Data processing method, electronic device, and computer-readable storage medium

Abstract

Embodiments of the present application provide a data processing method, an electronic device and a computer readable storage medium. The method comprises: obtaining a data query request; concurrently invoking a project data interface based on the data query request to obtain initial project data; performing analysis processing on the initial project data to obtain project level identification information, wherein the project level identification information is used to represent a level path corresponding to the initial project data; performing classification processing on the initial project data based on the project level identification information and a preset classification rule to obtain target project data, and sending the target project data to a front-end service layer. The present application solves the technical problems of low data processing efficiency and complex operation of related data processing methods.

Description

Technical Field

[0001] This application relates to the field of computer technology, and more specifically, to a data processing method, an electronic device, and a computer-readable storage medium. Background Technology

[0002] With the widespread adoption of cloud computing and agile development, Development and Operations (DevOps) has become crucial for improving software delivery efficiency. However, enterprise-level DevOps toolchains generally suffer from fragmented functionality and low integration, leading to process fragmentation. Developers are forced to switch between multiple systems, resulting in complex and inefficient operations. Meanwhile, traditional Continuous Integration / Continuous Deployment (CI / CD) pipelines lack visualized real-time monitoring and intelligent scheduling, resulting in a disconnect between continuous testing and deployment processes, and a lack of a unified platform for tracking quality metrics. Furthermore, code review workflows are inconsistent, and data from related code repository systems is fragmented from DevOps process data, creating data silos and lacking unified data analysis and visualization.

[0003] There is currently no good solution to the above problems. Summary of the Invention

[0004] This application provides a data processing method, an electronic device, and a computer-readable storage medium to at least solve the technical problems of low data processing efficiency and complex operation in related data processing methods.

[0005] According to one aspect of the embodiments of this application, a data processing method is provided. The method is applied to a data processing system, which includes a front-end service layer and a project data interface. The method includes: obtaining a data query request; concurrently calling the project data interface based on the data query request to obtain initial project data; parsing the initial project data to obtain project level identification information, wherein the project level identification information is used to represent the level path corresponding to the initial project data; classifying the initial project data based on the project level identification information and a preset classification rule to obtain target project data; and sending the target project data to the front-end service layer.

[0006] Optionally, obtaining a data query request includes: obtaining a user authentication request; performing verification processing on the user authentication credentials corresponding to the user authentication request and a preset in-memory database to obtain a verification result, wherein the verification result is used to determine whether the user authentication credentials have passed verification; and generating a data query request based on the verification result.

[0007] Optionally, generating a data query request based on the verification result includes: in response to the verification result indicating that the user authentication credential has been verified, generating authentication response information based on the user authentication credential, wherein the authentication response information includes user identity information and access token; and generating a data query request based on the authentication response information.

[0008] Optionally, the data processing method further includes: generating a prompt message in response to the verification result indicating that the user authentication credential failed verification; and sending the prompt message to the front-end service layer so that the target user can re-enter the user authentication credential based on the prompt message.

[0009] Optionally, concurrently calling the project data interface based on the data query request to obtain initial project data includes: concurrently calling the project data interface based on the data query request to obtain basic project data; and filtering the basic project data according to preset filtering rules to obtain initial project data.

[0010] Optionally, the data processing method further includes: obtaining the concurrent call duration; and stopping the concurrent call process in response to the concurrent call duration being greater than or equal to a preset time threshold.

[0011] According to one aspect of the embodiments of this application, another data processing method is also provided. The method is applied to a data processing system, which includes a backend service layer. The method includes: receiving target project data, wherein the target project data is obtained by classifying initial project data based on project hierarchy identification information and preset classification rules, the project hierarchy identification information is obtained by parsing the initial project data, and the initial project data is obtained by concurrently calling the target data interface based on data query requests; rendering the target project data to obtain a hierarchical visual directory; and displaying the hierarchical visual directory in a graphical user interface.

[0012] Optionally, the data processing method further includes: obtaining user authentication credentials; generating a user authentication request based on the user authentication credentials; and sending the user authentication request to the backend service layer.

[0013] According to another aspect of the embodiments of this application, a data processing apparatus is also provided, comprising: a first acquisition module, configured to acquire a data query request; a calling module, configured to concurrently call a project data interface based on the data query request to obtain initial project data; a parsing module, configured to parse the initial project data to obtain project level identification information, wherein the project level identification information is used to represent the level path corresponding to the initial project data; and a classification module, configured to classify the initial project data based on the project level identification information and a preset classification rule to obtain target project data, and to send the target project data to the front-end service layer.

[0014] Optionally, the first acquisition module is further configured to: acquire a user authentication request; perform verification processing on the user authentication credential corresponding to the user authentication request and a preset in-memory database to obtain a verification result, wherein the verification result is used to determine whether the user authentication credential has passed verification; and generate a data query request based on the verification result.

[0015] Optionally, the first acquisition module is further configured to: in response to the verification result indicating that the user authentication credential verification is successful, generate authentication response information based on the user authentication credential, wherein the authentication response information includes user identity information and access token; and generate a data query request based on the authentication response information.

[0016] Optionally, the first acquisition module is further configured to: generate a prompt message in response to the verification result indicating that the user authentication credential failed verification; and send the prompt message to the front-end service layer so that the target user can re-enter the user authentication credential based on the prompt message.

[0017] Optionally, the calling module is also used to: concurrently call the project data interface based on the data query request to obtain basic project data; and filter the basic project data according to preset filtering rules to obtain initial project data.

[0018] Optionally, the calling module is also used to: obtain the concurrent call duration; and stop the concurrent call process in response to the concurrent call duration being greater than or equal to a preset time threshold.

[0019] According to another aspect of the embodiments of this application, a data processing apparatus is also provided, comprising: a receiving module for receiving target project data, wherein the target project data is obtained by classifying initial project data based on project hierarchy identification information and preset classification rules, the project hierarchy identification information is obtained by parsing the initial project data, and the initial project data is obtained by concurrently calling the target data interface based on data query requests; a processing module for rendering the target project data to obtain a hierarchical visual catalog; and a display module for displaying the hierarchical visual catalog in a graphical user interface.

[0020] Optionally, the data processing device further includes: a second acquisition module for acquiring user authentication credentials; a generation module for generating a user authentication request based on the user authentication credentials; and a sending module for sending the user authentication request to the backend service layer.

[0021] According to another aspect of the embodiments of this application, an electronic device is also provided, including: a memory storing an executable program; and a processor for running the program, wherein the program executes the methods in various embodiments of this application when it runs.

