Data preprocessing method in zero-code platform development

Abstract

The invention discloses a data preprocessing method in zero code platform development, and relates to the technical field of data processing.The method comprises the steps that at least one input data table is determined according to at least one preset data source, and at least one output data table is constructed according to a preset output data table rule; an operation node is constructed according to a preset service requirement, and at least one basic atomic operation configured in the operation node is subjected to combination processing to obtain a combination operation, and the combination operation is used for filtering data in an input data table associated with the operation node to obtain an array. Updating to an output data table associated with the operation node; and updating data in the at least one input data table to the at least one output data table according to the combined operation in the operation node to obtain a target output data table, and outputting the target output data table. According to the method, the performance of zero-code platform data preprocessing is improved.

Description

Technical Field

[0001] The present application relates to the field of data processing technology, and in particular to a data preprocessing method in the development of a zero-code platform. Background Art

[0002] In the current context of the popularization of the Internet, the Internet of Things, and mobile devices, the diversity and complexity of data have put forward higher requirements for data processing technology. However, when processing data, traditional zero-code platforms usually rely on fixed interface methods or need to write custom code. Once business needs change, the original code often needs to be significantly modified, which is not conducive to modular encapsulation and increases the complexity of development and maintenance. At the same time, complex data processing generally needs to be completed in the background, and there are differences in the presentation method and structure of data in different business scenarios, which can easily lead to too much redundant code in the background. Frequent interface calls will also cause pressure on the background services and servers, thereby affecting the user experience. This approach is not flexible enough when faced with a wide range of diverse data sources and the processing needs of different data ecosystems. Summary of the invention

[0003] The main purpose of this application is to provide a data preprocessing method in the development of a zero-code platform, aiming to improve the flexibility of data preprocessing in the zero-code platform.

[0004] To achieve the above purpose, this application proposes a data preprocessing method in zero-code platform development, including:

[0005] Determine at least one input data table according to at least one preset data source, and construct at least one output data table according to a preset output data table rule, wherein the worksheet fields and data types in the output data table are determined according to the output data table rule;

[0006] An operation node is constructed according to preset business requirements, and at least one basic atomic operation configured in the operation node is combined to obtain a combined operation, wherein the combined operation is used to update an array obtained by filtering data in an input data table associated with the operation node to an output data table associated with the operation node;

[0007] According to the combined operation in the operation node, data in at least one input data table is updated to at least one output data table to obtain a target output data table, and the target output data table is output.

[0008] In one embodiment, the step of combining at least one basic atomic operation configured in the operation node to obtain the combined operation includes:

[0009] Determine a preset initial data type, and configure at least one basic atomic operation for each initial data type, wherein the initial data type includes an array type, a Boolean type, an object type, a number type, a string type, and a time type;

[0010] For each operation node, all basic atomic operations configured for the initial data type are combined according to a preset operation order to obtain a combined operation.

[0011] In one embodiment, the basic atomic operation includes filtering and mapping, and the step of updating the data in at least one input data table to at least one output data table according to the combined operation in the operation node includes:

[0012] Determine at least one input data table associated with the operation node as a first input data table, and determine a target field in the first input data table, wherein the target field is a field in the first input data table selected by a user;

[0013] Filter the data belonging to the target field in the first input data table according to the preset filtering condition to obtain a target array;

[0014] Updates the target array to at least one output data table.

[0015] In one embodiment, the step of updating data in at least one input data table to at least one output data table according to the combination operation in the operation node to obtain the target output data table includes:

[0016] If there are at least two operation nodes, determining an arrangement order of the at least two operation nodes;

[0017] At least two operation nodes are controlled in an arrangement order, and at least one input data table is processed in sequence according to the respective corresponding combination operations to update the data in the at least one input data table to at least one output data table, wherein, when the controlled operation node is not the first operation node, the node data table output by the previous operation node of the non-first operation node is determined, and if a new input data table is detected, the node data table and the new input data table are processed according to the combination operation of the non-first operation node.

[0018] In one embodiment, the input data table includes a debugging input data table, and the data preprocessing method in the zero-code platform development further includes:

[0019] If a debugging instruction sent from outside is received, the preset parameters are used as the debugging input data table;

[0020] According to the combined operations in all operation nodes, data in at least one debugging input data table is updated to at least one output data table to obtain a debugging output data table, and the debugging output data table is displayed.

[0021] In one embodiment, the step of outputting the target output data table includes:

[0022] If a page component binding instruction sent from the outside is received, the data in the target output data table is bound to the page component specified by the page component binding instruction, and the target output data table is output through the page component;

[0023] If a page data binding instruction sent externally is received, the data in the target output data table is bound to the page data specified by the page data binding instruction, and the target output data table is output through the page data, wherein the page data is bound by at least one page component.

[0024] In addition, to achieve the above purpose, the present application also proposes a data preprocessing device in the development of a zero-code platform, and the data preprocessing device in the development of a zero-code platform includes:

[0025] An input-output module is defined, at least one input data table is determined according to at least one preset data source, and at least one output data table is constructed according to a preset output data table rule, wherein the worksheet fields and data types in the output data table are determined according to the output data table rule;

[0026] An operation node module is defined, an operation node is constructed according to preset business requirements, and at least one basic atomic operation configured in the operation node is combined to obtain a combined operation, wherein the combined operation is used to update an array obtained by filtering data in an input data table associated with the operation node to an output data table associated with the operation node;

[0027] The output data module updates the data in at least one input data table to at least one output data table according to the combination operation in the operation node, obtains the target output data table, and outputs the target output data table.

