A tree component optimization method based on React framework integrating virtualized rendering and incremental rendering

Abstract

The present invention belongs to the technical field of front-end development, and specifically provides a tree component optimization method based on the React framework integrating virtualized rendering and incremental rendering; comprising S1: data preprocessing: S2: dynamic virtualized rendering: dynamically calculating the node index range in the visible area according to the real-time scrolling position of the user's viewport, only rendering the nodes in the range, and realizing seamless lazy loading of data through scroll event monitoring; S3: intelligent incremental update: identifying the changed nodes through the state change comparison algorithm, and performing local re-rendering only for the changed nodes based on the component lifecycle control mechanism of the React framework; S4: lazy loading collaborative control: the present invention aims to solve the problems of performance, memory management and user experience faced by tree components in the React ecosystem when processing large-scale data, and is widely used in various Web application development scenarios that need to display and operate large-scale tree data structures.

Description

Technical Field

[0001] The present invention belongs to the technical field of front-end development, and in particular relates to a tree component optimization method based on a React framework integrating virtualized rendering and incremental rendering. Background Art

[0002] In today's digital age, with the explosive growth of data volume, the need to process large-scale data in front-end development has become more urgent. React, as a widely used front-end JavaScript framework, performs well in building interactive user interfaces, but faces many challenges when processing the tree structure display of large-scale data. At present, the relevant technologies for large-scale data tree structure display in the React ecosystem have the following problems:

[0003] Limitations of virtualized rendering technology: Although the virtualized rendering technology used by libraries such as React-virtualized and React-window can effectively improve performance by rendering only the content in the visible area when processing list and table data, the tree structure has a unique hierarchical nesting feature, which is difficult for these libraries to effectively support. The expansion and collapse operations of the tree structure and the complex associations between nodes make it difficult for virtualized rendering to fully play its advantages when processing tree data, resulting in limited performance improvement.

[0004] Performance bottleneck of component library Tree implementation: Widely used component libraries such as AntDesign provide rich functions and beautiful user interfaces with their Tree components. However, when faced with ultra-large-scale data (such as 200,000 records), the performance will drop sharply. This is because as the amount of data increases, the component needs to process a large amount of node information during rendering and data search, resulting in a significant increase in the amount of calculation, which in turn affects the overall performance. At the same time, its global search function is inefficient and cannot meet the needs of users to quickly locate the required information in massive data.

[0005] Shortcomings of specialized tree structure libraries: Libraries designed specifically for complex tree structures, such as react-complex-tree, support advanced features such as keyboard navigation, but have obvious shortcomings in performance and memory management when processing large data sets. Loading and processing large amounts of data will occupy too much memory resources, increasing the risk of memory overflow, and will also slow down the system, seriously affecting the user experience.

[0006] The tree components combined with virtualization are lacking in functionality: react-vtree and other tree components combined with virtualization technology have improved performance to a certain extent when processing large data sets, but their functions are relatively simple. In actual business scenarios, tree components are often required to have a variety of complex functions, such as data editing, permission control, custom styles, etc., and such components are difficult to meet these diverse business needs.

[0007] In addition, the common optimization methods used in the industry for large-scale data rendering also have their own shortcomings:

[0008] The dilemma of virtual scrolling in deep tree structures: Virtual scrolling technology only renders the content in the visible area, which is effective for simple list structures. However, when dealing with deep tree structures, due to the depth of the tree hierarchy and the complex relationship between nodes, virtual scrolling is difficult to accurately determine which nodes should be rendered, resulting in a significant reduction in optimization effects and failure to effectively improve performance.

[0009] Lazy loading is not adaptable to global search: Lazy loading reduces the burden of initial loading to a certain extent by loading child nodes on demand. However, when a global search is required, since some data has not been loaded, it is impossible to quickly locate all relevant nodes, which seriously affects the accuracy and efficiency of the search.

[0010] Data paging destroys the integrity of the tree structure: Data paging loads data in batches, which reduces the amount of data loaded at a time, but destroys the integrity and coherence of the tree structure. Users cannot intuitively obtain information about the entire tree structure during operation, which affects their understanding of the data structure and operating experience.

[0011] Application limitations of WebWorker: WebWorker is used to process complex calculations and can share some of the pressure on the main thread. However, in actual applications, its state synchronization and DOM operations still need to be processed by the main thread, which makes it impossible to give full play to the advantages of WebWorker in large-scale data processing scenarios and fundamentally solve performance problems.

[0012] In summary, existing technical solutions cannot take into account performance, functionality and user experience when processing large-scale tree-structured data. Developing an efficient, fully functional React tree component optimization technology that can adapt to large-scale data processing has become an urgent problem to be solved in the current front-end development field. Summary of the invention

[0013] In view of this, the purpose of the present invention is to overcome the shortcomings of the prior art and provide a tree component optimization method based on the React framework that integrates virtualized rendering and incremental rendering to achieve a high-performance, low-memory ReactTree component that supports large-scale data, providing developers with a powerful and flexible tree structure.

[0014] Display and operation tools. This technical solution aims to solve the performance, memory management and user experience problems faced by tree components in the React ecosystem when processing large-scale data. It is widely used in various Web application development scenarios that need to display and operate large-scale tree data structures, such as enterprise resource management systems, file directory management systems, and big data visualization analysis platforms.

