Point table Excel importing auxiliary method and device and electronic equipment

Abstract

The invention relates to a point table Excel importing auxiliary method and device and electronic equipment, and the method comprises the steps: reading header information of a point table Excel file, matching the header information with a preset template constraint, and establishing a mapping relation between a file column and a preset field; extracting data from the point table Excel file to generate a row-level data object; performing data standardization processing and consistency check on the row-level data object set to generate a local problem set containing problem entries; executing problem positioning and inverse labeling output, and generating and outputting a feedback result based on the local problem set; and when a preset submission condition is met, submitting the processed point table data to a server, if a failure detail is imported, matching the failure detail with the row-level data object set, generating a failure problem set, and then executing problem positioning and reverse labeling output again. According to the invention, the problem of difficulty in positioning and correction caused by the fact that the verification problem cannot be accurately associated to the original cell is solved.

Description

Technical Field

[0001] This invention relates to the field of monitoring system configuration data processing technology, and in particular to an auxiliary method, device and electronic device for importing point tables from Excel. Background Technology

[0002] In integrated monitoring systems, point data is the foundation for equipment monitoring, data acquisition, and control. It includes key information such as monitoring point identifiers, data types, and alarm thresholds. For medium to large-scale monitoring systems, the required number of points can reach thousands to hundreds of thousands. Traditional line-by-line data entry is inefficient and prone to errors. Therefore, the industry commonly uses predefined Excel templates as the unified medium for point data entry. After filling in the template, users can import the table content into the system server in batches using a dedicated client or tool.

[0003] However, existing methods for importing Excel spreadsheets have significant shortcomings. Due to a lack of effective identification and handling of structural issues such as template version differences and header field shifts, the import process is prone to failure due to incorrect field mapping. More importantly, when data validation (whether client-side initial checks or server-side in-depth checks) detects problems, existing methods typically only provide scattered, text-based error descriptions or suggestion lists. These suggestions cannot establish a precise and intuitive connection to specific cell locations in the original Excel file. To correct errors, users must perform extensive manual searching, comparison, and verification within the Excel worksheet, a tedious and easily overlooked process. Furthermore, after an import failure, the system lacks a mechanism to effectively organize and reverse-annotate the failure details back to the original table, often requiring users to perform full modifications and repeat the entire submission process, resulting in low efficiency. Simultaneously, the entire validation and correction process lacks standardized deliverables for archiving, review, and team collaboration.

[0004] Therefore, the existing point table Excel import method cannot efficiently and accurately locate and feed back data verification problems (including format errors, logical conflicts, and failure details returned by the server) to the specific cell location of the original Excel file during the import process. This makes error location difficult, the correction process cumbersome and prone to errors, which seriously affects the efficiency and success rate of large-scale point table data import. Summary of the Invention

[0005] Therefore, it is necessary to address the technical problem that existing point table Excel import methods cannot efficiently and accurately locate and feedback data verification issues during the import process to the specific cell locations of the original Excel file, resulting in difficulties in error location, cumbersome and error-prone correction processes, which seriously affect the efficiency and success rate of large-scale point table data import. To address this, a point table Excel import auxiliary method, device, and electronic device should be provided.

[0006] This invention provides an auxiliary method for importing point tables into Excel, the method comprising: Read the header information of the Excel file and match it with the preset template constraints to establish a mapping relationship between the file columns and preset fields; Based on the mapping relationship, data is extracted row by row from the point table Excel file, and a row-level data object is generated for each row of data. Each row-level data object contains the values ​​of each field in the row of data and the original cell position information corresponding to each value. Perform data normalization and consistency checks on the row-level data object set to generate a local problem set containing at least one problem entry, wherein each problem entry is associated with at least one row-level data object and the original cell location information corresponding to the field value that caused the problem within that object; Performing problem localization and reverse annotation output includes: generating and outputting a localizable feedback result based on the local problem set, wherein the feedback result is configured to associate and present the description information of at least one of the problem entries in the corresponding cell of the point table Excel file based on the original cell location information; When the preset submission conditions are met, the processed point table data is submitted to the server. If the server returns import failure details, the failure details are matched with the row-level data object set, and a set of failure issues is generated based on the matching results. Then, the problem location and reverse annotation output are performed again to output a locationable feedback result for the failure details.