[0028] In addition, to achieve the above-mentioned purpose, the present application also proposes a data preprocessing device in the development of a zero-code platform, the device including: a memory, a processor, and a computer program stored in the memory and executable on the processor, the computer program being configured to implement the steps of the data preprocessing method in the development of a zero-code platform as described above.

[0029] In addition, to achieve the above-mentioned purpose, the present application also proposes a medium, which is a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the data preprocessing method in the zero-code platform development as described above are implemented.

[0030] In addition, to achieve the above-mentioned purpose, the present application also provides a product, which is a computer program product. The computer program product includes a computer program, and when the computer program is executed by a processor, it implements the steps of the data preprocessing method in the zero-code platform development as described above.

[0031] One or more technical solutions proposed in this application have at least the following technical effects:

[0032] The present application determines at least one input data table based on at least one preset data source, and constructs at least one output data table based on preset output data table rules, wherein the worksheet fields and data types in the output data table are determined based on the output data table rules, which helps to achieve flexible selection and efficient organization of data, and facilitates subsequent data processing and analysis; constructs an operation node based on preset business needs, and combines at least one basic atomic operation configured in the operation node to obtain a combined operation, wherein the combined operation is used to update the array obtained by filtering the data in the input data table associated with the operation node to the output data table associated with the operation node, which enhances the flexibility and scalability of data processing, can meet diverse business needs, and improves the efficiency of data processing; updates the data in at least one input data table to at least one output data table based on the combined operation in the operation node to obtain a target output data table, and outputs the target output data table, which realizes intuitive display and interaction of data, facilitates users to quickly understand and use data, and improves user experience and decision-making efficiency. Ultimately, through this series of optimization measures, the flexibility of data preprocessing on the zero-code platform can be significantly improved, including increasing data processing speed, reducing resource consumption, and enhancing the stability and reliability of data processing, thereby providing users with a more efficient and convenient data processing experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0034] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0035] Figure 1 This is a flow chart of the first embodiment of the data preprocessing method in the zero-code platform development of this application;

[0036] Figure 2 This is a simplified process diagram of the first embodiment of the data preprocessing method in the zero-code platform development of this application;

[0037] Figure 3 A schematic diagram of a scenario for modifying an output data table for a data preprocessing method in the zero-code platform development of this application;

[0038] Figure 4 This is a scenario diagram of the first embodiment of the data preprocessing method in the zero-code platform development of this application;

[0039] Figure 5 A schematic diagram of a scenario for modifying a combined operation of a data preprocessing method in the zero-code platform development of this application;

[0040] Figure 6 A schematic diagram of a scenario for debugging the output data table of the data preprocessing method in the zero-code platform development of this application;

[0041] Figure 7 A schematic diagram of a scenario for selecting a binding target for a data preprocessing method in the zero-code platform development of this application;

[0042] Figure 8 This is a schematic diagram of the module structure of the data preprocessing device in the zero-code platform development of the embodiment of the present application;

[0043] Fig. 9 This is a schematic diagram of the device structure of the hardware operating environment involved in the data preprocessing method in the zero-code platform development in the embodiment of the present application.

[0044] The purpose, features and advantages of this application will be further described in conjunction with the embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0045] It should be understood that the specific embodiments described herein are only used to explain the technical solutions of the present application and are not used to limit the present application.

[0046] In order to better understand the technical solution of the present application, a detailed description will be given below in conjunction with the accompanying drawings and specific implementation methods.

[0047] It should be noted that the execution subject of this embodiment can be a computing service device with data processing, network communication and program running functions, such as a tablet computer, a personal computer, a mobile phone, etc., or an electronic device capable of realizing the above functions, a terminal system, etc. The following takes the system as an example to illustrate this embodiment and the following embodiments.

[0048] Based on this, this embodiment provides a data preprocessing method in zero-code platform development, referring to Figure 1 and Figure 2 , Figure 1 This is a flowchart of the data preprocessing method in the zero-code platform development of this application. Figure 2This is a simplified process diagram of the data preprocessing method in the zero-code platform development of this application. The data preprocessing method in the zero-code platform development includes steps S10 to S40:

[0049] Step S10, determining at least one input data table according to at least one preset data source, and constructing at least one output data table according to a preset output data table rule, wherein the worksheet fields and data types in the output data table are determined according to the output data table rule;

[0050] It should be noted that the data source is the source of data, which can be a database, file, API interface, etc., used to store and provide data for subsequent processing. The input data table is a data set selected from the data source for subsequent operation node processing. The output data table rules are user-defined. The fields and data types of the worksheet are customized as needed. The output data table is a data set stored according to the output data table rules after being processed by the operation node.

[0051] Select one or more input data tables from the preset data sources (such as databases, files, etc.). These input data tables contain the data required for subsequent processing. Define at least one output data table according to the output data table rules to store the processed data. The structure and format of the output data table can be customized according to business needs.

