Interface data product processing method and device, computer equipment and storage medium

Abstract

The invention relates to an interface data product processing method and device, computer equipment and a storage medium. The method comprises the following steps: acquiring an index data table and a constructed data model, and associating the index data table with the data model; acquiring a configured data service, wherein the data service is generated based on the index data table and the data model; generating a data product based on the data service, and configuring data product information for the data product; and based on the data product information, generating an interface document of the data product, and pushing the interface document. By adopting the method, the interface data product processing efficiency can be improved.

Description

Technical Field

[0001] The present application relates to the field of information technology, and in particular to a method, apparatus, computer equipment, computer-readable storage medium, and computer program product for processing interfaced data products. Background Art

[0002] Driven by the wave of digital transformation, data has become a core asset. Especially in the power industry, the opening and sharing of power grid data is of great significance for improving service quality, enhancing user experience and promoting industry innovation.

[0003] As data demanders' demands for data products become increasingly diversified and personalized, traditional methods usually respond to new data open interface requirements based on interface development and redeployment. For example, if the data open interface requirements change, it is necessary to modify the relevant code and develop a new interface to respond to the data requirements. It can be seen that the traditional interface-based data product method has the problem of low development efficiency. Summary of the Invention

[0004] Based on this, it is necessary to provide an efficient interface data product processing method, device, computer equipment, computer-readable storage medium and computer program product to address the above technical problems.

[0005] In a first aspect, the present application provides a method for processing an interfaced data product, comprising:

[0006] Obtain the indicator data table and the constructed data model, and associate the indicator data table with the data model;

[0007] Get the configured data service, which is generated based on the indicator data table and data model;

[0008] Generate data products based on data services and configure data product information for data products;

[0009] Based on the data product information, generate the interface document of the data product and push the interface document.

[0010] In one embodiment, there are multiple data services; generating a data product based on the data service and configuring data product information for the data product include:

[0011] Filter data service fields from multiple data services;

[0012] Combine multiple filtered data service fields to generate data products;

[0013] Configure the data product information of the data product, which includes the interface protocol, encryption method, desensitization method and data product identification.

[0014] In one embodiment, generating an interface document for a data product based on the data product information includes:

[0015] Get variable parameters of predefined data product interface;

[0016] Based on the data product information, determine the variable parameters and generate the interface access path of the data product;

[0017] The interface document includes the interface access path.

[0018] In one embodiment, the method further comprises:

[0019] Receive and respond to the indicator data query request with data product identifier sent by the client;

[0020] Determine the target data product and target data service corresponding to the data product identifier;

[0021] Obtain the structured query statement template for the target data service and the request parameters for the target data product;

[0022] Generate a structured query statement based on the structured query statement template and request parameters;

[0023] Execute structured query statements to retrieve indicator data query results that match the target data product from the indicator data table;

[0024] Feedback the indicator data query results to the client.

[0025] In one embodiment, before feeding back the indicator data query result to the client, the method further includes:

[0026] Merge the queried indicator data fields that match the target data product;

[0027] The merged indicator data query results are desensitized and encrypted.

[0028] In a second aspect, the present application further provides an interfaced data product processing device, comprising:

[0029] The data association module is used to obtain the indicator data table and the constructed data model, and associate the indicator data table with the data model;

[0030] The data acquisition module is used to obtain the configured data services, which are generated based on the indicator data table and data model;

[0031] A data configuration module is used to generate data products based on data services and configure data product information for the data products;

[0032] The data push module is used to generate the interface document of the data product based on the data product information and push the interface document.

[0033] In a third aspect, the present application further provides a computer device comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps in any one of the above-mentioned embodiments of the interfaced data product processing method when executing the computer program.

[0034] In a fourth aspect, the present application further provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the steps in any one of the above-mentioned embodiments of the interfaced data product processing method are implemented.

[0035] In a fifth aspect, the present application also provides a computer program product, comprising a computer program, which, when executed by a processor, implements the steps of any one of the above-mentioned embodiments of the interfaced data product processing method.