[0015] To achieve the above object, the technical solution adopted by the present invention is: a tree component optimization method based on the React framework integrating virtualized rendering and incremental rendering, comprising the following steps:

[0016] S1: Data preprocessing: Verify the integrity and correct the relationship of the input tree-shaped nested structure data, build a bidirectional index table of the parent-child relationship between nodes, and flatten the data into a one-dimensional array;

[0017] S2: Dynamic virtualized rendering: Dynamically calculate the node index range within the visible area according to the real-time scrolling position of the user's viewport, render only the nodes within the range, and implement seamless lazy loading of data through scroll event monitoring;

[0018] S3: Intelligent incremental update: The changed nodes are identified through the state change comparison algorithm, and based on the component lifecycle control mechanism of the React framework, only the changed nodes are partially re-rendered;

[0019] S4: Lazy loading collaborative control: When the user scrolls close to the boundary threshold of unloaded data, an asynchronous data request is triggered and new data is dynamically inserted into the existing data set, while updating the user interface;

[0020] S5: Global state management: Use centralized state to maintain the expansion, collapse and selection status of tree components, and implement state persistence and recovery through browser local storage.

[0021] Furthermore, the data preprocessing in step S1 specifically includes:

[0022] S11: Data integrity verification: Verify the uniqueness of each node ID and the existence of the parent node ID, mark invalid nodes or automatically correct them according to preset rules; including obtaining the input tree-shaped nested structure data from the backend, each node contains id, parentId and name attributes, verify the integrity of the data, ensure that all required fields exist and are in the correct format, check the uniqueness of the node ID and the validity of the parent node ID;

[0023] S12: Parent-child relationship correction: traverse the data set, check and correct parent-child relationship errors. If it is found that the parent node ID of a node does not exist, adjust the parent node ID of the node or treat it as a top-level node;

[0024] S13: Bidirectional index table construction: Generate a hash table to store node ID and object mapping, and add a parent node pointer and a reference to the direct child node set for each node; including traversing the entire tree structure, creating a bidirectional index pointing to its parent node and child node for each node, and building a bidirectional index table of the parent-child relationship between nodes;

[0025] S14: Data flattening processing: Convert the nested structure into a linear array through depth-first traversal, retain the hierarchical depth information, and sort by node type and hierarchical depth according to business needs; convert the tree structure data into a one-dimensional array to complete the data flattening processing.

[0026] Furthermore, the step S2 of dynamic virtualization rendering specifically includes:

[0027] S21: Visible area calculation: Based on the current scroll position and viewport size, calculate the node index range within the visible area;

[0028] S22: Node selective rendering: only render nodes within the calculated index range;

[0029] S23: Scroll event monitoring: monitor user scroll events and determine whether to trigger lazy loading of data based on the scroll position;

[0030] S24: Seamless lazy loading of data: When the lazy loading conditions are met, seamless lazy loading of data is achieved.

[0031] Furthermore, the step S3 of intelligent incremental update specifically includes:

[0032] S31: Changed node identification: The comparison algorithm compares the data status before and after to identify the changed nodes;

[0033] S32: Re-rendering judgment: According to the component lifecycle control mechanism of the React framework, it is judged whether the changed node needs to be re-rendered;

[0034] S33: Local re-rendering execution: local re-rendering is performed for the identified changed nodes.

[0035] Furthermore, the lazy loading collaborative control in step S4 specifically includes:

[0036] S41: Determine the boundary threshold: the current viewport position and the user scrolling direction factors determine the boundary threshold of the unloaded data;

[0037] S42: Asynchronous data request triggering: When the user scrolls close to the boundary threshold, the asynchronous data request function is triggered to obtain new data;

[0038] S43: New data insertion: dynamically insert the newly acquired data into the existing data set;

[0039] S44: Interface update: Update the user interface to reflect data changes.

[0040] Furthermore, the step S5 global state management specifically includes:

[0041] S51: centralized state initialization: initialize the centralized state to maintain the expansion or collapse and selection state of the tree component;

[0042] S52: state update processing: when the state changes, the centralized state is updated through the corresponding action function and reducer function;

[0043] S53: Status information acquisition: Use the useAppStateSelector function as a state selector in the React component to obtain the required status information;

[0044] S54: State persistence storage: Use the browser's LocalStorage or SessionStorage to store centralized state to achieve state persistence;

[0045] S55: State recovery operation: when the component is initialized or the page is refreshed, the state information is read from the local storage and the component state is restored.

[0046] The tree component optimization method based on the React framework integrating virtualized rendering and incremental rendering provided by the present invention has many significant beneficial effects compared with the prior art:

[0047] High-performance rendering of large-scale data: Through virtualized rendering technology, only visible elements in the viewport are rendered, reducing unnecessary DOM operations and greatly improving page loading speed. Combined with incremental rendering, only the changed parts are updated locally to avoid the overhead caused by global refresh. The combination of these two technologies enables components to easily support the rendering of 200,000 or more tree data structures, breaking through the limitation of React rendering large amounts of data and effectively solving the problem of slow loading and jamming of traditional React tree components when processing large amounts of data.

[0048] Fast search response: WebWorker is used to implement non-blocking search, and combined with data flattening and efficient indexing, millisecond-level search response is achieved under large amounts of data. Data flattening converts nested data structures into one-dimensional arrays that are easier to manage and query. Combined with efficient indexing, it greatly simplifies search logic and improves search efficiency, allowing users to quickly locate required information in massive amounts of data.