[0007] In one embodiment, the step of reading the header information of the point table Excel file and matching it with preset template constraints includes: Parse the Excel file containing the data points to obtain the column number of each data column and the text of the header cell; The column number and header text of each column are compared and similarity calculated with the expected column number range and allowed header keyword set defined for multiple preset fields in the preset template constraints. Based on the similarity calculation results, a preset field is determined for the mapping of each data column.

[0008] In one embodiment, the data normalization process includes at least one of the following operations: Convert string-type numeric values ​​to number types, unify physical units of various representations into standard units, and convert text-described status values ​​into internal system status codes based on a preset mapping table.

[0009] In one embodiment, the consistency check is performed based on a predefined set of rules, which includes at least one of field format rules, numerical range rules, business logic rules, and cross-field reference relationship verification rules.

[0010] In one embodiment, generating a local question set containing at least one question entry includes: Each problem item discovered during the inspection is classified into a problem level, which includes at least an error level that prevents submission and a warning level that allows submission; wherein, satisfying the preset submission conditions includes: there are no problem items with error levels in the local problem set.

[0011] In one embodiment, generating and outputting a locationable feedback result includes: A visual verification report file is generated. The visual verification report summarizes all the problem entries in the local problem set in the form of a list, and each problem entry contains link information or positioning parameters that can locate the corresponding cell in the point table Excel file.

[0012] In one embodiment, generating and outputting a locationable feedback result further includes: Generate and execute a annotation instruction, which is used in the point table Excel file to visually present the description information of the associated problem item by adding comments or modifying the cell background color on the cell indicated by the original cell location information.

[0013] In one embodiment, matching the failure details with the row-level data object set specifically involves: Analyze the import failure details and extract the failure data point identification information contained therein; Using the failure data point identification information as an index, search for row-level data objects with the same identification information in the row-level data object set; The original cell location information bound to the found row-level data object is associated with the corresponding failure reason to generate the set of failure issues.

[0014] In one embodiment, the process of re-performing problem localization and back-annotation output further includes: A final processing report is generated, which combines and records all problems found during the local verification process and the server import failure handling process, their location information and processing status.

[0015] The present invention also provides an auxiliary device for importing Excel spreadsheets, the device comprising: The template recognition and field mapping module is used to read the header information of the point table Excel file and match it with the preset template constraints to establish the mapping relationship between the file columns and the preset fields. The row-level data objectification module is used to extract data row by row from the point table Excel file based on the mapping relationship, and generate a row-level data object for each row of data. Each row-level data object contains the values ​​of each field in the row of data and the original cell position information corresponding to each value. The local validation and issue set generation module is used to perform data normalization processing and consistency checks on the row-level data object set, and generate a local issue set containing at least one issue entry, wherein each issue entry is associated with at least one row-level data object and the original cell position information corresponding to the field value that caused the issue within that object; The problem localization and anti-annotation output module is used to perform problem localization and anti-annotation output, including: generating and outputting a localizable feedback result based on the local problem set, wherein the feedback result is configured to associate and present the description information of at least one of the problem entries in the corresponding cell of the point table Excel file according to the original cell position information; The import submission and failure handling module is used to submit the processed point table data to the server when the preset submission conditions are met. If the server returns import failure details, the failure details are matched with the row-level data object set, and a set of failure issues is generated based on the matching results. Then, the problem location and reverse annotation output are performed again to output a locationable feedback result for the failure details.

[0016] The present invention also provides an electronic device, including a memory and a processor, wherein the memory stores a computer program, characterized in that the processor, when executing the computer program, implements the Excel import assistance method described in any of the above claims.

[0017] The aforementioned Excel import assistance method, device, and electronic equipment effectively overcome the technical problem of "verification issues not being accurately associated with the original Excel cells, leading to difficulties in locating and correcting them" by establishing a core data association of "row-level data objects binding to the original cell location information." This association is used to perform "problem location and reverse annotation output" in both local verification and server failure scenarios. Specifically, each field value is bound to its physical location in the table during the data extraction stage. Then, whether it's a problem found during local inspection or a failure detail returned by the server, it can be uniformly organized into problem entries associated with specific cells through this binding relationship. Finally, by generating a locationable feedback result that directly presents the problem description information in the corresponding cell of the original file, users can quickly and accurately locate and correct errors in the familiar Excel environment without needing to manually search and compare across tools. This reduces the cost of error location and correction, and improves the overall efficiency and success rate of importing point tables. Attached Figure Description

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

[0019] Figure 1 Here is a flowchart of an example of an auxiliary method for importing a point table from Excel; Figure 2 This is a schematic diagram illustrating the principle of an Excel import auxiliary method for a point table; Figure 3 This diagram illustrates the binding relationship between row-level data objects and cell location information. Figure 4 A logical diagram illustrating the generation, location, presentation, and reverse annotation output of the problem set; Figure 5 This is a schematic diagram of a point table Excel import auxiliary device according to one embodiment; Figure 6 This is an internal structural diagram of an electronic device according to one embodiment. Detailed Implementation

[0020] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0021] The following is combined with Figures 1-6 This invention describes an auxiliary method, apparatus, and electronic device for importing point tables into Excel.

