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

Abstract

The application relates to the technical field of data processing, and the fields of financial insurance business and intelligent medical treatment, and provides a data processing method and device, an electronic device and a computer readable storage medium, the method comprising the following steps: acquiring processing logic information and table information; generating business requirement information according to header content information in the processing logic information and the table information; generating code information based on a preset code generation model and the business requirement information; performing processing on the table information based on the code information to obtain a table processing result; performing verification processing on the table processing result to obtain verification result information; and performing saving processing on the code information in the case that the verification result represents that the table processing result is normal. Through the technical scheme, the human work burden can be reduced, and the processing efficiency of table data is improved.

Description

Technical Field

[0001] The embodiments of this application relate to, but are not limited to, the field of data processing, and particularly to a data processing method, apparatus, electronic device, and computer-readable storage medium. Background Technology

[0002] With the continuous development of society and the economy, people's living standards have been continuously improved, and the financial insurance industry and the smart healthcare field have also developed significantly, ensuring a better quality of life for people. Currently, the insurance industry and the smart healthcare field often require the processing of large amounts of tabular data. This is typically done manually, which not only increases the workload but also leads to low processing efficiency. Summary of the Invention

[0003] The following is an overview of the subject matter described in detail herein. This overview is not intended to limit the scope of the claims.

[0004] To address the problems mentioned in the background section, this application provides a data processing method, apparatus, electronic device, and computer-readable storage medium that can reduce human workload and improve the efficiency of tabular data processing.

[0005] In a first aspect, embodiments of this application provide a data processing method, including: Obtain processing logic information and table information; Based on the processing logic information and the header content information in the table information, business requirement information is generated; Based on the preset code generation model and the business requirement information, generate code information; The table information is processed based on the code information to obtain the table processing result; The table processing results are then validated to obtain validation result information. If the verification result indicates that the table processing result is normal, the code information is saved.

[0006] Secondly, embodiments of this application also provide a data processing apparatus, the apparatus comprising: The acquisition unit is used to acquire processing logic information and table information; A construction unit is used to generate business requirement information based on the processing logic information and the header content information in the table information; The analysis unit is used to generate code information based on a preset code generation model and the business requirement information; An execution unit is used to perform execution processing on the table information based on the code information to obtain the table processing result; The verification unit is used to verify the table processing results and obtain verification result information. The storage unit is used to save the code information when the verification result characterization table processing result is normal.

[0007] Thirdly, embodiments of this application also provide an electronic device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the data processing method described in the first aspect above.

[0008] Fourthly, embodiments of this application also provide a computer-readable storage medium storing computer-executable instructions for performing the data processing method described in the first aspect above.

[0009] The data processing method according to the embodiments provided in this application has at least the following beneficial effects: In the data processing process, processing logic information and table information are first obtained; then, business requirement information is generated based on the processing logic information and the header content information in the table information; next, code information is generated based on a pre-set code generation model and the business requirement information; then, the table information is processed based on the code information to obtain the table processing result; next, the table processing result is verified to obtain verification result information; finally, if the verification result indicates that the table processing result is normal, the code information is saved. Through the above technical solution, by generating code information based on a code generation model and business requirement information, and then processing the table information based on the code information to obtain the table processing result, table data is processed in an intelligent manner, which can effectively reduce the human workload and improve the efficiency of table data processing. Attached Figure Description

[0010] The accompanying drawings are used to provide a further understanding of the technical solutions of this application and constitute a part of the specification. They are used together with the embodiments of this application to explain the technical solutions of this application and do not constitute a limitation on the technical solutions of this application.

[0011] Figure 1 This is a schematic flowchart of a data processing method provided in one embodiment of this application; Figure 2 yes Figure 1 A schematic diagram of a specific implementation method of step S200; Figure 3 yes Figure 1 A schematic diagram of a specific implementation of step S300; Figure 4 yes Figure 1 A schematic diagram of a specific implementation of step S400; Figure 5 yes Figure 1 A schematic diagram of a specific implementation of step S500; Figure 6 Is it completed? Figure 1 A flowchart illustrating a specific implementation method following step S500; Figure 7 Is it completed? Figure 1 A flowchart illustrating a specific implementation method following step S600; Figure 8 This is a schematic diagram of a data processing apparatus provided in one embodiment of this application; Figure 9 This is a schematic diagram of an electronic device provided in one embodiment of this application. Detailed Implementation

[0012] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0013] It should be noted that although functional modules are divided in the device schematic diagram and a logical order is shown in the flowchart, in some cases, the steps shown or described may be performed in a different order than the module division in the device or the order in the flowchart. The terms "first," "second," etc., in the specification, claims, and the aforementioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be noted that, unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of this application only and is not intended to limit this application.

