A radio frequency chip data management method, system and readable storage medium

Abstract

The application relates to a radio frequency chip data management method, a system and a readable storage medium, at least one script generation module contained in a front-end page layer is used to import and / or edit a data processing script and generate a script saving instruction, a Java Spring service layer saves the data processing script to a database layer according to the script saving instruction; the front-end page layer triggers a data processing task, the Java Spring service layer generates a script processing request according to the data processing task by acquiring required information from the database layer, a Java Spring service layer and a Python data processing service layer are set, a Socket communication protocol is constructed, the Java Spring service layer sends a script processing request in a JSON format, the Python data processing service layer returns an execution result in a byte stream form, and a Docker container isolation execution mechanism of each script execution module in the Python data processing service layer is matched, so that the safe execution of the Python script in an enterprise-level Java system is realized, and the integration obstacle between the Python and Java technology stacks is overcome.

Description

Technical Field

[0001] This invention belongs to the field of chip data processing of integrated circuits, and particularly relates to a method, system and readable storage medium for radio frequency chip data management. Background Technology

[0002] Radio frequency (RF) chips are core components of wireless communication systems and are widely used in 5G communication, WiFi, Bluetooth, satellite navigation and other fields. In the research and development and production of RF chips, a lot of testing and verification work is required. These tests generate massive amounts of raw data, which need to be parsed, calculated and converted by Python scripts before they can be used for product quality analysis and yield improvement.

[0003] Currently, RF chip data processing mainly relies on users writing Python scripts using tools like Python / MATLAB, or using built-in fixed / customized data processing products. However, both methods have certain technical problems, such as: 1. Users write data processing scripts in Python, while enterprise-level systems often use Java / Spring technology stacks to ensure stability and security. There are integration barriers between the two technology stacks, requiring manual import of the processed data into the enterprise-level system. Furthermore, the code of the other system cannot be directly called and executed, and existing Python scripting skills cannot be reused, necessitating the reimplementation of the same algorithm logic in Java; 2. Scripts are usually stored as files in an external execution environment. Enterprise-level systems cannot directly access and execute external script files, lacking a mechanism to store scripts in a database and dynamically load and execute them at runtime, and making effective script management impossible; 3. For RF chip data parsing / calculation / conversion modules, each user has different processing needs. Fixed / customized processing workflows cannot skip certain modules or adjust the execution order, resulting in poor flexibility and scalability.

[0004] There is currently no effective solution to the technical requirement of how to securely and efficiently execute user-defined Python data processing scripts in an enterprise-level Java system, enabling cross-language technology reuse and flexible configuration of data processing workflows. Summary of the Invention

[0005] To address all or part of the problems in the prior art, this invention provides a radio frequency chip data management method, system, and readable storage medium. It enables the secure and efficient execution of user-defined Python data processing scripts within an enterprise-level Java system, facilitating the reuse of cross-language technology accumulation and flexible configuration of data processing workflows.

[0006] Firstly, this embodiment provides a radio frequency chip data management method, including: Front-end page layer, Java Spring service layer, Python data processing service layer, database layer; S1, according to at least one script generation module included in the front-end page layer, import and / or edit the data processing script and generate a script save instruction, the Java Spring service layer saves the data processing script to the database layer according to the script save instruction, and each data processing script has a unique ID; S2, the front-end page layer triggers a data processing task, the data processing task includes selected script information, and also includes at least one of the file to be processed and first product information; the Java Spring service layer obtains the required information from the database layer according to the data processing task to generate a script processing request, the required information includes the required script ID, or includes the required script and data processing object; S3, the Python data processing service layer receives the script processing request, loads the script corresponding to the required script ID from the database layer to parse the data of the file to be processed, or loads the script corresponding to the required script ID and the data in the data processing object to process the data; the Python data processing service layer returns the completed execution result to the Java Spring service layer, and the Java Spring service layer stores the execution result in the database layer.

[0007] In some embodiments, the data processing task includes a data parsing task, which includes selected script information and a file to be processed; the Java Spring service layer includes a script management module and a data storage module. The script management module obtains the required script ID from the database layer based on the script information, and the JavaSpring service layer generates a script processing request based on the required script ID and the file to be processed. The Python data processing service layer loads the corresponding script according to the required script ID to parse the data in the file to be processed, and obtains the second product information and test data; the data storage module receives the second product information and test data and stores them in the log table and the original data table in the database layer, respectively.

