CN110765129A - High-performance online expense settlement statistical method and device - Google Patents
High-performance online expense settlement statistical method and device Download PDFInfo
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Abstract
The invention discloses a high-performance online expense settlement statistical method and a high-performance online expense settlement statistical device, which comprise the following steps of: uploading the expense settlement Excel file to a server where a website is located through a Web browser; reading the content of the expense settlement Excel file at a server side; performing expense settlement Excel data structure design and organization on a server, and performing data statistics of 2 tables; the Web end analyzes and displays the data structure which is counted and completed by the server end; and the server side deletes the expense settlement Excel file. The invention aims to improve the working efficiency of an operator for determining Excel data with cost and complete more work in shorter time; meanwhile, the invention uses the B/S framework to get through the barrier of data exchange, improve the sharing degree of data and avoid the time consumption of file exchange and data transmission by using a medium or a transmission tool; the method can access through the webpage at any time, is simple and efficient, can be used at any time, and has no environmental limitation.
Description
Technical Field
The invention relates to the field of Excel, in particular to a high-performance online expense settlement statistical method and device.
Background
The traditional operation of the expense settlement Excel table is complex, a plurality of functions are not required to be completed by searching data and learning related operations for an operator just contacting Excel, the statistics of data with multiple data and fields is more complex, and the operator needs to perform complicated operations to process. Therefore, many operators cannot settle Excel operation, and cannot or cannot be finished quickly in a short time, and the progress and the efficiency of work are greatly influenced.
Disclosure of Invention
According to one aspect of the present invention, in order to solve the above technical problems, the technical solution adopted by the present invention is to provide a high-performance online expense settlement statistical method, which includes the following steps:
and 6, deleting the designated expense settlement dictionary table excel file and/or the cache file of the expense settlement data table excel file under the designated path of the server.
Further, in the high-performance online expense settlement statistical method of the present invention, the selecting an expense settlement dictionary table excel file in the WEB terminal in step 1 specifically means: selecting an expense settlement dictionary table excel file by using the file type of an input label in a Web end; the step of sending the key-value pairs to the server side means that the key-value pairs are sent to the server side through Ajax.
Further, in the high-performance online accounting statistical method of the present invention, the step 2 specifically includes: and the server receives the key-value pair transmitted by the Ajax of the client by using the HttpPostedFile () object of the C #, and appoints a path to store the key-value pair at the server by using a SaveAs method of the HttpPostedFile () object.
Further, in the high-performance online accounting statistical method of the present invention, step 3 specifically includes: when an online settlement accounting webpage of a client is opened, the client automatically sends an REST service request to a server, acquires the excel file names of the settlement accounting dictionary table contained in all key value pairs under the appointed path of the server, and then displays the excel file names of the settlement accounting dictionary table in the webpage by using a select tag.
Further, in the high-performance online settlement statistical method of the present invention, in step 4,
the uploading of the selected expense settlement data table excel file to the server specifically refers to the following steps: calling REST service to upload the selected expense settlement data table excel file to a server side;
the expense settlement Excel data statistics exe application program reads the corresponding expense settlement dictionary table Excel file and the content in the expense settlement data table Excel file, and the NPOI tool is used for reading the content.
Further, in the high-performance online cost settlement statistical method of the present invention,
the operation of the expense settlement Excel data statistics exe application program at the server terminal specifically comprises the following steps: running an expense settlement Excel data statistics exe application program at a server end by a start method of a Process object; the method comprises the following steps that for a request submitted by each client, an independent expense settlement Excel data statistics exe application program is respectively started;
further, in the high-performance online expense settlement statistical method of the present invention, in step 4, when reading the content, for the case that the classification names corresponding to a plurality of different economic classification codes in the expense settlement dictionary table excel file are the same, first traversing all data in the expense settlement dictionary table excel file recursively, changing the relationship of 1 to 1 classification name and economic classification code into the data relationship of 1 classification name to n economic classification codes, where n is a positive integer greater than 1, so as to simplify the data and reduce the data volume; secondly, arranging economic classification codes according to classification names, traversing an expense settlement data table excel file, sequentially grouping data records in the expense settlement data table excel file according to the values of 'economic classification' columns in the expense settlement data and storing the data records in a two-dimensional array according to the classification names, converting the two-dimensional array into a JSON format, and returning the JSON format to a client.
