CN113988003A - Method for custom directional analysis of multiple sheet contents of Excel file according to specified configuration - Google Patents
Method for custom directional analysis of multiple sheet contents of Excel file according to specified configuration Download PDFInfo
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- CN113988003A CN113988003A CN202111341318.2A CN202111341318A CN113988003A CN 113988003 A CN113988003 A CN 113988003A CN 202111341318 A CN202111341318 A CN 202111341318A CN 113988003 A CN113988003 A CN 113988003A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F40/00—Handling natural language data
- G06F40/10—Text processing
- G06F40/103—Formatting, i.e. changing of presentation of documents
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/28—Databases characterised by their database models, e.g. relational or object models
- G06F16/284—Relational databases
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F40/00—Handling natural language data
- G06F40/10—Text processing
- G06F40/12—Use of codes for handling textual entities
- G06F40/151—Transformation
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F40/00—Handling natural language data
- G06F40/10—Text processing
- G06F40/166—Editing, e.g. inserting or deleting
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F40/00—Handling natural language data
- G06F40/10—Text processing
- G06F40/166—Editing, e.g. inserting or deleting
- G06F40/177—Editing, e.g. inserting or deleting of tables; using ruled lines
- G06F40/18—Editing, e.g. inserting or deleting of tables; using ruled lines of spreadsheets
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F40/00—Handling natural language data
- G06F40/20—Natural language analysis
- G06F40/205—Parsing
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F8/00—Arrangements for software engineering
- G06F8/30—Creation or generation of source code
- G06F8/38—Creation or generation of source code for implementing user interfaces
Abstract
The invention discloses a method for custom directional analysis of multiple sheet contents of an Excel file according to specified configuration, which comprises the following steps: compiling a JSON format analysis configuration file; reading an analysis configuration file in a JSON format, and storing the analysis configuration file in a Java set object; reading all contents of the excel file and storing the contents in a Java set object; and analyzing and converting the excel file content into a Java set object according to the analysis rule. The method can read various data table data from an excel sheet on the premise of ensuring the data integrity, the read data has the database table name and the field name, and the required sql statement can be directly assembled subsequently, so that a convenient and efficient analysis function is provided for the data import function of the system.
Description
Technical Field
The invention relates to the technical field of web services, in particular to a method for custom directional analysis of multiple sheet contents of an Excel file according to specified configuration.
Background
In a software system, a plurality of systems have one function, namely excel file import or batch import, so that the aim of filling a large amount of data into a database through a page is fulfilled. Because of the functional difference of each module and the entity difference of the database in each system, each imported place needs to be coded again to complete the corresponding analysis function and write the analysis function into the database. This results in similar work being repeated. If the system needs to be slightly modified, the system code modification is needed, and the system is stopped due to updating and upgrading.
Disclosure of Invention
The invention provides a method for custom directional analysis of multiple sheet contents of an Excel file according to specified configuration, which aims to solve the problem of repeated development of Excel analysis in the prior art and achieve the purposes of universal, expandable, customizable and high-multiplexing Excel analysis by analyzing a configuration file. According to the method, the excel table data are directionally analyzed by reading the analysis rule and are converted into Java set objects, so that the data can be conveniently stored in a database and used in other ways. The key point is that the analysis of excel data can be customized and can be modified after being customized without modifying codes.
The technical scheme adopted by the invention is as follows: the method for custom directional analysis of multiple sheet contents of an Excel file according to specified configuration is characterized by comprising the following steps:
s1: compiling a JSON format analysis configuration file;
s2: reading an analysis configuration file in a JSON format, and storing the analysis configuration file in a Java set object;
s3: reading all contents of the excel file and storing the contents in a Java set object;
s4: and analyzing and converting the excel file content into a Java set object according to the analysis rule.
As a preferred mode of a method for custom-directed parsing of a plurality of sheet contents of an Excel file according to specified configuration, the JSON-format parsing configuration file comprises:
an application name for distinguishing modules in the system;
numbering Excel file sheets from 1 by default;
one or more table configurations corresponding to the analyzed result;
the table configuration corresponding to the result comprises a table name and field configuration;
the field configuration includes the field name, type, number of columns in excel (numbering from 0), and formatting pattern (field type is used when time).