[0008] In some embodiments, the data processing task further includes a data processing task, and the data parsing task includes selected script information and first product information; the Java Spring service layer further includes a data query module and a configuration information management module; The script management module obtains the required script ID from the database layer based on the script information; the data query module obtains the log ID and data table ID from the database layer based on the first product information; the data query module obtains product attribute information from the configuration information management module based on the first product information; and the Java Spring service layer generates a script processing request based on the required script ID, log ID, data table ID, and product attribute information. The Python data processing service layer loads the corresponding script and the original data table according to the required script ID and data table ID to process the data and obtain processing status information and processing results. The Python data processing service layer updates the processing status information to the log table with the log ID. The data storage module receives the processing results and stores them in the module result table in the database layer.

[0009] In some embodiments, the Java Spring service layer further includes an automation processing module, the data processing task further includes an automation processing task, and the automation execution task includes a data parsing task and a data processing task, wherein the data parsing task has a higher priority than the data processing task; Users upload files to be processed through the front-end page layer, and configure the required scripts to generate data parsing and data processing tasks; The automated processing module prioritizes the data parsing task to obtain the second product information and test data. The data storage module receives the second product information and test data and stores them respectively in the log table and the original data table in the database layer. The automated processing module processes the data processing task, obtains the second product information based on the data parsing task, and generates a script processing request according to the obtained required script ID, log ID, data table ID, and product attribute information. The Python data processing service layer loads the corresponding script and the original data table according to the required script ID and data table ID to process the data and obtain processing status information and processing results. The Python data processing service layer updates the processing status information to the log table with the log ID. The data storage module receives the processing results and stores them in the module result table in the database layer.

[0010] In some embodiments, the script generation module includes a script editor and a data preview module. Before the Java Spring service layer saves the data processing script to the database layer according to the script save instruction, a script verification step is also included. The script verification step includes: Users select verification data, as well as imported and / or edited data processing scripts, as test scripts to generate script verification tasks; The Java Spring service layer generates a script processing request from the verification data and the test script and sends it to the Python data processing service layer. The Python data processing service layer executes the test script and returns the test results to the front-end page layer through the Java Spring service layer. The front-end page layer visualizes the test results through the data preview module. After the verification is successful, the front-end page layer generates a script save instruction. After receiving the script save instruction, the Java Spring service layer verifies whether the test script passes the verification, and saves the test script that passes the verification to the script table of the database layer through the data storage module.

[0011] In some embodiments, the Python data processing service layer includes at least one script execution module corresponding to at least one script generation module, each script execution module being set up to run in an independent Docker container.

[0012] In some embodiments, the Java Spring service layer obtains the calculation type based on the script type in the data processing task, and the Python data processing service layer determines the required script execution module to execute based on the calculation type.

[0013] In some embodiments, the script processing request is set as a JSON format request, the JavaSpring service layer and the Python data processing service layer use the Socket communication protocol, the JavaSpring service layer sends the JSON format request, and the Python data processing service layer returns the execution result in the form of a byte stream.

[0014] Secondly, this embodiment provides a radio frequency chip data management system, including: A front-end page layer is used to import and / or edit data processing scripts and generate script save instructions based on at least one script generation module contained therein; the front-end page layer is used to trigger data processing tasks, the data processing tasks including selected script information, and at least one of a file to be processed and first product information; The Java Spring service layer is used to save the data processing script to the database layer according to the script save instruction, and each data processing script has a unique ID; it is used to obtain the required information from the database layer according to the data processing task to generate a script processing request, the required information including the required script ID, or including the required script and the data processing object, and finally store the returned execution result in the database layer. The Python data processing service layer is used to receive the script processing request, load the script corresponding to the required script ID from the database layer to parse the data of the file to be processed, or load the script corresponding to the required script ID and the data in the data processing object to process the data, and finally return the completed execution result to the Java Spring service layer. The database layer stores the data processing scripts generated by the front-end page layer, as well as the execution results of the Python data processing service layer.