[0036] The aforementioned interfaced data product processing method, apparatus, computer device, computer-readable storage medium, and computer program product, when a new data demander accesses the system or a data demander has new requirements, differs from existing interfaced data product processing methods that rely on redeveloping new interfaces or modifying program code and testing and deploying them. By associating indicator data tables and data models and configuring data services based on the associated indicator data tables and data models, the method improves the flexibility and efficiency of data service generation, obtains configured data services, and generates data products based on these data services. This facilitates the rapid adjustment and deployment of new data services and data products based on business needs, reduces the likelihood of redevelopment or large-scale modification of existing systems, and improves the flexibility and responsiveness of data product generation. After configuring data product information for a data product, an interface document for the data product is generated based on the data product information and pushed to the system. Generating interfaced data products through this parameterized configuration approach not only improves data product generation efficiency and reduces uncertainty and complexity during the development process, but also enhances the scalability and adaptability of the system, helping to shorten the development cycle of interfaced data products and reduce production costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the following briefly introduces the drawings required for use in the embodiments of the present application or related technical descriptions. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying any creative work.

[0038] Figure 1A diagram illustrating an application environment of an interfaced data product processing method in one embodiment;

[0039] Figure 2 A flowchart of a method for processing interfaced data products in one embodiment;

[0040] Figure 3 A flowchart of a method for processing interfaced data products in another embodiment;

[0041] Figure 4 A flowchart of a method for processing interfaced data products in another embodiment;

[0042] Figure 5 A schematic diagram of an interfaced data product configuration process in one embodiment;

[0043] Figure 6 A schematic diagram of an interfaced data product calling process in one embodiment;

[0044] Figure 7 It is a structural block diagram of an interfaced data product processing device in one embodiment;

[0045] Figure 8 FIG. 1 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0046] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0047] Simply put, data products are products that use data to achieve business goals. Their core is to fully utilize data as a production factor to achieve specific business goals, solve practical problems, serve specific users, and generate business value.

[0048] The interface data product processing method provided in the embodiment of the present application can be applied to Figure 1 In the application environment shown, the terminal 102 communicates with the server 104 via a network. The data storage system can store data that the server 104 needs to process. The data storage system can be integrated on the server 104 or placed on the cloud or other network servers.

[0049] Specifically, the operator may push the collected indicator data table to the database through the terminal 102, and send a data association message to the server 104 through the terminal 102. The server 104 obtains the indicator data table and the constructed data model, associates the indicator data table and the data model, and configures the data service based on the indicator data table and the data model, and uploads the configured data service to the server 104. The operator then sends a data product configuration message to the server 104 through the terminal 102. The server 104 obtains the configured data service, and then generates a data product based on the data service, and configures data product information for the data product. Finally, based on the data product information, an interface document for the data product is generated and the interface document is pushed.

[0050] Terminal 102 may include, but is not limited to, various personal computers, laptops, smartphones, tablets, IoT devices, and portable wearable devices. IoT devices may include smart speakers, smart TVs, smart air conditioners, smart car devices, and projectors. Portable wearable devices may include smart watches, smart bracelets, and head-mounted devices. Head-mounted devices may include virtual reality (VR) devices, augmented reality (AR) devices, smart glasses, and the like. Server 104 may be a standalone physical server, a server cluster or distributed system consisting of multiple physical servers, or a cloud server providing cloud computing services.

[0051] In an exemplary embodiment, Figure 2 As shown, a method for processing interface data products is provided, which is applied to Figure 1 The server 104 in FIG. 1 is used as an example to illustrate the process, which includes the following steps (hereinafter referred to as S) S100 to S400. Among them:

[0052] S100: Obtain an indicator data table and a constructed data model, and associate the indicator data table with the data model.

