Engineering cost data storage processing method and device

Abstract

The embodiment of the invention provides a project cost data storage processing method and device. The processing method comprises the steps of obtaining at least one first project cost file in a table format and at least one second project cost file in a proprietary format output by project cost software; converting the at least one first project cost file into first two-dimensional table structure data; at least one second project cost file is converted into second two-dimensional table structure data through middleware; establishing a table-row-column coordinate index system according to the first two-dimensional table structure data and the second two-dimensional table structure data; performing table-row-column dimension verification on the first two-dimensional table structure data and the second two-dimensional table structure data; and carrying out objectification storage on the first two-dimensional table structure data and the second two-dimensional table structure data which pass the verification. According to the embodiment of the invention, efficient integration and processing of different formats of project cost data are realized, and the efficiency of project cost data analysis is remarkably improved.

Description

Technical Field

[0001] The embodiments of the present invention relate to the field of computer information processing technology, and in particular to a method and device for processing engineering cost data. Background Art

[0002] Construction cost data involves core processes such as project budgeting, cost accounting, and bidding, requiring the integration of multiple data sources, including design documents, bills of quantities, and material price databases. Construction cost data also comes in a variety of heterogeneous file formats, such as xls / xlsx and proprietary formats like bwbd7 / bwsd7 / BJS2, used by power cost software.

[0003] Format differences require manual intervention in data parsing, which is inefficient. Cost parameters involve multi-dimensional indicators such as project quantity, unit price, and rate, and traditional rule engines find it difficult to cover dynamic business logic (such as cross-table reference verification and unit conversion fault tolerance). The project type requires the system to quickly adapt to new specifications, but the business rules in the traditional architecture are solidified at the code level, and updates require a lot of re-development work and deployment. Summary of the Invention

[0004] The technical problem to be solved by the embodiments of the present invention is to provide a method and device for storing and processing engineering cost data, which realizes the efficient integration and processing of engineering cost data in different formats and significantly improves the efficiency of engineering cost data analysis.

[0005] To solve the above technical problems, the technical solutions of the embodiments of the present invention are as follows:

[0006] A method for storing and processing engineering cost data, comprising:

[0007] Acquire at least one first engineering cost file in a table format and at least one second engineering cost file in a proprietary format output by engineering cost software;

[0008] Converting at least one first project cost file into first two-dimensional table structure data;

[0009] Converting at least one second engineering cost file into second two-dimensional table structure data through middleware; both the first two-dimensional table structure data and the second two-dimensional table structure data are data tables in a standard table format;

[0010] Establishing a table-row-column coordinate index system based on the first two-dimensional table structure data and the second two-dimensional table structure data;

[0011] Performing table-row-column dimension verification on the first two-dimensional table structure data and the second two-dimensional table structure data;

[0012] The first two-dimensional table structure data and the second two-dimensional table structure data that have passed verification are stored in an object-based manner.

[0013] Optionally, the first project cost file includes: a project cost file in xls / xlsx format;

[0014] The second engineering cost file includes: an engineering cost file in the bwbd7, bwsd7 and / or BJS2 proprietary format output by the engineering cost software.

[0015] Optionally, converting at least one first project cost file into first two-dimensional table structure data includes:

[0016] Parsing the rows, columns, and elements of the at least one first engineering cost file to obtain a first table element, wherein the first table element includes: multi-dimensional indicators of the first engineering cost file;

[0017] The first table element is mapped to the data table in the standard table format to obtain first two-dimensional table structure data.

[0018] Optionally, converting the at least one second project cost file into second two-dimensional table structure data through middleware includes:

[0019] Performing binary analysis on at least one second project cost file through the middleware to obtain a binary report file in a table format;

[0020] Parsing the rows, columns, and elements of the binary report file to obtain a second table element, wherein the second table element includes: multi-dimensional indicators of the second engineering cost file;

[0021] The second table element is mapped to the data table in the standard table format to obtain second two-dimensional table structure data.

[0022] Optionally, performing table-row-column dimension verification on the first two-dimensional table structure data and the second two-dimensional table structure data includes:

[0023] Get the set cost table verification rule content;

[0024] According to the cost table verification rules, performing table name compliance verification on the first two-dimensional table structure data and the second two-dimensional table structure data in the table dimension;

[0025] Performing data integrity verification on the first two-dimensional table structure data and the second two-dimensional table structure data in the row dimension according to the cost table verification rule content;

[0026] According to the cost table verification rule content, data standardization verification is performed on the first two-dimensional table structure data and the second two-dimensional table structure data in the column dimension.

[0027] Optionally, performing table name compliance verification on the first two-dimensional table structure data and the second two-dimensional table structure data in the table dimension according to the cost table verification rule content includes:

[0028] Use regular expressions to match table names to see if they conform to the set format specifications;

[0029] Identify table types through fuzzy semantic analysis and determine whether the table name semantically meets the set requirements;

[0030] The performing of data integrity verification on the first two-dimensional table structure data and the second two-dimensional table structure data in the row dimension according to the cost table verification rules includes:

[0031] Use the reflection mechanism to dynamically call the preset verification method to check whether the row data is missing or incomplete;

[0032] The performing of data standardization verification on the first two-dimensional table structure data and the second two-dimensional table structure data in the column dimension according to the cost table verification rules includes:

[0033] Perform column value range validation, measurement unit consistency detection, and business logic compliance judgment.