[0014] The embodiments of this application can acquire and process relevant data based on artificial intelligence technology. Artificial intelligence (AI) refers to the theories, methods, technologies, and application systems that use digital computers or machines controlled by digital computers to simulate, extend, and expand human intelligence, perceive the environment, acquire knowledge, and use that knowledge to obtain optimal results.

[0015] AI is a new technical science that studies and develops theories, methods, technologies, and application systems for simulating, extending, and expanding human intelligence. Artificial intelligence is a branch of computer science that attempts to understand the essence of intelligence and produce new intelligent machines that can react in a way similar to human intelligence. Research in this field includes robotics, speech recognition, image recognition, natural language processing, and expert systems. Artificial intelligence can simulate the information processes of human consciousness and thought. Furthermore, artificial intelligence utilizes digital computers or machines controlled by digital computers to simulate, extend, and expand human intelligence, perceiving the environment, acquiring knowledge, and using that knowledge to achieve optimal results—the theories, methods, technologies, and application systems available for use.

[0016] Foundational technologies for artificial intelligence generally include sensors, dedicated AI chips, cloud computing, distributed storage, big data processing, operating / interactive systems, and mechatronics. AI software technologies mainly encompass computer vision, robotics, biometrics, speech processing, natural language processing, and machine learning / deep learning.

[0017] Artificial intelligence, or AI, is the theory, method, technology, and application system that uses digital computers or machines controlled by digital computers to simulate, extend, and expand human intelligence, perceive the environment, acquire knowledge, and use that knowledge to obtain optimal results.

[0018] The servers involved in artificial intelligence technology can be standalone servers or cloud servers that provide basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery networks (CDN), and big data and artificial intelligence platforms.

[0019] This application provides a data processing method, apparatus, electronic device, and computer-readable storage medium. In the data processing process, firstly, processing logic information and table information are acquired; then, business requirement information is generated based on the processing logic information and the header content of the table information; next, code information is generated based on a pre-set code generation model and the business requirement information; then, the table information is processed based on the code information to obtain the table processing result; next, the table processing result is verified to obtain verification result information; finally, if the verification result indicates that the table processing result is normal, the code information is saved. Through the above technical solution, by generating code information based on a code generation model and business requirement information, and then processing the table information based on the code information to obtain the table processing result, table data is processed intelligently, which can effectively reduce the human workload and improve the efficiency of table data processing.

[0020] The data processing method provided in this application relates to the field of data processing technology. The data processing method provided in this application can be applied to a terminal or a server, and can also be software running on either a terminal or a server. In some embodiments, the terminal can be a smartphone, tablet, laptop, desktop computer, etc.; the server can be configured as an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms.

[0021] This application can be used in a wide variety of general-purpose or special-purpose computer system environments or configurations. Examples include: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, and distributed computing environments including any of the above systems or devices. This application can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform specific tasks or implement specific abstract data types. This application can also be practiced in distributed computing environments where tasks are performed by remote processing devices connected via a communication network. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices.

[0022] It should be noted that in all specific embodiments of this application, when processing data related to user identity or characteristics, such as user information, user behavior data, user historical data, and user location information, user permission or consent is obtained first. Furthermore, the collection, use, and processing of this data comply with relevant laws, regulations, and standards. In addition, when embodiments of this application require access to sensitive personal information of users, separate permission or consent from the user is obtained through pop-ups or redirection to confirmation pages. Only after obtaining the user's separate permission or consent is the necessary user-related data required for the proper functioning of these embodiments acquired.

[0023] The embodiments of this application will be further described below with reference to the accompanying drawings.

[0024] like Figure 1 As shown, Figure 1This is a schematic flowchart of a data processing method provided in one embodiment of this application. The data processing method includes the following steps: Step S100: Obtain processing logic information and table information.