[0052] Step S20, constructing an operation node according to preset business requirements, and combining at least one basic atomic operation configured in the operation node to obtain a combined operation, wherein the combined operation is used to update an array obtained by filtering data in an input data table associated with the operation node to an output data table associated with the operation node;

[0053] For example, refer to Figure 3 , Figure 3This is a schematic diagram of the scenario of modifying the output data table. For the output data table named a, add two data columns named name and desc, both of which are string types. These two columns are used to customize the column names of the table below. There is also an "initialize data" option below these two columns, allowing users to set initial values ​​for certain columns. The name and desc columns of the table below have four corresponding data sets, namely execution, assessment, cognition, and decision. When the confirmation button is clicked, the system will modify the settings of the output data table according to these four sets of data. There are several important buttons and operation options on the right side of the table below. Among them, the "+Add Data" button is used to manually add a single data item, and the "+Batch Data" button is used to batch import or add data. There is also a "Cancel" button at the bottom of the table below. Users can abandon the current operation and return to the previous interface by clicking the "Cancel" button.

[0054] It should be noted that an operation node is an operation unit that performs specific processing on the input data table in the data processing flow, such as screening, conversion, aggregation, etc. Basic atomic operations are the smallest and indivisible operation units in data processing, such as filtering and sorting. Composite operations are complex operations formed by combining multiple basic atomic operations to implement specific data processing logic.

[0055] Construct operation nodes according to business needs. Each operation node contains at least one combination of basic atomic operations, which can be filtering, sorting, aggregation, etc. A combined operation is formed by combining multiple basic atomic operations in a certain logical order. The function of the combined operation is to filter the data in the input data table associated with the operation node to obtain an array, and then update this array to the output data table associated with the operation node. You can set the style of the operation node, such as color, shape, etc., to clearly distinguish different operation nodes in the data processing flow chart.

[0056] Step S30: updating the data in at least one input data table to at least one output data table according to the combination operation in the operation node, obtaining a target output data table, and outputting the target output data table.

[0057] It should be noted that the target output data table is the output data table finally obtained after being processed by all operation nodes.

[0058] According to the combined operation in the operation node, the data in at least one input data table is updated to at least one output data table. This process is achieved by executing the basic atomic operations in the combined operation. Each operation node processes the data according to its internal logic. After processing by all operation nodes, one or more target output data tables will be obtained. These target output data tables contain the processed data, which meets the business requirements and data processing goals. Finally, the target output data tables are output for subsequent use or analysis.

[0059] For example, refer to Figure 4 In box 01, you can add an input worksheet by clicking the button to add an input worksheet. In box 02, you can add an output worksheet by clicking the button to add an output worksheet. In box 03, you can add an operation node by clicking the add button 31. Click each operation node to edit the data processing operation in the operation node. Figure 4 In the example, Table 1 has been added as the input worksheet and Table 2 has been added as the output worksheet. Two operation nodes have been defined, namely, adding data to Table 1 and modifying the data in Table 1. Then, when the Execute button is clicked, the system will add data to Table 1 in the order of the operation nodes, modify the data in Table 1, and finally map the processed data in Table 1 to Table 2.

[0060] In this embodiment, at least one input data table is determined based on at least one preset data source, and at least one output data table is constructed based on preset output data table rules, wherein the worksheet fields and data types in the output data table are determined based on the output data table rules, which helps to achieve flexible selection and efficient organization of data and facilitates subsequent data processing and analysis; an operation node is constructed based on preset business needs, and at least one basic atomic operation configured in the operation node is combined to obtain a combined operation, wherein the combined operation is used to update the array obtained by filtering the data in the input data table associated with the operation node to the output data table associated with the operation node, which enhances the flexibility and scalability of data processing, can meet diverse business needs, and improves the efficiency of data processing; data in at least one input data table is updated to at least one output data table based on the combined operation in the operation node to obtain a target output data table, and the target output data table is output, which realizes intuitive display and interaction of data, facilitates users to quickly understand and use data, and improves user experience and decision-making efficiency. Ultimately, through this series of optimization measures, the flexibility of data preprocessing on the zero-code platform can be significantly improved, including increasing data processing speed, reducing resource consumption, and enhancing the stability and reliability of data processing, thereby providing users with a more efficient and convenient data processing experience.

[0061] In a feasible implementation manner, the steps in step S30 may include steps R10 to R50:

[0062] Step R10, if there are at least two operation nodes, determining the arrangement order of the at least two operation nodes;

[0063] Step R20, control at least two operation nodes in an arrangement order, and process at least one input data table in sequence according to their corresponding combination operations to update the data in at least one input data table to at least one output data table, wherein, when the controlled operation node is not the first operation node, determine the node data table output by the previous operation node of the non-first operation node, and if a new input data table is detected, process the node data table and the new input data table according to the combination operation of the non-first operation node.

[0064] It should be noted that the node data table refers to the data table processed by the operation node.

[0065] When there are at least two operation nodes, the execution order of these operation nodes must be determined first. This is usually determined based on business logic, data processing requirements, or data flow dependencies. For example, if there is a data cleaning operation and a data aggregation operation, the data cleaning operation is usually executed before the data aggregation operation. According to the determined arrangement order, each operation node is controlled in turn to perform its corresponding combination operation. The first operation node reads data directly from the input data table and processes it to generate the first output data table (which is also the node data table of subsequent operation nodes). Each operation node processes the input data table (for non-first operation nodes, it is the output data table of the previous operation node) according to its own combination operation. The processed data is updated to the output data table for use by subsequent operation nodes or as the final processing result.