[0034] Optionally, performing table name compliance verification on the first two-dimensional table structure data and the second two-dimensional table structure data in the table dimension according to the cost table verification rule content further includes:

[0035] An error report with positioning information is generated, wherein the error report marks the table number, row and column coordinates of the illegal data and the violated rule entry.

[0036] An embodiment of the present invention further provides a device for storing and processing construction cost data, comprising:

[0037] an acquisition module, configured to acquire at least one first engineering cost file in a table format and at least one second engineering cost file in a proprietary format output by engineering cost software;

[0038] A processing module is used to convert at least one first engineering cost file into first two-dimensional table structure data; convert at least one second engineering cost file into second two-dimensional table structure data through middleware; the first two-dimensional table structure data and the second two-dimensional table structure data are both data tables in standard table format; establish a table-row-column coordinate index system based on the first two-dimensional table structure data and the second two-dimensional table structure data; perform table-row-column dimension verification on the first two-dimensional table structure data and the second two-dimensional table structure data; and object-store the first two-dimensional table structure data and the second two-dimensional table structure data that have passed the verification.

[0039] An embodiment of the present invention further provides a computing device, comprising:

[0040] one or more processors;

[0041] The storage device is used to store one or more programs, and when the one or more programs are executed by the one or more processors, the one or more processors implement the method as described above.

[0042] An embodiment of the present invention further provides a computing device readable storage medium, wherein the computing device readable storage medium stores a program, and when the program is executed by a processor, the method described above is implemented.

[0043] The above solution of the embodiment of the present invention has at least the following beneficial effects:

[0044] The above-mentioned scheme of the embodiment of the present invention obtains multi-format engineering cost files and converts various format files into two-dimensional table structure data, thereby avoiding the problem of data parsing requiring manual intervention due to format differences, changing the previous situation of low efficiency due to complicated formats, and realizing efficient integration and processing of engineering cost data in different formats, thereby significantly improving the efficiency of engineering cost data parsing.

[0045] A table-row-column coordinate indexing system has been established to perform table-row-column dimension verification on two-dimensional table structure data, enabling more comprehensive processing of multi-dimensional indicators such as project quantity, unit price, and rate involved in cost parameters. Compared to traditional rule engines that struggle to cover dynamic business logic (such as cross-table reference verification and unit conversion error tolerance), this approach based on a standard two-dimensional table structure and dimension verification can more flexibly handle various complex business logic and has better adaptability and processing capabilities for dynamically changing business needs.

[0046] Validated two-dimensional table data is stored in an object-based format. This data storage and management method decouples business rules from the code layer. When a project requires the system to quickly adapt to new specifications, there's no need to extensively redevelop and redeploy business rules at the code layer, as is required with traditional architectures. Because the data is already stored in a standardized, object-based format, adjustments only need to be made to the relevant data processing logic and validation rules, eliminating the need for large-scale changes to the entire code architecture. This enables faster response to new specifications and improves the system's flexibility and scalability. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 It is a flowchart of a method for storing and processing engineering cost data according to an embodiment of the present invention.

[0048] Figure 2 It is an architectural diagram of the engineering cost data storage and processing method of Example 1 of an embodiment of the present invention.

[0049] Figure 3 It is a module diagram of a device for storing and processing engineering cost data according to an embodiment of the present invention. DETAILED DESCRIPTION

[0050] Exemplary embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present invention are shown in the accompanying drawings, it should be understood that the present invention can be implemented in various forms and should not be limited by the embodiments set forth herein. Rather, these embodiments are provided to enable a more thorough understanding of the present invention and to fully convey the scope of the present invention to those skilled in the art.

[0051] like Figure 1 As shown, an embodiment of the present invention provides a method for storing and processing construction cost data, including:

[0052] Step 11: Acquire at least one first engineering cost file in a table format and at least one second engineering cost file in a proprietary format output by engineering cost software;

[0053] Step 12: converting at least one first project cost file into first two-dimensional table structure data;

[0054] Step 13: converting at least one second engineering cost file into second two-dimensional table structure data through middleware; both the first two-dimensional table structure data and the second two-dimensional table structure data are data tables in a standard table format;

[0055] Step 14: establishing a table-row-column coordinate index system based on the first two-dimensional table structure data and the second two-dimensional table structure data;

[0056] Step 15: Perform table-row-column dimension verification on the first two-dimensional table structure data and the second two-dimensional table structure data;

[0057] Step 16: Object-based storage of the first two-dimensional table structure data and the second two-dimensional table structure data that have passed verification.

[0058] In this embodiment, multi-format engineering cost files are obtained through step 11, and various format files are converted into two-dimensional table structure data in steps 12 and 13, avoiding the problem of data parsing requiring manual intervention due to format differences, changing the previous situation of low efficiency due to complicated formats, and realizing efficient integration and processing of engineering cost data in different formats, significantly improving the efficiency of engineering cost data parsing.