[0025] The data processing method provided in this application first acquires processing logic information and table information during the data processing process, preparing for subsequent intelligent processing of the table data based on the processing logic information and table information. The processing logic information is used to characterize the form in which the table information needs to be processed; for example, data extraction, filtering, comparison, and arrangement can be performed on the table information. In some embodiments of this application, the table information can be tables in the insurance business field, such as customer basic information tables, insurance product purchase record tables, claims record tables, customer feedback record tables, insurance business statistics tables, and property insurance business archive tables. In some embodiments of this application, the table information can also be tables in the smart healthcare field, such as patient basic information tables, electronic medical record tables, clinical decision support system tables, smart healthcare technology application tables, and patient health monitoring tables.

[0026] For example, table information can include various types of data. In the insurance business, an insurance product purchase record table can record insurance information, payment information, and related information. Insurance information can include policy number, insurance product name, insurance type, sum insured, premium amount, insurance period, application date, and effective date. Character information can include premium payment method, payment status, and payment date. Related information can include beneficiary information and insured information. Alternatively, in the smart healthcare field, electronic medical records can include medical record summary information, examination result information, treatment record information, and follow-up record information. Medical record summary information includes patient problems, current symptoms, and previous diagnoses; examination result information includes laboratory test results and examination dates; treatment record information includes surgical records, medication records, and treatment dates; and follow-up record information includes follow-up dates and follow-up results.

[0027] It is worth noting that user permission or consent is obtained before acquiring processing logic information and table information. Furthermore, the collection, use, and processing of this data comply with relevant laws, regulations, and standards. In addition, when this application embodiment needs to acquire sensitive personal information of users, separate permission or consent from the user is obtained through pop-ups or redirects to confirmation pages. Only after explicitly obtaining the user's separate permission or consent is the necessary user-related data for the normal operation of this application embodiment acquired.

[0028] In some embodiments of this application, after obtaining the processing logic information and table information, corresponding business requirement information can be generated based on the header content information in the processing logic information and table information. Subsequently, based on the pre-trained code generation model and the generated business requirement information, corresponding code information can be generated. The code information can then be used to process the table information, thereby achieving intelligent processing of table information, reducing the workload of manual processing, and accelerating the processing efficiency of table data.

[0029] Step S200: Generate business requirement information based on the processing logic information and the header content information in the table information.

[0030] The data processing method provided in this application embodiment can generate corresponding business requirement information based on the header content information in the processing logic information and table information after obtaining the processing logic information and table information, so as to prepare for the subsequent generation of code information.

[0031] It is worth noting that in the process of generating business requirement information based on the processing logic information and the header content information in the table information, the header content information is first filtered out from the table information; then, the object information and operation information are determined from the processing logic information, where the object information and operation information correspond one-to-one; next, the object information and the header content information are matched to obtain the target header processing object; finally, the target header processing object is merged with the corresponding operation information to obtain the corresponding business requirement information, which prepares for the subsequent generation of code information.

[0032] It is worth noting that the table information includes header information; in some embodiments of this application, the header information represents the first row or first column of the table, used to describe the meaning of each row or column of data in the table. The header information is crucial for the readability, data management, and analysis of the table. For example, in a policy information table in the insurance business field, the header information may include policy number, customer number, insurance product name, insurance type, sum insured, premium amount, insurance period, application date, effective date, beneficiary information, payment method, and payment status, etc. In an electronic medical record form in the smart healthcare field, the header information may include medical record number, patient number, past medical history, physical examination, preliminary diagnosis, treatment plan, and follow-up plan, etc.

[0033] It is worth noting that corresponding business requirement information can be generated based on the processing logic information and the header information in the table. For example, in the insurance business field, the header information may include policy number, customer number, insurance product name, insurance type, sum insured, premium amount, insurance period, application date, effective date, beneficiary information, payment method, and payment status. The processing logic information can be to sort the policies according to the application date. Therefore, the generated business requirement information can be to sort the insurance information in the policy information table according to the application date in the header information. Similarly, in the smart healthcare field, the header information may include medical record number, patient number, past medical history, physical examination, preliminary diagnosis, treatment plan, and follow-up plan. The processing logic information can be to sort the electronic medical record according to the patient number. Therefore, the generated business requirement information can be to sort the medical record information in the electronic medical record table according to the patient number in the header information.

[0034] like Figure 2 As shown, generating business requirement information based on processing logic information and table header information can include the following steps: Step S210: Filter the header content information from the table information; Step S220: Determine object information and operation information from the processing logic information, wherein the object information and operation information correspond one-to-one; Step S230: Match the object information with the table header content information to obtain the target table header processing object; Step S240: Merge the target header processing object with the corresponding operation information to obtain business requirement information.