[0053] In practical applications, a pre-built data model defines the structure, type, and relationships of different indicator data. This can involve obtaining an indicator data table from a database and configuring an association between the established indicator data table and the established data table. In this embodiment, using electricity data as an example in a data trading scenario, we obtain an indicator data table index_a for "monthly electricity consumption" and an indicator data table index_b for "daily voltage fluctuation." We configure data model 1 to be associated with indicator data table index_a, and data model 2 to be associated with indicator data table index_b.

[0054] As you can understand, when a data demander requests new data access, the operator pre-creates an indicator data table in the data center and pushes it to the database. To respond to the new data access request, a new indicator data table is retrieved from the database and configured to be associated with the data model. For example, when a new "peak hour power consumption" indicator is added, the operator creates an indicator data table for peak hour power consumption indicators in the data center and pushes it to the database. The operator obtains the power system's indicator data table (e.g., power consumption, voltage, current, and other power indicator data tables) and associates it with the pre-created data model.

[0055] S200: Obtain configured data services, where the data services are generated based on the indicator data table and the data model.

[0056] The data service may include a data service identifier and a structured query statement template.

[0057] In actual applications, operators can pre-write a customized structured query statement template based on the fields in the data model based on business needs, configure a data service identifier, and associate the data service identifier with the structured query statement template to configure the data service. The data service identifier can include a data service number and a data service name. The data service number uniquely identifies the data service, while the data service name summarizes the content of the data service. For example, based on business needs, an operator might configure a data service to query indicator data, such as "select a,b,c from 'xxx indicator table' where aa = [enterprise credit code] and month = [query month]." Another example might be configuring a data service to query a user's electricity consumption data for a specific time period. After determining the indicator data and data model that match the needs, an SQL (Structured Query Language) template might be written, such as "select A,B,C from index_a where code = [code]." The configured data service is then retrieved.

[0058] S300: Generate a data product based on the data service and configure data product information for the data product.

[0059] Data products are interfaced data products, which are open to downstream users through methods such as APIs (Application Programming Interfaces). Data product information may include interface protocols, encryption methods, and desensitization strategies.

[0060] In practical applications, the required data services can be determined based on actual business needs, and associations can be established between the required data services and the data products to be generated. One data service can be configured to correspond to one data product, or multiple data services can be configured to correspond to one data product. For example, multiple data services such as user electricity consumption query, electricity consumption behavior analysis, and energy efficiency recommendations can be combined to generate an energy efficiency management data product for enterprises. According to the requirements of the data product, the interface protocol, encryption protocol, and desensitization strategy are configured for the data product. For example, for this data product, HTTPS (Hypertext Transfer Protocol Secure) is selected as the interface protocol, and the AES (Advanced Encryption Standard) encryption algorithm is used. The desensitization strategy includes desensitizing user sensitive information.

[0061] S400: Generate an interface document for the data product based on the data product information and push the interface document.

[0062] The interface document of the data product is used to enable customers to access the data in the data product.

[0063] In practical applications, an interface document can be generated based on the data product's configured data product information, including information such as API call methods, parameter descriptions, and return data formats. For example, for an energy efficiency management data product, the interface document can be used to call the data product's API to query an enterprise's electricity consumption data and energy efficiency recommendations. After the interface document is generated, it can be pushed to the data requester.

[0064] In the aforementioned interface-based data product processing method, when a new data demander connects to the system or has new requirements, unlike existing interface-based data product processing methods that rely on redeveloping new interfaces or modifying program code and testing and deploying them, this method improves the flexibility and efficiency of data service generation by associating indicator data tables and data models and configuring data services based on the associated indicator data tables and data models. This method then retrieves configured data services and generates data products based on these data services. This facilitates the rapid adjustment and deployment of new data services and data products based on business needs, reduces the likelihood of redevelopment or large-scale modification of existing systems, and improves the flexibility and responsiveness of data product generation. After configuring data product information for the data product, interface documentation for the data product is generated and pushed based on the data product information. Generating interface-based data products through this parameterized configuration approach not only improves data product generation efficiency and reduces uncertainty and complexity during the development process, but also enhances the system's scalability and adaptability, helping to shorten the development cycle of interface-based data products and reduce production costs.