Further, in the high-performance online expense settlement statistical method of the present invention, in step 5, in the expense settlement data corresponding to the table display classification name dynamically created as a new floating display, each row displays the details of the expense use including year, month/day, voucher number, abstract, subject, economic classification, income, expenditure, borrowing and repayment.
Further, in the high-performance online accounting statistical method of the present invention, when the deletion is performed in step 6, the deletion is specifically performed by a delete method of a system.
According to another aspect of the present invention, to solve the technical problem, there is provided a high-performance online expense settlement statistic device, specifically a computer storage medium, having computer executable instructions stored therein, for implementing any one of the above-mentioned high-performance online expense settlement statistic methods.
The high-performance online expense settlement statistical method and device have the following beneficial effects: the Web end settlement Excel tool provided by the invention improves the sharing use degree of data, and avoids using a medium or a transmission tool to carry out file exchange; the Web system adopts a B/S (client/server) framework, can be used by multiple users when being installed once, avoids the complex operation of installation, is simple and efficient, can be used when being opened, and has no environmental limitation; the operating efficiency using NPOI tool code is faster than Excel tools, and NPOI tools do not require installation to deploy any Excel components. The method for automatically detecting and classifying the one-to-many data relation in the data dictionary comprises the following steps: aiming at the condition that a plurality of data classifications in a data dictionary table correspond to one data classification, the invention researches a recursive classification tree algorithm, simplifies a data structure, optimizes a data format, reduces data volume, solves the problems of large data volume transmitted by a server and a client, data redundancy, memory resource waste, low transmission efficiency and the like in the traditional method, and realizes automatic data relation detection and simple and convenient data statistical analysis.
Drawings
The invention will be further described with reference to the accompanying drawings and examples, in which:
FIG. 1 is a data representation diagram;
FIG. 2 is a flow chart of one embodiment of a high performance online cost resolution statistical method of the present invention;
FIG. 3 is a detailed flowchart of step 1 in FIG. 2;
FIG. 4 is a detailed flowchart of step 2 in FIG. 2;
FIG. 5 is a detailed flowchart of step 3 in FIG. 2;
FIG. 6 is a detailed flowchart of step 4 in FIG. 2;
FIG. 7 is a detailed flowchart of step 5 in FIG. 2
Fig. 8 is a detailed flowchart of step 6 in fig. 2.
Detailed Description
For a more clear understanding of the technical features, objects and effects of the present invention, embodiments of the present invention will now be described in detail with reference to the accompanying drawings.
The expense settlement dictionary table Excel file and the expense settlement data table Excel file used by the invention are Excel tables, and the Excel tables have two types:
dictionary table: the method comprises two columns of economic classification and classification name, wherein each row is a specific economic classification code and a corresponding classification name. A plurality of dictionary tables can be uploaded, and one of the dictionary tables can be selected by the Web terminal as the dictionary table used in the current calculation.
Data table: the included data columns are year, month/day, voucher number, summary, subject, economic category, income, expense, debit, and repayment, an example of which is shown below in fig. 1.
Referring to fig. 2, fig. 2 is a flow chart of an embodiment of the high performance online cost settlement statistical method of the present invention. In this embodiment, the high-performance online accounting statistical method of this embodiment includes the following steps:
Referring to fig. 3, fig. 3 is a detailed flowchart of step 1 in fig. 2, which specifically includes the following steps:
101. selecting a local expense settlement dictionary table Excel file (namely, the Excel file shown in FIG. 3) in a browser;
102. after the selection is finished, triggering an onchange method of the input;
103. converting the excel file of the local expense settlement dictionary table into a key-value pair through a FormData () object in an onchange method;
104. sending an Ajax request, and sending the key value pair to a server side;
105. and the server returns the state of the received file.
And 2, the server receives the key-value pair transmitted by the Ajax of the client by using the HttpPostedFile () object of the C #, and appoints a path to store the key-value pair at the server by using a SaveAs method of the HttpPostedFile () object.