[0035] For steps S210 to S240, in the process of generating business requirement information based on the header content information in the processing logic information and the table information, the header content information is first filtered out from the table information; then, the object information and operation information are determined from the processing logic information, wherein the object information and operation information correspond one-to-one; then, the object information and the header content information are matched to obtain the target header processing object; then, the target header processing object is merged with the corresponding operation information to obtain the corresponding business requirement information, which prepares for the subsequent code information generation.

[0036] It's worth noting that the process involves filtering the header information from the table data; then, determining the object information and operation information from the processing logic information, where there's a one-to-one correspondence between the object information and the operation information. The object information represents the object to be operated on, and the operation information represents the method of operation. Matching the object information with the header information yields the target header processing object; finally, merging the target header processing object with the corresponding operation information yields the relevant business requirement information.

[0037] It is worth noting that matching the object information with the header content information yields the target header processing object, i.e., filtering the header processing object corresponding to the object information from the header content information; subsequently, merging the filtered target header processing object with the corresponding operation information yields the corresponding business requirement information, preparing for the subsequent code information generation.

[0038] For example, in the insurance business field, the policy information table may include policy number, customer number, insurance product name, insurance type, sum insured, premium amount, insurance period, application date, effective date, beneficiary information, payment method, and payment status. The processing logic may involve sorting the policies based on the application date; filtering the application date from the table information; determining the application date as the target information from the processing logic; sorting as the operation information; subsequently matching the application date with the header information to determine the target header processing object as the application date; and finally merging the application date and the sorting to obtain the corresponding business requirement information. Alternatively, for electronic medical records in the field of smart healthcare, the header information may include medical record number, patient number, past medical history, physical examination, preliminary diagnosis, treatment plan, and follow-up plan. The processing logic may involve sorting the electronic medical records based on the patient number; filtering the patient number from the table information; determining the object information as the patient number from the processing logic; and sorting the records. Subsequently, matching the patient number with the header information will determine the target header processing object as the patient number. Finally, merging the patient number and the sorted information will yield the corresponding business requirement information.

[0039] Step S300: Generate code information based on the preset code generation model and business requirement information.

[0040] The data processing method provided in this application generates business requirement information based on processing logic information and the header content information in the table information. Then, it can generate corresponding code information based on the pre-trained code generation model and the business requirement information. Subsequently, it can perform execution processing on the table information based on the code information to achieve intelligent data processing, reduce the workload of humans, and improve the processing efficiency of table data.

[0041] It is worth noting that in the process of generating code information based on a preset code generation model and business requirement information, the business requirement information can be converted into instruction information; then, the encoder based on the code generation model encodes the instruction information to obtain instruction encoding information; next, the instruction encoding information is analyzed to obtain instruction analysis information; finally, the decoder based on the code generation model decodes the instruction analysis information to obtain the corresponding code information. Based on the above technical solution, code information generation becomes simpler, more accurate, and faster.

[0042] It's worth noting that code generation models are artificial intelligence-based systems that automatically generate code. They are typically built on robust language model architectures, learning from vast amounts of code data to understand the syntax and semantics of programming languages ​​and generate compliant code snippets or complete programs. Based on these models, code snippets or complete programs can be generated quickly, reducing repetitive work for developers. By learning from large amounts of code data, the models can generate more standardized and less error-prone code. In certain scenarios, code generation models can fully automate code generation, such as generating simple scripts or template code.

[0043] like Figure 3 As shown, generating code information based on a preset code generation model and business requirements information may include the following steps: Step S310: Convert business requirement information into instruction information; Step S320: The encoder based on the code generation model encodes the instruction information to obtain instruction encoding information; Step S330: Analyze and process the instruction encoding information to obtain instruction analysis information; Step S340: The decoder based on the code generation model decodes the instruction analysis information to obtain code information.

[0044] For steps S310 to S340, in the process of generating code information based on a pre-set code generation model and business requirement information, the business requirement information is first converted into instruction information; then, the encoder of the code generation model encodes the instruction information to obtain instruction encoding information; next, the instruction encoding information is analyzed to obtain instruction analysis information; finally, the decoder of the code generation model decodes the instruction analysis information to obtain the corresponding code information. Based on the above technical solution, the generation of code information can be more accurate.