[0059] A table-row-column coordinate indexing system has been established, and in step 15, table-row-column dimension verification is performed on the two-dimensional table structure data. This allows for more comprehensive processing of multi-dimensional indicators such as project quantity, unit price, and rate involved in cost parameters. Compared to traditional rule engines that struggle to cover dynamic business logic (such as cross-table reference verification and unit conversion error tolerance), this approach based on a standard two-dimensional table structure and dimension verification can more flexibly handle various complex business logics and has better adaptability and processing capabilities for dynamically changing business needs.

[0060] The validated two-dimensional table data is stored in an object-oriented manner (step 16). This data storage and management method decouples business rules from the code layer to a certain extent. When the project type requires the system to quickly adapt to new specifications, there is no need to redevelop and deploy a large number of business rules at the code layer as in traditional architectures. Because the data is already stored in a standardized, object-oriented form, only the relevant data processing logic and validation rules need to be adjusted, without the need for large-scale changes to the entire code architecture. This allows for faster response to new specifications and improves the system's flexibility and scalability.

[0061] In an optional embodiment of the present invention, the first engineering cost file includes: an engineering cost file in xls / xlsx format;

[0062] The second engineering cost file includes: an engineering cost file in the bwbd7, bwsd7 and / or BJS2 proprietary format output by the engineering cost software.

[0063] In this embodiment, after clearly obtaining files of a specific format, corresponding processing strategies can be formulated according to the characteristics of each format, making the entire process from data acquisition to final storage more standardized and normalized, improving the efficiency and accuracy of data processing, and facilitating system maintenance and upgrades.

[0064] In an optional embodiment of the present invention, in step 12, converting at least one first project cost file into first two-dimensional table structure data includes:

[0065] Step 121: Parse the rows, columns, and elements of the at least one first engineering cost file to obtain a first table element, where the first table element includes: multi-dimensional indicators of the first engineering cost file;

[0066] Step 122: Map the first table element to the data table in the standard table format to obtain first two-dimensional table structure data.

[0067] In step 13, converting at least one second project cost file into second two-dimensional table structure data through middleware includes:

[0068] Step 131: performing binary parsing on at least one second project cost file through middleware to obtain a binary report file in a table format;

[0069] Step 132: Parse the rows, columns, and elements of the binary report file to obtain a second table element, where the second table element includes: multi-dimensional indicators of the second engineering cost file;

[0070] Step 133: Map the second table element to the data table in the standard table format to obtain second two-dimensional table structure data.

[0071] In this embodiment, the first engineering cost file is directly parsed by rows, columns, and elements to obtain table elements; the second engineering cost file is then processed using middleware after binary parsing. These two approaches are adapted to different file types, effectively solving the problem of multi-source data integration in the engineering cost field. They can automatically process various file formats, such as xls / xlsx and proprietary power formats, without manual format conversion, significantly reducing data processing time and improving data parsing efficiency, thus avoiding data processing obstacles caused by format incompatibilities.

[0072] During the parsing process, the file's multi-dimensional indicators are captured as table elements, ensuring the integrity of the project cost data. Core parameters such as project quantities, unit prices, and rates, as well as other relevant indicators, are preserved during the conversion process, providing comprehensive data support for subsequent accurate cost analysis and budgeting, avoiding the issues associated with traditional methods, such as lost or incomplete data, that can impact analytical reliability.

[0073] The parsed table elements are uniformly mapped to a data table in a standard table format, forming a two-dimensional table structure. This standardized storage method provides a unified storage structure for construction cost data from different sources and formats, facilitating centralized data management, retrieval, and analysis. This eliminates data fragmentation, improves data standardization and consistency, and lays the foundation for building an intelligent construction cost data analysis platform.

[0074] The unified data format and structure enhances data versatility across different systems and business scenarios. This makes subsequent in-depth data analysis, data interaction with other systems, and data expansion based on new business needs more convenient and efficient. When new project types or business rules are added, data based on the standard two-dimensional table structure can be quickly adapted, reducing system expansion and maintenance costs and significantly improving the system's business scalability.

[0075] In an optional embodiment of the present invention, in step 14, performing table-row-column dimension verification on the first two-dimensional table structure data and the second two-dimensional table structure data includes:

[0076] Step 141, obtaining the set cost table verification rule content;

[0077] Step 142: Perform table name compliance verification on the first two-dimensional table structure data and the second two-dimensional table structure data in the table dimension according to the cost table verification rule content;

[0078] Step 143: Perform data integrity verification on the first two-dimensional table structure data and the second two-dimensional table structure data in the row dimension according to the cost table verification rule content;

[0079] Step 144 : Perform data standardization verification on the first two-dimensional table structure data and the second two-dimensional table structure data in the column dimension according to the cost table verification rule content.

[0080] Step 141 obtains the set cost table verification rules, providing a clear basis and standard for the entire verification process. By pre-setting verification rules, data can be checked in a targeted manner based on the actual needs and specifications of the engineering cost business, ensuring that the verification process can accurately identify and correct any problems in the data, thereby improving the effectiveness and pertinence of the verification.

[0081] Step 142 performs table name compliance verification at the table level based on the cost table verification rules. Table names are important identifiers of data structures, and their compliance directly impacts data management and identification. Verifying that table names comply with prescribed naming rules and business requirements can avoid data search difficulties and confusion caused by confusing or non-standard table names, ensuring standardized and orderly data storage and management.