[0066] For non-first operation nodes, the node data table output by the previous operation node needs to be determined before execution. If a new input data table is detected during execution (for example, the operation node is set to process according to the new input data table instead of only processing the node data table output by the previous operation node), the non-first operation node will apply its combined operation to the node data table and the new input data table to achieve data merging, updating or other processing.

[0067] Through this embodiment, multiple operation nodes are executed in sequence according to a determined arrangement order, and each operation node performs processing based on the output of its previous operation node (or for the first operation node, the original input data table), and passes the processing result to the next operation node or as the final output. In this way, the entire data processing process forms a complete data flow, realizing the conversion and update from the input data table to the output data table.

[0068] In a feasible implementation, the steps in step S10 may include step T10:

[0069] Step T10: selecting at least one data source as an input data table through a preset data source search method, wherein the data source search method includes keyword search and category search.

[0070] It should be noted that the data source search method is a method or means for finding and selecting a target data source from multiple data sources. Different search methods may be based on different standards or conditions, such as keywords, categories, etc. Keyword search is a search method for finding relevant data sources by entering specific keywords or phrases. The system will match the entered keywords in the data sources and return a list of data sources containing these keywords. Category search is a search method for finding relevant data sources according to a preset classification system. Data sources are classified into different categories, and users can quickly find the target data source by selecting a category.

[0071] Before starting a search, the system or user needs to determine which data source search method to use. In this embodiment, two methods, keyword search and classification search, are provided for selection. Users can choose the most suitable search method based on actual needs and the characteristics of the data source. Perform a keyword search (or classification search) If the keyword search method is selected, the user needs to enter one or more keywords, and the system will match all available data sources to find the data source containing these keywords.

[0072] If the classification search method is selected, the user needs to browse or select one or some categories in the preset classification system, and the system will return the corresponding data source list according to the selected category. The system returns a list of data sources based on the search method, and the user can view the detailed information of each data source in the list, such as the data source name, description, data type, etc. The user selects one or more target data sources as input data tables based on actual needs and data source information. The system reads and extracts the data from the data source selected by the user and generates one or more input data tables. These input data tables will be further processed and used by the system as the basis for subsequent data processing or analysis.

[0073] This embodiment uses a preset data source search method to quickly and accurately find and select a target data source as an input data table. This mechanism improves the efficiency and accuracy of data processing, allowing users to more conveniently obtain and use required data.

[0074] Based on the first embodiment of the present application, in the second embodiment of the present application, the same or similar contents as those in the first embodiment can be referred to the above description, and will not be repeated hereafter. On this basis, the steps of step S30 also include steps A10 to A20:

[0075] Step A10, determining a preset initial data type, and configuring at least one basic atomic operation for each initial data type, wherein the initial data type includes an array type, a Boolean type, an object type, a number type, a string type, and a time type;

[0076] It should be noted that the initial data type is the type or category of data, such as string, number, object, etc., which determines the operations and storage methods that can be performed on the data. Basic atomic operations are indivisible basic data processing operations and are the basic units for building more complex data processing processes. When defining basic atomic operations, you need to define its input parameters, returned data, and the type of returned data.

[0077] First, according to the type of data in the input data table (such as array type, Boolean type, object type, digital type, string type, time type, etc.), define the corresponding basic atomic operation. For each basic atomic operation, further define its operation content. This includes determining the input parameters required for the operation (such as the string to be replaced, the number to be operated, etc.), the data returned by the operation (such as the string after replacement, the result of the operation, etc.) and the type of the returned data (such as string type, digital type, etc.). By defining the operation content, the specific behavior and expected output of each basic atomic operation can be clearly understood, providing a basis for subsequent combined operations. In this embodiment, a variety of basic atomic operations are defined, including string replacement operations, digital operation operations, object to array operations, and other operations, which are not limited in this embodiment. For example, the string type can perform operations such as append (append, add new content at the end of the string), length (length, obtain the number of characters in the string), the number type can perform operations such as four arithmetic operations, toString (convert to string), and the object type can be converted into an array. These operations are respectively applicable to processing string data, digital data, and object data.

[0078] Step A20: for each operation node, all basic atomic operations configured for the initial data type are combined according to a preset operation sequence to obtain a combined operation.

[0079] It should be noted that the combined operation is to combine multiple basic atomic operations in a certain logical order to form an operation set that can perform more complex data processing tasks.

[0080] According to business needs and data processing flow, at least one basic atomic operation is combined to obtain a combined operation. The combined operation can execute multiple basic atomic operations in a certain logical order to achieve more complex data processing tasks. In the combination process, it is necessary to ensure that the data transfer and dependency between the basic atomic operations are correct. They all belong to chain expression operations, and the operations that can be selected in the next step are determined by the return result of the previous step. For example, the output of a basic atomic operation can be used as the input of another basic atomic operation. Finally, the input data table is processed using the combined operation. According to the defined basic atomic operations and combined logic, the data in the input data table is filtered, converted, calculated, and other operations are performed to obtain the processed data. The processed data can be stored in a new data table or directly used for subsequent data analysis, visualization, and other tasks.