[0045] It is worth noting that, based on the acquisition of business requirement information, this information can be converted into instruction information. This conversion allows the encoder of the code generation model to encode the instruction information. Once the instruction encoding information is obtained, it can be analyzed to produce instruction analysis information. Subsequently, the code generation model can directly decode this instruction analysis information to obtain the corresponding code information.

[0046] It's worth noting that the encoder in a code generation model transforms the input data into a compact, fixed-length representation (typically a vector or tensor), responsible for extracting key information and features from the input. The decoder in a code generation model converts the representation generated by the encoder into output data, which is typically used to generate outputs relevant to the input.

[0047] Step S400: Perform table processing based on code information to obtain table processing results.

[0048] The data processing method provided in this application, after generating code information based on a pre-set code generation model and business requirement information, can then perform execution processing on table information based on the code information to obtain the corresponding table processing results; by performing execution processing on table information through code information, intelligent table data processing can be achieved, reducing human burden and improving the processing efficiency of table information.

[0049] It is worth noting that, given the code information, a pre-defined interpreter can be used to interpret and process the obtained code information to produce code interpretation information. This interpretation information is then converted into code execution instructions. Finally, the table information can be processed according to these instructions to obtain the table processing result. This technical solution enables simple and quick table data processing operations.

[0050] It is worth noting that the table processing result can be obtained by executing code information on the table information. For example, in the insurance business field, for a policy information table, the header information may include policy number, customer number, insurance product name, insurance type, sum insured, premium amount, insurance period, application date, effective date, beneficiary information, payment method, and payment status. The processing logic can be to sort the policies according to the application date. Therefore, the generated code information is used to control the sorting of insurance information in the policy information table based on the application date in the header information. Alternatively, for an electronic medical record table in the smart healthcare field, the header information may include medical record number, patient number, past medical history, physical examination, preliminary diagnosis, treatment plan, and follow-up plan. The processing logic can be to sort the electronic medical record according to the patient number. Therefore, the generated code information is used to control the sorting of medical record information in the electronic medical record table based on the patient number in the header information.

[0051] like Figure 4 As shown, processing table information based on code information to obtain table processing results can include the following steps: Step S410: The code information is interpreted based on a preset interpreter to obtain code interpretation information; Step S420: Convert the code interpretation information into code execution instructions; Step S430: Perform table processing on the table information according to the code execution instructions to obtain the table processing result.

[0052] For steps S410 to S430, in the process of processing table information based on code information to obtain table processing results, firstly, the code information is interpreted using a pre-set interpreter to obtain code interpretation information; then, the code interpretation information is converted into code execution instructions; finally, the table information is processed according to the code execution instructions to obtain the corresponding table processing results. This technical solution makes the table information processing process more intelligent, convenient, and faster.

[0053] It is worth noting that the interpreter can interpret the code information to obtain the corresponding code interpretation information; then it converts the code interpretation information into code execution instructions to prepare for the subsequent execution and processing of table information; subsequently, the code execution instructions can be directly used to execute and process the table information to obtain the table processing results.

[0054] Step S500: Validate the table processing results to obtain validation result information.

[0055] The data processing method provided in this application embodiment, after performing table processing on table information based on code information to obtain table processing results, also needs to verify the table processing results to obtain corresponding verification result information; subsequently, if the verification result indicates that the table processing result is normal, the code information can be saved; if the verification result indicates that the table processing result is abnormal, the code generation model can be adjusted to readjust and retrain the code generation model to improve the accuracy of the code information subsequently generated by the code generation model.

[0056] It's worth noting that validating the table processing results involves comparing them with the expected results. If they match, the validation result is considered normal; otherwise, it's considered abnormal. For example, in the insurance industry, when sorting policy information by application date, it's possible to verify if the application dates are arranged in a specific order. If they are, the table processing result is normal; otherwise, it's abnormal. Similarly, in smart healthcare, when sorting electronic medical record information by number, it's possible to verify if the numbers are arranged in a specific order. If they are, the table processing result is normal; otherwise, it's abnormal.

[0057] like Figure 5 As shown, validating the table processing results to obtain validation result information can include the following steps: Step S510: Determine the standard information of operation requirements based on business needs information; Step S520: The table processing results are checked according to the standard information of the operation requirements to obtain the verification result information.