[0082] Step 143 performs a row-level data integrity check based on the cost table validation rules. Each row in the construction cost data typically represents a specific project or record. Data integrity is crucial for accurate cost accounting and project budget estimates. By checking that each row contains the necessary fields, data loss is avoided, ensuring that the data fully reflects the actual construction cost situation and improving data quality and usability.

[0083] Step 144 performs data standardization verification on the column dimension according to the cost table verification rules. Different columns typically correspond to different cost indicators or attributes, such as project quantity and unit price. By verifying that the format and value range of column data meet the specified standards, data consistency and accuracy can be ensured. For example, ensuring that project quantity data is a positive integer and that the number of decimal places in unit price data meets the required standards can avoid calculation errors and analysis deviations caused by incorrect data format or abnormal values, thereby improving the reliability of data processing and analysis results.

[0084] Through comprehensive validation across three dimensions—table, row, and column—we can thoroughly examine and correct potential issues within standard two-dimensional table-structured datasets. Strict control is exercised across everything from table structure compliance to the integrity and standardization of every row and column, significantly improving data quality and reliability. High-quality data is the foundation for accurate project cost analysis and decision-making, providing strong support for cost control, bidding, and other aspects of engineering projects.

[0085] Dimensional verification makes locating data issues clearer and more accurate. When data issues are discovered, it's quickly determined whether the anomaly is in the table structure, row data, or column data. This allows technical and business personnel to conduct targeted troubleshooting and repairs, improving data processing efficiency and reducing the time and cost of data repairs.

[0086] Strictly verified data is more adaptable to subsequent data processing and analysis operations, reducing the occurrence of system errors and anomalies caused by data quality issues. This helps enhance the stability and reliability of the entire engineering cost data management system, ensuring its normal operation and improving the system's service quality and user satisfaction.

[0087] In an optional embodiment of the present invention, in step 142, performing table name compliance verification on the first two-dimensional table structure data and the second two-dimensional table structure data in the table dimension according to the cost table verification rules includes:

[0088] Use regular expressions to match table names to see if they conform to the set format specifications;

[0089] Identify table types through fuzzy semantic analysis and determine whether the table name semantically meets the set requirements;

[0090] In step 143, performing data integrity verification on the first two-dimensional table structure data and the second two-dimensional table structure data in the row dimension according to the cost table verification rules includes:

[0091] Use the reflection mechanism to dynamically call the preset verification method to check whether the row data is missing or incomplete;

[0092] In step 144, performing data standardization verification on the first two-dimensional table structure data and the second two-dimensional table structure data in the column dimension according to the cost table verification rules includes:

[0093] Perform column value range validation, measurement unit consistency detection, and business logic compliance judgment.

[0094] In this embodiment, step 1421 uses regular expressions to check whether the table name conforms to the specified format specifications. Regular expressions have powerful pattern matching capabilities and can accurately check whether the character composition, length, and use of special characters in the table name comply with regulations. This helps ensure the consistency of the table name format, making data storage and management more standardized and orderly, and facilitating subsequent data retrieval and processing. For example, it can accurately determine whether the table name contains illegal characters or whether it complies with specific naming format requirements, avoiding data management difficulties caused by confusing table name formats.

[0095] Step 1422 uses fuzzy semantic analysis to identify the table type and determine whether the table name semantically meets the set requirements. Fuzzy semantic analysis can understand the meaning of the table name at a semantic level. Even if the table name has certain differences in expression, it can determine whether it is consistent with the actual table content and usage. This can effectively avoid situations where the table name does not match the actual data content, improving the readability and comprehensibility of the data. For example, for a table storing engineering quantity data, semantic analysis can determine whether the table name accurately reflects the core content of the table, preventing misleading naming issues.

[0096] Step 1431 uses the reflection mechanism to dynamically call preset verification methods to check whether the row data is missing or incomplete. The reflection mechanism allows the program to obtain class information and dynamically call its methods at runtime, making the verification process more flexible. For row data with different structures and contents, the appropriate verification method can be dynamically selected based on the actual situation without the need for pre-hard coding. This improves the system's adaptability to different types of construction cost data, enabling more comprehensive detection of missing values, null values, and other incompleteness that may exist in the row data, ensuring data integrity and providing a reliable data foundation for accurate construction cost analysis.

[0097] Step 1441 verifies the column's numerical range to ensure that the values in the column data are within a reasonable range. Many numerical data types (such as project quantities and unit prices) in construction cost data have specific ranges. Data outside of these ranges may be erroneous or unreasonable. Numerical range verification can promptly identify and correct these abnormal data, preventing errors in construction cost calculations caused by incorrect values and improving data accuracy and reliability.

[0098] Conducting unit consistency checks is crucial for project cost data. Different project quantities or costs may have different units of measurement. Ensuring the consistency of units within a column of data can prevent calculation errors caused by unit confusion. For example, when calculating material usage, if some data is in tons and some in kilograms, failing to perform unit consistency checks can result in erroneous results. This checking step ensures the standardization and accuracy of data, facilitating effective data analysis and comparison.