[0022] According to another aspect of the embodiments of this application, a computer-readable storage medium is also provided, the computer-readable storage medium including a stored executable program, wherein, when the executable program is running, it controls the device where the computer-readable storage medium is located to perform the methods of various embodiments of this application.

[0023] According to another aspect of the embodiments of this application, a computer program product is also provided, including a computer program that, when executed by a processor, implements the methods of various embodiments of this application.

[0024] According to another aspect of the embodiments of this application, a computer program product is also provided, including a non-volatile computer-readable storage medium storing a computer program that, when executed by a processor, implements the methods in various embodiments of this application.

[0025] According to another aspect of the embodiments of this application, a computer program is also provided, which, when executed by a processor, implements the methods of the various embodiments of this application.

[0026] In this embodiment, asynchronous concurrent calls to the relevant code repository system's Application Programming Interface (API) combined with a custom tree structure construction algorithm are used. This involves obtaining data query requests, concurrently calling the project data interface based on these requests to obtain initial project data, parsing the initial project data to obtain project hierarchy identification information (representing the hierarchical path of the initial project data), and then classifying the initial project data based on the project hierarchy identification information and preset classification rules to obtain target project data. Finally, the target project data is sent to the front-end service layer. This achieves the goal of transforming the flat project data of the relevant code repository system into a hierarchical tree structure and enabling efficient distribution. This improves data processing efficiency and simplifies operations, thus solving the technical problems of low data processing efficiency and complex operations inherent in other data processing methods. Attached Figure Description

[0027] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings:

[0028] Figure 1 This is a schematic diagram of an optional data processing system according to an embodiment of this application;

[0029] Figure 2This is a flowchart of an optional data processing method according to an embodiment of this application;

[0030] Figure 3 This is a flowchart of another optional data processing method according to an embodiment of this application;

[0031] Figure 4 This is a schematic diagram of an optional data processing system method according to an embodiment of this application;

[0032] Figure 5 This is a schematic diagram of another optional data processing method according to an embodiment of this application;

[0033] Figure 6 This is a schematic diagram of another optional data processing method according to an embodiment of this application;

[0034] Figure 7 This is a structural block diagram of an optional data processing apparatus according to an embodiment of this application;

[0035] Figure 8 This is a structural block diagram of another optional data processing apparatus according to an embodiment of this application. Detailed Implementation

[0036] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort should fall within the scope of protection of the present application.

[0037] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0038] With the rapid development of cloud computing, microservice architecture, and agile development methodologies, the development and operation models of enterprise software have undergone fundamental changes. The traditional waterfall development model is no longer sufficient to meet the demands of a rapidly iterating market. DevOps, as a technical practice that integrates software development and operation, has become a key means for modern enterprises to improve software delivery efficiency and quality. Currently, breaking down the collaboration barriers between development and operation teams, and achieving continuous integration (CI) and continuous deployment (CD) through automated processes to promote efficient collaboration across the entire R&D process, has become a core research direction in the field of software engineering.

[0039] However, related DevOps toolchains generally suffer from problems such as fragmented functionality, low integration, poor user experience, and data silos. Various DevOps tools are deployed in a scattered manner, lacking a unified user interface, forcing developers to frequently switch between multiple systems, increasing operational complexity and efficiency losses. Simultaneously, related pipelines are inefficient, lacking visualized real-time monitoring and intelligent scheduling mechanisms, making it difficult to handle high-concurrency scenarios. Continuous Testing (CT) is disconnected from the CI / CD process, and quality metrics such as test coverage and pass rates lack a unified platform for display and tracking, resulting in poor data quality. Furthermore, Pull Request (PR) management lacks a unified workflow, making it difficult to track code merge status and review efficiency. Related code repository system data is fragmented from DevOps process data, forming data silos and lacking unified data analysis and visualization.

[0040] Therefore, the relevant methods still suffer from technical problems such as low data processing efficiency and complex operation.

[0041] According to an embodiment of this application, a method embodiment for data processing is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0042] Figure 1 This is a schematic diagram of an optional data processing system according to an embodiment of this application, such as... Figure 1 As shown. Figure 1 This application provides a detailed schematic diagram of the overall architecture of the enterprise-level DevOps end-to-end automated management platform. The architecture employs a layered design, comprising, from bottom to top, an infrastructure layer, a backend service layer, a frontend service layer, and a client access layer.

[0043] The infrastructure layer provides Docker-based resource scheduling and containerization support, and leverages a lightweight Python 3.13 slim image to achieve "build once, run anywhere" cross-platform deployment capabilities, ensuring system compatibility and deployment efficiency. Docker is an open-source application container engine that packages applications and their dependencies into standardized, lightweight containers.

[0044] The backend service layer is based on the FastAPI (Fast Application Programming Interface) asynchronous framework and the Python asynchronous HTTP client (aiohttp), supporting high-concurrency Representational State Transfer Application Programming Interface (RESTful API) services. It is configured with Cross-Origin Resource Sharing (CORS) middleware to support access from multiple front-end domains, enabling username-and-password-based user authentication and authorization management. FastAPI is a high-performance asynchronous web framework based on Python. For data integration, the code repository integration module supports query functions such as project lists, commit records, branch management, and enterprise email filtering. It uses a custom algorithm to construct a hierarchical tree structure of project data from relevant code repository systems, automatically handling API pagination and timeout protection, and supporting the retrieval of large amounts of data.

[0045] The front-end service layer is built using Vue 3, TypeScript, and Vite, and includes seven functional modules: Continuous Integration (CI), Continuous Deployment (CD), Continuous Testing (CT), code review (PR), release note management, task monitoring, and a toolkit. It is responsible for user interface rendering and interaction. Vue 3 is the third major version of Vue.js, a progressive JavaScript framework for building user interfaces. TypeScript is an open-source programming language developed by Microsoft that adds a type system to JavaScript. Vite is a next-generation front-end build tool designed to provide a fast development server startup and hot-reload experience.

[0046] Furthermore, the front-end service layer utilizes the Vue 3 Composition API (Composition Application Programming Interface) to achieve logic reuse and responsive layout adaptation. The Composition API is a set of programming interfaces / methods in the Vue 3 framework used to organize component logic.

[0047] The client access layer initiates requests through a browser, which are then processed by the CORS middleware before communicating with the backend. Each layer is decoupled and collaborates through standardized data interfaces, collectively forming a complete DevOps ecosystem loop.