[0058] For steps S510 to S520, in the process of verifying the table processing results to obtain verification result information, the operation requirement standard information is first determined based on the business requirement information; then, the table processing results are checked against the operation requirement standard information to obtain the corresponding verification result information. If the operation requirement standard information matches the table processing results, the verification result is considered normal; if the operation requirement standard information does not match the table processing results, the verification result is considered abnormal.

[0059] It is worth noting that operational requirement standards can be determined based on business needs information. These operational requirement standards are used to characterize the desired effect of the business requirements. Subsequently, by verifying the table processing results based on the operational requirement standards, the corresponding verification results can be obtained quickly and easily.

[0060] Step S600: If the verification result characterization table processing result is normal, save the code information.

[0061] The data processing method provided in this application, after verifying the table processing results to obtain verification result information, can save the code information if the verification result indicates that the result is normal. Subsequently, when new table information is received, it can be processed based on the previously received code information, further improving the processing efficiency of batch table information and bringing greater convenience to users. It is worth noting that the above technical solution can only be used when performing the same operation on batches of table information, and based on the above technical solution, the processing efficiency of batch table information can be significantly improved.

[0062] like Figure 6 As shown, after validating the table processing results and obtaining the validation result information, the following steps may also be included: Step S610: If the verification result indicates that the table processing result is abnormal, determine the table processing abnormality information from the table processing result. Step S620: Adjust the code generation model according to the exception information in the table.

[0063] For steps S610 to S620, after verifying the table processing results to obtain verification result information, if the verification result indicates that the table processing results are abnormal, the abnormal information of the table processing can be determined from the table processing results. Subsequently, the code generation model can be adjusted based on the abnormal information of the table processing to make the subsequently generated code information more accurate and improve the accuracy of code generation.

[0064] It is worth noting that comparing the processed table results with the expected results indicates an anomaly in the verification process. For example, in the insurance industry, when sorting policy information by application date, it's possible to verify whether the application dates are arranged in a specific order. If they are not, the table processing result is abnormal. Similarly, in the smart healthcare field, when sorting electronic medical record information by serial number, it's possible to verify whether the serial numbers are arranged in a specific order. If they are not, the table processing result is abnormal.

[0065] like Figure 7 As shown, assuming the verification result indicates the table processing result is normal, after saving the code information, the following steps can be included: Step S630: Obtain new table information; Step S640: Perform execution processing on the new table information based on the code information.

[0066] For steps S630 to S640, if the verification result indicates that the table processing result is normal, after saving the code information, new table information can be obtained; then, the new table information is processed based on the code information, without having to regenerate the corresponding code using the code generation model, which further improves the processing efficiency of table information.

[0067] It is worth noting that the new table information can only be processed based on the previous code information if the new table information requires the same operation as the previous table information.

[0068] In addition, such as Figure 8 As shown, one embodiment of this application also provides a data processing apparatus 10, the apparatus comprising: Acquisition unit 100 is used to acquire processing logic information and table information; The construction unit 200 is used to generate business requirement information based on the processing logic information and the header content information in the table information; Analysis unit 300 is used to generate code information based on a preset code generation model and business requirement information; Execution unit 400 is used to perform execution processing on table information based on code information to obtain table processing results; The verification unit 500 is used to verify the table processing results and obtain verification result information. The storage unit 600 is used to save the code information when the verification result characterization table processing result is normal.

[0069] It should be noted that the data processing process first involves acquiring processing logic information and table information; then, based on the processing logic information and the table header information, business requirement information is generated; next, code information is generated based on a pre-defined code generation model and the business requirement information; then, the table information is processed using the code information to obtain the table processing result; next, the table processing result is verified to obtain the verification result information; finally, if the verification result indicates that the table processing result is normal, the code information is saved. This technical solution, which generates code information based on a code generation model and business requirement information, and then processes table information using the code information to obtain the table processing result, intelligently processes table data, significantly reducing the human workload and improving the efficiency of table data processing.

[0070] The specific implementation of the data processing device 10 is basically the same as the specific embodiment of the data processing method described above, and will not be repeated here.

[0071] In addition, such as Figure 9 As shown, one embodiment of this application also provides an electronic device 700, which includes: a memory 720, a processor 710, and a computer program stored on the memory 720 and executable on the processor 710.

[0072] The processor 710 and memory 720 can be connected via a bus or other means.

[0073] The non-transient software program and instructions required to implement the data processing method of the above embodiments are stored in the memory 720. When executed by the processor 710, the data processing method of each of the above embodiments is executed.