[0099] Checking the business logic compliance of column data ensures that it adheres to the actual logic and rules of the engineering cost management business. Engineering cost management has specific calculation methods, processes, and constraints. By checking whether column data conforms to these business logics, we can identify potential logical errors or irrationalities in the data. For example, we can check whether cost calculations follow the correct rates and formulas, and whether the calculated quantities are consistent with the actual project situation. This helps ensure the rationality and validity of the data, providing a reliable basis for engineering cost decision-making.

[0100] These detailed verification steps, encompassing multiple dimensions, from table names and row data to column data, employ diverse technical means and methods for comprehensive verification. This enables a more in-depth and detailed identification and correction of various data issues. By enhancing data compliance, integrity, and standardization, the overall quality of engineering cost data has been significantly improved, reducing the impact of data errors on subsequent business processing and analysis, enhancing the reliability and stability of the data management system, and providing strong data support for the smooth implementation and management of engineering projects.

[0101] In an optional embodiment of the present invention, in step 14, performing table name compliance verification on the first two-dimensional table structure data and the second two-dimensional table structure data in the table dimension according to the cost table verification rules further includes:

[0102] Step 145: Generate an error report with location information, where the error report marks the table number, row and column coordinates of the offending data and the violated rule entry.

[0103] In an optional embodiment of the present invention, in step 15, object-based storage of the first two-dimensional table structure data and the second two-dimensional table structure data that have passed verification includes:

[0104] The standardized two-dimensional table data sets (first two-dimensional table structure data and second two-dimensional table structure data) that have passed the above verification are stored in an object-based manner. Based on the established table-row-column coordinate index system, the two-dimensional table data is converted into business objects for persistent storage, supporting the structured reading operations of the cost document data in subsequent processes, so as to facilitate subsequent analysis and processing of the data.

[0105] In this embodiment, the error report marks the table number, row and column coordinates of the offending data, allowing technical or business personnel to quickly and accurately locate the problematic data. When processing large-scale engineering cost data, faced with numerous tables and data items, quickly locating erroneous data can greatly save time in troubleshooting and improve work efficiency. For example, if a compliance issue is discovered in a table name, the location information in the report can directly find the corresponding table and specific location without having to check all the data one by one.

[0106] The error report also identifies the rule entries that were violated, allowing relevant personnel to clearly understand the specific reasons for the data violations. In engineering cost data management, verification rules are often complex and diverse. Identifying the reasons for violations helps staff accurately understand the problem and make targeted data corrections. For example, if a table name violates a specific naming format rule, the rule entry prompt in the report will allow staff to immediately know and make modifications according to the rules, avoiding blind guesswork and repeated attempts.

[0107] By combining the location of erroneous data and the cause of the violation, staff can more efficiently perform data corrections. By being able to directly identify problematic data and clearly identify the problem, the uncertainty and trial-and-error costs involved in the correction process are reduced, thereby accelerating data corrections and improving the timeliness of data processing. This is crucial for ensuring the quality and availability of construction cost data, ensuring that subsequent data processing and analysis are based on accurate and compliant data.

[0108] Generating error reports with location information facilitates data quality traceability. Throughout the lifecycle of an engineering cost project, data quality may require multiple inspections and assessments. Saving these error reports allows you to review past data issues and their resolutions in subsequent work, helping you learn from past experiences, refine data management processes and validation rules, and further improve data quality.

[0109] Example 1

[0110] like Figure 2 As shown, the architecture of the method for storing and processing engineering cost data includes:

[0111] Project cost documents, which serve as the initial input for the entire process and include various documents related to project cost data;

[0112] A heterogeneous file parser, comprising a heterogeneous file adapter and a data format converter,

[0113] The heterogeneous file adapter is responsible for identifying proprietary formats of engineering cost files in different formats, such as xls / xlsx, bwbd7, bwsd7, and BJS2, to achieve compatible processing of heterogeneous file formats; the data format converter converts the contents of engineering cost files in different formats into a processable data format to prepare for subsequent steps;

[0114] Parsing rule configuration, which provides the heterogeneous file parser with the rules required for parsing, and guides the heterogeneous file adapter and data format converter to correctly process the file;

[0115] Dynamic verification engine, the dynamic verification engine includes a rule loader and a verification executor,

[0116] The rule loader loads the cost table verification rule content, such as obtaining relevant rules from the parsing rule configuration; the verification executor verifies the converted data in the table-row-column dimension based on the loaded rules, such as checking the compliance of the table name, the integrity of the row data, and the standardization of the column data;

[0117] Cost document data conversion, including cost document data structured storage,

[0118] The structured storage of cost file data converts the verified engineering cost data into a standard two-dimensional table structure data set and stores it for easy management and analysis;

[0119] Customized extended parameters, including form generator and data item parameter associator,

[0120] The form generator generates a corresponding form based on the processed data; the data item parameter associator realizes parameter association between data items to meet specific business needs.

[0121] Standardized two-dimensional table data sets that have passed the aforementioned validation are stored as objects. Based on the established table-row-column coordinate indexing system, the two-dimensional table data is converted into business objects for persistent storage. This supports structured read operations on cost document data in subsequent processes, facilitating subsequent data analysis and processing. Compared to traditional fragmented data storage methods, structured storage can significantly improve data retrieval efficiency and reduce data management costs.