Referring to fig. 4, fig. 4 is a specific flowchart of step 2 in fig. 2, which specifically includes the following steps:
201: the server receives the key value pair transmitted in the step 1;
202. judging whether the name of an excel file in a cost resolution dictionary table contained in a key value pair exists in a specified path or not, if so, explaining that the name is repeated, and processing the problem of name repetition at the moment, and then entering a step 203, for example, adding-1 or a copy and the like to the rear of the current file name, and if not, entering the step 203;
203. saving the key value pair in the appointed path of the server;
204. and returning a file saving result, such as whether the file is saved successfully or not.
And 3, when the online expense settlement statistical webpage of the client is opened, the client automatically sends an REST service request to the server, acquires the excel file names of the expense settlement dictionary table contained in all key value pairs under the appointed path of the server, and displays the excel file names of the expense settlement dictionary table in the webpage by using a select label. Referring specifically to fig. 5, fig. 5 is a specific flowchart of step 3 in fig. 2.
And 4, selecting a displayed name of the Excel file of the expense settlement dictionary table so as to determine the Excel file of the expense settlement dictionary table currently selected to be used, selecting an Excel file of the expense settlement data table at the client, calling REST service to upload the selected Excel file of the expense settlement data table to the server, running an expense settlement Excel data statistics Excel application program at the server by a Process object start method, taking the selected name of the Excel file of the expense settlement dictionary table and the uploaded name of the Excel file of the expense settlement data table as program starting parameters of the expense settlement Excel data statistics Excel application program, and reading the corresponding contents of the Excel file of the expense settlement dictionary table and the Excel file of the expense settlement data table by the expense settlement Excel application program by using an NPOI tool and returning the contents to the client. For the request submitted by each client, an independent expense settlement Excel data statistics exe application program is respectively started, so that the concurrency problem is solved. Referring specifically to fig. 6, fig. 6 is a specific flowchart of step 4 in fig. 2.
When content is read, aiming at the condition that classification names corresponding to a plurality of different economic classification codes in an excel file of a expense settlement dictionary table are the same, all data in the excel file of the expense settlement dictionary table are traversed through recursion, the relationship between 1 to 1 classification name and economic classification codes is changed into the data relationship between 1 classification name and n economic classification codes, and n is a positive integer greater than 1, so that the data is simplified and the data volume is reduced; secondly, arranging economic classification codes according to classification names, traversing an expense settlement data table excel file, sequentially grouping data records in the expense settlement data table excel file according to the values of 'economic classification' columns in the expense settlement data and storing the data records in a two-dimensional array according to the classification names, converting the two-dimensional array into a JSON format, and returning the JSON format to a client.
And 6, deleting the designated expense settlement dictionary table excel file and/or the cache file of the expense settlement data table excel file under the designated path of the server by a delete method of a System. Referring specifically to fig. 8, fig. 8 is a specific flowchart of step 6 in fig. 2.
While the present invention has been described with reference to the embodiments shown in the drawings, the present invention is not limited to the embodiments, which are illustrative and not restrictive, and it will be apparent to those skilled in the art that various changes and modifications can be made therein without departing from the spirit and scope of the invention as defined in the appended claims.
Claims (10)
1. A high-performance online expense settlement statistical method is characterized by comprising the following steps:
step 1, acquiring an excel file of a expense settlement dictionary table selected by an administrator from a WEB terminal, compiling the excel file of the expense settlement dictionary table into a key value pair by using FormData (), and then sending the key value pair to a server terminal;
step 2, the server receives the key value pairs transmitted by the WEB end, and stores the key value pairs in a path appointed by the server end;
step 3, when the online expense settlement statistical webpage of the client is opened, the client automatically acquires the excel file names of the expense settlement dictionary table contained in all key value pairs under the appointed path of the server, and displays the excel file names of the expense settlement dictionary table in the webpage;
step 4, selecting a displayed name of the Excel file of the expense settlement dictionary table, so as to determine the Excel file of the expense settlement dictionary table currently selected for use, then selecting an Excel file of the expense settlement data table at the client, uploading the selected Excel file of the expense settlement data table to the server, then operating an expense settlement Excel data statistics Excel application program at the server, taking the selected name of the Excel file of the expense settlement dictionary table and the uploaded name of the Excel file of the expense settlement data table as program starting parameters of the expense settlement Excel data statistics Excel application program, and reading the corresponding contents of the Excel file of the expense settlement table and the Excel file of the expense settlement data table by the expense settlement Excel application program and returning the contents to the client;
step 5, the client receives the read content returned by the server and analyzes the read content, and the income and expenditure sum of each classification name is counted and summed in sequence to obtain a statistical result; then dynamically creating a table tag, and sequentially displaying the corresponding income and expenditure sum of each classification name; then counting the total income and total expenditure corresponding to all the classification names, displaying the total income and total expenditure on the last line of the table, adding a click event of the table, clicking to obtain the current click line to obtain the classification name corresponding to the current line, obtaining the expense settlement data corresponding to the classification name from the counting result, and then dynamically creating a new floating display of the expense settlement data corresponding to the table display classification name;
and 6, deleting the designated expense settlement dictionary table excel file and/or the cache file of the expense settlement data table excel file under the designated path of the server.