[0049] Smooth interactive experience: Supports common tree-like interactive events such as click, expand or collapse, and maintains smoothness and stability when handling these interactive operations. By optimizing the scrolling experience, such as applying CSS3 transition properties or JavaScript animation libraries to achieve smooth scrolling effects, and using CSS hardware acceleration to improve scrolling performance, it provides users with a natural and efficient operating experience, improving user satisfaction and loyalty to the application.

[0050] Efficient memory management: Adopt technologies such as data flattening and IndexedDB caching large amounts of data to minimize memory usage. Data flattening reduces the memory overhead caused by complex nested structures. IndexedDB stores large amounts of data locally, reducing the amount of data in memory, reasonably allocating and utilizing system resources, avoiding system crashes or performance degradation caused by excessive memory consumption, and ensuring long-term stable operation of applications.

[0051] Adaptive rendering strategy: It can dynamically adjust the rendering batch and quantity according to the device performance. On devices with lower performance, it automatically reduces the number of renderings to ensure page smoothness; on high-performance devices, it increases the rendering batch to make full use of device performance and improve user experience. This adaptive strategy enables the application to maintain good performance on different devices and expands the scope of application of the application.

[0052] Enhanced functional scalability: Through centralized state management mechanisms, such as using libraries such as Redux or MobX, the readability and maintainability of the code are improved. Clear definitions of actions and reducers make state changes more transparent and controllable, making it easier for developers to manage and debug component states. At the same time, state persistence and recovery functions, such as using the browser's LocalStorage or SessionStorage to save user states, allow users to continue operations from where they left off last time when refreshing the page or re-entering the application, improving the convenience of the application and user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0054] Figure 1 It is a flow chart of the tree component optimization method of the present invention based on the React framework integrating virtualized rendering and incremental rendering. DETAILED DESCRIPTION

[0055] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present invention. Instead, they are merely examples of devices and methods consistent with some aspects of the present invention as detailed in the appended claims.

[0056] Embodiment 1

[0057] See also Figure 1 This embodiment provides a tree component optimization method based on the React framework integrating virtualized rendering and incremental rendering, comprising the following steps:

[0058] S1: Data preprocessing: Verify the integrity and correct the relationship of the input tree-shaped nested structure data, build a bidirectional index table of the parent-child relationship between nodes, and flatten the data into a one-dimensional array;

[0059] S2: Dynamic virtualized rendering: Dynamically calculate the node index range within the visible area according to the real-time scrolling position of the user's viewport, render only the nodes within the range, and implement seamless lazy loading of data through scroll event monitoring;

[0060] Virtualized rendering technology aims to optimize performance for long lists or complex hierarchical structures (such as Tree components). In the React framework, traditional rendering methods tend to render the entire component tree to the DOM at one time, which may cause performance bottlenecks when processing large amounts of data, such as long loading times and high memory usage. To overcome these challenges, this technology uses a virtual scrolling mechanism to render only the elements visible in the viewport instead of rendering all the data. In this way, unnecessary DOM operations can be greatly reduced, thereby improving the page loading speed and the smoothness of interaction. The core of implementing this technology is to dynamically calculate which nodes should be rendered and dynamically update these nodes based on the user's scrolling behavior. At the same time, in order to ensure user experience, edge cases must be properly handled, including data loading and unloading during fast scrolling, precise control of the scroll bar position, and other issues.

[0061] S3: Intelligent incremental update: The changed nodes are identified through the state change comparison algorithm, and based on the component lifecycle control mechanism of the React framework, only the changed nodes are partially re-rendered;

[0062] As an effective performance optimization strategy, incremental rendering is particularly suitable for scenarios with large data sets that are frequently updated. Traditionally, whenever the state changes, React re-renders all affected components and their subcomponents. For complex component trees, this will result in a lot of unnecessary redrawing work, even if only a few data items have actually changed. By implementing incremental rendering, we can perform local updates only on the parts that have changed, thus avoiding the performance burden of a full refresh. In the specific operation process, a mechanism must be built to monitor data changes and intelligently determine which parts need to be re-rendered. This requires not only a deep understanding of React's state management and lifecycle hooks, but also the use of tools such as shouldComponentUpdate or React.memo to minimize unnecessary rendering operations.

[0063] As a preferred method, the intelligent incremental update in this embodiment can be performed in the following manner:

[0064] Identification of changed nodes: Use a special state change comparison algorithm to compare the data status before and after, so as to accurately identify the changed nodes. In React components, the state management mechanism is used to control the data status. Once the data state changes, by comparing the key attributes of the node in the two states before and after, such as node name, parent node ID, etc., the changed data points can be accurately found.

[0065] Re-rendering judgment: According to the component lifecycle control mechanism of the React framework, specific tools and methods are used to determine whether the changed nodes need to be re-rendered each time the state or attributes are updated.

[0066] Use the shouldComponentUpdate method: For class components, define the shouldComponentUpdate method in the component. In this method, compare the key information of the node in the current attribute and the attribute to be updated, such as the node's ID, name, and parent node ID. If these key information have not changed, it is determined that re-rendering is not necessary to avoid wasted work. For example, in a class component that displays tree structure nodes, when the key attributes of the node are consistent before and after the update, re-rendering is not performed to save system resources.

