React experimental_useOptimistic Merge Algorithm: A Deep Dive into Optimistic Updates

In the ever-evolving world of front-end development, creating responsive and engaging user interfaces is paramount. React, with its component-based architecture, provides developers with powerful tools to achieve this goal. One such tool, currently experimental, is the experimental_useOptimistic hook, designed to enhance the user experience through optimistic updates. This blog post provides a comprehensive exploration of this hook, focusing particularly on the merge algorithm that powers it.

What are Optimistic Updates?

Optimistic updates are a UI pattern where you immediately update the user interface as if an operation (e.g., a button click, form submission) has been successful, before actually receiving confirmation from the server. This provides a perceived performance boost and makes the application feel more responsive. If the server confirms the operation, nothing changes. However, if the server reports an error, you revert the UI to its previous state and inform the user.

Consider these examples:

• Social Media: Liking a post on a social media platform. The like count increments instantly, and the user sees the updated number immediately. If the like fails to register on the server, the count reverts to its original value.
• Task Management: Marking a task as complete in a to-do list application. The task appears crossed out instantly, providing immediate feedback. If the completion fails to persist, the task reverts to its incomplete state.
• E-commerce: Adding an item to a shopping cart. The cart count updates instantly, and the user sees the item in the cart preview. If adding to the cart fails, the item is removed from the preview and the count reverts.

Introducing experimental_useOptimistic

React's experimental_useOptimistic hook simplifies the implementation of optimistic updates. It allows you to manage optimistic state updates easily, providing a mechanism to revert to the original state if necessary. This hook is experimental, meaning its API might change in future releases.

Basic Usage

The experimental_useOptimistic hook takes two arguments:

• Initial state: The initial value of the state.
• Updater function: A function that takes the current state and an optimistic value and returns the new optimistic state. This is where the merge algorithm comes into play.

It returns an array containing two elements:

• Optimistic state: The current optimistic state (either the initial state or the result of the updater function).
• Optimistic dispatch: A function that accepts an optimistic value. Calling this function triggers the updater function to calculate a new optimistic state.

Here's a simplified example:

            import { experimental_useOptimistic as useOptimistic, useState } from 'react';

function MyComponent() {
  const [originalValue, setOriginalValue] = useState(0);
  const [optimisticValue, updateOptimisticValue] = useOptimistic(
    originalValue,
    (state, optimisticUpdate) => state + optimisticUpdate // Simple merge algorithm: adds the optimistic update to the current state
  );

  const handleClick = () => {
    updateOptimisticValue(1); // Optimistically increment by 1
    // Simulate an asynchronous operation (e.g., API call)
    setTimeout(() => {
      setOriginalValue(originalValue + 1); // Update the real value after successful operation
    }, 1000);
  };

  return (
    

      
Original Value: {originalValue}
      
Optimistic Value: {optimisticValue}
      Increment
    
  );
}

export default MyComponent;

            

              
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In this example, clicking the "Increment" button optimistically increments the `optimisticValue` by 1. After a 1-second delay, the `originalValue` is updated to reflect the actual server-side change. If the simulated API call had failed, we would need to reset `originalValue` back to its previous value.

The Merge Algorithm: Powering Optimistic Updates

The heart of experimental_useOptimistic lies in its merge algorithm, which is implemented within the updater function. This algorithm determines how the optimistic update is applied to the current state to produce the new optimistic state. The complexity of this algorithm depends on the structure of the state and the nature of the updates.

Different scenarios require different merge strategies. Here are a few common examples:

1. Simple Value Updates

As demonstrated in the previous example, for simple values like numbers or strings, the merge algorithm can be as straightforward as adding the optimistic update to the current state or replacing the current state with the optimistic value.

            (state, optimisticUpdate) => state + optimisticUpdate // For numbers
(state, optimisticUpdate) => optimisticUpdate // For strings or booleans (replace the entire state)

            

              
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2. Object Merging

When dealing with objects as state, you often need to merge the optimistic update with the existing object, preserving the original properties while updating the specified ones. This is commonly done using the spread operator or the Object.assign() method.

            (state, optimisticUpdate) => ({ ...state, ...optimisticUpdate });

            

              
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Consider a profile update scenario:

            const [profile, updateOptimisticProfile] = useOptimistic(
  {
    name: "John Doe",
    location: "New York",
    bio: "Software Engineer"
  },
  (state, optimisticUpdate) => ({ ...state, ...optimisticUpdate })
);

const handleLocationUpdate = (newLocation) => {
  updateOptimisticProfile({ location: newLocation }); // Optimistically update the location
  // Simulate API call to update the profile on the server
};

            

              
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In this example, only the `location` property is updated optimistically, while the `name` and `bio` properties remain unchanged.

