payloads instead of the default rejected action. In your slice's extraReducers, handle the rejected case to store error information in state, optionally including error messages, status codes, or validation errors from the API response. You can also use the thunkAPI.rejectWithValue to pass structured error data that components can use to show specific error messages, implement retry logic using the thunkAPI.dispatch, or handle errors globally in middleware to show notifications or log to error tracking services.