[0067] Use React.memo to wrap components: For functional components, use React.memo to wrap them. React.memo will perform a shallow comparison of the attributes before and after the component. If there is no difference between the attributes before and after, the component will be prevented from re-rendering. However, for complex attributes, such as objects with multiple levels or array-type attributes, shallow comparison may not be able to accurately determine whether re-rendering is required. At this time, a custom comparison function can be provided to compare the key parts of the attributes in detail according to business needs, so as to more accurately decide whether to re-render the component. For example, in a functional component that processes tree nodes, a custom comparison function can be used to accurately determine the changes in node attributes and avoid unnecessary rendering.

[0068] Partial re-rendering execution: Through a specific local re-rendering function, a local update operation is performed on the identified changed nodes. Only a virtual DOM fragment containing the changed nodes is created, and then this fragment is rendered to the corresponding position on the page, instead of re-rendering the entire component tree. Combined with the previous use of shouldComponentUpdate or React.memo to avoid unnecessary component re-rendering, the local re-rendering function can more accurately update the nodes that have actually changed, greatly improving rendering efficiency. For example, in a tree component, when the information of a node changes, only the node and its related parts are re-rendered, instead of redrawing the entire tree structure, which effectively reduces the rendering workload and improves system performance.

[0069] S4: Lazy loading collaborative control: When the user scrolls close to the boundary threshold of unloaded data, an asynchronous data request is triggered and new data is dynamically inserted into the existing data set, while updating the user interface;

[0070] S5: Global state management: Use centralized state to maintain the expansion, collapse and selection status of tree components, and implement state persistence and recovery through browser local storage.

[0071] In this embodiment, data flattening refers to the process of converting nested data structures into a one-dimensional array form that is easier to manage and query. In the context of the Tree component, the original data is usually a multi-layer nested object or array, which makes traversal, search and update operations complicated and inefficient. Through flattening, we flatten all nodes into a list, each of which contains references to its parent node and child nodes. The advantage of doing this is that it can greatly simplify the logical processing flow, such as searching for a specific node or determining the hierarchical relationship between nodes. At the same time, it also provides basic support for other optimization measures (such as virtualized rendering and incremental rendering) because they rely on efficient data access patterns. However, implementing this process requires considering how to maintain the hierarchical relationship between nodes and how to perform various operations without destroying the original structure.

[0072] In this embodiment, the steps for efficient state management need to be further explained: when faced with complex components such as Tree, relying solely on the state management mechanism within the component may lead to difficulties in code maintenance and debugging. Therefore, adopting a centralized state management solution has become an inevitable trend. Libraries such as Redux or MobX allow us to store all the states of the application in a single location and adjust the state through well-defined actions and reducers. This approach not only improves the readability and maintainability of the code, but also makes the state change process more transparent and controllable. Especially in the Tree component, due to the interactive behaviors such as selecting, expanding or collapsing a large number of nodes, excellent state management is particularly critical. It helps us effectively track the changes in the state of each node, ensure the synchronous rendering of the interface and background data, and thus reduce unnecessary calculations.

[0073] As an implementation manner, the data preprocessing in step S1 of this embodiment specifically includes:

[0074] S11: Data integrity verification: Verify the uniqueness of each node ID and the existence of the parent node ID, mark invalid nodes or automatically correct them according to preset rules; including obtaining the input tree-shaped nested structure data from the backend, each node contains id, parentId and name attributes, verify the integrity of the data, ensure that all required fields exist and are in the correct format, check the uniqueness of the node ID and the validity of the parent node ID;

[0075] S12: Parent-child relationship correction: traverse the data set, check and correct parent-child relationship errors. If it is found that the parent node ID of a node does not exist, adjust the parent node ID of the node or treat it as a top-level node;

[0076] S13: Bidirectional index table construction: Generate a hash table to store node ID and object mapping, and add a parent node pointer and a reference to the direct child node set for each node; including traversing the entire tree structure, creating a bidirectional index pointing to its parent node and child node for each node, and building a bidirectional index table of the parent-child relationship between nodes;

[0077] S14: Data flattening processing: Convert the nested structure into a linear array through depth-first traversal, retain the hierarchical depth information, and sort by node type and hierarchical depth according to business needs; convert the tree structure data into a one-dimensional array to complete the data flattening processing.

[0078] In this step, you first need to obtain tree structure data from the backend. This data usually exists in the form of nested objects or arrays, and each node contains attributes such as id, parentId, name, etc. After obtaining the data, you should use the validateIncomingData function to perform preliminary validation on the data to ensure that all required fields exist and are in the correct format. This step includes checking whether each node has a unique ID, whether the parent node ID points to a valid parent node, etc.

[0079] Then, by traversing the entire tree structure, references to the parent and child nodes are created for each node. At this point, the createLookupTable function is called, which not only helps to establish an easy-to-manage data structure, but also facilitates subsequent operations (such as searching for specific nodes and determining the hierarchical relationship between nodes). This process involves converting the tree structure into a one-dimensional array and maintaining a hash table (lookup table) where the key is the node ID and the value is the object pointing to the node.

[0080] After completing the above steps, you need to fully verify the accuracy of the parent-child relationship. Use the validateAndFixRelations function to traverse the entire data set to check and correct any possible parent-child relationship errors. If a node is found that claims that its parent node ID does not exist, the parent node ID of the node needs to be adjusted or it needs to be treated as a top-level node. This step ensures that the final one-dimensional array not only contains all the node information, but also correctly reflects the hierarchical relationship between them.

[0081] Finally, all node information is integrated and the data is further optimized according to business needs. For example, nodes can be sorted according to node type or layer depth to improve search efficiency. In addition, additional metadata can be added to nodes to better support front-end display and interaction.