[0048] This embodiment provides a data processing method, which is applied to a data processing system, including a front-end service layer and a project data interface. Figure 2 This is a flowchart of an optional data processing method according to an embodiment of this application, such as... Figure 2 As shown, the process includes the following steps:

[0049] Step S21: Obtain the data query request;

[0050] Step S22: Concurrently call the project data interface based on the data query request to obtain the initial project data;

[0051] Step S23: Parse the initial project data to obtain project level identification information, wherein the project level identification information is used to represent the level path corresponding to the initial project data;

[0052] Step S24: Classify the initial project data based on the project level identification information and preset classification rules to obtain the target project data, and send the target project data to the front-end service layer.

[0053] The aforementioned data processing system represents an enterprise-level DevOps full-process automated management platform built on a microservice architecture. This system includes a front-end service layer and a back-end service layer, which are used to acquire, process, display, and manage project data from relevant code repository systems. The code repository system is a platform for storing, managing, and collaborating on the development of source code, while the back-end service layer is responsible for core business logic processing and interaction with external systems.

[0054] The aforementioned front-end service layer represents a high-efficiency development environment and user interface presentation layer built on the Vue 3 framework, combined with the TypeScript language and Vite build tools. It is responsible for receiving user interaction commands and sending requests to the backend, as well as receiving data returned by the backend and performing visualization rendering.

[0055] The aforementioned project data interface represents the set of API interfaces in the backend service layer used for data interaction with the code repository system. Specifically, it includes standardized RESTful APIs for querying project lists, commit records, branch management, etc. The backend service layer concurrently calls this interface through aiohttp to obtain flattened project data from the relevant code repository system.

[0056] The aforementioned data query request represents a Hypertext Transfer Protocol (HTTP) request containing query conditions sent by the front-end service layer to the project data interface. This request is used to trigger the back-end service layer to retrieve specific relevant code repository system project data, such as project lists and commit records.

[0057] The initial project data mentioned above represents the raw, flattened data set obtained from the relevant code repository system through concurrent calls to the project data interface. It typically contains the project's basic attributes and metadata, such as the project identifier (ID), project name (name_with_namespace), and commit history.

[0058] The aforementioned project hierarchy identifier information represents the hierarchical path information parsed from the project name field in the initial project data. Specifically, it includes hierarchical node information such as organization name, product line name, and project name. This information is used to represent the hierarchical relationship of the organization, product line, or sub-project to which the initial project data belongs, that is, to define the position of the project in the tree structure and the parent-child node relationship, such as the tree structure path of "organization / product line / project".

[0059] The aforementioned preset classification rules represent logical mapping rules based on the fields defined in the project hierarchy identifier information. These fields can be namespaces, path separators, etc. These rules are used to parse and classify the flattened initial project data into the corresponding hierarchy nodes, dividing the initial project data into different hierarchy nodes to construct a tree structure that conforms to business logic.

[0060] The target project data mentioned above represents a collection of project data with a hierarchical tree structure formed after parsing and classification. This data structure clearly shows the hierarchical relationship between projects, which facilitates hierarchical visualization by the front-end service layer.

[0061] For example, when obtaining a data query request, the user enters query conditions, such as a specific product line or time range, through the browser interface of the front-end service layer. The front-end service layer captures the above input information, assembles it into a data query request containing filter parameters, and sends the request to the project data interface of the back-end service layer via the HTTP protocol.

[0062] This application embodiment uses concurrent calls to the project data interface based on data query requests to obtain initial project data. For example, after receiving a data query request, the backend service layer utilizes the asynchronous programming capabilities of the FastAPI framework and the aiohttp asynchronous HTTP client to simultaneously initiate multiple concurrent requests to the project data interface of the code repository system according to the parameters in the request. This concurrent call mechanism avoids synchronous blocking, quickly retrieves a large amount of raw project data (i.e., initial project data) from the flattened code repository system, and processes the API pagination logic to obtain the complete dataset.

[0063] This application embodiment obtains project hierarchy identification information by parsing the initial project data. For example, the backend service layer, through the code repository system integration module, calls the code repository system API interface to traverse the obtained initial project data and calls the build_project_tree algorithm to dynamically construct a tree structure from the flattened initial project data of the code repository system according to hierarchical relationships, such as organization / product line / project.

[0064] Specifically, the backend service layer parses the `name_with_namespace` field of each project record. By identifying separators in the field, such as forward slashes or other separators, it extracts the hierarchical path string representing the organization, product line, and sub-project, generating project hierarchical identification information. For example, the project record `{"name_with_namespace":"xxx / EVB / BCM / BCMproject","id":312}` is parsed into the hierarchical path `{"EVB":{"BCM":{"BCMproject":[{"id":312}]}}}`.

[0065] This application embodiment classifies initial project data based on project hierarchy identifier information and preset classification rules to obtain target project data, and then sends the target project data to the front-end service layer. Exemplarily, the back-end service layer, according to preset classification rules and using project hierarchy identifier information as the key, recursively inserts the initial project data into a tree structure to construct hierarchical target project data. After construction, the back-end service layer encapsulates the target project data into a JSON response via a standardized RESTful API and sends it to the front-end service layer. Upon receiving the data, the front-end service layer uses the Tool Kit module to render it into a hierarchical, visual directory structure for user browsing and manipulation.

[0066] Based on the above steps S21 to S24, this embodiment of the application adopts an asynchronous concurrent call to the application programming interface of the relevant code repository system combined with a custom tree structure construction algorithm. By obtaining a data query request, and then concurrently calling the project data interface based on the data query request, initial project data is obtained. The initial project data is then parsed to obtain project hierarchical identification information, which represents the hierarchical path corresponding to the initial project data. The initial project data is then classified based on the project hierarchical identification information and preset classification rules to obtain target project data. The target project data is then sent to the front-end service layer. This achieves the goal of transforming the flat project data of the relevant code repository system into a hierarchical tree structure and realizing efficient distribution, thereby improving data processing efficiency and simplifying operations. This solves the technical problems of low data processing efficiency and complex operation in related data processing methods.

[0067] Optionally, obtaining a data query request includes: obtaining a user authentication request; performing verification processing on the user authentication credentials corresponding to the user authentication request and a preset in-memory database to obtain a verification result, wherein the verification result is used to determine whether the user authentication credentials have passed verification; and generating a data query request based on the verification result.

[0068] The aforementioned user authentication request represents an initial HTTP request sent by the front-end service layer to the back-end service layer after receiving the login information entered by the user. This request contains sensitive information such as username and password, and is used to obtain the access token required for subsequent operations.

[0069] The aforementioned user authentication credentials represent the identity information entered by the user, which may specifically include a username and password. These credentials are used to compare the user's identity with records in the storage system during the authentication process to confirm the legitimacy of the user's identity.