[0015] In some of these embodiments, it also includes: The Java Spring service layer includes a script management module, a data query module, a data storage module, and a configuration information management module; the database layer includes a script table, a raw data table, a log table, and a module result table. The script management module is used to verify whether the test scripts pass the verification. For test scripts that pass the verification, the data storage module saves them to the script table of the database layer. It is also used to retrieve the required script ID from the script table of the database layer based on the script information. The data query module is used to retrieve product attribute information from the configuration information management module based on product information; The data storage module is used to store the test data obtained from data parsing into the original data table, and to store the processing status information and processing results obtained from data processing into the log table and the module result table, respectively.

[0016] Thirdly, this embodiment provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the radio frequency chip data management method described in the first aspect above.

[0017] Compared with related technologies, the radio frequency chip data management method, system, and readable storage medium provided in this embodiment have the following advantages: Users import / edit Python scripts through the front-end page layer. Selected scripts are saved to the script table in the database layer through the script management module of the Java Spring service layer. The script management module can also implement script version management and access control, storing scripts in the database instead of the file system. At runtime, the Python data processing service layer loads and executes them on demand, enabling script updates without redeploying the application. It supports version management and execution traceability. By setting up a Java Spring service layer and a Python data processing service layer, and building a Socket communication protocol, the Java Spring service layer sends script processing requests in JSON format, and the Python data processing service layer returns execution results in byte stream format. Combined with the Docker container isolation execution mechanism of each script execution module in the Python data processing service layer, the secure execution of Python scripts in enterprise-level Java systems is achieved, overcoming the integration barriers between Python and Java technology stacks. Breaking away from customized / fixed processing workflows, this invention can independently perform data parsing, data processing, and self-configurable automated processing. It adopts a multi-module architecture (data parsing is mandatory, data processing is optional), which can perform data parsing, data processing, and automated processing independently. It supports skipping certain modules or adjusting the execution order, and can adapt to the processing needs of different customers without modifying the core code. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of this application or the conventional technology, the drawings used in the description of the embodiments or the conventional technology will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 This is a flowchart of a radio frequency chip data management method in one embodiment; Figure 2 This is an architecture diagram of the radio frequency chip data management system in one embodiment. Detailed Implementation

[0020] To facilitate understanding of this application, a more complete description will be provided below with reference to the accompanying drawings, which illustrate embodiments of the present application. However, the present application can be implemented in many different forms and is not limited to the embodiments described herein. Rather, these embodiments are provided so that the disclosure of this application will be thorough and complete.

[0021] 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 particular embodiments only and is not intended to be limiting of the application.

[0022] It should also be understood that the terms "comprising / including" or "having," etc., specify the presence of the stated features, wholes, steps, operations, components, parts, or combinations thereof, but do not preclude the possibility of the presence or addition of one or more other features, wholes, steps, operations, components, parts, or combinations thereof. Meanwhile, in this specification, the term "and / or" includes any and all combinations of the associated listed items.

[0023] In order to provide such an embodiment, Figure 1 The radio frequency chip data management method shown includes: Front-end page layer, Java Spring service layer, Python data processing service layer, database layer; S1, according to at least one script generation module included in the front-end page layer, import and / or edit the data processing script and generate a script save instruction, the Java Spring service layer saves the data processing script to the database layer according to the script save instruction, and each data processing script has a unique ID; S2, the front-end page layer triggers a data processing task, the data processing task includes selected script information, and also includes at least one of the file to be processed and first product information; the Java Spring service layer obtains the required information from the database layer according to the data processing task to generate a script processing request, the required information includes the required script ID, or includes the required script and data processing object; S3, the Python data processing service layer receives the script processing request, loads the script corresponding to the required script ID from the database layer to parse the data of the file to be processed, or loads the script corresponding to the required script ID and the data in the data processing object to process the data; the Python data processing service layer returns the completed execution result to the Java Spring service layer, and the Java Spring service layer stores the execution result in the database layer.

[0024] Users import / edit Python scripts through the front-end page layer. Selected scripts are saved to the database layer via the Java Spring service layer, storing them in the database rather than the file system. At runtime, the Python data processing service layer loads and executes the scripts on demand, allowing for script updates without application redeployment. For user data processing needs (data parsing and database entry, and processing of already entered data), users can trigger data processing tasks through the front-end page layer. The Java Spring service layer retrieves the necessary information from the database layer based on the data processing task, generates a script processing request, and sends the JSON-formatted script processing request via the Socket communication protocol. The Python data processing service layer returns the execution result in byte stream format, enabling secure execution of Python scripts in enterprise-level Java systems and overcoming integration barriers between Python and Java technology stacks.