[0065] To improve work efficiency, in an exemplary embodiment, the number of data services is multiple, such as Figure 3 As shown, S300 includes S320 to S360. Among them:

[0066] S320: Filter data service fields from multiple data services.

[0067] The data service field may be an indicator data field included in the data service.

[0068] In practical applications, natural language processing can be used to parse business requirements documents, extract key information, and convert it into data service field combination instructions, thereby filtering the data service fields to be combined from the data service fields of different data services. Alternatively, semantic analysis can be used to establish a mapping relationship between business terms and data service fields. After parsing the business requirements document, the corresponding data service fields can be filtered based on the mapping relationship. For example, field A in data service 1 and field G in data service 3 can be filtered as the data service fields to be combined.

[0069] S340: Combine the multiple filtered data service fields to generate a data product.

[0070] In practical applications, multiple filtered data service fields are combined to generate data products, which data demanders can use for data training, prediction, and other purposes. For example, data model 1 is associated with the indicator data table index_a, and data model 2 is associated with the indicator data table index_b. Data service 1 is configured based on data model 1, and its structured statement template is "select A, B, C from index_a where code = [code]." Data service 2 is configured based on data model 2, and its structured statement template is "select E, F, G from index_b where code = [code]." The data service fields filtered based on the requirements are field A of data service 1 and field G of data service 2. Thus, field A of data service 1 and field G of data service 2 are combined to generate data product 1.

[0071] S360, configure data product information of the data product, the data product information including interface protocol, encryption method, desensitization method and data product identification.

[0072] Among them, the data product identifier represents the unique identifier of the data product.

[0073] In practical applications, continuing with the above example, a randomly generated data product number that does not overlap with other data products can be used as a data product identifier, for example, configuring the data product number of data product 1 as "aaaproduct." Interface protocols, encryption methods, and desensitization methods can be predefined with multiple supported methods and configured based on the data product's processing requirements. For example, interface protocols include RESTful API (Representational State Transfer) and SOAP (Simple Object Access Protocol); encryption methods include AES (Advanced Encryption Standard) and RSA asymmetric encryption; and desensitization methods include field replacement, field masking, and shuffling. Field replacement involves replacing sensitive fields with predetermined fictitious values ​​or fixed characters (such as "*"). For example, substation ID "S001" is replaced with "N123." Field masking involves determining the target masked field within the sensitive field based on the characters to be retained and replacing it with a preset symbol. For example, the telephone number is masked to "138****1234", and the substation address "XX Road, Haidian District, Beijing" is masked to "XX Road, XX District, Beijing".

[0074] In this embodiment, generating data products by combining data services is conducive to quickly adjusting and deploying new data services and data products according to business needs, reducing the possibility of redeveloping or large-scale modification of existing systems, and improving the efficiency, flexibility and demand response speed of data product generation.

[0075] In an exemplary embodiment, based on the data product information, generating the interface document of the data product includes S420 to S440.

[0076] S420: Obtain variable parameters of a predefined data product interface.

[0077] S440 , based on the data product information, determining variable parameters, and generating an interface access path for the data product, where the interface document includes the interface access path.

[0078] In actual applications, it can be a predefined API interface for configuring the interface access path, which includes variable parameters, to obtain the variable parameters of the predefined data product interface. It can be determined that the data product identifier in the data product information is a variable parameter, and the interface access path is generated based on the predefined interface and variable parameters. Exemplarily, the predefined API interface can be / serviceApi / {product_id}, where {product_id} is a variable parameter representing different data product identifiers. Assume that the configured data product identifier is "PHPC001", and generate a data product interface access path such as / serviceApi / PHPC001.

[0079] In other implementations, the interface document also includes request methods, return fields, field annotations, request parameters, etc.

[0080] In this embodiment, the variable parameter path is set through the data product identifier, which improves the scalability of the system and reduces the complexity of interface management.

[0081] After configuring the data product, in an exemplary embodiment, as Figure 4 As shown, the interfaced data product processing method further includes S510 to S560.

