A report efficient processing method based on RPA

Abstract

The application discloses a report efficient processing method based on RPA, and belongs to the technical field of report efficient processing of RPA, and comprises the following steps: S1: automatic login; S2: query; S3: cache; S4: processing; and S5: coroutine.The report efficient processing method disclosed by the application utilizes the coroutine technology, realizes the report continuity query function based on RPA, and after the production end module submits a query, does not need to wait for report return data, but directly queries the next report; the waiting time during the query report is utilized, the production end module continues to complete the query operation in the waiting time period, the efficiency of report query processing is improved, after multiple reports are processed, the return data is switched to the consumption end module for processing, and the continuity work of threads is realized.

Description

Technical Field

[0001] This invention relates to the field of RPA-based efficient report processing technology, and in particular to an RPA-based efficient report processing method. Background Technology

[0002] Bank staff need to download and view business reports from the system. As the volume of reports increases, the workload for staff to query reports also increases. Currently, when using RPA to automatically query and download reports, the query time is long due to the huge amount of data. For example, it may take 7-8 seconds to return the results after clicking the query button. Furthermore, RPA automation can only process reports linearly, one report at a time. This means that the data returned by one report must be processed before the next report can be queried, resulting in low efficiency in querying reports because of the wasted waiting time. Summary of the Invention

[0003] The purpose of this invention is to provide an efficient report processing method based on RPA, which realizes continuous report query function based on RPA. After the production module submits a query, it does not need to wait for the report to return data, but directly queries the next report. By utilizing the waiting time when querying reports, the production module continues to complete the query operation during the waiting period, thereby improving the efficiency of report query processing. After processing multiple reports, the process switches to the consumer module to process the returned data, realizing continuous operation of threads, so as to solve the problems mentioned in the background technology.

[0004] To achieve the above objectives, the present invention provides the following technical solution: an efficient report processing method based on RPA, comprising the following steps:

[0005] S1: Automated Login: The report automation query module uses RPA technology to automate the report query process, obtains the username and password, and automatically logs into the report query system;

[0006] S2: Query: The production module is responsible for inputting report query conditions and performing the query. At the same time, it sends the report query condition information to the message notification module. The message notification module stores the received report query condition information in the database table and records the report query condition information in the database table as a query.

[0007] S3: Cache: When the production module detects that the query report information result has been returned, it stores the returned report information result data in the cache area module, and at the same time updates the status of the corresponding report query condition information record in the database table to "returned".

[0008] S4: Processing: The consumer module obtains the report query condition information with the status of "returned" from the database table, matches the corresponding returned report information result data from the cache area module according to the report query condition information, and then processes the returned report information result data accordingly.

[0009] S5: Coroutine: After the production module completes the query of multiple reports, the consumer module checks the returned report query conditions. If no report is found, the production module continues to query the next report. If a report is found, the consumer module processes the returned report results.

[0010] Furthermore, in S1, the RPA robot is given a separate account and password, which are managed separately from the passwords and accounts of human employees. The account and password for the RPA robot report query system are stored in the RPA management platform. The RPA management platform has variables set up to configure password variables and protect the security of the account and password.

[0011] Furthermore, in S2, the query method for the production module is data extraction. In this process, data extraction first extracts report information that meets the query conditions from the data source, and during the extraction process, data security is monitored to prevent data leakage and misuse.

[0012] Furthermore, for S4 and S5, the methods for processing report information are data cleaning, data analysis, and data visualization. Data cleaning cleans the extracted report information to ensure the accuracy and consistency of the data. Data analysis selects analysis tools and algorithms for the obtained report information results, automates the running of data analysis programs, and automatically generates data analysis reports. Data visualization visualizes the analysis results after data analysis, displaying automatically generated charts and reports on the production module to better understand and analyze the data.

[0013] Furthermore, data cleaning reduces error rates and improves efficiency by automating the removal of duplicate data and the processing of missing data.