[0022] like Figure 1 and Figure 2 As shown in one embodiment, a point table Excel import assistance method includes the following steps: Step S110: Read the header information of the point table Excel file and match it with the preset template constraints to establish a mapping relationship between the file columns and preset fields.

[0023] This process specifically includes standardizing field names by unifying capitalization, whitespace, and synonyms in the header text to reduce the impact of differences in data entry on matching. It also includes performing mapping confidence assessment and structural problem identification (such as missing fields, duplicates, or non-unique mappings) to identify and prevent structural errors at the source. This process solves the problem of unstable field alignment caused by template version or header drift.

[0024] Step S120: Based on the mapping relationship, extract data row by row from the point table Excel file and generate a row-level data object for each row of data. Each row-level data object contains the values ​​of each field in the row of data and the original cell position information corresponding to each value.

[0025] Based on this mapping relationship, data is extracted line by line from the file, generating a row-level data object for each line. The key improvement lies in the fact that each row-level data object not only contains the values ​​of each field, but also the original cell position information corresponding to each value. See [link to relevant documentation]. Figure 3 The original cell location information includes the worksheet name, column number, and the original row number of the row corresponding to the row-level data object in the Excel file. Furthermore, it can generate row-level fingerprint information for each row-level data object, calculated from a combination of key fields. This design lays the data foundation for the precise location of all subsequent problems and for matching with server failure details.

[0026] Step S130: Perform data normalization and consistency checks on the row-level data object set to generate a local problem set containing at least one problem entry, wherein each problem entry is associated with at least one row-level data object and the original cell location information corresponding to the field value that caused the problem within that object.

[0027] Data normalization is performed on the row-level data object set. This includes at least one of the following operations: converting string-type numeric values ​​to numeric types, unifying physical units of various representations into standard units, and converting text-described status values ​​into system internal status codes based on a pre-defined mapping table. This normalization process is organized based on a set of rules accumulated from numerous equipment vendors' equipment point table rule bases, enabled for different template versions or point table types. Simultaneously, a consistency check is performed based on a predefined set of rules (including at least one of field format rules, numerical range rules, business logic rules, and cross-field reference relationship validation rules). This consistency check covers missing required fields, format types, inline constraints, and initial screening of file conflicts, generating a local problem set. Each problem entry is associated with the row-level data object that triggered the problem and its original cell location information. Furthermore, the process of generating the problem set includes problem classification. Specifically, each problem entry discovered during the check is classified into a problem level, including at least an error level that prevents submission and a warning level that allows submission. Deduplication and merging logic is applied when multiple rules are triggered in the same cell, thus transforming the abstract check results into a clear, locatable, categorized, and merged problem list.

[0028] Step S140, performing problem localization and back-annotation output, includes: generating and outputting a localizable feedback result based on the local problem set, wherein the feedback result is configured to associate and present the description information of at least one problem item in the corresponding cell of the point table Excel file based on the original cell location information.

[0029] The process of performing issue localization and back-annotation output involves generating and outputting a locationable feedback result based on the local issue set and its bound original cell location information. This feedback result is configured to directly associate and display the description information of the issue entries in the corresponding cells of the origin table Excel file. Specifically, this includes: generating a visual verification report file, which summarizes all issue entries in the local issue set in list form, with each issue entry containing link information or location parameters that can locate the corresponding cell in the origin table Excel file; or generating and executing an annotation instruction, which visually displays the associated issue entry description information in the origin table Excel file by adding comments or modifying the cell background color, at the cell indicated by the original cell location information. See [link to relevant documentation]. Figure 4The problem location presentation also supports problem aggregation statistics by row, field or problem type, filtering by severity, and automatically locating and jumping to the corresponding cell based on cell position information when the user selects a problem item, and displaying the context information of key fields in that row to help with understanding. This series of steps allows users to quickly locate, understand and prioritize key issues in the original file without having to manually search across tools, significantly reducing the cost of correction and the cognitive threshold.