[0025] In some embodiments, the data processing task includes a data parsing task, which includes selected script information and a file to be processed; the Java Spring service layer includes a script management module and a data storage module. The script management module obtains the required script ID from the database layer based on the script information, and the JavaSpring service layer generates a script processing request based on the required script ID and the file to be processed. The Python data processing service layer loads the corresponding script according to the required script ID to parse the data in the file to be processed, and obtains the second product information and test data; the data storage module receives the second product information and test data and stores them in the log table and the original data table in the database layer, respectively.

[0026] When the data processing task is a standalone data parsing task, it can be triggered by a user uploading a file and selecting a script on the front-end page. In this case, the data parsing task contains script information and the file to be processed. The script information can be a visually displayed script name, with a unique correspondence between the script name and script ID, or a unique correspondence between the script name and script ID for each individual account. The Java Spring service layer as a whole has a communication module for bidirectional communication with the front-end page layer, database layer, and Python data processing service layer, which will not be elaborated here. The script management module of the Java Spring service layer can obtain the script ID from the database layer based on the script information. The Python data processing service layer loads the script from the database layer based on the script ID, parses the file to be processed, and stores the obtained second product information and test data into the corresponding table in the database layer through the data storage module of the Java Spring service layer, completing the data parsing and database entry. The first and second product information includes, for example, recording product-specific information such as waferID, LOTID, and layer.

[0027] In some embodiments, the data processing task further includes a data processing task, and the data parsing task includes selected script information and first product information; the Java Spring service layer further includes a data query module and a configuration information management module; The script management module obtains the required script ID from the database layer based on the script information; the data query module obtains the log ID and data table ID from the database layer based on the first product information; the data query module obtains product attribute information from the configuration information management module based on the first product information; and the Java Spring service layer generates a script processing request based on the required script ID, log ID, data table ID, and product attribute information. The Python data processing service layer loads the corresponding script and the original data table according to the required script ID and data table ID to process the data and obtain processing status information and processing results. The Python data processing service layer updates the processing status information to the log table with the log ID. The data storage module receives the processing results and stores them in the module result table in the database layer.

[0028] When the data processing task is a standalone task, it involves processing data that has already been parsed and stored in the database. This can be triggered by the user selecting the product and script to be processed on the front-end page. In this case, the data parsing task contains product and script information. The script information can be a visually displayed script name with a unique correspondence between the script name and script ID, or a unique correspondence between the script name and script ID for each individual account. The Java Spring service layer has a communication module that enables bidirectional communication with the front-end page layer, database layer, and Python data processing service layer, which will not be elaborated here. The script management module of the Java Spring service layer can obtain the script ID from the database layer based on the script information, and the log ID and data table ID from the database layer based on the product information. Then, the Python data processing service layer loads the script and data from the database layer based on the script ID and data table ID for processing. The obtained processing status information (log table needs to be updated) and processing results are stored in the log table and module result table in the database layer, respectively. Specifically, the processing status information and log... ID association allows the Python data processing service layer to directly update the corresponding log table. Processing results are associated with the calculation type (data processing includes multiple types, each with a corresponding calculation ID), and stored in the corresponding module result table. Product attribute information is used to automatically retrieve the attribute values ​​corresponding to the attribute names during script execution for calculation. Processing status information includes the status bits in the log table and the cumulative processing count.

[0029] In some embodiments, the Java Spring service layer further includes an automation processing module, the data processing task further includes an automation processing task, and the automation execution task includes a data parsing task and a data processing task, wherein the data parsing task has a higher priority than the data processing task; Users upload files to be processed through the front-end page layer, and configure the required scripts to generate data parsing and data processing tasks; The automated processing module prioritizes the data parsing task to obtain the second product information and test data. The data storage module receives the second product information and test data and stores them respectively in the log table and the original data table in the database layer. The automated processing module processes the data processing task, obtains the second product information based on the data parsing task, and generates a script processing request according to the obtained required script ID, log ID, and product attribute information. The Python data processing service layer loads the corresponding script and original data table according to the required script ID and log ID to process the data and obtain processing status information and processing results. The Python data processing service layer updates the processing status information to the log table with the log ID. The data storage module receives the processing results and stores them in the module result table in the database layer.