[0074] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0075] Furthermore, one embodiment of this application provides a computer-readable storage medium storing computer-executable instructions that are executed by a processor 710 or a controller, for example, by a processor 710 in the above-described device embodiment, causing the processor 710 to perform the data processing method in the above-described embodiment.

[0076] The above embodiments can be used in combination, and modules with the same name in different embodiments may be the same or different.

[0077] The foregoing has described specific embodiments of this application; other embodiments are within the scope of the appended claims. In some cases, the actions or steps described in the claims may be performed in a different order than those shown in the embodiments and may still achieve the desired result. Furthermore, the processes depicted in the drawings do not necessarily have to follow the specific or sequential order shown to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0078] The various embodiments in this application are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, the embodiments of apparatus, devices, and computer-readable storage media are basically similar to the method embodiments, so the descriptions are relatively simple; relevant parts can be referred to the descriptions of the method embodiments.

[0079] The apparatus, device, computer-readable storage medium and method provided in the embodiments of this application are corresponding. Therefore, the apparatus, device and non-volatile computer storage medium also have similar beneficial technical effects as the corresponding method. Since the beneficial technical effects of the method have been described in detail above, the beneficial technical effects of the corresponding apparatus, device and computer storage medium will not be described again here.

[0080] In the 1990s, improvements to a technology could be clearly distinguished as either hardware improvements (e.g., improvements to the circuit structure of diodes, transistors, switches, etc.) or software improvements (improvements to the methodology). However, with technological advancements, many methodological improvements today can be considered direct improvements to the hardware circuit structure. Designers almost always obtain the corresponding hardware circuit structure by programming the improved methodology into the hardware circuit. Therefore, it cannot be said that a methodological improvement cannot be implemented using hardware physical modules. For example, a Programmable Logic Device (PLD) (such as a Field Programmable Gate Array (FPGA)) is such an integrated circuit whose logic function is determined by the user programming the device. Designers can program a digital system themselves to "integrate" it onto a PLD, without needing chip manufacturers to design and manufacture dedicated integrated circuit chips. Moreover, nowadays, instead of manually manufacturing integrated circuit chips, this programming is mostly implemented using "logic compiler" software, which is similar to the software compiler used when writing program development code. The original code before compilation must also be written in a specific programming language, which is called a Hardware Description Language (HDL). There is not just one HDL, but many kinds, such as ABEL (Advanced Boolean Expression Language), AHDL (Altera Hardware Description Language), Confluence, CUPL (Cornell University Programming Language), HDCal, JHDL (Java Hardware Description Language), Lava, Lola, MyHDL, PALASM, RHDL (Ruby Hardware Description Language), etc. Currently, the most commonly used are VHDL (Very-High-Speed ​​Integrated Circuit Hardware Description Language) and Verilog. Those skilled in the art should also understand that by simply performing some logic programming on the method flow using the aforementioned hardware description languages ​​and programming it into an integrated circuit, the hardware circuit that implements the logic method flow can be easily obtained.

[0081] The controller can be implemented in any suitable manner. For example, it can take the form of a microprocessor or processor and a computer-readable medium storing computer-readable program code (e.g., software or firmware) executable by the (micro)processor, logic gates, switches, application-specific integrated circuits (ASICs), programmable logic controllers, and embedded microcontrollers. Examples of controllers include, but are not limited to, the following microcontrollers: ARC625D, Atmel AT91SAM, Microchip PIC18F26K20, and Silicon Labs C8051F320. A memory controller can also be implemented as part of the control logic of the memory. Those skilled in the art will also recognize that, in addition to implementing the controller in purely computer-readable program code form, the same functionality can be achieved by logically programming the method steps to make the controller take the form of logic gates, switches, ASICs, programmable logic controllers, and embedded microcontrollers. Therefore, such a controller can be considered a hardware component, and the means included therein for implementing various functions can also be considered as structures within the hardware component. Alternatively, the means for implementing various functions can be considered as both software modules implementing the method and structures within the hardware component.

[0082] The systems, devices, modules, or units described in the above embodiments can be implemented by computer chips or entities, or by products with certain functions. A typical implementation device is a computer. Specifically, a computer can be, for example, a personal computer, laptop computer, cellular phone, camera phone, smartphone, personal digital assistant, media player, navigation device, email device, game console, tablet computer, wearable device, or any combination of these devices.