[0081] This embodiment implements data processing tasks based on data types by defining basic atomic operations, defining operation contents, combining basic atomic operations, and processing input data tables. This process is flexible and scalable and can be adjusted and optimized according to different business needs and data processing requirements.

[0082] In a feasible implementation manner, step S30 further includes steps B10 to B30:

[0083] Step B10, determining that at least one input data table associated with the operation node is a first input data table, and determining a target field in the first input data table, wherein the target field is a field in the first input data table selected by the user;

[0084] Step B20, filtering the data belonging to the target field in the first input data table according to a preset filtering condition to obtain a target array;

[0085] Step B30, updating the target array to at least one output data table.

[0086] It should be noted that the target field is a specific field in the input data table that is selected for the filtering operation. The filtering condition is the filtering criteria set for the target field, which is used to filter out the data that meets the conditions from the input data table. The target array is a set of qualified data that is filtered out from the input data table and belongs to the target field after the filtering operation. Updating the target array to at least one output data table is done by column mapping, which is a data conversion method that matches the columns (or fields) in the source data table with the columns (or fields) in the target data table so that the source data can be copied to the target data table.

[0087] First, select one or more fields from the input data table associated with the operation node as the target fields. These fields are the basis for subsequent filtering operations. Next, set the corresponding filtering conditions for each target field. The filtering conditions can be numeric ranges, string matching, date intervals, etc., depending on the data type and business requirements of the target field. According to the set filtering conditions, the data belonging to the target field in the input data table is filtered. This step traverses all records in the input data table and checks whether the value of the target field in each record meets the filtering conditions. The filtered data that meets the conditions will be collected into a new data set, namely the target array. The target array contains all the data retained after the filtering operation.

[0088] Next, update the data in the target array to the output data table by column mapping. Column mapping is to match the columns (or fields) in the target array with the columns (or fields) in the output data table. When performing column mapping, you need to ensure that each field in the target array can find a corresponding field in the output data table. If the corresponding fields do not exist in the output data table, you may need to create them first. After completing the column mapping, copy the data in the target array to the output data table one by one. This step will update the contents of the output data table to include the filtered data.

[0089] The data processing operations and filtering conditions involved are configured as configurable chain expression operations. The operations that can be selected in the next step are determined by the return results of the previous step.

[0090] For example, refer to Figure 5 , Figure 5This is a schematic diagram of the scenario of modifying the combined operation. Taking the operation node of adding data to the data table as an example, the user's goal is to add data to a target data table named c. The data value source is specified as obtaining static data from the existing "test_query_problem details_iteration" worksheet, and its accurate value source is specified as data.data.data.configs. The data structure of the worksheet can also be viewed below the value source selection box to facilitate the determination of the accurate value source. After determining the value source, the table data is generated into an array according to the attributes, and the filtering conditions are applied (such as the title of the table data is not empty). Here you can also choose to directly generate an array of the specified type. After the array is generated, the target columns (such as "key", "format" and "title") are matched with the mapping columns (such as "key", "format" and "title"). This shows that before adding data, it may be necessary to convert and map the data to ensure that the format and content of the data match the requirements of the data table.

[0091] This embodiment implements the function of filtering data from the input data table and updating it to the output data table by selecting the target field, setting the filtering condition, performing the filtering operation, and performing column mapping and data updating. This process is very common in data processing and analysis and can be used in scenarios such as data cleaning and data filtering.

[0092] Based on the first or second embodiment of the present application, in the third embodiment of the present application, the same or similar contents as those in the first or second embodiment can be referred to the above introduction, and will not be described in detail later. Step S40 includes steps C10 to C20:

[0093] Step C10, if a debugging instruction sent from the outside is received, the preset parameters are used as a debugging input data table;

[0094] It should be noted that the debugging instruction is a control signal from the outside, which is used to trigger the system to enter the debugging mode or perform a specific debugging operation. In the present embodiment, the debugging instruction is used to instruct the system to use preset parameters as input data. The preset parameters are a set of parameter values ​​predefined during the system setting or configuration stage, which are used to replace the input data during actual operation in specific circumstances (such as debugging, testing, etc.). These parameter values ​​are usually fixed to facilitate the reproduction and analysis of problems. The first input data table is a table used to store and process input data in the present embodiment, and is the starting point in the data processing flow. When the debugging instruction is received, the table is filled with preset parameters.

[0095] When the external system or user triggers the debugging function, a debugging instruction is sent to the system of this embodiment. After receiving the debugging instruction, the system enters the debugging mode and prepares to use the preset parameters as input data. If there are no preset parameters, the system default debugging parameters are used for debugging. The system fills the first input data table according to the values ​​of the preset parameters. These parameter values ​​are usually preset in the system configuration phase and are used to simulate the input data during actual operation. After filling, the first input data table contains the initial data for debugging.

[0096] Step C20, updating the data in at least one debugging input data table to at least one output data table according to the combined operations in all operation nodes, obtaining a debugging output data table, and displaying the debugging output data table.

[0097] It should be noted that the debugging output data table is the result obtained by the operation node after processing the input data through data processing operations. These debugging output data tables may contain new data sets, statistical values, etc., which are used for subsequent analysis, display or as input for other operation nodes.