[0014] Compared with the prior art, the beneficial effects of the present invention are as follows: The present invention proposes an efficient report processing method based on RPA, which utilizes coroutine technology to realize the continuous query function of reports based on RPA. After the production module submits a query, it does not need to wait for the report to return data, but directly queries the next report. It utilizes the waiting time when querying reports, and during the waiting period, the production module continues to complete the query operation, thereby improving the efficiency of report query processing. After processing multiple reports, it switches to the consumer module to process the returned data, realizing the continuous operation of threads. Attached Figure Description

[0015] Figure 1 This is a schematic diagram of the module of the present invention.

[0016] In the diagram: 1. Production module; 2. Message notification module; 3. Database table; 4. Cache area module; 5. Consumer module; 6. Automated report query module; 7. Coroutine module. Detailed Implementation

[0017] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0018] Please see Figure 1 An efficient report processing method based on RPA includes the following steps:

[0019] Step 1: Automated Login: The report automation query module 6 uses RPA technology to automate report query processing, obtains the username and password to automatically log in to the report query system, assigns the RPA robot a separate account and password, and manages them separately from the passwords and accounts of human employees. The account and password of the RPA robot report query system are stored in the RPA management platform, which has variables set in the RPA management platform to configure password variables and protect the security of the account and password.

[0020] The RPA management platform stores accounts in an Excel spreadsheet as configuration, which can include URLs, working directories, etc. The RPA robot retrieves account information by reading the parameter configuration table and then processes it within the business system.

[0021] The automated report query module 6 automates the report query process, reads preset report query conditions, and performs queries by inputting each condition into the query fields. It also downloads and saves the query results. The preset report query conditions include: organization number, query time range, and report name.

[0022] Specifically, in Python, coroutines are used to write asynchronous code. In RPA technology, Python's Asyncio technology is introduced to enable continuous thread execution. Through asynchronous programming with Asyncio, programs can continue executing other tasks while waiting for one operation to complete.

[0023] Step 2: Query: Production module 1 is responsible for inputting report query conditions and querying the report information database. At the same time, it sends the report query condition information to message notification module 2. Message notification module 2 stores the received report query condition information in database table 3, and records the report query condition information in database table 3 as a query. The query method of production module 1 is data extraction. Among them, data extraction first extracts report information that meets the query conditions from the data source. During the extraction process, attention is paid to data security to prevent data leakage and misuse.

[0024] The production module 1 is responsible for reading the preset report query conditions one by one, inputting the report query conditions into the fields, and clicking the query button to perform the query. Simultaneously, it sends the report information to the message notification terminal. The report information serves as the unique identifier for the report and includes: report name and organization number. After submitting a query, the production module no longer waits for returned data but directly reads the next preset report query conditions, inputs the report query conditions into the fields, and clicks the query button to perform the query.

[0025] The records stored in database table 3 by message notification module 2 include: report name, organization number, status, and time.

[0026] Specifically, the coroutine will not be executed immediately. By registering the coroutine to the input report query condition event loop, the event loop will schedule the execution of the coroutine and form a download task. The event loop is responsible for scheduling and executing the task. After submitting a query in the production module 1, there is no need to wait for the report to return data. Instead, the next report can be queried directly. After processing multiple reports, the process will switch to the consumer module 5 to process the returned data, thus achieving continuous operation of the thread.

[0027] Step 3: Caching: When the production module 1 detects that the query report information result has been returned, it stores the returned report information result data in the cache area module 4, and at the same time updates the status of the corresponding report query condition information record in database table 3 to "returned".

[0028] Once a query result is detected, the data will be returned to the data cache module 4, and the status of the corresponding record in database table 3 will be updated to "returned". This corresponding record will be the first record sorted in ascending chronological order. The returned report information structure data includes the report name, organization number, and the content of the requested report information.

[0029] Step 4: Processing: Consumer module 5 obtains the report query condition information with the status of "returned" from database table 3, and matches the corresponding returned report information result data from cache area module 4 according to the report query condition information, and then processes the returned report information result data accordingly.