3. Array Manipulation

Updating arrays requires more careful consideration, especially when adding, removing, or modifying elements. Here are a few common array manipulation scenarios:

• Adding an element: Concatenate the new element to the array.
• Removing an element: Filter the array to exclude the element to be removed.
• Updating an element: Map the array and replace the element with the updated version based on a unique identifier.

Consider a task list application:

            const [tasks, updateOptimisticTasks] = useOptimistic(
  [
    { id: 1, text: "Buy groceries", completed: false },
    { id: 2, text: "Walk the dog", completed: true }
  ],
  (state, optimisticUpdate) => {
    switch (optimisticUpdate.type) {
      case 'ADD':
        return [...state, optimisticUpdate.task];
      case 'REMOVE':
        return state.filter(task => task.id !== optimisticUpdate.id);
      case 'UPDATE':
        return state.map(task =>
          task.id === optimisticUpdate.task.id ? optimisticUpdate.task : task
        );
      default:
        return state;
    }
  }
);

const handleAddTask = (newTaskText) => {
  const newTask = { id: Date.now(), text: newTaskText, completed: false };
  updateOptimisticTasks({ type: 'ADD', task: newTask });
  // Simulate API call to add the task to the server
};

const handleRemoveTask = (taskId) => {
  updateOptimisticTasks({ type: 'REMOVE', id: taskId });
  // Simulate API call to remove the task from the server
};

const handleUpdateTask = (updatedTask) => {
  updateOptimisticTasks({ type: 'UPDATE', task: updatedTask });
  // Simulate API call to update the task on the server
};

            

              
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This example demonstrates how to add, remove, and update tasks in an array optimistically. The merge algorithm uses a switch statement to handle different update types.

4. Deeply Nested Objects

When dealing with deeply nested objects, a simple spread operator might not be sufficient, as it only performs a shallow copy. In such cases, you might need to use a recursive merging function or a library like Lodash's _.merge or Immer to ensure that the entire object is correctly updated.

Here's an example using a custom recursive merge function:

            function deepMerge(target, source) {
  for (const key in source) {
    if (typeof source[key] === 'object' && source[key] !== null && !Array.isArray(source[key])) {
      if (!target[key] || typeof target[key] !== 'object') {
        target[key] = {};
      }
      deepMerge(target[key], source[key]);
    } else {
      target[key] = source[key];
    }
  }
  return target;
}

const [config, updateOptimisticConfig] = useOptimistic(
  {
    theme: {
      primaryColor: "blue",
      secondaryColor: "green",
    },
    userSettings: {
      notificationsEnabled: true,
      language: "en"
    }
  },
  (state, optimisticUpdate) => {
    const newState = { ...state }; // Create a shallow copy
    deepMerge(newState, optimisticUpdate);
    return newState;
  }
);

const handleThemeUpdate = (newTheme) => {
  updateOptimisticConfig({ theme: newTheme });
  // Simulate API call to update the configuration on the server
};

            

              
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This example demonstrates how to use a recursive merge function to update deeply nested properties in the configuration object.

Customizing the Merge Algorithm

The flexibility of experimental_useOptimistic allows you to customize the merge algorithm to fit your specific needs. You can create custom functions that handle complex merging logic, ensuring that your optimistic updates are applied correctly and efficiently.

When designing your merge algorithm, consider the following factors:

• State structure: The complexity of the state data (simple values, objects, arrays, nested structures).
• Update types: The different types of updates that can occur (add, remove, update, replace).
• Performance: The efficiency of the algorithm, especially when dealing with large datasets.
• Immutability: Maintaining immutability of the state to prevent unexpected side effects.

Error Handling and Rollback

A crucial aspect of optimistic updates is handling errors and rolling back the optimistic state if the server operation fails. When an error occurs, you need to revert the UI to its original state and inform the user about the failure.

Here's an example of how to handle errors and rollback the optimistic state:

            import { experimental_useOptimistic as useOptimistic, useState, useRef } from 'react';

function MyComponent() {
  const [originalValue, setOriginalValue] = useState(0);
  const [optimisticValue, updateOptimisticValue] = useOptimistic(
    originalValue,
    (state, optimisticUpdate) => state + optimisticUpdate
  );

  // Use useRef to store the previous originalValue for rollback
  const previousValueRef = useRef(originalValue);

  const handleClick = async () => {
    previousValueRef.current = originalValue;
    updateOptimisticValue(1);

    try {
      // Simulate an asynchronous operation (e.g., API call)
      await new Promise((resolve, reject) => {
        setTimeout(() => {
          // Simulate a random error
          if (Math.random() < 0.2) {
            reject(new Error("Operation failed"));
          } else {
            setOriginalValue(originalValue + 1);
            resolve();
          }
        }, 1000);
      });
    } catch (error) {
      console.error("Operation failed:", error);
      // Rollback to the previous value
      setOriginalValue(previousValueRef.current);
      alert("Operation failed. Please try again."); // Inform the user
    }
  };

  return (
    

      
Original Value: {originalValue}
      
Optimistic Value: {optimisticValue}
      Increment
    
  );
}

            

              
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In this example, the `previousValueRef` is used to store the previous `originalValue` before applying the optimistic update. If the API call fails, the `originalValue` is reset to the stored value, effectively rolling back the optimistic update. An alert informs the user about the failure.

Benefits of Using experimental_useOptimistic

Using experimental_useOptimistic for implementing optimistic updates offers several benefits:

• Improved user experience: Provides a more responsive and engaging user interface.
• Simplified implementation: Simplifies the management of optimistic state updates.
• Centralized logic: Encapsulates the merging logic within the updater function, making the code more maintainable.
• Declarative approach: Allows you to define how optimistic updates are applied in a declarative manner.

Limitations and Considerations

While experimental_useOptimistic is a powerful tool, it's important to be aware of its limitations and considerations:

• Experimental API: The API is subject to change in future React releases.
• Complexity: Implementing complex merge algorithms can be challenging.
• Error handling: Proper error handling and rollback mechanisms are essential.
• Data consistency: Ensure that the optimistic updates align with the server-side data model.

Alternatives to experimental_useOptimistic

While experimental_useOptimistic provides a convenient way to implement optimistic updates, there are alternative approaches you can consider:

• Manual state management: You can manage the optimistic state manually using useState and custom logic.
• Redux with optimistic middleware: Redux middleware can be used to intercept actions and apply optimistic updates before dispatching them to the store.
• GraphQL libraries (e.g., Apollo Client, Relay): These libraries often provide built-in support for optimistic updates.

Use Cases Across Different Industries

Optimistic updates enhance user experience across various industries. Here are a few specific scenarios:

• Financial Technology (FinTech):
  • Real-time Trading Platforms: When a user places a trade, the platform can optimistically update the portfolio balance and trade confirmation status before the trade is actually executed. This provides immediate feedback, especially important in fast-paced trading environments.
    • Example: A stock trading app updates the user’s available balance instantly after placing a buy order, showing an estimated trade execution.
  • Online Banking: When transferring funds between accounts, the UI can show the transfer as complete immediately, with a confirmation pending in the background.
  • Example: An online bank app shows a successful transfer confirmation screen instantly while processing the actual transfer in the background.
• Healthcare Technology (HealthTech):
  • Appointment Scheduling: When scheduling an appointment, the system can immediately display the appointment as confirmed, with background checks verifying availability.
  • Example: A healthcare portal shows an appointment as confirmed immediately after the user selects a time slot.
  • Electronic Health Records (EHR) Updates: When updating patient information (e.g., allergies, medications), the changes can be displayed immediately, while the system saves them in the background.
  • Example: A physician updates a patient’s allergy list and sees the changes instantly, allowing them to continue with the consultation without waiting.
• Logistics and Supply Chain:
  • Order Tracking: When a package status is updated (e.g., "out for delivery"), the tracking information can be updated optimistically to reflect the change instantly.
  • Example: A courier app shows a package as "out for delivery" as soon as the driver scans it, even before the central system updates.
  • Inventory Management: When adjusting inventory levels (e.g., receiving a shipment), the inventory counts can be updated optimistically to show immediate availability.
  • Example: A warehouse management system shows the updated stock level of a product immediately after a receiving clerk confirms the arrival of a new shipment.
• Education Technology (EdTech):
  • Quiz Submissions: When a student submits a quiz, the system can immediately display a preliminary score, even before all answers are graded.
  • Example: An online learning platform shows a student an estimated score immediately after they submit a quiz, indicating potential performance.
  • Course Enrollment: When enrolling in a course, the system can immediately add the course to the student's dashboard, while verifying seat availability in the background.
  • Example: A university portal adds a course to a student’s enrolled courses list immediately after the student clicks "Enroll."

Conclusion

experimental_useOptimistic is a powerful tool for enhancing the user experience in React applications through optimistic updates. By understanding the merge algorithm and customizing it to fit your specific needs, you can create seamless and responsive user interfaces that provide a perceived performance boost. Remember to handle errors and roll back the optimistic state when necessary to maintain data consistency. As an experimental API, it's crucial to stay updated with the latest React releases and be prepared for potential changes in the future.

By carefully considering the state structure, update types, and error handling mechanisms, you can effectively leverage experimental_useOptimistic to build more engaging and responsive applications for your users, regardless of their global location or industry.

Further Reading

• React Documentation - experimental_useOptimistic
• React GitHub Repository
• Immer Library for Immutable State Updates (https://immerjs.github.io/immer/)