[0082] As an implementation manner, the step S2 of dynamic virtualization rendering in this embodiment specifically includes:

[0083] S21: Visible area calculation: Based on the current scroll position and viewport size, calculate the node index range within the visible area;

[0084] S22: Node selective rendering: only render nodes within the calculated index range;

[0085] S23: Scroll event monitoring: monitor user scroll events and determine whether to trigger lazy loading of data based on the scroll position;

[0086] S24: Seamless lazy loading of data: When the lazy loading conditions are met, seamless lazy loading of data is achieved.

[0087] In this implementation, the range of items in the viewport is calculated first: based on the current scroll position and viewport size, which nodes should be rendered. This is to avoid performance issues caused by loading all nodes at once. The task of calculating the visible node index range is undertaken by the calculateVisibleRange function, which is calculated based on the user's scroll position, the viewport height, and the height of each item.

[0088] Secondly, dynamically adjust the displayed content by listening to scroll events: By listening to the user's scroll events, determine whether to load more items or remove items that are no longer in the viewport based on the current position. This method helps reduce unnecessary DOM operations and thus improve page performance. The key lies in the onScrollEvent function, which is not only responsible for detecting whether the user is close to the bottom to trigger lazy loading, but also manages the nodes that have been rendered but are no longer in the visible area and decides when to remove them from the DOM.

[0089] Again, lazy loading is implemented and new data is seamlessly integrated: When the user approaches the bottom, additional data loading requests are triggered, and the newly loaded data is seamlessly integrated into the existing data set to ensure that the user's operation experience is not affected. The loadMoreItemsIfNeeded function plays a role in this process. It decides whether to initiate a new data request based on the scroll position and calls fetchAdditionalNodes to obtain the new data. Subsequently, refreshUIWithNewData is responsible for integrating the new data into the UI to ensure a smooth and seamless transition.

[0090] Finally, optimize the scrolling experience: To further enhance the user experience, you can apply animation effects and smooth transitions during the scrolling process. For example, use CSS3 transition properties or JavaScript animation libraries to achieve smooth scrolling effects. In addition, you can also consider caching some commonly used data to reduce the delay caused by repeated requests.

[0091] As an implementation manner, the step S3 intelligent incremental update in this embodiment specifically includes:

[0092] S31: Changed node identification: The comparison algorithm compares the data status before and after to identify the changed nodes;

[0093] S32: Re-rendering judgment: According to the component lifecycle control mechanism of the React framework, it is judged whether the changed node needs to be re-rendered;

[0094] S33: Local re-rendering execution: local re-rendering is performed for the identified changed nodes.

[0095] In this embodiment, data changes are first monitored: the data source is monitored to identify the changed parts of the data. The detectDataChanges function is used to track data changes to ensure that only the data parts that have actually changed are re-rendered. This function compares the before and after states to accurately locate the changed data points, thereby avoiding the waste of resources caused by full redrawing.

[0096] Second, implement a smart re-rendering strategy: Based on data changes, intelligently decide which components need to be re-rendered. Avoid unnecessary repeated rendering for unchanged parts to improve the overall performance of the application. This step relies on the shouldComponentUpdate logic, which is called every time a state or property is updated to determine whether the current component needs to be re-rendered, based on whether there is a substantial difference between the new and old states or properties.

[0097] Third, perform selective rendering: for specific changes, only the affected parts are re-rendered instead of the entire component or page, which significantly improves the response speed and user experience. The performSelectiveRendering function is used here to perform selective rendering to optimize performance. This function re-renders only the affected parts for specific changes, while keeping the other parts unchanged.

[0098] Finally, optimize rendering performance: In order to further improve rendering efficiency, you can use a variety of optimization techniques, such as batch updates, using virtual DOM, etc. In addition, you can also consider implementing asynchronous rendering, that is, distributing complex rendering tasks to multiple frames to avoid blocking the main thread.

[0099] As an implementation mode, the lazy loading collaborative control in step S4 in this implementation specifically includes:

[0100] S41: Determine the boundary threshold: the current viewport position and the user scrolling direction factors determine the boundary threshold of the unloaded data;

[0101] S42: Asynchronous data request triggering: When the user scrolls close to the boundary threshold, the asynchronous data request function is triggered to obtain new data;

[0102] S43: New data insertion: dynamically insert the newly acquired data into the existing data set;

[0103] S44: Interface update: Update the user interface to reflect data changes.

[0104] The specific implementation method in this embodiment is as follows:

[0105] Set loading threshold: Set a threshold to trigger loading when the user scrolls close to the boundary of unloaded data. The threshold can be flexibly set according to application requirements to balance loading speed and user experience. Here, the determineLoadThreshold function is used, which comprehensively considers factors such as the current viewport position and the user's scrolling direction to determine the best time to initiate an asynchronous request.

[0106] Request data asynchronously: Initiate an asynchronous request to obtain additional data and merge it into the existing data set. Ensure that the newly loaded data can be seamlessly integrated into the existing Tree component without affecting user operations. The fetchAdditionalNodes function will be called here, which is responsible for communicating with the server, obtaining the required data, integrating it into the current data structure, and notifying the UI layer that new data is available for display.

[0107] Refresh the UI to reflect new data: Update the UI to reflect the newly loaded data, and continue to monitor the user's scrolling behavior to prepare for the next lazy loading operation. The refreshUIWithNewData function is used here, which not only updates the interface elements, but also takes into account animation effects and smooth transitions, so that users do not feel the data loading process, providing a continuous and uninterrupted browsing experience.