As a preferred mode of a method for custom directional analysis of multiple sheet contents of an Excel file according to a specified configuration, in S1, a corresponding relationship exists in the configuration, which is specifically as follows:
the method comprises the steps that a sheet number of an excel file in an application name corresponds to a group of configurations;
the group of configurations comprises a plurality of table configurations corresponding to different analysis results;
a table contains a plurality of fields;
the table name is the name or the custom name of the database table, but can not be null;
the name of the field is the field name or custom name of the database table.
As a preferred mode of the method for custom directed parsing of multiple sheet contents of an Excel file according to a specified configuration, the implementation step of S2 includes:
s2.1: reading the content of the JSON file on the disk, and formatting the content into a JSON object;
s2.2: taking out the unresolved configuration group;
s2.2: reading the application name, the sheet number of the excel file and the table configuration corresponding to the result;
s2.3: taking out table configuration corresponding to the result in the unresolved configuration group;
s2.4: reading a form name and field configuration;
s2.5: extracting the configuration of the unresolved field, resolving the configuration of the field, and storing the configuration of the resolved field into a Java set object;
s2.6: the table configuration is stored in a Java set object;
s2.7: repeating the steps S2.4-S2.7;
s2.8: storing the configuration group into a Java set object;
s2.9: and repeating the steps S2.2-S2.9.
As a preferred mode of the method for custom directed parsing of multiple sheet contents of an Excel file according to a specified configuration, the implementation step of S4 includes:
s4.1: taking out unanalyzed sheet table data of excel;
s4.2: acquiring a corresponding configuration group according to the application name and the sheet number of the excel, and repeating the step S4.1 if the configuration group is not acquired;
s4.3: taking out a line of data of the sheet of the unresolved excel;
s4.4: taking out the table configuration, and reading the table name;
s4.5: taking out field configuration, excel column number, field name, field type and excel column value;
s4.6: field value formatting, if the field value is of a time type, converting the field value into the time type by using pattern formatting;
s4.7: storing the field data into a Java set object;
s4.8: repeating the steps S4.5-S4.7;
s4.9: storing table data into a Java set object;
s4.10: repeating the steps S4.2-S4.9;
s4.11: storing data into a Java set object;
s4.12: steps S4.1-S4.11 are repeated.
The invention has the beneficial effects that:
1) the method can read various data table data from an excel sheet on the premise of ensuring the data integrity, the read data has the database table name and the field name, and the required sql statement can be directly assembled subsequently, so that a convenient and efficient analysis function is provided for the data import function of the system.
2) Multiple applications (modules) are supported to use the same configuration file.
3) The table data in one sheet of one excel can be split and correspond to a plurality of table data objects.
4) Fields of the parsed target object may correspond to database table fields.
5) The analyzed target object has the name of the database table, so that the SQL sentence can be conveniently and quickly generated subsequently.
6) The time field may customize the formatting scheme.
7) The number of code modifications is reduced.
8) In a specific system, a page can be developed to provide a configuration file editing page, and user-defined configuration oriented analysis is realized.
Drawings
FIG. 1 is a schematic flow diagram of a method for custom directional analysis of multiple sheet contents of an Excel file according to a specified configuration, which is disclosed by the invention.
Fig. 2 is an example json profile structure for displaying a complete excel.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention clearer, the present invention will be described in further detail below with reference to the accompanying drawings, but embodiments of the present invention are not limited thereto.
Example 1:
referring to fig. 1, the implementation discloses a method for custom directional analysis of multiple sheet contents of an Excel file according to a specified configuration, which specifically includes the following contents:
example background: in a system a, the user exports data on the system page, and now the data needs to be stored in the database of the system B. The exported file is excel.