[0082] S510: Receive and respond to an indicator data query request carrying a data product identifier sent by a client.

[0083] In actual applications, the client can initiate an indicator data query request based on the interface document. Specifically, the client initiates the indicator data query request using the interface access path, request parameters, and data product identifier in the interface document, such as ' / serviceApi / aaaproduct'. The client then receives and responds to the indicator data query request.

[0084] S520: Determine a target data product and a target data service corresponding to the data product identifier.

[0085] In actual applications, the target data product is determined based on the data product identifier, and the target data service associated with the target data product is determined based on the association between the data product and the data service. For example, if the data product identifier indicates that data product 1 is the target data product, and data product 1 is associated with data service 1 and data service 3, data service 1 and data service 3 are determined as the target data services.

[0086] S530: Obtain a structured query statement template of the target data service and request parameters of the target data product.

[0087] In actual applications, after determining the target service, obtain the SQL query statement template corresponding to the target data service, and obtain the request parameters of the target data product in the indicator data query request.

[0088] S540: Generate a structured query statement based on the structured query statement template and the request parameters.

[0089] In actual applications, obtain request parameters based on the data query request and substitute them into the SQL query statement template of the target data service to construct an SQL query statement instance. For example, construct the SQL query statement "select A,B,C from index_a where code='12132165MB1P09595E'" for data service 1.

[0090] S550: Execute a structured query statement to retrieve indicator data query results that match the target data product from the indicator data table.

[0091] In actual applications, execute SQL query statement instances to query indicator data query results from the indicator data table.

[0092] S560: Feedback the indicator data query result to the client.

[0093] In this embodiment, on the one hand, initiating an indicator data query request through a data product identifier is conducive to improving data access efficiency. On the other hand, through parameterized data service definition and data product generation, the response speed to the client's data needs is improved, which is conducive to improving the timeliness of indicator data, thereby speeding up the data transaction process.

[0094] In an exemplary embodiment, before feeding back the indicator data query result to the client, the interface data product processing method further includes:

[0095] Merge the queried indicator data fields that match the target data product.

[0096] The merged indicator data query results are desensitized and encrypted.

[0097] In actual applications, if the target data product queried by the client is a data product composed of multiple data service fields, the execution results of the structured statements of each data service are merged to obtain the index data query results. For example, if data product 1 contains the A field from data service 1 and the G field from data service 3, the index data query results finally returned will only include the information of these two fields. After obtaining the index data query results, the index data query results are desensitized and encrypted. The index data query results can be desensitized according to the desensitization method of the pre-configured target data product. For example, the desensitization method can be based on a preset desensitization range and a desensitization label corresponding to the desensitization range, replacing the sensitive fields that meet the preset desensitization range with the desensitization label corresponding to the desensitization range. Specifically, the indicator data query result is `{A:130,G:230}`. The predefined masking range and corresponding masking labels are: the masking range 0-200 corresponds to the masking label [0, 200], and the masking range 200-500 corresponds to the masking label [200, 500]. The masked result is `{A:[0,200],G:[200,500]}`. The masked indicator data query result is encrypted according to the encryption method configured in the target data product.

[0098] In this embodiment, through desensitization and encryption processing, data compliance is improved, the security of indicator data query results during transmission and storage is improved, and the possibility of data leakage is reduced.

[0099] In order to more clearly illustrate the interfaced data product processing method provided by this application, a specific embodiment is described below. The specific embodiment includes the following steps:

[0100] S1, obtain the indicator data table and the constructed data model, and associate the indicator data table with the data model.

[0101] S2, obtains multiple configured data services, which are generated based on indicator data tables and data models.

[0102] S3, filter out data service fields from multiple data services, combine the filtered multiple data service fields to generate a data product, and configure data product information of the data product. The data product information includes interface protocol, encryption method, desensitization method and data product identification.

[0103] S4, obtaining variable parameters of a predefined data product interface, determining the variable parameters based on the data product information, and generating an interface access path for the data product, wherein the interface document includes the interface access path.