[0070] The aforementioned preset in-memory database refers to a high-speed data storage component, such as a Redis instance, deployed in the memory of the backend service layer server. It is used to store hashed user authentication information or session state to provide low-latency credential verification services and avoid high-frequency reads from the persistent database.

[0071] The above verification result represents the status identifier generated by the backend service layer after comparing the user authentication credentials with the preset in-memory database. This identifier clearly indicates whether the user authentication credentials match, thereby determining whether to allow the generation of data query requests or deny access.

[0072] For example, when obtaining a data query request, a user authentication request is first required. Specifically, the user enters their username and password through the login page of the front-end service layer. The front-end service layer captures the input data, assembles it into a user authentication request containing user authentication credentials, and sends the request to the authentication interface of the back-end service layer via Hypertext Transfer Protocol Secure (HTTPS).

[0073] Secondly, the user authentication credentials corresponding to the user authentication request are verified against the preset in-memory database to obtain a verification result. This result determines whether the user authentication credentials have passed verification. Upon receiving a user authentication request, the backend service layer extracts the user authentication credentials and compares them with the corresponding credentials stored in the preset in-memory database. If a matching user authentication credential exists in the preset in-memory database, a verification success result is generated; otherwise, if no matching credential exists, a verification failure result is generated. This process leverages the high-speed read / write capabilities of the preset in-memory database to complete authentication within milliseconds.

[0074] Then, a data query request is generated based on the verification result. For example, the backend service layer determines whether the verification result indicates successful verification. If the verification result is successful, the backend service layer generates a data query request context containing an access token and appends the access token to the subsequent data query request; if the verification result is unsuccessful, the backend service layer returns an error message and does not generate a data query request. These steps ensure that only authenticated users can initiate subsequent business data queries.

[0075] Based on the above optional embodiments, this application embodiment introduces a preset in-memory database to quickly verify user authentication credentials and strictly controls the generation of data query requests based on the verification results. This effectively solves the problems of high user authentication latency and weak security filtering mechanisms in related technologies, realizes low-latency authentication and strict access control in high-concurrency scenarios, and significantly improves the system's security, response speed, and resource utilization efficiency.

[0076] Optionally, generating a data query request based on the verification result includes: in response to the verification result indicating that the user authentication credential has been verified, generating authentication response information based on the user authentication credential, wherein the authentication response information includes user identity information and access token; and generating a data query request based on the authentication response information.

[0077] The authentication response information mentioned above represents a data packet returned by the backend service layer to the frontend service layer after successful verification. This data packet contains information used to identify the user's identity and a token used for subsequent authentication requests. The authentication response information is in JSON (JavaScript Object Notation) format, where JSON is a lightweight data exchange format.

[0078] The aforementioned user identification information represents attribute data used to uniquely identify authenticated users, specifically including basic information such as user ID, name, and email address, which is used to distinguish different users and display relevant user information in the system.

[0079] The aforementioned access token represents a temporary credential string generated by the backend service layer, i.e., an access token. This token is used to prove the legitimacy of the user's identity in subsequent data query requests, replacing the transmission of username and password for each request, thereby improving security and achieving stateless authentication.

[0080] In this embodiment, when generating a data query request based on the verification result, the first step, in response to a successful verification of the user authentication credentials, is to generate authentication response information based on the user authentication credentials. This authentication response information includes user identity information and an access token. For example, when the backend service layer determines that the verification result indicates the user authentication credentials have been verified, it extracts the user's detailed information from a preset in-memory database or an associated user information table to generate user identity information. Simultaneously, the backend service layer generates a time-sensitive and secure random string as an access token. The backend service layer combines and encapsulates the user identity information and the access token to form authentication response information, which is then returned to the frontend service layer via an HTTP response.

[0081] Then, a data query request is generated based on the authentication response information. For example, the front-end service layer receives the authentication response information and parses out the access token. The front-end service layer appends this access token to the subsequent business request header, assembling it into a data query request containing authentication information. The front-end service layer sends the generated data query request to the back-end service layer. When the back-end service layer receives this request, it verifies the validity of the access token to confirm the user's identity, thereby allowing the execution of subsequent data query operations.

[0082] Based on the above optional embodiments, this application embodiment generates authentication response information containing user identity information and access token after verification, and generates a data query request based on the information. This effectively solves the problems of logical complexity and security risks caused by the separation of identity authentication and business requests in the prior art, realizes rapid identification of user identity and stateless secure authentication, and significantly improves the rigor of the system authentication process, the security of data transmission, and the efficiency of front-end and back-end interaction.

[0083] Optionally, the data processing method further includes: generating a prompt message in response to the verification result indicating that the user authentication credential failed verification; and sending the prompt message to the front-end service layer so that the target user can re-enter the user authentication credential based on the prompt message.

[0084] The above message indicates a standardized error message returned by the backend service layer to the frontend service layer when verification fails. This message informs the frontend user of the specific reason or status of the authentication failure so that the frontend can provide corresponding interface feedback.

[0085] The aforementioned target user refers to an end user attempting to access the data processing system. This user enters user authentication credentials on the front-end service layer interface and updates the input content based on the prompts.

[0086] In this embodiment, a prompt message is generated in response to a verification result indicating that the user authentication credential has failed verification. For example, the backend service layer determines that the verification result indicates the user authentication credential has failed verification. Based on a preset error code mapping rule, the backend service layer generates a prompt message containing an error description, such as "Username or password incorrect." The backend service layer encapsulates the prompt message in an HTTP response status code and response body, such as 401 Unauthorized, and prepares to send it to the frontend.

[0087] Then, in this embodiment of the application, a prompt message is sent to the front-end service layer so that the target user can re-enter their user authentication credentials based on the prompt message. Exemplarily, the back-end service layer sends an HTTP response containing the prompt message back to the front-end service layer via a network protocol. The front-end service layer captures this response, parses the prompt message, and displays it prominently on the login interface, such as in a red text box. After seeing the prompt message, the target user changes their username or password in the front-end input box and submits new user authentication credentials again, thereby triggering a new round of authentication.

[0088] Based on the above optional embodiments, this application embodiment generates and sends a prompt message when verification fails, guiding the target user to re-enter the user authentication credentials. This effectively solves the problems of unclear authentication failure feedback and broken operation process in the prior art, realizes accurate perception of authentication failure status and on-the-spot retry, and significantly improves the smoothness of user interaction, the intuitiveness of error handling and the overall ease of use of the system.

[0089] Optionally, concurrently calling the project data interface based on the data query request to obtain initial project data includes: concurrently calling the project data interface based on the data query request to obtain basic project data; and filtering the basic project data according to preset filtering rules to obtain initial project data.