[0030] When the data processing task is automated, the user uploads a file and selects a data parsing script and at least one type of data processing script on the front-end page layer to trigger the process. In this case, the automated processing task can include a standalone data parsing task, or a data parsing task and a data processing task, with the data parsing task being processed first. Specifically, the automation module in the JavaSpring service layer first starts the data parsing task. After completion, it obtains product information (stored in a log table) and test data (stored in a raw data table), at which point the data processing task is started. To facilitate the automation process, an automation configuration module is provided on the front-end page layer for users to upload files to be processed and select the required data parsing and data processing scripts.

[0031] In some embodiments, the script generation module includes a script editor and a data preview module. Before the Java Spring service layer saves the data processing script to the database layer according to the script save instruction, a script verification step is also included. The script verification step includes: Users select verification data, as well as imported and / or edited data processing scripts, as test scripts to generate script verification tasks; The Java Spring service layer generates a script processing request from the verification data and the test script and sends it to the Python data processing service layer. The Python data processing service layer executes the test script and returns the test results to the front-end page layer through the Java Spring service layer. The front-end page layer visualizes the test results through the data preview module. After the verification is successful, the front-end page layer generates a script save instruction. After receiving the script save instruction, the Java Spring service layer verifies whether the test script passes the verification, and saves the test script that passes the verification to the script table of the database layer through the data storage module.

[0032] For scripts uploaded / edited by users in the script generation module, a verification process can be used to check whether there are any problems with the scripts. Scripts that pass the verification are then saved to the database layer to reduce the risk of errors during batch execution.

[0033] In some embodiments, the Python data processing service layer includes at least one script execution module corresponding to at least one script generation module, each script execution module being set up to run in an independent Docker container.

[0034] In some embodiments, the Java Spring service layer obtains the calculation type based on the script type in the data processing task, and the Python data processing service layer determines the required script execution module to execute based on the calculation type.

[0035] In this embodiment, the script type may include data parsing script, de-embedding script, data extraction script, and data conversion script, wherein the de-embedding script, data extraction script, and data conversion script are data processing scripts.

[0036] In some embodiments, the script processing request is set as a JSON format request, the JavaSpring service layer and the Python data processing service layer use the Socket communication protocol, the JavaSpring service layer sends the JSON format request, and the Python data processing service layer returns the execution result in the form of a byte stream.

[0037] In one embodiment, an RF chip data management system is provided, comprising: A front-end page layer is used to import and / or edit data processing scripts and generate script save instructions based on at least one script generation module contained therein; the front-end page layer is used to trigger data processing tasks, the data processing tasks including selected script information, and at least one of a file to be processed and first product information; The Java Spring service layer is used to save the data processing script to the database layer according to the script save instruction, and each data processing script has a unique ID; it is used to obtain the required information from the database layer according to the data processing task to generate a script processing request, the required information including the required script ID, or including the required script and the data processing object, and finally store the returned execution result in the database layer. The Python data processing service layer is used to receive the script processing request, load the script corresponding to the required script ID from the database layer to parse the data of the file to be processed, or load the script corresponding to the required script ID and the data in the data processing object to process the data, and finally return the completed execution result to the Java Spring service layer. The database layer stores the data processing scripts generated by the front-end page layer, as well as the execution results of the Python data processing service layer.

[0038] In some of these embodiments, it also includes: The Java Spring service layer includes a script management module, a data query module, a data storage module, and a configuration information management module; the database layer includes a script table, a raw data table, a log table, and a module result table. The script management module is used to verify whether the test scripts pass the verification. For test scripts that pass the verification, the data storage module saves them to the script table of the database layer. It is also used to retrieve the required script ID from the script table of the database layer based on the script information. The data query module is used to retrieve product attribute information from the configuration information management module based on product information; The data storage module is used to store the test data obtained from data parsing into the original data table, and to store the processed results obtained from data processing into the module result table.