[0104] For example, Figure 5The figure below illustrates the data product configuration process. Specifically, the data center synchronizes the indicator data table to the database, associates the indicator data table with the established data model, configures the data service based on data requirements through parameterized SQL query templates, and then generates the data product based on actual data requirements by combining data service fields and configuring the data product information.

[0105] S5, receives and responds to the indicator data query request carrying the data product identifier sent by the client, determines the target data product and target data service corresponding to the data product identifier, obtains the structured query statement template of the target data service, and the request parameters of the target data product, generates a structured query statement based on the structured query statement template and the request parameters, executes the structured query statement, and queries the indicator data query results that match the target data product from the indicator data table.

[0106] S6: Merge the queried indicator data fields that match the target data product to obtain the indicator data query result, perform data desensitization and encryption on the indicator data query result, and feed the indicator data query result back to the client.

[0107] In actual applications, after configuring the data product, the process of the client calling the data product is as follows: Figure 6 As shown, the client initiates an indicator data query request carrying query parameters through the interface document of the data product, receives and responds to the data query request, verifies the token, determines the information of the target data product, and thus determines the target data service of the target data product combination, substitutes the request parameters to construct an SQL query statement instance of the target data service and executes it, combines the fields of the execution result to obtain the indicator data query result, desensitizes and encrypts the indicator data query result, and feeds it back to the client.

[0108] It should be understood that, although the various steps in the flowcharts involved in the various embodiments described above are displayed in sequence according to the instructions of the arrows, these steps are not necessarily executed in sequence in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and these steps can be executed in other orders. Moreover, at least a portion of the steps in the flowcharts involved in the various embodiments described above can include multiple steps or multiple stages, and these steps or stages are not necessarily executed and completed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a portion of steps or stages in other steps.

[0109] In an exemplary embodiment, Figure 7As shown, an interfaced data product processing device 600 is provided, comprising: a data association module 610, a data acquisition module 620, a data configuration module 630 and a data push module 640, wherein:

[0110] A data association module 610 is used to associate the indicator data table with the data model;

[0111] Data acquisition module 620, used to obtain the indicator data table and the constructed data model, and obtain the configured data service, the data service is generated based on the indicator data table and the data model;

[0112] The data configuration module 630 is used to generate data products based on data services and configure data product information for the data products;

[0113] The data push module 640 is used to generate an interface document of the data product based on the data product information and push the interface document.

[0114] In an exemplary embodiment, the data configuration module 630 is also used to filter out data service fields from multiple data services; combine the filtered multiple data service fields to generate data products; and configure data product information of the data product, the data product information including interface protocol, encryption method, desensitization method and data product identification.

[0115] In an exemplary embodiment, the data push module 640 is further used to obtain variable parameters of a predefined data product interface; determine the variable parameters based on the data product information, and generate an interface access path for the data product; the interface document includes the interface access path.

[0116] In an exemplary embodiment, the interfaced data product processing device 600 further includes a request receiving module 650, an indicator data query module 660, and a query result feedback module 670, wherein:

[0117] The request receiving module 650 is further configured to receive and respond to an indicator data query request carrying a data product identifier sent by a client.

[0118] The indicator data query module 660 is also used to determine the target data product and target data service corresponding to the data product identifier; obtain the structured query statement template of the target data service and the request parameters of the target data product; generate a structured query statement based on the structured query statement template and the request parameters; execute the structured query statement, and query the indicator data query results that match the target data product from the indicator data table.

[0119] The query result feedback module 670 is further configured to feed back the indicator data query result to the client.

[0120] In an exemplary embodiment, the interfaced data product processing device 600 also includes a data processing module 680 for merging the queried indicator data fields that match the target data product to obtain the indicator data query results, and performing data desensitization and encryption processing on the indicator data query results.

[0121] Each module in the interfaced data product processing device 600 may be implemented in whole or in part through software, hardware, or a combination thereof. Each module may be embedded in or independent of a processor in a computer device in the form of hardware, or may be stored in a memory in the computer device in the form of software, so that the processor can call and execute the corresponding operations of each module.