[0090] The aforementioned basic project data represents the raw, flattened data set obtained directly from the relevant code repository system through concurrent calls to the project data interface. This data includes complete fields such as project ID, project name, and commit history.

[0091] The aforementioned preset filtering rules represent data filtering logic defined based on the filtering conditions in the data query request. These rules are used to remove records that do not meet the conditions from the basic project data, retaining the target data. For example, filtering conditions can be time range, branch name, company email address, etc.

[0092] In this embodiment, when concurrently calling the project data interface based on data query requests to obtain initial project data, the initial calls are first made to the project data interface to obtain basic project data. For example, the backend service layer, through the code repository system integration module, calls the code repository system application interface to parse the filter parameters in the data query request. Utilizing the asynchronous features of the FastAPI framework, multiple aiohttp asynchronous HTTP client sessions are instantiated. The backend service layer constructs multiple concurrent HTTP GET requests to the code repository system project data interface based on the parameters. These requests are sent in parallel and await responses. The backend service layer collects the response results of all concurrent requests and merges them into a basic project data set containing complete original records. This set may contain a large amount of redundant data unrelated to the current query conditions. The backend service layer automatically handles pagination logic through asynchronous requests, supporting the retrieval of a large number of submitted records, such as 100 records per page.

[0093] Then, in this embodiment of the application, the basic project data is filtered according to preset filtering rules to obtain initial project data. For example, the backend service layer traverses the basic project data set, comparing each project record with the preset filtering rules defined in the data query request. For instance, it checks whether the project creation time is within a specified range, whether the project branch conforms to a specific naming convention, or whether the email address of the submitter is a corporate email address. The backend service layer removes basic project data records that do not conform to the preset filtering rules, retains the records that meet the requirements, and finally generates a simplified initial project data set, which is then passed to the subsequent parsing and processing module.

[0094] Based on the above optional embodiments, this application embodiment obtains basic project data by concurrently calling the project data interface based on data query requests, and then filters the basic project data according to preset filtering rules to obtain initial project data. This effectively solves the problem of resource waste caused by serial blocking of data acquisition and invalid data transmission in the prior art, realizes rapid retrieval and accurate filtering of large-scale data in high-concurrency environments, significantly reduces system network load and computing overhead, and improves the real-time performance and overall operating efficiency of data processing.

[0095] Optionally, the data processing method further includes: obtaining the concurrent call duration; and stopping the concurrent call process in response to the concurrent call duration being greater than or equal to a preset time threshold.

[0096] The above concurrent call duration represents the total time consumed by the backend service layer from initiating a concurrent HTTP request for the project data interface until all concurrent requests are completed or a specific termination condition is triggered. This duration reflects the system's performance in processing batch data requests under the current network environment and load.

[0097] The aforementioned preset time threshold represents the upper limit of time pre-configured based on system stability requirements and user experience standards. This threshold is used to define the tolerance limit of concurrent call processes. When the actual running time exceeds this threshold, it is determined that the call process has a timeout risk or performance abnormality.

[0098] The above concurrent call process indicates that the backend service layer uses the FastAPI asynchronous framework and the aiohttp asynchronous HTTP client to simultaneously initiate multiple data retrieval requests to the project data interface of the code repository system. This process aims to improve data retrieval efficiency through parallel processing.

[0099] The above-described process for stopping concurrent calls indicates that when the duration of concurrent calls exceeds a preset time threshold, the backend service layer actively interrupts unfinished concurrent HTTP requests, releases relevant network resources and asynchronous task handles, and implements an operational mechanism to prevent resource waste and system blocking.

[0100] For example, when obtaining the concurrent call duration, the backend service layer records the start timestamp when initiating the concurrent call process. As the aiohttp asynchronous task executes, the backend service layer monitors the status of all concurrent requests in real time. When all completed requests are aggregated or timeout check logic is triggered, the backend service layer calculates the difference between the current time and the start timestamp to obtain the current concurrent call duration, and compares this duration with the preset time threshold configured by the system.

[0101] In this embodiment, the concurrent call process is stopped when the concurrent call duration is greater than or equal to a preset time threshold. For example, the backend service layer determines whether the calculated concurrent call duration meets the condition of "greater than or equal to the preset time threshold." If the condition is met, the backend service layer immediately sends cancellation instructions to all unresponsive aiohttp asynchronous tasks, forcibly terminating the remaining concurrent HTTP requests. The backend service layer releases the memory resources and network connections associated with the terminated tasks and records timeout logs, thereby ending the current concurrent call process and preventing the invalidation of system resources.

[0102] Based on the above optional embodiments, this application embodiment effectively solves the problems of resource waste and system stability risks caused by the lack of timeout protection for concurrent requests in the prior art by obtaining the concurrent call duration and stopping the concurrent call process when it is detected to be greater than or equal to a preset time threshold. It realizes dynamic circuit breaking and resource reclamation in the asynchronous task execution process, and significantly improves the robustness, response speed and overall security of the system when dealing with network latency or interface anomalies.

[0103] Figure 3 This is a flowchart of another optional data processing method according to an embodiment of this application, such as... Figure 3 As shown. Applied to a data processing system, which includes a backend service layer, the data processing method includes: receiving target project data, wherein the target project data is obtained by classifying initial project data based on project hierarchy identification information and preset classification rules; the project hierarchy identification information is obtained by parsing the initial project data; and the initial project data is obtained by concurrently calling the target data interface based on data query requests; rendering the target project data to obtain a hierarchical visual directory; and displaying the hierarchical visual directory in a graphical user interface.

[0104] The aforementioned backend service layer represents a service module built on the FastAPI high-performance asynchronous framework. This module is responsible for receiving frontend requests, processing business logic, calling external API interfaces, and interacting with the database, providing high-concurrency data processing capabilities and stable API service support for the embodiments of this application.

[0105] The aforementioned target data interface represents a RESTful API endpoint provided by the relevant code repository system for querying project information. The backend service layer concurrently accesses this interface through the aiohttp asynchronous HTTP client to obtain a large amount of basic project data.

[0106] The above rendering process refers to the process of converting structured target project data into a graphical component data format that the front end can recognize. For example, the graphical component data format that the front end can recognize can be a JSON object tree or a Document Object Model (DOM) node structure. This process maps the data logic into the attributes required by the visual elements so that the front-end framework can draw the interface.

[0107] The above-mentioned hierarchical visualization directory represents a tree-structured view of project hierarchy displayed in the front-end graphical user interface. This view intuitively reflects the inclusion relationship between organizations, product lines, and projects, and allows users to expand or collapse nodes to browse project details.