[0098] The system executes each operation node in sequence according to a predetermined order or logic. In each operation node, the system calls the corresponding data processing operation to process the first input data table (or the output data of the previous operation node). After each operation node is executed, a debug output data table will be generated. The system stores these debug output data tables for subsequent analysis, display or as input for other operation nodes. Finally, the system displays the debug output data tables of all operation nodes to the user or external system. The display method can be data tables, charts, log information, etc., depending on the user's needs and the configuration of the system.

[0099] For example, refer to Figure 6 , Figure 6 This is a schematic diagram of the debugging output data table scenario. When the system completes debugging according to the debugging instructions, the page will display the following Figure 6 The debugging data table shown in the figure has three columns corresponding to the data preprocessing operations performed by the three operation nodes. There is an expansion button on the far right of each column. When the expansion button is clicked, the table before and after execution will be displayed. Taking the first operation node as an example (adding data to item data table c), the data table before execution shows "No data" and lists three fields: key, format, and title. After execution, data is added to the data table, showing the specific key value ("DecisionResult", etc.), format value (indicating that the data format is a table type), and title value (such as "Balanced Scheme Parameter Details", etc.).

[0100] This embodiment triggers the use of preset parameters through debugging instructions, and processes data through a series of operation nodes and their corresponding data processing operations. This mechanism enables the system to be debugged and tested without relying on actual input data, thereby improving the reliability and stability of the system.

[0101] In a feasible implementation manner, step S40 further includes steps D10 to D20:

[0102] Step D10, if a page component binding instruction sent from the outside is received, the data in the target output data table is bound to the page component specified by the page component binding instruction, and the target output data table is output through the page component;

[0103] It should be noted that the component binding instruction is an operation signal from the user, which is used to specify that certain data is bound to a specific user interface component. Components are basic elements for building user interfaces, such as buttons, text boxes, etc.

[0104] When an external system or user triggers a component binding event (such as clicking a button, submitting a form, etc.), a component binding instruction is sent to the system of this embodiment. The instruction contains the location of the data to be bound in the output data table (such as field name, row number, etc.) and the identifier of the target component (such as component ID, class name, etc.). The system parses the component binding instruction and finds the corresponding data in the target output data table. Then, the system binds this data to the component specified by the instruction. This usually involves updating the properties or status of the component so that the data is correctly displayed on the user interface.

[0105] Step D20, if a page data binding instruction sent externally is received, the data in the target output data table is bound to the page data specified by the page data binding instruction, and the target output data table is output through the page data, wherein the page data is bound by at least one page component.

[0106] It should be noted that the page data binding instruction is similar to the component binding instruction, but it is a data binding for the entire page or a part of the page. This means that the data specified by the instruction will be bound to the global data structure of the page, which can be accessed and used by multiple components on the page. Page data is a page-level data structure used to store and manage data that needs to be displayed or operated on the page. This data can come from the output data table or be obtained or calculated by other means.

[0107] Similarly, when the data of an entire page or a part of a page needs to be updated, the external system sends a page data binding instruction. The instruction contains the location of the data to be bound in the target output data table and the identifier or path of the target page data. The system parses the page data binding instruction and finds the corresponding data in the target output data table. Then, the system binds this data to the page data specified by the instruction. This means that the data is stored in the global data structure of the page and can be accessed and used by multiple components on the page. It is worth noting that page data is different from component data. It has a higher level of abstraction and a wider scope of application. Once the page data is updated, all components bound to the data will automatically reflect these changes. This improves data consistency and maintainability.

[0108] For example, refer to Figure 7 , Figure 7 This is a schematic diagram of the scene for selecting a binding target. Among them, "Component" and "Page Static Data" are two main options, which represent different types of targets that users can bind the target output data table to. Confirm that "Component" is selected and the system will receive a page component binding instruction. Confirm that "Page Static Data" is selected and the system will receive a page data binding instruction. When you click "Component", the page will display the current component, such as Figure 7 As shown in the figure, the components of the current page are "Unnamed Repeating Component 1", "Unnamed Tab Page 2", and "Unnamed Table 3". These check boxes indicate that users can also select these specific components or page elements as binding targets. Below the options, there are two buttons: "Clear" and "OK". Users can cancel the current selection and reset the interface to the initial state by clicking the "Clear" button. Clicking the "OK" button saves the user's selection and performs the related binding operations.

[0109] This embodiment dynamically binds data to user interface components or page data according to external instructions. This mechanism enables the user interface to flexibly respond to data changes, improving user experience and system scalability.

[0110] It should be noted that the above examples are only used to understand the present application and do not constitute a limitation on the data preprocessing method in the development of the zero-code platform of the present application. More forms of simple transformations based on this technical concept are all within the scope of protection of the present application.

[0111] This application also provides a data preprocessing device in the development of a zero-code platform, please refer to Figure 8 , the data preprocessing devices in the zero-code platform development include:

[0112] An input-output module 10 is defined, which determines at least one input data table according to at least one preset data source, and constructs at least one output data table according to a preset output data table rule, wherein the worksheet fields and data types in the output data table are determined according to the output data table rule;

[0113] An operation node module 20 is defined, an operation node is constructed according to preset business requirements, and at least one basic atomic operation configured in the operation node is combined to obtain a combined operation, wherein the combined operation is used to update an array obtained by filtering data in an input data table associated with the operation node to an output data table associated with the operation node;

[0114] The output data module 30 updates the data in at least one input data table to at least one output data table according to the combination operation in the operation node, obtains a target output data table, and outputs the target output data table.