[0122] The form generator within the custom extended parameters generates forms based on processed data, while the data item parameter associator associates parameters between data items. Supporting six types of interactive data item definitions, it flexibly adapts to different project types and business needs. This not only reduces the response time for business rule updates from weeks to hours, but also enables the construction of a traceable data lineage map, significantly enhancing system scalability and business agility.

[0123] When querying, it is possible to obtain standard two-dimensional table data and extended parameter data at the same time, avoiding multiple queries or data association operations, providing a one-stop solution for reading engineering file data, meeting the engineering personnel's needs for data comprehensiveness and relevance, and improving data analysis and decision-making efficiency.

[0124] The present invention avoids manual intervention in data analysis by acquiring and converting multi-format engineering cost documents, changes inefficiency, realizes efficient integration of data in different formats, and significantly improves data analysis efficiency. Based on the standard two-dimensional table structure and table-row-column dimension verification, it can more comprehensively process multi-dimensional cost indicators, flexibly deal with complex business logic such as cross-table reference verification and unit conversion fault tolerance, and has strong adaptability. Object-oriented storage decouples business rules from the code layer. When adapting to new specifications, there is no need to make large-scale changes to the code architecture. Only the data processing logic and verification rules need to be adjusted, and the response speed is fast.

[0125] Clearly obtain specific format files (xls / xlsx, bwbd7, bwsd7, BJS2, etc.) to make subsequent processing steps more targeted, facilitate the formulation of strategies based on format characteristics, standardize and normalize data processing processes, improve efficiency and accuracy, and facilitate system maintenance and upgrades.

[0126] The heterogeneous file adapter quickly and accurately identifies the proprietary formats of files of different formats. Based on the format feature structure matching rules, it avoids the tedious and error-prone problems of manual identification, improves the efficiency and accuracy of identification, and lays a solid foundation for subsequent data processing; ensures the accuracy and consistency of the entire data processing process, and improves the quality of engineering cost data management.

[0127] Use the corresponding parsing tools to read the content of files in different formats, and take advantage of the tools to avoid data loss or reading errors, providing a complete and accurate data foundation for subsequent processing. Extract key data of engineering cost from the parsed files, remove irrelevant information, improve data processing efficiency and accuracy, and focus on core cost data. Convert cost data in different formats into standardized two-dimensional table data to facilitate sorting, screening, statistics and other operations, facilitate comparison and integration of data from different sources, and improve the flexibility and versatility of data processing. Fill data into a data set according to the standard two-dimensional table structure, so that the data is orderly and standardized, easy to manage and maintain, and provide a good foundation for data verification and storage, ensuring data consistency and integrity. Establish a coordinate index system for the cells of the two-dimensional table to quickly locate data, meet the needs of rapid response and real-time analysis of large-scale cost data, and improve data processing speed and performance.

[0128] Obtain the content of the set verification rules to make the verification work more targeted, accurately identify and correct data problems, and improve the effectiveness of verification. The table dimension verifies the compliance of the table name to avoid data search and management problems caused by confusion in table names. The row dimension checks the integrity of the data to avoid missing information fields so that the data fully reflects the project cost. The column dimension verifies the standardization of the data to ensure that the format, value range, etc. meet the standards to avoid calculation and analysis deviations. Comprehensive multi-dimensional verification thoroughly checks and corrects data problems, controls the quality of all aspects of the data, and provides strong support for project cost analysis decisions. Dimensional verification makes data problem positioning clear and accurate, improves data processing efficiency, and reduces repair time and cost. Strictly verified data reduces system errors and anomalies, ensures the normal operation of the system, and improves service quality and user satisfaction.

[0129] Use regular expressions to match table name format specifications to ensure that the character composition and length of table names comply with regulations, making data storage and management standardized and orderly. Identify table types through fuzzy semantic analysis to avoid mismatches between table names and content, and improve data readability and comprehensibility. Use reflection mechanisms to dynamically call verification methods to adapt to different row data structures and comprehensively test data integrity. Validate numerical ranges to avoid calculation errors caused by incorrect numerical values; detect consistency of measurement units to prevent unit confusion; and determine business logic compliance to ensure that data complies with business rules, providing a reliable basis for decision-making. Multi-dimensional and detailed verification can deeply discover and correct data problems, improve data compliance, integrity, and standardization, and enhance the reliability and stability of the data management system.

[0130] Marking the table number and row and column coordinates of offending data allows for quick identification of problematic data, saving troubleshooting time and improving work efficiency. Marking the violated rule entries allows staff to clearly identify the problem and make targeted data corrections. Combining location and cause reduction reduces correction uncertainty and trial-and-error costs, speeding up data corrections and ensuring data quality availability. This facilitates data quality traceability, allowing users to review issues and their resolutions, drawing on experience to improve management processes and rules.

[0131] like Figure 3 As shown, in an embodiment of the present invention, a device 30 for storing and processing construction cost data includes:

[0132] An acquisition module 30 is configured to acquire at least one first engineering cost file in a table format and at least one second engineering cost file in a proprietary format output by engineering cost software;

[0133] The processing module 31 is used to convert at least one first engineering cost file into first two-dimensional table structure data; convert at least one second engineering cost file into second two-dimensional table structure data through middleware; the first two-dimensional table structure data and the second two-dimensional table structure data are both data tables in standard table format; establish a table-row-column coordinate index system based on the first two-dimensional table structure data and the second two-dimensional table structure data; perform table-row-column dimension verification on the first two-dimensional table structure data and the second two-dimensional table structure data; and object-store the first two-dimensional table structure data and the second two-dimensional table structure data that have passed the verification.