[0108] The graphical user interface described above represents a front-end display interface built on the Vue 3 framework and combined with TypeScript. This interface provides users with interactive operation entry points through a browser window, including a login page, a project list page, and a data display area, which are used to present a hierarchical visual directory and other business module information.

[0109] This application embodiment receives target project data, which is obtained by classifying initial project data based on project hierarchy identification information and preset classification rules. The project hierarchy identification information is obtained by parsing the initial project data, and the initial project data is obtained by concurrently calling the target data interface based on data query requests. For example, the backend service layer first obtains the initial project data by concurrently calling the target data interface based on data query requests. Then, the backend service layer parses fields such as `name_with_namespace` in the initial project data to extract hierarchical node information such as organization and product line, forming project hierarchy identification information. Next, the backend service layer applies preset classification rules to classify each project record in the initial project data into the corresponding organization node and product line node according to the project hierarchy identification information, recursively constructing a tree-like data structure containing parent-child relationships, and finally generating the target project data and passing it to the frontend service layer.

[0110] The target project data is rendered to obtain a hierarchical visual directory. For example, the front-end service layer receives the target project data returned by the back-end service layer. Leveraging Vue 3's reactivity, the front-end service layer maps the target project data to a component tree structure, generating corresponding user interface (UI) component instances for each level node and setting their expand / collapse states and style attributes. The front-end service layer executes rendering logic, converting the component tree into the final hierarchical visual directory interface elements, ensuring that the hierarchical relationships are accurately presented visually.

[0111] A hierarchical visual catalog is displayed in a graphical user interface. For example, the front-end service layer renders the generated hierarchical visual catalog into the browser's graphical user interface. Users interact with the hierarchical visual catalog through mouse operations, such as clicking node arrows. The interface updates in real time to show or hide child node project information, allowing users to intuitively browse and locate specific projects within the enterprise.

[0112] Based on the above optional embodiments, this application embodiment classifies the initial project data based on project hierarchy identification information and preset classification rules to obtain target project data, and renders the target project data to display a hierarchical visual directory in a graphical user interface. This effectively solves the problem of structural chaos and difficulty in positioning caused by the flat display of project data in the prior art, realizes intuitive visualization and interactive operation of project hierarchy relationships, and significantly improves the efficiency of users browsing project structure, the clarity of data display, and the overall user experience.

[0113] Optionally, the data processing method further includes: obtaining user authentication credentials; generating a user authentication request based on the user authentication credentials; and sending the user authentication request to the backend service layer.

[0114] For example, in the embodiment of this application, user authentication credentials are obtained in the front-end service layer. Specifically, the user accesses the login page of the front-end service layer through the browser of the client access layer. The front-end uses Vue 3 Composition API technology to capture the username and password manually entered by the user on the user interface, thereby obtaining the raw data for identity verification.

[0115] A user authentication request is generated based on the user authentication credentials. For example, the front-end service layer encapsulates the captured username and password into a standard HTTP request format, determines the target interface address, such as the / login interface, and forms a user authentication request containing authentication data, in preparation for sending a verification instruction to the server.

[0116] The user authentication request is sent to the backend service layer. For example, the frontend service layer transmits the generated user authentication request over the network to the backend service layer via the HTTP protocol. The request is processed by a CORS cross-domain middleware to resolve cross-domain issues, and finally reaches the backend service layer for credential verification.

[0117] Based on the above optional embodiments, this application embodiment captures the username and password entered by the user on the front end to generate user authentication credentials, and constructs a user authentication request based on the credentials and sends it to the backend service layer. This achieves decoupling between the view and business logic, utilizes the backend FastAPI asynchronous framework to support high-concurrency processing, and maintains a response time of less than 100 milliseconds under 100 concurrent requests. At the same time, the CORS middleware ensures the security of cross-domain communication, and the in-memory database query enables low-latency reading of user credentials, significantly improving operational efficiency.

[0118] For example, embodiments of this application utilize the CT Platform continuous testing module to achieve visualization and real-time monitoring of the entire testing process, thereby solving the problems of scattered quality assurance data and lack of a unified tracking platform in the existing DevOps system.

[0119] Specifically, the backend service layer integrates the CI / CD pipeline of relevant code repository systems and third-party testing tools to collect key quality indicators in real time for various environments, such as the Staging pre-release environment and the Production environment. These indicators include test pass rate, number of failed test cases, code coverage, and average execution time. The structured data is then stored separately to distinguish the test status of different environments.

[0120] At the presentation level, the front-end service layer utilizes Vue 3 component technology to render intuitive statistical cards and data tables: the statistical cards centrally display an overview of core metrics, such as overall pass rate and coverage, while the data tables list in detail the name of each test suite, test case statistics, execution time, and current status badge. Test case statistics include, but are not limited to, pass, failure, and skip counts. Furthermore, through the Task Monitoring module's scheduled retrieval mechanism, the front-end can refresh the latest test data in real time, ensuring that developers can keep abreast of test dynamics.

[0121] For example, this application embodiment achieves automated generation of structured release instructions through the dynamic template technology of the Release Note release management module, thereby solving the problems of high maintenance costs and unintuitive information display in traditional version release documents. In specific implementation, users first view a version overview through the front-end Release Note page, such as the latest version, versions to be released, and the total number of releases, and can filter by project or status using drop-down filters. When a user clicks on a specific version card, the front-end sends a request to the back-end based on the version ID, and the back-end data processing module then loads detailed data such as the version's highlights, code repository system commit records, and test reports. Subsequently, the front-end uses Vue 3's dynamic component technology to dynamically load the corresponding display template according to the version type, such as feature updates, bug fixes, etc., and renders the acquired data in a structured manner on the page. The above mechanism not only achieves automated assembly of version information, keeping the loading time of the version details page within 500ms, but also improves the readability of information through differentiated template design, effectively reducing the document maintenance costs for developers during the version release process, and achieving standardized management of the version release process.

[0122] For example, embodiments of this application utilize the collaborative working mechanism of the Task Monitoring module and the PipelinePlugins management module to achieve visualized tracking and flexible expansion of the entire DevOps process.