[0030] Step S150: When the preset submission conditions are met, the processed point table data is submitted to the server. If the server returns import failure details, the failure details are matched with the row-level data object set, and a set of failure issues is generated based on the matching results. Then, the problem location and back-annotation output are performed again to output the locationable feedback results for the failure details.

[0031] When the preset submission conditions are met (including the absence of error level issues in the local issue set), the processed data is submitted to the server. If import failure details are received, the failure details are matched with the locally stored set of row-level data objects to generate a set of failed issues. The aforementioned issue location and back-annotation output process is then executed again, transforming the scattered failure information returned by the server into locatable and back-annotated issues. This allows users to quickly correct and resubmit in a targeted manner, forming a closed loop. Specifically, matching the failure details with the set of row-level data objects involves: parsing the import failure details and extracting the failure data point identifier information contained therein; using the failure data point identifier information as an index, searching for row-level data objects with the same identifier information in the set of row-level data objects; and associating the original cell position information bound to the found row-level data objects with the corresponding failure reasons to generate a set of failed issues.

[0032] In addition, after re-executing the problem localization and back-annotation output, the process includes: generating a final processing report. The final processing report combines and records all problems found during the local verification process and the server import failure handling process, their location information, and processing status. At the end of the process, a final processing report that combines and records all problems is generated for archiving and review. The visual verification report or final processing report may include a "summary area" for displaying a statistical overview and a "details area" for listing detailed problems one by one.

[0033] The process reads the header information from the point table Excel file and matches it against preset template constraints. This includes: parsing the point table Excel file to obtain the column numbers and header cell text for each data column; comparing and calculating the similarity between the column number and header text of each column and the expected column number range and allowed header keyword set defined for each preset field in the preset template constraints; and determining the preset field to which each data column is mapped based on the similarity calculation results. Parsing the file to obtain the column numbers and header text, comparing and calculating the similarity between them and the expected column number range and allowed keyword set defined for each preset field in the template constraints, and determining the mapping relationship based on the calculation results—this refined process improves the accuracy and robustness of field mapping through quantitative comparison.

[0034] The aforementioned Excel import assistance method for point tables utilizes a data architecture of "binding row-level data objects to original cell location information" and "generating row-level fingerprint information." Combined with standardization and confidence assessment during template matching, scalable rule sets during normalization, hierarchical and merging mechanisms during issue generation, aggregation, redirection, and contextual prompts during location feedback, and identifier matching during failure handling, it unifies the location and processing paths for local validation issues and server-side failure details. Ultimately, it systematically presents issues in the original point table environment through locationable feedback results (including structured summaries and detailed reports or direct cell annotations). Specifically, when the number of rows involved in the failure details is small, a "focused review mode" can be entered to generate and submit only a set of issues for the failed rows, further reducing repetitive work. Overall, it systematically solves technical problems such as insufficient template structure recognition, inability to accurately associate validation issues with original cells, difficulty in locating failure details, and lack of deliverable review materials. Through client-side preprocessing, a unified location data structure, and a flexible feedback mechanism, it improves the success rate of point table import, correction efficiency, and the convenience of collaborative archiving.

[0035] The Excel import auxiliary device provided by the present invention is described below. The Excel import auxiliary device described below and the Excel import auxiliary method described above can be referred to in correspondence.

[0036] like Figure 5 As shown in one embodiment, a point table Excel import auxiliary device includes a template recognition and field mapping module 510, a row-level data objectification module 520, a local verification and problem set generation module 530, a problem location and anti-annotation output module 540, and an import submission and failure handling module 550.

[0037] The template recognition and field mapping module 510 is used to read the header information of the point table Excel file and match it with the preset template constraints to establish the mapping relationship between the file columns and the preset fields.

[0038] The row-level data objectification module 520 is used to extract data row by row from the point table Excel file based on the mapping relationship, and generate a row-level data object for each row of data. Each row-level data object contains the values ​​of each field in the row of data and the original cell position information corresponding to each value.

[0039] The local verification and issue set generation module 530 is used to perform data normalization processing and consistency checks on the row-level data object set, and generate a local issue set containing at least one issue entry, wherein each issue entry is associated with at least one row-level data object and the original cell position information corresponding to the field value that caused the issue within that object.