[0134] Optionally, the first project cost file includes: a project cost file in xls / xlsx format;

[0135] The second engineering cost file includes: an engineering cost file in the bwbd7, bwsd7 and / or BJS2 proprietary format output by the engineering cost software.

[0136] Optionally, converting at least one first project cost file into first two-dimensional table structure data includes:

[0137] Parsing the rows, columns, and elements of the at least one first engineering cost file to obtain a first table element, wherein the first table element includes: multi-dimensional indicators of the first engineering cost file;

[0138] The first table element is mapped to the data table in the standard table format to obtain first two-dimensional table structure data.

[0139] Optionally, converting the at least one second project cost file into second two-dimensional table structure data through middleware includes:

[0140] Performing binary analysis on at least one second project cost file through the middleware to obtain a binary report file in a table format;

[0141] Parsing the rows, columns, and elements of the binary report file to obtain a second table element, wherein the second table element includes: multi-dimensional indicators of the second engineering cost file;

[0142] The second table element is mapped to the data table in the standard table format to obtain second two-dimensional table structure data.

[0143] Optionally, performing table-row-column dimension verification on the first two-dimensional table structure data and the second two-dimensional table structure data includes:

[0144] Get the set cost table verification rule content;

[0145] According to the cost table verification rules, performing table name compliance verification on the first two-dimensional table structure data and the second two-dimensional table structure data in the table dimension;

[0146] Performing data integrity verification on the first two-dimensional table structure data and the second two-dimensional table structure data in the row dimension according to the cost table verification rule content;

[0147] According to the cost table verification rule content, data standardization verification is performed on the first two-dimensional table structure data and the second two-dimensional table structure data in the column dimension.

[0148] Optionally, performing table name compliance verification on the first two-dimensional table structure data and the second two-dimensional table structure data in the table dimension according to the cost table verification rule content includes:

[0149] Use regular expressions to match table names to see if they conform to the set format specifications;

[0150] Identify table types through fuzzy semantic analysis and determine whether the table name semantically meets the set requirements;

[0151] The performing of data integrity verification on the first two-dimensional table structure data and the second two-dimensional table structure data in the row dimension according to the cost table verification rules includes:

[0152] Use the reflection mechanism to dynamically call the preset verification method to check whether the row data is missing or incomplete;

[0153] The performing of data standardization verification on the first two-dimensional table structure data and the second two-dimensional table structure data in the column dimension according to the cost table verification rules includes:

[0154] Perform column value range validation, measurement unit consistency detection, and business logic compliance judgment.

[0155] Optionally, performing table name compliance verification on the first two-dimensional table structure data and the second two-dimensional table structure data in the table dimension according to the cost table verification rule content further includes:

[0156] An error report with positioning information is generated, wherein the error report marks the table number, row and column coordinates of the illegal data and the violated rule entry.

[0157] It should be noted that the device is a device corresponding to the above method, and all implementation methods in the above method embodiments are applicable to the embodiments of the device and can achieve the same technical effects.

[0158] An embodiment of the present invention further provides a computing device, comprising:

[0159] one or more processors;

[0160] The storage device is used to store one or more programs, and when the one or more programs are executed by the one or more processors, the one or more processors implement the method as described above.

[0161] An embodiment of the present invention further provides a computing device readable storage medium storing instructions that, when executed on a computing device, cause the computing device to execute the method described above. All implementations in the above method embodiments are applicable to this embodiment and can achieve the same technical effects.

[0162] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed in the present invention can be implemented in electronic hardware, or a combination of computing device software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professionals and technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the present invention.

[0163] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0164] In the embodiments provided by the present invention, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed can be through some interface, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0165] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0166] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0167] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a storage medium readable by a computing device. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computing device software product is stored in a storage medium and includes a number of instructions for enabling a computing device (which can be a personal computing device, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes various media that can store program code, such as a USB flash drive, a mobile hard disk, ROM, RAM, a magnetic disk, or an optical disk.

[0168] In addition, it should be noted that, in the apparatus and method of the present invention, it is obvious that each component or each step can be decomposed and / or recombined. These decompositions and / or recombinations should be regarded as equivalent schemes of the present invention. Moreover, the steps of performing the above-mentioned series of processing can naturally be performed in chronological order according to the order of description, but it is not necessary to perform them in chronological order, and some steps can be performed in parallel or independently of each other. For those of ordinary skill in the art, it will be understood that all or any steps or components of the method and apparatus of the present invention can be implemented in any computing device (including processors, storage media, etc.) or a network of computing devices in hardware, firmware, software or a combination thereof, which can be achieved by those of ordinary skill in the art using their basic programming skills after reading the description of the present invention.