[0123] Specifically, the backend task scheduling module is responsible for periodically triggering CI / CD pipelines and various test tasks, while the TaskMonitoring module collects the execution status and log information of these tasks in real time, forming a unified task monitoring view. Meanwhile, the Pipeline Plugins module supports custom pipeline plugins, such as static code analysis and security scanning, and provides an interface for installing, configuring, and enabling these plugins in the front-end Tool Kit, achieving plug-and-play functionality. When the Task Monitoring module detects a task failure, the system automatically associates the corresponding plugin with the pipeline node and sends alerts via instant messaging or email, ensuring that the fault can be quickly located and handled. This embodiment not only achieves transparent monitoring of the entire DevOps process but also greatly improves the platform's scalability through its plug-in architecture, enabling flexible adaptation to customized business scenarios and meeting diverse automated operation and maintenance needs.

[0124] Figure 4 This is a schematic diagram of an optional data processing system method according to an embodiment of this application, such as... Figure 4As shown in the diagram, this figure illustrates the complete request interaction process under the front-end and back-end separation architecture in this embodiment, demonstrating the efficient collaboration mechanism between the Vue 3 front-end and the FastAPI back-end. Specifically, the user first initiates a business request through the browser. The front-end service layer uses the Vue 3 framework to process the user interface and sends an HTTP request to the back-end FastAPI service via the Fetch API. After receiving the request, the back-end service layer first handles cross-domain issues using a cross-domain resource sharing middleware, and then performs user credential verification and business logic processing. User credentials are stored in a pre-defined in-memory database. After successful verification, the back-end returns standardized JSON response data, which the front-end receives and renders to the user interface.

[0125] Figure 5 This is a schematic diagram of another optional data processing method according to an embodiment of this application, such as... Figure 5 As shown in the diagram. This diagram illustrates in detail the entire user authentication process based on a front-end and back-end separation architecture, specifically corresponding to... Figure 1 This scenario illustrates the interaction between the authentication and authorization module and the front-end login. First, the user accesses the login page of the front-end service layer through a client browser and enters their username and password. The front-end uses a Vue 3 composite application interface to capture the user's authentication credentials, including the username and password. Then, the front-end sends an authentication request to the back-end FastAPI application via an HTTP request, such as the ` / login` interface. This request is first processed by a cross-domain resource sharing middleware to resolve cross-domain communication issues. Upon receiving the request, the back-end calls the authentication and authorization module to query and verify the user's credentials from the pre-set in-memory database in the infrastructure layer. If the credentials are verified, the back-end generates and returns an authentication response, a JSON response containing the user's ID, name, email address, and access token. If verification fails, a standardized error message is returned. Finally, the front-end displays a login success screen or an error message based on the back-end's response, thus completing the entire authentication loop. This process vividly demonstrates the technical effects of low-latency credential reading, fast response under high concurrency, and cross-domain security.

[0126] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties. Furthermore, the collection, use and processing of the relevant data must comply with the relevant laws, regulations and standards of the relevant countries and regions, and corresponding operation entry points are provided for users to choose to authorize or refuse.

[0127] Figure 6 This is a schematic diagram of another optional data processing method according to an embodiment of this application, such as... Figure 6As shown. The method includes:

[0128] Step S601: Obtain user authentication request;

[0129] Step S602: Verify the user authentication credentials corresponding to the user authentication request and the preset memory database to obtain the verification result. The verification result is used to determine whether the user authentication credentials have passed the verification.

[0130] Step S603: In response to the verification result that the user authentication credential verification is successful, an authentication response information is generated based on the user authentication credential, wherein the authentication response information includes user identity information and access token;

[0131] Step S604: Generate a data query request based on the authentication response information;

[0132] Step S605: In response to the verification result that the user authentication credential failed to be verified, a prompt message is generated;

[0133] Step S606: Send the prompt message to the front-end service layer so that the target user can re-enter the user authentication credentials based on the prompt message;

[0134] Step S607: Concurrently call the project data interface based on the data query request to obtain basic project data;

[0135] Step S608: Filter the basic project data according to the preset filtering rules to obtain the initial project data;

[0136] Step S609: Obtain the concurrent call duration;

[0137] Step S610: In response to the concurrent call duration being greater than or equal to a preset time threshold, the concurrent call process is stopped;

[0138] Step S611: Parse the initial project data to obtain project level identification information, wherein the project level identification information is used to represent the level path corresponding to the initial project data.

[0139] Step S612: Classify the initial project data based on the project level identification information and preset classification rules to obtain the target project data, and send the target project data to the front-end service layer.

[0140] Based on the above steps S601 to S612, this embodiment of the application adopts an asynchronous concurrent call to the application programming interface of the relevant code repository system combined with a custom tree structure construction algorithm. By obtaining a data query request, and then concurrently calling the project data interface based on the data query request, initial project data is obtained. The initial project data is then parsed to obtain project hierarchical identification information, wherein the project hierarchical identification information is used to represent the hierarchical path corresponding to the initial project data. The initial project data is then classified based on the project hierarchical identification information and preset classification rules to obtain target project data, and the target project data is sent to the front-end service layer. This achieves the purpose of transforming the flat project data of the relevant code repository system into a hierarchical tree structure and realizing efficient distribution, thereby achieving the technical effects of improving data processing efficiency and simplifying operation, and thus solving the technical problems of low data processing efficiency and complex operation of related data processing methods.

[0141] Figure 7 This is a structural block diagram of an optional data processing apparatus according to an embodiment of this application, such as... Figure 7 As shown. It should be noted that this device can be used to execute the aforementioned data processing method. The device includes: a first acquisition module 701, used to acquire a data query request; a calling module 702, used to concurrently call the project data interface based on the data query request to obtain initial project data; a parsing module 703, used to parse the initial project data to obtain project level identification information, wherein the project level identification information is used to represent the level path corresponding to the initial project data; and a classification module 704, used to classify the initial project data based on the project level identification information and preset classification rules to obtain target project data, and to send the target project data to the front-end service layer.

[0142] Optionally, the first acquisition module 701 is further configured to: acquire a user authentication request; perform verification processing on the user authentication credential corresponding to the user authentication request and a preset in-memory database to obtain a verification result, wherein the verification result is used to determine whether the user authentication credential has passed verification; and generate a data query request based on the verification result.

[0143] Optionally, the first acquisition module 701 is further configured to: in response to the verification result indicating that the user authentication credential verification is successful, generate authentication response information based on the user authentication credential, wherein the authentication response information includes user identity information and access token; and generate a data query request based on the authentication response information.

[0144] Optionally, the first acquisition module 701 is further configured to: generate a prompt message in response to the verification result indicating that the user authentication credential has failed verification; and send the prompt message to the front-end service layer so that the target user can re-enter the user authentication credential based on the prompt message.

[0145] Optionally, module 702 is also used to: concurrently call the project data interface based on the data query request to obtain basic project data; and filter the basic project data according to preset filtering rules to obtain initial project data.