[0115] The data preprocessing device in the zero-code platform development provided by the present application adopts the data preprocessing method in the zero-code platform development in the above-mentioned embodiment, which can improve the flexibility of the zero-code platform data preprocessing. Compared with the prior art, the beneficial effects of the data preprocessing device in the zero-code platform development provided by the present application are the same as the beneficial effects of the data preprocessing method in the zero-code platform development provided by the above-mentioned embodiment, and the other technical features of the data preprocessing device in the zero-code platform development are the same as the features disclosed in the above-mentioned embodiment method, which will not be repeated here.

[0116] The present application provides a data preprocessing device in zero-code platform development, and the data preprocessing device in zero-code platform development includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the data preprocessing method in the zero-code platform development in the above-mentioned embodiment one.

[0117] Reference below Fig. 9, which shows a schematic diagram of the structure of a data preprocessing device in the zero-code platform development suitable for implementing the embodiment of the present application. The data preprocessing device in the zero-code platform development in the embodiment of the present application may include but is not limited to mobile terminals such as mobile phones, laptops, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions), PMPs (Portable Media Players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Fig. 9 The data preprocessing device shown in the zero-code platform development is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0118] like Fig. 9 As shown, the data preprocessing device in the zero-code platform development may include a processing device 1001 (such as a central processing unit, a graphics processor, etc.), which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM: Read Only Memory) 1002 or the program loaded from the storage device 1003 to the random access memory (RAM: Random Access Memory) 1004. In RAM1004, various programs and data required for the operation of the data preprocessing device in the zero-code platform development are also stored. The processing device 1001, ROM1002 and RAM1004 are connected to each other through a bus 1005. The input / output (I / O) interface 1006 is also connected to the bus. Typically, the following systems can be connected to the I / O interface 1006: input devices 1007 including, for example, a touch screen, a touchpad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; output devices 1008 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; storage devices 1003 including, for example, a magnetic tape, a hard disk, etc.; and communication devices 1009. The communication device 1009 can allow the data preprocessing device in the zero-code platform development to communicate wirelessly or wired with other devices to exchange data. Although the figure shows a data preprocessing device in the zero-code platform development with various systems, it should be understood that it is not required to implement or have all the systems shown. More or fewer systems may be implemented or have instead.

[0119] In particular, according to the embodiments disclosed in the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, the embodiments disclosed in the present application include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication device, or installed from a storage device 1003, or installed from a ROM 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiment disclosed in the present application are executed.

[0120] The data preprocessing device in the zero-code platform development provided by this application adopts the data preprocessing method in the zero-code platform development in the above embodiment, which can improve the flexibility of zero-code platform data preprocessing. Compared with the prior art, the beneficial effects of the data preprocessing device in the zero-code platform development provided by this application are the same as the beneficial effects of the data preprocessing method in the zero-code platform development provided by the above embodiment, and the other technical features of the data preprocessing device in the zero-code platform development are the same as the features disclosed in the method of the previous embodiment, which will not be repeated here.

[0121] It should be understood that the various parts disclosed in this application can be implemented by hardware, software, firmware or a combination thereof. In the description of the above embodiments, specific features, structures, materials or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0122] The above are only specific implementations of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0123] The present application provides a medium, which is a computer-readable storage medium having computer-readable program instructions (i.e., a computer program) stored thereon, and the computer-readable program instructions are used to execute the data preprocessing method in the zero-code platform development in the above-mentioned embodiment.

[0124] The computer-readable storage medium provided in the present application may be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems or devices, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM: Random Access Memory), a read-only memory (ROM: Read Only Memory), an erasable programmable read-only memory (EPROM: Erasable Programmable Read Only Memory or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM: CD-Read Only Memory), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system or device. The program code contained on the computer-readable storage medium may be transmitted using any appropriate medium, including but not limited to: wires, optical cables, RF (Radio Frequency: Radio Frequency), etc., or any suitable combination of the above.

[0125] The above-mentioned computer-readable storage medium may be included in the data preprocessing device in the zero-code platform development; or it may exist independently without being assembled into the data preprocessing device in the zero-code platform development.

[0126] The computer-readable storage medium carries one or more programs. When the one or more programs are executed by the data preprocessing device in the zero-code platform development, the data preprocessing device in the zero-code platform development:

[0127] Determine at least one input data table according to at least one preset data source, and construct at least one output data table according to a preset output data table rule, wherein the worksheet fields and data types in the output data table are determined according to the output data table rule;

[0128] An operation node is constructed according to preset business requirements, and at least one basic atomic operation configured in the operation node is combined to obtain a combined operation, wherein the combined operation is used to update an array obtained by filtering data in an input data table associated with the operation node to an output data table associated with the operation node;

[0129] According to the combined operation in the operation node, data in at least one input data table is updated to at least one output data table to obtain a target output data table, and the target output data table is output.

[0130] Computer program code for performing the operations of the present application may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0131] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present application. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0132] The modules involved in the embodiments described in this application may be implemented by software or hardware, wherein the name of the module does not constitute a limitation on the unit itself in some cases.