Preparation work: and compiling a json configuration file according to the database table design of the system B, and placing the edited file at a disk position which can be accessed and read by the system B. The contents of the Json profile are such that:
[{"appName":"1","sheetNo":"1","tables":[{"tableName":"F16","columns":[{"colName":"A0100","type":"String","excelColNum":"0"},{"colName":"F1601","type":"Date","excelColNum":"13"},{"colName":"F1602","type":"String","excelColNum":"9"},{"colName":"F1603","type":"String","excelColNum":"10"},{"colName":"F1604","type":"String","excelColNum":"11"},{"colName":"F1606","type":"Date","excelColNum":"7"},{"colName":"F1607","type":"String","excelColNum":"5"},{"colName":"tc_full_name","type":"String","excelColNum":"1"},{"colName":"tc_source_org_id","type":"String","excelColNum":"2"},{"colName":"tc_target_org_id","type":"String","excelColNum":"4"},{"colName":"tc_source_org_name","type":"String","excelColNum":"3"},{"colName":"tc_id_card_no","type":"String","excelColNum":"6"}]}]},{"appName":"1","sheetNo":"2","tables":[{"tableName":"F13","columns":[{"colName":"A0100","type":"String","excelColNum":"0"},{"colName":"F1300","type":"String","excelColNum":"1"},{"colName":"F1301","type":"String","excelColNum":"2"},{"colName":"F1302","type":"String","excelColNum":"3"},{"colName":"F1303","type":"String","excelColNum":"4"},{"colName":"F1304","type":"String","excelColNum":"5"},{"colName":"F1305","type":"String","excelColNum":"6"},{"colName":"F1306","type":"String","excelColNum":"7"},{"colName":"F1307","type":"String","excelColNum":"8"},{"colName":"F1308","type":"String","excelColNum":"9"},{"colName":"F1309","type":"Date","excelColNum":"10"},{"colName":"F1310","type":"String","excelColNum":"11"},{"colName":"F1311","type":"Date","excelColNum":"12"},{"colName":"F1320","type":"String","excelColNum":"13"},{"colName":"F1321","type":"String","excelColNum":"14"},{"colName":"F1322","type":"String","excelColNum":"15"},{"colName":"F1323","type":"String","excelColNum":"16"},{"colName":"F1324","type":"String","excelColNum":"17"},{"colName":"F1325","type":"String","excelColNum":"18"},{"colName":"f13a1","type":"String","excelColNum":"19"}]}]},{"appName":"2","sheetNo":"1","tables":[{"tableName":"F15","columns":[{"colName":"A0100","type":"String","excelColNum":"0"},{"colName":"F1501","type":"Date","excelColNum":"1"},{"colName":"F1502","type":"String","excelColNum":"2"},{"colName":"F1503","type":"String","excelColNum":"3"},{"colName":"F1504","type":"String","excelColNum":"4"},{"colName":"F1505","type":"String","excelColNum":"5"},{"colName":"F1506","type":"Date","excelColNum":"6"},{"colName":"F1507","type":"String","excelColNum":"7"},{"colName":"F1509","type":"String","excelColNum":"8"}]},{"tableName":"A01","columns":[{"colName":"A0100","type":"String","excelColNum":"0"},{"colName":"A0101","type":"String","excelColNum":"9"},{"colName":"A0102","type":"String","excelColNum":"14"},{"colName":"A0103","type":"String","excelColNum":"15"},{"colName":"A0104","type":"String","excelColNum":"16"},{"colName":"A0106","type":"String","excelColNum":"17"},{"colName":"A0107","type":"Date","excelColNum":"18"},{"colName":"A0111","type":"String","excelColNum":"19"},{"colName":"A0112","type":"String","excelColNum":"20"},{"colName":"A0114","type":"String","excelColNum":"21"},{"colName":"A0117","type":"String","excelColNum":"22"},{"colName":"A0121","type":"String","excelColNum":"23"},{"colName":"A0131","type":"String","excelColNum":"24"},{"colName":"A0134","type":"Date","excelColNum":"25"},{"colName":"A0135","type":"String","excelColNum":"26"},{"colName":"A0151","type":"String","excelColNum":"27"},{"colName":"A0181","type":"String","excelColNum":"28"},{"colName":"A0184","type":"String","excelColNum":"10"},{"colName":"A0187","type":"String","excelColNum":"29"},{"colName":"A01A1","type":"String","excelColNum":"30"},{"colName":"A01A2","type":"String","excelColNum":"31"},{"colName":"A0221","type":"String","excelColNum":"32"},{"colName":"A0302","type":"String","excelColNum":"33"},{"colName":"A0801","type":"String","excelColNum":"34"},{"colName":"A0802","type":"String","excelColNum":"35"},{"colName":"AT001","type":"String","excelColNum":"11"},{"colName":"D0100","type":"String","excelColNum":"12"},{"colName":"tc_org_name","type":"String","excelColNum":"13"},{"colName":"A01Z2","type":"String","excelColNum":"36"}]},{"tableName":"C02","columns":[{"colName":"A0100","type":"String","excelColNum":"0"},{"colName":"C0201","type":"String","excelColNum":"37"},{"colName":"C0203","type":"Date","excelColNum":"38"},{"colName":"C0204","type":"String","excelColNum":"39"},{"colName":"C0205","type":"Date","excelColNum":"40"},{"colName":"C0207","type":"String","excelColNum":"41"},{"colName":"C0212","type":"String","excelColNum":"42"},{"colName":"C0213","type":"String","excelColNum":"43"},{"colName":"C0214","type":"Date","excelColNum":"44"},{"colName":"C0217","type":"String","excelColNum":"45"}]}]},{"appName":"2","sheetNo":"2","tables":[{"tableName":"E21","columns":[{"colName":"A0100","type":"String","excelColNum":"0"},{"colName":"D0100","type":"String","excelColNum":"1"},{"colName":"E07ID","type":"String","excelColNum":"2"},{"colName":"E2100","type":"String","excelColNum":"3"},{"colName":"E2102","type":"String","excelColNum":"4"},{"colName":"E2103","type":"String","excelColNum":"5"},{"colName":"E2104","type":"String","excelColNum":"6"},{"colName":"E2105","type":"String","excelColNum":"7"},{"colName":"E2106","type":"String","excelColNum":"8"},{"colName":"E2107","type":"String","excelColNum":"9"},{"colName":"E2109","type":"String","excelColNum":"10"},{"colName":"E2110","type":"String","excelColNum":"11"},{"colName":"E2111","type":"String","excelColNum":"12"},{"colName":"E2112","type":"String","excelColNum":"13"},{"colName":"E2113","type":"String","excelColNum":"14"},{"colName":"E2114","type":"String","excelColNum":"15"},{"colName":"E2115","type":"String","excelColNum":"16"},{"colName":"E2117","type":"String","excelColNum":"17"},{"colName":"E2118","type":"String","excelColNum":"18"},{"colName":"E2121","type":"String","excelColNum":"19"},{"colName":"E2122","type":"String","excelColNum":"20"},{"colName":"E2154","type":"String","excelColNum":"21"},{"colName":"E2155","type":"String","excelColNum":"22"},{"colName":"E2156","type":"String","excelColNum":"23"},{"colName":"E2157","type":"String","excelColNum":"2"},{"colName":"E2161","type":"String","excelColNum":"24"},{"colName":"E21M1","type":"String","excelColNum":"25"},{"colName":"E21M2","type":"String","excelColNum":"26"}]}]}]
in the configuration 2 modules of system B are defined, module 1 and module 2 respectively.
The module 1 respectively analyzes data corresponding to a sheet with a sheet name of F16 from a sheet with an excel file index of 1, and analyzes data corresponding to a sheet with a sheet name of F13 from a sheet with an excel file index of 2, wherein the sheet field name is self-defined and is not a database table field beginning with 'tc _'.
The module 2 analyzes data corresponding to the tables with the table names of F15, A01 and C02 from the sheet with the excel file index of 1, and analyzes data corresponding to the table with the table name of E21 from the sheet with the excel file index of 2, wherein the table field name is self-defined and is not a database table field beginning with 'tc _'.
The json profile is stored in the code project tracking directory of system B. So that system B can read normally.
Transforming an uploading import interface to finish the oriented analysis of the content data of the excel file;
an uploading import interface is modified, and a parameter appName is added to distinguish which module the uploaded file belongs to;
and after the second process flow of the uploading file is read through the uploading input interface, converting the stream data into a Java object and storing the Java object into a Java set object. When the excel file is read, only the sheet with the required index of 1 and the sheet with the required index of 2 are read.
Referring to fig. 2, fig. 2 is a json profile structure example for displaying a complete excel. Calling the configuration file analysis method provided by the invention, reading the json configuration file, and storing the analysis configuration in the Java set object. The reference codes for the analytical method are as follows:
and sequentially reading the unanalyzed sheet data of the excel file, inquiring corresponding configuration data in the configuration information set by taking the module name and the index number of the sheet as a key, and exiting the cycle and entering the next cycle if the configuration data is not inquired. And when the configuration information is acquired, analyzing the excel data according to the configuration information, and storing the excel data into the Java set object after analysis.