[0108] Improve lazy loading experience: To further improve the lazy loading experience, a preloading mechanism can be used to preload a portion of data before the user approaches the end to reduce waiting time. In addition, the loading strategy can be dynamically adjusted according to network conditions to ensure a good user experience even in a low-bandwidth environment.

[0109] As an implementation mode, the global state management in step S5 in this embodiment specifically includes:

[0110] S51: centralized state initialization: initialize the centralized state to maintain the expansion or collapse and selection state of the tree component;

[0111] S52: state update processing: when the state changes, the centralized state is updated through the corresponding action function and reducer function;

[0112] S53: Status information acquisition: Use the useAppStateSelector function as a state selector in the React component to obtain the required status information;

[0113] S54: State persistence storage: Use the browser's LocalStorage or SessionStorage to store centralized state to achieve state persistence;

[0114] S55: State recovery operation: when the component is initialized or the page is refreshed, the state information is read from the local storage and the component state is restored.

[0115] In this embodiment, the implementation steps of state management are as follows:

[0116] First, initialize the state management library: initialize the state management library (such as Redux or MobX) and establish a global state storage mechanism. Clarify which states need to be centrally managed and which states can be retained in local components. Configure the core functions of the state management library, including middleware, enhancers, etc., through the initializeGlobalStateStore function to ensure the stability and scalability of the state management system.

[0117] Next, define actions and reducers: Design actions and reducers to describe and process state changes. Make sure each action clearly represents a specific state change, and that reducers can update the global state based on these actions. Define all possible action types and their corresponding processing logic through the defineActionsAndReducers function, making the state change process transparent and controllable.

[0118] Then, access the state efficiently: In the React component, use the state selector to obtain the required part of the state. When the state changes, use React's Context API to share the state when necessary to keep the user interface in sync with the background data. The useAppStateSelector function simplifies the state acquisition process and reduces unnecessary duplication of code, thereby improving development efficiency and application performance.

[0119] Finally, implement state persistence and recovery: In order to provide a better user experience, you can consider implementing state persistence storage, such as using the browser's LocalStorage or SessionStorage to save the user's state to ensure that user data is not lost even if the page is refreshed. In addition, you can also implement a state recovery mechanism to allow users to continue from where they left off last time.

[0120] Embodiment 2

[0121] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with specific embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0122] 1. Data Preprocessing

[0123] 1. Data integrity verification

[0124] Get tree-shaped nested structure data containing id, parentId and name attributes from the backend. For example, in an enterprise organizational structure management system, each employee information is a node, id is the employee number, parentId is the employee number of the superior, and name is the employee name.

[0125] Use the validateIncomingData function to validate the data. This function will traverse each node in the data set and check whether the id is unique. You can create a Set data structure to store the ids that have appeared. Each time you check the id of a new node, determine whether it is already in the Set. For the parent node parentId, check whether it points to a node that already exists in the data set. If an invalid node is found, such as a duplicate id or a parentId pointing to a non-existent node, mark it. In subsequent processing, for the marked invalid node, if its parentId is invalid, you can correct the data according to preset rules, such as setting its parentId to the default top-level organization node ID.

[0126] (II) Amendment of the Father-Son Relationship

[0127] Use the validateAndFixRelations function to traverse the data set. During the traversal process, for each node, determine whether its parentId exists in the data set. If not, process it according to the business logic. For example, in a file directory management system, if the parent directory ID claimed by a file node does not exist, the file node can be regarded as a direct child node under the root directory, that is, its parentId is adjusted to the root directory ID; or according to specific business rules, it can be processed as a new top-level node.

[0128] (III) Bidirectional index table construction

[0129] Traverse the entire tree structure and generate a hash table to store the node ID and object mapping. For example, create a JavaScript object nodeLookup, where the key is the node ID and the value is the corresponding node object.

[0130] Add a parent node pointer and a reference to the direct child node set for each node. During the traversal process, for each node, find the corresponding parent node in nodeLookup through its parentId, and add the current node to the child node set of the parent node; at the same time, add a pointer to the parent node in the current node object. Taking the tree structure of a forum post as an example, each post node establishes a bidirectional association with the parent post (if any) and the child post in this way, which is convenient for quickly finding and managing the relationship between posts.

[0131] 4. Data flattening

[0132] The depth-first traversal algorithm is used to convert the nested structure into a linear array. During the traversal process, the level depth information of each node is recorded. For example, a counter is used to increase the value of the counter when entering a new level and decrease the value of the counter when leaving the level, and the value of the counter is used as the level depth of the node.

[0133] Sort by node type and hierarchical depth according to business needs. For example, in an e-commerce product classification management system, you can sort the product classification from small to large according to the hierarchical depth, which is convenient for front-end display and user search for product classification. After sorting, the tree structure data is converted into a one-dimensional array, which facilitates subsequent virtual rendering and data query.

[0134] 2. Dynamic Virtualization Rendering

[0135] 1. Calculation of Visible Area

[0136] Based on the current scroll position and viewport size, use the calculateVisibleRange function to calculate the node index range within the visible area. For example, in a tree component that displays a large number of file directories, obtain the height of the browser window as the viewport size, and obtain the current scroll offset by listening to the scroll event. Based on the fixed height of each node on the page, calculate the first and last node indexes visible in the current viewport.