[0133] The readable storage medium provided in this application is a computer-readable storage medium, which stores computer-readable program instructions (i.e., computer programs) for executing the data preprocessing method in the above-mentioned zero-code platform development, and can improve the flexibility of zero-code platform data preprocessing. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in this application are the same as the beneficial effects of the data preprocessing method in the zero-code platform development provided in the above-mentioned embodiment, and will not be repeated here.

[0134] The present application also provides a product, which is a computer program product, including a computer program, which, when executed by a processor, implements the steps of the data preprocessing method in the zero-code platform development as described above.

[0135] The computer program product provided in this application can improve the flexibility of zero-code platform data preprocessing. Compared with the prior art, the beneficial effects of the computer program product provided in this application are the same as the beneficial effects of the data preprocessing method in the zero-code platform development provided in the above embodiment, which will not be repeated here.

[0136] The above are only some embodiments of the present application, and are not intended to limit the patent scope of the present application. All equivalent structural changes made using the contents of the present application specification and drawings under the technical concept of the present application, or direct / indirect application in other related technical fields are included in the patent protection scope of the present application.

Claims

1. A data preprocessing method in zero-code platform development, characterized in that: The data preprocessing method in the zero-code platform development includes: Determine at least one input data table according to at least one preset data source, and construct at least one output data table according to a preset output data table rule, wherein the worksheet fields and data types in the output data table are determined according to the output data table rule; An operation node is constructed according to preset business requirements, and at least one basic atomic operation configured in the operation node is combined to obtain a combined operation, wherein the combined operation is used to update an array obtained by filtering data in an input data table associated with the operation node to an output data table associated with the operation node; According to the combined operation in the operation node, the data in the at least one input data table is updated to at least one output data table to obtain a target output data table, and the target output data table is output.

2. The data preprocessing method in zero-code platform development as claimed in claim 1, characterized in that: The step of combining and processing at least one basic atomic operation configured in the operation node to obtain a combined operation includes: Determine a preset initial data type, and configure at least one basic atomic operation for each of the initial data types, wherein the initial data types include array type, Boolean type, object type, number type, string type, and time type; For each of the operation nodes, all basic atomic operations configured for the initial data type are combined according to a preset operation order to obtain a combined operation.

3. The data preprocessing method in zero-code platform development according to claim 1, characterized in that: The basic atomic operation includes filtering and mapping, and the step of updating the data in the at least one input data table to the at least one output data table according to the combined operation in the operation node includes: Determine at least one input data table associated with the operation node as a first input data table, and determine a target field in the first input data table, wherein the target field is a field in the first input data table selected by a user; Filter the data belonging to the target field in the first input data table according to a preset filtering condition to obtain a target array; The target array is updated to at least one of the output data tables.

4. The data preprocessing method in zero-code platform development according to claim 1, characterized in that: The step of updating the data in the at least one input data table to the at least one output data table according to the combined operation in the operation node further comprises: If there are at least two operation nodes, determining an arrangement order of the at least two operation nodes; The at least two operation nodes are controlled in accordance with the arrangement order, and the at least one input data table is processed in sequence according to the respective corresponding combination operations to update the data in at least one input data table to at least one output data table, wherein, when the controlled operation node is not the first operation node, the node data table output by the previous operation node of the non-first operation node is determined, and if a new input data table is detected, the node data table and the new input data table are processed according to the combination operation of the non-first operation node.

5. The data preprocessing method in zero-code platform development as claimed in claim 4, characterized in that: The input data table includes a debugging input data table, and the data preprocessing method in the zero-code platform development further includes: If a debugging instruction sent from outside is received, the preset parameters are used as the debugging input data table; According to the combined operations in all the operation nodes, the data in the at least one debugging input data table is updated to the at least one output data table to obtain a debugging output data table, and the debugging output data table is displayed.

6. The data preprocessing method in zero-code platform development as claimed in claim 1, characterized in that: The step of outputting the target output data table comprises: If a page component binding instruction sent from the outside is received, the data in the target output data table is bound to the page component specified by the page component binding instruction, and the target output data table is output through the page component; If a page data binding instruction sent externally is received, the data in the target output data table is bound to the page data specified by the page data binding instruction, and the target output data table is output through the page data, wherein the page data is bound by at least one of the page components.

7. A data preprocessing device in zero-code platform development, characterized in that: The data preprocessing device in the zero-code platform development includes: An input-output module is defined, at least one input data table is determined according to at least one preset data source, and at least one output data table is constructed according to a preset output data table rule, wherein the worksheet fields and data types in the output data table are determined according to the output data table rule; An operation node module is defined, an operation node is constructed according to preset business requirements, and at least one basic atomic operation configured in the operation node is combined to obtain a combined operation, wherein the combined operation is used to update an array obtained by filtering data in an input data table associated with the operation node to an output data table associated with the operation node; The output data module updates the data in the at least one input data table to at least one output data table according to the combination operation in the operation node, obtains a target output data table, and outputs the target output data table.

8. A data preprocessing device in zero-code platform development, characterized in that: The data preprocessing device in the zero-code platform development includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program is configured to implement the steps of the data preprocessing method in the zero-code platform development as described in any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the data preprocessing method in the zero-code platform development as described in any one of claims 1 to 6.

10. A computer program product, comprising a computer program, which, when executed by a processor, implements the steps of the data preprocessing method in the zero-code platform development as described in any one of claims 1 to 6.

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