[0169] Therefore, the purpose of the present invention can also be achieved by running a program or a group of programs on any computing device. The computing device can be a well-known general-purpose device. Therefore, the purpose of the present invention can also be achieved simply by providing a program product containing program code that implements the method or device. That is to say, such a program product also constitutes the present invention, and the storage medium storing such a program product also constitutes the present invention. Obviously, the storage medium can be any well-known storage medium or any storage medium developed in the future. It should also be pointed out that in the device and method of the present invention, it is obvious that each component or each step can be decomposed and / or recombined. These decompositions and / or recombinations should be regarded as equivalent schemes of the present invention. In addition, the steps of performing the above-mentioned series of processing can naturally be performed in chronological order according to the order of description, but do not necessarily need to be performed in chronological order. Certain steps can be performed in parallel or independently of each other.

[0170] The above is a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications should also be regarded as within the scope of protection of the present invention.

Claims

1. A method for storing and processing engineering cost data, characterized in that: include: Acquire at least one first engineering cost file in a table format and at least one second engineering cost file in a proprietary format output by engineering cost software; Converting at least one first project cost file into first two-dimensional table structure data; Converting at least one second engineering cost file into second two-dimensional table structure data through the middleware; Both the first two-dimensional table structure data and the second two-dimensional table structure data are data tables in a standard table format; Establishing a table-row-column coordinate index system based on the first two-dimensional table structure data and the second two-dimensional table structure data; Performing table-row-column dimension verification on the first two-dimensional table structure data and the second two-dimensional table structure data; The first two-dimensional table structure data and the second two-dimensional table structure data that have passed verification are stored in an object-based manner.

2. The method for storing and processing construction cost data according to claim 1, characterized in that: The first engineering cost file includes: an engineering cost file in xls / xlsx format; The second engineering cost file includes: an engineering cost file in the bwbd7, bwsd7 and / or BJS2 proprietary format output by the engineering cost software.

3. The method for storing and processing construction cost data according to claim 2, characterized in that: The converting of at least one first project cost file into first two-dimensional table structure data includes: Parsing the rows, columns, and elements of the at least one first engineering cost file to obtain a first table element, wherein the first table element includes: multi-dimensional indicators of the first engineering cost file; The first table element is mapped to the data table in the standard table format to obtain first two-dimensional table structure data.

4. The method for storing and processing construction cost data according to claim 1, characterized in that: The converting of at least one second project cost file into second two-dimensional table structure data through the middleware includes: Performing binary analysis on at least one second project cost file through the middleware to obtain a binary report file in a table format; Parsing the rows, columns, and elements of the binary report file to obtain a second table element, wherein the second table element includes: multi-dimensional indicators of the second engineering cost file; The second table element is mapped to the data table in the standard table format to obtain second two-dimensional table structure data.

5. The method for storing and processing construction cost data according to claim 1, characterized in that: The performing table-row-column dimension verification on the first two-dimensional table structure data and the second two-dimensional table structure data includes: Get the set cost table verification rule content; According to the cost table verification rules, performing table name compliance verification on the first two-dimensional table structure data and the second two-dimensional table structure data in the table dimension; Performing data integrity verification on the first two-dimensional table structure data and the second two-dimensional table structure data in the row dimension according to the cost table verification rule content; According to the cost table verification rule content, data standardization verification is performed on the first two-dimensional table structure data and the second two-dimensional table structure data in the column dimension.

6. The method for storing and processing construction cost data according to claim 5, characterized in that: The step of performing table name compliance verification on the first two-dimensional table structure data and the second two-dimensional table structure data in the table dimension according to the cost table verification rules includes: Use regular expressions to match table names to see if they conform to the set format specifications; Identify table types through fuzzy semantic analysis and determine whether the table name semantically meets the set requirements; The performing of data integrity verification on the first two-dimensional table structure data and the second two-dimensional table structure data in the row dimension according to the cost table verification rules includes: Use the reflection mechanism to dynamically call the preset verification method to check whether the row data is missing or incomplete; The performing of data standardization verification on the first two-dimensional table structure data and the second two-dimensional table structure data in the column dimension according to the cost table verification rules includes: Perform column value range validation, measurement unit consistency detection, and business logic compliance judgment.

7. The method for storing and processing construction cost data according to claim 5, characterized in that: The step of performing table name compliance verification on the first two-dimensional table structure data and the second two-dimensional table structure data in the table dimension according to the cost table verification rules further includes: An error report with positioning information is generated, wherein the error report marks the table number, row and column coordinates of the illegal data and the violated rule entry.

8. A device for storing and processing engineering cost data, characterized in that: include: an acquisition module, configured to acquire at least one first engineering cost file in a table format and at least one second engineering cost file in a proprietary format output by engineering cost software; A processing module, configured to convert at least one first project cost file into first two-dimensional table structure data; Converting at least one second engineering cost file into second two-dimensional table structure data through the middleware; The first two-dimensional table structure data and the second two-dimensional table structure data are both data tables in a standard table format; a table-row-column coordinate index system is established based on the first two-dimensional table structure data and the second two-dimensional table structure data; Performing table-row-column dimension verification on the first two-dimensional table structure data and the second two-dimensional table structure data; The first two-dimensional table structure data and the second two-dimensional table structure data that have passed verification are stored in an object-based manner.

9. A computing device, characterized in that include: one or more processors; A storage device for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the method according to any one of claims 1 to 7.

10. A computing device readable storage medium, characterized in that: The computing device readable storage medium stores a program, which implements the method according to any one of claims 1 to 7 when executed by a processor.

Images