[0137] (II) Node Selective Rendering

[0138] Only render nodes within the calculated index range. In React components, conditional rendering is used to filter out the node data that needs to be rendered according to the calculated index range, and then these nodes are rendered to the page using methods such as map functions. For example:

[0139] const visibleNodes = data.slice(startIndex, endIndex);returnvisibleNodes.map((node) => ( <treenode key="{node.id}" node="{node}" / > ));

[0140] (III) Scrolling event monitoring

[0141] The onScrollEvent function is used to listen to user scrolling events. Inside the function, the lazy loading of data is determined based on the scrolling position. For example, when the user scrolls to a certain distance (such as 100 pixels) from the bottom of the currently visible area, the lazy loading condition is considered to be met.

[0142] 4. Seamless lazy loading of data

[0143] When the lazy loading conditions are met, the loadMoreItems function is called to implement seamless lazy loading of data. The loadMoreItems function sends a request to the server to obtain new data. For example, the fetch API is used to send an HTTP request, which carries relevant information about the currently loaded data, such as the ID or level information of the last node, so that the server returns the correct new data. After obtaining the new data, the state of the React component is updated to merge the new data with the existing data, and the relevant nodes are re-rendered to ensure that the user does not feel the interruption of data loading during the scrolling process.

[0144] 3. Intelligent incremental update

[0145] 1. Identification of Changed Nodes

[0146] Use the stateChangeComparisonAlgorithm state change comparison algorithm to compare the data state before and after and identify the changed nodes. In React components, the data state is managed through state management hooks such as useState or useReducer. When the data state changes, in the stateChangeComparisonAlgorithm function, the property values ​​of the two state objects before and after can be compared, such as whether the node's name, parentId and other properties have changed, to accurately find the changed data points.

[0147] (II) Re-rendering judgment

[0148] According to the component lifecycle control mechanism of the React framework, the shouldComponentUpdate function is used to determine whether the changed nodes need to be re-rendered each time the state or attributes are updated. For example, in the shouldComponentUpdate function, the new state or attributes are compared with the old state or attributes. If the changed node attributes affect the display or behavior of the current component, true is returned, indicating that re-rendering is required; otherwise, false is returned to avoid unnecessary rendering.

[0149] 3. Partial re-rendering execution

[0150] Use the performPartialRerender function to perform partial re-rendering for the identified changed nodes. For example, in React, you can create a new virtual DOM fragment containing the changed nodes, and then use React's render method or ReactDOM.render method to render the fragment to the corresponding position on the page instead of re-rendering the entire component tree, thereby improving rendering efficiency.

[0151] 4. Lazy loading collaborative control

[0152] 1. Determination of Boundary Threshold

[0153] The determineBoundaryThreshold function takes into account the current viewport position, the user's scrolling direction and other factors to determine the boundary threshold of unloaded data. For example, in a long list tree structure, the boundary threshold is dynamically adjusted according to the viewport height and the user's scrolling speed. If the user scrolls quickly, the boundary threshold can be appropriately expanded to trigger lazy loading in advance to avoid data loading delays when the user scrolls quickly.

[0154] (II) Asynchronous data request triggering

[0155] When the user scrolls close to the boundary threshold, the asynchronous data request function is triggered to obtain new data. For example, use async / await syntax combined with the fetch API to send a request to the server. In the request, carry relevant information about the current data, such as the amount of loaded data, the ID of the last node, etc. The server returns the corresponding new data based on this information.

[0156] (III) Inserting new data

[0157] Dynamically insert newly acquired data into an existing data set. In React, data insertion is implemented by updating component state. For example, use the concat method to add new data to the end of an existing data array, and then re-render related components so that the new data can be displayed correctly on the page.

[0158] (IV) Interface update

[0159] Call the updateUserInterface function to update the user interface to reflect data changes. When updating the interface, you can add transition animation effects to make data loading and display smoother. For example, use the transition property of CSS or JavaScript animation library to add a fade-in animation to the newly inserted node to improve the user experience.

[0160] 5. Global State Management

[0161] 1. Centralized State Initialization

[0162] Use the initializeCentralizedState function to initialize the centralized state to maintain the expansion / collapse and selection status of the tree component. For example, when using the Redux library, create an initial state object that contains the state of the tree component, such as:

[0163] javascript

[0164] const initialState = {

[0165] treeNodes: {},

[0166] expandedNodes: [],

[0167] selectedNodes: []};

[0168] Then create a Redux store through the createStore function and pass the above initial state as a parameter.

[0169] (II) Status update processing

[0170] When the state changes, the centralized state is updated through the corresponding action function and reducer function based on the React state management mechanism. For example, when the user clicks to expand a node, an EXPAND_NODE action is triggered. In the reducer function, the expandedNodes array is updated according to this action, and the ID of the clicked node is added to the array, thereby realizing the state update and ensuring that the interface display is consistent with the data state.

[0171] (III) Obtaining status information

[0172] Use the useAppStateSelector function as a state selector in a React component to obtain the required state information. For example, in a component that displays a tree structure, use the useAppStateSelector function to obtain the selectedNodes state to determine which nodes are currently selected, and then set the corresponding style or perform specific operations in the component based on this information.