[0039] In light of the above, this embodiment provides a specific radio frequency chip data management system for further explanation. (Refer to...) Figure 2 As shown, the system adopts a four-layer architecture design, including a front-end page layer, a Java Spring service layer, a Python data processing service layer, and a database layer.

[0040] Front-end page layer: It includes four independent script generation modules, an automation configuration module, and a data management page. The four script generation modules are Parse, De-Embedding, Extract, and Transform modules. Each script generation module contains a script editor and a data preview module. The script editor can use the Monaco Editor code editor component, which supports Python syntax highlighting, code completion, error prompts, and undo / redo functions. The data preview module is used to visualize the test results of the script verification, such as through tables / charts, to facilitate viewing the accuracy of the script execution results.

[0041] The automation configuration module is used to configure which of the Parse, De-Embedding, Extract, and Transform modules should be used to operate on files in different paths, for automated processing of data insertion.

[0042] The data management page is used by users to process existing data in the database layer. It allows users to trigger individual data processing tasks through the data upload interface and data processing script options.

[0043] Java Spring service layer: It includes a script management module, a data storage module, a data query module, a configuration information management module, and an automated processing module; The script management module is used to verify whether the test scripts pass the verification. For test scripts that pass the verification, the data storage module saves them to the script table of the database layer. It is also used to obtain the required script ID from the script table of the database layer according to the script information, and supports script version management and permission control.

[0044] The data storage module is used to store the execution results returned by the Python data processing service layer to the database layer. Specifically, it stores the parsed results in the original data table and the processed results in the module result table.

[0045] The data query module is used to query the log ID from the database layer based on product information, and to query product attribute information from the configuration information management module based on product information.

[0046] The database layer includes a log table, a raw data table, a script table, and a module result table.

[0047] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the steps in the above-described embodiments of the radio frequency chip data management methods.

[0048] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments described above. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile 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 many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0049] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0050] In the description of this specification, the references to terms such as "some embodiments," "other embodiments," "ideal embodiments," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example that are included in at least one embodiment or example of this application. In this specification, the illustrative descriptions of the above terms do not necessarily refer to the same embodiments or examples.

[0051] The technical features of the above embodiments can be combined in any way. For the sake of brevity, 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 specification.

[0052] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A method for managing data of a radio frequency chip, characterized in that, include: Front-end page layer, Java Spring service layer, Python data processing service layer, database layer; S1, according to at least one script generation module included in the front-end page layer, import and / or edit the data processing script and generate a script save instruction, the Java Spring service layer saves the data processing script to the database layer according to the script save instruction, and each data processing script has a unique ID; S2, the front-end page layer triggers a data processing task, the data processing task includes selected script information, and also includes at least one of the file to be processed and first product information; the Java Spring service layer obtains the required information from the database layer according to the data processing task to generate a script processing request, the required information includes the required script ID, or includes the required script and data processing object; S3, the Python data processing service layer receives the script processing request, loads the script corresponding to the required script ID from the database layer to parse the data of the file to be processed, or loads the script corresponding to the required script ID and the data in the data processing object to process the data; the Python data processing service layer returns the completed execution result to the Java Spring service layer, and the Java Spring service layer stores the execution result in the database layer.

2. The method of claim 1, wherein, The data processing task includes a data parsing task, which includes selected script information and a file to be processed; the Java Spring service layer includes a script management module and a data storage module. The script management module obtains the required script ID from the database layer based on the script information, and the Java Spring service layer generates a script processing request based on the required script ID and the file to be processed. The Python data processing service layer loads the corresponding script according to the required script ID to parse the data in the file to be processed, and obtains the second product information and test data; the data storage module receives the second product information and test data and stores them in the log table and the original data table in the database layer, respectively.

3. The method of claim 2, wherein, The data processing task also includes a data processing task, and the data parsing task includes selected script information and first product information; the Java Spring service layer also includes a data query module and a configuration information management module; The script management module obtains the required script ID from the database layer based on the script information; the data query module obtains the log ID and data table ID from the database layer based on the first product information; the data query module obtains product attribute information from the configuration information management module based on the first product information; and the Java Spring service layer generates a script processing request based on the required script ID, log ID, data table ID, and product attribute information. The Python data processing service layer loads the corresponding script and the original data table according to the required script ID and data table ID to process the data and obtain processing status information and processing results; the Python data processing service layer updates the processing status information to the log table with the log ID; the data storage module receives the processing results and stores them in the module result table in the database layer.