2. The high-performance online expense settlement statistical method according to claim 1, wherein the selecting an expense settlement dictionary table excel file in the WEB terminal in step 1 specifically includes: selecting an expense settlement dictionary table excel file by using the file type of an input label in a Web end; the step of sending the key-value pairs to the server side means that the key-value pairs are sent to the server side through Ajax.
3. The high-performance online accounting decision statistical method as claimed in claim 2, wherein the step 2 specifically comprises: and the server receives the key-value pair transmitted by the Ajax of the client by using the HttpPostedFile () object of the C #, and appoints a path to store the key-value pair at the server by using a SaveAs method of the HttpPostedFile () object.
4. The high-performance online accounting statistical method as claimed in claim 1, wherein the step 3 specifically comprises: when an online settlement accounting webpage of a client is opened, the client automatically sends an REST service request to a server, acquires the excel file names of the settlement accounting dictionary table contained in all key value pairs under the appointed path of the server, and then displays the excel file names of the settlement accounting dictionary table in the webpage by using a select tag.
5. The high-performance online cost settlement statistical method of claim 1, wherein, in step 4,
the uploading of the selected expense settlement data table excel file to the server specifically refers to the following steps: calling REST service to upload the selected expense settlement data table excel file to a server side;
the expense settlement Excel data statistics exe application program reads the corresponding expense settlement dictionary table Excel file and the content in the expense settlement data table Excel file, and the NPOI tool is used for reading the content.
6. The high performance online cost settlement statistical method of claim 1,
the operation of the expense settlement Excel data statistics exe application program at the server terminal specifically comprises the following steps: running an expense settlement Excel data statistics exe application program at a server end by a start method of a Process object; and respectively starting an independent expense settlement Excel data statistics exe application program for the request submitted by each client.
7. The high-performance online expense settlement statistical method according to claim 1, wherein, in the step 4, when reading the content, for the case that the classification names corresponding to a plurality of different economic classification codes in the expense settlement dictionary table excel file are the same, all data in the expense settlement dictionary table excel file are traversed through recursion first, the relationship between the classification name and the economic classification code of 1 to 1 is changed into the data relationship between the classification name and the economic classification code of 1 to n, and n is a positive integer greater than 1, so as to simplify the data and reduce the data volume; secondly, arranging economic classification codes according to classification names, traversing an expense settlement data table excel file, sequentially grouping data records in the expense settlement data table excel file according to the values of 'economic classification' columns in the expense settlement data and storing the data records in a two-dimensional array according to the classification names, converting the two-dimensional array into a JSON format, and returning the JSON format to a client.
8. The high-performance online expense settlement statistic method according to claim 1, wherein in step 5, in the dynamically created new floating displayed table, the expense settlement data corresponding to the categorized name is displayed, and each row displays the details of the expense usage including year, month/day, voucher number, abstract, subject, economic classification, income, expenditure, debit and repayment.
9. The method as claimed in claim 1, wherein the deletion in step 6 is performed by a delete method of system.
10. A high performance online cost settlement statistic apparatus, particularly a computer storage medium, wherein the computer storage medium has stored therein computer executable instructions for implementing the high performance online cost settlement statistic method as claimed in any one of claims 1-9.
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