A general method for parsing a single line of data according to configuration information may refer to the following writing:
through the steps, multiple sheets in one excel file are subjected to custom directional analysis into a format of multiple rows of table data corresponding to the table name through a json format configuration file. By the mode, even if the name, number and type of the table name or the table field need to be modified, the analysis code does not need to be modified, and the purposes of high expansibility and high reusability are really achieved.
The above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (5)
1. A method for custom directional analysis of multiple sheet contents of an Excel file according to specified configuration is characterized by comprising the following steps:
s1: compiling a JSON format analysis configuration file;
s2: reading an analysis configuration file in a JSON format, and storing the analysis configuration file in a Java set object;
s3: reading all contents of the excel file and storing the contents in a Java set object;
s4: and analyzing and converting the excel file content into a Java set object according to the analysis rule.
2. The method for custom directed parsing of multiple sheet contents of an Excel file according to specified configuration according to claim 1, wherein the parsing configuration file in JSON format comprises:
an application name for distinguishing modules in the system;
numbering Excel file sheets from 1 by default;
one or more table configurations corresponding to the analyzed result;
the table configuration corresponding to the result comprises a table name and field configuration;
and field configuration, including field name, type, column number in excel and formatting pattern.
3. The method for custom directional analysis of multiple sheet contents of an Excel file according to specified configuration according to claim 1, wherein in S1, there is a corresponding relationship in configuration, specifically as follows:
the method comprises the steps that a sheet number of an excel file in an application name corresponds to a group of configurations;
the group of configurations comprises a plurality of table configurations corresponding to different analysis results;
a table contains a plurality of fields;
the table name is the name or the custom name of the database table, but can not be null;
the name of the field is the field name or custom name of the database table.
4. The method for custom directed parsing of multiple sheet contents of an Excel file according to specified configuration according to claim 3, wherein the step of implementing S2 comprises:
s2.1: reading the content of the JSON file on the disk, and formatting the content into a JSON object;
s2.2: taking out the unresolved configuration group;
s2.2: reading the application name, the sheet number of the excel file and the table configuration corresponding to the result;
s2.3: taking out table configuration corresponding to the result in the unresolved configuration group;
s2.4: reading a form name and field configuration;
s2.5: extracting the configuration of the unresolved field, resolving the configuration of the field, and storing the configuration of the resolved field into a Java set object;
s2.6: the table configuration is stored in a Java set object;
s2.7: repeating the steps S2.4-S2.7;
s2.8: storing the configuration group into a Java set object;
s2.9: and repeating the steps S2.2-S2.9.
5. The method for custom directed parsing of multiple sheet contents of an Excel file according to specified configuration according to claim 4, wherein the step of implementing S4 comprises:
s4.1: taking out unanalyzed sheet table data of excel;
s4.2: acquiring a corresponding configuration group according to the application name and the sheet number of the excel, and repeating the step S4.1 if the configuration group is not acquired;
s4.3: taking out a line of data of the sheet of the unresolved excel;
s4.4: taking out the table configuration, and reading the table name;
s4.5: taking out field configuration, excel column number, field name, field type and excel column value;
s4.6: field value formatting, if the field value is of a time type, converting the field value into the time type by using pattern formatting;
s4.7: storing the field data into a Java set object;
s4.8: repeating the steps S4.5-S4.7;
s4.9: storing table data into a Java set object;
s4.10: repeating the steps S4.2-S4.9;
s4.11: storing data into a Java set object;
s4.12: steps S4.1-S4.11 are repeated.
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| CN117787251A (en) * | 2024-02-28 | 2024-03-29 | 江苏中威科技软件系统有限公司 | Method for combining or merging and reading EXCEL hidden contents by multi-format files |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117787251A (en) * | 2024-02-28 | 2024-03-29 | 江苏中威科技软件系统有限公司 | Method for combining or merging and reading EXCEL hidden contents by multi-format files |
| CN117787251B (en) * | 2024-02-28 | 2024-05-07 | 江苏中威科技软件系统有限公司 | Method for combining or merging and reading EXCEL hidden contents by multi-format files |
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