[0146] Optionally, module 702 is also used to: obtain the concurrent call duration; and stop the concurrent call process in response to the concurrent call duration being greater than or equal to a preset time threshold.

[0147] Figure 8 This is a structural block diagram of another optional data processing apparatus according to an embodiment of this application, such as... Figure 8 As shown. Applied to a data processing system, the data processing system includes a backend service layer. The data processing device includes: a receiving module 801, used to receive target project data, wherein the target project data is obtained by classifying initial project data based on project hierarchy identification information and preset classification rules; the project hierarchy identification information is obtained by parsing the initial project data; and the initial project data is obtained by concurrently calling the target data interface based on data query requests; a processing module 802, used to render the target project data to obtain a hierarchical visual directory; and a display module 803, used to display the hierarchical visual directory in a graphical user interface.

[0148] Optionally, the data processing device further includes: a second acquisition module 804, used to acquire user authentication credentials; a generation module 805, used to generate a user authentication request based on the user authentication credentials; and a sending module 806, used to send the user authentication request to the backend service layer.

[0149] Embodiments of this application also provide an electronic device, including: a memory storing an executable program; and a processor for running the program, wherein the program executes the methods described in various embodiments of this application during runtime.

[0150] Obtain data query requests; concurrently call the project data interface based on the data query requests to obtain initial project data; parse and process the initial project data to obtain project level identification information, where the project level identification information is used to represent the level path corresponding to the initial project data; classify the initial project data based on the project level identification information and preset classification rules to obtain target project data, and send the target project data to the front-end service layer.

[0151] Embodiments of this application also provide a computer-readable storage medium, which includes a stored executable program, wherein, when the executable program is executed, it controls the device where the computer-readable storage medium is located to perform the methods of various embodiments of this application:

[0152] Obtain data query requests; concurrently call the project data interface based on the data query requests to obtain initial project data; parse and process the initial project data to obtain project level identification information, where the project level identification information is used to represent the level path corresponding to the initial project data; classify the initial project data based on the project level identification information and preset classification rules to obtain target project data, and send the target project data to the front-end service layer.

[0153] Embodiments of this application also provide a computer program product, including a computer program that, when executed by a processor, implements the methods of various embodiments of this application:

[0154] Obtain data query requests; concurrently call the project data interface based on the data query requests to obtain initial project data; parse and process the initial project data to obtain project level identification information, where the project level identification information is used to represent the level path corresponding to the initial project data; classify the initial project data based on the project level identification information and preset classification rules to obtain target project data, and send the target project data to the front-end service layer.

[0155] Embodiments of this application also provide a computer program product, including a non-volatile computer-readable storage medium for storing a computer program, which, when executed by a processor, implements the methods of various embodiments of this application.

[0156] Obtain data query requests; concurrently call the project data interface based on the data query requests to obtain initial project data; parse and process the initial project data to obtain project level identification information, where the project level identification information is used to represent the level path corresponding to the initial project data; classify the initial project data based on the project level identification information and preset classification rules to obtain target project data, and send the target project data to the front-end service layer.

[0157] Embodiments of this application also provide a computer program that, when executed by a processor, implements the methods described in the various embodiments of this application above:

[0158] Obtain data query requests; concurrently call the project data interface based on the data query requests to obtain initial project data; parse and process the initial project data to obtain project level identification information, where the project level identification information is used to represent the level path corresponding to the initial project data; classify the initial project data based on the project level identification information and preset classification rules to obtain target project data, and send the target project data to the front-end service layer.

[0159] In the above embodiments of this application, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0160] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units can be a logical functional division, and in actual implementation, there may be other division methods. For instance, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual coupling, direct coupling, or communication connection may be through some interfaces; the indirect coupling or communication connection between units or modules may be electrical or other forms.

[0161] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0162] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0163] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server layer, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0164] The above description is only a preferred embodiment of this application. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of this application, and these improvements and modifications should also be considered within the scope of protection of this application.

Claims

1. A data processing method, characterized in that, Applied to a data processing system, the data processing system including a front-end service layer and a project data interface, the method includes: Get data query request; Based on the data query request, the project data interface is called concurrently to obtain the initial project data; The initial project data is parsed to obtain project level identification information, wherein the project level identification information is used to represent the level path corresponding to the initial project data; The initial project data is classified based on the project hierarchy identification information and preset classification rules to obtain target project data, and the target project data is sent to the front-end service layer.

2. The method according to claim 1, characterized in that, Obtaining the data query request includes: Obtain user authentication request; The user authentication credentials corresponding to the user authentication request and the preset memory database are verified to obtain a verification result, wherein the verification result is used to determine whether the user authentication credentials have passed the verification. The data query request is generated based on the verification result.

3. The method according to claim 2, characterized in that, Generating the data query request based on the verification result includes: In response to the verification result indicating that the user authentication credential has passed verification, an authentication response information is generated based on the user authentication credential, wherein the authentication response information includes user identity information and access token; The data query request is generated based on the authentication response information.

4. The method according to claim 2, characterized in that, The method further includes: In response to the verification result indicating that the user authentication credential failed verification, a prompt message is generated; The prompt message is sent to the front-end service layer so that the target user can re-enter the user authentication credentials based on the prompt message.

5. The method according to claim 1, characterized in that, Based on the data query request, the project data interface is called concurrently to obtain initial project data, including: Based on the data query request, the project data interface is called concurrently to obtain basic project data; The basic project data is filtered according to preset filtering rules to obtain the initial project data.

6. The method according to claim 5, characterized in that, The method further includes: Get the duration of concurrent calls; In response to the concurrent call duration being greater than or equal to a preset time threshold, the concurrent call process is stopped.

7. A data processing method, characterized in that, Applied to a data processing system, the data processing system including a backend service layer, the method includes: Receive target project data, wherein the target project data is obtained by classifying initial project data based on project level identification information and preset classification rules, the project level identification information is obtained by parsing the initial project data, and the initial project data is obtained by concurrently calling the target data interface based on data query requests; The target project data is rendered to obtain a hierarchical visual directory; The hierarchical visual catalog is displayed in the graphical user interface.

8. The method according to claim 7, characterized in that, The method further includes: Obtain user authentication credentials; Generate a user authentication request based on the user authentication credentials; The user authentication request is sent to the backend service layer.

9. An electronic device, characterized in that, include: Memory, which stores executable programs; A processor for running the program, wherein the program, when running, performs the method according to any one of claims 1 to 8.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored executable program, wherein, when the executable program is executed, it controls the device on which the storage medium is located to perform the method according to any one of claims 1 to 8.

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