[0040] The problem localization and back-annotation output module 540 is used to perform problem localization and back-annotation output, including: generating and outputting a localizable feedback result based on the local problem set. The feedback result is configured to associate and present the description information of at least one problem item in the corresponding cell of the point table Excel file based on the original cell position information.

[0041] The import submission and failure handling module 550 is used to submit the processed point table data to the server when the preset submission conditions are met. If the server returns import failure details, the failure details are matched with the row-level data object set, and a set of failure issues is generated based on the matching results. Then, the problem location and back-annotation output are performed again to output the locationable feedback results for the failure details.

[0042] Figure 6 This example illustrates a schematic diagram of the physical structure of an electronic device, which can be a smart terminal. Its internal structure diagram can be as follows: Figure 6 As shown. The electronic device includes a processor, memory, and a network interface connected via a system bus. The processor provides computing and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The network interface is used to communicate with external terminals via a network connection. When the computer program is executed by the processor, it implements a point table Excel import auxiliary method, which includes: Read the header information of the Excel file and match it with the preset template constraints to establish a mapping relationship between the file columns and preset fields; Based on the mapping relationship, data is extracted row by row from the Excel file of the point table, and a row-level data object is generated for each row of data. Each row-level data object contains the value of each field in the row of data and the original cell position information corresponding to each value. Perform data normalization and consistency checks on the row-level data object set to generate a local problem set containing at least one problem entry. Each problem entry is associated with at least one row-level data object and the original cell location information corresponding to the field value that caused the problem within that object. The process of performing problem localization and back-annotation output includes: generating and outputting a localizable feedback result based on the local problem set, wherein the feedback result is configured to associate and present the description information of at least one problem item in the corresponding cell of the point table Excel file based on the original cell location information; When the preset submission conditions are met, the processed point table data is submitted to the server. If the server returns import failure details, the failure details are matched with the row-level data object set, and a set of failure issues is generated based on the matching results. Then, the problem location and reverse annotation output are performed again to output a locationable feedback result for the failure details.

[0043] Those skilled in the art will understand that Figure 6 The structure shown is merely a block diagram of a portion of the structure related to the present invention and does not constitute a limitation on the electronic device to which the present invention is applied. A specific electronic device may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0044] On the other hand, the present invention also provides a computer storage medium storing a computer program, which, when executed by a processor, implements an auxiliary method for importing Excel spreadsheets, the method comprising: Read the header information of the Excel file and match it with the preset template constraints to establish a mapping relationship between the file columns and preset fields; Based on the mapping relationship, data is extracted row by row from the Excel file of the point table, and a row-level data object is generated for each row of data. Each row-level data object contains the value of each field in the row of data and the original cell position information corresponding to each value. Perform data normalization and consistency checks on the row-level data object set to generate a local problem set containing at least one problem entry. Each problem entry is associated with at least one row-level data object and the original cell location information corresponding to the field value that caused the problem within that object. The process of performing problem localization and back-annotation output includes: generating and outputting a localizable feedback result based on the local problem set, wherein the feedback result is configured to associate and present the description information of at least one problem item in the corresponding cell of the point table Excel file based on the original cell location information; When the preset submission conditions are met, the processed point table data is submitted to the server. If the server returns import failure details, the failure details are matched with the row-level data object set, and a set of failure issues is generated based on the matching results. Then, the problem location and reverse annotation output are performed again to output a locationable feedback result for the failure details.

[0045] On another front, a computer program product or computer program is provided, comprising computer instructions stored in a computer-readable storage medium. A processor of an electronic device reads the computer instructions from the computer-readable storage medium, and when the processor executes the computer instructions, it implements a dot-matrix Excel import assistance method, which includes: Read the header information of the Excel file and match it with the preset template constraints to establish a mapping relationship between the file columns and preset fields; Based on the mapping relationship, data is extracted row by row from the Excel file of the point table, and a row-level data object is generated for each row of data. Each row-level data object contains the value of each field in the row of data and the original cell position information corresponding to each value. Perform data normalization and consistency checks on the row-level data object set to generate a local problem set containing at least one problem entry. Each problem entry is associated with at least one row-level data object and the original cell location information corresponding to the field value that caused the problem within that object. The process of performing problem localization and back-annotation output includes: generating and outputting a localizable feedback result based on the local problem set, wherein the feedback result is configured to associate and present the description information of at least one problem item in the corresponding cell of the point table Excel file based on the original cell location information; When the preset submission conditions are met, the processed point table data is submitted to the server. If the server returns import failure details, the failure details are matched with the row-level data object set, and a set of failure issues is generated based on the matching results. Then, the problem location and reverse annotation output are performed again to output a locationable feedback result for the failure details.