[0122] In an exemplary embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as shown in FIG. Figure 8 As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, abbreviated as I / O) and a communication interface. The processor, memory and input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and computer program in the non-volatile storage medium. The database of the computer device is used to store data. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, an interfaced data product processing method is implemented.

[0123] Those skilled in the art will understand that Figure 8 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0124] In an exemplary embodiment, a computer device is provided, including a memory and a processor. The memory stores a computer program, and the processor implements the steps of any one of the above-mentioned interfaced data product processing method embodiments when executing the computer program.

[0125] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps of any one of the above-mentioned interfaced data product processing method embodiments are implemented.

[0126] In one embodiment, a computer program product is provided, comprising a computer program, which, when executed by a processor, implements the steps of any one of the above-mentioned interfaced data product processing method embodiments.

[0127] 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, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0128] Those skilled in the art will understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. In particular, any reference to memory, database, or other media used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The databases involved in the various embodiments provided herein may include at least one of a relational database and a non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the various embodiments provided herein may be, but are not limited to, general-purpose processors, central processing units (CPUs), graphics processing units (GPUs), digital signal processors (DSPs), programmable logic devices (PLDs), quantum computing-based data processing logic devices, artificial intelligence (AI) processors, and the like.

[0129] The technical features of the above embodiments can be combined arbitrarily. In order to make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0130] The above-described embodiments merely represent several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present application. It should be noted that a person of ordinary skill in the art may make various modifications and improvements without departing from the spirit of the present application, and these modifications and improvements fall within the scope of protection of the present application. Therefore, the scope of protection of the present application shall be determined by the appended claims.

Claims

1. A method for processing interfaced data products, characterized in that: The method comprises: Obtaining an indicator data table and a constructed data model, and associating the indicator data table with the data model; Obtaining a configured data service, where the data service is generated based on the indicator data table and the data model; generating a data product based on the data service and configuring data product information for the data product; Based on the data product information, an interface document of the data product is generated and pushed.

2. The method according to claim 1, characterized in that There are multiple data services; generating a data product based on the data services and configuring data product information for the data product includes: Filter data service fields from multiple data services; Combine multiple filtered data service fields to generate data products; Configure data product information of the data product, wherein the data product information includes an interface protocol, an encryption method, a desensitization method, and a data product identifier.

3. The method according to claim 2, characterized in that The step of generating an interface document for the data product based on the data product information includes: Get variable parameters of predefined data product interface; Based on the data product information, determining the variable parameter, and generating an interface access path for the data product; The interface document includes an interface access path.

4. The method according to claim 3, characterized in that The method further comprises: Receive and respond to the indicator data query request with data product identifier sent by the client; Determining a target data product and a target data service corresponding to the data product identifier; Obtaining a structured query statement template for the target data service and request parameters for the target data product; Generate a structured query statement based on the structured query statement template and the request parameters; Executing the structured query statement to query the indicator data query results that match the target data product from the indicator data table; Feedback the indicator data query result to the client.

5. The method according to claim 4, characterized in that Before feeding back the indicator data query result to the client, the method further includes: Merge the queried indicator data fields that match the target data product; The merged indicator data query results are desensitized and encrypted.

6. An interface data product processing device, characterized in that: The device comprises: A data association module is used to obtain an indicator data table and a constructed data model, and associate the indicator data table with the data model; A data acquisition module, configured to acquire configured data services, wherein the data services are generated based on the indicator data table and the data model; A data configuration module, configured to generate a data product based on the data service and configure data product information for the data product; The data push module is used to generate an interface document of the data product based on the data product information and push the interface document.

7. The device according to claim 6, characterized in that The data configuration module is also used to: filter out data service fields from multiple data services; combine the filtered multiple data service fields to generate data products; configure data product information of the data product, and the data product information includes interface protocol, encryption method, desensitization method and data product identification.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 5 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 5 are implemented.

10. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 5 are implemented.

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