[0173] 4. State persistence storage

[0174] Use the browser's LocalStorage or SessionStorage to store centralized states and achieve state persistence. For example, after each state update, convert the relevant state data (such as expandedNodes and selectedNodes) into a JSON string, and then use the LocalStorage.setItem method to store it locally. For example:

[0175] javascript

[0176] const stateToSave = {

[0177] expandedNodes: expandedNodes,

[0178] selectedNodes: selectedNodes};localStorage.setItem('treeComponentState', JSON.stringify(stateToSave));

[0179] (V) Status recovery operation

[0180] When the component is initialized or the page is refreshed, the state information is read from the local storage and the component state is restored. For example, in the useEffect hook of the component, use the LocalStorage.getItem method to obtain the stored state data, then convert it back to object form, update the component state, and restore the component to the state when the user last left.

[0181] javascript

[0182] useEffect(() => {

[0183] const savedState = localStorage.getItem('treeComponentState');

[0184] if (savedState) {

[0185] const state = JSON.parse(savedState);

[0186] / / Update component status

[0187] }}, []);

[0188] Through the above specific implementation methods, the tree component optimization method based on the React framework integrating virtualized rendering and incremental rendering can be effectively implemented, thereby improving the performance, interactive experience and state management capabilities of the tree component when processing large-scale data.

[0189] Although the embodiments of the present invention have been shown and described above, it will be appreciated that the above embodiments are exemplary and are not to be construed as limitations of the present invention. A person skilled in the art may change, modify, substitute and vary the above embodiments within the scope of the present invention.

Claims

1. A tree component optimization method based on React framework integrating virtualized rendering and incremental rendering, characterized by: The steps include: S1: Data preprocessing: Verify the integrity and correct the relationship of the input tree-shaped nested structure data, build a bidirectional index table of the parent-child relationship between nodes, and flatten the data into a one-dimensional array; S2: Dynamic virtualized rendering: Dynamically calculate the node index range within the visible area according to the real-time scrolling position of the user's viewport, render only the nodes within the range, and implement seamless lazy loading of data through scroll event monitoring; S3: Intelligent incremental update: The changed nodes are identified through the state change comparison algorithm, and based on the component lifecycle control mechanism of the React framework, only partial re-rendering is performed on the changed nodes; S4: Lazy loading collaborative control: When the user scrolls close to the boundary threshold of unloaded data, an asynchronous data request is triggered and new data is dynamically inserted into the existing data set, while updating the user interface; S5: Global state management: Use centralized state to maintain the expansion, collapse and selection state of tree components, and implement state persistence and recovery through browser local storage; The step S5 global state management specifically includes: S51: Centralized state initialization: Initialize the centralized state to maintain the expansion / collapse and selection states of the tree component; S52: state update processing: when the state changes, the centralized state is updated through the corresponding action function and reducer function; S53: Status information acquisition: Use the useAppStateSelector function as a state selector in the React component to obtain the required status information; S54: State persistence storage: Use the browser's LocalStorage or SessionStorage to store centralized state to achieve state persistence; S55: State recovery operation: when the component is initialized or the page is refreshed, the state information is read from the local storage and the component state is restored.

2. The method according to claim 1, characterized in that: The data preprocessing step S1 specifically includes: S11: Data integrity verification: Verify the uniqueness of each node ID and the existence of the parent node ID, mark invalid nodes or automatically correct them according to preset rules; including obtaining the input tree-shaped nested structure data from the backend, each node contains id, parentId and name attributes, verify the integrity of the data, ensure that all required fields exist and are in the correct format, check the uniqueness of the node ID and the validity of the parent node ID; S12: Parent-child relationship correction: traverse the data set, check and correct parent-child relationship errors. If it is found that the parent node ID of a node does not exist, adjust the parent node ID of the node or treat it as a top-level node; S13: Bidirectional index table construction: Generate a hash table to store node ID and object mapping, and add a parent node pointer and a reference to the direct child node set for each node; including traversing the entire tree structure, creating a bidirectional index pointing to its parent node and child node for each node, and building a bidirectional index table of the parent-child relationship between nodes; S14: Data flattening processing: Convert the nested structure into a linear array through depth-first traversal, retain the hierarchical depth information, and sort by node type and hierarchical depth according to business needs; convert the tree structure data into a one-dimensional array to complete the data flattening processing.

3. The method according to claim 2, characterized in that: The step S2 of dynamic virtualization rendering specifically includes: S21: Visible area calculation: Based on the current scroll position and viewport size, calculate the node index range within the visible area; S22: Node selective rendering: only render nodes within the calculated index range; S23: Scroll event monitoring: monitor user scroll events and determine whether to trigger lazy loading of data based on the scroll position; S24: Seamless lazy loading of data: When the lazy loading conditions are met, seamless lazy loading of data is achieved.

4. The method according to claim 3, characterized in that: The step S3 of intelligent incremental update specifically includes: S31: Changed node identification: The comparison algorithm compares the data status before and after to identify the changed nodes; S32: Re-rendering judgment: According to the component lifecycle control mechanism of the React framework, it is judged whether the changed node needs to be re-rendered; S33: Local re-rendering execution: local re-rendering is performed for the identified changed nodes.

5. The method according to claim 4, characterized in that: The step S4 lazy loading collaborative control specifically includes: S41: Determine the boundary threshold: the current viewport position and the user scrolling direction factors determine the boundary threshold of the unloaded data; S42: Asynchronous data request triggering: When the user scrolls close to the boundary threshold, the asynchronous data request function is triggered to obtain new data; S43: New data insertion: dynamically insert the newly acquired data into the existing data set; S44: Interface update: Update the user interface to reflect data changes.

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