[0030] The consumer module 5 is responsible for retrieving report information with a "returned" status from database table 3, matching the returned data with the same registration name and organization number from the cache area based on the registration name and organization number in the report information, and then displaying the returned data on the report query system interface. Clicking the download button saves the report file to the corresponding path. Simultaneously, after consuming a report, the module deletes that report from database table 3.

[0031] Step 5: Coroutines: After the producer module 1 completes the query of multiple reports, the coroutine module 7 pauses the operation of the producer module 1 and switches to the consumer module 5 to query the report information that has been returned. The consumer module 5 queries the report query condition information that has been returned. If it does not exist, the producer module 1 continues to query the next report information. If it exists, the consumer module 5 processes the returned report information results. This avoids the thread being in a situation of waiting for returned data when the query time is long, thereby improving the efficiency of report query.

[0032] The methods for processing report information include data cleaning, data analysis, and data visualization. Data cleaning cleans the extracted report information to ensure its accuracy and consistency. Data analysis selects analysis tools and algorithms for the obtained report information results, automates the running of data analysis programs, and automatically generates data analysis reports. Data visualization visualizes the analysis results after data analysis, displaying automatically generated charts and reports on the production module 1 to facilitate better understanding and analysis of the data.

[0033] Data cleaning reduces error rates and improves efficiency by automating the removal of duplicate data and the processing of missing data.

[0034] RPA technology is used for data aggregation and analysis in financial statements. RPA can automatically extract information and analyze data to determine the financial situation. It can also aggregate all relevant data into a single report for decision-makers to analyze. Based on Python's asynchronous architecture, combined with Asyncio technology, it is often used to handle high-concurrency network requests. It utilizes the waiting time when querying reports, allowing the production side to continue the query operation during the waiting period, thereby improving the efficiency of report query processing.

[0035] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. A method for efficient report processing based on RPA, characterized in that, Includes the following steps: S1: Automated Login: The report automation query module (6) uses RPA technology to automate the report query process, obtains the username and password, and automatically logs into the report query system; S2: Query: The production module (1) is responsible for inputting the report query conditions and querying the report information database. At the same time, it sends the report query condition information to the message notification module (2). The message notification module (2) stores the received report query condition information in the database table (3) and records the report query condition information in the database table (3) as a query. S3: Cache: When the production module (1) detects that the query report information result has been returned, it stores the returned report information result data in the cache area module (4), and at the same time updates the status of the corresponding report query condition information record in the database table (3) to "returned". S4: Processing: The consumer module (5) obtains the report query condition information in the database table (3) that is in the state of being returned, and matches the corresponding returned report information result data from the cache area module (4) according to the report query condition information, and then processes the returned report information result data accordingly. S5: Coroutine: After the production module (1) completes the query of multiple reports, the consumer module (5) queries the report query conditions that have been returned. If they do not exist, the production module (1) continues to query the next report information. If they exist, the consumer module (5) processes the returned report information results.

2. The RPA-based efficient report processing method as described in claim 1, characterized in that, For S1, the RPA robot is given a separate account and password, which are managed separately from the passwords and accounts of human employees. The account and password for the RPA robot report query system are stored in the RPA management platform. Variables are set in the RPA management platform to configure password variables and protect the security of the account and password.

3. The RPA-based efficient report processing method as described in claim 2, characterized in that, In S2, the query method of the production module (1) is data extraction. The data extraction first extracts the report information that meets the query conditions from the data source, and monitors the security of the data during the extraction process to prevent data leakage and abuse.

4. The RPA-based efficient report processing method as described in claim 3, characterized in that, For S4 and S5, the methods for processing report information are data cleaning, data analysis and data visualization. Data cleaning cleans the extracted report information to ensure the accuracy and consistency of the data. Data analysis selects analysis tools and algorithms for the obtained report information results data, automatically runs the data analysis program and automatically generates data analysis reports. Data visualization visualizes the analysis results after data analysis. The production module (1) displays automatically generated charts and reports to better understand and analyze the data.

5. The RPA-based efficient report processing method as described in claim 4, characterized in that, Data cleaning reduces error rates and improves efficiency by automating the removal of duplicate data and the processing of missing data.

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