4. The method of claim 3, wherein, The Java Spring service layer also includes an automation processing module, and the data processing task also includes an automation processing task. The automation execution task includes a data parsing task and a data processing task, with the data parsing task having a higher priority than the data processing task. Users upload files to be processed through the front-end page layer, and configure the required scripts to generate data parsing and data processing tasks; The automated processing module prioritizes the data parsing task to obtain the second product information and test data. The data storage module receives the second product information and test data and stores them respectively in the log table and the original data table in the database layer. The automated processing module processes the data processing task, obtains the second product information based on the data parsing task, and generates a script processing request according to the obtained required script ID, log ID, data table ID, and product attribute information. The Python data processing service layer loads the corresponding script and the original data table according to the required script ID and data table ID to process the data and obtain processing status information and processing results. The Python data processing service layer updates the processing status information to the log table with the log ID. The data storage module receives the processing results and stores them in the module result table in the database layer.

5. The method of claim 2, wherein, The script generation module includes a script editor and a data preview module. Before the Java Spring service layer saves the data processing script to the database layer according to the script save instruction, it also includes a script verification step, which includes: Users select verification data, as well as imported and / or edited data processing scripts, as test scripts to generate script verification tasks; The Java Spring service layer generates a script processing request from the verification data and the test script and sends it to the Python data processing service layer. The Python data processing service layer executes the test script and returns the test results to the front-end page layer through the Java Spring service layer. The front-end page layer visualizes the test results through the data preview module. After the verification is successful, the front-end page layer generates a script save instruction. After receiving the script save instruction, the Java Spring service layer verifies whether the test script passes the verification, and saves the test script that passes the verification to the script table of the database layer through the data storage module.

6. The method of claim 1, wherein, The Python data processing service layer includes at least one script execution module corresponding to at least one script generation module, and each script execution module is set to run in an independent Docker container.

7. The method of claim 6, wherein, The Java Spring service layer obtains the calculation type based on the script type in the data processing task, and the Python data processing service layer determines the required script execution module based on the calculation type and executes it.

8. The method of claim 1, wherein, The script processing request is set to JSON format. The Java Spring service layer and the Python data processing service layer use the Socket communication protocol. The Java Spring service layer sends the JSON format request, and the Python data processing service layer returns the execution result in the form of a byte stream.

9. A radio frequency chip data management system, characterized by, include: The front-end page layer is used to import and / or edit data processing scripts and generate script save instructions based on at least one script generation module contained therein; The front-end page layer is used to trigger data processing tasks, which include selected script information and at least one of the files to be processed and first product information. The Java Spring service layer is used to save the data processing script to the database layer according to the script save instruction, and each data processing script has a unique ID; it is used to obtain the required information from the database layer according to the data processing task to generate a script processing request, the required information including the required script ID, or including the required script and the data processing object, and finally store the returned execution result in the database layer. The Python data processing service layer is used to receive the script processing request, load the script corresponding to the required script ID from the database layer to parse the data of the file to be processed, or load the script corresponding to the required script ID and the data in the data processing object to process the data, and finally return the completed execution result to the Java Spring service layer. The database layer stores the data processing scripts generated by the front-end page layer, as well as the execution results of the Python data processing service layer.

10. The system of claim 9, wherein, Also includes: The Java Spring service layer includes a script management module, a data query module, a data storage module, and a configuration information management module. The database layer includes a script table, a raw data table, a log table, and a module result table; The script management module is used to verify whether the test scripts pass the verification. Test scripts that pass the verification are saved to the script table of the database layer through the data storage module. Used to retrieve the required script ID from the script table of the database layer based on the script information; The data query module is used to retrieve product attribute information from the configuration information management module based on product information; The data storage module is used to store the test data obtained from data parsing into the original data table, and to store the processing status information and processing results obtained from data processing into the log table and the module result table, respectively.

11. A computer readable storage medium having stored thereon a computer program, characterized in that, The computer program, when executed by a processor, implements the steps of the radio frequency chip data management method of any one of claims 1 to 8.

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