[0083] For ease of description, the above apparatus is described by dividing it into various functional units. Of course, in implementing the embodiments of this application, the functions of each unit can be implemented in one or more software and / or hardware.

[0084] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, embodiments of this application can take the form of entirely hardware embodiments, entirely software embodiments, or embodiments combining software and hardware aspects. Furthermore, embodiments of this application can take the form of computer program products implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0085] This specification is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0086] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0087] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0088] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0089] Memory may include non-persistent storage in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash memory (FlashRAM). Memory is an example of computer-readable media.

[0090] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can store information by any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0091] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0092] In this application embodiment, "at least one" refers to one or more, and "more than one" refers to two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent the existence of A alone, A and B simultaneously, or B alone. A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one of the following" and similar expressions refer to any combination of these items, including any combination of singular or plural items. For example, at least one of a, b, and c can represent: a, b, c, a and b, a and c, b and c, or a and b and c, where a, b, and c can be single or multiple.

[0093] The embodiments of this application can be described in the general context of computer-executable instructions, such as program modules, that are executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform a specific task or implement a specific abstract data type. The embodiments of this application can also be practiced in distributed computing environments where tasks are performed by remote processing devices connected via a communication network. In a distributed computing environment, program modules can reside in local and remote computer storage media, including storage devices.

[0094] The various embodiments in this application are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, the system embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions of the method embodiments.

[0095] The above description is merely an embodiment of this application and is not intended to limit this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principle of this application should be included within the scope of the claims of this application.

Claims

1. A data processing method, characterized in that, include: Obtain processing logic information and table information; Based on the processing logic information and the header content information in the table information, business requirement information is generated; Based on the preset code generation model and the business requirement information, generate code information; The table information is processed based on the code information to obtain the table processing result; The table processing results are then validated to obtain validation result information. If the verification result indicates that the table processing result is normal, the code information is saved.

2. The data processing method according to claim 1, characterized in that, The step of generating business requirement information based on the processing logic information and the header content information in the table information includes: Filter the header content information from the table information; Object information and operation information are determined from the processing logic information, wherein the object information and the operation information correspond one-to-one; The object information is matched with the header content information to obtain the target header processing object; The target header processing object is merged with the corresponding operation information to obtain the business requirement information.

3. The data processing method according to claim 1, characterized in that, The code information generated based on the preset code generation model and the business requirement information includes: Convert the business requirement information into instruction information; The encoder based on the code generation model encodes the instruction information to obtain instruction encoding information; The instruction encoding information is analyzed and processed to obtain instruction analysis information; The decoder based on the code generation model decodes the instruction analysis information to obtain the code information.

4. The data processing method according to claim 1, characterized in that, The step of performing table processing based on the code information to obtain table processing results includes: The code information is interpreted and processed based on a preset interpreter to obtain code interpretation information; Convert the code interpretation information into code execution instructions; The table information is processed according to the code execution instructions to obtain the table processing result.

5. The data processing method according to claim 1, characterized in that, The verification process for the table processing results, to obtain verification result information, includes: Determine the operational requirement standards based on the aforementioned business needs information; The table processing results are verified according to the standard information of the operation requirements to obtain the verification result information.

6. The data processing method according to claim 1, characterized in that, After verifying the table processing results to obtain verification result information, the method further includes: If the verification result indicates that the table processing result is abnormal, the abnormal table processing information shall be determined from the table processing result; The code generation model is adjusted based on the exception information processed in the table.

7. The data processing method according to claim 1, characterized in that, After saving the code information when the verification result characterization table processing result is normal, the method further includes: Get new form information; The new table information is processed based on the code information.

8. A data processing apparatus, characterized in that, The device includes: The acquisition unit is used to acquire processing logic information and table information; A construction unit is used to generate business requirement information based on the processing logic information and the header content information in the table information; The analysis unit is used to generate code information based on a preset code generation model and the business requirement information; An execution unit is used to perform execution processing on the table information based on the code information to obtain the table processing result; The verification unit is used to verify the table processing results and obtain verification result information. The storage unit is used to save the code information when the verification result characterization table processing result is normal.

9. An electronic device, comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, when the processor executes the computer program, it implements the data processing method as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing computer-executable instructions, characterized in that, The computer-executable instructions are used to execute the data processing method according to any one of claims 1 to 7.

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