[0046] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. This 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 of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided by this invention can include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory may include random access memory (RAM) or external cache memory.

[0047] By way of illustration and not limitation, RAM is available in a variety of forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0048] 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.

[0049] The above-described embodiments are merely illustrative of several implementations of the present invention, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of the invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these modifications and improvements all fall within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the appended claims.

Claims

1. A method for importing point tables from Excel, characterized in that, The method includes: Read the header information of the Excel file and match it with the preset template constraints to establish a mapping relationship between the file columns and preset fields; Based on the mapping relationship, data is extracted row by row from the point table Excel file, and a row-level data object is generated for each row of data. Each row-level data object contains the values ​​of each field in the row of data and the original cell position information corresponding to each value. Perform data normalization and consistency checks on the row-level data object set to generate a local problem set containing at least one problem entry, wherein each problem entry is associated with at least one row-level data object and the original cell location information corresponding to the field value that caused the problem within that object; Performing problem localization and reverse annotation output includes: generating and outputting a localizable feedback result based on the local problem set, wherein the feedback result is configured to associate and present the description information of at least one of the problem entries in the corresponding cell of the point table Excel file based on the original cell location information; When the preset submission conditions are met, the processed point table data is submitted to the server. If the server returns import failure details, the failure details are matched with the row-level data object set, and a set of failure issues is generated based on the matching results. Then, the problem location and reverse annotation output are performed again to output a locationable feedback result for the failure details.

2. The auxiliary method for importing Excel spreadsheets according to claim 1, characterized in that, The step of reading the header information of the point table Excel file and matching it with preset template constraints includes: Parse the Excel file containing the data points to obtain the column number of each data column and the text of the header cell; The column number and header text of each column are compared and similarity calculated with the expected column number range and allowed header keyword set defined for multiple preset fields in the preset template constraints. Based on the similarity calculation results, a preset field is determined for the mapping of each data column.

3. The auxiliary method for importing Excel spreadsheets according to claim 1, characterized in that, The data normalization process includes at least one of the following operations: Convert string-type numeric values ​​to number types, unify physical units of various representations into standard units, and convert text-described status values ​​into internal system status codes based on a preset mapping table.

4. The auxiliary method for importing Excel spreadsheets according to claim 1, characterized in that, The consistency check is performed based on a predefined set of rules, which includes at least one of field format rules, numerical range rules, business logic rules, and cross-field reference relationship verification rules.

5. The auxiliary method for importing point tables into Excel according to claim 1, characterized in that, The generation of a local issue set containing at least one issue entry includes: Each problem item discovered during the inspection is classified into a problem level, which includes at least an error level that prevents submission and a warning level that allows submission; wherein, satisfying the preset submission conditions includes: there are no problem items with error levels in the local problem set.

6. The auxiliary method for importing point tables into Excel according to claim 1, characterized in that, The generation and output of a locationable feedback result includes: A visual verification report file is generated. The visual verification report summarizes all the problem entries in the local problem set in the form of a list, and each problem entry contains link information or positioning parameters that can locate the corresponding cell in the point table Excel file.

7. The auxiliary method for importing point tables into Excel according to claim 1, characterized in that, The generation and output of a locationable feedback result also includes: Generate and execute a annotation instruction, which is used in the point table Excel file to visually present the description information of the associated problem item by adding comments or modifying the cell background color on the cell indicated by the original cell location information.

8. The auxiliary method for importing Excel spreadsheets according to claim 1, characterized in that, The matching of the failure details with the row-level data object set specifically involves: Analyze the import failure details and extract the failure data point identification information contained therein; Using the failure data point identification information as an index, search for row-level data objects with the same identification information in the row-level data object set; The original cell location information bound to the found row-level data object is associated with the corresponding failure reason to generate the set of failure issues.

9. The auxiliary method for importing point tables into Excel according to any one of claims 1 to 8, characterized in that, The process of re-executing problem localization and back-annotation output then includes: A final processing report is generated, which combines and records all problems found during the local verification process and the server import failure handling process, their location information and processing status.

10. An electronic device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the point table Excel import auxiliary method as described in any one of claims 1 to 8.

Images